diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index e69c1d7..cddf466 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -37,7 +37,7 @@ jobs: - name: Check documentation links run: sphinx-build -b linkcheck docs dist/docs - - name: Validate the CITATION.cff - uses: citation-file-format/cffconvert-github-action@2.0.0 - with: - args: "--infile ./CITATION.cff --validate" + - name: Validate the CITATION.cff + uses: citation-file-format/cffconvert-github-action@2.0.0 + with: + args: "--infile ./CITATION.cff --validate" diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index 9afae93..70c5089 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -16,6 +16,7 @@ jobs: matrix: os: ["ubuntu-latest", "windows-latest", "macos-latest"] python-version: ["3.10", "3.11", "3.13", "3.14"] + options: ["standard", "space_weather"] numpy_ver: ["latest"] test_config: ["latest"] include: @@ -27,11 +28,13 @@ jobs: xarray_ver: "2024.5.0" os: ubuntu-latest test_config: "SPEC0000" + options: "standard" # Operational compliance settings - python-version: "3.12" numpy_ver: "2.0.0" os: "ubuntu-22.04" test_config: "Ops" + options: "space_weather" # Minimum version settings - python-version: "3.10" dask_ver: "2022.12.1" @@ -45,7 +48,8 @@ jobs: xarray_ver: "2022.12.0" os: "ubuntu-22.04" test_config: "Min" - name: Python ${{ matrix.python-version }} on ${{ matrix.os }} with numpy ${{ matrix.numpy_ver }} + options: "standard" + name: Python ${{ matrix.python-version }} on ${{ matrix.os }} with numpy ${{ matrix.numpy_ver }} for ${{ matrix.options }} runs-on: ${{ matrix.os }} steps: - uses: actions/checkout@v6 @@ -87,10 +91,14 @@ jobs: if: ${{ matrix.test_config == 'latest'}} run: pip install .[test] + - name: Install extra dependencies + if: ${{ !startsWith(matrix.options, 'standard') }} + run: pip install .[${{ matrix.options }}] + - name: Set up the data directory run: | mkdir gdmData - python -c "import GeospaceDataManagement; GeospaceDataManagement.params['data_dirs'] = 'gdmData'" + python -c "import GeospaceDataManagement; GeospaceDataManagement.params['data_dirs'] = 'gdmData'; print(GeospaceDataManagement.params)" - name: Test PEP8 compliance run: flake8 . --count --select=D,E,F,H,W --show-source --statistics diff --git a/CHANGELOG.md b/CHANGELOG.md index e882017..b797b52 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,20 @@ Change Log All notable changes to this project will be documented in this file. This project adheres to [Semantic Versioning](https://semver.org/). -[0.0.1] - 2026-10-XX +[0.0.2] - 2026-10-02 +-------------------- +* ENH: + - Added Space Weather instruments as an optional installation + - Allow `generate_instrument_list` to include only a subset of the instruments +* BUG: + - Fixed assignment issue in Instrument, where meta data could not be added if + a variable did not exist + - Fixed assignment issue in Instrument, where xarray behaviour changed in + more recent versions of Python +* DOC: + - Added missing sections to docstrings + - Added information about space weather instruments and methods + +[0.0.1] - 2026-09-25 -------------------- Initial Release diff --git a/CITATION.cff b/CITATION.cff index 01fe937..a217a64 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -21,4 +21,4 @@ keywords: - "Observations" - "Models" license: MIT -version: 0.0.1 +version: 0.0.2 diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index e70dca1..ef831f2 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -1,34 +1,29 @@ -Contributing -============ +# Contributing Bug reports, feature suggestions, and other contributions are greatly -appreciated! GeospaceDataManager welcomes both feedback and contributions. +appreciated! GeospaceDataManagement welcomes both feedback and contributions. -Short version -------------- +## Short version * Submit bug reports, feature requests, and questions at - [GitHub](https://github.com/USNavalResearchLaboratory/GeospaceDataManager/issues) + [GitHub](https://github.com/USNavalResearchLaboratory/GeospaceDataManagement/issues) * Make all pull requests to the ``develop`` branch -Issues ------- +## Issues Bug reports, questions, and feature requests should all be made as GitHub Issues. Templates are provided for each type of issue, to help you include all the necessary information. -Questions -^^^^^^^^^ +### Questions Not sure how something works? Ask away! The more information you provide, the easier the question will be to answer. -Bug reports -^^^^^^^^^^^ +### Bug reports -When [reporting a bug](https://github.com/GeospaceDataManager/GeospaceDataManager/issues) please include: +When [reporting a bug](https://github.com/USNavalResearchLaboratory/GeospaceDataManagement/issues) please include: * Your operating system name and version @@ -36,11 +31,10 @@ When [reporting a bug](https://github.com/GeospaceDataManager/GeospaceDataManage * Detailed steps to reproduce the bug -Feature requests and feedback -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +### Feature requests and feedback The best way to send feedback is to file an -[issue](https://github.com/GeospaceDataManager/GeospaceDataManager/issues). +[issue](https://github.com/USNavalResearchLaboratory/GeospaceDataManagement/issues). If you are proposing a new feature or a change in something that already exists: @@ -49,17 +43,16 @@ If you are proposing a new feature or a change in something that already exists: * Keep the scope as narrow as possible, to make it easier to implement. -Development ------------ +## Development -To set up `GeospaceDataManager` for local development: +To set up `GeospaceDataManagement` for local development: -1. [Fork GeospaceDataManager on GitHub](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/fork-a-repo). +1. [Fork GeospaceDataManagement on GitHub](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/fork-a-repo). 2. Clone your fork locally: ``` - git clone git@github.com:your_name_here/GeospaceDataManager.git + git clone git@github.com:your_name_here/GeospaceDataManagement.git ``` 3. Create a branch for local development: @@ -75,8 +68,8 @@ To set up `GeospaceDataManager` for local development: standard tests. Tests for custom functions should be added to the appropriately named file - in ``GeospaceDataManager/tests``. For example, custom functions for the time - utilities are tested in ``GeospaceDataManager/tests/test_utils_time.py``. If + in ``GeospaceDataManagement/tests``. For example, custom functions for the time + utilities are tested in ``GeospaceDataManagement/tests/test_utils_time.py``. If no test file exists, then you should create one. This testing uses pytest, which will run tests on any Python file in the test directory that starts with ``test``. Classes must begin with ``Test``, and methods must begin with @@ -95,7 +88,7 @@ To set up `GeospaceDataManager` for local development: flake8 . --count --select=D,E,F,H,W --show-source --statistics ``` - Note that GeospaceDataManager uses the `flake-docstrings` and `hacking` + Note that GeospaceDataManagement uses the `flake-docstrings` and `hacking` packages to ensure standards in docstring formatting. 6. Update/add documentation (in ``docs``). Even if you don't think it's @@ -109,7 +102,7 @@ To set up `GeospaceDataManager` for local development: git commit -m "AAA: Brief description of your changes" ``` Where AAA is a standard shorthand for the type of change (e.g., BUG or DOC). - `GeospaceDataManager` follows the [numpy development workflow](https://numpy.org/doc/stable/dev/development_workflow.html), + `GeospaceDataManagement` follows the [numpy development workflow](https://numpy.org/doc/stable/dev/development_workflow.html), see the discussion there for a full list of this shorthand notation. 9. Once you are happy with the local changes, push to GitHub: @@ -121,11 +114,10 @@ To set up `GeospaceDataManager` for local development: 10. Submit a pull request through the GitHub website. Pull requests should be made to the ``develop`` branch. Note that automated tests will be run on GitHub Actions, but these must be initialized by a member of the - GeospaceDataManager team for outside contributors. + GeospaceDataManagement team for outside contributors. -Pull Request Guidelines ------------------------ +## Pull Request Guidelines If you need some code review or feedback while you're developing the code, just make a pull request. Pull requests should be made to the ``develop`` branch. @@ -145,10 +137,9 @@ will delay tests by other developers, please ensure that the code passes all tests on your local system first. -Project Style Guidelines ------------------------- +## Project Style Guidelines -In general, GeospaceDataManager follows PEP8 and numpydoc guidelines. Pytest +In general, GeospaceDataManagement follows PEP8 and numpydoc guidelines. Pytest runs the unit and integration tests, flake8 checks for style, and sphinx-build performs documentation tests. However, there are certain additional style elements that have been adopted to ensure the project maintains a consistent @@ -160,8 +151,8 @@ coding style. These include: * Use no more than 80 characters per line * Avoid using Instrument class key attribute names as unrelated variable names: `platform`, `name`, `tag`, and `inst_id` -* The GeospaceDataManager logger is imported into each sub-module and provides - status updates at the info and warning levels (as appropriate) +* The GeospaceDataManagement logger is imported into each sub-module and + provides status updates at the info and warning levels (as appropriate) * Several dependent packages have common nicknames, including: * `import datetime as dt` * `import numpy as np` @@ -175,7 +166,7 @@ coding style. These include: * Use setup_method (or setup_class) and teardown_method (or teardown_class) in test classes * Use pytest parametrize in test classes when appropriate -* Use GeospaceDataManager testing utilities when appropriate +* Use GeospaceDataManagement testing utilities when appropriate * Provide testing class methods with informative failure statements and descriptive, one-line docstrings * Block and inline comments should use proper English grammar and punctuation diff --git a/GeospaceDataManagement/__init__.py b/GeospaceDataManagement/__init__.py index a82238a..aef616d 100644 --- a/GeospaceDataManagement/__init__.py +++ b/GeospaceDataManagement/__init__.py @@ -1,4 +1,4 @@ -"""GeospaceDataManagement +"""GeospaceDataManagement (a.k.a. gdm). A package providing a simple and flexible interface for downloading, loading, cleaning, and managing scientific measurements. @@ -43,15 +43,9 @@ gdm_dir = os.path.join(home_dir, '.gdm') # Set directory for test data -if resources is None: - test_data_path = os.path.join(os.path.realpath(os.path.dirname(__file__)), - 'tests', 'test_data') - citation = os.path.join(os.path.realpath(os.path.dirname(__file__)), - 'citation.txt') -else: - test_data_path = str(resources.files(__package__).joinpath('tests', - 'test_data')) - citation = str(resources.files(__package__).joinpath('citation.txt')) +test_data_path = str(resources.files(__package__).joinpath('tests', + 'test_data')) +citation = str(resources.files(__package__).joinpath('citation.txt')) # Create a .gdm directory or parameters file if one doesn't exist. settings_file = os.path.join(gdm_dir, 'gdm_settings.json') diff --git a/GeospaceDataManagement/_instrument.py b/GeospaceDataManagement/_instrument.py index 94393a3..d1a3351 100644 --- a/GeospaceDataManagement/_instrument.py +++ b/GeospaceDataManagement/_instrument.py @@ -834,6 +834,11 @@ def __setitem__(self, key, new_data): # Simple assignment inst['name'] = newData + # Assignment with Metadata + inst['name'] = {'data':new_data, + 'long_name':long_name, + 'units':units} + Raises ------ ValueError @@ -846,7 +851,6 @@ def __setitem__(self, key, new_data): If a single new value is set, the value will be broadcast over time. """ - new = copy.deepcopy(new_data) # xarray format chosen for Instrument object @@ -885,9 +889,27 @@ def __setitem__(self, key, new_data): # Try loading as values self.data[var_key].loc[indict] = in_data except (TypeError, KeyError, IndexError): - # Original code - # Try loading indexed as integers - self.data[key[-1]][indict] = in_data + # Attempt to use loc, which will currently fail for Python 3.14 + sel_dict = { + self.data[var_key].dims[i]: self.data[var_key][ + self.data[var_key].dims[i]].values[kind] + for i, kind in enumerate(ind_keys)} + + try: + self.data[var_key].loc[sel_dict] = in_data + except (ValueError, KeyError, IndexError, TypeError): + # Input is probably an integer, get the desired data + # through array assignment. Because the original behaviour + # used indices for each dimension instead of paired indices, + # we invoke meshgrid to get the full range of index + # combinations + sel_dat = self.data[var_key].values.copy() + sel_ind = np.meshgrid(ind_keys) + sel_dat[sel_ind] = in_data + self.data[var_key].values = sel_dat + + # Finish updating by adding meta data + self.data[var_key].attrs.update(new) return elif isinstance(key, str): @@ -957,6 +979,10 @@ def __setitem__(self, key, new_data): for keyname in key: self.data[keyname] = in_data[keyname] + # Attach meta data, if it exists + if len(new) > 0: + self.data[key].attrs.update(new) + return def __delitem__(self, key): @@ -1191,13 +1217,13 @@ def _assign_attrs(self, by_name=False): Notes ----- - methods + methods include: init, preprocess, and clean - functions + functions include: load, list_files, download, and list_remote_files, concat_data - attributes + attributes include: directory_format, file_format, and multi_file_day - test attributes + test attributes include: _test_download, _test_download_ci, _new_tests, and _password_req """ @@ -1608,7 +1634,7 @@ def _get_var_type_code(self, coltype): np.dtypes.StringDType, np.dtypes.BytesDType, pds.StringDtype] except AttributeError: - # TODO(#1227) np.dtypes not introduced until somewhere around + # TODO(#1) np.dtypes not introduced until somewhere around # numpy version 1.25 str_types = [str, np.str_, np.bytes_, pds.StringDtype] diff --git a/GeospaceDataManagement/citation.txt b/GeospaceDataManagement/citation.txt index e91003e..ed9f5f4 100644 --- a/GeospaceDataManagement/citation.txt +++ b/GeospaceDataManagement/citation.txt @@ -1 +1 @@ -Burrell, A. G. (2026). USNavalResearchLaboratory/GeospaceDataManagement v0.0.1 (Version v0.0.1). https://github.com/USNavalResearchLaboratory/GeospaceDataManagement +Burrell, A. G. (2026). USNavalResearchLaboratory/GeospaceDataManagement v0.0.2 (Version v0.0.2). https://github.com/USNavalResearchLaboratory/GeospaceDataManagement diff --git a/GeospaceDataManagement/instruments/__init__.py b/GeospaceDataManagement/instruments/__init__.py index d44708e..f1faf67 100644 --- a/GeospaceDataManagement/instruments/__init__.py +++ b/GeospaceDataManagement/instruments/__init__.py @@ -4,8 +4,22 @@ Each instrument is contained within a subpackage of this set. """ -__all__ = ['gdm_ndtesting', 'gdm_netcdf', 'gdm_testing', - 'gdm_testmodel'] +__test__ = ['gdm_ndtesting', 'gdm_netcdf', 'gdm_testing', + 'gdm_testmodel'] +__all__ = list(__test__) + +from GeospaceDataManagement.instruments import methods # noqa 401 +try: + from GeospaceDataManagement.instruments import sw_methods # noqa 401 + __sw__ = ['ace_epam', 'ace_mag', 'ace_sis', 'ace_swepam', 'norp_rf', + 'sw_ae', 'sw_al', 'sw_ap', 'sw_apo', 'sw_au', 'sw_cp', + 'sw_dst', 'sw_f107', 'sw_flare', 'sw_hpo', 'sw_kp', + 'sw_mgii', 'sw_polarcap', 'sw_sbfield', 'sw_ssn', + 'sw_stormprob'] + __all__.extend(__sw__) +except ImportError as ierr: + import GeospaceDataManagement + GeospaceDataManagement.logger.info(ierr) for inst in __all__: exec("from GeospaceDataManagement.instruments import {x}".format(x=inst)) diff --git a/GeospaceDataManagement/instruments/ace_epam.py b/GeospaceDataManagement/instruments/ace_epam.py new file mode 100644 index 0000000..bde02db --- /dev/null +++ b/GeospaceDataManagement/instruments/ace_epam.py @@ -0,0 +1,250 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports ACE Electron, Proton, and Alpha Monitor data. + +Properties +---------- +platform + 'ace' Advanced Composition Explorer +name + 'epam' Electron, Proton, and Alpha Monitor +tag + - 'realtime' Real-time data from the Space Weather Prediction Center (SWPC) + - 'historic' Historic data from the SWPC +inst_id + - '' + +Note +---- +This is not the ACE scientific data set, which is provided by NASA + +Examples +-------- +The real-time data is stored by generation date, where each file contains the +data for the current day. If you leave download dates empty, though, it will +grab today's file three times and assign dates from yesterday, today, and +tomorrow. +:: + + epam = gdm.Instrument('ace', 'epam', tag='realtime') + epam.download(start=epam.today()) + epam.load(date=epam.today()) + + + +Warnings +-------- +The 'realtime' data contains a changing period of time. Loading multiple files, +loading multiple days, the data padding feature, and multi_file_day feature +available from the pyast.Instrument object is not appropriate for 'realtime' +data. + +""" + +import datetime as dt +import functools +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.methods.general import load_csv_data +from GeospaceDataManagement.instruments.sw_methods import ace as mm_ace +from GeospaceDataManagement.instruments.sw_methods import general + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'ace' +name = 'epam' +tags = {'realtime': 'Real-time data from the SWPC', + 'historic': ' Historic data from the SWPC'} +inst_ids = {inst_id: [tag for tag in tags.keys()] for inst_id in ['']} + +# Define today's date +now = dt.datetime.now(tz=dt.timezone.utc) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates (first level: inst_id, second level: tag) +_test_dates = {inst_id: {'realtime': dt.datetime(now.year, now.month, now.day), + 'historic': dt.datetime(2009, 1, 1)} + for inst_id in inst_ids.keys()} + +# Set clean warning tests +_clean_warn = {inst_id: {tag: mm_ace.clean_warn for tag in inst_ids[inst_id]} + for inst_id in inst_ids.keys()} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the appropriate acknowledgements and references + self.acknowledgements = mm_ace.acknowledgements() + self.references = mm_ace.references(self.name) + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean the real-time ACE data using the status flag. + + Note + ---- + Supports 'clean' and 'dirty'. Replaces all fill values with NaN. + Clean - status flag of zero (nominal data) + Dirty - status flag < 9 (accepts bad data record, removes no data record) + + """ + # Perform the standard ACE cleaning + max_status = mm_ace.clean(self) + + # Replace bad values with NaN and remove times with no valid data + ecols = ['eflux_38-53', 'eflux_175-315'] + + # Evaluate the electron flux data + self[self.data['status_e'] > max_status, ecols] = np.nan + + # Evaluate the proton flux data + pcols = ['pflux_47-68', 'pflux_115-195', 'pflux_310-580', + 'pflux_795-1193', 'pflux_1060-1900'] + self[self.data['status_p'] > max_status, pcols] = np.nan + + # Include both fluxes and the anisotropy index in the removal eval + eval_cols = ecols + pcols + eval_cols.append('anis_ind') + + # Remove times without any good data + good_sum = np.isfinite([self.data[ecol].values for ecol in eval_cols]).sum( + axis=0) + if 0 in good_sum: + self.data = self.data.where(self.data['Epoch'][good_sum != 0], + drop=True) + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + +download = functools.partial(mm_ace.download, name=name, now=now) +list_files = functools.partial(mm_ace.list_files, name=name) + + +def load(fnames, tag='', inst_id=''): + """Load the ACE space weather prediction data. + + Parameters + ---------- + fnames : array-like + Series, list, or array of filenames. + tag : str + Instrument tag (default=''). + inst_id : str + ACE instrument ID (default=''). + + Returns + ------- + data : xr.Dataset + Object containing instrument data + + See Also + -------- + GeospaceDataManagement.instruments.methods.general.load_csv_data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # Save each file to the output DataFrame + data = load_csv_data(fnames, + read_csv_kwargs={'index_col': 0, + 'parse_dates': True}).to_xarray() + + # Assign the meta data + meta, status_desc = mm_ace.common_metadata() + flux_desc = '5-min averaged Differential ' + + meta['status_e'] = {'units': '', 'name': 'Diff e- Flux Status', + 'notes': '', 'desc': status_desc, 'fill_val': np.nan, + 'min_val': 0, 'max_val': 9} + meta['status_p'] = {'units': '', 'name': 'Diff Proton Flux Status', + 'notes': '', 'desc': status_desc, + 'fill_val': np.nan, 'min_val': 0, 'max_val': 9} + meta['anis_ind'] = {'units': '', 'name': 'Anisotropy Index', + 'notes': '', 'desc': 'Range: 0.0 - 2.0', + 'fill_val': -1.0, 'min_val': 0.0, 'max_val': 2.0} + meta['eflux_38-53'] = {'units': 'particles/cm2-s-ster-MeV', + 'name': 'Diff e- Flux 38-53 eV', + 'notes': '', + 'desc': ''.join([flux_desc, + 'Electron Flux between 35-53 eV']), + 'fill_val': -1.0e5, 'min_val': -np.inf, + 'max_val': np.inf} + meta['eflux_175-315'] = {'units': 'particles/cm2-s-ster-MeV', + 'name': 'Diff e- Flux 175-315 eV', + 'notes': '', + 'desc': ''.join([flux_desc, 'Electron Flux ', + 'between 175-315 eV']), + 'fill_val': -1.0e5, 'min_val': -np.inf, + 'max_val': np.inf} + meta['pflux_47-68'] = {'units': 'particles/cm2-s-ster-MeV', + 'name': 'Diff Proton Flux 47-68 keV', + 'notes': '', + 'desc': ''.join([flux_desc, + 'Proton Flux between 47-68 keV']), + 'fill_val': -1.0e5, 'min_val': -np.inf, + 'max_val': np.inf} + meta['pflux_115-195'] = {'units': 'particles/cm2-s-ster-MeV', + 'name': 'Diff Proton Flux 115-195 keV', + 'notes': '', + 'desc': ''.join([flux_desc, 'Proton Flux', + ' between 115-195 keV']), + 'fill_val': -1.0e5, 'min_val': -np.inf, + 'max_val': np.inf} + meta['pflux_310-580'] = {'units': 'particles/cm2-s-ster-MeV', + 'name': 'Diff Proton Flux 310-580 keV', + 'notes': '', + 'desc': ''.join([flux_desc, 'Proton Flux ' + ' between 310-580 keV']), + 'fill_val': -1.0e5, 'min_val': -np.inf, + 'max_val': np.inf} + meta['pflux_795-1193'] = {'units': 'particles/cm2-s-ster-MeV', + 'name': 'Diff Proton Flux 795-1193 keV', + 'notes': '', + 'desc': ''.join([flux_desc, 'Proton Flux', + ' between 795-1193 keV']), + 'fill_val': -1.0e5, 'min_val': -np.inf, + 'max_val': np.inf} + meta['pflux_1060-1900'] = {'units': 'particles/cm2-s-ster-MeV', + 'name': 'Diff Proton Flux 1060-1900 keV', + 'notes': '', + 'desc': ''.join([flux_desc, 'Proton Flux ', + 'between 1060-1900 keV']), + 'fill_val': -1.0e5, 'min_val': -np.inf, + 'max_val': np.inf} + + # Add the meta data + for dvar in data.data_vars.keys(): + if dvar in meta.keys(): + data[dvar].attrs.update(meta[dvar]) + + return data diff --git a/GeospaceDataManagement/instruments/ace_mag.py b/GeospaceDataManagement/instruments/ace_mag.py new file mode 100644 index 0000000..1fcb14f --- /dev/null +++ b/GeospaceDataManagement/instruments/ace_mag.py @@ -0,0 +1,193 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports ACE Magnetometer data. + +Properties +---------- +platform + 'ace' Advanced Composition Explorer +name + 'mag' Magnetometer +tag + - 'realtime' Real-time data from the Space Weather Prediction Center (SWPC) + - 'historic' Historic data from the SWPC +inst_id + - '' + +Note +---- +This is not the ACE scientific data set, which will be available at NASA + +Examples +-------- +The real-time data is stored by generation date, where each file contains the +data for the current day. If you leave download dates empty, though, it will +grab today's file three times and assign dates from yesterday, today, and +tomorrow. +:: + + mag = gdm.Instrument('ace', 'mag', tag='realtime') + mag.download(start=mag.today()) + mag.load(date=mag.today()) + + + +Warnings +-------- +The 'realtime' data contains a changing period of time. Loading multiple files, +loading multiple days, the data padding feature, and multi_file_day feature +available from the pyast.Instrument object is not appropriate for 'realtime' +data. + +""" + +import datetime as dt +import functools +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.methods.general import load_csv_data +from GeospaceDataManagement.instruments.sw_methods import ace as mm_ace +from GeospaceDataManagement.instruments.sw_methods import general + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'ace' +name = 'mag' +tags = {'realtime': 'Real-time data from the SWPC', + 'historic': ' Historic data from the SWPC'} +inst_ids = {inst_id: [tag for tag in tags.keys()] for inst_id in ['']} + +# Define today's date +now = dt.datetime.now(tz=dt.timezone.utc) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates (first level: inst_id, second level: tag) +_test_dates = {inst_id: {'realtime': dt.datetime(now.year, now.month, now.day), + 'historic': dt.datetime(2009, 1, 1)} + for inst_id in inst_ids.keys()} + +# Set clean warning tests +_clean_warn = {inst_id: {tag: mm_ace.clean_warn for tag in inst_ids[inst_id]} + for inst_id in inst_ids.keys()} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the appropraite acknowledgements and references + self.acknowledgements = mm_ace.acknowledgements() + self.references = mm_ace.references(self.name) + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean real-time ACE data using the status flag. + + Note + ---- + Supports 'clean' and 'dirty'. Replaces all fill values with NaN. + Clean - status flag of zero (nominal data) + Dirty - status flag < 9 (accepts bad data record, removes no data record) + + """ + # Perform the standard ACE cleaning + max_status = mm_ace.clean(self) + + # Replace bad values with NaN and remove times with no valid data + self.data = self.data.where(self.data['status'] <= max_status, drop=True) + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + +download = functools.partial(mm_ace.download, name=name, now=now) +list_files = functools.partial(mm_ace.list_files, name=name) + + +def load(fnames, tag='', inst_id=''): + """Load the ACE space weather prediction data. + + Parameters + ---------- + fnames : array-like + Series, list, or array of filenames + tag : str + Instrument tag, not used. (default='') + inst_id : str + ACE instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing instrument data + + See Also + -------- + gdm.instruments.methods.general.load_csv_data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # Save each file to the output DataFrame + data = load_csv_data(fnames, + read_csv_kwargs={'index_col': 0, + 'parse_dates': True}).to_xarray() + + # Assign the meta data + meta, status_desc = mm_ace.common_metadata() + + meta['status'] = {'units': '', 'name': 'Status', + 'notes': '', 'desc': status_desc, + 'fill_val': np.nan, 'min_val': 0, 'max_val': 9} + meta['bx_gsm'] = {'units': 'nT', 'name': 'Bx GSM', + 'notes': '', 'desc': '1-min averaged IMF Bx', + 'fill_val': -999.9, 'min_val': -np.inf, 'max_val': np.inf} + meta['by_gsm'] = {'units': 'nT', 'name': 'By GSM', + 'notes': '', 'desc': '1-min averaged IMF By', + 'fill_val': -999.9, 'min_val': -np.inf, 'max_val': np.inf} + meta['bz_gsm'] = {'units': 'nT', 'notes': '', 'name': 'Bz GSM', + 'desc': '1-min averaged IMF Bz', 'fill_val': -999.9, + 'min_val': -np.inf, 'max_val': np.inf} + meta['bt_gsm'] = {'units': 'nT', 'name': 'Bt GSM', 'notes': '', + 'desc': '1-min averaged IMF Bt', 'fill_val': -999.9, + 'min_val': -np.inf, 'max_val': np.inf} + meta['lat_gsm'] = {'units': 'degrees', 'name': 'GSM Lat', + 'notes': '', 'desc': 'GSM Latitude', 'fill_val': -999.9, + 'min_val': -90.0, 'max_val': 90.0} + meta['lon_gsm'] = {'units': 'degrees', 'name': 'GSM Lon', 'notes': '', + 'desc': 'GSM Longitude', 'fill_val': -999.9, + 'min_val': 0.0, 'max_val': 360.0} + + # Add the meta data + for dvar in data.data_vars.keys(): + if dvar in meta.keys(): + data[dvar].attrs.update(meta[dvar]) + + return data diff --git a/GeospaceDataManagement/instruments/ace_sis.py b/GeospaceDataManagement/instruments/ace_sis.py new file mode 100644 index 0000000..beca605 --- /dev/null +++ b/GeospaceDataManagement/instruments/ace_sis.py @@ -0,0 +1,208 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports ACE Solar Isotope Spectrometer data. + +Properties +---------- +platform + 'ace' Advanced Composition Explorer +name + 'sis' Solar Isotope Spectrometer +tag + - 'realtime' Real-time data from the Space Weather Prediction Center (SWPC) + - 'historic' Historic data from the SWPC +inst_id + - '' + +Note +---- +This is not the ACE scientific data set, which will be available at NASA + +Examples +-------- +The real-time data is stored by generation date, where each file contains the +data for the current day. If you leave download dates empty, though, it will +grab today's file three times and assign dates from yesterday, today, and +tomorrow. +:: + + sis = gdm.Instrument('ace', 'sis', tag='realtime') + sis.download(start=sis.today()) + sis.load(date=sis.today()) + + + +Warnings +-------- +The 'realtime' data contains a changing period of time. Loading multiple files, +loading multiple days, the data padding feature, and multi_file_day feature +available from the pyast.Instrument object is not appropriate for 'realtime' +data. + +""" + +import datetime as dt +import functools +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.methods.general import load_csv_data +from GeospaceDataManagement.instruments.sw_methods import ace as mm_ace +from GeospaceDataManagement.instruments.sw_methods import general + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'ace' +name = 'sis' +tags = {'realtime': 'Real-time data from the SWPC', + 'historic': ' Historic data from the SWPC'} +inst_ids = {inst_id: [tag for tag in tags.keys()] for inst_id in ['']} + +# Define today's date +now = dt.datetime.now(tz=dt.timezone.utc) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates (first level: inst_id, second level: tag) +_test_dates = {inst_id: {'realtime': dt.datetime(now.year, now.month, now.day), + 'historic': dt.datetime(2009, 1, 1)} + for inst_id in inst_ids.keys()} + +# Set clean warning tests +_clean_warn = {inst_id: {tag: mm_ace.clean_warn for tag in inst_ids[inst_id]} + for inst_id in inst_ids.keys()} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the appropraite acknowledgements and references + self.acknowledgements = mm_ace.acknowledgements() + self.references = mm_ace.references(self.name) + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean real-time ACE data using the status flag. + + Note + ---- + Supports 'clean' and 'dirty'. Replaces all fill values with NaN. + Clean - status flag of zero (nominal data) + Dirty - status flag < 9 (accepts bad data record, removes no data record) + + """ + # Perform the standard ACE cleaning + max_status = mm_ace.clean(self) + + # Evaluate the different proton fluxes. Replace bad values with NaN and + # times with no valid data + self.data['int_pflux_10MeV'] = self.data['int_pflux_10MeV'].where( + (self.data['status_10'] <= max_status), other=np.nan) + self.data['int_pflux_30MeV'] = self.data['int_pflux_30MeV'].where( + (self.data['status_30'] <= max_status), other=np.nan) + + eval_cols = ['int_pflux_10MeV', 'int_pflux_30MeV'] + + # Remove lines without any good data + good_sum = np.isfinite([self.data[ecol].values for ecol in eval_cols]).sum( + axis=0) + if 0 in good_sum: + self.data = self.data.where(self.data['Epoch'][good_sum != 0], + drop=True) + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + +download = functools.partial(mm_ace.download, name=name, now=now) +list_files = functools.partial(mm_ace.list_files, name=name) + + +def load(fnames, tag='', inst_id=''): + """Load the ACE space weather prediction data. + + Parameters + ---------- + fnames : array-like + Series, list, or array of filenames. + tag : str + Instrument tag, not used. (default='') + inst_id : str + ACE instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing instrument data + + See Also + -------- + GeospaceDataManagement.instruments.methods.general.load_csv_data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # Save each file to the output DataFrame + data = load_csv_data(fnames, read_csv_kwargs={'index_col': 0, + 'parse_dates': True}) + + # Assign the meta data + meta, status_desc = mm_ace.common_metadata() + flux_name = 'Integral Proton Flux' + + meta['status_10'] = {'units': '', + 'name': ''.join([flux_name, ' > 10 MeV Status']), + 'notes': '', 'desc': status_desc, 'fill_val': np.nan, + 'min_val': 0, 'max_val': 9} + meta['status_30'] = {'units': '', + 'name': ''.join([flux_name, ' > 30 MeV Status']), + 'notes': '', 'desc': status_desc, 'fill_val': np.nan, + 'min_val': 0, 'max_val': 9} + meta['int_pflux_10MeV'] = {'units': 'p/cs2-sec-ster', + 'name': ''.join([flux_name, ' > 10 MeV']), + 'notes': '', + 'desc': ''.join(['5-min averaged ', flux_name, + ' > 10 MeV']), + 'fill_val': -1.0e5, 'min_val': -np.inf, + 'max_val': np.inf} + meta['int_pflux_30MeV'] = {'units': 'p/cs2-sec-ster', + 'name': ''.join([flux_name, ' > 30 MeV']), + 'notes': '', + 'desc': ''.join(['5-min averaged ', flux_name, + ' > 30 MeV']), + 'fill_val': -1.0e5, 'min_val': -np.inf, + 'max_val': np.inf} + + # Convert the data to xarray and add meta data + data = data.to_xarray() + for dvar in data.data_vars.keys(): + if dvar in meta.keys(): + data[dvar].attrs.update(meta[dvar]) + + return data diff --git a/GeospaceDataManagement/instruments/ace_swepam.py b/GeospaceDataManagement/instruments/ace_swepam.py new file mode 100644 index 0000000..41b2fa9 --- /dev/null +++ b/GeospaceDataManagement/instruments/ace_swepam.py @@ -0,0 +1,190 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports ACE Solar Wind Electron Proton Alpha Monitor data. + +Properties +---------- +platform + 'ace' Advanced Composition Explorer +name + 'swepam' Solar Wind Electron Proton Alpha Monitor +tag + - 'realtime' Real-time data from the Space Weather Prediction Center (SWPC) + - 'historic' Historic data from the SWPC +inst_id + - '' + +Note +---- +This is not the ACE scientific data set, which will be available at NASA + +Examples +-------- +The real-time data is stored by generation date, where each file contains the +data for the current day. If you leave download dates empty, though, it will +grab today's file three times and assign dates from yesterday, today, and +tomorrow. +:: + + + swepam = gdm.Instrument('ace', 'swepam', tag='realtime') + swepam.download(start=swepam.today()) + swepam.load(date=swepam.today()) + +Warnings +-------- +The 'realtime' data contains a changing period of time. Loading multiple files, +loading multiple days, the data padding feature, and multi_file_day feature +available from the pyast.Instrument object is not appropriate for 'realtime' +data. + +""" + +import datetime as dt +import functools +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.methods.general import load_csv_data +from GeospaceDataManagement.instruments.sw_methods import ace as mm_ace +from GeospaceDataManagement.instruments.sw_methods import general + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'ace' +name = 'swepam' +tags = {'realtime': 'Real-time data from the SWPC', + 'historic': ' Historic data from the SWPC'} +inst_ids = {inst_id: [tag for tag in tags.keys()] for inst_id in ['']} + +# Define today's date +now = dt.datetime.now(tz=dt.timezone.utc) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates (first level: inst_id, second level: tag) +_test_dates = {inst_id: {'realtime': dt.datetime(now.year, now.month, now.day), + 'historic': dt.datetime(2009, 1, 1)} + for inst_id in inst_ids.keys()} + +# Set clean warning tests +_clean_warn = {inst_id: {tag: mm_ace.clean_warn for tag in inst_ids[inst_id]} + for inst_id in inst_ids.keys()} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the appropraite acknowledgements and references + self.acknowledgements = mm_ace.acknowledgements() + self.references = mm_ace.references(self.name) + + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean real-time ACE data using the status flag. + + Note + ---- + Supports 'clean' and 'dirty'. Replaces all fill values with NaN. + Clean - status flag of zero (nominal data) + Dirty - status flag < 9 (accepts bad data record, removes no data record) + + """ + # Perform the standard ACE cleaning + max_status = mm_ace.clean(self) + + # Replace bad values with NaN and remove times with no valid data + self.data = self.data.where(self.data['status'] <= max_status, drop=True) + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + +download = functools.partial(mm_ace.download, name=name, now=now) +list_files = functools.partial(mm_ace.list_files, name=name) + + +def load(fnames, tag='', inst_id=''): + """Load the ACE space weather prediction data. + + Parameters + ---------- + fnames : array-like + Series, list, or array of filenames. + tag : str + Instrument tag, not used. (default='') + inst_id : str + ACE instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing instrument data + + See Also + -------- + GeospaceDataManagement.instruments.methods.general.load_csv_data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # Save each file to the output DataFrame + data = load_csv_data(fnames, + read_csv_kwargs={'index_col': 0, + 'parse_dates': True}).to_xarray() + + # Assign the meta data + meta, status_desc = mm_ace.common_metadata() + sw_desc = '1-min averaged Solar Wind ' + + meta['status'] = {'units': '', 'name': 'Status', 'notes': '', + 'desc': status_desc, 'fill_val': np.nan, 'min_val': 0, + 'max_val': 9} + meta['sw_proton_dens'] = {'units': 'p/cc', + 'name': 'Solar Wind Proton Density', 'notes': '', + 'desc': ''.join([sw_desc, 'Proton Density']), + 'fill_val': -9999.9, 'min_val': 0.0, + 'max_val': np.inf} + meta['sw_bulk_speed'] = {'units': 'km/s', 'name': 'Solar Wind Bulk Speed', + 'notes': '', + 'desc': ''.join([sw_desc, 'Bulk Speed']), + 'fill_val': -9999.9, 'min_val': -np.inf, + 'max_val': np.inf} + meta['sw_ion_temp'] = {'units': 'K', 'name': 'Solar Wind Ti', 'notes': '', + 'desc': ''.join([sw_desc, 'Ion Temperature']), + 'fill_val': -1.0e5, 'min_val': 0.0, + 'max_val': np.inf} + + # Add meta data + for dvar in data.data_vars.keys(): + if dvar in meta.keys(): + data[dvar].attrs.update(meta[dvar]) + + return data diff --git a/GeospaceDataManagement/instruments/methods/general.py b/GeospaceDataManagement/instruments/methods/general.py index dffecdd..cf65110 100644 --- a/GeospaceDataManagement/instruments/methods/general.py +++ b/GeospaceDataManagement/instruments/methods/general.py @@ -4,6 +4,7 @@ # # ---------------------------------------------------------------------------- # Original Authors: pysat development team (c) 2016, Russell Stoneback +# Original Authors: pysat development team, (c) 2020 pysat # # Modified 2026+ # This is a U.S. government work and not under copyright protection in the U.S. @@ -270,3 +271,35 @@ def load_csv_data(fnames, read_csv_kwargs=None): data.index.name = "Epoch" return data + + +def is_fill_val(data, fill_val): + """Evaluate whether or not a value is a fill value. + + Parameters + ---------- + data : int, float, or str + Data value + fill_val : int, float, or str + Fill value + + Returns + ------- + is_fill : bool + True if the data is equal to the fill value, False if it is not. + + """ + + try: + # NaN and finite evaluation will fail for non-numeric types + if np.isnan(fill_val): + is_fill = np.isnan(data) + elif np.isfinite(fill_val): + is_fill = data == fill_val + else: + is_fill = ~np.isfinite(data) + except TypeError: + # Use equality for string and similar types + is_fill = data == fill_val + + return is_fill diff --git a/GeospaceDataManagement/instruments/norp_rf.py b/GeospaceDataManagement/instruments/norp_rf.py new file mode 100644 index 0000000..49cdc12 --- /dev/null +++ b/GeospaceDataManagement/instruments/norp_rf.py @@ -0,0 +1,228 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# ---------------------------------------------------------------------------- +"""Supports solar radio flux values from the Nobeyama Radio Polarimeters. + +Properties +---------- +platform + 'norp' +name + 'rf' +tag + - 'daily' Daily solar flux values from 1951-11-01 onward +inst_id + - None supported + +Examples +-------- +Download and load all of the daily radio flux data. +:: + + rf = gdm.Instrument('norp', 'rf', tag='daily') + rf.download(start=dt.datetime(1951, 11, 1), stop=rf.today()) + rf.load(date=dt.datetime(1951, 11, 1), end_date=rf.today()) + +""" + +import datetime as dt +import numpy as np +import pandas as pds + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'norp' +name = 'rf' +tags = {'daily': 'Daily solar flux values'} +inst_ids = {'': [tag for tag in tags.keys()]} + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'daily': dt.datetime(1951, 11, 1)}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the required Instrument attributes + self.acknowledgements = sw_methods.norp.acknowledgements() + self.references = sw_methods.norp.references(self.name, self.tag) + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean the solar radio flux, empty function as this is not necessary.""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load NoRP solar radio flux files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames. + tag : str + Instrument tag. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data. + + See Also + -------- + GeospaceDataManagement.instruments.methods.general.load_csv_data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # Get the desired file dates and file names from the daily indexed list + file_dates = list() + if tag in ['daily']: + unique_files = list() + for fname in fnames: + file_dates.append(dt.datetime.strptime(fname[-10:], '%Y-%m-%d')) + if fname[0:-11] not in unique_files: + unique_files.append(fname[0:-11]) + fnames = unique_files + + # Load the CSV data files + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={"index_col": 0, "parse_dates": True}) + + # If there is a date range, downselect here + if len(file_dates) > 0: + idx, = np.where((data.index >= min(file_dates)) + & (data.index < max(file_dates) + dt.timedelta(days=1))) + data = data.iloc[idx, :] + + # Initialize the metadata + meta = dict() + for col in data.columns: + meta = {'units': 'SFU', 'notes': '', + 'name': 'NoRP solar sadio flux {:} w/AU corr'.format( + col.replace("_", " ")), + 'desc': ''.join(['NoRP solar radio flux at ', + col.replace("_", " "), ' with Astronomical ', + 'Unit (AU) correction in Solar Flux Units', + ' (SFU).']), + 'fill_val': np.nan, 'min_val': 0, 'max_val': np.inf} + + # Convert the data to xarray and add meta data + data = data.to_xarray() + for dvar in data.data_vars.keys(): + if dvar in meta.keys(): + data[dvar].attrs.update(meta[dvar]) + + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local NoRP solar radio flux data files. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + out_files : pds.Series + A Series containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + # Files are by month, going to add date to monthly filename for each day of + # the month. The load routine will load a month of data and use the + # appended date to select out appropriate data. + if format_str is None: + format_str = "_".join(["norp", "rf", tag, '{year:04d}-{month:02d}.txt']) + + out_files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + if not out_files.empty: + out_files.loc[out_files.index[-1] + pds.DateOffset(months=1) + - pds.DateOffset(days=1)] = out_files.iloc[-1] + out_files = out_files.asfreq('D', 'pad') + out_files = out_files + '_' + out_files.index.strftime('%Y-%m-%d') + + return out_files + + +def download(date_array, tag, inst_id, data_path, update_files=False, + mock_download_dir=None): + """Download NoRP solar radio flux data. + + Parameters + ---------- + date_array : array-like + Sequence of dates for which files will be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the satellite ID for a constellation. + data_path : str + Path to data directory. + update_files : bool + Re-download data for files that already exist if True (default=False) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If a problem is encountered connecting to the gateway or retrieving + data from the remote or local repository. + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + # Download the daily radio flux data from NoRP, saving data in monthly files + sw_methods.norp.daily_rf_downloads(data_path, + mock_download_dir=mock_download_dir, + start=date_array[0], stop=date_array[-1]) + + return diff --git a/GeospaceDataManagement/instruments/sw_ae.py b/GeospaceDataManagement/instruments/sw_ae.py new file mode 100644 index 0000000..221490a --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_ae.py @@ -0,0 +1,180 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports the auroral electrojet AE values. + +Properties +---------- +platform + 'sw' +name + 'ae' +tag + - 'lasp' Predicted AE from real-time ACE or DSCOVR provided by LASP +inst_id + - '' + +""" + +import datetime as dt +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.sw_methods import auroral_electrojet +from GeospaceDataManagement.instruments.sw_methods import lasp + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'ae' +tags = {'lasp': 'Predicted AE from real-time ACE or DSCOVR provided by LASP'} +inst_ids = {'': [tag for tag in tags.keys()]} + +# Generate today's date to support loading predicted data sets +today = gdm.utils.time.today() +tomorrow = today + dt.timedelta(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'lasp': today}} + +# ---------------------------------------------------------------------------- +# Instrument methods + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = auroral_electrojet.acknowledgements( + self.name, self.tag) + self.references = auroral_electrojet.references(self.name, self.tag) + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the AE index, empty function.""" + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load the AE index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + tag : str + Instrument tag string. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={'index_col': 0, + 'parse_dates': True}).to_xarray() + + # Create metadata + data['ae'].attrs.update({'units': 'nT', 'name': 'AE', 'notes': tags[tag], + 'desc': ''.join(['Auroral Electrojet index, best', + ' estimate of the average value', + ' over the next two hours']), + 'fill_val': np.nan, 'min_val': -np.inf, + 'max_val': np.inf}) + + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local data files for AE data. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + # Get the format string, if not supplied by the user + if format_str is None: + format_str = ''.join(['sw_ae_', tag, '_{year:4d}-{month:2d}-', + '{day:2d}.txt']) + + # Get the desired files + files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + + return files + + +def download(date_array, tag, inst_id, data_path, mock_download_dir=None): + """Download the AE index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes for which files will be downloaded. + tag : str + Instrument tag, used to determine download location. + inst_id : str + Instrument ID, not used. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If the data link has an unexpected format or an unknown mock download + directory is supplied. + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + lasp.prediction_downloads(name, tag, data_path, mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_al.py b/GeospaceDataManagement/instruments/sw_al.py new file mode 100644 index 0000000..07ddce0 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_al.py @@ -0,0 +1,181 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports the auroral electrojet AL values. + +Properties +---------- +platform + 'sw' +name + 'al' +tag + - 'lasp' Predicted AL from real-time ACE or DSCOVR provided by LASP +inst_id + - '' + +""" + +import datetime as dt +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.sw_methods import auroral_electrojet +from GeospaceDataManagement.instruments.sw_methods import lasp + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'al' +tags = {'lasp': 'Predicted AL from real-time ACE or DSCOVR provided by LASP'} +inst_ids = {'': [tag for tag in tags.keys()]} + +# Generate today's date to support loading predicted data sets +today = gdm.utils.time.today() +tomorrow = today + dt.timedelta(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'lasp': today}} + +# ---------------------------------------------------------------------------- +# Instrument methods + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = auroral_electrojet.acknowledgements( + self.name, self.tag) + self.references = auroral_electrojet.references(self.name, self.tag) + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the AL index, empty function.""" + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load the AL index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + tag : str + Instrument tag string. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={'index_col': 0, + 'parse_dates': True}).to_xarray() + + # Create metadata + data['al'].attrs.update({'units': 'nT', 'name': 'AL', 'notes': tags[tag], + 'desc': ''.join(['Auroral Electrojet lower ', + 'envelope, best estimate of the', + ' average value over the next ', + 'two hours']), + 'fill_val': np.nan, 'min_val': -np.inf, + 'max_val': 0.0}) + + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local data files for AL data. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + # Get the format string, if not supplied by the user + if format_str is None: + format_str = ''.join(['sw_al_', tag, '_{year:4d}-{month:2d}-', + '{day:2d}.txt']) + + # Get the desired files + files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + + return files + + +def download(date_array, tag, inst_id, data_path, mock_download_dir=None): + """Download the AL index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes for which files will be downloaded. + tag : str + Instrument tag, used to determine download location. + inst_id : str + Instrument ID, not used. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If the data link has an unexpected format or if an unknown mock + download directory is supplied. + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + lasp.prediction_downloads(name, tag, data_path, mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_ap.py b/GeospaceDataManagement/instruments/sw_ap.py new file mode 100644 index 0000000..d5cf4f4 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_ap.py @@ -0,0 +1,279 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports ap index values. + +Properties +---------- +platform + 'sw' +name + 'ap' +tag + - 'def' Definitive ap data from GFZ + - 'now' Nowcast ap data from GFZ + - 'prediction' Predictions from SWPC for the next 3 days + - 'forecast' Forecast data from SWPC (next 3 days) + - 'recent' The last 30 days of Ap data from SWPC + - '45day' 45-Day forecast data from the Air Force +inst_id + - '' + +Note +---- +Downloads data from ftp.gfz-potsdam.de or SWPC. These files also contain Kp +data (with the GFZ data additionally containing Cp data), and so the additional +data files will be saved to the appropriate data directories to avoid multiple +downloads. + +The historic definitive and nowcast Kp files are stored in yearly files, with +the current year being updated remotely on a regular basis. If you are using +historic data for the current year, we recommend re-downloading it before +performing your data processing. + +The forecast data is stored by generation date, where each file contains the +forecast for the next three days, the observed daily Ap from the prior day, and +the estimated Ap from the current day. Forecast data downloads are only +supported for the current day. When loading forecast data, the date specified +with the load command is the date the forecast was generated. The data loaded +will span three days. To always ensure you are loading the most recent data, +load the data with tomorrow's date. + +Recent data is also stored by the generation date from the SWPC. Each file +contains 30 days of Ap measurements. The load date issued to +GeospaceDataManagement corresponds to the generation date. + +Examples +-------- +:: + + ap = gdm.Instrument('sw', 'ap', tag='recent') + ap.download() + ap.load(date=ap.tomorrow()) + + +Warnings +-------- +The 'forecast', 'recent', and '45day' tags load Ap data for a specific period of +time. Loading multiple files, loading multiple days, the data padding feature, +and multi_file_day feature available from the gdm.Instrument object is not +appropriate for this tag data. + +""" + +import datetime as dt +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.methods import general +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'ap' +tags = {'def': 'Definitive Kp data from GFZ', + 'now': 'Nowcast Kp data from GFZ', + 'prediction': 'SWPC Predictions for the next three days', + 'forecast': 'SWPC Forecast data: prior day to three days hence', + 'recent': 'SWPC provided Kp for past 30 days', + '45day': 'Air Force 45-day Forecast'} +inst_ids = {'': list(tags.keys())} + +# Generate todays date to support loading forecast data +now = dt.datetime.now(tz=dt.timezone.utc) +today = dt.datetime(now.year, now.month, now.day) +tomorrow = today + dt.timedelta(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates +_test_dates = {'': {'def': dt.datetime(2009, 1, 1), + 'now': dt.datetime(2020, 1, 1), + 'forecast': tomorrow, + 'prediction': tomorrow, + 'recent': today, + '45day': today}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = sw_methods.kp_ap.acknowledgements( + self.name, self.tag) + self.references = sw_methods.kp_ap.references(self.name, self.tag) + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the Kp, not required for this index (empty function).""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load Ap index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + tag : str + Instrument tag (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + result : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataMangagement. Not intended for direct use by user. + + """ + meta = dict() + + if tag in ['def', 'now']: + # Load the definitive or nowcast data. The Ap data stored in yearly + # files, and we need to return data daily. The daily date is + # attached to filename. Parse off the last date, load month of data, + # and downselect to the desired day + result = sw_methods.gfz.load_def_now(fnames) + + # Initalize the meta data + fill_val = np.nan + for kk in result.keys(): + if kk.lower().find('ap') >= 0: + meta[kk] = sw_methods.kp_ap.get_ap_metadata(fill_val) + elif kk.find('Bartels') >= 0: + meta[kk] = sw_methods.kp_ap.get_bartel_metadata(kk) + else: + # Load the forecast, recent, prediction, or 45day data + result = general.load_csv_data( + fnames, {'index_col': 0, 'parse_dates': True}) + fill_val = -1 + + # Initalize the meta data + for kk in result.keys(): + meta[kk] = sw_methods.kp_ap.get_ap_metadata(fill_val) + + # Cast the data as xarray and save the meta data + result = result.to_xarray() + for dvar in result.data_vars.keys(): + if dvar in meta.keys(): + result[dvar].attrs.update(meta[dvar]) + + return result + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local files for the requested Instrument tag. + + Parameters + ----------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm._files.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataMangagement. Not intended for direct use by user. + + """ + + if tag in ['def', 'now']: + files = sw_methods.gfz.kp_ap_cp_list_files(name, tag, inst_id, + data_path, + format_str=format_str) + else: + files = sw_methods.swpc.list_files(name, tag, inst_id, data_path, + format_str=format_str) + + return files + + +def download(date_array, tag, inst_id, data_path, mock_download_dir=None): + """Download the Ap index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the instrument identification, not used. