doc: Update docstrings across fitbase/ and pdf/ to group standards

docs/examples/coreshellnp.py

@@ -20,7 +20,8 @@
 different phases, each with an appropriate characteristic function.
 """
 
-import numpy
+from pathlib import Path
+
 from pyobjcryst import loadCrystal
 from scipy.optimize import leastsq
 
@@ -134,35 +135,18 @@ def makeRecipe(stru1, stru2, datname):
     return recipe
 
 
-def plotResults(recipe):
-    """Plot the results contained within a refined FitRecipe."""
-    # All this should be pretty familiar by now.
-    r = recipe.cdszns.profile.x
-    g = recipe.cdszns.profile.y
-    gcalc = recipe.cdszns.profile.ycalc
-    diffzero = -0.8 * max(g) * numpy.ones_like(g)
-    diff = g - gcalc + diffzero
-
-    import pylab
-
-    pylab.plot(r, g, "bo", label="G(r) Data")
-    pylab.plot(r, gcalc, "r-", label="G(r) Fit")
-    pylab.plot(r, diff, "g-", label="G(r) diff")
-    pylab.plot(r, diffzero, "k-")
-    pylab.xlabel(r"$r (\AA)$")
-    pylab.ylabel(r"$G (\AA^{-2})$")
-    pylab.legend(loc=1)
-
-    pylab.show()
-    return
+plot_styles = {
+    "xlabel": r"$r (\AA)$",
+    "ylabel": r"$G (\AA^{-2})$",
+}
 
 
 def main():
     """Set up and refine the recipe."""
     # Make the data and the recipe
-    cdsciffile = "data/CdS.cif"
-    znsciffile = "data/ZnS.cif"
-    data = "data/CdS_ZnS_nano.gr"
+    cdsciffile = Path(__file__).parent / "data/CdS.cif"
+    znsciffile = Path(__file__).parent / "data/ZnS.cif"
+    data = Path(__file__).parent / "data/CdS_ZnS_nano.gr"
 
     # Make the recipe
     stru1 = loadCrystal(cdsciffile)
@@ -206,7 +190,7 @@ def main():
     res.print_results()
 
     # Plot!
-    plotResults(recipe)
+    recipe.plot_recipe(**plot_styles)
     return
 
 

docs/examples/crystalpdf.py

@@ -24,7 +24,8 @@
 demonstrates only the basic configuration.
 """
 
-import numpy
+from pathlib import Path
+
 from gaussianrecipe import scipyOptimize
 
 from diffpy.srfit.fitbase import (
@@ -67,7 +68,7 @@ def makeRecipe(ciffile, datname):
     # Qmax value, as well as initial values for the non-structural Parameters.
     generator = PDFGenerator("G")
     stru = Structure()
-    stru.read(ciffile)
+    stru.read(str(ciffile))
     generator.setStructure(stru)
 
     # The FitContribution
@@ -129,34 +130,17 @@ def makeRecipe(ciffile, datname):
     return recipe
 
 
-def plotResults(recipe):
-    """Plot the results contained within a refined FitRecipe."""
-    # All this should be pretty familiar by now.
-    r = recipe.nickel.profile.x
-    g = recipe.nickel.profile.y
-    gcalc = recipe.nickel.profile.ycalc
-    diffzero = -0.8 * max(g) * numpy.ones_like(g)
-    diff = g - gcalc + diffzero
-
-    import pylab
-
-    pylab.plot(r, g, "bo", label="G(r) Data")
-    pylab.plot(r, gcalc, "r-", label="G(r) Fit")
-    pylab.plot(r, diff, "g-", label="G(r) diff")
-    pylab.plot(r, diffzero, "k-")
-    pylab.xlabel(r"$r (\AA)$")
-    pylab.ylabel(r"$G (\AA^{-2})$")
-    pylab.legend(loc=1)
-
-    pylab.show()
-    return
+plot_styles = {
+    "xlabel": r"$r (\AA)$",
+    "ylabel": r"$G (\AA^{-2})$",
+}
 
 
 if __name__ == "__main__":
 
     # Make the data and the recipe
-    ciffile = "data/ni.cif"
-    data = "data/ni-q27r100-neutron.gr"
+    ciffile = Path(__file__).parent / "data/ni.cif"
+    data = Path(__file__).parent / "data/ni-q27r100-neutron.gr"
 
     # Make the recipe
     recipe = makeRecipe(ciffile, data)
@@ -170,6 +154,6 @@ def plotResults(recipe):
     res.print_results()
 
     # Plot!
-    plotResults(recipe)
+    recipe.plot_recipe(**plot_styles)
 
 # End of file

docs/examples/crystalpdfall.py

@@ -18,7 +18,8 @@
 structure to all the available data.
 """
 
-import numpy
+from pathlib import Path
+
 from gaussianrecipe import scipyOptimize
 from pyobjcryst import loadCrystal
 
