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| Layer / File(s) | Summary |
|---|---|
Preserve automatic major tick generation python/xy/pyplot/_axes.py, tests/pyplot/test_axis_tick_gallery_compat.py |
The axis logic leaves automatic linear major positions unset when no labels are present. Tests cover minorticks_on() and shared nonlinear axes. |
Priority:
Estimated code review effort: 2 (Simple) | ~10 minutes
Change: Bug fix · Severity of issue fixed: Medium
Possibly related PRs
- reflex-dev/xy#470: Changes tick getter and setter semantics, including how minor tick positions are computed and published.
Suggested reviewers: farhanaliraza, alek99
Merge Risk: 
bd658
-
Major tick density can change unexpectedly, and datetime axes can show misplaced or missing minor ticks when minor ticks are enabled.
Pre-merge checks: 
-
Check name Status Explanation Description Check Check skipped - CodeRabbit’s high-level summary is enabled. Title check The title clearly and concisely describes the main change: preventing minorticks_on() from fixing automatically generated major ticks. Linked Issues check Issue #493requiresminorticks_on()to keep automatic major ticks unpinned._apply_tickersnow detects automatic majors and does not publishtick_values; it still computes and publishes `minor_t…Out of Scope Changes check The changes stay within the tick-generation scope of issue #493. The production change prevents automatic major positions from becoming authored positions. The added tests cover the reported regressio…Docstring Coverage Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Documentation-only edits and deletions within survi… Full details: Linked Issues check
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Explanation
Issue
#493requiresminorticks_on()to keep automatic major ticks unpinned._apply_tickersnow detects automatic majors and does not publishtick_values; it still computes and publishesminor_tick_valuesandtick_count. The new regression test verifies both payload properties. The shared nonlinear-axis test protects the required label and position pairing.
Full details: Out of Scope Changes check
-
Explanation
The changes stay within the tick-generation scope of issue
#493. The production change prevents automatic major positions from becoming authored positions. The added tests cover the reported regression and label-position compatibility for nonlinear shared axes. No unrelated production or client changes are present.
Full details: Docstring Coverage
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Explanation
Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Documentation-only edits and deletions within surviving functions are included; unchanged diff context and fully deleted functions are excluded. Analyzed 1 functions across 1 files.
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Inline comments:
In `@tests/pyplot/test_axis_tick_gallery_compat.py`:
- Around line 323-327: Update the x-data setup in the shared-axis test so the
logit scale uses values within its valid (0, 1) domain, such as a linspace from
0.01 to 0.99, while preserving the existing range for other scales. Keep the
plotting and set_xscale flow unchanged.
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📒 Files selected for processing (2)
python/xy/pyplot/_axes.pytests/pyplot/test_axis_tick_gallery_compat.py
🚧 Files skipped from review as they are similar to previous changes (1)
- python/xy/pyplot/_axes.py
| xs = np.linspace(-100, 100, 50) | ||
| _fig, (leader, follower) = plt.subplots(2, sharex=True) | ||
| leader.plot(xs, xs) | ||
| follower.plot(xs, xs) | ||
| follower.set_xscale(scale, **({"linthresh": 2.0} if scale == "symlog" else {})) |
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🎯 Functional Correctness | 🟡 Minor | ⚡ Quick win
🧩 Analysis chain
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#!/bin/bash
set -eu
printf '%s\n' '--- target test ---'
sed -n '280,345p' tests/pyplot/test_axis_tick_gallery_compat.py
printf '%s\n' '--- scale references ---'
rg -n "logit|set_xscale|linthresh|tick_values" . -g '*.py' -g '!build/**' -g '!dist/**' | head -200Repository: reflex-dev/xy
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from pathlib import Path
p = Path("tests/pyplot/test_axis_tick_gallery_compat.py")
lines = p.read_text().splitlines()
for i in range(295, 338):
print(f"{i+1:4}: {lines[i]}")
PY
printf '%s\n' '--- candidate implementation files ---'
git ls-files | rg '(^|/)(scale|axis|ticker|transforms?)[^/]*\.py$|matplotlib/.*\.py$' | head -100Repository: reflex-dev/xy
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rg -n "class .*Logit|def .*logit|LogitScale|set_xscale|tick_values" . -g '*.py' | head -200Repository: reflex-dev/xy
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set -eu
printf '%s\n' '--- scale definitions ---'
sed -n '260,325p' python/xy/pyplot/_axes.py
sed -n '6165,6345p' python/xy/pyplot/_axes.py
printf '%s\n' '--- shared-axis tick generation ---'
sed -n '6700,6805p' python/xy/pyplot/_axes.py
printf '%s\n' '--- logit locator ---'
sed -n '390,545p' python/xy/pyplot/_ticker.py
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from pathlib import Path
for path in ("python/xy/pyplot/_axes.py", "python/xy/pyplot/_ticker.py"):
text = Path(path).read_text().splitlines()
print(f"--- {path} ---")
needles = ("def _scale_values", "def _scale_limits", "LogitLocator", "def _get_tick", "def _axis_props")
for i, line in enumerate(text):
if any(needle in line for needle in needles):
lo, hi = max(0, i-8), min(len(text), i+35)
print(f"[{lo+1}:{hi}]")
for j in range(lo, hi):
print(f"{j+1:5}: {text[j]}")
PYRepository: reflex-dev/xy
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#!/bin/bash
set -eu
python3 - <<'PY'
import numpy as np
xs = np.linspace(-100, 100, 50)
valid_xs = np.linspace(0.01, 0.99, 50)
def logit_transform(values):
values = np.asarray(values, dtype=float)
with np.errstate(divide="ignore", invalid="ignore"):
result = np.log10(values / (1.0 - values))
return np.where((values > 0.0) & (values < 1.0), result, np.nan)
for name, values in (("current", xs), ("proposed", valid_xs)):
transformed = logit_transform(values)
print(name, "valid_points=", np.isfinite(transformed).sum(),
"masked_points=", np.isnan(transformed).sum(),
"data_min=", values.min(), "data_max=", values.max())
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Use valid x data for the logit case.