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Note + ---- + Called by GeospaceDataMangagement. Not intended for direct use by user. + + Warnings + -------- + Only able to download current recent data, not archived forecasts. + + Raises + ------ + IOError + If an unknown mock download directory is supplied. + + """ + + if tag in ['def', 'now']: + sw_methods.gfz.kp_ap_cp_download(platform, name, date_array, tag, + inst_id, data_path, mock_download_dir) + elif tag == 'recent': + sw_methods.swpc.kp_ap_recent_download(name, date_array, data_path, + mock_download_dir) + elif tag == 'forecast': + sw_methods.swpc.geomag_forecast_download(name, date_array, data_path, + mock_download_dir) + elif tag == 'prediction': + sw_methods.swpc.solar_geomag_predictions_download( + name, date_array, data_path, mock_download_dir) + else: + sw_methods.swpc.recent_ap_f107_download(name, date_array, data_path, + mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_apo.py b/GeospaceDataManagement/instruments/sw_apo.py new file mode 100644 index 0000000..dc220d5 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_apo.py @@ -0,0 +1,219 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports apo index values. + +Properties +---------- +platform + 'sw' +name + 'apo' +tag + - 'now' Near real-time nowcast apo data from GFZ +inst_id + - '30min' Half-hourly indices + - '60min' Hourly indices + +Note +---- +Downloads data from ftp.gfz-potsdam.de + +Examples +-------- +:: + + ap30 = gdm.Instrument('sw', 'apo', tag='now', inst_id='30min') + ap30.download(2009, 1) + ap30.load(yr=2009, doy=1) + +""" + +import datetime as dt +import numpy as np +import pandas as pds + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'apo' +tags = {'now': 'Near real-time nowcast apo data from GFZ'} +inst_ids = {inst_id: list(tags.keys()) for inst_id in ['30min', '60min']} + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates +_test_dates = {inst_id: {tag: dt.datetime(2009, 1, 1) + for tag in inst_ids[inst_id]} + for inst_id in inst_ids.keys()} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = sw_methods.gfz.ackn + self.references = sw_methods.gfz.hpo_refs + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the apo, not required for this index (empty function).""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load apo index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + tag : str + Instrument tag (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + result : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + # Load the nowcast data. The Hpo data is stored in monthly files, and we + # need to return data daily. The daily date is attached to filename. + # Parse off the last date, load month of data, and downselect to the + # desired day + result = sw_methods.gfz.load_def_now(fnames).to_xarray() + + # Initalize the meta data + dkey = 'ap{:s}'.format(inst_id.split('min')[0]) + result[dkey].attrs.update({ + 'units': '', 'name': dkey, + 'desc': "{:s}ourly Planetary Open linear index".format( + 'H' if inst_id == '60min' else 'Half-h'), + 'min_val': 0, 'max_val': np.inf, 'fill_val': np.nan}) + + return result + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local files for the requested Instrument tag. + + Parameters + ----------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm._files.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + if format_str is None: + format_str = 'ap{:s}_{{year:04d}}-{{month:02d}}.txt'.format( + inst_id.split('min')[0]) + + # Files are stored by month, going to add a date to the monthly filename for + # each day of month. The load routine will load the year and use the append + # date to select out approriate data. + files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + if not files.empty: + files.loc[files.index[-1] + + pds.DateOffset(months=1, days=-1)] = files.iloc[-1] + files = files.asfreq('D', 'pad') + files = files + '_' + files.index.strftime('%Y-%m-%d') + + return files + + +def download(date_array, tag, inst_id, data_path, update_files=False, + mock_download_dir=None): + """Download the apo index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the instrument identification, not used. + data_path : str + Path to data directory. + update_files : bool + Re-download data for files that already exist if True (default=False) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + Warnings + -------- + Only able to download current recent data, not archived forecasts. + + Raises + ------ + IOError + If an unknown mock download directory is supplied. + + """ + # Set the download input options + gfz_data_name = 'ap{:s}'.format(inst_id.split('min')[0]) + local_file_prefix = '{:s}_'.format(gfz_data_name) + local_date_fmt = "%Y-%m" + freq = pds.DateOffset(months=1, seconds=-1) + + # Call the download routine + sw_methods.gfz.json_downloads(date_array, data_path, local_file_prefix, + local_date_fmt, gfz_data_name, freq, + update_files=update_files, + mock_download_dir=mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_au.py b/GeospaceDataManagement/instruments/sw_au.py new file mode 100644 index 0000000..0949a5d --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_au.py @@ -0,0 +1,180 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports the auroral electrojet AU values. + +Properties +---------- +platform + 'sw' +name + 'au' +tag + - 'lasp' Predicted AU from real-time ACE or DSCOVR provided by LASP +inst_id + - '' + +""" + +import datetime as dt +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.sw_methods import auroral_electrojet +from GeospaceDataManagement.instruments.sw_methods import lasp + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'au' +tags = {'lasp': 'Predicted AU from real-time ACE or DSCOVR provided by LASP'} +inst_ids = {'': [tag for tag in tags.keys()]} + +# Generate today's date to support loading predicted data sets +today = gdm.utils.time.today() +tomorrow = today + dt.timedelta(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'lasp': today}} + +# ---------------------------------------------------------------------------- +# Instrument methods + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = auroral_electrojet.acknowledgements( + self.name, self.tag) + self.references = auroral_electrojet.references(self.name, self.tag) + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the AU index, empty function.""" + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load the AU index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + tag : str + Instrument tag string. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={'index_col': 0, + 'parse_dates': True}).to_xarray() + + # Create metadata + data['au'].attrs.update({'units': 'nT', 'name': 'AU', 'notes': tags[tag], + 'desc': ''.join(['Auroral Electrojet upper ', + 'envelope, best estimate ', + 'of the average value over the ', + 'next two hours']), + 'fill_val': np.nan, 'min_val': 0.0, + 'max_val': np.inf}) + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local data files for AU data. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + # Get the format string, if not supplied by the user + if format_str is None: + format_str = ''.join(['sw_au_', tag, '_{year:4d}-{month:2d}-', + '{day:2d}.txt']) + + # Get the desired files + files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + + return files + + +def download(date_array, tag, inst_id, data_path, mock_download_dir=None): + """Download the AU index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes for which files will be downloaded. + tag : str + Instrument tag, used to determine download location. + inst_id : str + Instrument ID, not used. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If the data link has an unexpected format or if an unknown mock + download directory is supplied. + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + lasp.prediction_downloads(name, tag, data_path, mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_cp.py b/GeospaceDataManagement/instruments/sw_cp.py new file mode 100644 index 0000000..0483329 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_cp.py @@ -0,0 +1,147 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports Cp index values. + +Properties +---------- +platform + 'sw' +name + 'cp' +tag + - 'def' Definitive Cp data from GFZ + - 'now' Nowcast Cp data from GFZ +inst_id + - '' + +Note +---- +Downloads data from ftp.gfz-potsdam.de (GFZ). These files also contain ap and Kp +data, and so the additional data files will be saved to the appropriate data +directories to avoid multiple downloads. + +The historic definitive and nowcast Cp files are stored in yearly files, with +the current year being updated remotely on a regular basis. If you are using +historic data for the current year, we recommend re-downloading it before +performing your data processing. + +Examples +-------- +:: + + cp_ind = gdm.Instrument('sw', 'cp', tag='def') + cp_ind.download(start=dt.datetime(2010, 1, 1)) + cp_ind.load(2010, 1) + +""" + +import datetime as dt +import functools +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'cp' +tags = {'def': 'Definitive Cp data from GFZ', + 'now': 'Nowcast Cp data from GFZ'} +inst_ids = {'': list(tags.keys())} + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates +_test_dates = {'': {'def': dt.datetime(2009, 1, 1), + 'now': dt.datetime(2020, 1, 1)}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = sw_methods.kp_ap.acknowledgements( + self.name, self.tag) + self.references = sw_methods.kp_ap.references(self.name, self.tag) + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the Kp, not required for this index (empty function).""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + +download = functools.partial(sw_methods.gfz.kp_ap_cp_download, platform, name) +list_files = functools.partial(sw_methods.gfz.kp_ap_cp_list_files, name) + + +def load(fnames, tag='', inst_id=''): + """Load Cp index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames. + tag : str + Instrument tag. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # Load the definitive or nowcast data. The Cp data stored in yearly + # files, and we need to return data daily. The daily date is + # attached to filename. Parse off the last date, load month of data, + # and downselect to the desired day + data = sw_methods.gfz.load_def_now(fnames).to_xarray() + + # Initalize the meta data + data['Bartels_solar_rotation_num'].attrs.update( + sw_methods.kp_ap.get_bartel_metadata('Bartels_solar_rotation_num')) + data['day_within_Bartels_rotation'].attrs.update( + sw_methods.kp_ap.get_bartel_metadata('day_within_Bartels_rotation')) + data['Cp'].attrs.update({'units': '', 'name': 'Cp index', + 'desc': ''.join([ + 'the daily planetary character figure, a ', + 'qualitative estimate of the overall level ', + 'of geomagnetic activity for this day ', + 'determined from the sum of the eight ap ', + 'amplitudes']), 'min_val': 0.0, + 'max_val': 2.5, 'fill_val': np.nan}) + data['C9'].attrs.update({'units': '', 'name': 'C9 index', + 'desc': 'the contracted scale for Cp', + 'min_val': 0, 'max_val': 9, 'fill_val': -1}) + + return data diff --git a/GeospaceDataManagement/instruments/sw_dst.py b/GeospaceDataManagement/instruments/sw_dst.py new file mode 100644 index 0000000..acf0863 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_dst.py @@ -0,0 +1,325 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports Dst values. Downloads data from NGDC. + +Properties +---------- +platform + 'sw' +name + 'dst' +tag + - 'noaa' Historic Dst data coalated by and maintained by NOAA/NCEI + - 'lasp' Predicted Dst from real-time ACE or DSCOVR provided by LASP +inst_id + - '' + +Note +---- +Will only work until 2057. + +""" + +import datetime as dt +import ftplib +import numpy as np +import os +import pandas as pds +import shutil + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.sw_methods import dst as mm_dst +from GeospaceDataManagement.instruments.sw_methods import lasp + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'dst' +tags = {'noaa': 'Historic Dst data coalated by and maintained by NOAA/NCEI', + 'lasp': 'Predicted Dst from real-time ACE or DSCOVR provided by LASP'} +inst_ids = {'': [tag for tag in tags.keys()]} + +# Generate today's date to support loading predicted data sets +today = gdm.utils.time.today() +tomorrow = today + dt.timedelta(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'noaa': dt.datetime(2000, 1, 1), 'lasp': today}} + +# Other tags assumed to be True +_test_download_ci = {'': {'noaa': False}} + +# ---------------------------------------------------------------------------- +# Instrument methods + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = mm_dst.acknowledgements(self.tag) + self.references = mm_dst.references(self.tag) + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the Dst index, empty function.""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load the Dst index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + tag : str + Instrument tag string. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataMangaement. Not intended for direct use by user. + + """ + + all_data = [] + + if tag == 'noaa': + # NOAA Dst data is actually stored by year, but users can load by day. + # Extract the actual dates from the input list of filenames as well as + # the names of the actual files. + fdates = [] + ufnames = [] + for filename in fnames: + fdates.append(dt.datetime.strptime(filename[-10:], '%Y-%m-%d')) + ufnames.append(filename[0:-11]) + + # Get unique filenames that map to actual data + ufnames = np.unique(ufnames).tolist() + + # Load unique files + for fname in ufnames: + with open(fname) as open_f: + lines = open_f.readlines() + idx = 0 + + # Check if all lines are good + max_lines = 0 + for line in lines: + if len(line) > 1: + max_lines += 1 + + # Prep memory + yr = np.zeros(max_lines * 24, dtype=int) + mo = np.zeros(max_lines * 24, dtype=int) + day = np.zeros(max_lines * 24, dtype=int) + ut = np.zeros(max_lines * 24, dtype=int) + dst = np.zeros(max_lines * 24, dtype=int) + + # Read data + for line in lines: + if len(line) > 1: + temp_year = np.int64(line[14:16] + line[3:5]) + if temp_year > 57: + temp_year += 1900 + else: + temp_year += 2000 + + yr[idx:idx + 24] = temp_year + mo[idx:idx + 24] = np.int64(line[5:7]) + day[idx:idx + 24] = np.int64(line[8:10]) + ut[idx:idx + 24] = np.arange(24) + temp = line.strip()[20:-4] + temp2 = [temp[4 * i:4 * (i + 1)] for i in np.arange(24)] + dst[idx:idx + 24] = temp2 + idx += 24 + + # Prep datetime index for the data and create DataFrame + start = dt.datetime(yr[0], mo[0], day[0], ut[0]) + stop = dt.datetime(yr[-1], mo[-1], day[-1], ut[-1]) + dates = pds.date_range(start, stop, freq='h') + new_data = pds.DataFrame(dst, index=dates, columns=['dst']) + + # Add to all data loaded for filenames + all_data.append(new_data) + + # Combine data together + data = pds.concat(all_data, sort=True, axis=0) + data.index.name = 'Epoch' + + # Pull out requested days + data = data.iloc[data.index >= fdates[0], :] + data = data.iloc[data.index < fdates[-1] + pds.DateOffset(days=1), :] + else: + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={'index_col': 0, 'parse_dates': True}) + + # Create metadata + data = data.to_xarray() + data['dst'].attrs.update({'units': 'nT', 'name': 'Dst', 'notes': tags[tag], + 'desc': 'Disturbance storm-time index', + 'fill_val': np.nan, 'min_val': -np.inf, + 'max_val': np.inf}) + + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local data files for Dst data. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataMangaement. Not intended for direct use by user. + + """ + # Get the format string, if not supplied by the user + if format_str is None: + if tag == 'noaa': + format_str = 'dst{year:4d}.txt' + else: + format_str = ''.join(['sw_dst_', tag, '_{year:4d}-{month:2d}-', + '{day:2d}.txt']) + + # Get the desired files + files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + + if tag == 'noaa': + # NOAA files yearly, so we need to add daily dates to the yearly + # filenames. The load routine will load a month of data and use + # the appended date to select out appropriate data. + if not files.empty: + files.loc[files.index[-1] + pds.DateOffset(years=1) + - pds.DateOffset(days=1)] = files.iloc[-1] + files = files.asfreq('D', 'pad') + files = files + '_' + files.index.strftime('%Y-%m-%d') + + return files + + +def download(date_array, tag, inst_id, data_path, mock_download_dir=None): + """Download the Dst index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes for which files will be downloaded. + tag : str + Instrument tag, used to determine download location. + inst_id : str + Instrument ID, not used. + data_path : str + Path to data directory. + If not None, will process any files with the correct name and date + as if they were downloaded. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded. (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied. + + Note + ---- + Called by GeospaceDataMangaement. Not intended for direct use by user. + + """ + # If a mock download directory was supplied, test to see it exists + if mock_download_dir is not None: + if not os.path.isdir(mock_download_dir): + raise IOError('file location is not a directory: {:}'.format( + mock_download_dir)) + + if tag == 'noaa': + if mock_download_dir is None: + # Connect to host, default port + ftp = ftplib.FTP('ftp.ngdc.noaa.gov') + + # User anonymous, passwd anonymous@ + ftp.login() + ftp.cwd('/STP/space-weather/geomagnetic-data/INDICES/DST') + + # Data stored by year. Only download for unique set of input years. + years = np.array([date.year for date in date_array]) + years = np.unique(years) + for year in years: + fname_root = 'dst{year:04d}.txt' + fname = fname_root.format(year=year) + saved_fname = os.path.join(data_path, fname) + if mock_download_dir is None: + try: + gdm.logger.info('Downloading file for {year:04d}'.format( + year=year)) + with open(saved_fname, 'wb') as fp: + ftp.retrbinary('RETR ' + fname, fp.write) + except ftplib.error_perm as exception: + if str(exception.args[0]).split(" ", 1)[0] != '550': + raise exception + else: + # File not present + os.remove(saved_fname) + gdm.logger.info('File not available for {:04d}'.format( + year)) + else: + # Get the local file, if it exists + down_fname = os.path.join(mock_download_dir, fname) + if os.path.isfile(down_fname): + shutil.copyfile(down_fname, saved_fname) + else: + gdm.logger.info("".join(["Data not downloaded for ", + down_fname, ", data may have ", + "been saved to an unexpected ", + "filename."])) + + if mock_download_dir is None: + ftp.close() + elif tag == 'lasp': + lasp.prediction_downloads(name, tag, data_path, mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_f107.py b/GeospaceDataManagement/instruments/sw_f107.py new file mode 100644 index 0000000..776ac08 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_f107.py @@ -0,0 +1,432 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports F10.7 index values. + +Properties +---------- +platform + 'sw' +name + 'f107' +tag + - 'historic' LASP F10.7 data (downloads by month, loads by day) + - 'prelim' Preliminary SWPC daily solar indices + - 'now' A mix of nowcast and definitive values from GFZ + - 'daily' Daily SWPC solar indices (contains last 30 days) + - 'forecast' Grab forecast data from SWPC (next 3 days) + - '45day' 45-Day Forecast data from the Air Force +inst_id + - '' No distinction, may include observed, adjusted, or both + - 'obs' Observed F10.7 + - 'adj' Adjusted F10.7 + +Examples +-------- +Download and load all of the historic F10.7 data. Note that it will not +stop on the current date, but a point in the past when post-processing has +been successfully completed. +:: + + f107 = gdm.Instrument('sw', 'f107', tag='historic') + f107.download(start=f107.lasp_stime, stop=f107.today()) + f107.load(date=f107.lasp_stime, end_date=f107.today()) + + +Note +---- +The forecast data is stored by generation date, where each file contains the +forecast for the next three days. Forecast data downloads are only supported +for the current day. When loading forecast data, the date specified with the +load command is the date the forecast was generated. The data loaded will span +three days. To always ensure you are loading the most recent data, load +the data with tomorrow's date. +:: + + f107 = gdm.Instrument('sw', 'f107', tag='forecast') + f107.download() + f107.load(date=f107.tomorrow()) + + +Warnings +-------- +The 'forecast' F10.7 data loads three days at a time. Loading multiple files, +loading multiple days, the data padding feature, and multi_file_day feature +available from the pyast.Instrument object is not appropriate for 'forecast' +data. + +Like 'forecast', the '45day' forecast loads a specific period of time (45 days) +and subsequent files contain overlapping data. Thus, loading multiple files, +loading multiple days, the data padding feature, and multi_file_day feature +available from the pyast.Instrument object is not appropriate for '45day' data. + +""" + +import datetime as dt +import numpy as np +import os +import pandas as pds + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'f107' +tags = {'historic': 'Daily LASP value of F10.7', + 'prelim': 'Preliminary SWPC daily solar indices', + 'now': 'Nowcast and definitive data from GFZ', + 'daily': 'Daily SWPC solar indices (contains last 30 days)', + 'forecast': 'SWPC Forecast F107 data next (3 days)', + '45day': 'Air Force 45-day Forecast'} + +# Dict keyed by inst_id that lists supported tags for each inst_id +inst_ids = {'': [tag for tag in tags.keys() if tag != 'now'], 'obs': ['now'], + 'adj': ['now']} + +# Dict keyed by inst_id that lists supported tags and a good day of test data +# generate todays date to support loading forecast data +now = dt.datetime.now(tz=dt.timezone.utc) +today = dt.datetime(now.year, now.month, now.day) +tomorrow = today + dt.timedelta(days=1) + +# The LASP archive start day is also important +lasp_stime = dt.datetime(1947, 2, 14) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'historic': dt.datetime(2009, 1, 1), + 'prelim': dt.datetime(2009, 1, 1), + 'daily': today, + 'forecast': tomorrow, + '45day': today}, + 'obs': {'now': dt.datetime(2009, 1, 1)}, + 'adj': {'now': dt.datetime(2009, 1, 1)}} + +# Other tags assumed to be True +_test_download_ci = {'': {'prelim': False}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the required Instrument attributes + self.acknowledgements = sw_methods.f107.acknowledgements(self.tag) + self.references = sw_methods.f107.references(self.tag) + gdm.logger.info(self.acknowledgements) + + # Define the historic F10.7 starting time + if self.tag == 'historic': + self.lasp_stime = lasp_stime + + return + + +def clean(self): + """Clean the F10.7 data, empty function as this is not necessary.""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load F10.7 index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames. + tag : str + Instrument tag. (default='') + inst_id : str + Instrument ID. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data. + + See Also + -------- + gdm.instruments.methods.general.load_csv_data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # Get the desired file dates and file names from the daily indexed list + file_dates = list() + if tag in ['historic', 'prelim', 'now']: + unique_files = list() + for fname in fnames: + file_dates.append(dt.datetime.strptime(fname[-10:], '%Y-%m-%d')) + if fname[0:-11] not in unique_files: + unique_files.append(fname[0:-11]) + fnames = unique_files + + # Load the CSV data files + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={"index_col": 0, "parse_dates": True}) + + # Rename the GFZ variable name to be consistent with the other data sets + if tag == 'now': + data = data.rename(columns={'F{:s}'.format(inst_id): 'f107'}) + + # If there is a date range, downselect here + if len(file_dates) > 0: + idx, = np.where((data.index >= min(file_dates)) + & (data.index < max(file_dates) + dt.timedelta(days=1))) + data = data.iloc[idx, :] + + # Initialize the metadata + desc_prefix = '' if inst_id == '' else '{:s} '.format(inst_id.capitalize()) + meta = {'f107': {'units': 'SFU', 'name': 'F10.7 cm solar index', + 'notes': '', 'desc': ''.join([ + desc_prefix, 'F10.7 cm radio flux in Solar Flux ', + 'Units (SFU)']), 'fill_val': np.nan, 'min_val': 0, + 'max_val': np.inf}} + + if tag == 'historic': + # LASP updated file format in June, 2022. Minimize impact downstream by + # continuing use of `f107` as primary data product. + if 'f107_adjusted' in data.columns: + # There may be a mix of old and new data formats. + if 'f107' in data.columns: + # Only fill NaN in the `f107` and `f107_adjusted` columns + # for consistency across both data sets + data.loc[np.isnan(data['f107']), 'f107'] = data.loc[ + np.isnan(data['f107']), 'f107_adjusted'] + + data.loc[np.isnan(data['f107_adjusted']), + 'f107_adjusted'] = data.loc[ + np.isnan(data['f107_adjusted']), 'f107'] + else: + data['f107'] = data['f107_adjusted'] + + # Add metadata + meta['f107_observed'] = dict(meta['f107']) + meta['f107_observed'] = { + 'desc': 'Raw F10.7 cm radio flux in Solar Flux Units (SFU)'} + + meta['f107_adjusted'] = dict(meta['f107_observed']) + meta['f107_adjusted']['desc'] = ''.join([ + 'F10.7 cm radio flux in Solar Flux Units (SFU)', + ' normalized to 1-AU']) + meta['f107']['desc'] = meta['f107_adjusted']['desc'] + + # Save the data and metadata in the desired format + data = data.to_xarray() + for dkey in meta.keys(): + if dkey in data: + data[dkey].attrs.update(meta[dkey]) + + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local F10.7 data files. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + out_files : pds.Series + A Series containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + if tag in ['historic', 'now']: + # Files are by month, going to add date to monthly filename for + # each day of the month. The load routine will load a month of + # data and use the appended date to select out appropriate data. + if format_str is None: + if tag == 'historic': + format_str = 'f107_monthly_{year:04d}-{month:02d}.txt' + else: + format_str = 'F{:s}_{{year:04d}}-{{month:02d}}.txt'.format( + inst_id) + out_files = gdm.Files.from_os(data_path=data_path, + format_str=format_str) + if not out_files.empty: + out_files.loc[out_files.index[-1] + pds.DateOffset(months=1) + - pds.DateOffset(days=1)] = out_files.iloc[-1] + out_files = out_files.asfreq('D', 'pad') + out_files = out_files + '_' + out_files.index.strftime( + '%Y-%m-%d') + + elif tag == 'prelim': + # Files are by year (and quarter) + if format_str is None: + format_str = ''.join(['f107_prelim_{year:04d}_{month:02d}', + '_v{version:01d}.txt']) + out_files = gdm.Files.from_os(data_path=data_path, + format_str=format_str) + + if not out_files.empty: + # Set each file's valid length at a 1-day resolution + orig_files = out_files.sort_index().copy() + new_files = list() + + for orig in orig_files.items(): + # Version determines each file's valid length + version = np.int64(orig[1].split("_v")[1][0]) + doff = pds.DateOffset(years=1) if version == 2 \ + else pds.DateOffset(months=3) + istart = orig[0] + iend = istart + doff - pds.DateOffset(days=1) + + # Ensure the end time does not extend past the number of + # possible days included based on the file's download time + fname = os.path.join(data_path, orig[1]) + dend = dt.datetime.utcfromtimestamp(os.path.getctime(fname)) + dend = dend - pds.DateOffset(days=1) + if dend < iend: + iend = dend + + # Pad the original file index + out_files.loc[iend] = orig[1] + out_files = out_files.sort_index() + + # Save the files at a daily cadence over the desired period + new_files.append(out_files.loc[istart: + iend].asfreq('D', 'pad')) + # Add the newly indexed files to the file output + out_files = pds.concat(new_files, sort=True) + out_files = out_files.dropna() + out_files = out_files.sort_index() + out_files = out_files + '_' + out_files.index.strftime('%Y-%m-%d') + + elif tag in ['daily', 'forecast', '45day']: + out_files = sw_methods.swpc.list_files(name, tag, inst_id, data_path, + format_str=format_str) + + return out_files + + +def download(date_array, tag, inst_id, data_path, update_files=False, + mock_download_dir=None): + """Download F107 index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like + Sequence of dates for which files will be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the satellite ID for a constellation. + data_path : str + Path to data directory. + update_files : bool + Re-download data for files that already exist if True (default=False) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If a problem is encountered connecting to the gateway or retrieving + data from the remote or local repository. + + Warnings + -------- + Only able to download current forecast data, not archived forecasts. + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + # Download standard F107 data + if tag == 'historic': + # Test the date array, updating it if necessary + if date_array.freq != 'MS': + date_array = gdm.utils.time.create_date_range( + dt.datetime(date_array[0].year, date_array[0].month, 1), + date_array[-1], freq='MS') + + # Download from LASP, by month + freq = pds.DateOffset(months=1, seconds=-1) + sw_methods.lisird.download(date_array, data_path, 'f107_monthly_', + '%Y-%m', 'noaa_radio_flux', freq, + update_files, + {'f107_adjusted': -99999.0, + 'f107_observed': -99999.0}, + mock_download_dir=mock_download_dir) + + elif tag == 'prelim': + # Get the local files, to ensure that the version 1 files are + # downloaded again if more data has been added + local_files = list_files(tag, inst_id, data_path) + + # Cut the date from the end of the local files + for i, lfile in enumerate(local_files): + local_files.iloc[i] = lfile[:-11] + + sw_methods.swpc.old_indices_dsd_download( + name, date_array, data_path, local_files, today, + mock_download_dir=mock_download_dir) + elif tag == 'now': + # Set the download input options + gfz_data_name = 'F{:s}'.format(inst_id) + local_file_prefix = '{:s}_'.format(gfz_data_name) + + # Call the download routine + sw_methods.gfz.json_downloads(date_array, data_path, local_file_prefix, + "%Y-%m", gfz_data_name, + pds.DateOffset(months=1, seconds=-1), + update_files=update_files, + mock_download_dir=mock_download_dir) + + elif tag == 'daily': + sw_methods.swpc.daily_dsd_download(name, today, data_path, + mock_download_dir=mock_download_dir) + + elif tag == 'forecast': + sw_methods.swpc.solar_geomag_predictions_download( + name, date_array, data_path, mock_download_dir=mock_download_dir) + + elif tag == '45day': + sw_methods.swpc.recent_ap_f107_download( + name, date_array, data_path, mock_download_dir=mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_flare.py b/GeospaceDataManagement/instruments/sw_flare.py new file mode 100644 index 0000000..707e202 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_flare.py @@ -0,0 +1,347 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports solar flare values. + +Properties +---------- +platform + 'sw' +name + 'flare' +tag + - 'prelim' Preliminary SWPC daily solar indices + - 'daily' Daily SWPC solar indices (contains last 30 days) + - 'prediction' Predictions from SWPC for the next 3 days + +Examples +-------- +Download and load the most recent flare predictions. To always ensure you are +loading the most recent data, load the data with tomorrow's date. +:: + + flare = gdm.Instrument('sw', 'flare', tag='prediction') + flare.download(start=flare.tomorrow()) + flare.load(date=flare.tomorrow()) + + +Note +---- +The forecast data is stored by generation date, where each file contains the +forecast for the next three days. Forecast data downloads are only supported +for the current day. When loading forecast data, the date specified with the +load command is the date the forecast was generated. The data loaded will span +three days. To always ensure you are loading the most recent data, load +the data with tomorrow's date. + + +Warnings +-------- +The 'prediction' flare data loads three days at a time. Loading multiple files, +loading multiple days, the data padding feature, and multi_file_day feature +available from the pyast.Instrument object is not appropriate for 'prediction' +data. + +""" + +import datetime as dt +import numpy as np +import os +import pandas as pds + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'flare' +tags = {'prelim': 'Preliminary SWPC daily solar indices', + 'daily': 'Daily SWPC solar indices (contains last 30 days)', + 'prediction': 'Predictions from SWPC for the next 3 days'} + +# Dict keyed by inst_id that lists supported tags for each inst_id +inst_ids = {'': [tag for tag in tags.keys()]} + +# Dict keyed by inst_id that lists supported tags and a good day of test data +# generate todays date to support loading forecast data +now = dt.datetime.now(tz=dt.timezone.utc) +today = dt.datetime(now.year, now.month, now.day) +tomorrow = today + dt.timedelta(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'prelim': dt.datetime(2009, 1, 1), + 'daily': tomorrow, + 'prediction': tomorrow}} + +# Other tags assumed to be True +_test_download_ci = {'': {'prelim': False}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the required Instrument attributes + self.acknowledgements = sw_methods.swpc.ackn + self.references = "".join(["Check SWPC for appropriate references: ", + "https://www.swpc.noaa.gov/phenomena"]) + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean the F10.7 data, empty function as this is not necessary.""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load the solar flare files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames. + tag : str + Instrument tag. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data. + + See Also + -------- + gdm.instruments.methods.general.load_csv_data + + """ + + # Get the desired file dates and file names from the daily indexed list + file_dates = list() + if tag in ['prelim']: + unique_files = list() + for fname in fnames: + file_dates.append(dt.datetime.strptime(fname[-10:], '%Y-%m-%d')) + if fname[0:-11] not in unique_files: + unique_files.append(fname[0:-11]) + fnames = unique_files + + # Load the CSV data files + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={"index_col": 0, "parse_dates": True}) + + # If there is a date range, downselect here + if len(file_dates) > 0: + idx, = np.where((data.index >= min(file_dates)) + & (data.index < max(file_dates) + dt.timedelta(days=1))) + data = data.iloc[idx, :] + + # Recast data + data = data.to_xarray() + + # Initialize the metadata + if tag == 'daily' or tag == 'prelim': + data['goes_bgd_flux'].attrs.update( + {'units': 'W/m^2', 'name': 'X-ray Background Flux', 'notes': '', + 'desc': 'GOES X-ray Background Flux', 'fill_val': '*', + 'min_val': -np.inf, 'max_val': np.inf}) + if 'c_flare' in data: + data['c_flare'].attrs.update( + {'units': '', 'name': 'C X-Ray Flares', 'notes': '', + 'desc': 'C-class X-Ray Flares', 'fill_val': -1, + 'min_val': 0, 'max_val': 9}) + if 'm_flare' in data: + data['m_flare'].attrs.update( + {'units': '', 'name': 'M X-Ray Flares', 'notes': '', + 'desc': 'M-class X-Ray Flares', 'fill_val': -1, + 'min_val': 0, 'max_val': 9}) + if 'x_flare' in data: + data['x_flare'].attrs.update( + {'units': '', 'name': 'X X-Ray Flares', 'notes': '', + 'desc': 'X-class X-Ray Flares', 'fill_val': -1, + 'min_val': 0, 'max_val': 9}) + if 'o1_flare' in data: + data['o1_flare'].attrs.update( + {'units': '', 'name': '1 Optical Flares', 'notes': '', + 'desc': '1-class Optical Flares', 'fill_val': -1, + 'min_val': 0, 'max_val': 9}) + if 'o2_flare' in data: + data['o2_flare'].attrs.update( + {'units': '', 'name': '2 Optical Flares', 'notes': '', + 'desc': '2-class Optical Flares', 'fill_val': -1, + 'min_val': 0, 'max_val': 9}) + if 'o3_flare' in data: + data['o3_flare'].attrs.update( + {'units': '', 'name': '3 Optical Flares', 'notes': '', + 'desc': '3-class Optical Flares', 'fill_val': -1, + 'min_val': 0, 'max_val': 9}) + elif tag == 'prediction': + for dkey in data: + if dkey.find('Region') < 0: + data[dkey].attrs.update( + {'units': '', 'name': dkey, 'notes': '', + 'desc': ''.join([dkey.replace('_', ' '), + ' Probabilities']), 'fill_val': -1, + 'min_val': 0, 'max_val': 100}) + else: + data[dkey].attrs.update( + {'units': '', 'name': dkey, 'notes': '', + 'desc': 'SWPC Solar Region Number', 'fill_val': -1, + 'min_val': 1, 'max_val': 9999}) + + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local solar flare data files. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + out_files : gdm._files.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + if tag == 'prelim': + # Files are by year (and quarter) + if format_str is None: + format_str = ''.join(['flare_prelim_{year:04d}_{month:02d}', + '_v{version:01d}.txt']) + out_files = gdm.Files.from_os(data_path=data_path, + format_str=format_str) + + if not out_files.empty: + # Set each file's valid length at a 1-day resolution + orig_files = out_files.sort_index().copy() + new_files = list() + + for orig in orig_files.items(): + # Version determines each file's valid length + version = int(orig[1].split("_v")[1][0]) + doff = pds.DateOffset(years=1) if version == 2 \ + else pds.DateOffset(months=3) + istart = orig[0] + iend = istart + doff - pds.DateOffset(days=1) + + # Ensure the end time does not extend past the number of + # possible days included based on the file's download time + fname = os.path.join(data_path, orig[1]) + dend = dt.datetime.utcfromtimestamp(os.path.getctime(fname)) + dend = dend - pds.DateOffset(days=1) + if dend < iend: + iend = dend + + # Pad the original file index + out_files.loc[iend] = orig[1] + out_files = out_files.sort_index() + + # Save the files at a daily cadence over the desired period + new_files.append(out_files.loc[istart: + iend].asfreq('D', 'pad')) + # Add the newly indexed files to the file output + out_files = pds.concat(new_files, sort=True) + out_files = out_files.dropna() + out_files = out_files.sort_index() + out_files = out_files + '_' + out_files.index.strftime('%Y-%m-%d') + + else: + out_files = sw_methods.swpc.list_files(name, tag, inst_id, data_path, + format_str=format_str) + + return out_files + + +def download(date_array, tag, inst_id, data_path, update_files=False, + mock_download_dir=None): + """Download solar flare data from the appropriate repository. + + Parameters + ---------- + date_array : array-like + Sequence of dates for which files will be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the satellite ID for a constellation. + data_path : str + Path to data directory. + update_files : bool + Re-download data for files that already exist if True (default=False) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If a problem is encountered connecting to the gateway or retrieving + data from the remote or local repository. + + Warnings + -------- + Only able to download current forecast data, not archived forecasts. + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + if tag == 'prelim': + # Get the local files, to ensure that the version 1 files are + # downloaded again if more data has been added + local_files = list_files(tag, inst_id, data_path) + + sw_methods.swpc.old_indices_dsd_download(name, date_array, data_path, + local_files, today, + mock_download_dir) + + elif tag == 'daily': + sw_methods.swpc.daily_dsd_download(name, today, data_path, + mock_download_dir) + + elif tag == 'prediction': + sw_methods.swpc.solar_geomag_predictions_download( + name, date_array, data_path, mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_hpo.py b/GeospaceDataManagement/instruments/sw_hpo.py new file mode 100644 index 0000000..7d96614 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_hpo.py @@ -0,0 +1,220 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports Hpo index values. + +Properties +---------- +platform + 'sw' +name + 'hpo' +tag + - 'now' Near real-time nowcast Hpo data from GFZ +inst_id + - '30min' Half-hourly resolution indices + - '60min' Hourly resolution indices + +Note +---- +Downloads data from ftp.gfz-potsdam.de + +Examples +-------- +:: + + hp30 = gdm.Instrument('sw', 'hpo', tag='now', inst_id='30min') + hp30.download(2009, 1) + hp30.load(yr=2009, doy=1) + +""" + +import datetime as dt +import numpy as np +import pandas as pds + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'hpo' +tags = {'now': 'Near real-time nowcast Hpo data from GFZ'} +inst_ids = {inst_id: list(tags.keys()) for inst_id in ['30min', '60min']} + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates +_test_dates = {inst_id: {tag: dt.datetime(2009, 1, 1) + for tag in inst_ids[inst_id]} + for inst_id in inst_ids.keys()} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = sw_methods.gfz.ackn + self.references = sw_methods.gfz.hpo_refs + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the Kp, not required for this index (empty function).""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load Hpo index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames. + tag : str + Instrument tag. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + result : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # Load the nowcast data. The Hpo data is stored in monthly files, and we + # need to return data daily. The daily date is attached to filename. + # Parse off the last date, load month of data, and downselect to the + # desired day + result = sw_methods.gfz.load_def_now(fnames).to_xarray() + + # Initalize the meta data + dkey = 'Hp{:s}'.format(inst_id.split('min')[0]) + result[dkey].attrs.update({'units': '', 'name': dkey, + 'desc': "{:s}ourly Planetary Open index".format( + 'H' if inst_id == '60min' else 'Half-h'), + 'min_val': 0, 'max_val': np.inf, + 'fill_val': np.nan}) + + return result + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local files for the requested Instrument tag. + + Parameters + ----------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm._files.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + if format_str is None: + format_str = 'Hp{:s}_{{year:04d}}-{{month:02d}}.txt'.format( + inst_id.split('min')[0]) + + # Files are stored by month, going to add a date to the monthly filename for + # each day of month. The load routine will load the year and use the append + # date to select out approriate data. + files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + if not files.empty: + files.loc[files.index[-1] + + pds.DateOffset(months=1, days=-1)] = files.iloc[-1] + files = files.asfreq('D', 'pad') + files = files + '_' + files.index.strftime('%Y-%m-%d') + + return files + + +def download(date_array, tag, inst_id, data_path, update_files=False, + mock_download_dir=None): + """Download the Hpo index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the instrument identification, not used. + data_path : str + Path to data directory. + update_files : bool + Re-download data for files that already exist if True (default=False) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + Warnings + -------- + Only able to download current recent data, not archived forecasts. + + Raises + ------ + IOError + If an unknown mock download directory is supplied. + + """ + + # Set the download input options + gfz_data_name = 'Hp{:s}'.format(inst_id.split('min')[0]) + local_file_prefix = '{:s}_'.format(gfz_data_name) + local_date_fmt = "%Y-%m" + freq = pds.DateOffset(months=1, seconds=-1) + + # Call the download routine + sw_methods.gfz.json_downloads(date_array, data_path, local_file_prefix, + local_date_fmt, gfz_data_name, freq, + update_files=update_files, + mock_download_dir=mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_kp.py b/GeospaceDataManagement/instruments/sw_kp.py new file mode 100644 index 0000000..9ae1797 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_kp.py @@ -0,0 +1,269 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports Kp index values. + +Properties +---------- +platform + 'sw' +name + 'kp' +tag + - 'def' Definitive Kp data from GFZ + - 'now' Nowcast Kp data from GFZ + - 'prediction' Predictions from SWPC for the next 3 days + - 'forecast' Forecast data from SWPC (next 3 days) + - 'recent' The last 30 days of Kp data from SWPC +inst_id + - '' + +Note +---- +Downloads data from ftp.gfz-potsdam.de or SWPC. These files also contain ap +data (with the GFZ data additionally containing Cp data), and so the additional +data files will be saved to the appropriate data directories to avoid multiple +downloads. + +The historic definitive and nowcast Kp files are stored in yearly files, with +the current year being updated remotely on a regular basis. If you are using +historic data for the current year, we recommend re-downloading it before +performing your data processing. + +The forecast data is stored by generation date, where each file contains the +forecast for the next three days. Forecast data downloads are only supported +for the current day. When loading forecast data, the date specified with the +load command is the date the forecast was generated. The data loaded will span +three days. To always ensure you are loading the most recent data, load +the data with tomorrow's date. + +Recent data is also stored by the generation date from the SWPC. Each file +contains 30 days of Kp measurements. The load date issued to +GeospaceDataManagement corresponds to the generation date. + +Examples +-------- +:: + + kp = gdm.Instrument('sw', 'kp', tag='recent') + kp.download() + kp.load(date=kp.tomorrow()) + + +Warnings +-------- +The 'forecast', 'prediction', and 'recent' tags load Kp data for a specific +period of time. Loading multiple files, loading multiple days, the data padding +feature, and multi_file_day feature available from the pyast.Instrument object +is not appropriate for these tags data. + +""" + +import datetime as dt +import numpy as np + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'kp' +tags = {'def': 'Definitive Kp data from GFZ', + 'now': 'Nowcast Kp data from GFZ', + 'prediction': 'SWPC Predictions for the next three days', + 'forecast': 'SWPC Forecast data next (3 days)', + 'recent': 'SWPC provided Kp for past 30 days'} +inst_ids = {'': list(tags.keys())} + +# Generate todays date to support loading forecast data +now = dt.datetime.now(tz=dt.timezone.utc) +today = dt.datetime(now.year, now.month, now.day) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates +_test_dates = {'': {'def': dt.datetime(2009, 1, 1), + 'now': dt.datetime(2020, 1, 1), + 'forecast': today + dt.timedelta(days=1), + 'prediction': today + dt.timedelta(days=1), + 'recent': today}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = sw_methods.kp_ap.acknowledgements( + self.name, self.tag) + self.references = sw_methods.kp_ap.references(self.name, self.tag) + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean the Kp, not required for this index (empty function).""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load Kp index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + tag : str + Instrument tag (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + result : pandas.DataFrame + Object containing satellite data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + if tag in ['def', 'now']: + # Load the definitive or nowcast data. The Kp data stored in yearly + # files, and we need to return data daily. The daily date is + # attached to filename. Parse off the last date, load month of data, + # and downselect to the desired day + result = sw_methods.gfz.load_def_now(fnames) + fill_val = np.nan + else: + # Load the prediction, forecast or recent data + result = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={'parse_dates': True, 'index_col': 0}) + fill_val = -1 + + # Recast the data + result = result.to_xarray() + + # Initalize the meta data + if tag in ['forecast', 'recent', 'prediction']: + for kk in result.keys(): + result[kk].attrs.update(sw_methods.kp_ap.get_kp_metadata(fill_val)) + else: + for kk in result.keys(): + if kk.find('Kp') >= 0: + result[kk].attrs.update(sw_methods.kp_ap.get_kp_metadata( + fill_val)) + elif kk.find('Bartels') >= 0: + result[kk].attrs.update( + sw_methods.kp_ap.get_bartel_metadata(kk)) + + return result + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local files for the requested Instrument tag. + + Parameters + ----------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm._files.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + if tag in ['def', 'now']: + files = sw_methods.gfz.kp_ap_cp_list_files(name, tag, inst_id, + data_path, + format_str=format_str) + else: + files = sw_methods.swpc.list_files(name, tag, inst_id, data_path, + format_str=format_str) + + return files + + +def download(date_array, tag, inst_id, data_path, mock_download_dir=None): + """Download the Kp index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the instrument identification, not used. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied or there is a problem + downloading the data. + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + Warnings + -------- + Only able to download current forecast data, not archived forecasts. + + """ + + # Download standard Kp data + if tag in ['def', 'now']: + sw_methods.gfz.kp_ap_cp_download(platform, name, date_array, tag, + inst_id, data_path, mock_download_dir) + elif tag == 'forecast': + sw_methods.swpc.geomag_forecast_download(name, date_array, data_path, + mock_download_dir) + elif tag == 'recent': + sw_methods.swpc.kp_ap_recent_download(name, date_array, data_path, + mock_download_dir) + elif tag == 'prediction': + sw_methods.swpc.solar_geomag_predictions_download( + name, date_array, data_path, mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_methods/__init__.py b/GeospaceDataManagement/instruments/sw_methods/__init__.py new file mode 100644 index 0000000..9f68190 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/__init__.py @@ -0,0 +1,16 @@ +"""Imports for the Space Weather instrument methods.""" + +try: + from GeospaceDataManagement.instruments.sw_methods import ace # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import auroral_electrojet # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import dst # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import f107 # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import general # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import gfz # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import norp # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import kp_ap # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import lasp # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import lisird # noqa F401 + from GeospaceDataManagement.instruments.sw_methods import swpc # noqa F401 +except ImportError: + raise ImportError('missing Space Weather dependencies') diff --git a/GeospaceDataManagement/instruments/sw_methods/ace.py b/GeospaceDataManagement/instruments/sw_methods/ace.py new file mode 100644 index 0000000..a638f2d --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/ace.py @@ -0,0 +1,414 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Provides general routines for the ACE space weather instruments.""" + +import datetime as dt +import numpy as np +import os +import pandas as pds + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.sw_methods import general + +clean_warn = {'dusty': [('logger', 'WARN', + "unused clean level 'dusty', reverting to 'clean'", + 'clean')]} + + +def acknowledgements(): + """Define the acknowledgements for the specified ACE instrument. + + Returns + ------- + ackn : str + Acknowledgements for the ACE instrument + + """ + + ackn = ''.join(['NOAA provided funds for the modification of ', + ' the ACE transmitter to enable the broadcast of', + ' the real-time data and also funds to the ', + 'instrument teams to provide the algorithms for ', + 'processing the real-time data.']) + + return ackn + + +def references(name): + """Define the references for the specified ACE instrument. + + Parameters + ---------- + name : str + Instrument name of the ACE instrument + + Returns + ------- + ref : str + Reference for the ACE instrument paper + + """ + + refs = {'mag': "".join(["'The ACE Magnetic Field Experiment', ", + "C. W. Smith, M. H. Acuna, L. F. Burlaga, ", + "J. L'Heureux, N. F. Ness and J. Scheifele, ", + "Space Sci. Rev., 86, 613-632 (1998)."]), + 'epam': ''.join(['Gold, R. E., S. M. Krimigis, S. E. Hawkins, ', + 'D. K. Haggerty, D. A. Lohr, E. Fiore, ', + 'T. P. Armstrong, G. Holland, L. J. Lanzerotti,', + ' Electron, Proton and Alpha Monitor on the ', + 'Advanced Composition Explorer Spacecraft, ', + 'Space Sci. Rev., 86, 541, 1998.']), + 'swepam': ''.join(['McComas, D., Bame, S., Barker, P. et al. ', + 'Solar Wind Electron Proton Alpha Monitor ', + '(SWEPAM) for the Advanced Composition ', + 'Explorer. Space Sci. Rev., 86, 563–612', + ' (1998). ', + 'https://doi.org/10.1023/A:1005040232597']), + 'sis': ''.join(['Stone, E., Cohen, C., Cook, W. et al. The ', + 'Solar Isotope Spectrometer for the Advanced ', + 'Composition Explorer. Space Sci. Rev., 86, ', + '357–408 (1998). ', + 'https://doi.org/10.1023/A:1005027929871'])} + + if name not in refs.keys(): + raise KeyError('unknown ACE instrument, accepts {:}'.format( + refs.keys())) + + return refs[name] + + +def clean(inst): + """Clean the common aspects of the ACE space weather data. + + Parameters + ---------- + inst : gdm.Instrument + ACE Instrument object + + Returns + ------- + max_status : int + Maximum allowed status + + Note + ---- + gdm Instrument is modified in place + + """ + + if inst.platform != "ace": + raise AttributeError("Can't apply ACE cleaning to platform {:}".format( + inst.platform)) + + # Set the clean level + if inst.clean_level == 'dusty': + gdm.logger.warning("unused clean level 'dusty', reverting to 'clean'") + inst.clean_level = 'clean' + + max_status = 9 + if inst.clean_level == "clean": + max_status = 0 + elif inst.clean_level == "dirty": + max_status = 8 + + return max_status + + +def list_files(name, tag='', inst_id='', data_path='', format_str=None): + """List the local ACE data files. + + Parameters + ---------- + name : str + ACE Instrument name. + tag : str + ACE Instrument tag. (default='') + inst_id : str + Specifies the ACE instrument ID. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + if format_str is None: + format_str = '_'.join(["ace", name, tag, + '{year:04d}-{month:02d}-{day:02d}.txt']) + + files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + + return files + + +def download(date_array, name, tag='', inst_id='', data_path='', now=None, + mock_download_dir=None): + """Download the requested ACE Space Weather data. + + Parameters + ---------- + date_array : array-like + Array of datetime values + name : str + ACE Instrument name. + tag : str + ACE Instrument tag. (default='') + inst_id : str + ACE instrument ID. (default='') + data_path : str + Path to data directory. (default='') + now : dt.datetime or NoneType + Current universal time, if None this is determined for each + download. (default=None) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied or the file format + changes. + + Note + ---- + Called by GeospaceDataMangement. Not intended for direct use by user. + + Warnings + -------- + - Only able to download current real-time data + - File requested not available on server + + """ + # Ensure now is up-to-date, if desired + if now is None: + now = dt.datetime.now(tz=dt.timezone.utc) + + # Define the file information for each data type and check the + # date range + if tag == 'realtime': + file_fmt = "{:s}-{:s}.txt".format("ace", "magnetometer" + if name == "mag" else name) + + if any([len(date_array) > 1, date_array[0].year != now.year, + date_array[0].month != now.month, + date_array[0].day != now.day]): + gdm.logger.warning(''.join(['real-time data only available for ', + 'current day, data in this file will ', + 'have the wrong date.'])) + else: + data_rate = 1 if name in ['mag', 'swepam'] else 5 + file_fmt = '_'.join(["%Y%m%d", "ace", name, + '{:d}m.txt'.format(data_rate)]) + + url = {'realtime': 'https://services.swpc.noaa.gov/text/', + 'historic': 'https://sohoftp.nascom.nasa.gov/sdb/ace/daily/'} + + data_cols = {'mag': ['jd', 'sec', 'status', 'bx_gsm', 'by_gsm', + 'bz_gsm', 'bt_gsm', 'lat_gsm', 'lon_gsm'], + "swepam": ['jd', 'sec', 'status', 'sw_proton_dens', + 'sw_bulk_speed', 'sw_ion_temp'], + "epam": ['jd', 'sec', 'status_e', 'eflux_38-53', + 'eflux_175-315', 'status_p', 'pflux_47-68', + 'pflux_115-195', 'pflux_310-580', + 'pflux_795-1193', 'pflux_1060-1900', 'anis_ind'], + 'sis': ['jd', 'sec', 'status_10', 'int_pflux_10MeV', + 'status_30', 'int_pflux_30MeV']} + + # Cycle through all the dates + for dl_date in date_array: + # Get the file text from the remote or local destination + raw_data = general.get_local_or_remote_text(url[tag], mock_download_dir, + dl_date.strftime(file_fmt)) + + if raw_data is None: + gdm.logger.info("".join(["Data not downloaded for ", + dl_date.strftime(file_fmt), ", date may", + " be out of range for the database or ", + "data may have been saved to an ", + "unexpected filename. Check URL: ", + url[tag], ", or directory: ", + repr(mock_download_dir)])) + else: + # Split the file at the last header line and the new line markers + raw_data = raw_data.split('#-----------------')[-1] + raw_data = raw_data.split('\n')[1:] # Remove the last header line + + # Parse the file, treating the 4 time columns separately + data_dict = {col: list() for col in data_cols[name]} + times = list() + nsplit = len(data_cols[name]) + 4 + for raw_line in raw_data: + split_line = raw_line.split() + if len(split_line) == nsplit: + times.append(dt.datetime.strptime( + ' '.join(split_line[:4]), '%Y %m %d %H%M')) + for i, col in enumerate(data_cols[name]): + # Convert to a number and save + # + # Output is saved as a float, so don't bother to + # differentiate between int and float + data_dict[col].append(float(split_line[4 + i])) + else: + if len(split_line) > 0: + raise IOError(''.join([ + 'unexpected line encoutered in ', url[tag], "/", + dl_date.strftime(file_fmt), ":\n", raw_line])) + + # Put data into nicer DataFrame + data = pds.DataFrame(data_dict, index=times) + + # Write out as a file + data_file = '{:s}.txt'.format( + '_'.join(["ace", name, tag, dl_date.strftime('%Y-%m-%d')])) + data.to_csv(os.path.join(data_path, data_file), header=True) + + return + + +def common_metadata(unit_label='units', name_label='name', note_label='notes', + desc_label='desc', fill_label='fill_val', + min_label='min_val', max_label='max_val'): + """Define the common metadata information for all ACE instruments. + + Parameters + ---------- + unit_label : str + Label for unit meta data + name_label : str + Label for name meta data + note_label : str + Label for note meta data + desc_label : str + Label for description meta data + fill_label : str + Label for fill value meta data + min_label : str + Label for minimum value meta data + max_label : str + Label for maximum value meta data + + Returns + ------- + meta_dict : dict + Dict with meta data + status_desc : str + Description of the status flags + + """ + # Define the Julian day and seconds of day + meta_dict = {'jd': {unit_label: 'days', name_label: 'MJD', note_label: '', + desc_label: 'Modified Julian Day', fill_label: np.nan, + min_label: -np.inf, max_label: np.inf}, + 'sec': {unit_label: 's', name_label: 'Sec of Day', + note_label: '', desc_label: 'Seconds of Julian Day', + fill_label: np.nan, min_label: -np.inf, + max_label: np.inf}} + + # Provide information about the status flags + status_desc = '0 = nominal data, 1 to 8 = bad data record, 9 = no data' + + return meta_dict, status_desc + + +def ace_swepam_hourly_omni_norm(as_inst, speed_key='sw_bulk_speed', + dens_key='sw_proton_dens', + temp_key='sw_ion_temp', note_label='note'): + """Normalize ACE SWEPAM variables as described in the OMNI processing _[1]. + + Parameters + ---------- + as_inst : gdm.Instrument + Instrument object with ACE SWEPAM data. + speed_key : str + Data key for bulk solar wind speed data in km/s + (default='sw_bulk_speed') + dens_key : str + Data key for solar wind proton density data in P/cm^3 + (default='sw_proton_dens') + temp_key : str + Data key for solar wind ion temperature data in K + (default='sw_ion_temp') + note_label : str + Meta data label for notes (default='note') + + References + ---------- + [1] https://omniweb.gsfc.nasa.gov/html/omni_min_data.html + + """ + + # Check the input to make sure all the necessary data variables are present + for var in [speed_key, dens_key, temp_key]: + if var not in as_inst.variables: + raise ValueError('instrument missing variable: {:}'.format(var)) + + # Let yt be the fractional years since 1998.0 + yt = np.array([gdm.utils.time.datetime_to_dec_year(itime) - 1998.0 + for itime in as_inst.index]) + + # The normalization depends on the year + yt_dens = (yt >= 2019.0) & (yt <= 2021.0) + yt_temp = (yt >= 2019.0) & (yt <= 2020.0) + + # Get the masks for the different velocity limits + ilow = as_inst[speed_key] < 395 + imid = (as_inst[speed_key] >= 395) & (as_inst[speed_key] <= 405) + ihigh = as_inst[speed_key] > 405 + + # Calculate the normalized plasma density + norm_n = np.array(as_inst[dens_key]) + norm_n[ilow] *= (0.925 + 0.0039 * yt[ilow]) + norm_n[imid] *= (74.02 - 0.164 * as_inst[speed_key][imid] + + 0.0171 * as_inst[speed_key][imid] * yt[imid] + - 6.72 * yt[imid]) / 10.0 + norm_n[ihigh] *= (0.761 + 0.0210 * yt[ihigh]) + + # Overwrite the calculation for the year where velocity isn't important + norm_n[yt_dens] = np.power(10.0, -0.010 + 1.006 + * np.log10(as_inst[dens_key][yt_dens])) + + # Normalize the temperature + norm_t = np.array(as_inst[temp_key]) + norm_t[~yt_temp] = np.power(10.0, + -0.069 + 1.024 * np.log10(norm_t[~yt_temp])) + norm_t[yt_temp] = np.power(10.0, + 0.266 + 0.947 * np.log10(norm_t[yt_temp])) + + # Update the instrument data + as_inst['sw_proton_dens_norm'] = pds.Series(norm_n, index=as_inst.index) + as_inst['sw_ion_temp_norm'] = pds.Series(norm_t, index=as_inst.index) + + # Add meta data + for dkey, nkey in [[dens_key, 'sw_proton_dens_norm'], + [temp_key, 'sw_ion_temp_norm']]: + note = ''.join([ + 'Normalized for hourly OMNI as described in ', + 'https://omniweb.gsfc.nasa.gov/html/omni_min_data.html']) + + as_inst[nkey].attrs.update(as_inst[dkey].attrs) + as_inst[nkey].attrs.update({note_label: note}) + + return diff --git a/GeospaceDataManagement/instruments/sw_methods/auroral_electrojet.py b/GeospaceDataManagement/instruments/sw_methods/auroral_electrojet.py new file mode 100644 index 0000000..e645aaf --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/auroral_electrojet.py @@ -0,0 +1,78 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: A +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Provides support routines for auroral electrojet indices.""" + + +def acknowledgements(name, tag): + """Define the acknowledgements for the index and data source. + + Parameters + ---------- + name : str + Name of the auroral electrojet index + tag : str + Tag of the auroral electrojet index + + Returns + ------- + ackn : str + Acknowledgements string associated with the appropriate auroral + electrojet tag. + + """ + + ackn = {'lasp': ''.join(['Preliminary ', name.upper(), ' predictions are ', + 'provided by LASP, contact Xinlin Li for more ', + 'details '])} + + return ackn[tag] + + +def references(name, tag): + """Define the references for the auroral electrojet data. + + Parameters + ---------- + name : str + Name of the auroral electrojet index + tag : string + Tag of the space weather index + + Returns + ------- + refs : str + Reference string associated with the appropriate Dst tag. + + """ + + davis = ''.join(['Davis, T. N., and Sugiura, M. (1966), Auroral electrojet', + ' activity index AE and its universal time variations, ', + 'J. Geophys. Res., 71( 3), 785– 801, ', + 'doi:10.1029/JZ071i003p00785.']) + + luo_au_al_ae = ''.join(['Luo, B., Li, X., Temerin, M., and Liu, S. (2013),', + 'Prediction of the AU, AL, and AE indices using ', + 'solar wind parameters, J. Geophys. Res. Space ', + 'Physics, 118, 7683– 7694, ', + 'doi:10.1002/2013JA019188.']) + li_al = ''.join(['Li, X., Oh, K. S., and Temerin, M. (2007), Prediction ', + 'of the AL index using solar wind parameters, J. ', + 'Geophys. Res., 112, A06224, doi:10.1029/2006JA011918.']) + + refs = {'lasp': {'ae': '\n'.join([davis, luo_au_al_ae]), + 'au': '\n'.join([davis, luo_au_al_ae]), + 'al': '\n'.join([davis, li_al, luo_au_al_ae])}} + + return refs[tag][name] diff --git a/GeospaceDataManagement/instruments/sw_methods/dst.py b/GeospaceDataManagement/instruments/sw_methods/dst.py new file mode 100644 index 0000000..6324459 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/dst.py @@ -0,0 +1,65 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Provides default routines for Dst.""" + + +def acknowledgements(tag): + """Define the acknowledgements for the Dst data. + + Parameters + ---------- + tag : str + Tag of the space weather index + + Returns + ------- + ackn : str + Acknowledgements string associated with the appropriate Dst tag. + + """ + + ackn = {'noaa': 'Dst is maintained at NCEI (formerly NGDC) at NOAA', + 'lasp': ''.join(['Preliminary Dst predictions are provided by ', + 'LASP, contact Xinlin Li for more details ', + ''])} + + return ackn[tag] + + +def references(tag): + """Define the references for the Dst data. + + Parameters + ---------- + tag : string + Tag of the space weather index + + Returns + ------- + refs : str + Reference string associated with the appropriate Dst tag. + + """ + + refs = {'noaa': ''.join(['See referenece list and publication at: ', + 'Sugiura M. and T. Kamei, http://', + 'wdc.kugi.kyoto-u.ac.jp/dstdir/dst2/', + 'onDstindex.html, last updated June 1991, ', + 'accessed Dec 2020']), + 'lasp': ''.join(['A New Model for the Prediction of Dst on the ', + 'Basis of the Solar Wind [Temerin and Li, 2002] ', + 'and Dst model for 1995-2002 [Temerin and Li, ', + '2006]'])} + + return refs[tag] diff --git a/GeospaceDataManagement/instruments/sw_methods/f107.py b/GeospaceDataManagement/instruments/sw_methods/f107.py new file mode 100644 index 0000000..b5b4a2c --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/f107.py @@ -0,0 +1,454 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Routines for the F10.7 solar index.""" + +import datetime as dt +import numpy as np +import pandas as pds +import xarray as xr + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.methods.general import is_fill_val +from GeospaceDataManagement.utils.meta import default_fill_values_from_type + + +def acknowledgements(tag): + """Define the acknowledgements for the F10.7 data. + + Parameters + ---------- + tag : str + Tag of the space weather index + + Returns + ------- + ackn : str + Acknowledgements string associated with the appropriate F10.7 tag. + + """ + lisird = 'NOAA radio flux obtained through LISIRD' + swpc = ''.join(['Prepared by the U.S. Dept. of Commerce, NOAA, Space ', + 'Weather Prediction Center']) + + ackn = {'historic': lisird, 'prelim': swpc, 'daily': swpc, + 'forecast': swpc, '45day': swpc, + 'now': gdm.instruments.sw_methods.gfz.ackn} + + return ackn[tag] + + +def references(tag): + """Define the references for the F10.7 data. + + Parameters + ---------- + tag : str + Instrument tag for the F10.7 data. + + Returns + ------- + refs : str + Reference string associated with the appropriate F10.7 tag. + + """ + noaa_desc = ''.join(['Dataset description: ', + 'https://www.ngdc.noaa.gov/stp/space-weather/', + 'solar-data/solar-features/solar-radio/noontime-flux', + '/penticton/documentation/dataset-description', + '_penticton.pdf, accessed Dec 2020']) + orig_ref = ''.join(["Covington, A.E. (1948), Solar noise observations on", + " 10.7 centimetersSolar noise observations on 10.7 ", + "centimeters, Proceedings of the IRE, 36(44), ", + "p 454-457."]) + swpc_desc = ''.join(['Dataset description: https://www.swpc.noaa.gov/', + 'sites/default/files/images/u2/Usr_guide.pdf']) + gfz_desc = ''.join(['Dataset description: https://kp.gfz-potsdam.de/app/', + 'format/Kp_ap_Ap_SN_F107_format.txt']) + + refs = {'historic': "\n".join([noaa_desc, orig_ref]), + 'prelim': "\n".join([swpc_desc, orig_ref]), + 'now': "\n".join([gfz_desc, orig_ref]), + 'daily': "\n".join([swpc_desc, orig_ref]), + 'forecast': "\n".join([swpc_desc, orig_ref]), + '45day': "\n".join([swpc_desc, orig_ref])} + + return refs[tag] + + +def combine_f107(standard_inst, forecast_inst, start=None, stop=None, + note_label='notes', fill_label='fill_val'): + """Combine the output from the measured and forecasted F10.7 sources. + + Parameters + ---------- + standard_inst : gdm.Instrument or NoneType + Instrument object containing data for the 'sw' platform, 'f107' name, + and 'historic', 'prelim', 'now', or 'daily' tag + forecast_inst : gdm.Instrument or NoneType + Instrument object containing data for the 'sw' platform, 'f107' name, + and 'now', 'prelim', '45day' or 'forecast' tag + start : dt.datetime or NoneType + Starting time for combining data, or None to use earliest loaded + date from the gdm Instruments (default=None) + stop : dt.datetime or NoneType + Ending time for combining data, or None to use the latest loaded date + from the gdm Instruments (default=None) + note_label : str + Meta label for notes (default='notes') + fill_label : str + Meta label for fill value (default='fill_val') + + Returns + ------- + f107_inst : gdm.Instrument + Instrument object containing F10.7 observations for the desired period + of time, merging the standard, 45day, and forecasted values based on + their reliability + + Raises + ------ + ValueError + If appropriate time data is not supplied, or if the date range is badly + formed. + + Notes + ----- + Merging prioritizes the standard data, then the 45day data, and finally + the forecast data. + + Will not attempt to download any missing data, but will load data. + + If no data is present, but dates are provided, supplies a series of fill + values. + + """ + + # Initialize metadata and flags + notes = "Combines data from" + stag = standard_inst.tag if len(standard_inst.tag) > 0 else 'default' + tag = 'combined_{:s}_{:s}'.format(stag, forecast_inst.tag) + inst_flag = 'standard' + + # If the start or stop times are not defined, get them from the Instruments + if start is None: + stimes = [inst.index.min() for inst in [standard_inst, forecast_inst] + if len(inst.index) > 0] + start = min(stimes) if len(stimes) > 0 else None + + if stop is None: + stimes = [inst.index.max() for inst in [standard_inst, forecast_inst] + if len(inst.index) > 0] + stop = max(stimes) + pds.DateOffset(days=1) if len(stimes) > 0 else None + + if start is None or stop is None: + raise ValueError(' '.join(("must either load in Instrument objects or", + "provide starting and ending times"))) + + if start >= stop: + raise ValueError("date range is zero or negative") + + # Initialize the output instrument + f107_inst = gdm.Instrument() + f107_inst.inst_module = gdm.instruments.sw_f107 + f107_inst.tag = tag + f107_inst.date = start + f107_inst.doy = np.int64(start.strftime("%j")) + fill_val = None + index_name = None + + f107_times = list() + f107_values = list() + + # Cycle through the desired time range + itime = dt.datetime(start.year, start.month, start.day) + while itime < stop and inst_flag is not None: + # Load and save the standard data for as many times as possible + if inst_flag == 'standard': + # Test to see if data loading is needed + if not np.any(standard_inst.index == itime): + # Set the load kwargs, which vary by GeospaceDataManagement + # version and tag + load_kwargs = {'date': itime} + + if standard_inst.tag == 'daily': + # Add 30 days + load_kwargs['date'] += dt.timedelta(days=30) + + standard_inst.load(**load_kwargs) + + if standard_inst.empty: + good_times = [False] + else: + index_name = standard_inst.index.name + good_times = ((standard_inst.index >= itime) + & (standard_inst.index < stop)) + + if notes.find("standard") < 0: + notes += " the {:} source ({:} to ".format(inst_flag, + itime.date()) + + if np.any(good_times): + if fill_val is None: + f107_inst.data.attrs.update(standard_inst.data.attrs) + for var in standard_inst.variables: + f107_inst[var].attrs.update(standard_inst[var].attrs) + + if fill_label in f107_inst['f107'].attrs: + fill_val = f107_inst['f107'].attrs[fill_label] + else: + fill_val = default_fill_values_from_type(float) + + good_vals = np.array([not is_fill_val(val, fill_val) for val + in standard_inst['f107'][good_times]]) + new_times = list(standard_inst.index[good_times][good_vals]) + else: + new_times = [] + + if len(new_times) > 0: + f107_times.extend(new_times) + new_vals = list(standard_inst['f107'].values[good_times][ + good_vals]) + f107_values.extend(new_vals) + itime = f107_times[-1] + pds.DateOffset(days=1) + else: + inst_flag = 'forecast' + notes += "{:})".format(itime.date()) + + # Load and save the forecast data for as many times as possible + if inst_flag == "forecast": + # Determine which files should be loaded + if len(forecast_inst.index) == 0: + if len(forecast_inst.files.files) > 0: + files = np.unique(forecast_inst.files.files[itime:stop]) + else: + files = [None] # No load, because no files are available + else: + files = [None] # No load needed, if already initialized + + # Cycle through all possible files of interest, saving relevant + # data + for filename in files: + if filename is not None: + forecast_inst.load(fname=filename) + + if notes.find("forecast") < 0: + notes += " the {:} source ({:} to ".format(inst_flag, + itime.date()) + + # Determine which times to save + if forecast_inst.empty: + good_vals = [] + else: + # Check in case there was a problem with the standard data + if fill_val is None: + f107_inst.data.attrs.update(forecast_inst.data.attrs) + for var in forecast_inst.variables: + if var in f107_inst.variables: + f107_inst[var].attrs.update( + forecast_inst[var].attrs) + + if fill_label in f107_inst['f107'].attrs: + fill_val = f107_inst['f107'].attrs[fill_label] + else: + fill_val = default_fill_values_from_type(float) + + # Get the good times and values + good_times = ((forecast_inst.index >= itime) + & (forecast_inst.index < stop)) + good_vals = np.array([ + not is_fill_val(val, fill_val) for val + in forecast_inst['f107'][good_times]]) + if index_name is None: + index_name = forecast_inst.index.name + + # Save desired data and cycle time + if len(good_vals) > 0: + new_times = list(forecast_inst.index[good_times][ + good_vals]) + f107_times.extend(new_times) + new_vals = list( + forecast_inst['f107'][good_times].values[good_vals]) + f107_values.extend(new_vals) + itime = f107_times[-1] + pds.DateOffset(days=1) + + notes += "{:})".format(itime.date()) + + inst_flag = None + + if inst_flag is not None: + notes += "{:})".format(itime.date()) + + if index_name is None: + index_name = 'time' + if fill_val is None: + fill_val = default_fill_values_from_type(float) + + # Determine if the beginning or end of the time series needs to be padded + if len(f107_times) >= 2: + freq = gdm.utils.time.calc_freq(f107_times) + else: + freq = None + end_date = stop - pds.DateOffset(days=1) + date_range = pds.date_range(start=start, end=end_date, freq=freq) + + if len(f107_times) == 0: + f107_times = date_range + freq = gdm.utils.time.calc_freq(f107_times) + f107_values = [fill_val for i in range(len(f107_times))] + + if date_range[0] < f107_times[0]: + # Extend the time and value arrays from their beginning with fill + # values + itime = abs(date_range - f107_times[0]).argmin() + f107_times.reverse() + f107_values.reverse() + extend_times = list(date_range[:itime]) + extend_times.reverse() + f107_times.extend(extend_times) + f107_values.extend([fill_val for kk in extend_times]) + f107_times.reverse() + f107_values.reverse() + + if date_range[-1] > f107_times[-1]: + # Extend the time and value arrays from their end with fill values + itime = abs(date_range - f107_times[-1]).argmin() + 1 + extend_times = list(date_range[itime:]) + f107_times.extend(extend_times) + f107_values.extend([fill_val for kk in extend_times]) + + # Save output data + data = xr.Dataset(data_vars={'f107': ((index_name), f107_values)}, + coords={index_name: f107_times}) + + # Resample the output data, filling missing values + if (date_range.shape != f107_inst.index.shape + or abs(date_range - f107_inst.index).max().total_seconds() > 0.0): + data = data.resample(**{index_name: freq}).asfreq() + if fill_val is not None and np.isfinite(fill_val): + data[np.isnan(f107_inst.data)] = fill_val + + # Save the data to the instrument + f107_inst.data = data + + # Update the metadata notes for this procedure + notes += ", in that order" + f107_inst['f107'].attrs.update({note_label: notes}) + + return f107_inst + + +def calc_f107a(f107_inst, f107_name='f107', f107a_name='f107a', min_pnts=41, + fill_label='fill_val'): + """Calculate the 81 day mean F10.7. + + Parameters + ---------- + f107_inst : gdm.Instrument + Instrument holding the F10.7 data + f107_name : str + Data column name for the F10.7 data (default='f107') + f107a_name : str + Data column name for the F10.7a data (default='f107a') + min_pnts : int + Minimum number of points required to calculate an average (default=41) + fill_label : str + Meta fill value label (default='fill_val') + + Note + ---- + Will not pad data on its own + + """ + + # Test to see that the input data is present + if f107_name not in f107_inst.variables: + raise ValueError("unknown input data variable: {:}".format(f107_name)) + + # Test to see that the output data does not already exist + if f107a_name in f107_inst.variables: + raise ValueError("output data variable already exists: {:}".format( + f107a_name)) + + if fill_label in f107_inst[f107_name].attrs: + fill_val = f107_inst.meta[f107_name].attrs[fill_label] + else: + fill_val = default_fill_values_from_type(float) + + # Calculate the rolling mean. Since these values are centered but rolling + # function doesn't allow temporal windows to be calculated this way, create + # a hack for this. + # + # Ensure the data are evenly sampled at a daily frequency, since this is + # how often F10.7 is calculated. + time_name = f107_inst.index.name + f107_fill = f107_inst.data.resample(**{time_name: '1D'}).asfreq() + + # Replace the time index with an ordinal + time_ind = f107_fill[time_name].values + f107_fill['ordinal'] = ((time_name), [pds.Timestamp(tt).toordinal() + for tt in time_ind]) + f107_fill = f107_fill.swap_dims({time_name: 'ordinal'}) + + # Calculate the mean + f107_fill[f107a_name] = f107_fill[f107_name].rolling( + ordinal=81, min_periods=min_pnts, center=True).mean(skipna=True) + + # Replace the ordinal index with the time + f107_fill = f107_fill.swap_dims({'ordinal': time_name}) + f107_fill.drop_vars('ordinal') + + # Resample to the original frequency, if it is not equal to 1 day + freq = gdm.utils.time.calc_freq(f107_inst.index) + if freq != "86400s": + # Resample to the desired frequency + f107_fill = f107_fill.resample(**{time_name: freq}).ffill() + + # Save the output in a list + f107a = f107_fill[f107a_name] + f107a_values = list(f107a.values) + + # Fill any dates that fall just outside of the range + time_ind = pds.date_range(f107a[time_name].values[0], + f107_inst.index[-1], freq=freq) + for itime in time_ind[f107a[time_name].shape[0]:]: + if (itime - f107a[time_name].values[-1]).total_seconds() < 86400.0: + f107a_values.append(f107a[-1]) + else: + f107a_values.append(fill_val) + + # Redefine the data + + f107_fill = xr.Dataset({f107a_name: ((time_name), f107a_values), + time_name: ((time_name), time_ind)}) + + # There may be missing days in the output data, remove these + if f107_inst.index.shape < f107_fill[time_name].shape: + f107_fill = f107_fill.loc[f107_inst.index] + + # Update the metadata + if len(f107_inst.index) > 1: + notes = ''.join(('Calculated using data between ', + '{:} and {:}'.format(f107_inst.index[0], + f107_inst.index[-1]))) + else: + notes = 'Calculated using times: {:}'.format(f107_inst.index) + meta_dict = {'units': 'SFU', 'name': 'F10.7a', 'notes': notes, + 'desc': "81-day centered average of F10.7", + 'min_val': 0.0, 'max_val': np.nan, fill_label: fill_val} + + # Save the data + f107_inst[f107a_name] = f107_fill[f107a_name] + f107_inst[f107a_name].attrs.update(meta_dict) + + return diff --git a/GeospaceDataManagement/instruments/sw_methods/general.py b/GeospaceDataManagement/instruments/sw_methods/general.py new file mode 100644 index 0000000..02d36ab --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/general.py @@ -0,0 +1,140 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Provides routines that support general space weather instruments.""" + +import importlib +import numpy as np +import os +import requests + +import GeospaceDataManagement as gdm + + +def preprocess_fill(inst, fill_label='fill_val'): + """Preprocess the meta data by replacing the file fill values with NaN. + + Parameters + ---------- + inst : gdm.Instrument + gdm.Instrument object + fill_label : str + Meta label for fill values + + """ + # Replace all fill values with NaN + for col in inst.variables: + if fill_label in inst.data[col].attrs.keys(): + fill_val = inst.data[col].attrs[fill_label] + else: + fill_val = gdm.utils.meta.default_fill_values_from_type(type( + inst.data[col].values.dtype)) + + # Ensure we are dealing with a float for future nan comparison + if isinstance(fill_val, np.floating) or isinstance(fill_val, float): + if ~np.isnan(fill_val): + inst.data[col] = inst.data[col].where( + inst.data[col] != fill_val, other=np.nan) + inst.data[col].attrs[fill_label] = np.nan + + return + + +def get_instrument_data_path(inst_mod_name, tag='', inst_id='', **kwargs): + """Get the `data_path` attribute from an Instrument sub-module. + + Parameters + ---------- + inst_mod_name : str + Instrument module name + tag : str + String specifying the Instrument tag (default='') + inst_id : str + String specifying the instrument identification (default='') + kwargs : dict + Optional additional kwargs that may be used to initialize an Instrument + + Returns + ------- + data_path : str + Path where the Instrument data is stored + + """ + # Import the desired instrument module by name + inst_mod = importlib.import_module(".".join(["GeospaceDataManagement", + "instruments", inst_mod_name])) + + # Initialize a temporary instrument to obtain the object configuration + temp_inst = gdm.Instrument(inst_module=inst_mod, tag=tag, inst_id=inst_id, + **kwargs) + + # Save the data path for this Instrument down to the inst_id level + data_path = temp_inst.files.data_path + + # Delete the temporary instrument + del temp_inst + + return data_path + + +def get_local_or_remote_text(url, mock_download_dir, filename): + """Retrieve text from a remote or local file. + + Parameters + ---------- + filename : str + Filename without any directory structure + url : str + Remote URL where file is located + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Returns + ------- + raw_txt : str or NoneType + All the text from the desired file or None if the file could not be + retrieved + + Raises + ------ + IOError + If an unknown mock download directory is supplied. + + """ + if mock_download_dir is None: + # Set the download webpage + furl = ''.join([url, filename]) + req = requests.get(furl) + + if req.text.find('not found on this server') > 0: + # Ensure useful information about server is passed on to user + gdm.logger.warning('File {:} not found: {:}'.format(filename, url)) + raw_txt = None + else: + raw_txt = req.text if req.ok else None + else: + if not os.path.isdir(mock_download_dir): + raise IOError('file location is not a directory: {:}'.format( + mock_download_dir)) + + furl = os.path.join(mock_download_dir, filename) + + if os.path.isfile(furl): + with open(furl, 'r') as fpin: + raw_txt = fpin.read() + else: + raw_txt = None + + return raw_txt diff --git a/GeospaceDataManagement/instruments/sw_methods/gfz.py b/GeospaceDataManagement/instruments/sw_methods/gfz.py new file mode 100644 index 0000000..0ddcd1c --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/gfz.py @@ -0,0 +1,435 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Provides routines that support GFZ space weather instruments.""" + +import datetime as dt +import json +import numpy as np +import os +import pandas as pds +import requests + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.sw_methods import general + +# ---------------------------------------------------------------------------- +# Define the module variables + +ackn = ''.join(['CC BY 4.0, This index is produced by the Geomagnetic ', + 'Observatory Niemegk, GFZ German Research Centre for ', + 'Geosciences. Please cite the references in the ', + "'references' attribute"]) +geoind_refs = '\n'.join([''.join(["Bartels, J. (1949) - The standardized index", + "Ks and the planetary index Kp, IATME ", + "Bulletin 12b, 97."]), + ''.join(["Matzka, J., Bronkalla, O., Tornow, K., ", + "Elger, K. and Stolle, C., 2021. ", + "Geomagnetic Kp index. V. 1.0. GFZ Data ", + "Services, doi:10.5880/Kp.0001"]), + ''.join(["Matzka, J., Stolle, C., Yamazaki, Y., ", + "Bronkalla, O. and Morschhauser, A., 2021. ", + "The geomagnetic Kp index and derived ", + "indices of geomagnetic activity. Space ", + "Weather,doi:10.1029/2020SW002641"])]) +hpo_refs = '\n'.join([''.join(["Yamazaki, Y., Matzka, J., Stolle, C., ", + "Kervalishvili, G., Rauberg, J., Bronkalla, O.,", + " Morschhauser, A., Bruinsma, S., Shprits, ", + "Y.Y., Jackson, D.R., 2022. Geomagnetic ", + "Activity Index Hpo. Geophys. Res. Lett., 49, ", + "e2022GL098860, doi:10.1029/2022GL098860"]), + ''.join(["Matzka, J., Bronkalla, O., Kervalishvili, G.,", + " Rauberg, J. and Yamazaki, Y., 2022. ", + "Geomagnetic Hpo index. V. 2.0. GFZ Data ", + "Services, doi:10.5880/Hpo.0002"])]) + + +# ---------------------------------------------------------------------------- +# Define the module functions + +def json_downloads(date_array, data_path, local_file_prefix, local_date_fmt, + gfz_data_name, freq, update_files=False, is_def=False, + mock_download_dir=None): + """Download data from GFZ into CSV files at a specified cadence. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + data_path : str + Path to data directory. + local_file_prefix : str + Prefix for local files, e.g., 'tag_' or 'tag_monthly_' + local_date_fmt : str + String format for the local filename, e.g., '%Y-%m-%d' or '%Y-%m' + gfz_data_name : str + Name of the data index on the GFZ server, expects one of: 'Kp', 'ap', + 'Ap', 'Cp', 'C9', 'Hp30', 'Hp60', 'ap30', 'ap60', 'SN', 'Fobs', 'Fadj' + where SN is the international sunspot number and Fxxx is the observed + and adjusted F10.7. + freq : pds.DateOffset or dt.timedelta + Offset to add to the start date to ensure all data is downloaded + (inclusive) + update_files : bool + Re-download data for files that already exist if True (default=False) + is_def : bool + If true, selects only the definitive data, otherwise also includes + nowcast data (default=False) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date (following the local + file prefix and date format) as if they were downloaded (default=None) + + Raises + ------ + IOError + If there is a gateway timeout when downloading data or if an unknown + mock download directory is supplied. + + """ + + # If a mock download directory was supplied, test to see it exists + if mock_download_dir is not None: + if not os.path.isdir(mock_download_dir): + raise IOError('file location is not a directory: {:}'.format( + mock_download_dir)) + + # Set the local variables + base_url = "https://kp.gfz.de/app/json/" + time_fmt = "%Y-%m-%dT%H:%M:%SZ" + last_file = '' + + # Cycle through all the dates + for dl_date in date_array: + # Build the local filename + local_fname = ''.join([local_file_prefix, + dl_date.strftime(local_date_fmt), '.txt']) + local_file = os.path.join(data_path, local_fname) + + # Determine if the download should occur + if not os.path.isfile(local_file) or (update_files + and local_file != last_file): + if mock_download_dir is None: + # Get the URL for the desired data + stop = dl_date + freq + query_url = "{:s}?start={:s}&end={:s}&index={:s}".format( + base_url, dl_date.strftime(time_fmt), + stop.strftime(time_fmt), gfz_data_name) + + if is_def: + # Add the definitive flag + query_url = '{:s}&status=def'.format(query_url) + + # The data is returned as a JSON file + req = requests.get(query_url, verify=False) + + # Process the JSON file + if req.text.find('Gateway Timeout') >= 0: + raise IOError(''.join(['Gateway timeout when requesting ', + 'file using command: ', query_url])) + + raw_txt = req.text if req.ok else None + else: + # Get the text from the downloaded file + query_url = os.path.join(mock_download_dir, local_fname) + if os.path.isfile(query_url): + with open(query_url, 'r') as fpin: + raw_txt = fpin.read() + else: + raw_txt = None + + if raw_txt is not None: + raw_dict = json.loads(raw_txt) + data = pds.DataFrame.from_dict({gfz_data_name: + raw_dict[gfz_data_name]}) + if data.empty: + gdm.logger.warning("no data for {:}".format(dl_date)) + else: + # Convert the datetime strings to datetime objects + time_list = [dt.datetime.strptime(time_str, time_fmt) + for time_str in raw_dict['datetime']] + + # Add the time index + data.index = time_list + + # Create a local CSV file + data.to_csv(local_file, header=True) + else: + gdm.logger.info("".join(["Data not downloaded for ", + dl_date.strftime("%d %b %Y"), + ", date may be out of range ", + "for the database or data may ", + "have been saved to an unexpected", + " filename: {:}".format(query_url)])) + return + + +def kp_ap_cp_download(platform, name, date_array, tag, inst_id, data_path, + mock_download_dir=None): + """Download Kp, ap, and Cp data from GFZ. + + Parameters + ---------- + platform : str + Instrument platform. + name : str + Instrument name. + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + tag : str + String specifying the database, expects 'def' (definitive) or 'now' + (nowcast) + inst_id : str + Specifies the instrument identification, not used. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date (following the local + file prefix and date format) as if they were downloaded (default=None) + + Raises + ------ + ValueError + If an unknown instrument module is supplied. + IOError + If an unknown mock download directory is supplied. + + Note + ---- + Note that the download path for the complementary Instrument will use + the standard GeospaceDataManagement data paths + + """ + # If a mock download directory was supplied, test to see it exists + if mock_download_dir is not None: + if not os.path.isdir(mock_download_dir): + raise IOError('file location is not a directory: {:}'.format( + mock_download_dir)) + + # Set the page for the definitive or nowcast Kp + burl = ''.join(['https://datapub.gfz.de/download/10.5880.Kp.0001', + '/Kp_', 'nowcast' if tag == 'now' else 'definitive', '/']) + data_cols = ['Bartels_solar_rotation_num', 'day_within_Bartels_rotation', + 'Kp', 'daily_Kp_sum', 'ap', 'daily_Ap', 'Cp', 'C9'] + hours = np.arange(0, 24, 3) + kp_translate = {'0': 0.0, '3': 1.0 / 3.0, '7': 2.0 / 3.0} + dnames = list() + + inst_cols = {'sw_kp': [0, 1, 2, 3], 'sw_cp': [0, 1, 6, 7], + 'sw_ap': [0, 1, 4, 5]} + + # Construct the Instrument module name from the platform and name + inst_mod_name = '_'.join([platform, name]) + if inst_mod_name not in inst_cols.keys(): + raise ValueError('Unknown Instrument module {:}, expected {:}'.format( + inst_mod_name, inst_cols.keys())) + + data_paths = {inst_mod: data_path if inst_mod == inst_mod_name else + general.get_instrument_data_path(inst_mod, tag=tag, + inst_id=inst_id) + for inst_mod in inst_cols.keys()} + + # Check that the directories exist + for data_path in data_paths.values(): + gdm.utils.files.check_and_make_path(data_path) + + # Cycle through all the times + for dl_date in date_array: + fname = 'Kp_{:s}{:04d}.wdc'.format(tag, dl_date.year) + if fname not in dnames: + gdm.logger.info(' '.join(('Downloading file for', + dl_date.strftime('%Y')))) + if mock_download_dir is None: + furl = ''.join([burl, fname]) + req = requests.get(furl, verify=False) + + raw_txt = req.text if req.ok else None + else: + furl = os.path.join(mock_download_dir, fname) + if os.path.isfile(furl): + with open(furl, "r") as fpin: + raw_txt = fpin.read() + else: + raw_txt = None + + if raw_txt is not None: + # Split the file text into lines + lines = raw_txt.split('\n')[:-1] + + # Remove the header + while lines[0].find('#') == 0: + lines.pop(0) + + # Process the data lines + ddict = {dkey: list() for dkey in data_cols} + times = list() + for line in lines: + ldate = dt.datetime.strptime(' '.join([ + "{:02d}".format(int(dd)) for dd in + [line[:2], line[2:4], line[4:6]]]), "%y %m %d") + bsr_num = int(line[6:10]) + bsr_day = int(line[10:12]) + if line[28:30] == ' ': + kp_ones = 0.0 + else: + kp_ones = float(line[28:30]) + sum_kp = kp_ones + kp_translate[line[30]] + daily_ap = int(line[55:58]) + cp = float(line[58:61]) + c9 = int(line[61]) + + for i, hour in enumerate(hours): + # Set the time for this hour and day + times.append(ldate + dt.timedelta(hours=int(hour))) + + # Set the daily values for this hour + ddict['Bartels_solar_rotation_num'].append(bsr_num) + ddict['day_within_Bartels_rotation'].append(bsr_day) + ddict['daily_Kp_sum'].append(sum_kp) + ddict['daily_Ap'].append(daily_ap) + ddict['Cp'].append(cp) + ddict['C9'].append(c9) + + # Get the hourly-specific values + ikp = i * 2 + kp_ones = line[12 + ikp] + if kp_ones == ' ': + kp_ones = 0.0 + ddict['Kp'].append(np.float64(kp_ones) + + kp_translate[line[13 + ikp]]) + iap = i * 3 + ddict['ap'].append(np.int64(line[31 + iap:34 + iap])) + + # Put data into nicer DataFrames + for inst_mod in inst_cols.keys(): + sel_cols = np.array(data_cols)[inst_cols[inst_mod]] + sel_dict = {col: ddict[col] for col in sel_cols} + data = pds.DataFrame(sel_dict, index=times, + columns=sel_cols) + + # Write out as a CSV file + sfname = fname.replace('Kp', + inst_mod.split('_')[-1].capitalize()) + saved_fname = os.path.join(data_paths[inst_mod], + sfname).replace('.wdc', '.txt') + data.to_csv(saved_fname, header=True) + + # Record the filename so we don't download it twice + dnames.append(fname) + else: + gdm.logger.info("".join(["Unable to download data for ", + dl_date.strftime("%d %b %Y"), + ", date may be out of range for ", + "the database or data may have been", + " saved to an unexpected filename: ", + furl])) + return + + +def kp_ap_cp_list_files(name, tag, inst_id, data_path, format_str=None): + """List local files for Kp, ap, or Cp data obtained from GFZ. + + Parameters + ---------- + name : str + Instrument name. + tag : str + String specifying the database, expects 'def' (definitive) or 'now' + (nowcast) + inst_id : str + Specifies the instrument identification, not used. + data_path : str + Path to data directory. + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm._files.Files + A class containing the verified available files + + """ + + if format_str is None: + format_str = ''.join(['_'.join([name.capitalize(), tag]), + '{year:04d}.txt']) + + # Files are stored by year, going to add a date to the yearly filename for + # each month and day of month. The load routine will load the year and use + # the append date to select out approriate data. + files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + if not files.empty: + files.loc[files.index[-1] + + pds.DateOffset(years=1, days=-1)] = files.iloc[-1] + files = files.asfreq('D', 'pad') + files = files + '_' + files.index.strftime('%Y-%m-%d') + + return files + + +def load_def_now(fnames): + """Load GFZ yearly definitive or nowcast index data. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + + Returns + ------- + data : pandas.DataFrame + Object containing satellite data + + """ + + # Load the definitive or nowcast data. The GFZ index data are stored in + # yearly or monthly files that are separated by index ondownload. We need + # to return data daily. The daily date is attached to filename. Parse off + # the last date, load all data, and downselect to the desired day + unique_fnames = dict() + for filename in fnames: + fname = filename[0:-11] + fdate = dt.datetime.strptime(filename[-10:], '%Y-%m-%d') + if fname not in unique_fnames.keys(): + unique_fnames[fname] = [fdate] + else: + unique_fnames[fname].append(fdate) + + # Load the desired filenames + all_data = [] + for fname in unique_fnames.keys(): + # The daily date is attached to the filename. Parse off the last + # date, load the year of data, downselect to the desired day + fdate = min(unique_fnames[fname]) + temp = pds.read_csv(fname, index_col=0, parse_dates=True) + + if temp.empty: + gdm.logger.warn('Empty file: {:}'.format(fname)) + continue + + # Select the desired times and add to data list + all_data.append(pds.DataFrame(temp[fdate:max(unique_fnames[fname]) + + dt.timedelta(seconds=86399)])) + + # Combine data together + if len(all_data) > 0: + data = pds.concat(all_data, axis=0, sort=True) + + if data.index.name is None: + data.index.name = "Epoch" + else: + data = pds.DataFrame() + + return data diff --git a/GeospaceDataManagement/instruments/sw_methods/kp_ap.py b/GeospaceDataManagement/instruments/sw_methods/kp_ap.py new file mode 100644 index 0000000..33ffe85 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/kp_ap.py @@ -0,0 +1,910 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Provides routines to support the geomagnetic indices, Kp and Ap.""" + +import datetime as dt +import numpy as np +import pandas as pds +import xarray as xr + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.methods.general import is_fill_val +from GeospaceDataManagement.instruments.sw_methods import gfz +from GeospaceDataManagement.instruments.sw_methods import swpc + + +# -------------------------------------------------------------------------- +# Instrument utilities + +def acknowledgements(name, tag): + """Define the acknowledgements for the geomagnetic data sets. + + Parameters + ---------- + name : str + Instrument name of space weather index, accepts 'kp' or 'ap'. + tag : str + Instrument tag. + + """ + + ackn = {'kp': {'forecast': swpc.ackn, 'recent': swpc.ackn, 'def': gfz.ackn, + 'now': gfz.ackn, 'prediction': swpc.ackn}, + 'ap': {'forecast': swpc.ackn, 'recent': swpc.ackn, + 'prediction': swpc.ackn, '45day': swpc.ackn, + 'def': gfz.ackn, 'now': gfz.ackn}, + 'cp': {'def': gfz.ackn, 'now': gfz.ackn}} + + return ackn[name][tag] + + +def references(name, tag): + """Define the references for the geomagnetic data sets. + + Parameters + ---------- + name : str + Instrument name of space weather index, accepts kp or ap. + tag : str + Instrument tag. + + """ + + gen_refs = "\n".join([''.join(["J. Bartels, The technique of scaling ", + "indices K and Q of geomagnetic activity, ", + "Ann. Intern. Geophys. Year 4, 215-226, ", + "1957."]), + ''.join(["J. Bartels,The geomagnetic measures for ", + "the time-variations of solar corpuscular ", + "radiation, described for use in ", + "correlation studies in other geophysical ", + "fields, Ann. Intern. Geophys. Year 4, ", + "227-236, 1957."]), + ''.join(["P.N. Mayaud, Derivation, Meaning and Use ", + "of Geomagnetic Indices, Geophysical ", + "Monograph 22, Am. Geophys. Union, ", + "Washington D.C., 1980."]), + ''.join(["G.K. Rangarajan, Indices of magnetic ", + "activity, in Geomagnetism, edited by I.A. ", + "Jacobs, Academic, San Diego, 1989."]), + ''.join(["M. Menvielle and A. Berthelier, The ", + "K-derived planetary indices: description ", + "and availability, Rev. Geophys. 29, 3, ", + "415-432, 1991."])]) + + refs = {'kp': {'forecast': gen_refs, 'recent': gen_refs, + 'prediction': gen_refs, 'def': gfz.geoind_refs, + 'now': gfz.geoind_refs}, + 'ap': {'recent': gen_refs, 'forecast': gen_refs, '45day': gen_refs, + 'prediction': gen_refs, 'def': gfz.geoind_refs, + 'now': gfz.geoind_refs}, + 'cp': {'def': gfz.geoind_refs, 'now': gfz.geoind_refs}} + + return refs[name][tag] + + +def get_kp_metadata(fill_val=-1, unit_label='units', desc_label='desc', + min_label='min_val', max_label='max_val', + fill_label='fill_val'): + """Initialize the Kp meta data using our knowledge of the index. + + Parameters + ---------- + fill_val : int or float + File-specific fill value (default=-1) + unit_label : str + Meta data label for units (default='units') + desc_label : str + Meta data label for description (default='desc') + min_label : str + Meta data label for minimum value (default='min_val') + max_label : str + Meta data label for maximum value (default='max_val') + fill_label : str + Meta data label for fill value (default='fill_val') + + Returns + ------- + meta_dict : dict + Dictionary with default meta data + + """ + meta_dict = {unit_label: '', desc_label: "Planetary K-index", min_label: 0, + max_label: 9, fill_label: fill_val} + + return meta_dict + + +def get_ap_metadata(fill_val=-1, unit_label='units', desc_label='desc', + min_label='min_val', max_label='max_val', + fill_label='fill_val'): + """Initialize the ap meta data using our knowledge of the index. + + Parameters + ---------- + fill_val : int or float + File-specific fill value (default=-1) + unit_label : str + Meta data label for units (default='units') + desc_label : str + Meta data label for description (default='desc') + min_label : str + Meta data label for minimum value (default='min_val') + max_label : str + Meta data label for maximum value (default='max_val') + fill_label : str + Meta data label for fill value (default='fill_val') + + Returns + ------- + meta_dict : dict + Dictionary with default meta data + + """ + meta_dict = {unit_label: '', desc_label: "ap (equivalent range) index", + min_label: 0, max_label: 400, fill_label: fill_val} + + return meta_dict + + +def get_bartel_metadata(data_key, fill_val=-1, unit_label='units', + name_label='name', desc_label='desc', + min_label='min_val', max_label='max_val', + fill_label='fill_val'): + """Initialize the Bartel rotation meta data using our knowledge of the data. + + Parameters + ---------- + data_key : str + String denoting the data key + fill_val : int or float + File-specific fill value (default=-1) + unit_label : str + Meta data label for units (default='units') + name_label : str + Meta data label for variable name (default='name') + desc_label : str + Meta data label for description (default='desc') + min_label : str + Meta data label for minimum value (default='min_val') + max_label : str + Meta data label for maximum value (default='max_val') + fill_label : str + Meta data label for fill value (default='fill_val') + + Returns + ------- + meta_dict : dict + Dictionary with default meta data + + """ + + if data_key.find('solar_rotation_num') >= 0: + units = '' + bname = 'Bartels solar rotation number' + desc = 'A sequence of 27-day intervals counted from February 8, 1832' + max_val = np.inf + elif data_key.find('day_within') >= 0: + units = 'day' + bname = 'Days within Bartels solar rotation' + desc = 'Number of days within the Bartels solar rotation' + max_val = 27 + else: + raise ValueError('unknown data key: {:}'.format(data_key)) + + meta_dict = {unit_label: units, name_label: bname, desc_label: desc, + min_label: 1, max_label: max_val, fill_label: fill_val} + + return meta_dict + +# -------------------------------------------------------------------------- +# Common custom functions + + +def convert_3hr_kp_to_ap(kp_inst, var_name='Kp', unit_label='units', + name_label='name', desc_label='desc', + min_label='min_val', max_label='max_val', + fill_label='fill_val', note_label='notes'): + """Calculate 3 hour ap from 3 hour Kp index. + + Parameters + ---------- + kp_inst : gdm.Instrument + Instrument containing Kp data + var_name : str + Variable name for the Kp data (default='Kp') + unit_label : str + Meta data label for units (default='units') + name_label : str + Meta data label for variable name (default='name') + desc_label : str + Meta data label for description (default='desc') + min_label : str + Meta data label for minimum value (default='min_val') + max_label : str + Meta data label for maximum value (default='max_val') + fill_label : str + Meta data label for fill value (default='fill_val') + note_label : str + Meta data notes label (default='notes') + + Raises + ------ + ValueError + If `var_name` is not present in `kp_inst`. + + Note + ---- + Conversion between ap and Kp indices is described at: + https://www.ngdc.noaa.gov/stp/GEOMAG/kp_ap.html + + Assigns new data to '3hr_ap'. + + """ + # Kp are keys, where n.3 = n+ and n.6 = (n+1)-. E.g., 0.6 = 1- + kp_to_ap = {0: 0, 0.3: 2, 0.6: 3, 1: 4, 1.3: 5, 1.6: 6, 2: 7, 2.3: 9, + 2.6: 12, 3: 15, 3.3: 18, 3.6: 22, 4: 27, 4.3: 32, 4.6: 39, + 5: 48, 5.3: 56, 5.6: 67, 6: 80, 6.3: 94, 6.6: 111, 7: 132, + 7.3: 154, 7.6: 179, 8: 207, 8.3: 236, 8.6: 300, 9: 400} + + def ap(kk): + if np.isfinite(kk): + return kp_to_ap[np.floor(kk * 10.0) / 10.0] + else: + return np.nan + + # Test the input + if var_name not in kp_inst.variables: + raise ValueError('Variable name for Kp data is missing: {:}'.format( + var_name)) + + # Convert from Kp to ap + fill_val = kp_inst[var_name].attrs[fill_label] + ap_data = np.array([ap(kp) if kp != fill_val else fill_val + for kp in kp_inst[var_name].values]) + + # Add metadata + meta_dict = get_ap_metadata(fill_val, unit_label=unit_label, + min_label=min_label, max_label=max_label, + fill_label=fill_label, desc_label=desc_label) + meta_dict[desc_label] = "3-hr ap (equivalent range) index" + meta_dict[note_label] = ''.join([ + 'ap converted from Kp as described at: ', + 'https://www.ngdc.noaa.gov/stp/GEOMAG/kp_ap.html']) + + # Append the output to the Instrument + kp_inst['3hr_ap'] = ((kp_inst.index.name), ap_data, meta_dict) + return + + +def calc_daily_Ap(ap_inst, ap_name='3hr_ap', daily_name='Ap', + running_name=None, min_periods=8, unit_label='units', + name_label='name', desc_label='desc', min_label='min_val', + max_label='max_val', fill_label='fill_val', + note_label='notes'): + """Calculate the daily Ap index from the 3hr ap index. + + Parameters + ---------- + ap_inst : gdm.Instrument + Instrument containing 3-hourly ap data + ap_name : str + Column name for 3-hourly ap data (default='3hr_ap') + daily_name : str + Column name for daily Ap data (default='Ap') + running_name : str or NoneType + Column name for daily running average of ap, not output if None + (default=None) + min_periods : int + Mininmum number of observations needed to output an average value + (default=8) + unit_label : str + Meta data label for units (default='units') + name_label : str + Meta data label for variable name (default='name') + desc_label : str + Meta data label for description (default='desc') + min_label : str + Meta data label for minimum value (default='min_val') + max_label : str + Meta data label for maximum value (default='max_val') + fill_label : str + Meta data label for fill value (default='fill_val') + note_label : str + Meta data notes label (default='notes') + + Raises + ------ + ValueError + If `ap_name` or `daily_name` aren't present in `ap_inst` + + Note + ---- + Ap is the mean of the 3hr ap indices measured for a given day + + Option for running average is included since this information is used + by MSIS when running with sub-daily geophysical inputs + + """ + + # Test that the necessary data is available + if ap_name not in ap_inst.variables: + raise ValueError("bad 3-hourly ap variable name: {:}".format(ap_name)) + + # Test to see that we will not be overwritting data + if daily_name in ap_inst.variables: + raise ValueError("daily Ap variable name already exists: " + daily_name) + + # Calculate the daily mean value, first filling the data to the desired + # 3-hour frequency + time_name = ap_inst.index.name + ap_fill = ap_inst.data.resample(**{time_name: '3h'}).asfreq() + + # Now replace the time index with an ordinal in hours + time_ind = ap_fill[time_name].values + ap_fill['ordinal'] = ((time_name), [ + int((tt - time_ind[0]) / np.timedelta64(3, 'h')) for tt in time_ind]) + ap_fill = ap_fill.swap_dims({time_name: 'ordinal'}) + + # Calculate the mean + ap_mean = ap_fill[ap_name].rolling(ordinal=8, + min_periods=min_periods).mean() + + # Replace the ordinal index with the time + ap_mean = ap_mean.swap_dims({'ordinal': time_name}) + ap_mean.drop_vars('ordinal') + + if running_name is not None: + ap_inst[running_name] = ap_mean + + meta_dict = get_ap_metadata( + ap_inst[ap_name].attrs[fill_label], unit_label=unit_label, + desc_label=desc_label, min_label=min_label, max_label=max_label, + fill_label=fill_label) + meta_dict[desc_label] = "running daily Ap index" + meta_dict[note_label] = '24-h running ave of 3-hourly ap indices' + + ap_inst[running_name].attrs.update(meta_dict) + + # Resample, backfilling so that each day uses the mean for the data from + # that day only + # + # Pad the data so the first day will be backfilled and incomplete days will + # have fill values + ap_pad = pds.Series(np.full(shape=(1,), fill_value=np.nan), + index=[ap_mean[time_name].values[0] + - pds.DateOffset(hours=3)]) + ap_full = pds.Series( + np.full(shape=ap_mean[time_name].shape, fill_value=np.nan), + index=ap_mean[time_name].values) + mean_ser = pds.Series(ap_mean, index=ap_mean[time_name]) + + # Extract the mean that only uses data for one day + ap_sel = ap_pad.combine_first(mean_ser.iloc[[i for i, tt in + enumerate(mean_ser.index) + if tt.hour == 21]]) + + # Backfill this data + ap_data = ap_sel.resample('3h').bfill().combine_first(ap_full) + + # Save the output for the original time range + ap_inst[daily_name] = ((time_name), pds.Series(ap_data[1:], + index=ap_data.index[1:])) + + # Add metadata + meta_dict = get_ap_metadata(ap_inst[ap_name].attrs[fill_label], + unit_label=unit_label, desc_label=desc_label, + min_label=min_label, max_label=max_label, + fill_label=fill_label) + meta_dict[desc_label] = "daily Ap index" + meta_dict[note_label] = 'Ap daily mean calculated from 3-hourly ap indices' + ap_inst.data[daily_name].attrs.update(meta_dict) + + return + + +def filter_geomag(inst, min_kp=0, max_kp=9, filter_time=24, kp_inst=None, + var_name='Kp'): + """Filter Instrument data for given time after Kp drops below gate. + + Parameters + ---------- + inst : gdm.Instrument or NoneType + Instrument with non-Kp data to be filtered by geomagnetic activity + min_kp : float + Minimum Kp value allowed. Kp values below this filter the data in + inst (default=0) + max_kp : float + Maximum Kp value allowed. Kp values above this filter the data in + inst (default=9) + filter_time : int + Number of hours to filter data after Kp drops below max_kp (default=24) + kp_inst : gdm.Instrument or NoneType + Kp gdm.Instrument object with or without data already loaded. If None, + will load GFZ definitive kp data for the instrument date (default=None) + var_name : str + String providing the variable name for the Kp data (default='Kp') + + Raises + ------ + IOError + If no Kp data is available to load + + Note + ---- + Loads Kp data for the same timeframe covered by inst and sets inst.data to + NaN for times when Kp > max_kp or Kp < min_kp and for filter_time after Kp + drops below max_kp. + + Default max and min values accept all Kp, so changing only one will cause + the filter to act as a high- or low-pass function. + + This routine is written for standard Kp data (tags of 'def', 'now'), not + the forecast or recent data. However, it will work with these Kp data if + they are supplied. + + """ + # Load the desired data + if kp_inst is None: + kp_inst = gdm.Instrument(inst_module=gdm.instruments.sw_kp, + tag='def', pad=dt.timedelta(days=1)) + + if kp_inst.empty: + load_kwargs = {'date': inst.index[0], 'end_date': inst.index[-1], + 'verifyPad': True} + kp_inst.load(**load_kwargs) + + if kp_inst.empty: + raise IOError( + 'unable to load {:} data for {:}-{:}, check local data'.format( + ':'.join([inst.platform, inst.name, inst.tag, inst.inst_id]), + inst.index[0], inst.index[-1])) + + # Begin filtering, starting at the beginning of the instrument data + sel_data = kp_inst[(inst.index[0] - dt.timedelta(days=1)): + (inst.index[-1] + dt.timedelta(days=1))] + drop_data = sel_data.where((sel_data[var_name] > max_kp) + | (sel_data[var_name] < min_kp), drop=True) + + # Determine the time filter range for removing each flagged data + for dtime in drop_data[kp_inst.index.name].values: + sind = pds.Timestamp(dtime).to_pydatetime() + eind = sind + dt.timedelta(hours=filter_time) + inst.data = inst.data.where( + (inst.data[inst.index.name] < np.datetime64(sind)) + | (inst.data[inst.index.name] > np.datetime64(eind)), other=np.nan) + + # Drop fill data + inst.data = inst.data.dropna(dim=inst.index.name, how='all') + + return + + +# -------------------------------------------------------------------------- +# Common analysis functions + +def convert_ap_to_kp(ap_data, fill_val=-1, ap_name='ap', kp_name='Kp', + unit_label='units', name_label='name', desc_label='desc', + min_label='min_val', max_label='max_val', + fill_label='fill_val', note_label='notes'): + """Convert Ap into Kp. + + Parameters + ---------- + ap_data : array-like + Array-like object containing Ap data + fill_val : int, float, NoneType + Fill value for the data set (default=-1) + ap_name : str + Name of the input ap (default='ap') + kp_name : str + Name of the output Kp (default='Kp') + unit_label : str + Meta data label for units (default='units') + name_label : str + Meta data label for variable name (default='name') + desc_label : str + Meta data label for description (default='desc') + min_label : str + Meta data label for minimum value (default='min_val') + max_label : str + Meta data label for maximum value (default='max_val') + fill_label : str + Meta data label for fill value (default='fill_val') + note_label : str + Meta data notes label (default='notes') + + Returns + ------- + kp_data : array-like + Array-like object containing Kp data + meta_dict : dict + Dictionary with meta data + + """ + # Ensure ap data is list-like + ap_data = gdm.utils.listify(ap_data) + + # Convert from ap to Kp + kp_data = np.array([round_ap(aa, fill_val=fill_val) for aa in ap_data]) + + # Set the metadata + meta_dict = get_kp_metadata(fill_val=fill_val, unit_label=unit_label, + desc_label=desc_label, min_label=min_label, + max_label=max_label, fill_label=fill_label) + meta_dict[desc_label] = 'Kp converted from {:}'.format(ap_name) + meta_dict[note_label] = ''.join( + ['Kp converted from ', ap_name, 'as described at: ', + 'https://www.ngdc.noaa.gov/stp/GEOMAG/kp_ap.html']) + meta_dict[name_label] = 'Kp' + + # Return the data and metadata in the Instrument + return kp_data, meta_dict + + +def round_ap(ap_in, fill_val=np.nan): + """Round an ap value to the nearest Kp value. + + Parameters + ---------- + ap_in : float + Ap value as a floating point number. + fill_val : float + Value for unassigned or bad indices. (default=np.nan) + + Returns + ------- + float + Fill value for infinite or out-of-range data, otherwise the best kp + index is provided. + + """ + + # Define the ap to kp conversion + one_third = 1.0 / 3.0 + two_third = 2.0 / 3.0 + ap_to_kp = {0: 0, 2: one_third, 3: two_third, 4: 1, 5: 1.0 + one_third, + 6: 1.0 + two_third, 7: 2, 9: 2.0 + one_third, + 12: 2.0 + two_third, 15: 3, 18: 3.0 + one_third, + 22: 3.0 + two_third, 27: 4, 32: 4.0 + one_third, + 39: 4.0 + two_third, 48: 5, 56: 5.0 + one_third, + 67: 5.0 + two_third, 80: 6, 94: 6.0 + one_third, + 111: 6.0 + two_third, 132: 7, 154: 7.0 + one_third, + 179: 7.0 + two_third, 207: 8, 236: 8.0 + one_third, + 300: 8.0 + two_third, 400: 9} + max_ap = 400 + + # Infinite or NaN values will return the fill value + if not np.isfinite(ap_in): + return fill_val + + # Ap values that correspond exactly to a Kp value will return that value + if ap_in in ap_to_kp.keys(): + return ap_to_kp[ap_in] + + # The input Ap value may be appropriate, but does not correspond directly + # to a Kp index. Get a sorted list of directly corresponding Ap indices, + # with Kp returned as double (N- = N.6667, N+ = N.3333333) + ap_keys = sorted([akey for akey in ap_to_kp.keys() if akey <= ap_in]) + + # If the value is too large or too small, return the fill value + if len(ap_keys) == 0 or (ap_keys[-1] < ap_in and ap_keys[-1] == max_ap): + return fill_val + + # The value is realistic, return the Kp value + return ap_to_kp[ap_keys[-1]] + + +def combine_kp(standard_inst=None, recent_inst=None, forecast_inst=None, + start=None, stop=None, fill_val=np.nan, unit_label='units', + name_label='name', desc_label='desc', min_label='min_val', + max_label='max_val', fill_label='fill_val', note_label='notes'): + """Combine the output from the different Kp sources for a range of dates. + + Parameters + ---------- + standard_inst : gdm.Instrument or NoneType + Instrument object containing data for the 'sw' platform, 'kp' name, + and 'def' tag or None to exclude (default=None) + recent_inst : gdm.Instrument or NoneType + Instrument object containing data for the 'sw' platform, 'kp' name, + and 'recent' tag or None to exclude (default=None) + forecast_inst : gdm.Instrument or NoneType + Instrument object containing data for the 'sw' platform, 'kp' name, + and 'forecast' tag or None to exclude (default=None) + start : dt.datetime or NoneType + Starting time for combining data, or None to use earliest loaded + date from the Instruments (default=None) + stop : dt.datetime + Ending time for combining data, or None to use the latest loaded date + from the Instruments (default=None) + fill_val : int or float + Desired fill value (since the standard instrument fill value differs + from the other sources) (default=np.nan) + unit_label : str + Meta data label for units (default='units') + name_label : str + Meta data label for variable name (default='name') + desc_label : str + Meta data label for description (default='desc') + min_label : str + Meta data label for minimum value (default='min_val') + max_label : str + Meta data label for maximum value (default='max_val') + fill_label : str + Meta data label for fill value (default='fill_val') + note_label : str + Meta data notes label (default='notes') + + Returns + ------- + kp_inst : gdm.Instrument + Instrument object containing Kp observations for the desired period of + time, merging the standard, recent, and forecasted values based on + their reliability + + Raises + ------ + ValueError + If only one Kp instrument or bad times are provided + + Note + ---- + Merging prioritizes the standard data, then the recent data, and finally + the forecast data. + + Will not attempt to download any missing data, but will load data. + + If no data is present, but dates are provided, supplies a series of fill + values. + + """ + notes = "Combines data from" + + # Create an ordered list of the Instruments, excluding any that are None + all_inst = list() + tag = 'combined' + inst_flag = None + if standard_inst is not None: + all_inst.append(standard_inst) + tag += '_standard' + if inst_flag is None: + inst_flag = 'standard' + + if recent_inst is not None: + all_inst.append(recent_inst) + tag += '_recent' + if inst_flag is None: + inst_flag = 'recent' + + if forecast_inst is not None: + all_inst.append(forecast_inst) + tag += '_forecast' + if inst_flag is None: + inst_flag = 'forecast' + + if len(all_inst) < 2: + raise ValueError("need at two Kp Instrument objects to combine them") + + # If the start or stop times are not defined, get them from the Instruments + if start is None: + stimes = [inst.index.min() for inst in all_inst if len(inst.index) > 0] + start = min(stimes) if len(stimes) > 0 else None + + if stop is None: + stimes = [inst.index.max() for inst in all_inst if len(inst.index) > 0] + stop = max(stimes) + dt.timedelta(days=1) if len(stimes) > 0 else None + + if start is None or stop is None: + raise ValueError(' '.join(("must either load in Instrument objects or", + "provide starting and ending times"))) + + # Initialize the output instrument + kp_inst = gdm.Instrument() + + kp_inst.inst_module = gdm.instruments.sw_kp + kp_inst.tag = tag + kp_inst.date = start + kp_inst.doy = np.int64(start.strftime("%j")) + kp_meta = get_kp_metadata(fill_val=fill_val, unit_label=unit_label, + desc_label=desc_label, min_label=min_label, + max_label=max_label, fill_label=fill_label) + + kp_times = list() + kp_values = list() + index_name = None + + # Cycle through the desired time range + itime = start + while itime < stop and inst_flag is not None: + # Load and save the standard data for as many times as possible + if inst_flag == 'standard': + # Test to see if data loading is needed + if not np.any(standard_inst.index == itime): + standard_inst.load(date=itime) + + if notes.find("standard") < 0: + notes += " the {:} source ({:} to ".format(inst_flag, + itime.date()) + + if len(standard_inst.index) == 0: + inst_flag = 'forecast' if recent_inst is None else 'recent' + notes += "{:})".format(itime.date()) + else: + local_fill_val = standard_inst['Kp'].attrs[fill_label] + good_times = ((standard_inst.index >= itime) + & (standard_inst.index < stop)) + good_vals = np.array([ + not is_fill_val(val, local_fill_val) + for val in standard_inst['Kp'][good_times]]) + new_times = list(standard_inst.index[good_times][good_vals]) + + if len(new_times) > 0: + kp_times.extend(new_times) + kp_values.extend(list( + standard_inst['Kp'][good_times].values[good_vals])) + itime = kp_times[-1] + pds.DateOffset(hours=3) + + if index_name is None: + index_name = standard_inst.index.name + else: + inst_flag = 'forecast' if recent_inst is None else 'recent' + notes += "{:})".format(itime.date()) + + # Load and save the recent data for as many times as possible + if inst_flag == 'recent': + # Determine which files should be loaded + if len(recent_inst.index) == 0: + if len(recent_inst.files.files) > 0: + files = np.unique(recent_inst.files.files[itime:stop]) + else: + files = [None] # No files available + else: + files = [None] # No load needed, if already initialized + + # Cycle through all possible files of interest, saving relevant + # data + for filename in files: + if filename is not None: + recent_inst.load(fname=filename) + + if notes.find("recent") < 0: + notes += " the {:} source ({:} to ".format(inst_flag, + itime.date()) + + # Determine which times to save + if recent_inst.empty: + new_times = [] + else: + local_fill_val = recent_inst['Kp'].attrs[fill_label] + good_times = ((recent_inst.index >= itime) + & (recent_inst.index < stop)) + good_vals = np.array([ + not is_fill_val(val, local_fill_val) + for val in recent_inst['Kp'][good_times]]) + new_times = list(recent_inst.index[good_times][good_vals]) + + # Save output data and cycle time + if len(new_times) > 0: + kp_times.extend(new_times) + kp_values.extend(list( + recent_inst['Kp'][good_times].values[good_vals])) + itime = kp_times[-1] + pds.DateOffset(hours=3) + + if index_name is None: + index_name = recent_inst.index.name + + inst_flag = 'forecast' if forecast_inst is not None else None + notes += "{:})".format(itime.date()) + + # Load and save the forecast data for as many times as possible + if inst_flag == "forecast": + # Determine which files should be loaded + if len(forecast_inst.index) == 0: + if len(forecast_inst.files.files) > 0: + files = np.unique(forecast_inst.files.files[itime:stop]) + else: + files = [None] # No files have been downloaded + else: + files = [None] # No load needed, if already initialized + + # Cycle through all possible files of interest, saving relevant + # data + for filename in files: + if filename is not None: + forecast_inst.load(fname=filename) + + if notes.find("forecast") < 0: + notes += " the {:} source ({:} to ".format(inst_flag, + itime.date()) + + # Determine which times to save + if not forecast_inst.empty: + local_fill_val = forecast_inst['Kp'].attrs[fill_label] + good_times = ((forecast_inst.index >= itime) + & (forecast_inst.index < stop)) + good_vals = np.array([ + not is_fill_val(val, local_fill_val) + for val in forecast_inst['Kp'][good_times]]) + + # Save desired data + new_times = list(forecast_inst.index[good_times][good_vals]) + + if index_name is None: + index_name = forecast_inst.index.name + + if len(new_times) > 0: + kp_times.extend(new_times) + new_vals = list(forecast_inst['Kp'][good_times][ + good_vals]) + kp_values.extend(new_vals) + + # Cycle time + itime = kp_times[-1] + pds.DateOffset(hours=3) + notes += "{:})".format(itime.date()) + + inst_flag = None + + if inst_flag is not None: + notes += "{:})".format(itime.date()) + + if index_name is None: + index_name = 'time' + + # Determine if the beginning or end of the time series needs to be padded + freq = None if len(kp_times) < 2 else gdm.utils.time.calc_freq(kp_times) + end_date = stop - pds.DateOffset(days=1) + date_range = pds.date_range(start=start, end=end_date, freq=freq) + + if len(kp_times) == 0: + kp_times = date_range + kp_values = [fill_val for i in range(len(kp_times))] + + if date_range[0] < kp_times[0]: + # Extend the time and value arrays from their beginning with fill + # values + itime = abs(date_range - kp_times[0]).argmin() + kp_times.reverse() + kp_values.reverse() + extend_times = list(date_range[:itime]) + extend_times.reverse() + kp_times.extend(extend_times) + kp_values.extend([fill_val for kk in extend_times]) + kp_times.reverse() + kp_values.reverse() + + if date_range[-1] > kp_times[-1]: + # Extend the time and value arrays from their end with fill values + itime = abs(date_range - kp_times[-1]).argmin() + 1 + extend_times = list(date_range[itime:]) + kp_times.extend(extend_times) + kp_values.extend([fill_val for kk in extend_times]) + + # Update the metadata notes for this procedure + notes += ", in that order" + kp_meta[note_label] = notes + + # Save output data and meta data + kp_inst.data = xr.Dataset({index_name: ((index_name), kp_times), + 'Kp': ((index_name), kp_values, kp_meta)}) + + # Resample the output data, filling missing values + if (date_range.shape != kp_inst.index.shape + or abs(date_range - kp_inst.index).max().total_seconds() > 0.0): + kp_inst.data = kp_inst.data.resample(**{index_name: freq}).asfreq() + nan_fill = np.isnan(kp_inst.data['Kp'].values) + if np.isfinite(fill_val) and nan_fill.any(): + kp_inst.data['Kp'][nan_fill] = fill_val + + return kp_inst diff --git a/GeospaceDataManagement/instruments/sw_methods/lasp.py b/GeospaceDataManagement/instruments/sw_methods/lasp.py new file mode 100644 index 0000000..13b8e7b --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/lasp.py @@ -0,0 +1,113 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Provides support routines for LASP data.""" + +import datetime as dt +import numpy as np +import os +import pandas as pds +import requests + +import GeospaceDataManagement as gdm + + +def prediction_downloads(name, tag, data_path, mock_download_dir=None): + """Download LASP 96-hour prediction data. + + Parameters + ---------- + name : str + Instrument name, currently supports Dst, AL, AE, and AU. + tag : str + Instrument tag, used to create a descriptive file name. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date (following the local + file prefix and date format) as if they were downloaded (default=None) + + Raises + ------ + IOError + If the data link has an unexpected format or an unknown mock download + directory is supplied. + + """ + times = list() + data_dict = {name.lower(): []} + fname = ''.join([name.lower(), '_last_96_hrs.txt']) + + if mock_download_dir is None: + # Set the remote data variables + url = ''.join(['https://lasp.colorado.edu/space_weather/dsttemerin/', + fname]) + + # Download the webpage + req = requests.get(url) + + # Test to see if the file was found on the server + if req.text.find('not found on this server') > 0: + gdm.logger.warning(''.join(['LASP last 96 hour Dst file not ', + 'found on server: ', url])) + raw_txt = None + else: + raw_txt = req.text + else: + # If a mock download directory was supplied, test to see it exists + if mock_download_dir is not None: + if not os.path.isdir(mock_download_dir): + raise IOError('file location is not a directory: {:}'.format( + mock_download_dir)) + + # Get the data from the mock download directory + url = os.path.join(mock_download_dir, fname) + if os.path.isfile(url): + with open(url, 'r') as fpin: + raw_txt = fpin.read() + else: + gdm.logger.warning(''.join(['LASP last 96 hour file not found in', + 'the local directory: ', url, + ", data may have been saved to an ", + "unexpected filename"])) + raw_txt = None + + if raw_txt is not None: + # Split the file into lines, removing the header and + # trailing empty line + file_lines = raw_txt.split('\n')[1:-1] + + # Format the data + for line in file_lines: + # Split the line on whitespace + line_cols = line.split() + + if len(line_cols) != 2: + raise IOError(''.join(['unexpected line encountered in file ', + 'retrieved from ', url, ':\n', line])) + + # Format the time and AL values + times.append(dt.datetime.strptime(line_cols[0], '%Y/%j-%H:%M:%S')) + data_dict[name.lower()].append(np.float64(line_cols[1])) + + # Re-cast the data as a pandas DataFrame + data = pds.DataFrame(data_dict, index=times) + + # Write out as a file + file_base = '_'.join(['sw', name, tag, + gdm.utils.time.today().strftime('%Y-%m-%d')]) + file_name = os.path.join(data_path, '{:s}.txt'.format(file_base)) + data.to_csv(file_name) + + return diff --git a/GeospaceDataManagement/instruments/sw_methods/lisird.py b/GeospaceDataManagement/instruments/sw_methods/lisird.py new file mode 100644 index 0000000..d7de3d8 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/lisird.py @@ -0,0 +1,223 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Provides support functions for the LASP LISIRD data base.""" + +import datetime as dt +import json +import numpy as np +import os +import pandas as pds +import requests + +import GeospaceDataManagement as gdm + +ackn = "".join(["LASP Interactive Solar Irradiance Data Center provides ", + "access to many solar datasets generated by researchers at ", + "LASP and other institutions."]) + + +def references(platform, name, tag, inst_id): + """Provide references for different Instrument data products. + + Parameters + ---------- + platform : str + Instrument platform + name : str + Instrument name + tag : str + Instrument tag + inst_id : str + Instrument ID + + Returns + ------- + refs : str + String of references + + """ + + refs = {'sw': {'mgii': { + 'composite': { + '': ''.join(["Viereck, R. A., Floyd, L. E., Crane, P. C., Woods, ", + "T. N., Knapp, B. G., Rottman, G., Weber, M., Puga,", + " L. C., and DeLand, M. T. (2004), A composite Mg ", + "II index spanning from 1978 to 2003, Space Weather", + ", 2, S10005, doi:10.1029/2004SW000084."])}, + 'sorce': { + '': "\n".join([ + "".join(["Snow, M, William E. McClintock, Thomas N. Woods, ", + "Oran R. White, Jerald W. Harder, and Gary Rottman ", + "(2005). The Mg II Index from SORCE, Solar Phys., ", + "230, 1, 325-344."]), + "".join(["Heath, D. and Schlesinger, B. (1986). The Mg 280-nm ", + "doublet as a monitor of changes in solar ", + "ultraviolet irradiance, JGR, 91, 8672-8682."])])}}}} + + return refs[platform][name][tag][inst_id] + + +def build_lisird_url(lisird_data_name, start, stop): + """Build a LASP LISIRD direct download URL. + + Parameters + ---------- + lisird_data_name : str + Name of the data set on the LISARD server + start : dt.datetime + Start time + stop : dt.datetime + Stop time + + Returns + ------- + url : str + URL that will download the desired data + + """ + + # Define the formatting for the start and stop times + tfmt = "%Y-%m-%dT%H:%M:%S.000Z" + + url = "".join(["https://lasp.colorado.edu/lisird/latis/dap/", + lisird_data_name, ".json?&time>=", start.strftime(tfmt), + '&time<=', stop.strftime(tfmt), + "&format_time(yyyy-MM-dd'T'HH:mm:ss.SSS)"]) + + return url + + +def download(date_array, data_path, local_file_prefix, local_date_fmt, + lisird_data_name, freq, update_files=False, fill_vals=None, + mock_download_dir=None): + """Download routine for LISIRD data. + + Parameters + ---------- + date_array : array-like + Sequence of dates for which files will be downloaded. + data_path : str + Path to data directory. + local_file_prefix : str + Prefix for local files, e.g., 'tag_' or 'tag_monthly_' + local_date_fmt : str + String format for the local filename, e.g., '%Y-%m-%d' or '%Y-%m' + lisird_data_name : str + Name of the data set on the LISARD server + freq : pds.DateOffset or dt.timedelta + Offset to add to the start date to ensure all data is downloaded + (inclusive) + update_files : bool + Re-download data for files that already exist if True (default=False) + fill_vals : dict or NoneType + Dict of fill values to replace with NaN by variable name or None to + leave alone (default=None) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date (following the local + file prefix and date format) as if they were downloaded (default=None) + + Raises + ------ + IOError + If there is a gateway timeout when downloading data or an unknown mock + download directory is supplied. + KeyError + If the `fill_vals` input does not match the downloaded data. + + """ + # If a mock download directory was supplied, test to see it exists + if mock_download_dir is not None: + if not os.path.isdir(mock_download_dir): + raise IOError('file location is not a directory: {:}'.format( + mock_download_dir)) + + # Initialize the fill_vals dict, if necessary + if fill_vals is None: + fill_vals = {} + + # Cycle through all the dates + for dl_date in date_array: + # Build the local filename + fname = ''.join([local_file_prefix, dl_date.strftime(local_date_fmt), + '.txt']) + local_file = os.path.join(data_path, fname) + + # Determine if the download should occur + if update_files or not os.path.isfile(local_file): + if mock_download_dir is None: + # Get the URL for the desired data + url = build_lisird_url(lisird_data_name, dl_date, + dl_date + freq) + + # The data is returned as a JSON file + req = requests.get(url) + + # Process the JSON file + if req.text.find('Gateway Timeout') >= 0: + raise IOError(''.join(['Gateway timeout when requesting ', + 'file using command: ', url])) + + # Load the dict if text was retrieved + json_dict = json.loads(req.text) if req.ok else {'': {}} + else: + # Get the local repository filename + url = os.path.join(mock_download_dir, fname) + if os.path.isfile(url): + with open(url, 'r') as fpin: + raw_txt = fpin.read() + + json_dict = json.loads(raw_txt) + else: + json_dict = {'': {}} + + if lisird_data_name in json_dict.keys(): + raw_dict = json_dict[lisird_data_name] + data = pds.DataFrame.from_dict(raw_dict['samples']) + if data.empty: + gdm.logger.warning("no data for {:}".format(dl_date)) + else: + # The URL specifies the time format, so break it down + frac_sec = [int(tval.split('.')[-1]) + for tval in data['time']] + times = [dt.datetime.strptime(tval.split('.')[0], + '%Y-%m-%dT%H:%M:%S') + + dt.timedelta(microseconds=frac_sec[i] * 6) + for i, tval in enumerate(data.pop('time'))] + data.index = times + + # Replace fill value with NaNs + for var in fill_vals.keys(): + if var in data.columns: + idx, = np.where(data[var] == fill_vals[var]) + data.iloc[idx, :] = np.nan + else: + raise KeyError(''.join(['unknown fill value ', + 'variable name supplied: ', + var])) + + # Create a local CSV file + data.to_csv(local_file, header=True) + else: + if len(json_dict.keys()) == 1 and '' in json_dict.keys(): + gdm.logger.info("".join(["Data not downloaded for ", + dl_date.strftime("%d %b %Y"), + ", date may be out of range ", + "for the database or data may ", + "have been saved to an ", + "unexpected filename: ", url])) + else: + raise IOError(''.join(['Returned unexpectedly formatted ', + 'data using command: ', url])) + return diff --git a/GeospaceDataManagement/instruments/sw_methods/norp.py b/GeospaceDataManagement/instruments/sw_methods/norp.py new file mode 100644 index 0000000..cbbb568 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/norp.py @@ -0,0 +1,229 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# ---------------------------------------------------------------------------- +"""Supports data from the Nobeyama Radio Polarimeters.""" + +import datetime as dt +import numpy as np +import os +import pandas as pds +import requests + +import GeospaceDataManagement as gdm + + +def acknowledgements(): + """Define the acknowledgements for NoRP data. + + Returns + ------- + ackn : str + Acknowledgements associated with the appropriate NoRP name and tag. + + """ + ackn = ''.join(['The Nobeyama Radio Polarimeters (NoRP) are operated by ', + 'Solar Science Observatory, a branch of National ', + 'Astronomical Observatory of Japan, and their observing ', + 'data are verified scientifically by the consortium for ', + 'NoRP scientific operations.', + '\nFor questions regarding the data please contact ', + 'solar_helpdesk@ml.nao.ac.jp']) + + return ackn + + +def references(name, tag): + """Define the references for NoRP data. + + Parameters + ---------- + name : str + Instrument name for the NoRP data. + tag : str + Instrument tag for the NoRP data. + + Returns + ------- + refs : str + Reference string associated with the appropriate F10.7 tag. + + """ + refs = {'rf': {'daily': "\n".join([ + ''.join(['Shimojo and Iwai "Over seven decades of solar microwave ', + 'data obtained with Toyokawa and Nobeyama Radio Polarimeters', + '", GDJ, 10, 114-129 (2023)']), + ''.join(['Nakajima et al. "The Radiometer and Polarimeters at 80, 35,', + ' and 17 GHz for Solar Observations at Nobeyama", PASJ, 37,', + ' 163 (1985)']), + ''.join(['Torii et al. "Full-Automatic Radiopolarimeters for Solar ', + 'Patrol at Microwave Frequencies", Proc. of the Res. Inst. ', + 'of Atmospherics, Nagoya Univ., 26, 129 (1979)']), + ''.join(['Shibasaki et al. "Solar Radio Data Acquisition and ', + 'Communication System (SORDACS) of Toyokawa Observatory", ', + 'Proc. of the Res. Inst. of Atmospherics, Nagoya Univ., 26, ', + '117 (1979)']), + 'Tanaka, "Toyokawa Observatory", Solar Physics, 1, 2, 295 (1967)', + ''.join(['Tsuchiya and Nagase "Atmospheric Absorption in Microwave ', + 'Solar Observation and Solar Flux Measurement at 17 Gc/s", ', + 'PASJ, 17, 86 (1965)']), + ''.join(['Tanaka and Kakinuma. "EQUIPMENT FOR THE OBSERVATION OF SOLAR', + ' RADIO EMISSION AT 9400, 3750, 2000 AND 1000 Mc/s", Proc. ', + 'of the Res. Inst. of Atmospherics, Nagoya Univ., 4, 60 ', + '(1957)']), + ''.join(['Tanaka et al. "EQUIPMENT FOR THE OBSERVATION OF SOLAR NOISE ', + 'AT 3,750 MC", Proc. of the Res. Inst. of Atmospherics, ', + 'Nagoya Univ., 1, 71 (1953)'])])}} + + return refs[name][tag] + + +def daily_rf_downloads(data_path, mock_download_dir=None, start=None, + stop=None): + """Download LASP 96-hour prediction data. + + Parameters + ---------- + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date (following the local + file prefix and date format) as if they were downloaded (default=None) + + Raises + ------ + IOError + If the data link has an unexpected format or an unknown mock download + directory is supplied. + + Note + ---- + Saves data in month-long files + + """ + # Initalize the output information + times = list() + data_dict = dict() + + # Set the file name + fname = 'TYKW-NoRP_dailyflux.txt' + + if mock_download_dir is None: + # Set the remote data variables + url = '/'.join(['https://solar.nro.nao.ac.jp/norp/data/daily', fname]) + + # Download the webpage + req = requests.get(url) + + # Test to see if the file was found on the server + if req.text.find('not found on this server') > 0: + gdm.logger.warning(''.join(['NoRP daily flux file not found on ', + 'server: ', url])) + raw_txt = None + else: + raw_txt = req.text + else: + # If a mock download directory was supplied, test to see it exists + if mock_download_dir is not None: + if not os.path.isdir(mock_download_dir): + raise IOError('file location is not a directory: {:}'.format( + mock_download_dir)) + + # Get the data from the mock download directory + url = os.path.join(mock_download_dir, fname) + if os.path.isfile(url): + with open(url, 'r') as fpin: + raw_txt = fpin.read() + else: + gdm.logger.warning(''.join(['NoRP daily flux file not found in', + 'the local directory: ', url, + ", data may have been saved to an ", + "unexpected filename"])) + raw_txt = None + + if raw_txt is not None: + # Split the text to get the header lines + file_lines = raw_txt.split('\n')[:2] + + # If needed, set or adjust the start and end times + line_cols = file_lines[0].split() + file_start = dt.datetime.strptime(line_cols[-3], '(%Y-%m-%d') + file_stop = dt.datetime.strptime(line_cols[-1], '%Y-%m-%d)') + + # Evaluate the file start time + if start is None or start < file_start: + start = file_start + elif start.day > 1: + # Set the start time to be the start of the month + start = dt.datetime(start.year, start.month, 1) + + # Evaluate the file stop time + if stop is None or stop < file_stop: + stop = file_stop + elif stop.day < 31: + # Set the stop time to be the end of the month + month_end = stop + dt.timedelta(days=1) + while month_end.month == stop.month: + stop = dt.datetime(month_end.year, month_end.month, + month_end.day) + month_end += dt.timedelta(days=1) + + # Set the data columns + data_cols = [col.replace(" ", "_") for col in file_lines[1].split(',')] + for col in data_cols[1:]: + data_dict[col] = list() + + # Split the text to get the file line for the desired period + start_txt = raw_txt.split(start.strftime('"%Y-%m-%d"'))[1] + stop_txt = ''.join([start.strftime('"%Y-%m-%d"'), start_txt]).split( + stop.strftime('"%Y-%m-%d"')) + file_lines = stop_txt[0].split('\n')[:-1] + if len(stop_txt) > 1: + file_lines.append(''.join([stop.strftime('"%Y-%m-%d"'), + stop_txt[1]]).split('\n')[0]) + + # Format the data for the desired time period + for line in file_lines: + # Split the line on comma + line_cols = line.split(',') + + if len(line_cols) != len(data_cols): + raise IOError(''.join(['unexpected line encountered in file ', + 'retrieved from ', url, ':\n', line])) + + # Format the time and values + times.append(dt.datetime.strptime(line_cols[0], '"%Y-%m-%d"')) + for i, col in enumerate(data_cols[1:]): + if line_cols[i + 1].lower().find('nan') == 0: + data_dict[col].append(np.nan) + else: + data_dict[col].append(np.float64(line_cols[i + 1])) + + # Re-cast the data as a pandas DataFrame + data = pds.DataFrame(data_dict, index=times) + + # Write out the files using a monthly cadance + file_base = '_'.join(['norp', 'rf', 'daily', '%Y-%m.txt']) + + while start < stop: + # Set the output file name + file_name = os.path.join(data_path, start.strftime(file_base)) + + # Downselect the output data + file_data = data[start:start + pds.DateOffset(months=1) + - dt.timedelta(microseconds=1)] + + # Save the output data to file + file_data.to_csv(file_name) + + # Cycle the time + start += pds.DateOffset(months=1) + + return diff --git a/GeospaceDataManagement/instruments/sw_methods/swpc.py b/GeospaceDataManagement/instruments/sw_methods/swpc.py new file mode 100644 index 0000000..24cd59c --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_methods/swpc.py @@ -0,0 +1,1014 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Provides routines that support SWPC space weather instruments.""" + +import datetime as dt +import ftplib +import numpy as np +import os +import pandas as pds +import sys + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.sw_methods import general + +# ---------------------------------------------------------------------------- +# Define the module variables + +ackn = ''.join(['Prepared by the U.S. Dept. of Commerce, NOAA, Space ', + 'Weather Prediction Center']) +forecast_warning = ''.join(['This routine can only download the current ', + 'forecast, not archived forecasts']) + + +# ---------------------------------------------------------------------------- +# Define the module functions + +def daily_dsd_download(name, today, data_path, mock_download_dir=None): + """Download the daily NOAA Daily Solar Data indices. + + Parameters + ---------- + name : str + Instrument name, expects one of 'f107', 'flare', 'ssn', or 'sbfield'. + today : dt.datetime + Datetime for current day. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied or the desired file + is missing. + + Note + ---- + Note that the download path for the complementary Instrument will use + the standard GeospaceDataManagement data paths + + """ + gdm.logger.info('This routine only downloads the latest 30 day file') + + # Get the file information + raw_txt = general.get_local_or_remote_text( + 'https://services.swpc.noaa.gov/text/', mock_download_dir, + 'daily-solar-indices.txt') + + if raw_txt is None: + gdm.logger.info("".join(["Data not downloaded for ", + "daily-solar-indices.txt, data may have ", + "been saved to an unexpected filename."])) + else: + # Get the file paths and output names + file_paths = {data_name: data_path if name == data_name else + general.get_instrument_data_path( + 'sw_{:s}'.format(data_name), tag='daily') + for data_name in ['f107', 'flare', 'ssn', 'sbfield']} + + # Try and obtain the file date; otherwise assume it was issued today + fdate = find_issue_date(raw_txt) + if fdate is None: + fdate = today + + outfiles = { + data_name: os.path.join(file_paths[data_name], '_'.join([ + data_name, 'daily', '{:s}.txt'.format( + fdate.strftime('%Y-%m-%d'))])) + for data_name in file_paths.keys()} + + # Check that the directories exist + for data_path in file_paths.values(): + gdm.utils.files.check_and_make_path(data_path) + + # Save the output + rewrite_daily_solar_data_file(fdate.year, outfiles, raw_txt) + + return + + +def old_indices_dsd_download(name, date_array, data_path, local_files, today, + mock_download_dir=None): + """Download the old NOAA Daily Solar Data indices. + + Parameters + ---------- + name : str + Instrument name, expects one of 'f107', 'flare', 'ssn', or 'sbfield'. + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + data_path : str + Path to data directory. + local_files : pds.Series + A Series containing the local filenames indexed by time. + today : dt.datetime + Datetime for current day + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied. + + Note + ---- + Note that the download path for the complementary Instrument will use + the standard data paths + + """ + # Get the file paths + file_paths = {data_name: data_path if name == data_name else + general.get_instrument_data_path('sw_{:s}'.format(data_name), + tag='prelim') + for data_name in ['f107', 'flare', 'ssn', 'sbfield']} + + # Check that the directories exist + for data_path in file_paths.values(): + gdm.utils.files.check_and_make_path(data_path) + + if mock_download_dir is None: + # Connect to the host, default port + ftp = ftplib.FTP('ftp.swpc.noaa.gov') + ftp.login() # User anonymous, passwd anonymous + ftp.cwd('/pub/indices/old_indices') + elif not os.path.isdir(mock_download_dir): + raise IOError('file location is not a directory: {:}'.format( + mock_download_dir)) + + bad_fname = list() + + # To avoid downloading multiple files, cycle dates based on file length + dl_date = date_array[0] + while dl_date <= date_array[-1]: + # The file name changes, depending on how recent the requested data is + qnum = (dl_date.month - 1) // 3 + 1 # Integer floor division + qmonth = (qnum - 1) * 3 + 1 + quar = 'Q{:d}_'.format(qnum) + fnames = ['{:04d}{:s}DSD.txt'.format(dl_date.year, ss) + for ss in ['_', quar]] + versions = ["01_v2", "{:02d}_v1".format(qmonth)] + vend = [dt.datetime(dl_date.year, 12, 31), + dt.datetime(dl_date.year, qmonth, 1) + + pds.DateOffset(months=3) - pds.DateOffset(days=1)] + downloaded = False + rewritten = False + + # Attempt the download(s) + for iname, fname in enumerate(fnames): + # Test to see if we already tried this filename + if fname in bad_fname: + continue + + local_fname = fname + saved_fname = os.path.join(data_path, local_fname) + outfiles = { + data_name: os.path.join(file_paths[data_name], '_'.join( + [data_name, 'prelim', '{:04d}'.format(dl_date.year), + '{:s}.txt'.format(versions[iname])])) + for data_name in file_paths.keys()} + + if os.path.isfile(outfiles[name]): + downloaded = True + + # Check the date to see if this should be rewritten + checkfile = os.path.split(outfiles[name])[-1] + has_file = local_files == checkfile + if np.any(has_file): + if has_file[has_file].index[-1] < vend[iname]: + # This file will be updated again, but only attempt to + # do so if enough time has passed from the last time it + # was downloaded + yesterday = today - pds.DateOffset(days=1) + if has_file[has_file].index[-1] < yesterday: + rewritten = True + else: + # The file does not exist, if it can be downloaded, it + # should be 'rewritten' + rewritten = True + + # Attempt to download if the file does not exist or if the + # file has been updated + if rewritten or not downloaded: + if mock_download_dir is None: + try: + sys.stdout.flush() + ftp.retrbinary('RETR ' + fname, + open(saved_fname, 'wb').write) + downloaded = True + gdm.logger.info(' '.join(('Downloaded file for ', + dl_date.strftime('%x')))) + + except ftplib.error_perm as exception: + # Could not fetch, so cannot rewrite + rewritten = False + + # Test for an error + if str(exception.args[0]).split(" ", 1)[0] != '550': + raise IOError(exception) + else: + # File isn't actually there, try the next name. The + # extra wrapping is for Windows, which can encounter + # permission errors when handling files. + attempt = 0 + while attempt < 100: + try: + os.remove(saved_fname) + attempt = 100 + except PermissionError: + attempt += 1 + + # Save this so we don't try again. Because there are + # two possible filenames for each time, it's ok if + # one isn't there. We just don't want to keep + # looking for it. + bad_fname.append(fname) + else: + # Set the saved filename + saved_fname = os.path.join(mock_download_dir, local_fname) + + if os.path.isfile(saved_fname): + downloaded = True + rewritten = True + else: + gdm.logger.info("".join([saved_fname, "is missing, ", + "data may have been saved ", + "to an unexpected filename."])) + rewritten = False + + # If the first file worked, don't try again + if downloaded: + break + + if not downloaded: + gdm.logger.info(' '.join(('File not available for', + dl_date.strftime('%x')))) + elif rewritten: + with open(saved_fname, 'r') as fprelim: + lines = fprelim.read() + + rewrite_daily_solar_data_file(dl_date.year, outfiles, lines) + if mock_download_dir is None: + # Only remove the file if it wasn't obtained from a local dir + os.remove(saved_fname) + + # Cycle to the next date + dl_date = vend[iname] + pds.DateOffset(days=1) + + # Close connection after downloading all dates + if mock_download_dir is None: + ftp.close() + + return + + +def rewrite_daily_solar_data_file(year, outfiles, lines): + """Rewrite the SWPC Daily Solar Data files. + + Parameters + ---------- + year : int + Year of data file (format changes based on date) + outfiles : dict + Output filenames for all relevant Instruments + lines : str + String containing all output data (result of 'read') + + """ + + # Get to the solar index data + if year > 2000: + raw_data = lines.split('#---------------------------------')[-1] + raw_data = raw_data.split('\n')[1:-1] + optical = True + else: + raw_data = lines.split('# ')[-1] + raw_data = raw_data.split('\n') + optical = False if raw_data[0].find('Not Available') or year == 1994 \ + else True + istart = 7 if year < 2000 else 1 + raw_data = raw_data[istart:-1] + + # Parse the data + solar_times, data_dict = parse_daily_solar_data(raw_data, year, optical) + + # Separate data by Instrument name + data_cols = {'f107': ['f107'], + 'flare': ['goes_bgd_flux', 'c_flare', 'm_flare', 'x_flare', + 'o1_flare', 'o2_flare', 'o3_flare', 'o1_flare', + 'o2_flare', 'o3_flare', 'c_flare', 'm_flare', + 'x_flare'], + 'ssn': ['ssn', 'ss_area', 'new_reg'], + 'sbfield': ['smf']} + + for data_name in data_cols.keys(): + name_dict = {dkey: data_dict[dkey] for dkey in data_dict.keys() + if dkey in data_cols[data_name]} + + # Collect into DataFrame + data = pds.DataFrame(name_dict, index=solar_times) + + # Write out as a file + data.to_csv(outfiles[data_name], header=True) + gdm.logger.info('Wrote: {:}'.format(outfiles[data_name])) + + return + + +def parse_daily_solar_data(data_lines, year, optical): + """Parse the data in the SWPC daily solar index file. + + Parameters + ---------- + data_lines : list + List of lines containing data + year : list + Year of file + optical : boolean + Flag denoting whether or not optical data is available + + Returns + ------- + dates : list + List of dates for each date/data pair in this block + values : dict + Dict of lists of values, where each key is the value name + + """ + + # Initialize the output + dates = list() + val_keys = ['f107', 'ssn', 'ss_area', 'new_reg', 'smf', 'goes_bgd_flux', + 'c_flare', 'm_flare', 'x_flare', 'o1_flare', 'o2_flare', + 'o3_flare'] + optical_keys = ['o1_flare', 'o2_flare', 'o3_flare'] + xray_keys = ['c_flare', 'm_flare', 'x_flare'] + values = {kk: list() for kk in val_keys} + + # Cycle through each line in this file + for line in data_lines: + # Split the line on whitespace + split_line = line.split() + + # Format the date + dfmt = "%Y %m %d" if year > 1996 else "%d %b %y" + dates.append(dt.datetime.strptime(" ".join(split_line[0:3]), dfmt)) + + # Format the data values + j = 0 + for i, kk in enumerate(val_keys): + if year == 1994 and kk == 'new_reg': + # New regions only in files after 1994 + val = -999 + elif np.any([year == 1994 and kk in xray_keys, + not optical and kk in optical_keys]): + # X-ray flares in files after 1994, optical flares come later + val = -1 + else: + val = split_line[j + 3] + j += 1 + + if kk != 'goes_bgd_flux': + if val == "*": + val = -999 if i < 5 else -1 + else: + val = int(val) + values[kk].append(val) + + return dates, values + + +def solar_geomag_predictions_download(name, date_array, data_path, + mock_download_dir=None): + """Download the 3-day solar-geomagnetic predictions from SWPC. + + Parameters + ---------- + name : str + Instrument name, expects one of 'kp', 'ap', 'stormprob', 'f107', + 'flare', or 'polarcap'. + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied or the desired file + is missing. + + Note + ---- + Note that the download path for the complementary Instrument will use + the standard data paths + + """ + gdm.logger.info(forecast_warning) + + # Get the file paths + file_paths = {data_name: data_path if name == data_name else + general.get_instrument_data_path( + 'sw_{:s}'.format(data_name), + tag='forecast' if data_name == 'f107' else 'prediction') + for data_name in ['kp', 'ap', 'stormprob', 'f107', 'flare', + 'polarcap']} + + # Check that the directories exist + for data_path in file_paths.values(): + gdm.utils.files.check_and_make_path(data_path) + + # Get the file information + raw_txt = general.get_local_or_remote_text( + 'https://services.swpc.noaa.gov/text/', mock_download_dir, + '3-day-solar-geomag-predictions.txt') + + if raw_txt is None: + gdm.logger.info("".join(["Data not downloaded for ", + "3-day-solar-geomag-predictions.txt, data ", + "may have been saved to an unexpected ", + "filename."])) + else: + # Parse text to get the date the prediction was generated + dl_date = find_issue_date(raw_txt, '%Y %b %d %H%M UTC') + + # Parse the data to get the prediction dates + date_strs = raw_txt.split(':Prediction_dates:')[-1].split('\n')[0] + pred_times = [ + dt.datetime.strptime(' '.join(date_str.split()), '%Y %b %d') + for date_str in date_strs.split(' ') if len(date_str) > 0] + + # Separate out the data by chunks + ap_raw = raw_txt.split(':Geomagnetic_A_indices:')[-1] + kp_raw = raw_txt.split(':Pred_Mid_k:')[-1] + storm_raw = raw_txt.split(':Prob_Mid:')[-1] + pc_raw = raw_txt.split(':Polar_cap:')[-1] + f107_raw = raw_txt.split(':10cm_flux:')[-1] + flare_raw = raw_txt.split(':Whole_Disk_Flare_Prob:')[-1] + + # Initalize the data for each data type + data_vals = {data_name: dict() for data_name in file_paths.keys()} + data_times = {data_name: pred_times for data_name in file_paths.keys()} + + # Process the ap data + for line in ap_raw.split('\n'): + if line.find(":") == 0: + break + elif line.find("A_") == 0: + split_line = line.split() + if split_line[0] == "A_Planetary": + dkey = "daily_Ap" + else: + dkey = split_line[0] + + data_vals['ap'][dkey] = [int(val) for val in split_line[1:]] + + # Process the Kp data + hr_strs = ['00-03UT', '03-06UT', '06-09UT', '09-12UT', '12-15UT', + '15-18UT', '18-21UT', '21-00UT'] + data_times['kp'] = pds.date_range(pred_times[0], periods=24, freq='3h') + + for line in kp_raw.split('\n'): + if line.find("Prob_Mid") >= 0: + break + elif line.find("UT") > 0: + split_line = line.split() + reg, hr = split_line[0].split('/') + dkey = '{:s}_lat_Kp'.format(reg) + + # Initalize the Kp data for this region + if dkey not in data_vals['kp'].keys(): + data_vals['kp'][dkey] = np.full(shape=(24,), + fill_value=np.nan) + + # Save the Kp data into the correct day and hour index + hr_index = hr_strs.index(hr) + data_vals['kp'][dkey][hr_index] = float(split_line[1]) + data_vals['kp'][dkey][hr_index + 8] = float(split_line[2]) + data_vals['kp'][dkey][hr_index + 16] = float(split_line[3]) + + # Process the storm probabilities + for line in storm_raw.split('\n'): + if line.find("Polar_cap") >= 0: + break + elif len(line) > 0: + split_line = line.split() + if split_line[0].find('/') > 0: + dkey = split_line[0].replace('/', '-Lat_') + data_vals['stormprob'][dkey] = [ + int(val) for val in split_line[1:]] + + # Process the polar cap prediction + data_vals['polarcap']['absorption_forecast'] = [ + str_val for str_val in pc_raw.split('\n')[1].split()] + data_times['polarcap'] = [ + ptimes for i, ptimes in enumerate(pred_times) + if i < len(data_vals['polarcap']['absorption_forecast'])] + + # Process the F10.7 data + data_vals['f107']['f107'] = [ + int(val) for val in f107_raw.split('\n')[1].split()] + + # Process the flare data + dkey_root = 'Whole_Disk_Flare_Prob' + for line in flare_raw.split('\n'): + if len(line) > 0 and line.find("#") < 0: + if line.find(":") == 0: + dkey_root = line.split(":")[1] + else: + split_line = line.split() + + if len(split_line) == 4: + dkey = "_".join([dkey_root, split_line[0]]) + data_vals['flare'][dkey] = [ + int(val) for val in split_line[1:]] + else: + data_vals['flare']['{:s}_Region'.format(dkey_root)] = [ + int(split_line[0]), -1, -1] + data_vals['flare']['{:s}_Class_C'.format(dkey_root)] = [ + int(split_line[1]), -1, -1] + data_vals['flare']['{:s}_Class_M'.format(dkey_root)] = [ + int(split_line[2]), -1, -1] + data_vals['flare']['{:s}_Class_X'.format(dkey_root)] = [ + int(split_line[3]), -1, -1] + data_vals['flare']['{:s}_Class_P'.format(dkey_root)] = [ + int(split_line[4]), -1, -1] + + # Save the data by type into files + for data_name in data_vals.keys(): + # Put the data values into a nicer DataFrame + data = pds.DataFrame(data_vals[data_name], + index=data_times[data_name]) + + # Save the data as a CSV file + data_tag = 'forecast' if data_name == 'f107' else 'prediction' + data_file = '_'.join([data_name, data_tag, + '{:s}.txt'.format(dl_date.strftime( + '%Y-%m-%d'))]) + data.to_csv(os.path.join(file_paths[data_name], data_file), + header=True) + + return + + +def geomag_forecast_download(name, date_array, data_path, + mock_download_dir=None): + """Download the 3-day geomagnetic Kp, ap, and storm data from SWPC. + + Parameters + ---------- + name : str + Instrument name, expects one of 'kp', 'ap', or 'stormprob'. + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied or the desired file + is missing. + + Note + ---- + Note that the download path for the complementary Instrument will use + the standard data paths + + """ + gdm.logger.info(forecast_warning) + + # Get the file paths + file_paths = {data_name: data_path if name == data_name else + general.get_instrument_data_path( + 'sw_{:s}'.format(data_name), tag='forecast') + for data_name in ['kp', 'ap', 'stormprob']} + + # Check that the directories exist + for data_path in file_paths.values(): + gdm.utils.files.check_and_make_path(data_path) + + # Get the file information + raw_txt = general.get_local_or_remote_text( + 'https://services.swpc.noaa.gov/text/', mock_download_dir, + '3-day-geomag-forecast.txt') + + if raw_txt is None: + gdm.logger.info("".join(["Data not downloaded for ", + "3-day-geomag-forecast.txt, data may have ", + "been saved to an unexpected filename."])) + else: + # Parse text to get the date the prediction was generated + dl_date = find_issue_date(raw_txt, '%Y %b %d %H%M UTC') + + # Separate out the data by chunks + ap_raw = raw_txt.split('NOAA Ap Index Forecast')[-1] + kp_raw = raw_txt.split('NOAA Kp index forecast ')[-1] + storm_raw = raw_txt.split('NOAA Geomagnetic Activity Probabilities')[-1] + + # Get dates of the forecasts + date_str = kp_raw[0:6] + ' ' + str(dl_date.year) + forecast_date = dt.datetime.strptime(date_str, '%d %b %Y') + + # Strings we will use to parse the downloaded text for Kp + lines = ['00-03UT', '03-06UT', '06-09UT', '09-12UT', '12-15UT', + '15-18UT', '18-21UT', '21-00UT'] + + # Storage for daily Kp forecasts. Get values for each day, then combine + # them together + kp_day1 = [] + kp_day2 = [] + kp_day3 = [] + for line in lines: + raw = kp_raw.split(line)[-1].split('\n')[0] + cols = raw.split() + kp_day1.append(float(cols[-3])) + kp_day2.append(float(cols[-2])) + kp_day3.append(float(cols[-1])) + + kp_times = pds.date_range(forecast_date, periods=24, freq='3h') + kp_day = [] + for dd in [kp_day1, kp_day2, kp_day3]: + kp_day.extend(dd) + + # Put Kp data into nicer DataFrame + data_frames = {'kp': pds.DataFrame(kp_day, index=kp_times, + columns=['Kp'])} + + # Parse the Ap data + ap_times = pds.date_range(dl_date - dt.timedelta(days=1), periods=5, + freq='1D') + obs_line = ap_raw.split('Observed Ap')[-1].split('\n')[0] + est_line = ap_raw.split('Estimated Ap')[-1].split('\n')[0] + pred_line = ap_raw.split('Predicted Ap')[-1].split('\n')[0] + ap_vals = [int(obs_line[-3:]), int(est_line[-3:])] + + for ap_val in pred_line.split()[-1].split('-'): + ap_vals.append(int(ap_val)) + + # Put the Ap data into a nicer DataFrame + data_frames['ap'] = pds.DataFrame(ap_vals, index=ap_times, + columns=['daily_Ap']) + + # Parse the storm probabilities + storm_dict = {} + for storm_line in storm_raw.split('\n')[1:5]: + storm_split = storm_line.split() + + # Build the storm data column name + dkey = '_'.join(storm_split[:-1]) + + # Assign the storm probabilities + storm_dict[dkey] = [int(sp) for sp in storm_split[-1].split('/')] + + # Put the storm probabilities into a nicer DataFrame + storm_times = pds.date_range(forecast_date, periods=3, freq='1D') + data_frames['stormprob'] = pds.DataFrame(storm_dict, index=storm_times) + + # Save the data files + for data_name in data_frames.keys(): + filename = '{:s}_forecast_{:s}.txt'.format( + data_name, dl_date.strftime('%Y-%m-%d')) + data_frames[data_name].to_csv(os.path.join( + file_paths[data_name], filename), header=True) + + return + + +def kp_ap_recent_download(name, date_array, data_path, mock_download_dir=None): + """Download recent Kp and ap data from SWPC. + + Parameters + ---------- + name : str + Instrument name, expects 'kp' or 'ap'. + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied or the desired file + is missing. + + Note + ---- + Note that the download path for the complementary Instrument will use + the standard data paths + + """ + gdm.logger.info(forecast_warning) + + # Get the file paths + file_paths = {data_name: data_path if name == data_name else + general.get_instrument_data_path( + 'sw_{:s}'.format(data_name), tag='recent') + for data_name in ['kp', 'ap']} + + # Check that the directories exist + for data_path in file_paths.values(): + gdm.utils.files.check_and_make_path(data_path) + + # Get the file information + raw_txt = general.get_local_or_remote_text( + 'https://services.swpc.noaa.gov/text/', mock_download_dir, + 'daily-geomagnetic-indices.txt') + + if raw_txt is None: + gdm.logger.info("".join(["Data not downloaded for ", + "daily-geomagnetic-indices.txt, data may ", + "have been saved to an unexpected ", + "filename."])) + else: + # Parse text to get the date the prediction was generated + dl_date = find_issue_date(raw_txt) + + # Data is the forecast value for the next three days + raw_data = raw_txt.split('# Date ')[-1] + + # Keep only the middle bits that matter + raw_data = raw_data.split('\n')[1:-1] + + # Hold times from the file + times = [] + + # Holds Kp and Ap values for each station + sub_kps = [[], [], []] + sub_aps = [[], [], []] + + # Iterate through file lines and parse out the info we want + for line in raw_data: + times.append(dt.datetime.strptime(line[0:10], '%Y %m %d')) + + # Pick out Kp values for each of the three columns. The columns + # used to all have integer values, but now some have floats. + kp_sub_lines = [line[17:33], line[40:56], line[63:]] + ap_sub_lines = [line[10:17], line[33:40], line[56:63]] + for i, sub_line in enumerate(kp_sub_lines): + # Process the Kp data, which has 3-hour values + split_sub = sub_line.split() + for ihr in np.arange(8): + if sub_line.find('.') < 0: + # These are integer values + sub_kps[i].append( + int(sub_line[(ihr * 2):((ihr + 1) * 2)])) + else: + # These are float values + sub_kps[i].append(np.float64(split_sub[ihr])) + + # Process the Ap data, which has daily values + sub_aps[i].append(np.int64(ap_sub_lines[i])) + + # Create times on 3 hour cadence + kp_times = pds.date_range(times[0], periods=(8 * 30), freq='3h') + + # Put both data sets into DataFrames + data = {'kp': pds.DataFrame({'mid_lat_Kp': sub_kps[0], + 'high_lat_Kp': sub_kps[1], + 'Kp': sub_kps[2]}, index=kp_times), + 'ap': pds.DataFrame({'mid_lat_Ap': sub_aps[0], + 'high_lat_Ap': sub_aps[1], + 'daily_Ap': sub_aps[2]}, index=times)} + + # Write out the data sets as files + for dkey in data.keys(): + data_file = '{:s}_recent_{:s}.txt'.format( + dkey, dl_date.strftime('%Y-%m-%d')) + + data[dkey].to_csv(os.path.join(file_paths[dkey], data_file), + header=True) + + return + + +def recent_ap_f107_download(name, date_array, data_path, + mock_download_dir=None): + """Download 45-day ap and F10.7 data from SWPC. + + Parameters + ---------- + name : str + Instrument name, expects 'f107' or 'ap'. + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied or the desored file + is missing. + + Note + ---- + Note that the download path for the complementary Instrument will use + the standard data paths + + """ + gdm.logger.info(forecast_warning) + + # Get the file paths + file_paths = {data_name: data_path if name == data_name else + general.get_instrument_data_path( + 'sw_{:s}'.format(data_name), tag='45day') + for data_name in ['f107', 'ap']} + + # Check that the directories exist + for data_path in file_paths.values(): + gdm.utils.files.check_and_make_path(data_path) + + # Get the file information + raw_txt = general.get_local_or_remote_text( + 'https://services.swpc.noaa.gov/text/', mock_download_dir, + '45-day-forecast.txt') + + if raw_txt is None: + gdm.logger.info("".join(["Data not downloaded for ", + "45-day-forecast.txt, data may have been", + " saved to an unexpected filename."])) + else: + # Parse text to get the date the prediction was generated + dl_date = find_issue_date(raw_txt, '%Y %b %d %H%M UTC') + + # Get to the forecast data + raw_data = raw_txt.split('45-DAY AP FORECAST')[-1] + + # Grab Ap part + raw_ap = raw_data.split('45-DAY F10.7 CM FLUX FORECAST')[0] + raw_ap = raw_ap.split('\n')[1:-1] + + # Get the F107 + raw_f107 = raw_data.split('45-DAY F10.7 CM FLUX FORECAST')[-1] + raw_f107 = raw_f107.split('\n')[1:10] + + # Parse the data + ap_times, ap = parse_45day_block(raw_ap) + f107_times, f107 = parse_45day_block(raw_f107) + + # Save the data in DataFrames + data = {'ap': pds.DataFrame(ap, index=ap_times, columns=['daily_Ap']), + 'f107': pds.DataFrame(f107, index=f107_times, columns=['f107'])} + + # Ensure there is a download date + if dl_date is None: + dl_date = ap_times[0] + + # Write out the data files + for data_name in data.keys(): + file_name = '{:s}_45day_{:s}.txt'.format( + data_name, dl_date.strftime('%Y-%m-%d')) + data[data_name].to_csv(os.path.join(file_paths[data_name], + file_name), header=True) + + return + + +def parse_45day_block(block_lines): + """Parse the data blocks used in the 45-day Ap and F10.7 Flux Forecast file. + + Parameters + ---------- + block_lines : list + List of lines containing data in this data block + + Returns + ------- + dates : list + List of dates for each date/data pair in this block + values : list + List of values for each date/data pair in this block + + """ + + # Initialize the output + dates = list() + values = list() + + # Cycle through each line in this block + for line in block_lines: + # Split the line on whitespace + split_line = line.split() + + # Format the dates + dates.extend([dt.datetime.strptime(tt, "%d%b%y") + for tt in split_line[::2]]) + + # Format the data values + values.extend([int(vv) for vv in split_line[1::2]]) + + return dates, values + + +def list_files(name, tag, inst_id, data_path, format_str=None): + """List local files for Kp or ap data obtained from SWPC. + + Parameters + ---------- + name : str + Instrument name. + tag : str + String specifying the database, expects 'def' (definitive) or 'now' + (nowcast) + inst_id : str + Specifies the instrument identification, not used. + data_path : str + Path to data directory. + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + files : gdm._files.Files + A class containing the verified available files + + """ + + if format_str is None: + format_str = '_'.join([name, tag, + '{year:04d}-{month:02d}-{day:02d}.txt']) + files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + + # Pad list of files data to include most recent file under tomorrow + if not files.empty: + pds_offset = dt.timedelta(days=1) + files.loc[files.index[-1] + pds_offset] = files.values[-1] + files.loc[files.index[-1] + pds_offset] = files.values[-1] + + return files + + +def find_issue_date(file_txt, date_fmt="%H%M UT %d %b %Y"): + r"""Find the issue date for a SWPC file. + + Parameters + ---------- + file_txt : str + String containing all text in a file. + date_fmt : str + Expected date format (default='%H%M UT %d %b %Y') + + Returns + ------- + dl_date : dt.datetime or NoneType + Datetime object with time that the file was issued or None if an + error is encountered + + Note + ---- + Assumes the file has a line formatted as: ':Issued: \n' + + """ + dl_date = None + + # Parse text to get the date the prediction was generated + if file_txt.find(':Issued:') >= 0: + date_str = file_txt.split(':Issued: ')[-1].split('\n')[0] + + try: + dl_date = dt.datetime.strptime(date_str, date_fmt) + except Exception as err: + gdm.logger.critical(''.join(['Unexpected issued date format ', + repr(date_str), ' did not match ', + date_fmt, '; failed with error: ', + repr(err)])) + else: + gdm.logger.critical('Unable to find issue line in file') + + return dl_date diff --git a/GeospaceDataManagement/instruments/sw_mgii.py b/GeospaceDataManagement/instruments/sw_mgii.py new file mode 100644 index 0000000..80f6576 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_mgii.py @@ -0,0 +1,306 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports the MgII core-to-wing ratio index. + +Properties +---------- +platform + 'sw' +name + 'mgii' +tag + - 'composite' Composite data set of MgII core-to-wing index + - 'sorce' SORCE SOLSTICE MgII core-to-wing index + +Examples +-------- +Download a month of the composite MgII data and load the second day of the +month. +:: + + stime = dt.datetime(1981, 2, 2) + mgii = gdm.Instrument('sw', 'mgii', tag='composite') + mgii.download(start=stime) + mgii.load(date=stime) + +""" + +import datetime as dt +import numpy as np +import pandas as pds + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.sw_methods import general +from GeospaceDataManagement.instruments.sw_methods import lisird + + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'mgii' +tags = {'composite': 'Composite data set of MgII core-to-wing index', + 'sorce': 'SORCE SOLSTICE MgII core-to-wing index'} + +# Dict keyed by inst_id that lists supported tags for each inst_id +inst_ids = {'': [tag for tag in tags.keys()]} + +# Dict keyed by inst_id that lists supported tags and a good day of test data +# generate todays date to support loading forecast data +now = dt.datetime.now(tz=dt.timezone.utc) +today = dt.datetime(now.year, now.month, now.day) +tomorrow = today + pds.DateOffset(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'composite': dt.datetime(1981, 11, 6), + 'sorce': dt.datetime(2005, 3, 6)}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the required Instrument attributes + self.acknowledgements = lisird.ackn + self.references = lisird.references(self.platform, self.name, self.tag, + self.inst_id) + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean the MGII data, empty function as this is not necessary.""" + + if self.tag == 'sorce': + gdm.logger.warning(''.join(["The SORCE MGII core-to-wing ratio has ", + "an associated uncertaintly ('unc') ", + "that should be considered when using ", + 'the data'])) + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load MGII core-to-wing ratio index files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames. + tag : str + Instrument tag. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data. + + See Also + -------- + gdm.instruments.methods.general.load_csv_data + + """ + # Get the desired file dates and file names from the daily indexed list + file_dates = list() + if tag == 'composite': + unique_files = list() + for fname in fnames: + file_dates.append(dt.datetime.strptime(fname[-10:], '%Y-%m-%d')) + if fname[0:-11] not in unique_files: + unique_files.append(fname[0:-11]) + fnames = unique_files + + # Load the CSV data files + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={"index_col": 0, "parse_dates": True}) + + # If there is a date range, downselect here + if len(file_dates) > 0: + idx, = np.where((data.index >= min(file_dates)) + & (data.index < max(file_dates) + dt.timedelta(days=1))) + data = data.iloc[idx, :] + + # Recast the data + data = data.to_xarray() + + # Initalize the metadata + notes = { + 'composite': ''.join([ + 'The Mg II Index is a proxy for solar chromospheric variability. ', + 'This composite data record is based on the work of Viereck et ', + 'al. (2004) Space Weather, vol 2, CiteID S10005 for measurements', + ' from 1978 through 2003. For this time range, the Upper ', + 'Atmosphere Research Satellite (UARS) Solar Ultraviolet Spectral ', + 'Irradiance Monitor (SUSIM), UARS Solar Stellar Irradiance ', + 'Comparison Experiment (SOLSTICE), ERS-2/Global Ozone Monitoring ', + 'Experiment (GOME) and five NOAA solar backscatter ultraviolet ', + 'data sets were used. Initially, the best data sets were ', + 'selected. Then the gaps in the record were filled with data ', + 'from various other Mg II data sets. Where no alternate data were', + ' available, a cubic spline function was used to bridge the ', + 'missing data. In some cases the data gaps were too long for ', + 'reasonable spline fits (more than 5 days), and for these gaps ', + 'the F10.7 cm flux data were scaled to fill the gaps.\nStarting ', + 'in 2003, the data from SORCE SOLSTICE is used exclusively. The ', + 'SOLSTICE spectra have been convolved with a 1.1 nm triangular ', + 'response function to improve the long-term agreement with other ', + 'measurements. All of the data sets have been normalized to a ', + 'commonscale to create a single long-term record.\nFor more ', + 'details please see https://lasp.colorado.edu/home/sorce/', + 'instruments/solstice/solstice-data-product-release-notes/.']), + 'sorce': ''.join([ + 'The SORCE Magnesium II core-to-wing index is produced from SORCE', + ' SOLSTICE instrument measurements using the definition in Snow ', + 'et al. [2005]. The spectral resolution of SORCE SOLSTICE (0.1 ', + 'nm) allows the emission cores of the Mg II doublet to be fully ', + 'resolved and modeled with Gaussian functions. To determine the ', + 'wing irradiances, the spectrum is convolved with a 1.1 nm ', + 'triangular bandpass and then measured at the four wavelengths ', + 'used by NOAA as described in Heath and Schlesinger [1986]. This', + ' method has several advantages; most importantly it extracts a ', + 'more precise measurement of solar activity [Snow et al., 2005]. ', + 'A simple linear correlation with the standard NOAA data product ', + 'can be used to scale this SORCE measurement to be compatible ', + 'with the long-term composite Mg II index maintained by NOAA.'])} + data['mg_index'].attrs.update( + {'units': '', 'name': 'MG II index', 'notes': notes[tag], + 'desc': 'MG II core-to-wing ratio index', 'fill_val': np.nan, + 'min_val': 0, 'max_val': np.inf}) + + if 'unc' in data: + data['unc'].attrs.update( + {'units': '', 'name': 'MG II Index Uncertainty', + 'notes': "".join([ + "As described in Snow et al. (2005), the formal uncertainty", + " in each SOLSTICE MgII index measurement is about 0.65%. ", + "This is derived from the statistical uncertainty of the ", + "underlying spectral measurements and the way they are ", + "combined to produce the index."]), + 'desc': 'MG II core-to-wing ratio index uncertainty', + 'fill_val': np.nan, 'min_val': 0, 'max_val': np.inf}) + + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local MGII core-to-wing ratio index files. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + out_files : gdm._files.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # If the format string is not supplied, build the default string + if format_str is None: + format_str = "".join([ + "mgii_", tag, "_{year:04d}-{month:02d}", + '.txt' if tag == 'composite' else '-{day:02d}.txt']) + + # Get the files using the default function + out_files = gdm.Files.from_os(data_path=data_path, format_str=format_str) + + if tag == 'composite': + # Files are by month, going to add date to monthly filename for + # each day of the month. The load routine will load a month of + # data and use the appended date to select out appropriate data. + if not out_files.empty: + out_files.loc[out_files.index[-1] + pds.DateOffset(months=1) + - pds.DateOffset(days=1)] = out_files.iloc[-1] + out_files = out_files.asfreq('D', 'pad') + out_files = out_files + '_' + out_files.index.strftime( + '%Y-%m-%d') + + return out_files + + +def download(date_array, tag, inst_id, data_path, mock_download_dir=None): + """Download MGII core-to-wing index data from the appropriate repository. + + Parameters + ---------- + date_array : array-like + Sequence of dates for which files will be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the ID for the Instrument (not used). + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded. (default=None) + + Raises + ------ + IOError + If a problem is encountered connecting to the gateway or retrieving + data from the remote or local repository. + + """ + + # Set the download input options + local_file_prefix = "mgii_{:s}_".format(tag) + lisird_data_name = "{:s}_mg_index".format(tag) + + if tag == "composite": + local_file_prefix = "mgii_composite_" + local_date_fmt = "%Y-%m" + freq = pds.DateOffset(months=1, seconds=-1) + + # Adjust the date array if monthly downloads are desired + if date_array.freq != 'MS': + date_array = gdm.utils.time.create_date_range( + dt.datetime(date_array[0].year, date_array[0].month, 1), + date_array[-1], freq='MS') + + elif tag == "sorce": + local_date_fmt = "%Y-%m-%d" + freq = dt.timedelta(seconds=86399) + + # Download the desired data + lisird.download(date_array, data_path, local_file_prefix, local_date_fmt, + lisird_data_name, freq, mock_download_dir=mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_polarcap.py b/GeospaceDataManagement/instruments/sw_polarcap.py new file mode 100644 index 0000000..7ccad56 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_polarcap.py @@ -0,0 +1,185 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports polar cap indexes. + +Properties +---------- +platform + 'sw' +name + 'polarcap' +tag + - 'prediction' Predictions from SWPC for the next 3 days +inst_id + - '' + +Note +---- +Downloads data from SWPC. These files also contain other data indices, and so +the additional data files will be saved to the appropriate data directories to +avoid multiple downloads. + +The forecast/prediction data is stored by generation date, where each file +contains the forecast for the next three days. Forecast data downloads are only +supported for the current day. When loading forecast data, the date specified +with the load command is the date the forecast was generated. The data loaded +will span three days. To always ensure you are loading the most recent data, +load the data with tomorrow's date. + +Examples +-------- +:: + + pc = gdm.Instrument('sw', 'polarcap', tag='prediction') + pc.download() + pc.load(date=pc.tomorrow()) + + +Warnings +-------- +The 'prediction' tag loads polar cap absoprtion predictions for a specific +period of time. Loading multiple files, loading multiple days, the data padding +feature, and multi_file_day feature available from the pyast.Instrument object +is not appropriate for these tags data. + +""" + +import datetime as dt +import functools + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments.methods import general +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'polarcap' +tags = {'prediction': 'SWPC Predictions for the next three days'} +inst_ids = {'': list(tags.keys())} + +# Generate todays date to support loading forecast data +now = dt.datetime.now(tz=dt.timezone.utc) +today = dt.datetime(now.year, now.month, now.day) +tomorrow = today + dt.timedelta(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates +_test_dates = {'': {'prediction': tomorrow}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = sw_methods.swpc.ackn + self.references = "".join(["Check SWPC for appropriate references: ", + "https://www.swpc.noaa.gov/phenomena"]) + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the polar cap indexes, not required (empty function).""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + +list_files = functools.partial(sw_methods.swpc.list_files, name) + + +def load(fnames, tag='', inst_id=''): + """Load storm probability files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + tag : str + Instrument tag (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + # Load the data + data = general.load_csv_data( + fnames, {'index_col': 0, 'parse_dates': True}).to_xarray() + + # Initialize the metadata + for dkey in data.data_vars.keys(): + data[dkey].attrs.update({'units': '', 'name': dkey, + 'desc': dkey.replace('_', ' '), + 'min_val': 'green', 'max_val': 'red', + 'fill_val': ''}) + + return data + + +def download(date_array, tag, inst_id, data_path, mock_download_dir=None): + """Download the polar cap indices from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the instrument identification, not used. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded. (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied. + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + Warnings + -------- + Only able to download current recent data, not archived forecasts. + + """ + + if tag == 'prediction': + sw_methods.swpc.solar_geomag_predictions_download( + name, date_array, data_path, mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_sbfield.py b/GeospaceDataManagement/instruments/sw_sbfield.py new file mode 100644 index 0000000..b396c25 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_sbfield.py @@ -0,0 +1,280 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports solar magnetic field values. + +Properties +---------- +platform + 'sw' +name + 'sbfield' +tag + - 'prelim' Preliminary SWPC daily solar indices + - 'daily' Daily SWPC solar indices (contains last 30 days) + +Examples +-------- +Download and load some preliminary solar magnetic field data. +:: + + smf = gdm.Instrument('sw', 'sbfield', tag='prelim') + smf.download(start=dt.datetime(2001, 1, 1)) + smf.load(date=dt.datetime(2001, 1, 1)) + +""" + +import datetime as dt +import numpy as np +import os +import pandas as pds + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'sbfield' +tags = {'prelim': 'Preliminary SWPC daily solar indices', + 'daily': 'Daily SWPC solar indices (contains last 30 days)'} + +# Dict keyed by inst_id that lists supported tags for each inst_id +inst_ids = {'': [tag for tag in tags.keys()]} + +# Dict keyed by inst_id that lists supported tags and a good day of test data +# generate todays date to support loading forecast data +now = dt.datetime.now(tz=dt.timezone.utc) +today = dt.datetime(now.year, now.month, now.day) +tomorrow = today + pds.DateOffset(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'prelim': dt.datetime(2009, 1, 1), + 'daily': tomorrow}} + +# Other tags assumed to be True +_test_download_ci = {'': {'prelim': False}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the required Instrument attributes + self.acknowledgements = sw_methods.swpc.ackn + self.references = "".join(["Scherrer, P.H., Wilcox, J.M., Svalgaard, L. ", + "et al. The mean magnetic field of the Sun: ", + "Observations at Stanford. Sol Phys 54, 353–361", + " (1977). https://doi.org/10.1007/BF00159925"]) + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean the data, empty function as this is not necessary.""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load solar magnetic field files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames. + tag : str + Instrument tag. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data. + + See Also + -------- + gdm.instruments.methods.general.load_csv_data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + # Get the desired file dates and file names from the daily indexed list + file_dates = list() + if tag == 'prelim': + unique_files = list() + for fname in fnames: + file_dates.append(dt.datetime.strptime(fname[-10:], '%Y-%m-%d')) + if fname[0:-11] not in unique_files: + unique_files.append(fname[0:-11]) + fnames = unique_files + + # Load the CSV data files + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={"index_col": 0, "parse_dates": True}) + + # If there is a date range, downselect here + if len(file_dates) > 0: + idx, = np.where((data.index >= min(file_dates)) + & (data.index < max(file_dates) + dt.timedelta(days=1))) + data = data.iloc[idx, :] + + # Convert the data type + data = data.to_xarray() + + # Initialize the metadata + data['smf'].attrs.update({'units': 'G', 'name': 'Solar Mean Field', + 'notes': '', 'desc': 'Standford Solar Mean Field', + 'fill_val': -999, 'min_val': 0, + 'max_val': np.inf}) + + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local solar magnetic field data files. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + out_files : gdm._files.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + + if tag == 'prelim': + # Files are by year (and quarter) + if format_str is None: + format_str = ''.join(['sbfield_prelim_{year:04d}_{month:02d}', + '_v{version:01d}.txt']) + out_files = gdm.Files.from_os(data_path=data_path, + format_str=format_str) + + if not out_files.empty: + # Set each file's valid length at a 1-day resolution + orig_files = out_files.sort_index().copy() + new_files = list() + + for orig in orig_files.items(): + # Version determines each file's valid length + version = int(orig[1].split("_v")[1][0]) + doff = pds.DateOffset(years=1) if version == 2 \ + else pds.DateOffset(months=3) + istart = orig[0] + iend = istart + doff - pds.DateOffset(days=1) + + # Ensure the end time does not extend past the number of + # possible days included based on the file's download time + fname = os.path.join(data_path, orig[1]) + dend = dt.datetime.utcfromtimestamp(os.path.getctime(fname)) + dend = dend - pds.DateOffset(days=1) + if dend < iend: + iend = dend + + # Pad the original file index + out_files.loc[iend] = orig[1] + out_files = out_files.sort_index() + + # Save the files at a daily cadence over the desired period + new_files.append(out_files.loc[istart: + iend].asfreq('D', 'pad')) + # Add the newly indexed files to the file output + out_files = pds.concat(new_files, sort=True) + out_files = out_files.dropna() + out_files = out_files.sort_index() + out_files = out_files + '_' + out_files.index.strftime('%Y-%m-%d') + + elif tag == 'daily': + out_files = sw_methods.swpc.list_files(name, tag, inst_id, data_path, + format_str=format_str) + + return out_files + + +def download(date_array, tag, inst_id, data_path, update_files=False, + mock_download_dir=None): + """Download solar magnetic field data from the appropriate repository. + + Parameters + ---------- + date_array : array-like + Sequence of dates for which files will be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the satellite ID for a constellation. + data_path : str + Path to data directory. + update_files : bool + Re-download data for files that already exist if True (default=False) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded. (default=None) + + Raises + ------ + IOError + If a problem is encountered connecting to the gateway or retrieving + data from the remote or local repository. + + Warnings + -------- + Only able to download current forecast data, not archived forecasts. + + """ + if tag == 'prelim': + # Get the local files, to ensure that the version 1 files are + # downloaded again if more data has been added + local_files = list_files(tag, inst_id, data_path) + + sw_methods.swpc.old_indices_dsd_download(name, date_array, data_path, + local_files, today, + mock_download_dir) + + elif tag == 'daily': + sw_methods.swpc.daily_dsd_download(name, today, data_path, + mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_ssn.py b/GeospaceDataManagement/instruments/sw_ssn.py new file mode 100644 index 0000000..7d74a10 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_ssn.py @@ -0,0 +1,321 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports Sunspot Number (SSN) and related indices. + +Properties +---------- +platform + 'sw' +name + 'ssn' +tag + - 'prelim' Preliminary SWPC daily solar indices + - 'daily' Daily SWPC solar indices (contains last 30 days) + - 'now' Nowcast and definitive international sunspot number data from GFZ + +Examples +-------- +Download and load some preliminary SSN data. +:: + + ssn = gdm.Instrument('sw', 'ssn', tag='prelim') + ssn.download(start=dt.datetime(2001, 1, 1)) + ssn.load(date=dt.datetime(2001, 1, 1)) + +""" + +import datetime as dt +import numpy as np +import os +import pandas as pds + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'ssn' +tags = {'prelim': 'Preliminary SWPC daily solar indices', + 'daily': 'Daily SWPC solar indices (contains last 30 days)', + 'now': + 'Nowcast and definitive international sunspot number data from GFZ'} + +# Dict keyed by inst_id that lists supported tags for each inst_id +inst_ids = {'': [tag for tag in tags.keys()]} + +# Dict keyed by inst_id that lists supported tags and a good day of test data +# generate todays date to support loading forecast data +now = dt.datetime.now(tz=dt.timezone.utc) +today = dt.datetime(now.year, now.month, now.day) +tomorrow = today + pds.DateOffset(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +_test_dates = {'': {'prelim': dt.datetime(2009, 1, 1), + 'now': dt.datetime(2009, 1, 1), + 'daily': tomorrow}} + +# Other tags assumed to be True +_test_download_ci = {'': {'prelim': False}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + # Set the required Instrument attributes + if self.tag == 'now': + self.acknowledgements = sw_methods.gfz.ackn + else: + self.acknowledgements = sw_methods.swpc.ackn + self.references = "".join(["E.g., Arlt, R., Vaquero, J.M. Historical ", + "sunspot records. Living Rev Sol Phys 17, 1 ", + '(2020). doi:10.1007/s41116-020-0023-y']) + gdm.logger.info(self.acknowledgements) + + return + + +def clean(self): + """Clean the data, empty function as this is not necessary.""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + + +def load(fnames, tag='', inst_id=''): + """Load SSN files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames. + tag : str + Instrument tag. (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data. + + See Also + -------- + gdm.instruments.methods.general.load_csv_data + + """ + + # Get the desired file dates and file names from the daily indexed list + file_dates = list() + if tag in ['prelim', 'now']: + unique_files = list() + for fname in fnames: + file_dates.append(dt.datetime.strptime(fname[-10:], '%Y-%m-%d')) + if fname[0:-11] not in unique_files: + unique_files.append(fname[0:-11]) + fnames = unique_files + + # Load the CSV data files + data = gdm.instruments.methods.general.load_csv_data( + fnames, read_csv_kwargs={"index_col": 0, "parse_dates": True}) + + # Adjust variable names to be consistent across data sets + if tag == 'now': + data = data.rename(columns={'SN': 'ssn'}) + + # If there is a date range, downselect here + if len(file_dates) > 0: + idx, = np.where((data.index >= min(file_dates)) + & (data.index < max(file_dates) + dt.timedelta(days=1))) + data = data.iloc[idx, :] + + # Recast the data + data = data.to_xarray() + + # Initialize the metadata + data['ssn'].attrs.update({'units': '', 'name': 'Sunspot Number', + 'notes': '', 'desc': 'SESC Sunspot Number', + 'fill_val': -999, 'min_val': 0, + 'max_val': np.inf}) + if 'ss_area' in data: + data['ss_area'].attrs.update({ + 'units': '10$^-6$ Solar Hemisphere', 'name': 'Sunspot Area', + 'notes': '', 'desc': ''.join(['Sunspot Area in Millionths of the ', + 'Visible Hemisphere']), + 'fill_val': -999, 'min_val': 0, 'max_val': 1.0e6}) + if 'new_reg' in data: + data['new_reg'].attrs.update({'units': '', 'name': 'New Regions', + 'notes': '', + 'desc': 'New active solar regions', + 'fill_val': -999, 'min_val': 0, + 'max_val': np.inf}) + + return data + + +def list_files(tag='', inst_id='', data_path='', format_str=None): + """List local solar magnetic field data files. + + Parameters + ---------- + tag : str + Instrument tag, accepts any value from `tags`. (default='') + inst_id : str + Instrument ID, not used. (default='') + data_path : str + Path to data directory. (default='') + format_str : str or NoneType + User specified file format. If None is specified, the default + formats associated with the supplied tags are used. (default=None) + + Returns + ------- + out_files : gdm._files.Files + A class containing the verified available files + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + """ + if tag == 'prelim': + # Files are by year (and quarter) + if format_str is None: + format_str = ''.join(['ssn_prelim_{year:04d}_{month:02d}', + '_v{version:01d}.txt']) + out_files = gdm.Files.from_os(data_path=data_path, + format_str=format_str) + + if not out_files.empty: + # Set each file's valid length at a 1-day resolution + orig_files = out_files.sort_index().copy() + new_files = list() + + for orig in orig_files.items(): + # Version determines each file's valid length + version = int(orig[1].split("_v")[1][0]) + doff = pds.DateOffset(years=1) if version == 2 \ + else pds.DateOffset(months=3) + istart = orig[0] + iend = istart + doff - pds.DateOffset(days=1) + + # Ensure the end time does not extend past the number of + # possible days included based on the file's download time + fname = os.path.join(data_path, orig[1]) + dend = dt.datetime.utcfromtimestamp(os.path.getctime(fname)) + dend = dend - pds.DateOffset(days=1) + if dend < iend: + iend = dend + + # Pad the original file index + out_files.loc[iend] = orig[1] + out_files = out_files.sort_index() + + # Save the files at a daily cadence over the desired period + new_files.append(out_files.loc[istart: + iend].asfreq('D', 'pad')) + # Add the newly indexed files to the file output + out_files = pds.concat(new_files, sort=True) + out_files = out_files.dropna() + out_files = out_files.sort_index() + out_files = out_files + '_' + out_files.index.strftime('%Y-%m-%d') + + elif tag == 'now': + if format_str is None: + format_str = 'SN_{year:04d}-{month:02d}.txt' + + out_files = gdm.Files.from_os(data_path=data_path, + format_str=format_str) + if not out_files.empty: + freq = pds.DateOffset(months=1, days=-1) + out_files.loc[out_files.index[-1] + freq] = out_files.iloc[-1] + out_files = out_files.asfreq('D', 'pad') + out_files = out_files + '_' + out_files.index.strftime('%Y-%m-%d') + + elif tag == 'daily': + out_files = sw_methods.swpc.list_files(name, tag, inst_id, data_path, + format_str=format_str) + + return out_files + + +def download(date_array, tag, inst_id, data_path, update_files=False, + mock_download_dir=None): + """Download solar magnetic field data from the appropriate repository. + + Parameters + ---------- + date_array : array-like + Sequence of dates for which files will be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the satellite ID for a constellation. + data_path : str + Path to data directory. + update_files : bool + Re-download data for files that already exist if True. (default=False) + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded. (default=None) + + Raises + ------ + IOError + If a problem is encountered connecting to the gateway or retrieving + data from the remote or local repository. + + Warnings + -------- + Only able to download current forecast data, not archived forecasts. + + """ + if tag == 'prelim': + # Get the local files, to ensure that the version 1 files are + # downloaded again if more data has been added + local_files = list_files(tag, inst_id, data_path) + + sw_methods.swpc.old_indices_dsd_download(name, date_array, data_path, + local_files, today, + mock_download_dir) + + elif tag == 'daily': + sw_methods.swpc.daily_dsd_download(name, today, data_path, + mock_download_dir) + + elif tag == 'now': + # Set the download input options + gfz_data_name = 'SN' + local_file_prefix = '{:s}_'.format(gfz_data_name) + + # Call the download routine + sw_methods.gfz.json_downloads(date_array, data_path, local_file_prefix, + "%Y-%m", gfz_data_name, + pds.DateOffset(months=1, seconds=-1), + update_files=update_files, + mock_download_dir=mock_download_dir) + + return diff --git a/GeospaceDataManagement/instruments/sw_stormprob.py b/GeospaceDataManagement/instruments/sw_stormprob.py new file mode 100644 index 0000000..8ffaf24 --- /dev/null +++ b/GeospaceDataManagement/instruments/sw_stormprob.py @@ -0,0 +1,195 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Supports storm probabilities. + +Properties +---------- +platform + 'sw' +name + 'stormprob' +tag + - 'prediction' Predictions from SWPC for the next 3 days + - 'forecast' Grab forecast data from SWPC (next 3 days) +inst_id + - '' + +Note +---- +Downloads data from SWPC. These files also contain other data indices, and so +the additional data files will be saved to the appropriate data directories to +avoid multiple downloads. + +The forecast data is stored by generation date, where each file contains the +forecast for the next three days. Forecast data downloads are only supported +for the current day. When loading forecast data, the date specified with the +load command is the date the forecast was generated. The data loaded will span +three days. To always ensure you are loading the most recent data, load +the data with tomorrow's date. + +Examples +-------- +:: + + storm = gdm.Instrument('sw', 'stormprob', tag='forecast') + storm.download() + storm.load(date=storm.tomorrow()) + + +Warnings +-------- +The 'forecast' tag loads storm probabilities for a specific period of time. +Loading multiple files, loading multiple days, the data padding feature, and +multi_file_day feature available from the pyast.Instrument object is not +appropriate for these tags data. + +""" + +import datetime as dt +import functools + +import GeospaceDataManagement as gdm +from GeospaceDataManagement.instruments import methods +from GeospaceDataManagement.instruments import sw_methods + +# ---------------------------------------------------------------------------- +# Instrument attributes + +platform = 'sw' +name = 'stormprob' +tags = {'forecast': 'SWPC Forecast data next (3 days)', + 'prediction': 'SWPC Predictions for the next three days'} +inst_ids = {'': list(tags.keys())} + +# Generate todays date to support loading forecast data +now = dt.datetime.now(tz=dt.timezone.utc) +today = dt.datetime(now.year, now.month, now.day) +tomorrow = today + dt.timedelta(days=1) + +# ---------------------------------------------------------------------------- +# Instrument test attributes + +# Set test dates +_test_dates = {'': {'forecast': tomorrow, 'prediction': tomorrow}} + +# ---------------------------------------------------------------------------- +# Instrument methods + +preprocess = sw_methods.general.preprocess_fill + + +def init(self): + """Initialize the Instrument object with instrument specific values.""" + + self.acknowledgements = sw_methods.swpc.ackn + self.references = "".join(["https://www.swpc.noaa.gov/sites/default/files", + "/images/NOAAscales.pdf"]) + gdm.logger.info(self.acknowledgements) + return + + +def clean(self): + """Clean the Kp, not required for this index (empty function).""" + + return + + +# ---------------------------------------------------------------------------- +# Instrument functions + +list_files = functools.partial(sw_methods.swpc.list_files, name) + + +def load(fnames, tag='', inst_id=''): + """Load storm probability files. + + Parameters + ---------- + fnames : pandas.Series + Series of filenames + tag : str + Instrument tag (default='') + inst_id : str + Instrument ID, not used. (default='') + + Returns + ------- + data : xr.Dataset + Object containing satellite data + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + Warnings + -------- + tag '' has been deprecated, will be removed in version 0.2.0+ + + """ + # Load the data + data = methods.general.load_csv_data( + fnames, {'index_col': 0, 'parse_dates': True}).to_xarray() + fill_val = -1 + + # Initialize the metadata + for dkey in data.data_vars.keys(): + data[dkey].attrs.update({'units': '', 'name': dkey, + 'desc': dkey.replace('_', ' '), + 'min_val': 0, 'max_val': 100, + 'fill_val': fill_val}) + + return data + + +def download(date_array, tag, inst_id, data_path, mock_download_dir=None): + """Download the storm probabilities from the appropriate repository. + + Parameters + ---------- + date_array : array-like or pandas.DatetimeIndex + Array-like or index of datetimes to be downloaded. + tag : str + Denotes type of file to load. + inst_id : str + Specifies the instrument identification, not used. + data_path : str + Path to data directory. + mock_download_dir : str or NoneType + Local directory with downloaded files or None. If not None, will + process any files with the correct name and date as if they were + downloaded. (default=None) + + Raises + ------ + IOError + If an unknown mock download directory is supplied. + + Note + ---- + Called by GeospaceDataManagement. Not intended for direct use by user. + + Warnings + -------- + Only able to download current recent data, not archived forecasts. + + """ + + if tag == 'forecast': + sw_methods.swpc.geomag_forecast_download(name, date_array, data_path, + mock_download_dir) + elif tag == 'prediction': + sw_methods.swpc.solar_geomag_predictions_download( + name, date_array, data_path, mock_download_dir) + + return diff --git a/GeospaceDataManagement/tests/classes/cls_instrument_access.py b/GeospaceDataManagement/tests/classes/cls_instrument_access.py index 0f0c4d9..3a74e94 100644 --- a/GeospaceDataManagement/tests/classes/cls_instrument_access.py +++ b/GeospaceDataManagement/tests/classes/cls_instrument_access.py @@ -834,9 +834,8 @@ def test_setting_data_by_name_with_meta(self): 'units': 'hours', 'long_name': 'double trouble'} assert np.all(self.testInst['doubleMLT'] == 2. * self.testInst['mlt']) - # TODO META - # assert self.testInst.meta['doubleMLT'].units == 'hours' - # assert self.testInst.meta['doubleMLT'].long_name == 'double trouble' + assert self.testInst['doubleMLT'].attrs['units'] == 'hours' + assert self.testInst['doubleMLT'].attrs['long_name'] == 'double trouble' return @pytest.mark.parametrize("changed,fixed", @@ -948,9 +947,8 @@ def test_basic_variable_renaming(self, lowercase, mapper): # Check for new name in the data and metadata inst_var = values[key].lower() if lowercase else values[key] assert inst_var in self.testInst.variables - # TODO assert values[key] in self.testInst.meta.keys() + assert len(self.testInst[inst_var].attrs) > 0 # Ensure old name not present assert key not in self.testInst.variables - # TODO assert key not in self.testInst.meta.keys() return diff --git a/GeospaceDataManagement/tests/classes/cls_instrument_library.py b/GeospaceDataManagement/tests/classes/cls_instrument_library.py index b714999..ef7bd62 100644 --- a/GeospaceDataManagement/tests/classes/cls_instrument_library.py +++ b/GeospaceDataManagement/tests/classes/cls_instrument_library.py @@ -218,7 +218,8 @@ def teardown_method(self): return - def initialize_test_package(self, inst_loc, user_info=None): + def initialize_test_package(self, inst_loc, inst_subset='test', + user_info=None): """Generate custom instrument lists for each category of tests. Parameters @@ -226,6 +227,9 @@ def initialize_test_package(self, inst_loc, user_info=None): inst_loc : python subpackage The location of the instrument subpackage to test, e.g., `gdm.instruments` + inst_subset : str + Name within hidden attribute that contains the list of desired + instruments (default='test') user_info : dict or NoneType Nested dictionary with user and password info for instrument module name. If None, no user or password is assumed. (default=None) @@ -247,7 +251,8 @@ def initialize_test_package(self, inst_loc, user_info=None): # Find all instruments for testing from user-specified location. instruments = generate_instrument_list(inst_loc=inst_loc, - user_info=user_info) + user_info=user_info, + subset=inst_subset) # Find all methods in the standard test class. method_list = [func for func in dir(self) @@ -473,13 +478,13 @@ def test_load_empty(self, inst_dict): # Check the empty status assert self.test_inst.empty, "Data was loaded for a far-future time" - assert self.test_inst.data.dims == xr.Dataset().dims, "Dims not empty" + assert self.test_inst.data.sizes == xr.Dataset().sizes, "Dims not empty" assert (self.test_inst.data.data_vars == xr.Dataset().data_vars), "Data variables not empty" return - # TODO(#1172): remove mark.new_tests at v3.3.0 + # TODO(#2): remove mark.new_tests at v0.1.0 @pytest.mark.second @pytest.mark.load_options @pytest.mark.new_tests diff --git a/GeospaceDataManagement/tests/test_data/20090101_ace_epam_5m.txt b/GeospaceDataManagement/tests/test_data/20090101_ace_epam_5m.txt new file mode 100644 index 0000000..081b9cd --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/20090101_ace_epam_5m.txt @@ -0,0 +1,306 @@ +:Data_list: 20090101_ace_epam_5m.txt +:Created: 2009 Jan 02 0011 UT +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# Units: Differential Flux particles/cm2-s-ster-MeV +# Units: Anisotropy Index 0.0 - 2.0 +# Status(S): 0 = nominal, 4,6,7,8 = bad data, unable to process, 9 = no data +# Missing data values: -1.00e+05, index = -1.00 +# Source: ACE Satellite - Electron, Proton, and Alpha Monitor +# +# +# 5-minute averaged Real-time Differential Electron and Proton Flux +# +# Modified Seconds ---------------------------- Differential Flux --------------------------- +# UT Date Time Julian of the ----- Electron ----- ------------------- Protons keV ------------------- Anis. +# YR MO DA HHMM Day Day S 38-53 175-315 S 47-68 115-195 310-580 761-1220 1060-1900 Index +#------------------------------------------------------------------------------------------------------------------- +2009 01 01 0000 54832 0 0 8.93e+02 2.55e+01 0 1.60e+03 2.00e+01 2.01e+00 8.38e-01 2.03e-01 0.08 +2009 01 01 0005 54832 300 0 6.98e+02 2.20e+01 0 1.53e+03 1.88e+01 2.16e+00 6.03e-01 9.48e-02 0.19 +2009 01 01 0010 54832 600 0 7.03e+02 2.60e+01 0 1.58e+03 2.08e+01 2.43e+00 6.67e-01 1.16e-01 0.46 +2009 01 01 0015 54832 900 0 7.23e+02 2.53e+01 0 7.95e+03 4.30e+01 2.40e+00 6.10e-01 2.12e-01 0.60 +2009 01 01 0020 54832 1200 0 8.58e+02 1.97e+01 0 2.42e+03 4.03e+01 2.48e+00 3.43e-01 1.16e-01 0.26 +2009 01 01 0025 54832 1500 0 7.04e+02 3.35e+01 0 1.64e+03 2.00e+01 2.41e+00 5.53e-01 1.74e-01 0.90 +2009 01 01 0030 54832 1800 0 6.78e+02 3.03e+01 0 1.53e+03 2.05e+01 3.07e+00 5.53e-01 1.45e-01 0.31 +2009 01 01 0035 54832 2100 0 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01 01 1935 54832 70500 0 7.41e+02 2.42e+01 0 1.54e+03 2.27e+01 2.29e+00 7.90e-01 1.48e-01 0.25 +2009 01 01 1940 54832 70800 0 9.59e+02 3.44e+01 0 1.62e+03 2.25e+01 3.03e+00 7.43e-01 2.61e-01 0.43 +2009 01 01 1945 54832 71100 0 7.49e+02 2.98e+01 0 1.70e+03 2.21e+01 1.23e+00 4.76e-01 1.74e-01 0.20 +2009 01 01 1950 54832 71400 0 7.31e+02 2.53e+01 0 1.68e+03 2.30e+01 2.13e+00 5.40e-01 1.37e-01 0.44 +2009 01 01 1955 54832 71700 0 9.65e+02 2.81e+01 0 1.69e+03 2.12e+01 2.27e+00 5.63e-01 2.05e-01 0.08 +2009 01 01 2000 54832 72000 0 8.82e+02 2.86e+01 0 1.72e+03 2.22e+01 2.29e+00 7.48e-01 2.53e-01 0.24 +2009 01 01 2005 54832 72300 0 7.12e+02 2.92e+01 0 1.74e+03 2.12e+01 2.52e+00 5.20e-01 1.05e-01 0.37 +2009 01 01 2010 54832 72600 0 7.32e+02 3.63e+01 0 1.62e+03 2.11e+01 2.25e+00 7.24e-01 1.45e-01 0.33 +2009 01 01 2015 54832 72900 0 8.84e+02 2.81e+01 0 1.74e+03 1.83e+01 2.02e+00 8.38e-01 1.93e-01 0.63 +2009 01 01 2020 54832 73200 0 7.30e+02 3.12e+01 0 1.76e+03 1.73e+01 2.71e+00 7.44e-01 1.89e-01 0.57 +2009 01 01 2025 54832 73500 0 7.50e+02 2.64e+01 0 1.69e+03 2.36e+01 2.31e+00 8.23e-01 2.09e-01 0.69 +2009 01 01 2030 54832 73800 0 9.25e+02 3.00e+01 0 2.10e+03 2.92e+01 2.34e+00 4.37e-01 1.90e-01 0.57 +2009 01 01 2035 54832 74100 0 6.39e+02 2.27e+01 0 2.42e+03 3.41e+01 2.66e+00 7.74e-01 1.25e-01 0.47 +2009 01 01 2040 54832 74400 0 6.35e+02 2.88e+01 0 1.91e+03 3.77e+01 2.85e+00 6.65e-01 8.43e-02 0.48 +2009 01 01 2045 54832 74700 0 7.70e+02 2.84e+01 0 1.55e+03 1.87e+01 1.97e+00 4.37e-01 1.90e-01 0.54 +2009 01 01 2050 54832 75000 0 7.51e+02 2.68e+01 0 1.66e+03 2.05e+01 2.66e+00 7.91e-01 1.60e-01 0.18 +2009 01 01 2055 54832 75300 0 6.93e+02 2.98e+01 0 1.66e+03 2.18e+01 2.56e+00 6.44e-01 2.00e-01 0.22 +2009 01 01 2100 54832 75600 0 7.58e+02 3.30e+01 0 1.56e+03 1.75e+01 2.52e+00 6.86e-01 1.58e-01 0.92 +2009 01 01 2105 54832 75900 0 7.89e+02 2.98e+01 0 1.61e+03 1.55e+01 3.07e+00 4.57e-01 1.45e-01 0.00 +2009 01 01 2110 54832 76200 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 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-1.00 +2009 01 01 2200 54832 79200 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00 +2009 01 01 2205 54832 79500 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00 +2009 01 01 2210 54832 79800 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00 +2009 01 01 2215 54832 80100 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00 +2009 01 01 2220 54832 80400 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00 +2009 01 01 2225 54832 80700 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00 +2009 01 01 2230 54832 81000 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00 +2009 01 01 2235 54832 81300 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00 +2009 01 01 2240 54832 81600 9 -1.00e+05 -1.00e+05 9 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00e+05 -1.00 +2009 01 01 2245 54832 81900 0 8.11e+02 2.81e+01 0 1.76e+03 1.78e+01 2.46e+00 6.86e-01 1.55e-01 0.16 +2009 01 01 2250 54832 82200 0 7.51e+02 2.78e+01 0 1.71e+03 1.92e+01 2.55e+00 5.63e-01 1.87e-01 0.06 +2009 01 01 2255 54832 82500 0 6.39e+02 2.20e+01 0 1.64e+03 1.94e+01 2.13e+00 5.82e-01 1.37e-01 0.11 +2009 01 01 2300 54832 82800 0 7.52e+02 2.67e+01 0 1.51e+03 2.23e+01 2.56e+00 6.44e-01 2.11e-01 0.68 +2009 01 01 2305 54832 83100 0 9.20e+02 2.45e+01 0 1.63e+03 1.91e+01 2.41e+00 5.98e-01 1.52e-01 0.42 +2009 01 01 2310 54832 83400 0 7.68e+02 3.19e+01 0 1.64e+03 2.08e+01 2.23e+00 8.31e-01 1.16e-01 0.29 +2009 01 01 2315 54832 83700 0 7.08e+02 2.99e+01 0 1.63e+03 2.24e+01 2.83e+00 3.52e-01 1.34e-01 0.24 +2009 01 01 2320 54832 84000 0 8.73e+02 3.02e+01 0 1.77e+03 1.88e+01 2.85e+00 7.69e-01 2.32e-01 0.34 +2009 01 01 2325 54832 84300 0 7.18e+02 2.73e+01 0 1.58e+03 1.70e+01 2.23e+00 5.61e-01 2.00e-01 0.29 +2009 01 01 2330 54832 84600 0 7.51e+02 3.06e+01 0 1.62e+03 1.71e+01 2.39e+00 7.04e-01 1.25e-01 0.85 +2009 01 01 2335 54832 84900 0 7.18e+02 3.29e+01 0 1.56e+03 1.91e+01 2.85e+00 6.03e-01 1.37e-01 0.45 +2009 01 01 2340 54832 85200 0 7.68e+02 2.80e+01 0 1.71e+03 2.04e+01 2.85e+00 6.65e-01 1.79e-01 0.76 +2009 01 01 2345 54832 85500 0 6.97e+02 2.71e+01 0 1.65e+03 1.87e+01 2.52e+00 6.33e-01 1.87e-01 0.73 +2009 01 01 2350 54832 85800 0 7.27e+02 2.63e+01 0 1.51e+03 2.01e+01 2.56e+00 5.40e-01 1.69e-01 0.58 +2009 01 01 2355 54832 86100 0 5.22e+02 1.82e+01 0 1.64e+03 2.03e+01 2.74e+00 6.53e-01 1.92e-01 0.28 diff --git a/GeospaceDataManagement/tests/test_data/20090101_ace_mag_1m.txt b/GeospaceDataManagement/tests/test_data/20090101_ace_mag_1m.txt new file mode 100644 index 0000000..1a4f21d --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/20090101_ace_mag_1m.txt @@ -0,0 +1,1460 @@ +:Data_list: 20090101_ace_mag_1m.txt +:Created: 2009 Jan 02 0011 UT +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# Magnetometer values are in GSM coordinates. +# +# Units: Bx, By, Bz, Bt in nT +# Units: Latitude degrees +/- 90.0 +# Units: Longitude degrees 0.0 - 360.0 +# Status(S): 0 = nominal data, 1 to 8 = bad data record, 9 = no data +# Missing data values: -999.9 +# Source: ACE Satellite - Magnetometer +# +# 1-minute averaged Real-time Interplanetary Magnetic Field Values +# +# Modified Seconds +# UT Date Time Julian of the ---------------- GSM Coordinates --------------- +# YR MO DA HHMM Day Day S Bx By Bz Bt Lat. Long. +#------------------------------------------------------------------------------------ +2009 01 01 0000 54832 0 0 -3.3 2.5 1.7 4.5 23.1 142.7 +2009 01 01 0001 54832 60 0 -3.4 2.2 2.0 4.5 25.8 147.3 +2009 01 01 0002 54832 120 0 -3.8 1.8 1.7 4.5 21.8 154.8 +2009 01 01 0003 54832 180 0 -3.7 1.9 2.0 4.6 25.1 153.4 +2009 01 01 0004 54832 240 0 -4.2 1.8 0.8 4.7 10.3 157.2 +2009 01 01 0005 54832 300 0 -4.4 1.0 -1.3 4.6 -16.2 167.2 +2009 01 01 0006 54832 360 0 -4.2 1.4 -1.9 4.8 -23.5 162.0 +2009 01 01 0007 54832 420 0 -4.2 1.5 -1.5 4.7 -18.4 159.9 +2009 01 01 0008 54832 480 0 -4.6 0.5 -1.3 4.8 -16.1 174.3 +2009 01 01 0009 54832 540 0 -4.6 0.8 -1.2 4.8 -14.3 169.7 +2009 01 01 0010 54832 600 0 -4.6 1.1 -0.7 4.7 -8.7 166.9 +2009 01 01 0011 54832 660 0 -4.7 1.0 -0.6 4.8 -7.6 168.5 +2009 01 01 0012 54832 720 0 -4.5 1.1 -0.3 4.7 -4.2 165.9 +2009 01 01 0013 54832 780 0 -4.3 1.5 -0.2 4.6 -2.0 161.2 +2009 01 01 0014 54832 840 0 -4.2 1.6 -0.0 4.5 -0.0 159.7 +2009 01 01 0015 54832 900 0 -4.1 1.3 -0.8 4.4 -10.2 162.1 +2009 01 01 0016 54832 960 0 -4.2 0.5 -1.5 4.5 -19.8 172.7 +2009 01 01 0017 54832 1020 0 -3.9 -1.0 -2.0 4.5 -26.4 194.0 +2009 01 01 0018 54832 1080 0 -4.1 -0.7 -1.8 4.6 -22.9 190.0 +2009 01 01 0019 54832 1140 0 -3.9 -1.4 -1.7 4.4 -22.5 199.5 +2009 01 01 0020 54832 1200 0 -3.1 -2.1 -2.2 4.3 -30.1 213.7 +2009 01 01 0021 54832 1260 0 -3.7 -0.3 -2.5 4.5 -34.2 185.0 +2009 01 01 0022 54832 1320 0 -3.5 -0.8 -2.6 4.4 -35.8 193.0 +2009 01 01 0023 54832 1380 0 -4.0 0.2 -2.1 4.5 -27.3 177.1 +2009 01 01 0024 54832 1440 0 -4.3 0.7 -0.8 4.5 -10.7 171.0 +2009 01 01 0025 54832 1500 0 -4.3 1.3 -0.9 4.6 -10.9 163.1 +2009 01 01 0026 54832 1560 0 -4.4 1.3 -1.2 4.7 -14.9 163.7 +2009 01 01 0027 54832 1620 0 -4.4 1.5 0.3 4.6 3.9 161.1 +2009 01 01 0028 54832 1680 0 -4.4 1.5 -0.1 4.7 -1.8 161.0 +2009 01 01 0029 54832 1740 0 -4.5 1.2 -0.7 4.7 -8.2 165.2 +2009 01 01 0030 54832 1800 0 -4.4 1.3 -0.6 4.7 -7.7 163.9 +2009 01 01 0031 54832 1860 0 -4.6 0.9 -0.9 4.8 -11.1 168.8 +2009 01 01 0032 54832 1920 0 -4.6 0.4 -1.1 4.7 -13.5 175.2 +2009 01 01 0033 54832 1980 0 -4.6 0.5 -1.3 4.8 -15.8 174.2 +2009 01 01 0034 54832 2040 0 -4.4 0.2 -1.7 4.7 -21.0 176.9 +2009 01 01 0035 54832 2100 0 -4.4 -0.0 -1.6 4.7 -19.4 180.4 +2009 01 01 0036 54832 2160 0 -4.5 -0.3 -1.5 4.7 -18.1 183.5 +2009 01 01 0037 54832 2220 0 -4.4 -0.0 -1.4 4.6 -17.4 180.4 +2009 01 01 0038 54832 2280 0 -4.2 0.4 -1.5 4.4 -19.3 174.6 +2009 01 01 0039 54832 2340 0 -3.6 0.5 -2.6 4.4 -35.4 171.5 +2009 01 01 0040 54832 2400 0 -3.3 0.0 -2.8 4.3 -40.8 179.4 +2009 01 01 0041 54832 2460 0 -3.8 0.2 -2.3 4.5 -31.5 177.3 +2009 01 01 0042 54832 2520 0 -3.8 -0.0 -2.3 4.5 -31.0 180.2 +2009 01 01 0043 54832 2580 0 -3.2 -0.9 -3.0 4.5 -41.5 195.8 +2009 01 01 0044 54832 2640 0 -3.2 -1.0 -3.1 4.6 -42.4 197.9 +2009 01 01 0045 54832 2700 0 -3.1 0.2 -2.7 4.1 -40.4 177.2 +2009 01 01 0046 54832 2760 0 -3.5 0.6 -2.0 4.1 -29.5 170.7 +2009 01 01 0047 54832 2820 0 -3.8 -0.0 -1.7 4.2 -24.8 180.2 +2009 01 01 0048 54832 2880 0 -3.6 -0.1 -2.1 4.1 -31.1 181.1 +2009 01 01 0049 54832 2940 0 -3.5 0.3 -2.2 4.1 -32.3 175.3 +2009 01 01 0050 54832 3000 0 -4.1 0.2 -1.4 4.3 -19.4 177.7 +2009 01 01 0051 54832 3060 0 -4.3 -0.0 -1.0 4.4 -12.8 180.3 +2009 01 01 0052 54832 3120 0 -4.4 0.3 -0.8 4.5 -9.9 176.6 +2009 01 01 0053 54832 3180 0 -4.3 0.6 -0.6 4.4 -8.2 172.1 +2009 01 01 0054 54832 3240 0 -4.1 0.9 -0.8 4.3 -10.9 168.0 +2009 01 01 0055 54832 3300 0 -4.2 1.0 -0.5 4.3 -7.2 166.1 +2009 01 01 0056 54832 3360 0 -4.3 0.9 -0.6 4.4 -7.6 168.1 +2009 01 01 0057 54832 3420 0 -4.2 1.2 -0.2 4.4 -2.2 164.2 +2009 01 01 0058 54832 3480 0 -4.3 1.1 -0.0 4.5 -0.6 166.0 +2009 01 01 0059 54832 3540 0 -4.3 1.1 -0.6 4.5 -7.2 166.1 +2009 01 01 0100 54832 3600 0 -4.3 1.0 -0.5 4.5 -6.8 166.8 +2009 01 01 0101 54832 3660 0 -4.4 1.2 -0.0 4.6 -0.2 164.8 +2009 01 01 0102 54832 3720 0 -4.3 1.3 -0.0 4.5 -0.2 163.7 +2009 01 01 0103 54832 3780 0 -4.3 1.2 -0.1 4.4 -1.9 163.6 +2009 01 01 0104 54832 3840 0 -4.2 1.0 -1.0 4.4 -13.0 166.1 +2009 01 01 0105 54832 3900 0 -4.2 1.1 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Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# Units: proton flux p/cs2-sec-ster +# Status(S): 0 = nominal data, 1 to 8 = bad data record, 9 = no data +# Missing data values: -1.00e+05 +# Source: ACE Satellite - Solar Isotope Spectrometer +# +# 5-minute averaged Real-time Integral Flux of High-energy Solar Protons +# +# Modified Seconds +# UT Date Time Julian of the ---- Integral Proton Flux ---- +# YR MO DA HHMM Day Day S > 10 MeV S > 30 MeV +#-------------------------------------------------------------------- +2009 01 01 0000 54832 0 0 2.21e+00 0 1.54e+00 +2009 01 01 0005 54832 300 0 2.17e+00 0 1.53e+00 +2009 01 01 0010 54832 600 0 2.17e+00 0 1.54e+00 +2009 01 01 0015 54832 900 0 2.20e+00 0 1.54e+00 +2009 01 01 0020 54832 1200 0 2.18e+00 0 1.52e+00 +2009 01 01 0025 54832 1500 0 2.20e+00 0 1.55e+00 +2009 01 01 0030 54832 1800 0 2.14e+00 0 1.50e+00 +2009 01 01 0035 54832 2100 0 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1.51e+00 +2009 01 01 1345 54832 49500 0 2.16e+00 0 1.52e+00 +2009 01 01 1350 54832 49800 0 2.13e+00 0 1.48e+00 +2009 01 01 1355 54832 50100 0 2.13e+00 0 1.51e+00 +2009 01 01 1400 54832 50400 0 2.13e+00 0 1.49e+00 +2009 01 01 1405 54832 50700 0 2.19e+00 0 1.53e+00 +2009 01 01 1410 54832 51000 0 2.23e+00 0 1.57e+00 +2009 01 01 1415 54832 51300 0 2.12e+00 0 1.48e+00 +2009 01 01 1420 54832 51600 0 2.13e+00 0 1.49e+00 +2009 01 01 1425 54832 51900 0 2.17e+00 0 1.52e+00 +2009 01 01 1430 54832 52200 0 2.17e+00 0 1.51e+00 +2009 01 01 1435 54832 52500 0 2.16e+00 0 1.51e+00 +2009 01 01 1440 54832 52800 0 2.20e+00 0 1.53e+00 +2009 01 01 1445 54832 53100 0 2.11e+00 0 1.49e+00 +2009 01 01 1450 54832 53400 0 2.14e+00 0 1.49e+00 +2009 01 01 1455 54832 53700 0 2.16e+00 0 1.52e+00 +2009 01 01 1500 54832 54000 0 2.14e+00 0 1.49e+00 +2009 01 01 1505 54832 54300 0 2.09e+00 0 1.46e+00 +2009 01 01 1510 54832 54600 0 2.14e+00 0 1.50e+00 +2009 01 01 1515 54832 54900 0 2.07e+00 0 1.44e+00 +2009 01 01 1520 54832 55200 0 2.11e+00 0 1.48e+00 +2009 01 01 1525 54832 55500 0 2.13e+00 0 1.49e+00 +2009 01 01 1530 54832 55800 0 2.11e+00 0 1.47e+00 +2009 01 01 1535 54832 56100 0 2.10e+00 0 1.48e+00 +2009 01 01 1540 54832 56400 0 2.11e+00 0 1.46e+00 +2009 01 01 1545 54832 56700 0 2.25e+00 0 1.57e+00 +2009 01 01 1550 54832 57000 0 2.21e+00 0 1.54e+00 +2009 01 01 1555 54832 57300 0 2.20e+00 0 1.54e+00 +2009 01 01 1600 54832 57600 0 2.17e+00 0 1.51e+00 +2009 01 01 1605 54832 57900 0 2.13e+00 0 1.49e+00 +2009 01 01 1610 54832 58200 0 2.11e+00 0 1.47e+00 +2009 01 01 1615 54832 58500 0 2.10e+00 0 1.46e+00 +2009 01 01 1620 54832 58800 0 2.19e+00 0 1.53e+00 +2009 01 01 1625 54832 59100 0 2.15e+00 0 1.50e+00 +2009 01 01 1630 54832 59400 0 2.14e+00 0 1.49e+00 +2009 01 01 1635 54832 59700 0 2.16e+00 0 1.51e+00 +2009 01 01 1640 54832 60000 0 2.21e+00 0 1.54e+00 +2009 01 01 1645 54832 60300 0 2.17e+00 0 1.52e+00 +2009 01 01 1650 54832 60600 0 2.14e+00 0 1.50e+00 +2009 01 01 1655 54832 60900 0 2.14e+00 0 1.50e+00 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2.22e+00 0 1.56e+00 +2009 01 01 1840 54832 67200 0 2.15e+00 0 1.51e+00 +2009 01 01 1845 54832 67500 0 2.19e+00 0 1.53e+00 +2009 01 01 1850 54832 67800 0 2.18e+00 0 1.52e+00 +2009 01 01 1855 54832 68100 0 2.22e+00 0 1.55e+00 +2009 01 01 1900 54832 68400 0 2.25e+00 0 1.58e+00 +2009 01 01 1905 54832 68700 0 2.15e+00 0 1.49e+00 +2009 01 01 1910 54832 69000 0 2.12e+00 0 1.49e+00 +2009 01 01 1915 54832 69300 0 2.12e+00 0 1.48e+00 +2009 01 01 1920 54832 69600 0 2.16e+00 0 1.51e+00 +2009 01 01 1925 54832 69900 0 2.13e+00 0 1.49e+00 +2009 01 01 1930 54832 70200 0 2.11e+00 0 1.46e+00 +2009 01 01 1935 54832 70500 0 2.16e+00 0 1.52e+00 +2009 01 01 1940 54832 70800 0 2.07e+00 0 1.45e+00 +2009 01 01 1945 54832 71100 0 2.16e+00 0 1.49e+00 +2009 01 01 1950 54832 71400 0 2.16e+00 0 1.52e+00 +2009 01 01 1955 54832 71700 0 2.15e+00 0 1.50e+00 +2009 01 01 2000 54832 72000 0 2.12e+00 0 1.49e+00 +2009 01 01 2005 54832 72300 0 2.11e+00 0 1.46e+00 +2009 01 01 2010 54832 72600 0 2.11e+00 0 1.47e+00 +2009 01 01 2015 54832 72900 0 2.14e+00 0 1.49e+00 +2009 01 01 2020 54832 73200 0 2.32e+00 0 1.61e+00 +2009 01 01 2025 54832 73500 0 2.30e+00 0 1.60e+00 +2009 01 01 2030 54832 73800 0 2.17e+00 0 1.52e+00 +2009 01 01 2035 54832 74100 0 2.19e+00 0 1.53e+00 +2009 01 01 2040 54832 74400 0 2.17e+00 0 1.52e+00 +2009 01 01 2045 54832 74700 0 2.18e+00 0 1.52e+00 +2009 01 01 2050 54832 75000 0 2.17e+00 0 1.52e+00 +2009 01 01 2055 54832 75300 0 2.18e+00 0 1.53e+00 +2009 01 01 2100 54832 75600 0 2.16e+00 0 1.51e+00 +2009 01 01 2105 54832 75900 0 2.17e+00 0 1.51e+00 +2009 01 01 2110 54832 76200 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2115 54832 76500 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2120 54832 76800 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2125 54832 77100 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2130 54832 77400 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2135 54832 77700 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2140 54832 78000 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2145 54832 78300 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2150 54832 78600 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2155 54832 78900 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2200 54832 79200 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2205 54832 79500 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2210 54832 79800 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2215 54832 80100 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2220 54832 80400 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2225 54832 80700 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2230 54832 81000 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2235 54832 81300 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2240 54832 81600 9 -1.00e+05 9 -1.00e+05 +2009 01 01 2245 54832 81900 0 1.08e+01 0 9.96e+00 +2009 01 01 2250 54832 82200 0 2.20e+00 0 1.52e+00 +2009 01 01 2255 54832 82500 0 2.22e+00 0 1.55e+00 +2009 01 01 2300 54832 82800 0 2.18e+00 0 1.52e+00 +2009 01 01 2305 54832 83100 0 2.17e+00 0 1.52e+00 +2009 01 01 2310 54832 83400 0 2.15e+00 0 1.50e+00 +2009 01 01 2315 54832 83700 0 2.18e+00 0 1.52e+00 +2009 01 01 2320 54832 84000 0 2.21e+00 0 1.54e+00 +2009 01 01 2325 54832 84300 0 2.21e+00 0 1.53e+00 +2009 01 01 2330 54832 84600 0 2.16e+00 0 1.50e+00 +2009 01 01 2335 54832 84900 0 2.11e+00 0 1.48e+00 +2009 01 01 2340 54832 85200 0 2.16e+00 0 1.50e+00 +2009 01 01 2345 54832 85500 0 2.14e+00 0 1.48e+00 +2009 01 01 2350 54832 85800 0 2.13e+00 0 1.49e+00 +2009 01 01 2355 54832 86100 0 2.17e+00 0 1.55e+00 diff --git a/GeospaceDataManagement/tests/test_data/20090101_ace_swepam_1m.txt b/GeospaceDataManagement/tests/test_data/20090101_ace_swepam_1m.txt new file mode 100644 index 0000000..27f483c --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/20090101_ace_swepam_1m.txt @@ -0,0 +1,1458 @@ +:Data_list: 20090101_ace_swepam_1m.txt +:Created: 2009 Jan 02 0011 UT +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# Units: Proton density p/cc +# Units: Bulk speed km/s +# Units: Ion tempeture degrees K +# Status(S): 0 = nominal data, 1 to 8 = bad data record, 9 = no data +# Missing data values: Density and Speed = -9999.9, Temp. = -1.00e+05 +# Source: ACE Satellite - Solar Wind Electron Proton Alpha Monitor +# +# 1-minute averaged Real-time Bulk Parameters of the Solar Wind Plasma +# +# Modified Seconds ------------- Solar Wind ----------- +# UT Date Time Julian of the Proton Bulk Ion +# YR MO DA HHMM Day Day S Density Speed Temperature +#------------------------------------------------------------------------- +2009 01 01 0000 54832 0 0 2.0 521.2 2.48e+05 +2009 01 01 0001 54832 60 0 2.0 522.0 2.13e+05 +2009 01 01 0002 54832 120 0 2.1 520.9 2.22e+05 +2009 01 01 0003 54832 180 0 2.4 508.5 2.35e+05 +2009 01 01 0004 54832 240 1 2.2 519.1 2.85e+05 +2009 01 01 0005 54832 300 1 2.2 514.8 2.65e+05 +2009 01 01 0006 54832 360 1 2.5 513.0 2.48e+05 +2009 01 01 0007 54832 420 0 2.3 514.5 2.60e+05 +2009 01 01 0008 54832 480 9 -9999.9 -9999.9 -1.00e+05 +2009 01 01 0009 54832 540 9 -9999.9 -9999.9 -1.00e+05 +2009 01 01 0010 54832 600 1 2.4 512.8 2.71e+05 +2009 01 01 0011 54832 660 0 2.3 511.5 2.68e+05 +2009 01 01 0012 54832 720 1 2.3 513.6 2.81e+05 +2009 01 01 0013 54832 780 1 2.3 511.7 2.73e+05 +2009 01 01 0014 54832 840 1 2.4 515.8 2.78e+05 +2009 01 01 0015 54832 900 0 2.4 513.8 2.73e+05 +2009 01 01 0016 54832 960 1 2.3 519.1 2.64e+05 +2009 01 01 0017 54832 1020 1 2.3 519.1 2.68e+05 +2009 01 01 0018 54832 1080 1 2.3 520.2 2.98e+05 +2009 01 01 0019 54832 1140 1 2.4 517.4 2.63e+05 +2009 01 01 0020 54832 1200 0 2.0 526.2 2.49e+05 +2009 01 01 0021 54832 1260 0 2.0 521.2 2.90e+05 +2009 01 01 0022 54832 1320 0 2.2 524.2 2.67e+05 +2009 01 01 0023 54832 1380 1 2.2 514.7 2.41e+05 +2009 01 01 0024 54832 1440 1 -9999.9 -9999.9 -1.00e+05 +2009 01 01 0025 54832 1500 1 -9999.9 -9999.9 -1.00e+05 +2009 01 01 0026 54832 1560 1 2.3 518.8 2.81e+05 +2009 01 01 0027 54832 1620 0 2.3 520.6 2.63e+05 +2009 01 01 0028 54832 1680 1 2.3 512.2 2.74e+05 +2009 01 01 0029 54832 1740 1 2.4 513.9 2.68e+05 +2009 01 01 0030 54832 1800 1 2.3 516.3 2.72e+05 +2009 01 01 0031 54832 1860 0 2.4 515.4 2.61e+05 +2009 01 01 0032 54832 1920 1 2.3 513.1 2.62e+05 +2009 01 01 0033 54832 1980 0 2.6 514.3 2.49e+05 +2009 01 01 0034 54832 2040 0 2.5 514.3 2.53e+05 +2009 01 01 0035 54832 2100 1 2.4 516.9 2.71e+05 +2009 01 01 0036 54832 2160 1 2.5 516.2 2.66e+05 +2009 01 01 0037 54832 2220 0 2.5 516.0 2.69e+05 +2009 01 01 0038 54832 2280 1 2.3 519.5 2.72e+05 +2009 01 01 0039 54832 2340 0 2.5 520.8 2.43e+05 +2009 01 01 0040 54832 2400 0 2.2 523.0 2.35e+05 +2009 01 01 0041 54832 2460 0 2.2 523.0 2.35e+05 +2009 01 01 0042 54832 2520 9 -9999.9 -9999.9 -1.00e+05 +2009 01 01 0043 54832 2580 1 2.2 514.3 2.28e+05 +2009 01 01 0044 54832 2640 0 2.1 525.3 2.15e+05 +2009 01 01 0045 54832 2700 0 2.1 524.0 1.95e+05 +2009 01 01 0046 54832 2760 1 2.2 522.9 2.34e+05 +2009 01 01 0047 54832 2820 0 2.4 521.8 2.32e+05 +2009 01 01 0048 54832 2880 0 2.3 521.2 2.40e+05 +2009 01 01 0049 54832 2940 0 2.2 521.7 2.34e+05 +2009 01 01 0050 54832 3000 0 2.3 523.7 2.39e+05 +2009 01 01 0051 54832 3060 1 2.2 520.7 2.58e+05 +2009 01 01 0052 54832 3120 0 2.3 520.5 2.47e+05 +2009 01 01 0053 54832 3180 0 2.2 519.3 2.48e+05 +2009 01 01 0054 54832 3240 1 2.3 519.2 2.47e+05 +2009 01 01 0055 54832 3300 1 2.3 519.4 2.44e+05 +2009 01 01 0056 54832 3360 0 2.4 519.2 2.42e+05 +2009 01 01 0057 54832 3420 0 2.4 519.2 2.42e+05 +2009 01 01 0058 54832 3480 0 2.3 520.4 2.51e+05 +2009 01 01 0059 54832 3540 1 2.3 520.3 2.52e+05 +2009 01 01 0100 54832 3600 0 2.3 520.6 2.41e+05 +2009 01 01 0101 54832 3660 1 2.4 520.1 2.53e+05 +2009 01 01 0102 54832 3720 0 2.2 521.4 2.49e+05 +2009 01 01 0103 54832 3780 1 2.2 520.8 2.49e+05 +2009 01 01 0104 54832 3840 1 2.3 521.6 2.40e+05 +2009 01 01 0105 54832 3900 1 2.4 521.1 2.49e+05 +2009 01 01 0106 54832 3960 0 2.3 521.7 2.33e+05 +2009 01 01 0107 54832 4020 0 2.2 523.4 2.29e+05 +2009 01 01 0108 54832 4080 0 2.1 523.7 2.38e+05 +2009 01 01 0109 54832 4140 0 2.2 522.2 2.27e+05 +2009 01 01 0110 54832 4200 0 2.2 521.5 2.33e+05 +2009 01 01 0111 54832 4260 0 2.3 521.3 2.27e+05 +2009 01 01 0112 54832 4320 0 2.1 523.8 2.31e+05 +2009 01 01 0113 54832 4380 0 2.1 523.8 2.31e+05 +2009 01 01 0114 54832 4440 1 2.1 522.5 2.45e+05 +2009 01 01 0115 54832 4500 1 -9999.9 -9999.9 -1.00e+05 +2009 01 01 0116 54832 4560 1 2.1 523.8 1.91e+05 +2009 01 01 0117 54832 4620 0 1.7 529.2 1.97e+05 +2009 01 01 0118 54832 4680 0 1.8 525.9 1.91e+05 +2009 01 01 0119 54832 4740 0 1.7 529.2 1.95e+05 +2009 01 01 0120 54832 4800 0 1.8 528.9 1.84e+05 +2009 01 01 0121 54832 4860 1 2.1 526.0 2.21e+05 +2009 01 01 0122 54832 4920 0 2.2 526.1 2.15e+05 +2009 01 01 0123 54832 4980 0 2.0 529.2 2.06e+05 +2009 01 01 0124 54832 5040 0 2.0 528.8 2.03e+05 +2009 01 01 0125 54832 5100 1 2.1 525.7 2.15e+05 +2009 01 01 0126 54832 5160 0 1.9 527.1 1.94e+05 +2009 01 01 0127 54832 5220 1 1.8 524.2 2.50e+05 +2009 01 01 0128 54832 5280 1 1.8 521.6 2.53e+05 +2009 01 01 0129 54832 5340 1 1.8 521.6 2.53e+05 +2009 01 01 0130 54832 5400 1 1.6 524.4 2.46e+05 +2009 01 01 0131 54832 5460 0 1.8 524.3 2.44e+05 +2009 01 01 0132 54832 5520 0 1.5 523.5 2.44e+05 +2009 01 01 0133 54832 5580 0 2.2 515.7 2.37e+05 +2009 01 01 0134 54832 5640 0 1.8 524.1 2.27e+05 +2009 01 01 0135 54832 5700 0 1.7 526.3 1.97e+05 +2009 01 01 0136 54832 5760 0 1.9 534.5 1.71e+05 +2009 01 01 0137 54832 5820 1 1.8 535.5 1.26e+05 +2009 01 01 0138 54832 5880 0 1.7 538.1 1.59e+05 +2009 01 01 0139 54832 5940 0 1.6 529.9 1.60e+05 +2009 01 01 0140 54832 6000 0 1.5 516.6 1.81e+05 +2009 01 01 0141 54832 6060 0 1.7 507.1 2.06e+05 +2009 01 01 0142 54832 6120 1 1.5 510.2 2.13e+05 +2009 01 01 0143 54832 6180 0 1.4 512.6 1.88e+05 +2009 01 01 0144 54832 6240 0 1.5 514.2 1.99e+05 +2009 01 01 0145 54832 6300 0 1.5 514.2 1.99e+05 +2009 01 01 0146 54832 6360 0 1.4 516.9 2.00e+05 +2009 01 01 0147 54832 6420 0 1.5 512.4 1.97e+05 +2009 01 01 0148 54832 6480 9 -9999.9 -9999.9 -1.00e+05 +2009 01 01 0149 54832 6540 0 1.4 512.6 1.89e+05 +2009 01 01 0150 54832 6600 1 1.5 512.0 2.26e+05 +2009 01 01 0151 54832 6660 0 1.5 510.8 1.98e+05 +2009 01 01 0152 54832 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2009 Daily Solar Data +# +# Sunspot Stanford GOES14 +# Radio SESC Area Solar X-Ray ------ Flares ------ +# Flux Sunspot 10E-6 New Mean Bkgd X-Ray Optical +# Date 10.7cm Number Hemis. 