@@ -143,82 +144,20 @@ def makeRecipe(
     return recipe
 
 
-def plotResults(recipe):
-    """Plot the results contained within a refined FitRecipe."""
-    # All this should be pretty familiar by now.
-    xnickel = recipe.xnickel
-    xr_ni = xnickel.profile.x
-    xg_ni = xnickel.profile.y
-    xgcalc_ni = xnickel.profile.ycalc
-    xdiffzero_ni = -0.8 * max(xg_ni) * numpy.ones_like(xg_ni)
-    xdiff_ni = xg_ni - xgcalc_ni + xdiffzero_ni
-
-    xsilicon = recipe.xsilicon
-    xr_si = xsilicon.profile.x
-    xg_si = xsilicon.profile.y
-    xgcalc_si = xsilicon.profile.ycalc
-    xdiffzero_si = -0.8 * max(xg_si) * numpy.ones_like(xg_si)
-    xdiff_si = xg_si - xgcalc_si + xdiffzero_si
-
-    nnickel = recipe.nnickel
-    nr_ni = nnickel.profile.x
-    ng_ni = nnickel.profile.y
-    ngcalc_ni = nnickel.profile.ycalc
-    ndiffzero_ni = -0.8 * max(ng_ni) * numpy.ones_like(ng_ni)
-    ndiff_ni = ng_ni - ngcalc_ni + ndiffzero_ni
-
-    xsini = recipe.xsini
-    xr_sini = xsini.profile.x
-    xg_sini = xsini.profile.y
-    xgcalc_sini = xsini.profile.ycalc
-    xdiffzero_sini = -0.8 * max(xg_sini) * numpy.ones_like(xg_sini)
-    xdiff_sini = xg_sini - xgcalc_sini + xdiffzero_sini
-
-    import pylab
-
-    pylab.subplot(2, 2, 1)
-    pylab.plot(xr_ni, xg_ni, "bo", label="G(r) x-ray nickel Data")
-    pylab.plot(xr_ni, xgcalc_ni, "r-", label="G(r) x-ray nickel Fit")
-    pylab.plot(xr_ni, xdiff_ni, "g-", label="G(r) x-ray nickel diff")
-    pylab.plot(xr_ni, xdiffzero_ni, "k-")
-    pylab.xlabel(r"$r (\AA)$")
-    pylab.ylabel(r"$G (\AA^{-2})$")
-    pylab.legend(loc=1)
-
-    pylab.subplot(2, 2, 2)
-    pylab.plot(xr_si, xg_si, "bo", label="G(r) x-ray silicon Data")
-    pylab.plot(xr_si, xgcalc_si, "r-", label="G(r) x-ray silicon Fit")
-    pylab.plot(xr_si, xdiff_si, "g-", label="G(r) x-ray silicon diff")
-    pylab.plot(xr_si, xdiffzero_si, "k-")
-    pylab.legend(loc=1)
-
-    pylab.subplot(2, 2, 3)
-    pylab.plot(nr_ni, ng_ni, "bo", label="G(r) neutron nickel Data")
-    pylab.plot(nr_ni, ngcalc_ni, "r-", label="G(r) neutron nickel Fit")
-    pylab.plot(nr_ni, ndiff_ni, "g-", label="G(r) neutron nickel diff")
-    pylab.plot(nr_ni, ndiffzero_ni, "k-")
-    pylab.legend(loc=1)
-
-    pylab.subplot(2, 2, 4)
-    pylab.plot(xr_sini, xg_sini, "bo", label="G(r) x-ray sini Data")
-    pylab.plot(xr_sini, xgcalc_sini, "r-", label="G(r) x-ray sini Fit")
-    pylab.plot(xr_sini, xdiff_sini, "g-", label="G(r) x-ray sini diff")
-    pylab.plot(xr_sini, xdiffzero_sini, "k-")
-    pylab.legend(loc=1)
-
-    pylab.show()
-    return
-
+plot_styles = {
+    "xlabel": r"$r (\AA)$",
+    "ylabel": r"$G (\AA^{-2})$",
+}
 
 if __name__ == "__main__":
 
     # Make the data and the recipe
-    ciffile_ni = "data/ni.cif"
-    ciffile_si = "data/si.cif"
-    xdata_ni = "data/ni-q27r60-xray.gr"
-    ndata_ni = "data/ni-q27r100-neutron.gr"
-    xdata_si = "data/si-q27r60-xray.gr"
-    xdata_sini = "data/si90ni10-q27r60-xray.gr"
+    ciffile_ni = Path(__file__).parent / "data/ni.cif"
+    ciffile_si = Path(__file__).parent / "data/si.cif"
+    xdata_ni = Path(__file__).parent / "data/ni-q27r60-xray.gr"
+    ndata_ni = Path(__file__).parent / "data/ni-q27r100-neutron.gr"
+    xdata_si = Path(__file__).parent / "data/si-q27r60-xray.gr"
+    xdata_sini = Path(__file__).parent / "data/si90ni10-q27r60-xray.gr"
 
     # Make the recipe
     recipe = makeRecipe(
@@ -232,7 +171,9 @@ def plotResults(recipe):
     res = FitResults(recipe)
     res.print_results()
 
-    # Plot!
-    plotResults(recipe)
+    # Plot! The recipe has four contributions ("xnickel", "xsilicon",
+    # "nnickel", "xsini"), so plot_recipe produces one figure per
+    # contribution.
+    recipe.plot_recipe(**plot_styles)
 
 # End of file

docs/examples/crystalpdfobjcryst.py

@@ -19,7 +19,8 @@
 provided by the ObjCrystCrystalParSet structure adapter.
 """
 
-from crystalpdf import plotResults
+from pathlib import Path
+
 from gaussianrecipe import scipyOptimize
 from pyobjcryst import loadCrystal
 
@@ -90,9 +91,6 @@ def makeRecipe(ciffile, datname):
     # things by iterating through all the sgpars.
     for par in phase.sgpars:
         recipe.add_variable(par)
-    # set the initial thermal factor to a non-zero value
-    assert hasattr(recipe, "B11_0")
-    recipe.B11_0 = 0.1
 
     # We now select non-structural parameters to refine.
     # This controls the scaling of the PDF.
@@ -106,11 +104,17 @@ def makeRecipe(ciffile, datname):
     return recipe
 
 
+plot_styles = {
+    "xlabel": r"$r (\AA)$",
+    "ylabel": r"$G (\AA^{-2})$",
+}
+
+
 if __name__ == "__main__":
 
     # Make the data and the recipe
-    ciffile = "data/si.cif"
-    data = "data/si-q27r60-xray.gr"
+    ciffile = Path(__file__).parent / "data/si.cif"
+    data = Path(__file__).parent / "data/si-q27r60-xray.gr"
 
     # Make the recipe
     recipe = makeRecipe(ciffile, data)
@@ -123,6 +127,6 @@ def makeRecipe(ciffile, datname):
     res.print_results()
 
     # Plot!
-    plotResults(recipe)
+    recipe.plot_recipe(**plot_styles)
 
 # End of file

docs/examples/crystalpdftwodata.py

@@ -20,7 +20,8 @@
 underlying ObjCrystCrystalParSet.
 """
 
-import numpy
+from pathlib import Path
+
 from gaussianrecipe import scipyOptimize
 from pyobjcryst import loadCrystal
 
@@ -134,49 +135,18 @@ def makeRecipe(ciffile, xdatname, ndatname):
     return recipe
 
 
-def plotResults(recipe):
-    """Plot the results contained within a refined FitRecipe."""
-    # All this should be pretty familiar by now.
-    xr = recipe.xnickel.profile.x
-    xg = recipe.xnickel.profile.y
-    xgcalc = recipe.xnickel.profile.ycalc
-    xdiffzero = -0.8 * max(xg) * numpy.ones_like(xg)
-    xdiff = xg - xgcalc + xdiffzero
-
-    nr = recipe.nnickel.profile.x
-    ng = recipe.nnickel.profile.y
-    ngcalc = recipe.nnickel.profile.ycalc
-    ndiffzero = -0.8 * max(ng) * numpy.ones_like(ng)
-    ndiff = ng - ngcalc + ndiffzero
-
-    import pylab
-
-    pylab.subplot(2, 1, 1)
-    pylab.plot(xr, xg, "bo", label="G(r) x-ray Data")
-    pylab.plot(xr, xgcalc, "r-", label="G(r) x-ray Fit")
-    pylab.plot(xr, xdiff, "g-", label="G(r) x-ray diff")
-    pylab.plot(xr, xdiffzero, "k-")
-    pylab.legend(loc=1)
-
-    pylab.subplot(2, 1, 2)
-    pylab.plot(nr, ng, "bo", label="G(r) neutron Data")
-    pylab.plot(nr, ngcalc, "r-", label="G(r) neutron Fit")
-    pylab.plot(nr, ndiff, "g-", label="G(r) neutron diff")
-    pylab.plot(nr, ndiffzero, "k-")
-    pylab.xlabel(r"$r (\AA)$")
-    pylab.ylabel(r"$G (\AA^{-2})$")
-    pylab.legend(loc=1)
-
-    pylab.show()
-    return
+plot_styles = {
+    "xlabel": r"$r (\AA)$",
+    "ylabel": r"$G (\AA^{-2})$",
+}
 
 
 if __name__ == "__main__":
 
     # Make the data and the recipe
-    ciffile = "data/ni.cif"
-    xdata = "data/ni-q27r60nodg-xray.gr"
-    ndata = "data/ni-q27r100-neutron.gr"
+    ciffile = Path(__file__).parent / "data/ni.cif"
+    xdata = Path(__file__).parent / "data/ni-q27r60nodg-xray.gr"
+    ndata = Path(__file__).parent / "data/ni-q27r100-neutron.gr"
 
     # Make the recipe
     recipe = makeRecipe(ciffile, xdata, ndata)
@@ -188,7 +158,9 @@ def plotResults(recipe):
     res = FitResults(recipe)
     res.print_results()
 
-    # Plot!
-    plotResults(recipe)
+    # Plot! The recipe has two contributions ("xnickel" for x-ray,
+    # "nnickel" for neutron), so plot_recipe produces one figure per
+    # contribution.
+    recipe.plot_recipe(**plot_styles)
 
 # End of file