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b/GeospaceDataManagement/tests/test_data/3-day-geomag-forecast.txt @@ -0,0 +1,25 @@ +:Product: Geomagnetic Forecast +:Issued: 2023 Oct 31 2205 UTC +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# +NOAA Ap Index Forecast +Observed Ap 30 Oct 012 +Estimated Ap 31 Oct 010 +Predicted Ap 01 Nov-03 Nov 008-005-005 + +NOAA Geomagnetic Activity Probabilities 01 Nov-03 Nov +Active 25/20/20 +Minor storm 05/01/01 +Moderate storm 01/01/01 +Strong-Extreme storm 01/01/01 + +NOAA Kp index forecast 01 Nov - 03 Nov + Nov 01 Nov 02 Nov 03 +00-03UT 2.33 1.67 1.67 +03-06UT 2.67 1.67 1.33 +06-09UT 2.33 1.33 1.33 +09-12UT 2.00 1.33 1.33 +12-15UT 2.00 1.33 1.33 +15-18UT 2.00 1.33 1.33 +18-21UT 2.00 1.33 1.67 +21-00UT 2.33 1.67 1.67 diff --git a/GeospaceDataManagement/tests/test_data/3-day-solar-geomag-predictions.txt b/GeospaceDataManagement/tests/test_data/3-day-solar-geomag-predictions.txt new file mode 100644 index 0000000..595eeb7 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/3-day-solar-geomag-predictions.txt @@ -0,0 +1,68 @@ +:Product: 3-day Space Weather Predictions daypre.txt +:Issued: 2023 Oct 31 2200 UTC +# Prepared by the US Dept. of Commerce, NOAA, Space Weather Prediction Center +# Product description and SWPC contact on the Web +# http://www.swpc.noaa.gov/wwire.html +# +# 3-day Space Weather Predictions +# +:Prediction_dates: 2023 Nov 01 2023 Nov 02 2023 Nov 03 +:Geomagnetic_A_indices: +A_Fredericksburg 8 6 6 +A_Planetary 8 5 5 +# +# Predicted 3-hour Middle latitude k-indices +:Pred_Mid_k: +Mid/00-03UT 2 2 2 +Mid/03-06UT 3 2 1 +Mid/06-09UT 2 2 2 +Mid/09-12UT 2 1 1 +Mid/12-15UT 2 2 2 +Mid/15-18UT 2 1 1 +Mid/18-21UT 2 1 2 +Mid/21-00UT 2 2 2 +# +# Predicted 3-hour High latitude k-indices +:Pred_High_k: +High/00-03UT 2 1 1 +High/03-06UT 2 1 1 +High/06-09UT 3 1 1 +High/09-12UT 3 2 2 +High/12-15UT 3 2 2 +High/15-18UT 2 1 1 +High/18-21UT 2 1 1 +High/21-00UT 1 1 1 +# +# Probability of Geomagnetic conditions at Middle Latitude +:Prob_Mid: +Mid/Active 15 10 10 +Mid/Minor_Storm 5 5 5 +Mid/Major-Severe_Storm 1 1 1 +# +# Probability of Geomagnetic conditions at High Latitudes +:Prob_High: +High/Active 15 15 15 +High/Minor_Storm 20 20 20 +High/Major-Severe_Storm 20 15 15 +# +# Polar Cap Absorption Forecast +:Polar_cap: + green +# +# Solar +:10cm_flux: + 148 148 150 +# +:Whole_Disk_Flare_Prob: +Class_M 25 25 25 +Class_X 5 5 5 +Proton 1 1 1 +# +# Region Flare Probabilities for 2023 Nov 01 +# Region Class C M X P +:Reg_Prob: 2023 Oct 31 + 3472 15 1 1 1 + 3473 20 5 1 1 + 3474 50 15 5 1 + 3476 10 1 1 1 + 3477 15 5 1 1 diff --git a/GeospaceDataManagement/tests/test_data/45-day-forecast.txt b/GeospaceDataManagement/tests/test_data/45-day-forecast.txt new file mode 100644 index 0000000..9bfdedf --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/45-day-forecast.txt @@ -0,0 +1,32 @@ +:Product: 45 Day AP Forecast 45DF.txt +:Issued: 2023 Oct 31 2113 UTC +# Prepared by the U.S. Air Force. +# Retransmitted by the Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# +# 45-Day AP and F10.7cm Flux Forecast +#------------------------------------------------------------- +45-DAY AP FORECAST +01Nov23 008 02Nov23 005 03Nov23 005 04Nov23 005 05Nov23 005 +06Nov23 005 07Nov23 014 08Nov23 005 09Nov23 012 10Nov23 008 +11Nov23 005 12Nov23 005 13Nov23 005 14Nov23 008 15Nov23 010 +16Nov23 005 17Nov23 005 18Nov23 005 19Nov23 005 20Nov23 005 +21Nov23 005 22Nov23 015 23Nov23 010 24Nov23 015 25Nov23 015 +26Nov23 020 27Nov23 015 28Nov23 008 29Nov23 005 30Nov23 005 +01Dec23 005 02Dec23 005 03Dec23 005 04Dec23 005 05Dec23 005 +06Dec23 012 07Dec23 008 08Dec23 005 09Dec23 005 10Dec23 005 +11Dec23 008 12Dec23 010 13Dec23 008 14Dec23 005 15Dec23 005 +45-DAY F10.7 CM FLUX FORECAST +01Nov23 148 02Nov23 148 03Nov23 150 04Nov23 150 05Nov23 148 +06Nov23 146 07Nov23 144 08Nov23 136 09Nov23 136 10Nov23 138 +11Nov23 136 12Nov23 134 13Nov23 130 14Nov23 130 15Nov23 130 +16Nov23 125 17Nov23 123 18Nov23 120 19Nov23 125 20Nov23 125 +21Nov23 125 22Nov23 125 23Nov23 130 24Nov23 130 25Nov23 130 +26Nov23 130 27Nov23 132 28Nov23 134 29Nov23 134 30Nov23 136 +01Dec23 136 02Dec23 136 03Dec23 140 04Dec23 138 05Dec23 136 +06Dec23 136 07Dec23 138 08Dec23 136 09Dec23 134 10Dec23 130 +11Dec23 130 12Dec23 130 13Dec23 125 14Dec23 123 15Dec23 120 +FORECASTER: DY / GATES +99999 +NNNN diff --git a/GeospaceDataManagement/tests/test_data/Fadj_2009-01.txt b/GeospaceDataManagement/tests/test_data/Fadj_2009-01.txt new file mode 100644 index 0000000..4b098c9 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/Fadj_2009-01.txt @@ -0,0 +1 @@ +{"meta":{"source":"GFZ Potsdam","license":"CC BY 4.0"},"datetime":["2009-01-01T00:00:00Z","2009-01-02T00:00:00Z","2009-01-03T00:00:00Z","2009-01-04T00:00:00Z","2009-01-05T00:00:00Z","2009-01-06T00:00:00Z","2009-01-07T00:00:00Z","2009-01-08T00:00:00Z","2009-01-09T00:00:00Z","2009-01-10T00:00:00Z","2009-01-11T00:00:00Z","2009-01-12T00:00:00Z","2009-01-13T00:00:00Z","2009-01-14T00:00:00Z","2009-01-15T00:00:00Z","2009-01-16T00:00:00Z","2009-01-17T00:00:00Z","2009-01-18T00:00:00Z","2009-01-19T00:00:00Z","2009-01-20T00:00:00Z","2009-01-21T00:00:00Z","2009-01-22T00:00:00Z","2009-01-23T00:00:00Z","2009-01-24T00:00:00Z","2009-01-25T00:00:00Z","2009-01-26T00:00:00Z","2009-01-27T00:00:00Z","2009-01-28T00:00:00Z","2009-01-29T00:00:00Z","2009-01-30T00:00:00Z","2009-01-31T00:00:00Z","2009-02-01T00:00:00Z"],"Fadj":[66.6,67.6,67.2,66.6,66.9,66.5,66.7,66.5,67.4,68.5,67.7,67.0,68.2,68.9,68.8,68.5,69.6,68.8,68.6,68.1,67.2,66.9,67.8,66.6,67.7,67.8,67.6,67.4,67.3,67.1,67.4,67.5]} diff --git a/GeospaceDataManagement/tests/test_data/Fobs_2009-01.txt b/GeospaceDataManagement/tests/test_data/Fobs_2009-01.txt new file mode 100644 index 0000000..696eff0 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/Fobs_2009-01.txt @@ -0,0 +1 @@ +{"meta":{"source":"GFZ Potsdam","license":"CC BY 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b/GeospaceDataManagement/tests/test_data/Hp30_2009-01.txt new file mode 100644 index 0000000..5c1ad39 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/Hp30_2009-01.txt @@ -0,0 +1 @@ +{"meta":{"source":"GFZ Potsdam","license":"CC BY 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diff --git a/GeospaceDataManagement/tests/test_data/Hp60_2009-01.txt b/GeospaceDataManagement/tests/test_data/Hp60_2009-01.txt new file mode 100644 index 0000000..cc2906c --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/Hp60_2009-01.txt @@ -0,0 +1 @@ +{"meta":{"source":"GFZ Potsdam","license":"CC BY 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diff --git a/GeospaceDataManagement/tests/test_data/Kp_def2009.wdc b/GeospaceDataManagement/tests/test_data/Kp_def2009.wdc new file mode 100644 index 0000000..ccba0fc --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/Kp_def2009.wdc @@ -0,0 +1,375 @@ +# DOI: https://doi.org/10.5880/Kp.0001 +# LICENCE: CC BY 4.0, please cite: +# Matzka, J., Bronkalla, O., Tornow, K., Elger, K. and Stolle, C., 2021. +# Geomagnetic Kp index. V. 1.0. GFZ Data Services, +# https://doi.org/10.5880/Kp.0001 +# Matzka, J., Stolle, C., Yamazaki, Y., Bronkalla, O. and Morschhauser, A., +# 2021. The geomagnetic Kp index and derived indices of geomagnetic activity. +# Space Weather, https://doi.org/10.1029/2020SW002641 +# The Kp index was introduced by Bartels (1949) and is produced by Geomagnetic +# Observatory Niemegk, GFZ German Research Centre for Geosciences. + 9 1 12394 1172327202317 717150 6 9 12 7 9 6 3 6 70.42 + 9 1 22394 2 7 7 0 3 7201727 87 3 3 0 2 3 7 6 12 40.21 + 9 1 32394 3273027372023 720190 12 15 12 22 7 9 3 7 110.63 + 9 1 42394 423 7 710 72317 3 97 9 3 3 4 3 9 6 2 50.21 + 9 1 52394 51013101010171020100 4 5 4 4 4 6 4 7 50.21 + 9 1 62394 62017 3101013 0 0 73 7 6 2 4 4 5 0 0 40.10 + 9 1 72394 7 3 710 3 3 7 0 7 40 2 3 4 2 2 3 0 3 20.00 + 9 1 82394 8 0 0 3 72013 713 63 0 0 2 3 7 5 3 5 30.10 + 9 1 92394 9171310 720171710110 6 5 4 3 7 6 6 4 50.21 + 9 11023941030231010 3 0 310 90 15 9 4 4 2 0 2 4 50.21 + 9 11123941110 0 0 7 0 0 0 0 17 4 0 0 3 0 0 0 0 10.00 + 9 112239412 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 2 0 00.00 + 9 113239413102017 010101310 90 4 7 6 0 4 4 5 4 40.10 + 9 1142394142320101723 71313127 9 7 4 6 9 3 5 5 60.31 + 9 11523941513201013 7202323130 5 7 4 5 3 7 9 9 60.31 + 9 1162394162020 0 7 71310 0 77 7 7 0 3 3 5 4 0 40.10 + 9 117239417 3 710 3 31310 3 53 2 3 4 2 2 5 4 2 30.10 + 9 118239418 3 0 3 7 3 71010 43 2 0 2 3 2 3 4 4 20.00 + 9 119239419402323 710171723160 27 9 9 3 4 6 6 9 90.52 + 9 12023942020 7 7 3 3 02013 73 7 3 3 2 2 0 7 5 40.10 + 9 121239421 0 0 010 7202010 67 0 0 0 4 3 7 7 4 30.10 + 9 122239422 0 7 3 3 3 3 3 0 23 0 3 2 2 2 2 2 0 20.00 + 9 123239423 0 0 3 3 7 0 0 7 20 0 0 2 2 3 0 0 3 10.00 + 9 1242394241010 0 0 0 3 0 3 27 4 4 0 0 0 2 0 2 20.00 + 9 125239425 7 0 0 0 7 3 317 37 3 0 0 0 3 2 2 6 20.00 + 9 12623942633232720303317 3187 18 9 12 7 15 18 6 2 110.63 + 9 127239427 310 3 3 3172017 77 2 4 2 2 2 6 7 6 40.10 + 9 1282395 1 0 0 010 7 7 3 7 33 0 0 0 4 3 3 2 3 20.00 + 9 1292395 2 020231313 3 3 0 77 0 7 9 5 5 2 2 0 40.10 + 9 1302395 3 313 310 3 31320 70 2 5 2 4 2 2 5 7 40.10 + 9 1312395 41310231727132020143 5 4 9 6 12 5 7 7 70.31 + 9 2 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3 0 320 7 50 4 3 0 2 0 2 7 3 30.00 + 912222407 5 3 0 3 3 3 71713 50 2 0 2 2 2 3 6 5 30.00 + 912232407 6 31013 7 7 7 713 67 2 4 5 3 3 3 3 5 40.10 + 912242407 7 710 7 3 3 3 0 3 37 3 4 3 2 2 2 0 2 20.00 + 912252407 8 0 0 3 310102023 70 0 0 2 2 4 4 7 9 40.10 + 912262407 9172010 7 317 3 0 77 6 7 4 3 2 6 2 0 40.10 + 91227240710 0 3 3101310 3 0 43 0 2 2 4 5 4 2 0 20.00 + 91228240711 0 0 0 7 0 7 3 0 17 0 0 0 3 0 3 2 0 10.00 + 91229240712 0 0 3 0 0 0 0 0 3 0 0 2 0 0 0 0 0 00.00 + 91230240713 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00.00 + 91231240714 0 0 0 0 3 0 0 0 3 0 0 0 0 2 0 0 0 00.00 diff --git a/GeospaceDataManagement/tests/test_data/Kp_now2020.wdc b/GeospaceDataManagement/tests/test_data/Kp_now2020.wdc new file mode 100644 index 0000000..d8a1b01 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/Kp_now2020.wdc @@ -0,0 +1,376 @@ +# DOI: https://doi.org/10.5880/Kp.0001 +# LICENCE: CC BY 4.0, please cite: +# Matzka, J., Bronkalla, O., Tornow, K., Elger, K. and Stolle, C., 2021. +# Geomagnetic Kp index. V. 1.0. GFZ Data Services, +# https://doi.org/10.5880/Kp.0001 +# Matzka, J., Stolle, C., Yamazaki, Y., Bronkalla, O. and Morschhauser, A., +# 2021. The geomagnetic Kp index and derived indices of geomagnetic activity. +# Space Weather, https://doi.org/10.1029/2020SW002641 +# The Kp index was introduced by Bartels (1949) and is produced by Geomagnetic +# Observatory Niemegk, GFZ German Research Centre for Geosciences. +20 1 1254222 0 0 0 7 7131010 47 0 0 0 3 3 5 4 4 20.00 +20 1 2254223 0 0 3 7 3 71013 43 0 0 2 3 2 3 4 5 20.00 +20 1 32542241010272310 7 313103 4 4 12 9 4 3 2 5 50.21 +20 1 425422513 7 71010202320110 5 3 3 4 4 7 9 7 50.21 +20 1 52542261313171020233323153 5 5 6 4 7 9 18 9 80.42 +20 1 6254227333017 7 0 72317133 18 15 6 3 0 3 9 6 80.42 +20 1 72543 11017 7 3 7101323 90 4 6 3 2 3 4 5 9 40.21 +20 1 82543 21010 3 717271723113 4 4 2 3 6 12 6 9 60.31 +20 1 92543 32730372320272017200 12 15 22 9 7 12 7 6 110.63 +20 1102543 41310272317171010127 5 4 12 9 6 6 4 4 60.31 +20 1112543 520202013 313 710107 7 7 7 5 2 5 3 4 50.21 +20 1122543 61717 7 7 7 0 3 3 60 6 6 3 3 3 0 2 2 30.10 +20 1132543 7 7 7 7 3 3 0 710 43 3 3 3 2 2 0 3 4 20.00 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01720171313 3 3 87 0 6 7 6 5 5 2 2 40.10 +2011302555 510333320 710 313130 4 18 18 7 3 4 2 5 80.42 +2012 12555 613 0 0 0 0 0 010 23 5 0 0 0 0 0 0 4 10.00 +2012 22555 713 713 7 0 0 3 7 50 5 3 5 3 0 0 2 3 30.00 +2012 32555 8 0 0 0 31017 3 0 33 0 0 0 2 4 6 2 0 20.00 +2012 42555 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00.00 +2012 5255510 0 0 31020102710 80 0 0 2 4 7 4 12 4 40.10 +2012 62555112010101017 71720110 7 4 4 4 6 3 6 7 50.21 +2012 7255512 7 0 7 7 0 3 0 0 23 3 0 3 3 0 2 0 0 10.00 +2012 8255513 713131310 0 313 73 3 5 5 5 4 0 2 5 40.10 +2012 9255514203020 7 0133013133 7 15 7 3 0 5 15 5 70.42 +201210255515332710 7 3 31323120 18 12 4 3 2 2 5 9 70.31 +20121125551630231310 3 71713117 15 9 5 4 2 3 6 5 60.31 +20121225551713 710 7 3 71017 73 5 3 4 3 2 3 4 6 40.10 +2012132555183010 0 0 7 31710 77 15 4 0 0 3 2 6 4 40.10 +201214255519 0 3 0 3 0 71313 40 0 2 0 2 0 3 5 5 20.00 +20121525552017 010 0 0 0 710 43 6 0 4 0 0 0 3 4 20.00 +20121625552110 3 0 0 3 3 3 7 30 4 2 0 0 2 2 2 3 20.00 +201217255522 7 3 0 0 0 3 0 3 17 3 2 0 0 0 2 0 2 10.00 +201218255523 3 0 3 3 3 7 3 3 27 2 0 2 2 2 3 2 2 20.00 +20121925552413 7132017 71310100 5 3 5 7 6 3 5 4 50.21 +20122025552510 713101010 313 77 4 3 5 4 4 4 2 5 40.10 +2012212555262033232317 72043187 7 18 9 9 6 3 7 32 110.73 +2012222555273333302727232713213 18 18 15 12 12 9 12 5 130.73 +2012232556 13043272720101317187 15 32 12 12 7 4 5 6 120.73 +2012242556 2 727202327301317163 3 12 7 9 12 15 5 6 90.52 +2012252556 3231710102010 0 0 90 9 6 4 4 7 4 0 0 40.10 +2012262556 4 02010 3 7 72020 87 0 7 4 2 3 3 7 7 40.10 +2012272556 51317 31713 71017 97 5 6 2 6 5 3 4 6 50.21 +2012282556 62023232320131313150 7 9 9 9 7 5 5 5 70.42 +2012292556 723271010 7131323127 9 12 4 4 3 5 5 9 60.31 +2012302556 82327172017 7 727143 9 12 6 7 6 3 3 12 70.42 +2012312556 92310 713 3 7 3 7 73 9 4 3 5 2 3 2 3 40.10 diff --git a/GeospaceDataManagement/tests/test_data/SN_2009-01.txt b/GeospaceDataManagement/tests/test_data/SN_2009-01.txt new file mode 100644 index 0000000..dda6945 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/SN_2009-01.txt @@ -0,0 +1 @@ +{"meta":{"source":"GFZ Potsdam","license":"CC BY 4.0"},"datetime":["2009-01-01T00:00:00Z","2009-01-02T00:00:00Z","2009-01-03T00:00:00Z","2009-01-04T00:00:00Z","2009-01-05T00:00:00Z","2009-01-06T00:00:00Z","2009-01-07T00:00:00Z","2009-01-08T00:00:00Z","2009-01-09T00:00:00Z","2009-01-10T00:00:00Z","2009-01-11T00:00:00Z","2009-01-12T00:00:00Z","2009-01-13T00:00:00Z","2009-01-14T00:00:00Z","2009-01-15T00:00:00Z","2009-01-16T00:00:00Z","2009-01-17T00:00:00Z","2009-01-18T00:00:00Z","2009-01-19T00:00:00Z","2009-01-20T00:00:00Z","2009-01-21T00:00:00Z","2009-01-22T00:00:00Z","2009-01-23T00:00:00Z","2009-01-24T00:00:00Z","2009-01-25T00:00:00Z","2009-01-26T00:00:00Z","2009-01-27T00:00:00Z","2009-01-28T00:00:00Z","2009-01-29T00:00:00Z","2009-01-30T00:00:00Z","2009-01-31T00:00:00Z","2009-02-01T00:00:00Z"],"SN":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,9.0,10.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],"SNstatus":["def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def","def"]} diff --git a/GeospaceDataManagement/tests/test_data/TYKW-NoRP_dailyflux.txt b/GeospaceDataManagement/tests/test_data/TYKW-NoRP_dailyflux.txt new file mode 100644 index 0000000..789b026 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/TYKW-NoRP_dailyflux.txt @@ -0,0 +1,7 @@ +TYKW-NoRP solar daily flux (1951-11-02 -- 1951-11-06) +Date,1 GHz,2 GHz,3.75 GHz,9.4 GHz +"1951-11-02",NaN,NaN,NaN,NaN +"1951-11-03",NaN,NaN,NaN,NaN +"1951-11-04",NaN,NaN,NaN,NaN +"1951-11-05",NaN,NaN,NaN,NaN +"1951-11-06",NaN,NaN,115.000,NaN diff --git a/GeospaceDataManagement/tests/test_data/ace-epam.txt b/GeospaceDataManagement/tests/test_data/ace-epam.txt new file mode 100644 index 0000000..9e3f590 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/ace-epam.txt @@ -0,0 +1,42 @@ +:Data_list: ace_epam_5m.txt +:Created: 2023 Nov 01 1731 UT +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# Units: Differential Flux particles/cm2-s-ster-MeV +# Units: Anisotropy Index 0.0 - 2.0 +# Status(S): 0 = nominal, 4,6,7,8 = bad data, unable to process, 9 = no data +# Missing data values: -1.00e+05, index = -1.00 +# Source: ACE Satellite - Electron, Proton, and Alpha Monitor +# +# +# 5-minute averaged Real-time Differential Electron and Proton Flux +# +# Modified Seconds ---------------------------- Differential Flux --------------------------- +# UT Date Time Julian of the ----- Electron ----- ------------------- Protons keV ------------------- Anis. +# YR MO DA HHMM Day Day S 38-53 175-315 S 47-68 115-195 310-580 795-1193 1060-1900 Index +#------------------------------------------------------------------------------------------------------------------- +2023 11 01 1530 60249 55800 0 3.97e+03 1.63e+01 0 4.91e+03 3.40e+02 6.26e+01 2.15e+01 5.51e+00 -1.00 +2023 11 01 1535 60249 56100 0 3.90e+03 1.35e+01 0 5.26e+03 3.61e+02 6.54e+01 1.95e+01 5.26e+00 -1.00 +2023 11 01 1540 60249 56400 0 3.67e+03 1.37e+01 0 5.23e+03 3.88e+02 7.22e+01 2.08e+01 5.92e+00 -1.00 +2023 11 01 1545 60249 56700 0 3.60e+03 1.39e+01 0 5.28e+03 4.09e+02 7.04e+01 1.93e+01 6.16e+00 -1.00 +2023 11 01 1550 60249 57000 0 3.70e+03 1.34e+01 0 5.21e+03 3.97e+02 6.81e+01 1.95e+01 6.39e+00 -1.00 +2023 11 01 1555 60249 57300 0 3.77e+03 1.31e+01 0 5.59e+03 3.95e+02 6.53e+01 1.98e+01 6.52e+00 -1.00 +2023 11 01 1600 60249 57600 0 3.72e+03 1.31e+01 0 5.21e+03 3.11e+02 5.62e+01 2.19e+01 4.94e+00 -1.00 +2023 11 01 1605 60249 57900 0 4.14e+03 1.28e+01 0 4.86e+03 3.30e+02 5.89e+01 2.13e+01 4.95e+00 -1.00 +2023 11 01 1610 60249 58200 0 4.22e+03 1.80e+01 0 5.22e+03 3.35e+02 6.05e+01 2.24e+01 5.62e+00 -1.00 +2023 11 01 1615 60249 58500 0 4.13e+03 1.53e+01 0 5.06e+03 3.21e+02 6.09e+01 2.14e+01 5.57e+00 -1.00 +2023 11 01 1620 60249 58800 0 3.74e+03 9.66e+00 0 4.91e+03 3.49e+02 6.16e+01 2.36e+01 6.00e+00 -1.00 +2023 11 01 1625 60249 59100 0 3.41e+03 2.13e+01 0 4.76e+03 3.46e+02 6.78e+01 1.72e+01 7.23e+00 -1.00 +2023 11 01 1630 60249 59400 9 -1.00e+05 -1.00e+05 0 5.36e+03 3.32e+02 5.52e+01 1.46e+01 6.49e+00 -1.00 +2023 11 01 1635 60249 59700 0 3.86e+03 1.23e+01 0 5.16e+03 3.39e+02 6.06e+01 2.37e+01 6.02e+00 -1.00 +2023 11 01 1640 60249 60000 0 3.65e+03 1.77e+01 0 4.97e+03 3.31e+02 6.25e+01 2.29e+01 5.72e+00 -1.00 +2023 11 01 1645 60249 60300 0 3.77e+03 1.70e+01 0 4.60e+03 3.56e+02 6.35e+01 2.85e+01 4.24e+00 -1.00 +2023 11 01 1650 60249 60600 0 3.57e+03 1.28e+01 0 4.94e+03 3.96e+02 6.15e+01 2.50e+01 6.18e+00 -1.00 +2023 11 01 1655 60249 60900 0 3.50e+03 1.65e+01 0 4.77e+03 3.21e+02 6.24e+01 1.99e+01 5.02e+00 -1.00 +2023 11 01 1700 60249 61200 0 4.15e+03 1.12e+01 0 5.43e+03 3.59e+02 6.32e+01 2.17e+01 5.51e+00 -1.00 +2023 11 01 1705 60249 61500 0 3.73e+03 1.60e+01 0 5.11e+03 3.52e+02 6.38e+01 1.99e+01 5.50e+00 -1.00 +2023 11 01 1710 60249 61800 0 3.44e+03 1.71e+01 0 5.15e+03 3.66e+02 6.57e+01 2.10e+01 5.37e+00 -1.00 +2023 11 01 1715 60249 62100 0 3.71e+03 1.11e+01 0 4.91e+03 3.39e+02 6.19e+01 2.07e+01 5.53e+00 -1.00 +2023 11 01 1720 60249 62400 0 3.90e+03 1.54e+01 0 5.19e+03 3.45e+02 6.20e+01 2.03e+01 5.56e+00 -1.00 +2023 11 01 1725 60249 62700 0 3.63e+03 1.11e+01 0 5.16e+03 3.16e+02 5.66e+01 2.10e+01 5.39e+00 -1.00 diff --git a/GeospaceDataManagement/tests/test_data/ace-magnetometer.txt b/GeospaceDataManagement/tests/test_data/ace-magnetometer.txt new file mode 100644 index 0000000..bd2af0d --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/ace-magnetometer.txt @@ -0,0 +1,139 @@ +:Data_list: ace_mag_1m.txt +:Created: 2023 Nov 01 1741 UT +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# Magnetometer values are in GSM coordinates. +# +# Units: Bx, By, Bz, Bt in nT +# Units: Latitude degrees +/- 90.0 +# Units: Longitude degrees 0.0 - 360.0 +# Status(S): 0 = nominal data, 1 to 8 = bad data record, 9 = no data +# Missing data values: -999.9 +# Source: ACE Satellite - Magnetometer +# +# 1-minute averaged Real-time Interplanetary Magnetic Field Values +# +# Modified Seconds +# UT Date Time Julian of the ---------------- GSM Coordinates --------------- +# YR MO DA HHMM Day Day S Bx By Bz Bt Lat. Long. +#------------------------------------------------------------------------------------ +2023 11 01 1541 60249 56460 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1542 60249 56520 0 -4.1 -0.2 -1.1 4.3 -14.8 182.8 +2023 11 01 1543 60249 56580 0 -4.1 -0.0 -1.1 4.3 -15.2 180.2 +2023 11 01 1544 60249 56640 0 -4.1 -0.2 -1.3 4.3 -16.9 182.4 +2023 11 01 1545 60249 56700 0 -4.2 -0.3 -1.3 4.4 -17.2 184.1 +2023 11 01 1546 60249 56760 0 -4.2 -0.0 -1.4 4.4 -18.3 180.5 +2023 11 01 1547 60249 56820 0 -4.1 -0.2 -1.4 4.4 -19.3 183.3 +2023 11 01 1548 60249 56880 0 -4.2 0.5 -1.3 4.4 -16.8 173.0 +2023 11 01 1549 60249 56940 0 -4.0 0.7 -1.0 4.2 -13.8 169.8 +2023 11 01 1550 60249 57000 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1551 60249 57060 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1552 60249 57120 0 -3.3 -1.3 -2.4 4.3 -34.2 201.3 +2023 11 01 1553 60249 57180 0 -3.1 -1.6 -2.5 4.2 -35.3 207.7 +2023 11 01 1554 60249 57240 0 -3.0 -1.8 -2.3 4.2 -33.1 211.7 +2023 11 01 1555 60249 57300 0 -2.8 -2.0 -2.3 4.2 -34.4 215.3 +2023 11 01 1556 60249 57360 0 -2.4 -2.0 -2.5 4.0 -38.4 219.7 +2023 11 01 1557 60249 57420 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1558 60249 57480 0 -2.3 -1.6 -2.9 4.0 -45.8 215.9 +2023 11 01 1559 60249 57540 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1600 60249 57600 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1601 60249 57660 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1602 60249 57720 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1603 60249 57780 0 0.9 3.5 1.0 3.7 15.4 76.2 +2023 11 01 1604 60249 57840 0 0.5 3.6 0.3 3.6 5.3 81.3 +2023 11 01 1605 60249 57900 0 0.6 3.5 0.3 3.6 5.4 80.1 +2023 11 01 1606 60249 57960 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1607 60249 58020 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1608 60249 58080 0 0.4 2.8 2.0 3.5 35.4 82.0 +2023 11 01 1609 60249 58140 0 -0.2 3.2 1.6 3.6 26.9 93.4 +2023 11 01 1610 60249 58200 0 -0.5 3.3 1.7 3.7 26.4 98.2 +2023 11 01 1611 60249 58260 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1612 60249 58320 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1613 60249 58380 0 -0.5 3.4 1.7 3.8 25.8 98.1 +2023 11 01 1614 60249 58440 0 -0.9 3.7 1.4 4.1 20.4 103.6 +2023 11 01 1615 60249 58500 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1616 60249 58560 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1617 60249 58620 0 0.1 3.8 0.9 3.9 12.8 88.0 +2023 11 01 1618 60249 58680 0 -0.2 4.0 0.9 4.1 12.2 93.1 +2023 11 01 1619 60249 58740 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1620 60249 58800 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1621 60249 58860 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1622 60249 58920 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1623 60249 58980 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1624 60249 59040 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1625 60249 59100 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1626 60249 59160 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1627 60249 59220 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1628 60249 59280 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1629 60249 59340 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1630 60249 59400 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1631 60249 59460 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1632 60249 59520 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1633 60249 59580 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1634 60249 59640 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1635 60249 59700 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1636 60249 59760 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1637 60249 59820 0 -0.2 3.6 -1.0 3.7 -15.9 93.4 +2023 11 01 1638 60249 59880 0 -1.1 3.3 0.4 3.5 6.2 108.4 +2023 11 01 1639 60249 59940 0 -1.6 3.6 0.9 4.0 13.0 114.4 +2023 11 01 1640 60249 60000 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1641 60249 60060 0 -1.8 3.4 -0.7 3.9 -11.1 117.7 +2023 11 01 1642 60249 60120 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1643 60249 60180 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1644 60249 60240 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1645 60249 60300 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1646 60249 60360 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1647 60249 60420 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1648 60249 60480 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1649 60249 60540 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1650 60249 60600 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1651 60249 60660 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1652 60249 60720 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1653 60249 60780 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1654 60249 60840 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1655 60249 60900 0 -2.1 2.4 1.3 3.5 22.1 131.1 +2023 11 01 1656 60249 60960 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1657 60249 61020 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1658 60249 61080 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1659 60249 61140 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1700 60249 61200 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1701 60249 61260 9 -999.9 -999.9 -999.9 -999.9 -999.9 -999.9 +2023 11 01 1702 60249 61320 0 -2.7 1.7 2.2 3.8 34.5 148.1 +2023 11 01 1703 60249 61380 0 -2.8 2.0 1.9 3.9 28.9 144.3 +2023 11 01 1704 60249 61440 0 -2.6 2.3 1.7 3.9 25.7 139.1 +2023 11 01 1705 60249 61500 0 -2.7 2.1 2.0 3.9 30.4 142.3 +2023 11 01 1706 60249 61560 0 -2.8 2.1 2.1 4.0 30.7 142.8 +2023 11 01 1707 60249 61620 0 -2.9 2.3 1.3 4.0 18.9 141.3 +2023 11 01 1708 60249 61680 0 -2.8 2.6 0.6 3.9 9.5 137.1 +2023 11 01 1709 60249 61740 0 -3.3 2.3 0.5 4.0 6.8 145.2 +2023 11 01 1710 60249 61800 0 -2.5 2.8 0.7 3.8 11.0 131.9 +2023 11 01 1711 60249 61860 0 -2.6 2.9 0.4 3.9 5.2 131.7 +2023 11 01 1712 60249 61920 0 -2.9 2.6 -0.0 3.9 -0.1 137.8 +2023 11 01 1713 60249 61980 0 -2.5 2.9 0.5 3.9 7.5 131.7 +2023 11 01 1714 60249 62040 0 -2.3 2.9 1.0 3.8 15.3 128.6 +2023 11 01 1715 60249 62100 0 -2.4 2.9 -0.1 3.8 -1.2 129.2 +2023 11 01 1716 60249 62160 0 -2.1 3.0 -0.5 3.7 -7.1 124.9 +2023 11 01 1717 60249 62220 0 -0.9 1.8 -3.2 3.8 -57.7 117.2 +2023 11 01 1718 60249 62280 0 -0.9 2.0 -3.1 3.9 -54.6 114.9 +2023 11 01 1719 60249 62340 0 -1.4 2.9 -2.2 3.9 -35.3 115.4 +2023 11 01 1720 60249 62400 0 -1.8 2.4 -2.6 3.9 -40.5 127.7 +2023 11 01 1721 60249 62460 0 -1.8 2.7 -2.0 3.8 -31.6 123.1 +2023 11 01 1722 60249 62520 0 -1.7 1.8 -2.2 3.3 -42.1 134.4 +2023 11 01 1723 60249 62580 0 -0.8 1.3 3.1 3.4 63.6 121.4 +2023 11 01 1724 60249 62640 0 -0.6 1.0 3.4 3.6 70.8 122.6 +2023 11 01 1725 60249 62700 0 -0.4 0.7 3.4 3.5 77.3 121.7 +2023 11 01 1726 60249 62760 0 -0.5 2.0 3.0 3.6 54.8 104.0 +2023 11 01 1727 60249 62820 0 -1.0 2.8 2.2 3.7 35.9 110.4 +2023 11 01 1728 60249 62880 0 -1.0 3.1 1.8 3.7 28.5 107.0 +2023 11 01 1729 60249 62940 0 -1.8 3.3 1.1 4.0 16.9 117.6 +2023 11 01 1730 60249 63000 0 -1.6 3.5 1.0 4.0 14.3 113.8 +2023 11 01 1731 60249 63060 0 -1.6 3.6 0.5 4.0 7.6 114.1 +2023 11 01 1732 60249 63120 0 -1.9 3.4 -1.1 4.0 -15.3 119.5 +2023 11 01 1733 60249 63180 0 -1.6 2.8 -2.1 3.9 -33.3 119.1 +2023 11 01 1734 60249 63240 0 -1.8 3.1 -1.1 3.8 -17.0 119.6 +2023 11 01 1735 60249 63300 0 -1.7 3.5 -0.0 3.9 -0.3 115.7 +2023 11 01 1736 60249 63360 0 -1.8 3.5 -0.3 3.9 -4.2 118.0 +2023 11 01 1737 60249 63420 0 -2.2 3.2 -0.2 3.9 -3.3 124.2 +2023 11 01 1738 60249 63480 0 -1.8 3.1 -1.0 3.7 -15.2 120.6 +2023 11 01 1739 60249 63540 0 -1.4 2.9 -2.1 3.9 -33.0 115.4 diff --git a/GeospaceDataManagement/tests/test_data/ace-sis.txt b/GeospaceDataManagement/tests/test_data/ace-sis.txt new file mode 100644 index 0000000..85de336 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/ace-sis.txt @@ -0,0 +1,40 @@ +:Data_list: ace_sis_5m.txt +:Created: 2023 Nov 01 1741 UT +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# Units: proton flux p/cs2-sec-ster +# Status(S): 0 = nominal data, 1 to 8 = bad data record, 9 = no data +# Missing data values: -1.00e+05 +# Source: ACE Satellite - Solar Isotope Spectrometer +# +# 5-minute averaged Real-time Integral Flux of High-energy Solar Protons +# +# Modified Seconds +# UT Date Time Julian of the ---- Integral Proton Flux ---- +# YR MO DA HHMM Day Day S > 10 MeV S > 30 MeV +#-------------------------------------------------------------------- +2023 11 01 1540 60249 56400 0 1.01e+00 0 7.14e-01 +2023 11 01 1545 60249 56700 0 9.73e-01 0 6.94e-01 +2023 11 01 1550 60249 57000 0 9.78e-01 0 6.89e-01 +2023 11 01 1555 60249 57300 0 9.69e-01 0 6.92e-01 +2023 11 01 1600 60249 57600 0 9.88e-01 0 6.95e-01 +2023 11 01 1605 60249 57900 0 1.00e+00 0 7.18e-01 +2023 11 01 1610 60249 58200 0 1.01e+00 0 7.27e-01 +2023 11 01 1615 60249 58500 0 1.03e+00 0 7.40e-01 +2023 11 01 1620 60249 58800 0 9.47e-01 0 6.94e-01 +2023 11 01 1625 60249 59100 9 -1.00e+05 9 -1.00e+05 +2023 11 01 1630 60249 59400 9 -1.00e+05 9 -1.00e+05 +2023 11 01 1635 60249 59700 0 1.01e+00 0 7.14e-01 +2023 11 01 1640 60249 60000 0 9.57e-01 0 6.70e-01 +2023 11 01 1645 60249 60300 9 -1.00e+05 9 -1.00e+05 +2023 11 01 1650 60249 60600 9 -1.00e+05 9 -1.00e+05 +2023 11 01 1655 60249 60900 9 -1.00e+05 9 -1.00e+05 +2023 11 01 1700 60249 61200 0 9.79e-01 0 6.93e-01 +2023 11 01 1705 60249 61500 0 9.58e-01 0 6.80e-01 +2023 11 01 1710 60249 61800 0 9.95e-01 0 7.05e-01 +2023 11 01 1715 60249 62100 0 9.74e-01 0 6.94e-01 +2023 11 01 1720 60249 62400 0 9.98e-01 0 7.10e-01 +2023 11 01 1725 60249 62700 0 1.01e+00 0 7.08e-01 +2023 11 01 1730 60249 63000 0 9.70e-01 0 6.83e-01 +2023 11 01 1735 60249 63300 0 9.84e-01 0 6.96e-01 diff --git a/GeospaceDataManagement/tests/test_data/ace-swepam.txt b/GeospaceDataManagement/tests/test_data/ace-swepam.txt new file mode 100644 index 0000000..5cadc21 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/ace-swepam.txt @@ -0,0 +1,137 @@ +:Data_list: ace_swepam_1m.txt +:Created: 2023 Nov 01 1742 UT +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# Units: Proton density p/cc +# Units: Bulk speed km/s +# Units: Ion tempeture degrees K +# Status(S): 0 = nominal data, 1 to 8 = bad data record, 9 = no data +# Missing data values: Density and Speed = -9999.9, Temp. = -1.00e+05 +# Source: ACE Satellite - Solar Wind Electron Proton Alpha Monitor +# +# 1-minute averaged Real-time Bulk Parameters of the Solar Wind Plasma +# +# Modified Seconds ------------- Solar Wind ----------- +# UT Date Time Julian of the Proton Bulk Ion +# YR MO DA HHMM Day Day S Density Speed Temperature +#------------------------------------------------------------------------- +2023 11 01 1542 60249 56520 1 1.6 437.8 9.17e+04 +2023 11 01 1543 60249 56580 0 1.8 439.2 1.13e+05 +2023 11 01 1544 60249 56640 1 1.6 434.1 9.07e+04 +2023 11 01 1545 60249 56700 1 1.7 436.4 9.70e+04 +2023 11 01 1546 60249 56760 0 1.7 431.1 7.45e+04 +2023 11 01 1547 60249 56820 0 1.0 418.7 5.73e+04 +2023 11 01 1548 60249 56880 0 1.9 442.7 1.38e+05 +2023 11 01 1549 60249 56940 1 2.8 445.1 1.54e+05 +2023 11 01 1550 60249 57000 0 2.5 449.0 1.41e+05 +2023 11 01 1551 60249 57060 0 2.3 453.5 1.39e+05 +2023 11 01 1552 60249 57120 0 2.4 454.6 1.42e+05 +2023 11 01 1553 60249 57180 0 1.6 442.0 7.79e+04 +2023 11 01 1554 60249 57240 0 1.6 441.1 7.35e+04 +2023 11 01 1555 60249 57300 0 1.6 443.0 8.17e+04 +2023 11 01 1556 60249 57360 0 1.7 449.6 1.11e+05 +2023 11 01 1557 60249 57420 1 1.3 446.1 7.19e+04 +2023 11 01 1558 60249 57480 1 1.3 446.1 7.19e+04 +2023 11 01 1559 60249 57540 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1600 60249 57600 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1601 60249 57660 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1602 60249 57720 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1603 60249 57780 0 1.0 454.0 5.94e+04 +2023 11 01 1604 60249 57840 0 1.2 460.6 8.00e+04 +2023 11 01 1605 60249 57900 0 1.5 457.8 5.49e+04 +2023 11 01 1606 60249 57960 0 2.1 469.7 7.56e+04 +2023 11 01 1607 60249 58020 0 2.4 476.5 9.14e+04 +2023 11 01 1608 60249 58080 0 2.5 485.2 1.15e+05 +2023 11 01 1609 60249 58140 0 1.8 468.2 8.24e+04 +2023 11 01 1610 60249 58200 0 1.3 456.8 6.37e+04 +2023 11 01 1611 60249 58260 0 1.9 471.0 1.04e+05 +2023 11 01 1612 60249 58320 0 2.2 475.3 1.30e+05 +2023 11 01 1613 60249 58380 0 1.5 455.7 5.44e+04 +2023 11 01 1614 60249 58440 0 1.5 455.7 5.44e+04 +2023 11 01 1615 60249 58500 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1616 60249 58560 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1617 60249 58620 0 1.4 453.9 3.91e+04 +2023 11 01 1618 60249 58680 0 1.6 463.0 6.35e+04 +2023 11 01 1619 60249 58740 0 1.7 463.7 6.52e+04 +2023 11 01 1620 60249 58800 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1621 60249 58860 0 1.4 449.4 3.94e+04 +2023 11 01 1622 60249 58920 0 1.4 449.4 3.94e+04 +2023 11 01 1623 60249 58980 0 2.0 458.0 5.09e+04 +2023 11 01 1624 60249 59040 0 2.0 458.0 5.09e+04 +2023 11 01 1625 60249 59100 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1626 60249 59160 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1627 60249 59220 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1628 60249 59280 0 0.6 432.3 1.96e+04 +2023 11 01 1629 60249 59340 0 0.6 432.3 1.96e+04 +2023 11 01 1630 60249 59400 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1631 60249 59460 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1632 60249 59520 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1633 60249 59580 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1634 60249 59640 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1635 60249 59700 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1636 60249 59760 0 1.2 447.3 3.66e+04 +2023 11 01 1637 60249 59820 0 1.2 447.3 3.66e+04 +2023 11 01 1638 60249 59880 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1639 60249 59940 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1640 60249 60000 0 3.3 470.8 1.21e+05 +2023 11 01 1641 60249 60060 0 3.3 470.8 1.21e+05 +2023 11 01 1642 60249 60120 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1643 60249 60180 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1644 60249 60240 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1645 60249 60300 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1646 60249 60360 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1647 60249 60420 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1648 60249 60480 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1649 60249 60540 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1650 60249 60600 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1651 60249 60660 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1652 60249 60720 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1653 60249 60780 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1654 60249 60840 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1655 60249 60900 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1656 60249 60960 0 1.1 436.9 4.04e+04 +2023 11 01 1657 60249 61020 0 1.1 436.9 4.04e+04 +2023 11 01 1658 60249 61080 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1659 60249 61140 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1700 60249 61200 9 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1701 60249 61260 1 1.2 428.8 4.27e+04 +2023 11 01 1702 60249 61320 1 1.3 431.4 5.09e+04 +2023 11 01 1703 60249 61380 0 1.4 448.2 1.01e+05 +2023 11 01 1704 60249 61440 0 1.3 447.6 6.73e+04 +2023 11 01 1705 60249 61500 0 1.6 449.8 9.80e+04 +2023 11 01 1706 60249 61560 0 1.6 449.8 9.80e+04 +2023 11 01 1707 60249 61620 3 -9999.9 -9999.9 -1.00e+05 +2023 11 01 1708 60249 61680 0 0.8 416.2 3.10e+04 +2023 11 01 1709 60249 61740 1 2.1 443.0 1.40e+05 +2023 11 01 1710 60249 61800 1 2.2 443.0 1.24e+05 +2023 11 01 1711 60249 61860 0 2.0 438.8 8.62e+04 +2023 11 01 1712 60249 61920 1 2.0 438.5 8.64e+04 +2023 11 01 1713 60249 61980 1 2.1 439.4 9.51e+04 +2023 11 01 1714 60249 62040 1 2.0 443.7 8.89e+04 +2023 11 01 1715 60249 62100 0 1.7 447.5 7.30e+04 +2023 11 01 1716 60249 62160 0 1.9 448.7 7.50e+04 +2023 11 01 1717 60249 62220 0 2.1 453.3 8.96e+04 +2023 11 01 1718 60249 62280 0 1.7 458.9 7.30e+04 +2023 11 01 1719 60249 62340 0 1.8 457.0 5.98e+04 +2023 11 01 1720 60249 62400 0 2.2 449.6 6.27e+04 +2023 11 01 1721 60249 62460 0 1.8 450.3 6.75e+04 +2023 11 01 1722 60249 62520 0 1.6 452.0 8.20e+04 +2023 11 01 1723 60249 62580 0 1.7 450.0 8.44e+04 +2023 11 01 1724 60249 62640 0 1.4 457.7 6.44e+04 +2023 11 01 1725 60249 62700 0 1.3 462.1 5.61e+04 +2023 11 01 1726 60249 62760 0 1.2 461.3 6.12e+04 +2023 11 01 1727 60249 62820 0 1.2 460.4 5.94e+04 +2023 11 01 1728 60249 62880 0 1.3 459.6 5.89e+04 +2023 11 01 1729 60249 62940 0 1.6 454.0 6.35e+04 +2023 11 01 1730 60249 63000 0 1.8 449.3 6.38e+04 +2023 11 01 1731 60249 63060 0 2.1 453.6 7.05e+04 +2023 11 01 1732 60249 63120 0 2.8 459.7 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diff --git a/GeospaceDataManagement/tests/test_data/ap60_2009-01.txt b/GeospaceDataManagement/tests/test_data/ap60_2009-01.txt new file mode 100644 index 0000000..5c27871 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/ap60_2009-01.txt @@ -0,0 +1 @@ +{"meta":{"source":"GFZ Potsdam","license":"CC BY 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+2023/305-18:21:23 24.4 +2023/305-18:31:23 23.4 +2023/305-18:41:23 24.5 +2023/305-18:51:23 28.0 +2023/305-19:01:23 32.5 +2023/305-19:11:23 36.8 +2023/305-19:21:23 39.7 +2023/305-19:31:23 40.3 +2023/305-19:41:23 38.4 +2023/305-19:51:23 36.3 +2023/305-20:01:23 36.6 +2023/305-20:11:23 38.9 +2023/305-20:21:23 41.9 +2023/305-20:31:23 49.8 diff --git a/GeospaceDataManagement/tests/test_data/daily-geomagnetic-indices.txt b/GeospaceDataManagement/tests/test_data/daily-geomagnetic-indices.txt new file mode 100644 index 0000000..39c45e8 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/daily-geomagnetic-indices.txt @@ -0,0 +1,42 @@ +:Product: Daily Geomagnetic Data DGD.txt +:Issued: 1530 UT 01 Nov 2023 +# +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comment and suggestions to SWPC.Webmaster@noaa.gov +# +# Last 30 Days Daily Geomagnetic Data +# +# +# Middle Latitude High Latitude Estimated +# - Fredericksburg - ---- College ---- --- Planetary --- +# Date A K-indices A K-indices A K-indices +2023 10 03 6 1 2 2 1 3 2 1 1 19 2 0 2 4 5 5 3 0 8 1.33 2.67 1.67 1.33 2.33 2.33 2.33 1.67 +2023 10 04 8 2 2 2 2 2 1 2 3 19 1 1 5 5 4 2 2 2 10 2.67 2.33 2.67 2.67 2.00 1.67 2.00 3.33 +2023 10 05 11 3 4 2 3 2 1 2 2 22 3 4 3 6 4 1 1 2 16 4.33 5.00 2.33 3.00 2.00 1.00 1.33 2.33 +2023 10 06 7 2 2 2 2 1 2 1 3 10 2 3 4 1 2 3 0 2 9 2.33 2.67 2.33 1.67 1.33 1.67 1.00 3.33 +2023 10 07 -1 1 2-1-1-1-1-1-1 2 1 1 1 0 0 0 1 0 5 1.33 2.00 1.33 0.67 0.33 0.33 1.67 1.67 +2023 10 08 -1 -1-1-1-1-1-1-1-1 7 1 2 3 3 1 1 1 1 7 2.00 2.00 2.33 1.67 0.67 1.00 1.67 2.67 +2023 10 09 -1 -1-1-1-1-1-1-1-1 14 0 0 4 4 4 3 3 1 8 2.33 1.33 2.00 1.67 2.00 2.00 3.33 1.67 +2023 10 10 -1 -1-1-1-1-1-1-1-1 4 1 2 1 3 0 0 0 0 4 1.00 2.00 1.67 1.67 0.33 0.67 0.67 0.33 +2023 10 11 3 -1-1-1-1-1 0 1 2 2 0 0 1 2 1 0 0 0 4 0.67 0.67 1.33 1.33 1.00 1.00 0.67 1.00 +2023 10 12 3 -1 1 1 1 2 1 0 1 0 0 0 0 0 0 0 0 0 4 1.33 1.00 1.33 1.00 0.67 1.00 0.67 1.00 +2023 10 13 11 -1 1 3 2 3 3 3 2 15 0 3 3 3 4 4 3 1 13 1.00 2.67 3.33 2.67 3.00 3.67 2.67 2.33 +2023 10 14 6 1 1 1 3 2 1 2 1 5 1 1 1 3 1 0 2 1 8 2.00 1.67 2.00 3.00 1.67 1.00 2.67 1.00 +2023 10 15 2 0 0 1 1 1 1 1 1 1 0 0 0 1 1 0 0 0 4 0.67 0.33 1.00 0.67 0.67 0.67 1.00 2.00 +2023 10 16 3 2 0 1 1 2 1 0 0 0 0 0 0 0 0 0 0 0 4 2.00 0.33 0.67 1.00 1.33 0.67 0.33 0.33 +2023 10 17 2 0 0 0 0 2 1 1 1 0 0 0 0 0 0 0 0 0 3 0.67 0.33 0.67 1.00 1.00 0.33 0.00 0.67 +2023 10 18 8 0 2 2 2 3 3 2 2 12 0 1 0 3 5 4 1 1 9 0.33 2.00 1.33 2.33 3.00 3.00 2.33 2.33 +2023 10 19 8 2 3 2 3 2 1 1 1 24 2 4 4 6 3 4 2 1 10 2.67 3.67 2.33 2.67 1.67 1.67 1.67 1.00 +2023 10 20 8 2 2 2 2 2 1 2 3 10 1 1 3 4 3 1 1 2 8 1.33 2.33 2.33 2.33 2.00 1.00 2.33 2.67 +2023 10 21 13 3 3 4 4 2 2 1 1 39 3 5 6 6 4 5 2 2 22 4.00 4.67 5.00 3.33 2.67 3.33 1.67 1.00 +2023 10 22 7 2 1 2 2 1 2 3 1 17 1 1 4 5 4 3 2 2 8 2.33 1.67 2.33 2.33 1.33 1.67 3.00 1.67 +2023 10 23 2 1 0 0 0 1 1 0 1 1 1 0 0 0 1 1 0 0 3 1.00 0.33 0.33 0.33 1.00 0.67 0.67 0.67 +2023 10 24 2 1 0 0 1 1 1 1 1 3 1 0 1 2 0 1 1 1 4 0.33 0.33 0.67 1.33 0.67 1.00 1.33 1.33 +2023 10 25 3 1 0 0 1 2 1 1 1 2 0 0 0 1 1 1 1 0 4 0.67 1.00 0.33 0.67 1.00 0.67 1.33 1.67 +2023 10 26 18 2 2 2 4 4 3 4 4 29 1 2 1 6 6 5 2 1 23 2.67 2.67 2.00 4.67 4.00 3.33 4.33 4.67 +2023 10 27 9 3 4 2 2 2 1 1 1 33 3 5 4 5 3 3 3 6 11 3.33 4.00 2.67 2.33 1.67 1.67 1.33 1.00 +2023 10 28 13 1 2 2 4 4 2 2 3 86 6 6 7 7 7 6 3 3 19 1.00 3.00 3.33 4.00 4.33 3.33 3.00 3.67 +2023 10 29 21 4 3 4 4 4 3 3 3 49 4 5 6 6 6 5 3 3 28 4.67 3.67 4.67 3.67 4.00 4.00 3.33 4.00 +2023 10 30 10 3 2 1 3 3 2 2 2 31 5 2 1 6 6 3 2 2 12 4.00 2.00 1.33 3.33 3.33 1.67 2.33 2.33 +2023 10 31 6 2 2 1 2 2 2 1 1 18 2 2 3 5 5 3 1 1 9 2.67 2.33 2.00 2.67 2.67 1.33 1.67 2.00 +2023 11 01 -1 2 2 1 2 2-1-1-1 -1 1 2 3 4 4-1-1-1 9 2.33 2.67 2.33 2.67 2.33 -1.00 -1.00 -1.00 diff --git a/GeospaceDataManagement/tests/test_data/daily-solar-indices.txt b/GeospaceDataManagement/tests/test_data/daily-solar-indices.txt new file mode 100644 index 0000000..6a5f335 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/daily-solar-indices.txt @@ -0,0 +1,43 @@ +:Product: Daily Solar Data DSD.txt +:Issued: 1425 UT 01 Nov 2023 +# +# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center +# Please send comments and suggestions to SWPC.Webmaster@noaa.gov +# +# Last 30 Days Daily Solar Data +# +# Sunspot Stanford GOES15 +# Radio SESC Area Solar X-Ray ------ Flares ------ +# Flux Sunspot 10E-6 New Mean Bkgd X-Ray Optical +# Date 10.7cm Number Hemis. Regions Field Flux C M X S 1 2 3 +#--------------------------------------------------------------------------- +2023 10 02 158 146 810 1 -999 * 11 1 0 11 1 0 0 +2023 10 03 154 150 530 1 -999 * 14 0 0 14 0 0 0 +2023 10 04 155 151 630 1 -999 * 6 0 0 4 0 0 0 +2023 10 05 156 179 580 2 -999 * 10 0 0 9 0 0 0 +2023 10 06 155 138 460 0 -999 * 5 0 0 4 0 0 0 +2023 10 07 157 145 490 1 -999 * 9 1 0 11 0 0 0 +2023 10 08 157 149 570 2 -999 * 7 0 0 13 0 0 0 +2023 10 09 166 129 495 1 -999 * 16 0 0 23 1 0 0 +2023 10 10 164 120 560 1 -999 * 8 2 0 9 1 0 0 +2023 10 11 158 149 805 2 -999 * 8 0 0 6 0 0 0 +2023 10 12 157 126 580 0 -999 * 3 1 0 8 0 0 0 +2023 10 13 149 91 440 0 -999 * 5 0 0 11 0 0 0 +2023 10 14 148 100 490 1 -999 * 2 0 0 2 0 0 0 +2023 10 15 145 92 510 0 -999 * 3 0 0 4 0 0 0 +2023 10 16 144 106 430 1 -999 * 7 0 0 3 0 0 0 +2023 10 17 137 57 440 0 -999 * 2 0 0 3 0 0 0 +2023 10 18 135 54 330 0 -999 * 0 0 0 0 0 0 0 +2023 10 19 129 39 220 0 -999 * 8 0 0 1 0 0 0 +2023 10 20 126 56 180 1 -999 * 5 0 0 1 0 0 0 +2023 10 21 123 65 160 1 -999 * 2 0 0 0 0 0 0 +2023 10 22 119 48 90 1 -999 * 0 0 0 0 0 0 0 +2023 10 23 122 25 70 0 -999 * 2 0 0 4 0 0 0 +2023 10 24 121 34 40 0 -999 * 3 0 0 0 0 0 0 +2023 10 25 126 26 60 0 -999 * 10 0 0 1 0 0 0 +2023 10 26 126 57 90 2 -999 * 9 1 0 3 0 0 0 +2023 10 27 128 66 60 1 -999 * 1 0 0 0 0 0 0 +2023 10 28 128 70 80 1 -999 * 3 0 0 4 0 0 0 +2023 10 29 135 61 70 0 -999 * 8 0 0 5 0 0 0 +2023 10 30 140 62 220 0 -999 * 2 0 0 4 0 0 0 +2023 10 31 147 116 670 2 -999 * 7 0 0 1 0 0 0 diff --git a/GeospaceDataManagement/tests/test_data/dst_last_96_hrs.txt b/GeospaceDataManagement/tests/test_data/dst_last_96_hrs.txt new file mode 100644 index 0000000..1d64869 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/dst_last_96_hrs.txt @@ -0,0 +1,575 @@ + Time Predicted Dst +2023/301-21:10:16 -40.5 +2023/301-21:20:59 -39.9 +2023/301-21:30:56 -39.8 +2023/301-21:40:19 -41.0 +2023/301-21:49:52 -41.1 +2023/301-21:59:32 -41.6 +2023/301-22:09:00 -42.8 +2023/301-22:18:46 -43.0 +2023/301-22:28:40 -42.5 +2023/301-22:38:23 -42.0 +2023/301-22:48:07 -42.3 +2023/301-22:58:22 -44.2 +2023/301-23:09:04 -45.0 +2023/301-23:18:47 -43.7 +2023/301-23:27:44 -42.6 +2023/301-23:37:15 -40.3 +2023/301-23:46:57 -40.9 +2023/301-23:56:35 -43.2 +2023/302-00:05:58 -45.4 +2023/302-00:15:13 -47.8 +2023/302-00:24:46 -49.8 +2023/302-00:34:39 -50.3 +2023/302-00:44:41 -50.4 +2023/302-00:53:52 -50.4 +2023/302-01:03:19 -51.2 +2023/302-01:13:54 -51.7 +2023/302-01:25:02 -49.9 +2023/302-01:35:49 -47.6 +2023/302-01:45:21 -48.5 +2023/302-01:54:29 -51.3 +2023/302-02:04:04 -52.6 +2023/302-02:14:16 -52.1 +2023/302-02:24:34 -50.0 +2023/302-02:34:32 -47.0 +2023/302-02:44:18 -44.6 +2023/302-02:53:49 -43.8 +2023/302-03:03:59 -44.3 +2023/302-03:14:38 -45.3 +2023/302-03:24:15 -44.8 +2023/302-03:34:02 -43.4 +2023/302-03:44:28 -42.7 +2023/302-03:54:38 -42.6 +2023/302-04:04:32 -43.3 +2023/302-04:14:01 -45.4 +2023/302-04:23:39 -47.7 +2023/302-04:33:49 -48.7 +2023/302-04:44:09 -48.3 +2023/302-04:53:42 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"2009-01-07T00:00:00.000", "f107_adjusted": 66.7, "f107_observed": 69.0}, +{"time": "2009-01-08T00:00:00.000", "f107_adjusted": 66.5, "f107_observed": 68.7}, +{"time": "2009-01-09T00:00:00.000", "f107_adjusted": 67.4, "f107_observed": 69.7}, +{"time": "2009-01-10T00:00:00.000", "f107_adjusted": 68.5, "f107_observed": 70.9}, +{"time": "2009-01-11T00:00:00.000", "f107_adjusted": 67.7, "f107_observed": 70.0}, +{"time": "2009-01-12T00:00:00.000", "f107_adjusted": 67.0, "f107_observed": 69.3}, +{"time": "2009-01-13T00:00:00.000", "f107_adjusted": 68.2, "f107_observed": 70.5}, +{"time": "2009-01-14T00:00:00.000", "f107_adjusted": 68.9, "f107_observed": 71.2}, +{"time": "2009-01-15T00:00:00.000", "f107_adjusted": 68.8, "f107_observed": 71.1}, +{"time": "2009-01-16T00:00:00.000", "f107_adjusted": 68.5, "f107_observed": 70.8}, +{"time": "2009-01-17T00:00:00.000", "f107_adjusted": 69.6, "f107_observed": 71.9}, +{"time": "2009-01-18T00:00:00.000", "f107_adjusted": 68.8, "f107_observed": 71.1}, +{"time": "2009-01-19T00:00:00.000", "f107_adjusted": 68.6, "f107_observed": 70.8}, +{"time": "2009-01-20T00:00:00.000", "f107_adjusted": 68.1, "f107_observed": 70.4}, +{"time": "2009-01-21T00:00:00.000", "f107_adjusted": 67.2, "f107_observed": 69.4}, +{"time": "2009-01-22T00:00:00.000", "f107_adjusted": 66.9, "f107_observed": 69.0}, +{"time": "2009-01-23T00:00:00.000", "f107_adjusted": 67.8, "f107_observed": 70.0}, +{"time": "2009-01-24T00:00:00.000", "f107_adjusted": 66.6, "f107_observed": 68.8}, +{"time": "2009-01-25T00:00:00.000", "f107_adjusted": 67.7, "f107_observed": 69.8}, +{"time": "2009-01-26T00:00:00.000", "f107_adjusted": 67.8, "f107_observed": 69.9}, +{"time": "2009-01-27T00:00:00.000", "f107_adjusted": 67.6, "f107_observed": 69.7}, +{"time": "2009-01-28T00:00:00.000", "f107_adjusted": 67.4, "f107_observed": 69.5}, +{"time": "2009-01-29T00:00:00.000", "f107_adjusted": 67.3, "f107_observed": 69.3}, +{"time": "2009-01-30T00:00:00.000", "f107_adjusted": 67.1, "f107_observed": 69.1}, +{"time": "2009-01-31T00:00:00.000", "f107_adjusted": 67.4, "f107_observed": 69.4}] +}} diff --git a/GeospaceDataManagement/tests/test_data/mgii_composite_1981-11.txt b/GeospaceDataManagement/tests/test_data/mgii_composite_1981-11.txt new file mode 100644 index 0000000..a2f0cab --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/mgii_composite_1981-11.txt @@ -0,0 +1,32 @@ +{"composite_mg_index": { +"samples": [{"time": "1981-11-01T12:00:00.000", "mg_index": 0.28507999}, +{"time": "1981-11-02T12:00:00.000", "mg_index": 0.28593001}, +{"time": "1981-11-03T12:00:00.000", "mg_index": 0.28575}, +{"time": "1981-11-04T12:00:00.000", "mg_index": 0.28606001}, +{"time": "1981-11-05T12:00:00.000", "mg_index": 0.28619}, +{"time": "1981-11-06T12:00:00.000", "mg_index": 0.28536999}, +{"time": "1981-11-07T12:00:00.000", "mg_index": 0.28512999}, +{"time": "1981-11-08T12:00:00.000", "mg_index": 0.28494999}, +{"time": "1981-11-09T12:00:00.000", "mg_index": 0.28479999}, +{"time": "1981-11-10T12:00:00.000", "mg_index": 0.28476}, +{"time": "1981-11-11T12:00:00.000", "mg_index": 0.28437001}, +{"time": "1981-11-12T12:00:00.000", "mg_index": 0.28417999}, +{"time": "1981-11-13T12:00:00.000", "mg_index": 0.28415999}, +{"time": "1981-11-14T12:00:00.000", "mg_index": 0.28352001}, +{"time": "1981-11-15T12:00:00.000", "mg_index": 0.28095001}, +{"time": "1981-11-16T12:00:00.000", "mg_index": 0.27991}, +{"time": "1981-11-17T12:00:00.000", "mg_index": 0.27932999}, +{"time": "1981-11-18T12:00:00.000", "mg_index": 0.27779999}, +{"time": "1981-11-19T12:00:00.000", "mg_index": 0.27737001}, +{"time": "1981-11-20T12:00:00.000", "mg_index": 0.27680001}, +{"time": "1981-11-21T12:00:00.000", "mg_index": 0.27621999}, +{"time": "1981-11-22T12:00:00.000", "mg_index": 0.27632001}, +{"time": "1981-11-23T12:00:00.000", "mg_index": 0.27715001}, +{"time": "1981-11-24T12:00:00.000", "mg_index": 0.27801999}, +{"time": "1981-11-25T12:00:00.000", "mg_index": 0.27903}, +{"time": "1981-11-26T12:00:00.000", "mg_index": 0.28042999}, +{"time": "1981-11-27T12:00:00.000", "mg_index": 0.28198999}, +{"time": "1981-11-28T12:00:00.000", "mg_index": 0.28318}, +{"time": "1981-11-29T12:00:00.000", "mg_index": 0.28408}, +{"time": "1981-11-30T12:00:00.000", "mg_index": 0.28488001}] +}} diff --git a/GeospaceDataManagement/tests/test_data/mgii_sorce_2005-03-06.txt b/GeospaceDataManagement/tests/test_data/mgii_sorce_2005-03-06.txt new file mode 100644 index 0000000..c6c0bd6 --- /dev/null +++ b/GeospaceDataManagement/tests/test_data/mgii_sorce_2005-03-06.txt @@ -0,0 +1,20 @@ +{"sorce_mg_index": { +"samples": [{"time": "2005-03-06T01:49:00.480", "mg_index": 0.26555, "unc": 0.006454}, +{"time": "2005-03-06T02:01:32.160", "mg_index": 0.26729, "unc": 0.006337}, +{"time": "2005-03-06T03:13:40.800", "mg_index": 0.26726, "unc": 0.002008}, +{"time": "2005-03-06T06:04:10.560", "mg_index": 0.26695, "unc": 0.002009}, +{"time": "2005-03-06T06:40:36.480", "mg_index": 0.26827, "unc": 0.006307}, +{"time": "2005-03-06T06:53:08.160", "mg_index": 0.26758, "unc": 0.006332}, +{"time": "2005-03-06T12:56:44.160", "mg_index": 0.26864, "unc": 0.001999}, +{"time": "2005-03-06T14:10:10.560", "mg_index": 0.26812, "unc": 0.001994}, +{"time": "2005-03-06T14:46:45.119", "mg_index": 0.26704, "unc": 0.006361}, +{"time": "2005-03-06T14:59:16.800", "mg_index": 0.26806, "unc": 0.006313}, +{"time": "2005-03-06T16:11:08.160", "mg_index": 0.26801, "unc": 0.001997}, +{"time": "2005-03-06T19:01:46.559", "mg_index": 0.2687, "unc": 0.001989}, +{"time": "2005-03-06T19:38:29.760", "mg_index": 0.26766, "unc": 0.006343}, +{"time": "2005-03-06T19:51:01.440", "mg_index": 0.26846, "unc": 0.006295}, +{"time": "2005-03-06T20:38:58.560", "mg_index": 0.26755, "unc": 0.002012}, +{"time": "2005-03-06T22:39:56.160", "mg_index": 0.26842, "unc": 0.001993}, +{"time": "2005-03-06T22:52:45.120", "mg_index": 0.26803, "unc": 0.006319}, +{"time": "2005-03-06T23:05:16.800", "mg_index": 0.26844, "unc": 0.006296}] +}} diff --git a/GeospaceDataManagement/tests/test_data/sw/f107/all/f107_1947_to_2019-03-17.txt b/GeospaceDataManagement/tests/test_data/sw/f107/all/f107_1947_to_2019-03-17.txt deleted file mode 100644 index 7d5416d..0000000 --- a/GeospaceDataManagement/tests/test_data/sw/f107/all/f107_1947_to_2019-03-17.txt +++ /dev/null @@ -1,26083 +0,0 @@ -,f107 -1947-02-13, -1947-02-14,253.9 -1947-02-15, -1947-02-16, -1947-02-17,228.5 -1947-02-18, -1947-02-19,178.8 -1947-02-20,163.7 -1947-02-21, -1947-02-22, -1947-02-23, -1947-02-24,164.1 -1947-02-25,192.7 -1947-02-26,171.1 -1947-02-27, -1947-02-28,233.3 -1947-03-01, -1947-03-02, -1947-03-03, -1947-03-04, -1947-03-05,306.1 -1947-03-06,306.0 -1947-03-07,321.4 -1947-03-08,345.6 -1947-03-09, -1947-03-10,325.9 -1947-03-11,303.3 -1947-03-12,305.3 -1947-03-13,359.5 -1947-03-14,267.2 -1947-03-15,223.0 -1947-03-16, -1947-03-17,179.6 -1947-03-18,157.1 -1947-03-19,141.1 -1947-03-20,141.1 -1947-03-21,149.7 -1947-03-22,159.1 -1947-03-23, -1947-03-24,164.3 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18:00:00,2531,12,4.666666666666667,28.666666666666668 +2019-02-28 21:00:00,2531,12,3.0,28.666666666666668 diff --git a/GeospaceDataManagement/tests/test_data/sw/kp/kp1902.tab b/GeospaceDataManagement/tests/test_data/sw/kp/kp1902.tab deleted file mode 100644 index dd2c4ed..0000000 --- a/GeospaceDataManagement/tests/test_data/sw/kp/kp1902.tab +++ /dev/null @@ -1,32 +0,0 @@ -190201 2+ 3+ 3+ 2+ 2+ 4- 3o 4- 24o D3* 15 0.9 -190202 4- 4o 3o 2+ 2o 3+ 3o 3o 24+ D2* 16 0.9 -190203 3+ 3o 3- 1o 1+ 2+ 2o 2+ 18o 10 0.6 -190204 1- 0o 1- 0+ 1+ 2- 3o 2+ 10o 5 0.2 -190205 3o 1+ 1- 0+ 0+ 1o 1o 0+ 8o 5 0.2 -190206 1o 2o 2o 3- 3- 1+ 2+ 2+ 16+ 8 0.4 -190207 2- 1+ 1o 0o 0+ 1- 1o 2o 8o 4 0.1 -190208 2o 2- 2- 1+ 1- 1+ 2+ 4- 15- 8 0.4 -190209 3- 2o 2o 2+ 2- 2+ 3o 1o 17o 9 0.5 -190210 2+ 3- 1- 1+ 0+ 0+ 1o 1o 10- 5 0.2 -190211 1o 1+ 2- 1- 3o 3o 2o 2+ 15o 8 0.4 -190212 2o 2+ 0+ 0+ 1o 1- 0o 2+ 9o 4 0.2 -190213 2- 3- 3- 4- 4- 3o 1+ 2o 21- D4* 13 0.7 -190214 3- 3+ 2+ 3o 0+ 1- 2+ 2- 16+ 9 0.5 -190215 2+ 1o 1- 0+ 1- 0+ 1- 0o 6o Q9 3 0.1 -190216 0o 0o 1o 0o 1o 2o 1+ 1- 6o Q8 3 0.1 -190217 0o 0o 1- 0+ 0o 0+ 2o 2+ 6- Q0 3 0.1 -190218 3o 3o 0+ 1+ 1+ 1o 0+ 0+ 11- 6 0.3 -190219 0+ 1o 1o 0+ 0o 0+ 1- 0+ 4o Q5 2 0.0 -190220 0+ 0o 0+ 0o 0+ 1o 1+ 2- 5o Q6 3 0.0 -190221 3- 2o 4- 2- 3- 2- 1o 3o 18+ D5* 10 0.6 -190222 2o 0+ 1o 1- 0+ 0o 1- 1+ 6+ Q7 3 0.1 -190223 0+ 0o 0+ 0o 0o 1o 1o 0o 3- Q3 2 0.0 -190224 0o 0o 1- 1- 1o 0o 0o 0o 2+ Q2 1 0.0 -190225 0o 0o 1- 0+ 0o 0+ 0o 1- 2o Q1 1 0.0 -190226 1- 0o 0o 1- 0+ 1o 0o 1- 3+ Q4 2 0.0 -190227 1o 0o 1- 1o 3o 3+ 3o 4o 16o 11 0.6 -190228 4+ 3+ 2o 3+ 4+ 4- 5- 3o 29- D1 23 1.1 -1902 Mean 7 0.33 - -1902 Q 25 24 23 26 19 20 22 16 15 17 -1902 D 28 2* 1* 13* 21* diff --git a/GeospaceDataManagement/tests/test_files.py b/GeospaceDataManagement/tests/test_files.py index 1f72d99..60f8e58 100644 --- a/GeospaceDataManagement/tests/test_files.py +++ b/GeospaceDataManagement/tests/test_files.py @@ -26,8 +26,8 @@ import pytest import GeospaceDataManagement as gdm -from GeospaceDataManagement.instruments.methods.testing import create_files import GeospaceDataManagement.instruments.gdm_testing +from GeospaceDataManagement.instruments.methods.testing import create_files from GeospaceDataManagement.tests.classes.cls_ci import CICleanSetup from GeospaceDataManagement.utils import files as futils from GeospaceDataManagement.utils import testing diff --git a/GeospaceDataManagement/tests/test_instrument.py b/GeospaceDataManagement/tests/test_instrument.py index 5aa78ae..26fb93c 100644 --- a/GeospaceDataManagement/tests/test_instrument.py +++ b/GeospaceDataManagement/tests/test_instrument.py @@ -325,13 +325,21 @@ def test_setting_partial_data_by_2d_indices_and_name(self, changed, fixed): """ + # Create a new 2D data variable self.testInst.load(self.ref_time.year, self.ref_doy) self.testInst['doubleProfile'] = 2. * self.testInst['profiles'] - self.testInst[changed, changed, 'doubleProfile'] = 0 - assert np.all(np.all(self.testInst[fixed, fixed, 'doubleProfile'] - == 2. * self.testInst[fixed, 'profiles'])) - assert np.all(np.all(self.testInst[changed, changed, 'doubleProfile'] - == 0)) + + # Ensure all the values are positive, so that we don't accidentally pass + assert np.all(np.sign(self.testInst['doubleProfile'].values) >= 0), \ + 'Re-asses assigment value in this test to ensure robustness' + + # Re-assign some values to negative and evaluate the assignment + fill_val = -47 + self.testInst[changed, changed, 'doubleProfile'] = fill_val + assert np.all(self.testInst[fixed, 'doubleProfile'].values + == 2. * self.testInst[fixed, 'profiles'].values).all() + assert np.all(self.testInst[changed, changed, 'doubleProfile'].values + == fill_val).all() return @pytest.mark.parametrize("data,target", diff --git a/GeospaceDataManagement/tests/test_instruments.py b/GeospaceDataManagement/tests/test_instruments.py index 2f4d931..97f392f 100644 --- a/GeospaceDataManagement/tests/test_instruments.py +++ b/GeospaceDataManagement/tests/test_instruments.py @@ -15,7 +15,9 @@ Notes ----- -Imports test methods from gdm.tests.instrument_test_class +Imports test methods from gdm.tests.classes.cls_instrument_library, all +Instruments must undergo this testing in a single class as the pytest markers +cannot be updated for that test class mid-test. """ @@ -26,37 +28,39 @@ import pytest import GeospaceDataManagement as gdm -import GeospaceDataManagement.tests.classes.cls_instrument_library as \ - cls_inst_lib -from GeospaceDataManagement.tests.classes.cls_instrument_library import \ - InstLibTests +import GeospaceDataManagement.tests.classes.cls_instrument_library as clslib +from GeospaceDataManagement.utils import generate_instrument_list # Optional code to pass through user and password info to test instruments # dict, keyed by the Instrument, with a list of usernames and passwords user_info = {'gdm_testing': {'user': 'gdm_testing', 'password': 'angeline.g.burrell.civ@us.navy.mil'}} -# Initialize tests for sources in gdm.instruments in the same way data sources -# outside of GeospaceDataManagement would be tested -instruments = InstLibTests.initialize_test_package(InstLibTests, - inst_loc=gdm.instruments, - user_info=user_info) +# Initialize tests for sources in gdm.instruments. Keep seperate lists for +# different optional installation structures to allow testing only the +# available instruments +test_instruments = generate_instrument_list(inst_loc=gdm.instruments, + user_info=user_info, subset='test') +sw_instruments = generate_instrument_list(inst_loc=gdm.instruments, subset='sw') +instruments = clslib.InstLibTests.initialize_test_package( + clslib.InstLibTests, inst_loc=gdm.instruments, user_info=user_info, + inst_subset='all') +no_sw = False if len(sw_instruments['names']) > 0 else True -class TestInstruments(InstLibTests): +class TestInstruments(clslib.InstLibTests): """Main class for instrument tests. Notes ----- All standard tests, setup, and teardown inherited from the core - instrument test class. + instrument test class. As the markers are custom and can only be set + once, all groups of instruments must be tested in this class """ - # Custom package unit tests can be added here - - # Custom Integration Tests added to all test instruments in core package - @pytest.mark.parametrize("inst_dict", instruments['download']) + # Tests specifically for the GeospaceDataMangement test instruments + @pytest.mark.parametrize("inst_dict", test_instruments['download']) @pytest.mark.parametrize("kwarg,output", [(None, 0.0), (dt.timedelta(hours=1), 3600.0)]) def test_inst_start_time(self, inst_dict, kwarg, output): @@ -74,7 +78,7 @@ def test_inst_start_time(self, inst_dict, kwarg, output): """ - _, date = cls_inst_lib.initialize_test_inst_and_date(inst_dict) + _, date = clslib.initialize_test_inst_and_date(inst_dict) if kwarg: self.test_inst = gdm.Instrument( inst_module=inst_dict['inst_module'], start_time=kwarg) @@ -87,7 +91,7 @@ def test_inst_start_time(self, inst_dict, kwarg, output): assert self.test_inst[0, 'uts'] == output return - @pytest.mark.parametrize("inst_dict", instruments['download']) + @pytest.mark.parametrize("inst_dict", test_instruments['download']) def test_inst_num_samples(self, inst_dict): """Test operation of num_samples keyword. @@ -102,7 +106,7 @@ def test_inst_num_samples(self, inst_dict): # Number of samples needs to be <96 because freq is not settable. # Different test instruments have different default number of points. num = 10 - _, date = cls_inst_lib.initialize_test_inst_and_date(inst_dict) + _, date = clslib.initialize_test_inst_and_date(inst_dict) self.test_inst = gdm.Instrument(inst_module=inst_dict['inst_module'], num_samples=num) self.test_inst.load(date=date) @@ -110,7 +114,7 @@ def test_inst_num_samples(self, inst_dict): assert len(self.test_inst['uts']) == num return - @pytest.mark.parametrize("inst_dict", instruments['download']) + @pytest.mark.parametrize("inst_dict", test_instruments['download']) def test_inst_file_date_range(self, inst_dict): """Test operation of file_date_range keyword. @@ -124,7 +128,7 @@ def test_inst_file_date_range(self, inst_dict): file_date_range = pds.date_range(dt.datetime(2021, 1, 1), dt.datetime(2021, 12, 31)) - _, date = cls_inst_lib.initialize_test_inst_and_date(inst_dict) + _, date = clslib.initialize_test_inst_and_date(inst_dict) self.test_inst = gdm.Instrument(inst_module=inst_dict['inst_module'], file_date_range=file_date_range, update_files=True) @@ -133,7 +137,7 @@ def test_inst_file_date_range(self, inst_dict): assert all(file_date_range == file_list.index) return - @pytest.mark.parametrize("inst_dict", instruments['download']) + @pytest.mark.parametrize("inst_dict", test_instruments['download']) def test_inst_max_latitude(self, inst_dict): """Test operation of max_latitude keyword. @@ -145,7 +149,7 @@ def test_inst_max_latitude(self, inst_dict): """ - _, date = cls_inst_lib.initialize_test_inst_and_date(inst_dict) + _, date = clslib.initialize_test_inst_and_date(inst_dict) self.test_inst = gdm.Instrument(inst_module=inst_dict['inst_module']) if self.test_inst.name != 'testmodel': self.test_inst.load(date=date, max_latitude=10.) @@ -161,7 +165,7 @@ def test_inst_max_latitude(self, inst_dict): @pytest.mark.parametrize("change", [True, False]) @pytest.mark.parametrize('warn_type', ['logger', 'warning', 'error', 'mult']) - @pytest.mark.parametrize("inst_dict", instruments['download']) + @pytest.mark.parametrize("inst_dict", test_instruments['download']) def test_clean_with_warnings(self, clean_level, change, warn_type, inst_dict, caplog): """Run `test_clean_warn` with different warning behaviours. @@ -192,7 +196,6 @@ def test_clean_with_warnings(self, clean_level, change, warn_type, # Construct the expected warnings if warn_type == 'mult': # Note that we cannot test errors along with other warnings - # TODO(#1184) test for both warnings and errors inst_dict['inst_module']._clean_warn = { inst_dict['inst_id']: {inst_dict['tag']: {clean_level: [ ('warning', warn_level['warning'], warn_msg, final_level), @@ -220,3 +223,21 @@ def test_clean_with_warnings(self, clean_level, change, warn_type, self.test_clean_warn(clean_level, inst_dict, caplog) return + + # Tests specifically for the Space Weather instruments + @pytest.mark.skipif(no_sw, reason="Space Weather test only") + @pytest.mark.second + def test_45day_forecast_data_length(self): + """Test that the downloaded 45-day forecasts load 45 days of data.""" + # Initalize the desired instrument parameters + inst_dict = {'inst_module': gdm.instruments.sw_f107, + 'tag': '45day', 'inst_id': ''} + _, date = clslib.initialize_test_inst_and_date(inst_dict) + + # Load the downloaded data + self.test_inst = gdm.Instrument(**inst_dict) + self.test_inst.load(date=date) + + # Test that 45 days of F10.7 data are available + assert len(self.test_inst['f107']) == 45 + return diff --git a/GeospaceDataManagement/tests/test_methods_general.py b/GeospaceDataManagement/tests/test_methods_general.py index d8faa04..4daeaa2 100644 --- a/GeospaceDataManagement/tests/test_methods_general.py +++ b/GeospaceDataManagement/tests/test_methods_general.py @@ -4,6 +4,7 @@ # # ---------------------------------------------------------------------------- # Original Authors: pysat development team (c) 2016, Russell Stoneback +# Original Authors: pysat development team, (c) 2020 pysat # # Modified 2026+ # This is a U.S. government work and not under copyright protection in the U.S. @@ -14,6 +15,7 @@ """Unit tests for the general instrument methods.""" import datetime as dt +import numpy as np from os import path import pandas as pds import pytest @@ -325,3 +327,38 @@ def test_load_empty_filelist(self): # Evaluate the empty output assert self.data.empty return + + +class TestGeneralFill(object): + """Test class for `is_fill_val` method .""" + + def setup_method(self): + """Create a clean testing setup.""" + self.var = 'check' + return + + def teardown_method(self): + """Clean up previous testing setup.""" + del self.var + return + + @pytest.mark.parametrize("fill_val", [-1.0, -1, np.nan, np.inf, '']) + def test_is_fill(self, fill_val): + """Test the successful evaluation of fill values. + + Parameters + ---------- + fill_val : float, int, or str + Fill value to use as a comparison + + """ + # Set the data value to not be a fill value + if fill_val != '': + self.var = -47 + + # Evaluate the variable is False + assert not gen.is_fill_val(self.var, fill_val) + + # Evaluate the fill value is a fill value + assert gen.is_fill_val(fill_val, fill_val) + return diff --git a/GeospaceDataManagement/tests/test_params.py b/GeospaceDataManagement/tests/test_params.py index bb89fa0..b0f978e 100644 --- a/GeospaceDataManagement/tests/test_params.py +++ b/GeospaceDataManagement/tests/test_params.py @@ -228,7 +228,7 @@ def test_settings_file_must_be_present(self, capsys): # Ensure we can't create a parameters file without valid .json testing.eval_bad_input( Parameters, OSError, - 'GeospaceDataParameters is unable to locate a user settings') + 'GeospaceDataManagement is unable to locate a user settings') shutil.move(os.path.join(self.root, 'gdm_settings_moved.json'), os.path.join(self.root, 'gdm_settings.json')) diff --git a/GeospaceDataManagement/tests/test_registry.py b/GeospaceDataManagement/tests/test_registry.py index ae2a1cb..af39062 100644 --- a/GeospaceDataManagement/tests/test_registry.py +++ b/GeospaceDataManagement/tests/test_registry.py @@ -36,7 +36,7 @@ def ensure_updated_stored_modules(modules): gdm.params['user_modules'] """ - # make sure filesystem was updated + # Make sure filesystem was updated saved_modules = registry.load_saved_modules() for module_name, platform, name in modules: assert platform in saved_modules @@ -56,9 +56,8 @@ def ensure_live_registry_updated(modules): gdm.params['user_modules'] """ - + # Check that the global registry was updated for module_name, platform, name in modules: - # check that global registry was updated assert platform in gdm.params['user_modules'] assert name in gdm.params['user_modules'][platform] assert module_name in gdm.params['user_modules'][platform][name] @@ -312,23 +311,21 @@ class TestModuleRegistration(object): def setup_method(self): """Set up the unit test environment for each method.""" - + # Define the instrument location and package name self.inst_module = gdm.instruments - # package name pkg_name = self.inst_module.__name__ - # construct inputs similar to TestRegistration - # to enable use of existing methods - # almost fully general + # Construct inputs similar to TestRegistration to enable use of + # existing methods module_names = self.inst_module.__all__ - self.names = [snip.split('gdm')[-1][1:] for snip in module_names] - self.platforms = ['gdm'] * len(self.names) + self.names = [mname.split("_")[1] for mname in module_names] + self.platforms = [mname.split("_")[0] for mname in module_names] module_strings = ['.'.join((pkg_name, name)) for name in module_names] self.modules = [(mod, plat, nam) for mod, plat, nam in zip(module_strings, self.platforms, self.names)] - # remove any existing support which may be let over + # Remove any existing support which may be let over registry.remove(self.platforms, [None] * len(self.platforms)) return @@ -342,12 +339,13 @@ def teardown_method(self): def test_module_registration_multiple(self): """Test registering a module containing multiple instruments.""" - - # register package by module + # Register package by module registry.register_by_module(self.inst_module) - # check that global registry was updated + + # Check that that global registry was updated ensure_live_registry_updated(self.modules) - # verify update on disk + + # Verify the update on disk ensure_updated_stored_modules(self.modules) return diff --git a/GeospaceDataManagement/tests/test_sw_instruments.py b/GeospaceDataManagement/tests/test_sw_instruments.py new file mode 100644 index 0000000..a051a57 --- /dev/null +++ b/GeospaceDataManagement/tests/test_sw_instruments.py @@ -0,0 +1,311 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Unit and Integration Tests for Space Weather instrument modules. + +Note +---- +Standard test methods from gdm.tests.instrument_test_class are performed in +`test_instruments.py` along with any tests that require downloaded data. + +""" + +import datetime as dt +import logging +import os +import pytest +import sys +import tempfile + +# Import the instrument package and test classes +import GeospaceDataManagement as gdm +import GeospaceDataManagement.tests.classes.cls_instrument_library as clslib +from GeospaceDataManagement.utils import generate_instrument_list +from GeospaceDataManagement.utils import testing + + +# Tell the standard tests which instruments to run each test on. +# Need to return instrument list for custom tests. +sw_instruments = generate_instrument_list(inst_loc=gdm.instruments, subset='sw') +no_sw = False if len(sw_instruments['names']) > 0 else True + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestSWInstrumentLogging(object): + """Test logging messages raised under instrument-specific conditions.""" + + def setup_method(self): + """Create a clean the testing setup.""" + # Prepare for testing downloads + self.saved_path = gdm.params['data_dirs'] + gdm.params._set_data_dirs(path=gdm.test_data_path, store=False) + self.saved_files = list() + + # Assign the Instrument kwargs + self.inst_kwargs = [ + {'inst_module': gdm.instruments.sw_f107, 'tag': 'historic'}, + {'inst_module': gdm.instruments.sw_kp}, + {'inst_module': gdm.instruments.ace_epam}, + {'inst_module': gdm.instruments.sw_f107, 'tag': 'prelim'}] + + def teardown_method(self): + """Clean up previous testing setup.""" + # Clean up the GeospaceDataManager parameter space + gdm.params._set_data_dirs(path=self.saved_path, store=False) + + for saved_file in self.saved_files: + attempts = 0 + # Remove file with multiple attempts for Windows + while os.path.isfile(saved_file) and attempts < 100: + os.remove(saved_file) + attempts += 1 + + # Remove empty directories + try: + os.removedirs(os.path.split(saved_file)[0]) + except OSError: + pass # The directory isn't empty and that's ok + + del self.inst_kwargs, self.saved_path, self.saved_files + return + + def test_historic_download_past_limit(self, caplog): + """Test message raised if loading times not in the database.""" + + with caplog.at_level(logging.INFO, logger='GeospaceDataManagement'): + inst = gdm.Instrument(**self.inst_kwargs[0]) + inst.download(start=inst.today()) + + # Test the warning + captured = caplog.text + assert captured.find('date may be out of range for the database') >= 0 + + # Test the file was not downloaded + assert inst.today() not in inst.files.files.index + + @pytest.mark.parametrize("tag", ["def", "now"]) + def test_missing_kp_file(self, tag, caplog): + """Test message raised if loading times not in the database. + + Parameters + ---------- + tag: str + Kp Instrument tag + + """ + # Initalize the Instrument and time + inst = gdm.Instrument(tag=tag, **self.inst_kwargs[1]) + future_time = inst.today() + dt.timedelta(weeks=500) + cap_text = 'Unable to download' + + # Get the logging message + with caplog.at_level(logging.INFO, logger='GeospaceDataManagement'): + inst.download(start=future_time) + + # Test the warning + captured = caplog.text + assert captured.find(cap_text) >= 0, "Unexpected text: {:}".format( + captured) + + # Test the file was not downloaded + assert future_time not in inst.files.files.index + self.saved_files = [inst.files.data_path, + inst.files.data_path.replace('kp', 'ap'), + inst.files.data_path.replace('kp', 'cp')] + + return + + def test_realtime_ace_bad_day(self, caplog): + """Test message raised when downloading old ACE realtime data.""" + inst = gdm.Instrument(tag='realtime', **self.inst_kwargs[2]) + past_time = inst.today() - dt.timedelta(weeks=500) + + # Get the logging message + with caplog.at_level(logging.WARNING, logger='GeospaceDataManagement'): + inst.download(start=past_time) + + # Test the warning + captured = caplog.text + assert captured.find( + 'real-time data only') >= 0, "Unexpected text: {:}".format(captured) + + # Test the file was downloaded + assert past_time in inst.files.files.index + self.saved_files = [os.path.join(inst.files.data_path, + inst.files.files[past_time]), + os.path.join(inst.files.data_path, + inst.files.files[ + past_time + dt.timedelta(days=1)])] + + return + + def test_historic_ace_no_data(self, caplog): + """Test message raised when no historic ACE data found on server.""" + inst = gdm.Instrument(tag='historic', **self.inst_kwargs[2]) + past_time = dt.datetime(1800, 1, 1) # Pre-space age date + + # Get the logging message + with caplog.at_level(logging.WARNING, logger='GeospaceDataManagement'): + inst.download(start=past_time) + + # Test the warning + captured = caplog.text + assert captured.find( + 'not found:') >= 0, "Unexpected text: {:}".format(captured) + + # Test the file was not downloaded + assert past_time not in inst.files.files.index + self.saved_files = [inst.files.data_path] + + return + + def test_missing_prelim_file(self, caplog): + """Test message raised if loading times not in the DSD database.""" + # Initalize the Instrument, time, and expected log output + inst = gdm.Instrument(**self.inst_kwargs[3]) + future_time = inst.today() + dt.timedelta(weeks=500) + cap_text = 'File not available for' + + # Get the logging message + with caplog.at_level(logging.INFO, logger='GeospaceDataManagement'): + inst.download(start=future_time) + + # Test the warning + captured = caplog.text + assert captured.find(cap_text) >= 0, "Unexpected text: {:}".format( + captured) + + # Test the file was not downloaded + assert future_time not in inst.files.files.index + self.saved_files = [inst.files.data_path, + inst.files.data_path.replace('f107', 'sbfield'), + inst.files.data_path.replace('f107', 'ssn'), + inst.files.data_path.replace('f107', 'flare')] + + return + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestMockDownloads(object): + """Test mock download option for Instruments.""" + + def setup_method(self): + """Create a clean testing environment.""" + + # Use a temporary directory so that the user's setup is not altered. + # TODO(#974): Remove if/else when support for Python 3.9 is dropped. + if sys.version_info.minor >= 10: + self.tempdir = tempfile.TemporaryDirectory( + ignore_cleanup_errors=True) + else: + self.tempdir = tempfile.TemporaryDirectory() + + self.saved_path = gdm.params['data_dirs'] + gdm.params._set_data_dirs(path=self.tempdir.name, store=False) + self.dkwargs = {"mock_download_dir": self.tempdir.name} + return + + def teardown_method(self): + """Clean up downloaded files and parameters from tests.""" + + gdm.params._set_data_dirs(self.saved_path, store=False) + # Remove the temporary directory. In Windows, this occasionally fails + # by raising a wide variety of different error messages. Python 3.10+ + # can handle this, but lower Python versions cannot. + # TODO(#974): Remove try/except when support for Python 3.9 is dropped. + try: + self.tempdir.cleanup() + except Exception: + pass + + del self.dkwargs, self.tempdir, self.saved_path + return + + # TODO(#4): update 'download' key when possible + @pytest.mark.parametrize("inst_dict", sw_instruments['download']) + def test_error_bad_dir(self, inst_dict): + """Test IOError is raised for a bad mock-download directory. + + Parameters + ---------- + inst_dict : dict + Dictionary containing info to instantiate a specific instrument. + Set automatically from instruments['download'] when + `initialize_test_package` is run. + + """ + # Initalize the test instrument + test_inst, date = clslib.initialize_test_inst_and_date(inst_dict) + + # Evaluate the error message for a bad directory name + self.dkwargs['mock_download_dir'] = "not/a\\directory.path" + testing.eval_bad_input(test_inst.download, IOError, + 'file location is not a directory', + input_args=[date], input_kwargs=self.dkwargs) + return + + # TODO(#4): update 'download' key when possible + @pytest.mark.parametrize("inst_dict", sw_instruments['download']) + def test_loginfo_missing_file(self, inst_dict, caplog): + """Test log for info about a missing file when using mock downloads. + + Parameters + ---------- + inst_dict : dict + Dictionary containing info to instantiate a specific instrument. + Set automatically from instruments['download'] when + `initialize_test_package` is run. + + """ + # Initalize the test instrument + test_inst, date = clslib.initialize_test_inst_and_date(inst_dict) + + # Get the logging message + with caplog.at_level(logging.INFO, logger='GeospaceDataManagement'): + test_inst.download(start=date, **self.dkwargs) + + # Test the warning + captured = caplog.text + cap_text = "data may have been saved to an unexpected filename" + assert captured.find(cap_text) > 0, "Unexpected text: {:}".format( + captured) + return + + # TODO(#4): update 'download' key when possible + @pytest.mark.parametrize("inst_dict", sw_instruments['download']) + def test_mock_download(self, inst_dict): + """Test gdm's ability to process files downloaded by a user. + + Parameters + ---------- + inst_dict : dict + Dictionary containing info to instantiate a specific instrument. + Set automatically from instruments['download'] when + `initialize_test_package` is run. + + """ + # Initalize the test instrument + test_inst, date = clslib.initialize_test_inst_and_date(inst_dict) + + # Update the mock data directory + self.dkwargs['mock_download_dir'] = gdm.test_data_path + + # Test the download + assert len(test_inst.files.files) == 0 + test_inst.download(start=date, **self.dkwargs) + assert len(test_inst.files.files) > 0, "".join([ + repr(test_inst.platform), " ", repr(test_inst.name), " ", + repr(test_inst.tag), " ", repr(test_inst.inst_id), " failed to ", + "download using date=", repr(date), ", mock_download_dir=", + self.dkwargs['mock_download_dir']]) + return diff --git a/GeospaceDataManagement/tests/test_sw_methods_ace.py b/GeospaceDataManagement/tests/test_sw_methods_ace.py new file mode 100644 index 0000000..96514db --- /dev/null +++ b/GeospaceDataManagement/tests/test_sw_methods_ace.py @@ -0,0 +1,113 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Integration and unit test suite for ACE methods.""" + +import pytest + +import GeospaceDataManagement as gdm +try: + from GeospaceDataManagement.instruments.sw_methods import ace as mm_ace + no_sw = False +except ImportError: + no_sw = True + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestACEMethods(object): + """Test class for ACE methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + self.out = None + return + + def teardown_method(self): + """Clean up previous testing setup.""" + del self.out + return + + def test_acknowledgements(self): + """Test the ACE acknowledgements.""" + self.out = mm_ace.acknowledgements() + assert self.out.find('ACE') >= 0 + return + + @pytest.mark.parametrize('name', ['mag', 'epam', 'swepam', 'sis']) + def test_references(self, name): + """Test the references for an ACE instrument.""" + self.out = mm_ace.references(name) + assert self.out.find('Space Sci. Rev.') > 0 + return + + def test_references_bad_name(self): + """Test the references raise an informative error for bad instrument.""" + with pytest.raises(KeyError) as kerr: + mm_ace.references('ace') + + assert str(kerr.value).find('unknown ACE instrument') >= 0 + return + + def test_clean_bad_inst(self): + """Test AttributeError is raised with a non-ACE instrument.""" + inst = gdm.Instrument('gdm', 'testing') + + with pytest.raises(AttributeError) as aerr: + mm_ace.clean(inst) + + assert str(aerr.value).find("Can't apply ACE cleaning to platform") >= 0 + return + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestACESWEPAMMethods(object): + """Test class for ACE SWEPAM methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + self.testInst = gdm.Instrument('gdm', 'testing') + self.testInst.load(date=self.testInst.inst_module._test_dates['']['']) + + self.omni_keys = ['sw_proton_dens_norm', 'sw_ion_temp_norm'] + return + + def teardown_method(self): + """Clean up previous testing setup.""" + del self.testInst + return + + def test_ace_swepam_hourly_omni_norm(self): + """Test ACE SWEPAM conversion to OMNI hourly normalized standards.""" + + self.testInst['slt'] = 400.0 * self.testInst['slt'] + mm_ace.ace_swepam_hourly_omni_norm(self.testInst, speed_key='slt', + dens_key='mlt', temp_key='dummy3') + + # Test that normalized data and metadata are present and realistic + for okey in self.omni_keys: + assert okey in self.testInst.variables # Data variable exists + assert len(self.testInst[okey].attrs) > 0 # Meta data exists + assert (self.testInst[okey].values >= 0.0).all() # Values are pos + + return + + def test_ace_swepam_hourly_omni_norm_bad_keys(self): + """Test ACE SWEPAM conversion to OMNI hourly normalized standards.""" + + with pytest.raises(ValueError) as verr: + mm_ace.ace_swepam_hourly_omni_norm(self.testInst) + + # Test the error message for missing data variables + assert str(verr).find("instrument missing variable") >= 0 + + return diff --git a/GeospaceDataManagement/tests/test_sw_methods_ae.py b/GeospaceDataManagement/tests/test_sw_methods_ae.py new file mode 100644 index 0000000..1a17669 --- /dev/null +++ b/GeospaceDataManagement/tests/test_sw_methods_ae.py @@ -0,0 +1,65 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Integration and unit test suite for AE methods.""" + +import pytest + +try: + from GeospaceDataManagement.instruments.sw_methods import auroral_electrojet + no_sw = False +except ImportError: + no_sw = True + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestAEMethods(object): + """Test class for the auroral electrojet methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + self.out = None + return + + def teardown_method(self): + """Clean up previous testing setup.""" + del self.out + return + + @pytest.mark.parametrize('name', ['ae', 'al', 'au']) + def test_acknowledgements(self, name): + """Test the auroral electrojet acknowledgements. + + Parameters + ---------- + name : str + Instrument name + + """ + self.out = auroral_electrojet.acknowledgements(name, 'lasp') + assert self.out.find(name.upper()) >= 0 + return + + @pytest.mark.parametrize('name', ['ae', 'al', 'au']) + def test_references(self, name): + """Test the references for an AE instrument. + + Parameters + ---------- + name : str + Instrument name + + """ + self.out = auroral_electrojet.references(name, 'lasp') + assert self.out.find('Davis, T. N.') >= 0 + return diff --git a/GeospaceDataManagement/tests/test_sw_methods_f107.py b/GeospaceDataManagement/tests/test_sw_methods_f107.py new file mode 100644 index 0000000..0122341 --- /dev/null +++ b/GeospaceDataManagement/tests/test_sw_methods_f107.py @@ -0,0 +1,262 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Test suite for F10.7 methods.""" + +import datetime as dt +import numpy as np +import pandas as pds +import pytest +import xarray as xr + +import GeospaceDataManagement as gdm + +try: + from GeospaceDataManagement.instruments import sw_f107 + from GeospaceDataManagement.instruments.sw_methods import f107 as mm_f107 + no_sw = False +except ImportError: + no_sw = True + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestSWF107(object): + """Test class for F10.7 methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + # Load a test instrument + self.testInst = gdm.Instrument() + self.testInst.data = xr.Dataset({ + 'f107': (('time'), np.linspace(70, 200, 160)), + 'time': (('time'), [dt.datetime(2009, 1, 1) + dt.timedelta(days=i) + for i in range(160)])}) + return + + def teardown_method(self): + """Clean up previous testing setup.""" + del self.testInst + return + + def eval_f107a(self, nan_check=False): + """Evaluate the test instrument for F10.7a data. + + Parameters + ---------- + nan_check : bool + Check min and max values are NaN insensitive if True (default=False) + + """ + # Assert that new data and metadata exist + assert 'f107a' in self.testInst.variables + assert len(self.testInst['f107a'].attrs) > 0 + + # Assert the values are finite and realistic means + if nan_check: + assert (np.nanmin(self.testInst['f107a']) + > np.nanmin(self.testInst['f107'])) + assert (np.nanmax(self.testInst['f107a']) + < np.nanmax(self.testInst['f107'])) + else: + assert np.all(np.isfinite(self.testInst['f107a'])) + assert self.testInst['f107a'].min() > self.testInst['f107'].min() + assert self.testInst['f107a'].max() < self.testInst['f107'].max() + return + + @pytest.mark.parametrize("inargs,vmsg", [ + (["bad"], "unknown input data variable"), + (['f107', 'f107'], "output data variable already exists")]) + def test_calc_f107a_bad_inputs(self, inargs, vmsg): + """Test the calc_f107a with a bad inputs. + + Parameters + ---------- + inargs : list + List of input arguements that should raise a ValueError + vmsg : str + Expected ValueError message + + """ + + with pytest.raises(ValueError) as verr: + mm_f107.calc_f107a(self.testInst, *inargs) + + assert str(verr).find(vmsg) >= 0 + return + + def test_calc_f107a_daily(self): + """Test the calc_f107a routine with daily data.""" + + mm_f107.calc_f107a(self.testInst, f107_name='f107', f107a_name='f107a') + self.eval_f107a() + return + + def test_calc_f107a_high_rate(self): + """Test the calc_f107a routine with sub-daily data.""" + self.testInst.data = xr.Dataset( + {'f107': (('time'), np.linspace(70, 200, 3840)), + 'time': (('time'), [dt.datetime(2009, 1, 1) + dt.timedelta(hours=i) + for i in range(3840)])}) + mm_f107.calc_f107a(self.testInst, f107_name='f107', f107a_name='f107a') + self.eval_f107a() + + # Assert the same mean value is used for a day + assert len(np.unique(self.testInst['f107a'][:24])) == 1 + return + + def test_calc_f107a_daily_missing(self): + """Test the calc_f107a routine with some daily data missing.""" + + self.testInst.data = xr.Dataset( + {'f107': (('time'), np.linspace(70, 200, 160)), + 'time': (('time'), [dt.datetime(2009, 1, 1) + dt.timedelta( + days=(2 * i + 1)) for i in range(160)])}) + mm_f107.calc_f107a(self.testInst, f107_name='f107', f107a_name='f107a') + + # Assert that new data and metadata exist + self.eval_f107a(nan_check=True) + + # Assert the expected number of fill values + assert (len(self.testInst['f107a'][np.isnan(self.testInst['f107a'])]) + == 40) + return + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestSWF107Combine(object): + """Test class for the `combine_f107` method.""" + + def setup_method(self): + """Create a clean testing setup.""" + # Switch to test_data directory + self.saved_path = gdm.params['data_dirs'] + gdm.params.data['data_dirs'] = [gdm.test_data_path] + + # Set combination testing input + self.test_day = dt.datetime(2019, 3, 16) + inst_id = {tag: '' for tag in sw_f107.tags.keys()} + inst_id['now'] = 'obs' + self.combine_inst = {tag: gdm.Instrument(inst_module=sw_f107, tag=tag, + inst_id=inst_id[tag], + update_files=True) + for tag in sw_f107.tags.keys()} + self.combine_times = {"start": self.test_day - dt.timedelta(days=30), + "stop": self.test_day + dt.timedelta(days=3)} + + return + + def teardown_method(self): + """Clean up previous testing setup.""" + gdm.params.data['data_dirs'] = self.saved_path + del self.combine_inst, self.test_day, self.combine_times + return + + def test_combine_f107_none(self): + """Test `combine_f107` failure when no input is provided.""" + + with pytest.raises(TypeError) as terr: + mm_f107.combine_f107() + + assert str(terr).find("missing 2 required positional arguments") >= 0 + return + + def test_combine_f107_no_time(self): + """Test `combine_f107` failure when no times are provided.""" + + with pytest.raises(ValueError) as verr: + mm_f107.combine_f107(self.combine_inst['historic'], + self.combine_inst['forecast']) + + assert str(verr).find("must either load in Instrument objects") >= 0 + return + + def test_combine_f107_bad_time(self): + """Test `combine_f107` failure when bad times are provided.""" + + with pytest.raises(ValueError) as verr: + mm_f107.combine_f107(self.combine_inst['historic'], + self.combine_inst['forecast'], + start=self.combine_times['stop'], + stop=self.combine_times['start']) + + assert str(verr).find("date range is zero or negative") >= 0 + return + + def test_combine_f107_no_data(self): + """Test `combine_f107` when no data is present for specified times.""" + + combo_in = {kk: self.combine_inst['forecast'] for kk in + ['standard_inst', 'forecast_inst']} + combo_in['start'] = dt.datetime(2014, 2, 19) + combo_in['stop'] = dt.datetime(2014, 2, 24) + f107_inst = mm_f107.combine_f107(**combo_in) + + assert f107_inst.data.isnull().all()["f107"] + + del combo_in, f107_inst + return + + def test_combine_f107_no_data_no_files(self): + """Test `combine_f107` without data or files for the specified times.""" + + # Unset the file list for the instrument + self.combine_inst['forecast'].files.files = pds.Series([]) + + # Set the function inputs + combo_in = {kk: self.combine_inst['forecast'] for kk in + ['standard_inst', 'forecast_inst']} + combo_in['start'] = dt.datetime(2014, 2, 19) + combo_in['stop'] = dt.datetime(2014, 2, 24) + + # Run the method + f107_inst = mm_f107.combine_f107(**combo_in) + + # Test the output + assert np.isnan(f107_inst.data["f107"]).all() + + del combo_in, f107_inst + return + + def test_combine_f107_inst_time(self): + """Test `combine_f107` with times provided through datasets.""" + + self.combine_inst['historic'].load( + date=self.combine_inst['historic'].lasp_stime, + end_date=self.combine_times['start']) + self.combine_inst['forecast'].load(date=self.test_day) + + f107_inst = mm_f107.combine_f107(self.combine_inst['historic'], + self.combine_inst['forecast']) + + assert f107_inst.index[0] == self.combine_inst['historic'].lasp_stime + assert f107_inst.index[-1] <= self.combine_times['stop'] + assert len(f107_inst.vars_no_time) == 1 + assert 'f107' in f107_inst.variables + + del f107_inst + return + + def test_combine_f107_all(self): + """Test `combine_f107` with 'historic' and '45day' input.""" + + f107_inst = mm_f107.combine_f107(self.combine_inst['historic'], + self.combine_inst['45day'], + **self.combine_times) + + assert f107_inst.index[0] >= self.combine_times['start'] + assert f107_inst.index[-1] < self.combine_times['stop'] + assert len(f107_inst.vars_no_time) == 1 + assert 'f107' in f107_inst.variables + + del f107_inst + return diff --git a/GeospaceDataManagement/tests/test_sw_methods_general.py b/GeospaceDataManagement/tests/test_sw_methods_general.py new file mode 100644 index 0000000..006e8cd --- /dev/null +++ b/GeospaceDataManagement/tests/test_sw_methods_general.py @@ -0,0 +1,55 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Integration and unit test suite for ACE methods.""" + +import numpy as np +import pytest + +import GeospaceDataManagement as gdm +try: + from GeospaceDataManagement.instruments.sw_methods import general + no_sw = False +except ImportError: + no_sw = True + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestGeneralMethods(object): + """Test class for general methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + self.inst = gdm.Instrument('gdm', 'testing') + self.inst.load(date=self.inst.inst_module._test_dates['']['']) + self.var = self.inst.variables[0] + self.fill_label = 'fill_val' + return + + def teardown_method(self): + """Clean up previous testing setup.""" + del self.inst, self.var, self.fill_label + return + + def test_preprocess(self): + """Test the preprocessing routine updates all fill values to be NaN.""" + + # Make sure at least one fill value is not already NaN + self.inst[self.var].attrs['fill_val'] = 0.0 + + # Update the meta data using the general preprocess routine + general.preprocess_fill(self.inst, fill_label=self.fill_label) + + # Test the output + assert np.isnan(self.inst[self.var].attrs[self.fill_label]) + return diff --git a/GeospaceDataManagement/tests/test_sw_methods_gfz.py b/GeospaceDataManagement/tests/test_sw_methods_gfz.py new file mode 100644 index 0000000..25e2b84 --- /dev/null +++ b/GeospaceDataManagement/tests/test_sw_methods_gfz.py @@ -0,0 +1,56 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Integration and unit test suite for GFZ methods.""" + +import datetime as dt +import pytest +import tempfile + +import GeospaceDataManagement as gdm +try: + from GeospaceDataManagement.instruments.sw_methods import gfz + no_sw = False +except ImportError: + no_sw = True + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestGFZMethods(object): + """Test class for GFZ methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + # Prepare for testing downloads + self.tempdir = tempfile.TemporaryDirectory() + self.saved_path = gdm.params['data_dirs'] + gdm.params._set_data_dirs(path=self.tempdir.name, store=False) + return + + def teardown_method(self): + """Clean up previous testing setup.""" + # Clean up the GeospaceDataManagement parameter space + gdm.params._set_data_dirs(self.saved_path, store=False) + + del self.tempdir, self.saved_path + return + + def test_kp_ap_cp_download_bad_inst(self): + """Test the download doesn't work for an incorrect Instrument.""" + with pytest.raises(ValueError) as verr: + gfz.kp_ap_cp_download('platform', 'name', 'tag', 'inst_id', + [dt.datetime.now(tz=dt.timezone.utc)], + 'data/path') + + assert str(verr).find('Unknown Instrument module') >= 0 + return diff --git a/GeospaceDataManagement/tests/test_sw_methods_kp.py b/GeospaceDataManagement/tests/test_sw_methods_kp.py new file mode 100644 index 0000000..681d76c --- /dev/null +++ b/GeospaceDataManagement/tests/test_sw_methods_kp.py @@ -0,0 +1,684 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Test suite for Kp and Ap methods.""" + +import datetime as dt +import numpy as np +import pandas as pds +import pytest + +import GeospaceDataManagement as gdm +try: + from GeospaceDataManagement.instruments import sw_kp + from GeospaceDataManagement.instruments.sw_methods import kp_ap + no_sw = False +except ImportError: + no_sw = True + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestKpInitMetadata(object): + """Test class for Kp metadata initialization methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + self.test_function = kp_ap.get_kp_metadata + + # Set the default values + self.units = '' + self.desc = 'Planetary K-index' + self.min_val = 0 + self.max_val = 9 + self.fill_val = -1 + self.out_dict = {} + + return + + def teardown_method(self): + """Clean up previous testing setup.""" + del self.test_function, self.units, self.desc + del self.min_val, self.max_val, self.fill_val, self.out_dict + return + + def eval_defaults(self): + """Evaluate the outputs of the metadata.""" + + assert self.out_dict['units'] == self.units + assert self.out_dict['desc'] == self.desc + assert self.out_dict['min_val'] == self.min_val + assert self.out_dict['max_val'] == self.max_val + assert self.out_dict['fill_val'] == self.fill_val + return + + def test_get_metadata_defaults(self): + """Test default metadata initialization.""" + + self.out_dict = self.test_function() + self.eval_defaults() + + return + + def test_fill_metadata(self): + """Test metadata initialization with user-specified fill value.""" + self.out_dict = self.test_function(fill_val=666) + + self.fill_val = 666 + self.eval_defaults() + return + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestApInitMetadata(TestKpInitMetadata): + """Test class for Ap metadata initialization methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + self.test_function = kp_ap.get_ap_metadata + + # Set the default values + self.units = '' + self.desc = 'ap (equivalent range) index' + self.min_val = 0 + self.max_val = 400 + self.fill_val = -1 + self.out_dict = {} + return + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestBartelInitMetadata(object): + """Test class for Bartel metadata initialization methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + self.test_function = kp_ap.get_bartel_metadata + + # Set the default values + self.units = '' + self.desc = ''.join(['A sequence of 27-day intervals counted from ', + 'February 8, 1832']) + self.min_val = 1 + self.max_val = np.inf + self.fill_val = -1 + self.out_dict = {} + return + + def eval_defaults(self, data_key): + """Evaluate the outputs of the metadata. + + Parameters + ---------- + data_key : str + Name of the desired variable + + """ + if data_key.find('day_within') >= 0: + self.units = 'day' + name = 'Days within Bartels solar rotation' + self.desc = 'Number of days within the Bartels solar rotation' + self.max_val = 27 + else: + name = 'Bartels solar rotation number' + + assert self.out_dict['units'] == self.units + assert self.out_dict['name'] == name + assert self.out_dict['desc'] == self.desc + assert self.out_dict['max_val'] == self.max_val + assert self.out_dict['min_val'] == self.min_val + assert self.out_dict['fill_val'] == self.fill_val + + return + + @pytest.mark.parametrize("data_key", ["solar_rotation_num", + "day_within_solar_rotation"]) + def test_get_metadata_defaults(self, data_key): + """Test default metadata initialization. + + Parameters + ---------- + data_key : str + String denoting the data key + + """ + self.out_dict = self.test_function(data_key) + self.eval_defaults(data_key) + + return + + @pytest.mark.parametrize("data_key", ["solar_rotation_num", + "day_within_solar_rotation"]) + def test_fill_metadata(self, data_key): + """Test metadata initialization with user-specified fill value. + + Parameters + ---------- + data_key : str + String denoting the data key + + """ + self.out_dict = self.test_function(data_key, fill_val=666) + + self.fill_val = 666 + self.eval_defaults(data_key) + return + + def test_bad_data_variable(self): + """Test metadata initialization doesn't work with the wrong variable.""" + data_key = 'Kp' + + with pytest.raises(ValueError) as verr: + self.test_function(data_key) + + assert str(verr).find('unknown data key') >= 0 + return + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestSWKp(object): + """Test class for Kp methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + + # Load a test instrument + inst_dict = {'num_samples': 12} + self.inst = gdm.Instrument('gdm', 'testing', **inst_dict) + test_time = gdm.instruments.gdm_testing._test_dates[''][''] + + load_kwargs = {'date': test_time} + self.inst.load(**load_kwargs) + + # Create Kp data + self.inst.data[self.inst.index.name] = pds.DatetimeIndex(data=[ + test_time + dt.timedelta(hours=3 * i) for i in range(12)]) + self.inst['Kp'] = np.arange(0, 4, 1.0 / 3.0) + self.inst['ap_nan'] = np.full(shape=12, fill_value=np.nan) + self.inst['ap_inf'] = np.full(shape=12, fill_value=np.inf) + self.inst['Kp'].attrs.update({'fill_val': np.nan}) + self.inst['ap_nan'].attrs.update({'fill_val': np.nan}) + self.inst['ap_inf'].attrs.update({'fill_val': np.inf}) + return + + def teardown_method(self): + """Clean up previous testing setup.""" + del self.inst + return + + def test_convert_kp_to_ap(self): + """Test conversion of Kp to ap.""" + + kp_ap.convert_3hr_kp_to_ap(self.inst) + + assert '3hr_ap' in self.inst.variables + assert len(self.inst['3hr_ap'].attrs) > 0 + assert self.inst['3hr_ap'].min() >= self.inst['3hr_ap'].attrs['min_val'] + assert self.inst['3hr_ap'].max() <= self.inst['3hr_ap'].attrs['max_val'] + return + + def test_convert_kp_to_ap_fill_val(self): + """Test conversion of Kp to ap with fill values.""" + + # Set the first value to a fill value, then calculate ap + fill_label = 'fill_val' + fill_value = self.inst['Kp'].attrs[fill_label] + self.inst[self.inst.index[0], 'Kp'] = fill_value + kp_ap.convert_3hr_kp_to_ap(self.inst) + + # Test non-fill ap values + assert '3hr_ap' in self.inst.variables + assert len(self.inst['3hr_ap'].attrs.keys()) > 0 + assert self.inst['3hr_ap'][1:].min() >= self.inst[ + '3hr_ap'].attrs['min_val'] + assert self.inst['3hr_ap'][1:].max() <= self.inst[ + '3hr_ap'].attrs['max_val'] + + # Test the fill value in the data and metadata + assert np.isnan(self.inst['3hr_ap'][0]) + assert np.isnan(self.inst['3hr_ap'].attrs[fill_label]) + + return + + def test_convert_kp_to_ap_bad_input(self): + """Test conversion of Kp to ap with bad input.""" + # Rename the desired data variable to something that won't work + self.inst.rename({"Kp": "bad"}) + + with pytest.raises(ValueError) as verr: + kp_ap.convert_3hr_kp_to_ap(self.inst) + + assert str(verr).find("Variable name for Kp data is missing") >= 0 + return + + def test_convert_ap_to_kp(self): + """Test conversion of ap to Kp.""" + + kp_ap.convert_3hr_kp_to_ap(self.inst) + kp_out, kp_meta = kp_ap.convert_ap_to_kp(self.inst['3hr_ap']) + + # Assert original and coverted there and back Kp are equal + assert all(abs(kp_out - self.inst['Kp']) < 1.0e-4) + + # Assert the converted Kp meta data exists and is reasonable + assert kp_meta['fill_val'] == -1 + + del kp_out, kp_meta + return + + def test_convert_ap_to_kp_middle(self): + """Test conversion of ap to Kp where ap is not an exact Kp value.""" + + kp_ap.convert_3hr_kp_to_ap(self.inst) + new_val = self.inst[self.inst.index[8], '3hr_ap'] + 1 + self.inst[self.inst.index[8], '3hr_ap'] = new_val + kp_out, kp_meta = kp_ap.convert_ap_to_kp(self.inst['3hr_ap']) + + # Assert original and coverted there and back Kp are equal + assert all(abs(kp_out - self.inst.data['Kp']) < 1.0e-4) + + # Assert the converted Kp meta data exists and is reasonable + assert kp_meta['fill_val'] == -1 + + return + + def test_convert_ap_to_kp_nan_input(self): + """Test conversion of ap to Kp where ap is NaN.""" + + kp_out, kp_meta = kp_ap.convert_ap_to_kp(self.inst['ap_nan']) + + # Assert original and coverted there and back Kp are equal + assert all(kp_out == -1) + + # Assert the converted Kp meta data exists and is reasonable + assert kp_meta['fill_val'] == -1 + + del kp_out, kp_meta + return + + def test_convert_ap_to_kp_inf_input(self): + """Test conversion of ap to Kp where ap is Inf.""" + + kp_out, kp_meta = kp_ap.convert_ap_to_kp(self.inst['ap_inf']) + + # Assert original and coverted there and back Kp are equal + assert all(kp_out[1:] == -1) + + # Assert the converted Kp meta data exists and is reasonable + assert kp_meta['fill_val'] == -1 + + del kp_out, kp_meta + return + + def test_convert_ap_to_kp_fill_val(self): + """Test conversion of ap to Kp with fill values.""" + + # Set the first Kp value to a fill value + fill_label = 'fill_val' + fill_value = self.inst['Kp'].attrs[fill_label] + self.inst[self.inst.index[0], 'Kp'] = fill_value + + # Calculate ap + kp_ap.convert_3hr_kp_to_ap(self.inst) + + # Recalculate Kp from ap + kp_out, kp_meta = kp_ap.convert_ap_to_kp(self.inst['3hr_ap'], + fill_val=fill_value) + + # Test non-fill ap values + assert all(abs(kp_out[1:] - self.inst['Kp'][1:]) < 1.0e-4) + + # Test the fill value in the data and metadata + assert np.isnan(kp_out[0]) + assert np.isnan(kp_meta[fill_label]) + + return + + @pytest.mark.parametrize("filter_kwargs,ngood", [ + ({"min_kp": 2, 'filter_time': 0}, 6), + ({"max_kp": 2, 'filter_time': 0}, 7), + ({"min_kp": 2, "filter_time": 12}, 2), + ({"min_kp": 2, "max_kp": 3, 'filter_time': 0}, 4)]) + def test_filter_geomag(self, filter_kwargs, ngood): + """Test geomag_filter success for different limits. + + Parameters + ---------- + filter_kwargs : dict + Dict with kwarg input for `filter_geomag` + ngood : int + Expected number of good samples + + """ + + kp_ap.filter_geomag(self.inst, kp_inst=self.inst, + **filter_kwargs) + assert len(self.inst.index) == ngood, \ + 'Incorrect filtering using {:} of {:}'.format(filter_kwargs, + self.inst['Kp']) + return + + def test_filter_geomag_load_kp(self): + """Test geomag_filter loading the Kp instrument.""" + try: + kp_ap.filter_geomag(self.inst) + assert len(self.inst.index) == 12 # No filtering with defaults + except IOError as ierr: + assert str(ierr).find('unable to load') >= 0 # No data to load + return + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestSWKpCombine(object): + """Tests for the `combine_kp` method.""" + + def setup_method(self): + """Create a clean testing setup.""" + # Switch to test_data directory + self.saved_path = gdm.params['data_dirs'] + gdm.params.data['data_dirs'] = [gdm.test_data_path] + + # Set combination testing input + test_day = dt.datetime(2019, 3, 18) + idict = {'inst_module': sw_kp, 'update_files': True} + + self.combine = {"standard_inst": gdm.Instrument(tag="def", **idict), + "recent_inst": gdm.Instrument(tag="recent", **idict), + "forecast_inst": gdm.Instrument(tag="forecast", + **idict), + "start": test_day - dt.timedelta(days=30), + "stop": test_day + dt.timedelta(days=3), + "fill_val": -1} + self.load_kwargs = {"date": test_day} + + return + + def teardown_method(self): + """Clean up previous testing.""" + gdm.params.data['data_dirs'] = self.saved_path + del self.combine, self.saved_path, self.load_kwargs + return + + def test_combine_kp_none(self): + """Test combine_kp failure when no input is provided.""" + + with pytest.raises(ValueError) as verr: + kp_ap.combine_kp() + + assert str(verr).find("need at two Kp Instrument objects to") >= 0 + return + + def test_combine_kp_one(self): + """Test combine_kp raises ValueError with only one instrument.""" + + # Load a test instrument + test_inst = gdm.Instrument() + test_inst.data = pds.DataFrame({'Kp': np.arange(0, 4, 1.0 / 3.0)}, + index=[dt.datetime(2009, 1, 1) + + pds.DateOffset(hours=3 * i) + for i in range(12)]) + test_inst['Kp'].attrs.update({'fill_val': np.nan}) + + with pytest.raises(ValueError) as verr: + kp_ap.combine_kp(standard_inst=test_inst) + + assert str(verr).find("need at two Kp Instrument objects to") >= 0 + + return + + def test_combine_kp_no_time(self): + """Test combine_kp raises ValueError when no times are provided.""" + + # Remove the start times from the input dict + del self.combine['start'], self.combine['stop'] + + # Raise a value error + with pytest.raises(ValueError) as verr: + kp_ap.combine_kp(**self.combine) + + # Test the error message + assert str(verr).find("must either load in Instrument objects or") >= 0 + + return + + def test_combine_kp_no_data(self): + """Test combine_kp when no data is present for specified times.""" + + combo_in = {kk: self.combine['forecast_inst'] for kk in + ['standard_inst', 'recent_inst', 'forecast_inst']} + combo_in['start'] = dt.datetime(2014, 2, 19) + combo_in['stop'] = dt.datetime(2014, 2, 24) + kp_inst = kp_ap.combine_kp(**combo_in) + + assert kp_inst.data.isnull().all()["Kp"] + + del combo_in, kp_inst + return + + def test_combine_kp_no_data_no_files(self): + """Test combine_kp without data or files for the specified times.""" + + # Unset the file list for the instrument + self.combine['forecast_inst'].files.files = pds.Series([]) + + # Set the function inputs + combo_in = {kk: self.combine['forecast_inst'] for kk in + ['standard_inst', 'recent_inst', 'forecast_inst']} + combo_in['start'] = dt.datetime(2014, 2, 19) + combo_in['stop'] = dt.datetime(2014, 2, 24) + + # Run the method + kp_inst = kp_ap.combine_kp(**combo_in) + + # Test the output + assert kp_inst.data.isnull().all()["Kp"] + + del combo_in, kp_inst + return + + def test_combine_kp_inst_time(self): + """Test combine_kp when times are provided through the instruments.""" + + combo_in = {kk: self.combine[kk] for kk in + ['standard_inst', 'recent_inst', 'forecast_inst']} + + for ikey in combo_in.keys(): + combo_in[ikey].load(**self.load_kwargs) + + kp_inst = kp_ap.combine_kp(**combo_in) + + assert kp_inst.index[0] >= self.combine['start'] + + # kp_inst contains times up to 21:00:00, coombine['stop'] is midnight + assert kp_inst.index[-1].date() <= self.combine['stop'].date() + assert len(kp_inst.vars_no_time) == 1 + assert 'Kp' in kp_inst.variables + + assert np.isnan(kp_inst['Kp'].attrs['fill_val']) + assert len(kp_inst['Kp'][np.isnan(kp_inst['Kp'])]) == 0 + + del combo_in, kp_inst + return + + def test_combine_kp_all(self): + """Test combine_kp when all input is provided.""" + + kp_inst = kp_ap.combine_kp(**self.combine) + + assert kp_inst.index[0] >= self.combine['start'] + assert kp_inst.index[-1] < self.combine['stop'] + assert len(kp_inst.vars_no_time) == 1 + assert kp_inst.variables[0] == 'Kp' + + # Fill value is defined by combine + assert (kp_inst['Kp'].attrs['fill_val'] == self.combine['fill_val']) + assert (kp_inst['Kp'] != self.combine['fill_val']).all() + + del kp_inst + return + + def test_combine_kp_no_forecast(self): + """Test combine_kp when forecasted data is not provided.""" + + combo_in = {kk: self.combine[kk] for kk in self.combine.keys() + if kk != 'forecast_inst'} + kp_inst = kp_ap.combine_kp(**combo_in) + + assert kp_inst.index[0] >= self.combine['start'] + assert kp_inst.index[-1] < self.combine['stop'] + assert len(kp_inst.vars_no_time) == 1 + assert 'Kp' in kp_inst.variables + assert (kp_inst['Kp'].attrs['fill_val'] == self.combine['fill_val']) + assert (kp_inst['Kp'] == self.combine['fill_val']).any() + + del kp_inst, combo_in + return + + def test_combine_kp_no_recent(self): + """Test combine_kp when recent data is not provided.""" + + combo_in = {kk: self.combine[kk] for kk in self.combine.keys() + if kk != 'recent_inst'} + kp_inst = kp_ap.combine_kp(**combo_in) + + assert kp_inst.index[0] >= self.combine['start'] + assert kp_inst.index[-1] < self.combine['stop'] + assert len(kp_inst.vars_no_time) == 1 + assert 'Kp' in kp_inst.variables + assert kp_inst['Kp'].attrs['fill_val'] == self.combine['fill_val'] + assert (kp_inst['Kp'] == self.combine['fill_val']).any() + + del kp_inst, combo_in + return + + def test_combine_kp_no_standard(self): + """Test combine_kp when standard data is not provided.""" + + combo_in = {kk: self.combine[kk] for kk in self.combine.keys() + if kk != 'standard_inst'} + kp_inst = kp_ap.combine_kp(**combo_in) + + assert kp_inst.index[0] >= self.combine['start'] + assert kp_inst.index[-1] < self.combine['stop'] + assert len(kp_inst.vars_no_time) == 1 + assert 'Kp' in kp_inst.variables + assert kp_inst['Kp'].attrs['fill_val'] == self.combine['fill_val'] + assert self.combine['fill_val'] in kp_inst['Kp'].values + + del kp_inst, combo_in + return + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestSWAp(object): + """Test class for Ap methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + inst_dict = {'num_samples': 10} + self.test_inst = gdm.Instrument('gdm', 'testing', **inst_dict) + test_time = gdm.instruments.gdm_testing._test_dates[''][''] + + load_kwargs = {'date': test_time} + self.test_inst.load(**load_kwargs) + + # Create 3 hr Ap data + self.test_inst[self.test_inst.index.name] = pds.DatetimeIndex(data=[ + test_time + pds.DateOffset(hours=3 * i) for i in range(10)]) + self.test_inst['3hr_ap'] = np.array([0, 2, 3, 4, 5, 6, 7, 9, 12, 15]) + self.test_inst['3hr_ap'].attrs.update({ + 'units': '', 'name': 'ap', + 'desc': "3-hour ap (equivalent range) index", 'min_val': 0, + 'max_val': 400, 'fill_val': np.nan, 'notes': 'test ap'}) + return + + def teardown_method(self): + """Clean up previous testing.""" + del self.test_inst + return + + def test_calc_daily_Ap(self): + """Test daily Ap calculation.""" + + kp_ap.calc_daily_Ap(self.test_inst) + + assert 'Ap' in self.test_inst.variables + assert len(self.test_inst['Ap'].attrs.keys()) > 0 + + # Test unfilled values (full days) + assert np.all(self.test_inst['Ap'][:8].min() == 4.5) + + # Test fill values (partial days) + assert np.all(np.isnan(self.test_inst['Ap'][8:])) + return + + def test_calc_daily_Ap_w_running(self): + """Test daily Ap calculation with running mean.""" + + kp_ap.calc_daily_Ap(self.test_inst, running_name="running_ap") + + assert 'Ap' in self.test_inst.variables + assert len(self.test_inst['Ap'].attrs.keys()) > 0 + assert 'running_ap' in self.test_inst.variables + assert len(self.test_inst['running_ap'].attrs.keys()) > 0 + + # Test unfilled values (full days) + assert np.all(self.test_inst['Ap'][:8].min() == 4.5) + assert np.all(self.test_inst['running_ap'][6:].min() == 4.5) + + # Test fill values (partial days) + assert np.all(np.isnan(self.test_inst['Ap'][8:])) + assert np.all(np.isnan(self.test_inst['running_ap'][:6])) + return + + @pytest.mark.parametrize("inargs,vmsg", [ + (["no"], "bad 3-hourly ap variable name"), + (["3hr_ap", "3hr_ap"], "daily Ap variable name already exists")]) + def test_calc_daily_Ap_bad_3hr(self, inargs, vmsg): + """Test bad inputs raise ValueError for daily Ap calculation. + + Parameters + ---------- + inargs : list + Input arguements that should raise a ValueError + vmsg : str + Expected ValueError message + + """ + + with pytest.raises(ValueError) as verr: + kp_ap.calc_daily_Ap(self.test_inst, *inargs) + + assert str(verr).find(vmsg) >= 0 + return + + @pytest.mark.parametrize("ap,out", [(0, 0), (1, 0), (153, 7), (-1, None), + (460, None), (np.nan, None), + (np.inf, None), (-np.inf, None)]) + def test_round_ap(self, ap, out): + """Test `round_ap` returns expected value for successes and failures. + + Parameters + ---------- + ap : float + Input ap + out : float or NoneType + Expected output kp or None to use fill_value + + """ + + fill_value = -47.0 + if out is None: + out = fill_value + + assert out == kp_ap.round_ap(ap, fill_val=fill_value) + return diff --git a/GeospaceDataManagement/tests/test_sw_methods_lisird.py b/GeospaceDataManagement/tests/test_sw_methods_lisird.py new file mode 100644 index 0000000..a999705 --- /dev/null +++ b/GeospaceDataManagement/tests/test_sw_methods_lisird.py @@ -0,0 +1,65 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# +# DISTRIBUTION STATEMENT A: Approved for public release. Distribution is +# unlimited. +# ---------------------------------------------------------------------------- +"""Tests for the LISIRD functions.""" + +import datetime as dt +import logging +import pytest + +try: + from GeospaceDataManagement.instruments.sw_methods import lisird + from GeospaceDataManagement import test_data_path + no_sw = False +except ImportError: + no_sw = True + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestLISIRDFunctions(object): + """Unit tests for LISIRD functions.""" + + def setup_method(self): + """Create the test environment.""" + self.in_args = [[dt.datetime(2001, 1, 1)], test_data_path, 'test_', + '%Y-%m-%d', 'sorce_mg_index', + dt.timedelta(seconds=86399)] + return + + def teardown_method(self): + """Clean up the test environment.""" + + del self.in_args + return + + def test_download_empty_file(self, caplog): + """Test a logger warning is raised when no data is found.""" + + with caplog.at_level(logging.WARNING, logger='GeospaceDataManagement'): + lisird.download(*self.in_args) + + # Test the warning + captured = caplog.text + assert captured.find('no data for') >= 0 + return + + def test_download_bad_fill_columns(self): + """Test raises KeyError with unexpected column names from fill_vals.""" + + self.in_args[0][0] += dt.timedelta(weeks=160) + + with pytest.raises(KeyError) as kerr: + lisird.download(*self.in_args, fill_vals={"NOPE": -999.0}) + + assert str(kerr).find('unknown fill value variable name supplied') >= 0 + return diff --git a/GeospaceDataManagement/tests/test_sw_methods_norp.py b/GeospaceDataManagement/tests/test_sw_methods_norp.py new file mode 100644 index 0000000..d747185 --- /dev/null +++ b/GeospaceDataManagement/tests/test_sw_methods_norp.py @@ -0,0 +1,65 @@ +#!/usr/bin/env python +# Full license can be found in License.md +# Full author list can be found in CITATION.cff +# +# ---------------------------------------------------------------------------- +# Original Authors: pysat development team, (c) 2020 pysat +# +# Modified 2026+ +# This is a U.S. government work and not under copyright protection in the U.S. +# ---------------------------------------------------------------------------- +"""Integration and unit test suite for NoRP methods.""" + +import pytest + +try: + from GeospaceDataManagement.instruments.sw_methods import norp as mm_norp + no_sw = False +except ImportError: + no_sw = True + + +@pytest.mark.skipif(no_sw, reason="Space Weather test only") +class TestNoRPMethods(object): + """Test class for NoRP methods.""" + + def setup_method(self): + """Create a clean testing setup.""" + self.out = None + return + + def teardown_method(self): + """Clean up previous testing setup.""" + del self.out + return + + def test_acknowledgements(self): + """Test the NoRP acknowledgements.""" + self.out = mm_norp.acknowledgements() + assert self.out.find('NoRP') >= 0 + return + + @pytest.mark.parametrize('name,tag', [('rf', 'daily')]) + def test_references(self, name, tag): + """Test the references for a NoRP instrument. + + Parameters + ---------- + name : str + Instrument name + tag : str + Instrument tag + + """ + self.out = mm_norp.references(name, tag) + assert self.out.find('Toyokawa Observatory') > 0 + return + + def test_references_bad_name(self): + """Test the references raise an informative error for bad instrument.""" + with pytest.raises(KeyError) as kerr: + mm_norp.references('ace', 'sis') + + assert str(kerr.value).find('ace') >= 0, \ + "Unknown KeyError message: {:}".format(kerr.value) + return diff --git a/GeospaceDataManagement/tests/test_utils_coords.py b/GeospaceDataManagement/tests/test_utils_coords.py index f1fe821..369eacd 100644 --- a/GeospaceDataManagement/tests/test_utils_coords.py +++ b/GeospaceDataManagement/tests/test_utils_coords.py @@ -367,7 +367,7 @@ def test_establish_common_coord_single_val_only(self): class TestExpandXarrayDims(object): - """Unit tests for the `expand_xarray_dims` function TODO.""" + """Unit tests for the `expand_xarray_dims` function.""" def setup_method(self): """Set up the unit test environment.""" diff --git a/GeospaceDataManagement/tests/test_utils_files.py b/GeospaceDataManagement/tests/test_utils_files.py index b2860b1..5b8400b 100644 --- a/GeospaceDataManagement/tests/test_utils_files.py +++ b/GeospaceDataManagement/tests/test_utils_files.py @@ -29,6 +29,9 @@ from GeospaceDataManagement.utils import files as futils from GeospaceDataManagement.utils import testing +# TODO(#6): update to use alternate package instruments when one exists. +no_alt_package = True + class TestConstructSearchstring(object): """Unit tests for the `construct_searchstring_from_format` function.""" @@ -550,15 +553,15 @@ def test_cycle_selection(self): return +@pytest.mark.skipif(no_alt_package, reason="Test for alterate dir structure") class TestFileDirectoryTranslations(CICleanSetup): """Unit tests for file directory setup.""" def setup_method(self): """Set up the unit test environment for each method.""" - # Module is only required for testing installations on CI servers - import pysatSpaceWeather - + # TODO(#6): update to use alternate package instruments when one + # exists. # Create clean environment on the CI server CICleanSetup.setup_method(self) reload(gdm) @@ -570,24 +573,28 @@ def setup_method(self): # Create several gdm.SpaceWeather instruments and download data. # We want to start with a setup that covers general cases a user may # have. - gdm.utils.registry.register_by_module(pysatSpaceWeather.instruments) + gdm.utils.registry.register_by_module(gdm.instruments) self.insts = [] self.insts_dates = [] self.insts_kwargs = [] + # TODO(#6): update to use alternate package instruments when one + # exists. # Data by day, ACE SIS data self.insts.append(gdm.Instrument('ace', 'sis', tag='historic')) - test_dates = pysatSpaceWeather.instruments.ace_sis._test_dates - self.insts_dates.append([test_dates['']['historic']] * 2) + # test_dates = ace_sis._test_dates + # self.insts_dates.append([test_dates['']['historic']] * 2) self.insts_kwargs.append({}) + # TODO(#6): update to use alternate package instruments when one + # exists. # Data with date mangling, regular F10.7 data, stored monthly self.insts.append(gdm.Instrument('sw', 'f107', tag='historic')) - test_dates = pysatSpaceWeather.instruments.sw_f107._test_dates - self.insts_dates.append([test_dates['']['historic'], - test_dates['']['historic'] - + dt.timedelta(weeks=52)]) + # test_dates = sw_f107._test_dates + # self.insts_dates.append([test_dates['']['historic'], + # test_dates['']['historic'] + # + dt.timedelta(weeks=52)]) self.insts_kwargs.append({'freq': 'MS'}) # Download data for all instruments diff --git a/GeospaceDataManagement/tests/test_utils_meta.py b/GeospaceDataManagement/tests/test_utils_meta.py index 980f914..1936d1e 100644 --- a/GeospaceDataManagement/tests/test_utils_meta.py +++ b/GeospaceDataManagement/tests/test_utils_meta.py @@ -91,7 +91,7 @@ def test_update_fill_values_by_type(self, name): inst.load(date=self.ref_time) # Ensure there are fill values to check for strings and numbers - # TODO(#XX) Remove try/except after numpy >= 1.25 + # TODO(#1) Remove try/except after numpy >= 1.25 try: str_types = [str, np.str_, np.bytes_, np.dtypes.StrDType, np.dtypes.StringDType, np.dtypes.BytesDType, @@ -189,7 +189,7 @@ def test_default_fill_values_from_type_int(self, int_type): return @pytest.mark.parametrize("flt_type", [float, np.single, np.float32, - np.float64, np.float128, np.float16]) + np.float64, np.float16]) def test_default_fill_values_from_type_float(self, flt_type): """Test `default_vill_values_from_type` for object defaults. diff --git a/GeospaceDataManagement/utils/_core.py b/GeospaceDataManagement/utils/_core.py index 8589cc6..db51dfa 100644 --- a/GeospaceDataManagement/utils/_core.py +++ b/GeospaceDataManagement/utils/_core.py @@ -291,7 +291,7 @@ def fmt_output_in_cols(out_strs, ncols=3, max_num=6, lpad=None): return output -def generate_instrument_list(inst_loc, user_info=None): +def generate_instrument_list(inst_loc, user_info=None, subset="all"): """Iterate through and classify instruments in a given subpackage. Parameters @@ -303,6 +303,8 @@ def generate_instrument_list(inst_loc, user_info=None): Nested dictionary with user and password info for instrument module name. If None, no user or password is assumed. (default=None) EX: user_info = {'jro_isr': {'user': 'myname', 'password': 'email'}} + subset : str + Specify a subset of the instruments include (default='all') Returns ------- @@ -324,7 +326,13 @@ def generate_instrument_list(inst_loc, user_info=None): """ - instrument_names = inst_loc.__all__ + subset_attr = "__{:s}__".format(subset) + if not hasattr(inst_loc, subset_attr): + gdm.logger.critical('unknown subset of Instruments: {:}'.format(subset)) + instrument_names = [] + else: + instrument_names = getattr(inst_loc, subset_attr) + instrument_download = [] instrument_optional_load = [] instrument_no_download = [] diff --git a/GeospaceDataManagement/utils/files.py b/GeospaceDataManagement/utils/files.py index af373c3..2d63945 100644 --- a/GeospaceDataManagement/utils/files.py +++ b/GeospaceDataManagement/utils/files.py @@ -643,7 +643,7 @@ def update_data_directory_structure(new_template, test_run=True, new_template : str New directory template string. The default value for GeospaceDataManagement is - `os.path.join(('{platform}', '{name}', '{tag}', '{inst_id}'))` + `os.path.join(('{platform}', '{name}', '{tag}', '{inst_id}'))` test_run : bool If True, a printout of all proposed changes will be made, but the directory changes will not be enacted. (default=True) diff --git a/GeospaceDataManagement/utils/io.py b/GeospaceDataManagement/utils/io.py index 777e849..3681b4f 100644 --- a/GeospaceDataManagement/utils/io.py +++ b/GeospaceDataManagement/utils/io.py @@ -288,7 +288,7 @@ def inst_to_netcdf(inst, fname, base_instrument=None, unit_label='units', xr_data = inst.data.copy() # Convert datetime values into integers and then add meta data - xr_data[inst.index.name] = unix_time.astype(np.int64) + xr_data[inst.index.name] = ((inst.index.name), unix_time.astype(np.int64)) xr_data[inst.index.name] = xr_data[inst.index.name].assign_attrs(epoch_meta) # Set the standard encoding values diff --git a/GeospaceDataManagement/utils/meta.py b/GeospaceDataManagement/utils/meta.py index 136dde2..e7fa2d9 100644 --- a/GeospaceDataManagement/utils/meta.py +++ b/GeospaceDataManagement/utils/meta.py @@ -86,8 +86,8 @@ def get_meta_dict(**kwargs): meta_dict : dict Dictionary with keys of 'units', 'name', 'min_val', 'max_val', 'desc', 'notes', and 'fill_val', along with any additional keys from the input - parameters. Standard values will be assigned, unless these keys are - supplied upon input. + parameters. Standard values will be assigned, unless these keys are + supplied upon input. """ # Set the defaults diff --git a/GeospaceDataManagement/utils/testing.py b/GeospaceDataManagement/utils/testing.py index 6fc390c..e62a233 100644 --- a/GeospaceDataManagement/utils/testing.py +++ b/GeospaceDataManagement/utils/testing.py @@ -14,6 +14,7 @@ """Utilities to perform common testing evaluations.""" import numpy as np + from GeospaceDataManagement import utils as gdm_utils diff --git a/GeospaceDataManagement/utils/time.py b/GeospaceDataManagement/utils/time.py index 6bbb5e3..c261777 100644 --- a/GeospaceDataManagement/utils/time.py +++ b/GeospaceDataManagement/utils/time.py @@ -295,7 +295,13 @@ def create_datetime_index(year=None, month=None, day=None, uts=None): Returns ------- - Pandas timeseries index. + index : pds.DatetimeIndex + Pandas timeseries index + + Raises + ------ + ValueError + If provided inputs are incorrectly formatted Notes ----- diff --git a/MANIFEST.in b/MANIFEST.in index bc30cb3..96ccb22 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,7 +1,7 @@ -recursive-include GeospaceDataManager *.py +recursive-include GeospaceDataManagement *.py include *.md -recursive-include GeospaceDataManager *.txt -recursive-include GeospaceDataManager *.tab +recursive-include GeospaceDataManagement *.txt +recursive-include GeospaceDataManagement *.tab include LICENSE prune docs global-exclude *.pdf diff --git a/README.md b/README.md index be6c514..51f46d8 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,5 @@ +[![Pytest with Flake8](https://github.com/USNavalResearchLaboratory/GeospaceDataManagement/actions/workflows/main.yml/badge.svg)](https://github.com/USNavalResearchLaboratory/GeospaceDataManagement/actions/workflows/main.yml) [![Coverage Status](https://coveralls.io/repos/github/USNavalResearchLaboratory/GeospaceDataManagement/badge.svg)](https://coveralls.io/github/USNavalResearchLaboratory/GeospaceDataManagement) + GeospaceDataManagement provides a simple and flexible interface for robust data analysis from beginning to end - with a focus on downloading, loading, cleaning and managing scientific data. The project's plug-in design allows analysis diff --git a/docs/examples.rst b/docs/examples.rst new file mode 100644 index 0000000..ff6645e --- /dev/null +++ b/docs/examples.rst @@ -0,0 +1,12 @@ +Examples +======== + +Here are some examples that demonstrate how to use various tools and features. + +.. toctree:: + examples/ex_sw_init.rst + examples/ex_f107.rst + examples/ex_kp.rst + examples/ex_ace.rst + examples/ex_mult_downloads.rst + examples/ex_mock_downloads.rst diff --git a/docs/examples/ex_ace.rst b/docs/examples/ex_ace.rst new file mode 100644 index 0000000..9d55779 --- /dev/null +++ b/docs/examples/ex_ace.rst @@ -0,0 +1,86 @@ +.. _exace: + +Make ACE SWEPAM behave like OMNI Data +===================================== + +NASA OMNI data is *the* place to go for solar wind (SW) parameters. However, +this data set is not available in real time. Fortunately, we can use the +`OMNI processing `_ to +normalize the ACE SWEPAM SW proton density and ion temperature. This is +performed using the :py:func:`GeospaceDataManagement.instruments.methods.ace.ace_swepam_hourly_omni_norm` +function. The example below uses historic ACE SWEPAM data so that we can +compare the results to OMNI. + +:: + + + import datetime as dt + import matplotlib as mpl + import matplotlib.pyplot as plt + + import GeospaceDataManagement as gdm + + ace = gdm.Instrument(inst_module=gdm.instruments.ace_swepam, + tag='historic', update_files=True) + + # Add the OMNI conversion routine to the ACE instrument + ace.custom_attach(gdm.instruments.methods.ace.ace_swepam_hourly_omni_norm) + + # Pick a day with a geomagnetic storm + stime = dt.datetime(2014, 3, 26) + + # If needed, download the data + if stime not in ace.files.files.index: + ace.download(start=stime) + + # Load the data + ace.load(date=stime) + + print(ace.variables) + + +This should yield ``Index(['jd', 'sec', 'status', 'sw_proton_dens', +'sw_bulk_speed', 'sw_ion_temp', 'sw_proton_dens_norm', 'sw_ion_temp_norm'], +dtype='object')``. The variables with the ``'norm'`` suffix were added by the +conversion function. Also get the OMNI Data. Now, let's plot the two data sets +together. + +:: + + + fig = plt.figure() + fig.suptitle("L1 ACE and L2 OMNI HRO data for {:}".format(stime.date())) + ax_dens = fig.add_subplot(211) + ax_temp = fig.add_subplot(212) + + ax_dens.plot(ace.index, ace['sw_proton_dens_norm'], 'k-', label='ACE') + ax_dens.plot(omni.index, omni['proton_density'], 'b-', label='OMNI') + ax_temp.plot(ace.index, ace['sw_ion_temp_norm'], 'k-', label='ACE') + ax_temp.plot(omni.index, omni['T'], 'b-', label='OMNI') + ax_temp.set_yscale('log') + ax_dens.xaxis.set_major_formatter(mpl.dates.DateFormatter('')) + ax_temp.xaxis.set_major_formatter(mpl.dates.DateFormatter('%H:%M')) + ax_dens.set_xlim(stime, stime + dt.timedelta(days=1)) + ax_temp.set_xlim(stime, stime + dt.timedelta(days=1)) + ax_temp.set_xlabel('Universal Time (HH:MM)') + ax_dens.set_ylabel(r'SW N$_p$ ({:s})'.format(omni.meta['proton_density', + 'units'])) + ax_temp.set_ylabel(r'SW T$_i$ ({:s})'.format(omni.meta['T', 'units'])) + ax_dens.legend(loc=1, fontsize='medium', ncol=2) + + # If not running in interactive mode + plt.show() + + +This figure shows that the temperature adjustment agrees relatively well, but +that the proton density has a large offset. This descrepency can be attributed +to the data source. The :py:mod:`GeospaceDataManagement.instruments.ace_swepam` +module uses L1 data, while OMNI uses L2 data that has undergone additional +processing. For this time period most of the temperature data is of high +quality in the L2 data, but all the proton density data is flagged for removal. +The ACE L2 data is accessible through CDAWeb or the `ACE database +`_. + +.. image:: ../images/ex_ace_omni.png + :align: center + diff --git a/docs/examples/ex_f107.rst b/docs/examples/ex_f107.rst new file mode 100644 index 0000000..c37b473 --- /dev/null +++ b/docs/examples/ex_f107.rst @@ -0,0 +1,88 @@ +.. _exf107: + +Load F\ :sub:`10.7`\ from Multiple Sources +========================================== + +As shown in :ref:`exswinit`, there are several sources that provide +F\ :sub:`10.7`\ over different time periods. It can be useful to combine these +data sets into a single :py:class:`GeospaceDataManagement.Instrument` object. +This may be done using the +:py:func:`~GeospaceDataManagement.instruments.methods.f107.combine_f107` +function. + +:: + + + import datetime as dt + import matplotlib as mpl + import matplotlib.pyplot as plt + + import GeospaceDataManagement as gdm + + f107_hist = gdm.Instrument(inst_module=gdm.instruments.sw_f107, + tag='historic', update_files=True) + f107_prel = gdm.Instrument(inst_module=gdm.instruments.sw_f107, + tag='prelim', update_files=True) + f107_fore = gdm.Instrument(inst_module=gdm.instruments.sw_f107, + tag='45day', update_files=True) + + # If needed, download the data + f107_hist.download(start=f107_hist.lasp_stime, stop=dt.datetime(2018, 4, 1)) + f107_prel.download(start=f107_hist.files.files.index[-1], + stop=f107_prel.today()) + f107_fore.download(start=f107_fore.today()) + + # Check the downloaded file range for the historic source + print(f107_hist.files.files.index.min(), f107_hist.files.files.index.max()) + + +This should yield ``1947-02-01 00:00:00 2018-04-30 00:00:00``. Now, combine the +data in these :py:class:`GeospaceDataManagement.Instruments` using the +:py:func:`~GeospaceDataManagement.instruments.methods.f107.combine_f107` +function twice, after loading the available data + +:: + + # Load all the data + f107_hist.load(date=f107_hist.lasp_stime, + end_date=f107_hist.files.files.index.max() + + dt.timedelta(days=1)) + f107_prel.load(fname=f107_prel.files.files[0], + stop_fname=f107_prel.files.files[-1]) + f107_fore.load(date=f107_fore.today()) + + # Combine the historic sources for all available times + f107 = gdm.instruments.methods.f107.combine_f107(f107_hist, f107_prel) + + # Combine the 45 day measurements and forecast + f107 = gdm.instruments.methods.f107.combine_f107(f107, f107_fore) + + # Check the combined Instrument index + print(f107.index[0], f107.index[-1]) + + +This print statement yields ``1947-02-14 00:00:00 2022-10-07 00:00:00``, where +the end date is roughly 45 days in the future to account for the forecasted +data. The combined :py:class:`GeospaceDataManagement.Instrument` varialbe, +``f107`` can be used to plot the F\ :sub:`10.7`\ over time. + +:: + + + fig = plt.figure() + ax = fig.add_subplot(111) + + ax.plot(f107.index, f107['f107'], 'k.', ms=1) + ax.xaxis.set_major_formatter(mpl.dates.DateFormatter('%Y')) + ax.xaxis.set_major_locator(mpl.dates.YearLocator(11)) + ax.set_xlim(f107.index[0], f107.index[-1]) + ax.set_xlabel('Universal Time (Year C.E.)') + ax.set_ylabel(r'F$_{10.7}$ (sfu)') + + # If not running in interactive mode + plt.show() + + +.. image:: ../images/ex_f107_all.png + :align: center + diff --git a/docs/examples/ex_kp.rst b/docs/examples/ex_kp.rst new file mode 100644 index 0000000..12b81e8 --- /dev/null +++ b/docs/examples/ex_kp.rst @@ -0,0 +1,97 @@ +.. _exkp: + +Load Kp from Multiple Sources +============================= + +Following from the previous F\ :sub:`10.7`\ example, :ref:`exf107`, the space +weather methods also have a routine to combine several sources of Kp over +different time periods. This may be done using +:py:func:`~GeospaceDataManagement.instruments.methods.kp_ap.combine_kp`. + +:: + + + import datetime as dt + import matplotlib as mpl + import matplotlib.pyplot as plt + + import GeospaceDataManagement as gdm + + kp_his = gdm.Instrument(inst_module=gdm.instruments.sw_kp, + tag='def', update_files=True) + kp_rec = gdm.Instrument(inst_module=gdm.instruments.sw_kp, + tag='recent', update_files=True) + kp_for = gdm.Instrument(inst_module=gdm.instruments.sw_kp, + tag='forecast', update_files=True) + + # Set the time range + stime = dt.datetime(1999, 1, 1) + etime = kp_for.today() + + # If needed, download the data + kp_his.download(start=stime, stop=etime) + kp_rec.download(start=stime, stop=etime) + kp_for.download(start=etime) + + # Combine the Kp sources for all available times + kp = gdm.instruments.methods.kp_ap.combine_kp(kp_his, kp_rec, kp_for, + stime, etime) + + # Check the combined Instrument index + print(kp.index[0], kp.index[-1]) + + +This yields ``1999-01-01 00:00:00 2022-08-23 21:00:00``, where the last date is +your current date (not the date that I created this example). Now, we can take +the combined :py:class:`GeospaceDataManagement.Instrument` can be used to plot +the Kp over time. + +:: + + + fig = plt.figure() + ax = fig.add_subplot(111) + + # Color code data by activity level + ax.bar(kp.data.loc[kp['Kp'] < 4, 'Kp'].index, + kp.data.loc[kp['Kp'] < 4, 'Kp'], color='green', label='Quiet') + ax.bar(kp.data.loc[(kp['Kp'] >= 4) & (kp['Kp'] < 7), 'Kp'].index, + kp.data.loc[(kp['Kp'] >= 4) & (kp['Kp'] < 7), 'Kp'], color='orange', + label='Active') + ax.bar(kp.data.loc[kp['Kp'] >= 7, 'Kp'].index, + kp.data.loc[kp['Kp'] >= 7, 'Kp'], color='firebrick', label='Storm') + + # Format the figure + ax.set_xlim(stime, etime) + ax.set_ylim(0, 9) + ax.xaxis.set_major_formatter(mpl.dates.DateFormatter('%Y')) + ax.set_xlabel('Universal Time (Year C.E.)') + ax.set_ylabel(r'Kp') + ax.legend(loc=1, fontsize='medium') + + # If not running in interactive mode + plt.show() + + +.. image:: ../images/ex_kp_all.png + :align: center + + + +Convert Kp to ap +================ + +The Kp and ap have a well established relationship, which takes the logarithmic +Kp index and converts it to a linear scale that is easier to handle numerically. +The :py:func:`~GeospaceDataManagement.instruments.methods.kp_ap.convert_3hr_kp_to_ap` +converts Kp to ap, as shown below. + +:: + + + gdm.instruments.methods.kp_ap.convert_3hr_kp_to_ap(kp) + + print("Max: {:.1f} -> {:.1f}, Min: {:.1f} -> {:.1f}".format( + kp['Kp'].max(), kp['3hr_ap'].max(), kp['Kp'].min(), kp['3hr_ap'].min())) + +This yields ``Max: 9.0 -> 400.0, Min: 0.0 -> 0.0``. diff --git a/docs/examples/ex_mock_downloads.rst b/docs/examples/ex_mock_downloads.rst new file mode 100644 index 0000000..eb81db3 --- /dev/null +++ b/docs/examples/ex_mock_downloads.rst @@ -0,0 +1,104 @@ +.. _exmockdown: + +Mock downloads +============== + +The space weather instruments all allow +:py:class:`~GeospaceDataManagement._instrument.Instrument` downloads to +"download" data from a local directory. This allows the user to have full +control over the remote access, while still allowing +:py:mod:`GeospaceDataManagement` to handle the data extraction and file +handling. + +When using the mock-download option, :py:mod:`GeospaceDataManagement` requires +that you specify the local directory where you have stored the desired data +files. If you don't employ this option, downloads will be attempted from the +remote source. If you do employ this option and the directory is wrong, and +IOError will be raised. If instead the expected file is missing, a logging +Information message will be returned. + +:: + + import GeospaceDataManagement as gdm + + f107 = gdm.Instrument(inst_module=gdm.instruments.sw_f107, tag='45day') + + # 'Download' the data from a local directory + f107.download(start=f107.tomorrow(), mock_download_dir='my/data/directory') + + +These data files must have the same name as the remote file. In instances where +there is no remote filename (e.g., when "downloading" data from LISIRD), the +filename should reflect the internal name used by +:py:mod:`GeospaceDataManagement`. The locations and expected filenames for each +of the Instruments are provided in the table below. In this table, YYYY stands +for the 4-digit year, MM stands for the 2-digit month, and DD stands for the +2-digit day-of-month. QUERY is a placeholder for a index and date dependent +query needed to return the desired data. See the GFZ and LISIRD methods to see +how the queries are constructed. + ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| Remote Location | Filename | Instrument(s) | ++========================================================================+====================================+============================================================================================================================+ +| https://services.swpc.noaa.gov/text/ | 3-day-geomag-forecast.txt | sw-ap-forecast, sw-kp-forecast, sw-stormprob-forecast | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | 3-day-solar-geomag-predictions.txt | sw-ap-preciction, sw-f107-forecast, sw-flare-prediction, sw-kp-preciction, sw-polarcap-prediction, sw-stormprob-prediction | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | 45-day-ap-forecast.txt | sw-f107-45day, sw-ap-45day | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | ace-epam.txt | ace-epam-realtime | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | ace-magnetometer.txt | ace-mag-realtime | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | ace-sis.txt | ace-sis-realtime | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | ace-swepam.txt | ace-swepam-realtime | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | daily-geomagnetic-indices.txt | sw-ap-recent, sw-kp-recent | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | daily-solar-indices.txt | sw-ssn-daily, sw-f107-daily, sw-flare-daily, sw-sbfield-daily | ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| https://sohoftp.nascom.nasa.gov/sdb/ace/daily/ | YYYYMMDD_ace_epam_5m.txt | ace-epam-historic | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | YYYYMMDD_ace_mag_1m.txt | ace-mag-historic | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | YYYYMMDD_ace_sis_5m.txt | ace-sis-historic | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | YYYYMMDD_ace_swepam_1m.txt | ace-swepam-historic | ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| ftp://ftp.swpc.noaa.gov/pub/indices/old_indices | YYYY_DSD.txt | sw-ssn-prelim, sw-f107-prelim, sw-flare-prelim, sw-sbfield-prelim | ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| \https://kp.gfz-potsdam.de/app/json/?QUERY | Fadj_YYYY-MM.txt | sw-f107-now-adj | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | Fobs_YYYY-MM.txt | sw-f107-now-obs | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | Hp30_YYYY-MM.txt | sw-hpo-now-30min | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | Hp60_YYYY-MM.txt | sw-hpo-now-60min | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | SN_YYYY-MM.txt | sw-ssn-now | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | ap30_YYYY-MM.txt | sw-apo-now-30min | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | ap60_YYYY-MM.txt | sw-apo-now-60min | ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| https://datapub.gfz-potsdam.de/download/10.5880.Kp.0001/Kp_nowcast/ | Kp_nowYYYY.wdc | sw-ap-now, sw-cp-now, sw-kp-now | ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| https://datapub.gfz-potsdam.de/download/10.5880.Kp.0001/Kp_definitive/ | kp_defYYYY.wdc | sw-ap-def, sw-cp-def, sw-kp-def | ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| ftp://ftp.ngdc.noaa.gov/STP/GEOMAGNETIC_DATA/INDICES/DST | dstYYYY.txt | sw-dst-noaa | ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| \https://lasp.colorado.edu/lisird/latis/dap/QUERY | f107_monthly_YYYY-MM.txt | sw-f107-historic | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | mgii_composite_YYYY-MM.txt | sw-mgii-composite | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | mgii_sorce_YYYY-MM-DD.txt | sw-mgii-sorce | ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| \https://lasp.colorado.edu/space_weather/dsttemerin/ | ae_last_96_hrs.txt | sw-ae-lasp | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | al_last_96_hrs.txt | sw-al-lasp | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | au_last_96_hrs.txt | sw-au-lasp | ++ +------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ +| | dst_last_96_hrs.txt | sw-dst-lasp | ++------------------------------------------------------------------------+------------------------------------+----------------------------------------------------------------------------------------------------------------------------+ diff --git a/docs/examples/ex_mult_downloads.rst b/docs/examples/ex_mult_downloads.rst new file mode 100644 index 0000000..be4daf3 --- /dev/null +++ b/docs/examples/ex_mult_downloads.rst @@ -0,0 +1,91 @@ +.. _exmultdown: + +Downloading data from multiple Instruments +========================================== + +Unlike most data sets, space weather index data sets often contain a combination +of related indices. This means that data from multiple +:py:class:`GeospaceDataManagement.Instrument` sub-modules may be available in a +single file. This data is saved for all +:py:class:`GeospaceDataManagement.Instrument` sub-modules when downloading any +one of them. In this way, downloads are minimized and no data sets are hidden +or thrown away. The following example returns both F\ :sub:`10.7`\ and Ap +forecasts from SWPC. + +:: + + import GeospaceDataManagement as gdm + + f107 = gdm.Instrument(inst_module=gdm.instruments.sw_f107, tag='45day') + ap = gdm.Instrument(inst_module=gdm.instruments.sw_ap, tag='45day') + + # Test to see this data hasn't already been downloaded + assert (ap.today() not in f107.files.files) and (ap.today() + not in ap.files.files) + + # Download both data sets using only one Instrument + f107.download(start=f107.tomorrow()) + ap.download(start=ap.tomorrow()) + + # Show that both files have been downloaded + print(f107.files.files[f107.today()], ap.files.files[ap.today()]) + + +This will yield ``f107_45day_YYYY-MM-DD.txt ap_45day_YYYY-MM-DD.txt``, where +YYYY-MM-DD is the day you run this example. The table below shows a list of +the :py:class:`GeospaceDataManagement.Instrument` sub-modules and tags that +download multiple data sets. When possible, the same tag has been used across +:py:class:`GeospaceDataManagement.Instrument` sub-modules. + + ++----------------------+----------+-----------+------------+------------+ +| Remote Data Set | Platform | Name | Tag(s) | Inst ID(s) | ++======================+==========+===========+============+============+ +| GFZ Kp | SW | Kp | def, now | | ++----------------------+----------+-----------+------------+------------+ +| | | Ap | | | ++----------------------+----------+-----------+------------+------------+ +| | | Cp | | | ++----------------------+----------+-----------+------------+------------+ +| SWPC Daily DSD | SW | F107 | daily | | ++----------------------+----------+-----------+------------+------------+ +| | | Flare | | | ++----------------------+----------+-----------+------------+------------+ +| | | SSN | | | ++----------------------+----------+-----------+------------+------------+ +| | | SBField | | | ++----------------------+----------+-----------+------------+------------+ +| SWPC Prelim DSD | SW | F107 | prelim | | ++----------------------+----------+-----------+------------+------------+ +| | | Flare | | | ++----------------------+----------+-----------+------------+------------+ +| | | SSN | | | ++----------------------+----------+-----------+------------+------------+ +| | | SBField | | | ++----------------------+----------+-----------+------------+------------+ +| SWPC 3-day Solar-Geo | SW | F107 | forecast | | ++----------------------+----------+-----------+------------+------------+ +| Predictions | | Kp | prediction | | ++----------------------+----------+-----------+------------+------------+ +| | | Ap | | | ++----------------------+----------+-----------+------------+------------+ +| | | StormProb | | | ++----------------------+----------+-----------+------------+------------+ +| | | Flare | | | ++----------------------+----------+-----------+------------+------------+ +| | | PolarCap | | | ++----------------------+----------+-----------+------------+------------+ +| SWPC 3-day Geomag | SW | Kp | forecast | | ++----------------------+----------+-----------+------------+------------+ +| Forecast | | Ap | | | ++----------------------+----------+-----------+------------+------------+ +| | | StormProb | | | ++----------------------+----------+-----------+------------+------------+ +| SWPC Daily Geomag | SW | Kp | recent | | ++----------------------+----------+-----------+------------+------------+ +| | | Ap | | | ++----------------------+----------+-----------+------------+------------+ +| SWPC 45-day Forecast | SW | F107 | 45day | | ++----------------------+----------+-----------+------------+------------+ +| | | Ap | | | ++----------------------+----------+-----------+------------+------------+ diff --git a/docs/examples/ex_sw_init.rst b/docs/examples/ex_sw_init.rst new file mode 100644 index 0000000..efa165b --- /dev/null +++ b/docs/examples/ex_sw_init.rst @@ -0,0 +1,47 @@ +.. _exswinit: + +Loading F\ :sub:`10.7`\ +======================== + +The Space Weather Instruments included as an optional installation option +provide different historical, real-time, and forecasted solar, geomagnetic, and +other space weather indices. As specified in :ref:`tutorial_basics`, data may +be loaded using the following commands. Historic F\ :sub:`10.7`\ is used as +an example. + +:: + + + import GeospaceDataManagement as gdm + + f107 = gdm.Instrument(inst_module=gdm.instruments.sw_f107, + tag='historic', update_files=True) + f107.download(start=f107.lasp_stime, stop=f107.today()) + f107.load() + print(f107.data) + + +The output includes all available historic data (as implied by the tag name), +including the specified date. This data set starts on 14 February 1947, as +indicated by the special instrument attribute `f107.lasp_stime`, and will +not reach up to the present day. At the time of publication this produces the +output shown below (the index header has been added here for clarity). + +:: + + + f107 f107_adjusted f107_observed + 1947-02-14 253.9 253.9 NaN + 1947-02-17 228.5 228.5 NaN + 1947-02-19 178.8 178.8 NaN + 1947-02-20 163.7 163.7 NaN + 1947-02-24 164.1 164.1 NaN + ... ... ... ... + 2018-04-27 69.6 69.6 68.7 + 2018-04-28 71.1 71.1 70.2 + 2018-04-29 72.2 72.2 71.1 + 2018-04-30 71.3 71.3 70.2 + + [25367 rows x 3 columns] + + diff --git a/docs/images/ex_ace_omni.png b/docs/images/ex_ace_omni.png new file mode 100644 index 0000000..7772115 Binary files /dev/null and b/docs/images/ex_ace_omni.png differ diff --git a/docs/images/ex_f107_all.png b/docs/images/ex_f107_all.png new file mode 100644 index 0000000..7772111 Binary files /dev/null and b/docs/images/ex_f107_all.png differ diff --git a/docs/images/ex_kp_all.png b/docs/images/ex_kp_all.png new file mode 100644 index 0000000..4f06810 Binary files /dev/null and b/docs/images/ex_kp_all.png differ diff --git a/docs/index.rst b/docs/index.rst index e19c922..5cc19e8 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -1,10 +1,7 @@ -.. pysat documentation main file, created by - sphinx-quickstart on Thu Apr 23 23:07:56 2015. - You can adapt this file completely to your liking, but it should at least - contain the root `toctree` directive. +.. gdm documentation main file -Welcome to pysat's documentation! -================================= +Welcome to the GeospaceDataManagement documentation +=================================================== .. toctree:: :maxdepth: 2 @@ -15,6 +12,7 @@ Welcome to pysat's documentation! installation.rst quickstart.rst tutorial.rst + examples.rst instruments.rst new_instrument.rst dependency.rst diff --git a/docs/instruments.rst b/docs/instruments.rst index c876c2a..a15e655 100644 --- a/docs/instruments.rst +++ b/docs/instruments.rst @@ -8,3 +8,4 @@ Instruments instruments/general_instruments.rst instruments/testing_instruments.rst + instruments/sw_instruments.rst diff --git a/docs/instruments/sw_instruments.rst b/docs/instruments/sw_instruments.rst new file mode 100644 index 0000000..35306e0 --- /dev/null +++ b/docs/instruments/sw_instruments.rst @@ -0,0 +1,446 @@ +.. _instruments-sw: + +Space Weather Instruments +========================= + +These :py:class:`~GeospaceDataManagement._instruments.Instrument` modules are +made available with the 'space_weather' installation option. + +.. _ace-inst: + +ACE +--- + +The Space Weather Prediction Center (SWPC) provides several Advanced +Composition Explorer (ACE) instrument data sets for use as real-time and +historic measurements of the solar wind. This differs from the ACE scientific +data, which is available at a greater latency from +`CDAWeb `_. Information about these +data sets can be found at the `SWPC ACE Solar-Wind page +`_. + + +.. _ace-epam-inst: + +ACE EPAM +^^^^^^^^ + +EPAM is the Electron, Proton, and Alpha Monitor onboard ACE. + + +.. automodule:: GeospaceDataManagement.instruments.ace_epam + :members: + + +.. _ace-mag-inst: + +ACE MAG +^^^^^^^ + +Supports ACE Magnetometer data. + + +.. automodule:: GeospaceDataManagement.instruments.ace_mag + :members: + + +.. _ace-sis-inst: + +ACE SIS +^^^^^^^ + +Supports ACE Solar Isotope Spectrometer data. + + +.. automodule:: GeospaceDataManagement.instruments.ace_sis + :members: + + +.. _ace-swepam-inst: + +ACE SWEPAM +^^^^^^^^^^ + +Supports ACE Solar Wind Electron Proton Alpha Monitor data. + + +.. automodule:: GeospaceDataManagement.instruments.ace_swepam + :members: + + +.. _norp-inst: + +NoRP +---- + +The Nobeyama Radio Polarameters (NoRP) platform encompasses solar flux +measurements provided by the Japanese Solar Science Observatory. +`NoRP `_ provides +additional information and processing tools on their website. + +.. _norp-rf-inst: + +RF +^^^ + +RF is the radio flux measured from the sun at different wavelengths. This +provides a different measure of solar activity and has been corrected to be +in solar flux units at 1 AU. The daily data set currently starts in Nov 1951 +and is updated to extend to the current period, but not in real-time. + + +.. automodule:: GeospaceDataManagement.instruments.norp_rf + :members: + + +.. _sw-inst: + +SW +--- + +The Space Weather (SW) platform encompasses space weather indices that may be +found across a variety of platforms. Many of the remote centers that provide +these data sets include multiple types of data in each file. From +:py:mod:`GeospaceDataManagement` version 0.1.0, the remote information is separated +by :py:class:`pysat.Instrument` and saved into appropriate files. For example, +the definitive Kp data from the German Research Centre for Geosciences at +Potsdam (GFZ) will also download Ap and Cp data files. + +.. _sw-ae-inst: + +AE +^^^ + +AE is an auroral electrojet index that reflects the level of magnetic deflection +in the auroral zone due to the difference between the eastward and westward +electroject currents at Earth. Real-time predictions (last 96 hours) are +provided by +`LASP `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_ae + :members: + + +.. _sw-al-inst: + + +AL +^^^ + +AL is an auroral electrojet index that reflects the lower envelope, the negative +peak of the electroject currents at Earth. Real-time predictions (last 96 +hours) are provided by the +`LASP repository `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_al + :members: + + +.. _sw-au-inst: + + +AU +^^^ + +AU is an auroral electrojet index that reflects the upper envelope, the positive +peak of the electroject currents at Earth. Real-time predictions (last 96 +hours) are provided at the +`LASP page `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_au + :members: + + +.. _sw-ap-inst: + +Ap +^^^ + +Ap is a geomagnetic index that reflects the magnitude of geomagnetic +disturbances at Earth but unlike Kp uses a linear scale. Historic, recent +(last 30 days), and forecasted values are available from the +`GFZ Kp `_ and the +`SWPC Forecasts page `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_ap + :members: + + +.. _sw-apo-inst: + +apo +^^^ + +apo is a linear (half)-hourly, planetary, open-ended, geomagnetic index that +reflects the magnitude of geomagnetic disturbances at Earth. It is like Ap but +does not have an upper limit. Values from 1995 onwards are available from the +`GFZ Hpo page `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_apo + :members: + + +.. _sw-cp-inst: + +Cp +^^^ + +Cp is a derivative geomagnetic index that provides a qualitative estimate of the +overall level of magnetic activity for the day. The C9 index provides the same +information on a scale from 0-9 instead of 0.0-2.5. Historic values are +available from the `GFZ Kp page `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_cp + :members: + + +.. _sw-dst-inst: + +Dst +^^^ + +The Disturbance Storm Time (Dst) Index is a measure of magnetic activity +associated with the ring current. The National Centers for Environmental +Information (NCEI), formerly the National Geophysical Data Center (NGDC), +maintains the current database from which the historic Dst is downloaded. +`LASP `_ +performs the calculations and provides the predicted Dst for the last 96 hours. +You can learn more about the Dst Index at the +`WDC Kyoto Observatory page `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_dst + :members: + + +.. _sw-f107-inst: + +F \ :sub:`10.7`\ +^^^^^^^^^^^^^^^^ + +F \ :sub:`10.7`\ is the 10.7 cm radio solar flux (measured in solar flux units, +sfu) `[Cortie 1912] `_. +Historic indices, real-time indices, and forecasted indices are available from +the +`LASP F107 `_ and the +`SWPC F107 page `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_f107 + :members: + + +.. _sw-flare-inst: + +Solar Flares +^^^^^^^^^^^^ + +Solar flares have been monitored for decades and the data has been compiled +into standard measurements from different data sets. Historic indices, +real-time indices, and forecasted indices are available from +`SWPC `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_flare + :members: + + +.. _sw-hpo-inst: + +Hpo +^^^ + +Hpo is a (half)-Hourly, planetary, open-ended, geomagnetic index that +reflects the magnitude of geomagnetic disturbances at Earth. It is like Kp but +does not have an upper limit. Values from 1995 onwards are available from the +`GFZ Hp30 and Hp60 page `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_hpo + :members: + + + +.. _sw-kp-inst: + +Kp +^^^ + +Kp is a geomagnetic index that reflects the magnitude of geomagnetic +disturbances at Earth. Historic, recent (last 30 days), and forecasted values +are available from the +`GFZ Kp repository `_, and the +`SWPC Kp page `_. + + +.. automodule:: GeospaceDataManagement.instruments.sw_kp + :members: + + +.. _mgii-inst: + +MgII Core-to-Wing Ratio +^^^^^^^^^^^^^^^^^^^^^^^ + +The core-to-wing ratio of the solar MgII line is a proxy for solar chromospheric +variability. It has been used to extract a precise measurement of solar +activity at Earth. The two data sets provided by LASP together provide index +values from 1978 through 2020. + + +.. automodule:: GeospaceDataManagement.instruments.sw_mgii + :members: + +.. _sw-pc-inst: + +Polar Cap +^^^^^^^^^ + +Polar cap indices have been developed to provide information about high-latitude +conditions and inform ionospheric space weather models. Currently, this +:py:class:`~pysat._instrument.Instrument` provides absorption predictions from SWPC. + +.. automodule:: GeospaceDataManagement.instruments.sw_polarcap + :members: + + +.. _sw-sbfield-inst: + +Solar Magnetic Field +^^^^^^^^^^^^^^^^^^^^ + +The solar mean field provides a measure of of mean solar magnetic field using +full-disk optical observations of the iron line. The first observations were +made at Stanford by +`Scherrer et al. `_. + +.. automodule:: GeospaceDataManagement.instruments.sw_sbfield + :members: + + +.. _sw-ssn-inst: + +Sunspot Number +^^^^^^^^^^^^^^ + +The Sunspot Number (SSN) is one of the oldest continuously measured solar +indices. Currently, this Instrument provides preliminary and daily values from +SWPC (for example, here is the +`forecast page `_). + +.. automodule:: GeospaceDataManagement.instruments.sw_ssn + :members: + + +.. _sw-stormprob-inst: + +Storm Probability +^^^^^^^^^^^^^^^^^ + +Geomagnetic storm predictions are provided by SWPC for global, high-latitude, +and mid-latitude regions. SWPC uses the +`NOAA SW scales `_, which +are explained here. + +.. automodule:: GeospaceDataManagement.instruments.sw_stormprob + :members: + + +.. _sw-methods: + +Methods +------- + +Several methods exist to help combine multiple data sets and convert between +equivalent indices. Most of these directly support the Instrument sub-modules, +but others contain useful tools for manipulating specific data sets. + +ACE Methods +^^^^^^^^^^^ + +Supports the ACE instrument by providing reference and acknowledgement +information. + + +.. automodule:: GeospaceDataManagement.instruments.sw_methods.ace + :members: + +Dst Methods +^^^^^^^^^^^ + +Supports the Dst ring current index by providing reference and acknowledgement +information. + + +.. automodule:: GeospaceDataManagement.instruments.sw_methods.dst + :members: + +F \ :sub:`10.7`\ Methods +^^^^^^^^^^^^^^^^^^^^^^^^ + +Supports the F \ :sub:`10.7`\ radio flux by providing reference and +acknowledgement information as well as a routine to combine +F \ :sub:`10.7`\ data obtained from multiple sources. + + +.. automodule:: GeospaceDataManagement.instruments.sw_methods.f107 + :members: + + +Space Weather General Methods +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +General functions that are useful across the Space Weather Instruments. + + +.. automodule:: GeospaceDataManagement.instruments.sw_methods.general + :members: + + +GFZ Methods +^^^^^^^^^^^ + +Supports the German Research Centre for Geosciences at Potsdam (GFZ) data +products. + + +.. automodule:: GeospaceDataManagement.instruments.sw_methods.gfz + :members: + + +Kp and Ap Methods +^^^^^^^^^^^^^^^^^ + +Supports the Kp instrument by providing reference and acknowledgement +information, a routine to combine Kp from multiple sources, routines to convert +between Kp and Ap, and a routine that uses Kp data as a geomagnetic activity +filter for other data sets. + + +.. automodule:: GeospaceDataManagement.instruments.sw_methods.kp_ap + :members: + +LISIRD Methods +^^^^^^^^^^^^^^ + +Contains functions to support LASP Interactive Solar IRradiance Datacenter +(LISIRD) data sets and downloads. + + +.. automodule:: GeospaceDataManagement.instruments.sw_methods.lisird + :members: + +SWPC Methods +^^^^^^^^^^^^ + +Supports the Space Weather Prediction Center (SWPC) data products. + + +.. automodule:: GeospaceDataManagement.instruments.sw_methods.swpc + :members: diff --git a/docs/new_instrument.rst b/docs/new_instrument.rst index 2ef408b..8c116f4 100644 --- a/docs/new_instrument.rst +++ b/docs/new_instrument.rst @@ -36,9 +36,9 @@ syntax: import my_package registry.register_from_module(my_package.instruments) -After registry the instrument module name is stored in the user's home -directory in a hidden directory named :code:`~.GeospaceDataManagement`. The -instrument may then be instantiated with the instrument's platform and name: +After registry the instrument module name is stored in the user's home directory +in a hidden directory named :code:`~/.gdm`. The instrument may then be +instantiated with the instrument's platform and name: .. code-block:: python diff --git a/docs/quickstart.rst b/docs/quickstart.rst index 1eb9120..bc4b80e 100644 --- a/docs/quickstart.rst +++ b/docs/quickstart.rst @@ -28,9 +28,10 @@ it will remind you that you need to set this variable for your system. path that specifies a top-level directory to store science data. Most people are fine setting a single path for all of their data, but other -people have a LOT of data and need to store it on multiple disks. GeospaceDataManagement supports -setting the :py:attr:`data_dirs` parameter equal to either a string or a list of -strings, as illustrated in the example below. +people have a LOT of data and need to store it on multiple disks. +GeospaceDataManagement supports setting the :py:attr:`data_dirs` parameter +equal to either a string or a list of strings, as illustrated in the example +below. .. code:: python @@ -88,5 +89,4 @@ Explore the Possibilities At this point, you are set up to start exploring the tools and methods :py:mod:`GeospaceDataManagement` provides. For a more detailed -dive into :py:mod:`GeospaceDataManagement`, check out the :ref:`tutorial` and -:ref:`examples`. +dive into :py:mod:`GeospaceDataManagement`, check out the :ref:`tutorial`. diff --git a/pyproject.toml b/pyproject.toml index 080284d..48e24cf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "GeospaceDataManagement" -version = "0.0.1" +version = "0.0.2" description = "Supports scientific data management for geospace products" readme = "README.md" requires-python = ">=3.10" @@ -56,7 +56,6 @@ test = [ "flake8 >= 3.8.4", "flake8-docstrings >= 1.5", "hacking >= 1.0", - "pysatSpaceWeather<0.1.0", "pytest-cov >= 2.10.1", "pytest-ordering >= 0.6" ] @@ -69,6 +68,9 @@ doc = [ "sphinx >= 3.4.1", "sphinx_rtd_theme >= 1.2.2" ] +space_weather = [ + "requests" +] [project.urls] Source = "https://github.com/USNavalResearchLaboratory/GeospaceDataManagement" diff --git a/requirements.txt b/requirements.txt index 6671a14..889d14b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,6 +1,6 @@ dask netCDF4 -numpy>=1.12 +numpy>=1.21.6 pandas portalocker pytest