xs places every point outside the logit domain (0, 1). The default nonpositive="mask" setting converts every x value to NaN. Use np.linspace(0.01, 0.99, 50) for logit.
🤖 Prompt for AI Agents
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In `@tests/pyplot/test_axis_tick_gallery_compat.py` around lines 323 - 327, Update
the x-data setup in the shared-axis test so the logit scale uses values within
its valid (0, 1) domain, such as a linspace from 0.01 to 0.99, while preserving
the existing range for other scales. Keep the plotting and set_xscale flow
unchanged.
Source: MCP tools
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1 issue found across 2 files (changes from recent commits).
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<file name="tests/pyplot/test_axis_tick_gallery_compat.py">
<violation number="1" location="tests/pyplot/test_axis_tick_gallery_compat.py:323">
P3: The logit case uses data spanning [-100, 100], far outside the (0,1) domain that a logit (probability) scale is defined on. In `_apply_tickers` the auto-locator runs on the linear view and produces linear ticks, `tick_labels` is built from those ticks, and `tick_values = _scale_values(ticks, spec)` forward-transforms via logit, which masks everything outside (0,1) to NaN (the default `nonpositive="mask"` branch in `_scale_values`). So for logit every published `tick_values` is NaN, and the `len(...) == len(...)` assertion passes purely on count without validating that the labels/positions are meaningful. Use data within (0,1) for the logit parameterization (e.g. sample xs in `np.linspace(0.02, 0.98, ...)`) so the regression it is meant to guard is actually exercised, or drop logit from the parametrization.</violation>
</file>
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| source, so a `sharex` follower reaches the label branch with no locator of | ||
| its own. Labels without positions are rejected when the chart is built. | ||
| """ | ||
| xs = np.linspace(-100, 100, 50) |
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P3: The logit case uses data spanning [-100, 100], far outside the (0,1) domain that a logit (probability) scale is defined on. In _apply_tickers the auto-locator runs on the linear view and produces linear ticks, tick_labels is built from those ticks, and tick_values = _scale_values(ticks, spec) forward-transforms via logit, which masks everything outside (0,1) to NaN (the default nonpositive="mask" branch in _scale_values). So for logit every published tick_values is NaN, and the len(...) == len(...) assertion passes purely on count without validating that the labels/positions are meaningful. Use data within (0,1) for the logit parameterization (e.g. sample xs in np.linspace(0.02, 0.98, ...)) so the regression it is meant to guard is actually exercised, or drop logit from the parametrization.
Prompt for AI agents
Check if this issue is valid — if so, understand the root cause and fix it. At tests/pyplot/test_axis_tick_gallery_compat.py, line 323:
<comment>The logit case uses data spanning [-100, 100], far outside the (0,1) domain that a logit (probability) scale is defined on. In `_apply_tickers` the auto-locator runs on the linear view and produces linear ticks, `tick_labels` is built from those ticks, and `tick_values = _scale_values(ticks, spec)` forward-transforms via logit, which masks everything outside (0,1) to NaN (the default `nonpositive="mask"` branch in `_scale_values`). So for logit every published `tick_values` is NaN, and the `len(...) == len(...)` assertion passes purely on count without validating that the labels/positions are meaningful. Use data within (0,1) for the logit parameterization (e.g. sample xs in `np.linspace(0.02, 0.98, ...)`) so the regression it is meant to guard is actually exercised, or drop logit from the parametrization.</comment>
<file context>
@@ -310,3 +310,24 @@ def test_minorticks_on_leaves_automatic_major_ticks_unpinned() -> None:
+ source, so a `sharex` follower reaches the label branch with no locator of
+ its own. Labels without positions are rejected when the chart is built.
+ """
+ xs = np.linspace(-100, 100, 50)
+ _fig, (leader, follower) = plt.subplots(2, sharex=True)
+ leader.plot(xs, xs)
</file context>
|
Hi thanks for the catches The two logit comments are pointing at the same issue, and I agree the test should use values inside (0, 1). Small nuance: the emitted tick positions are actually finite on the current head because it falls back to a default domain, but that still means the test isn’t exercising a real logit dataset. The nonlinear label/position issue looks properly fixed in 8e7bff6. I don’t think the locator_params(nbins=4) issue is fully resolved, though. minorticks_on() still changes the count from 4 to 6, so the ladders are synchronized by ignoring the requested count rather than using it to calculate the minors. I also found a similar problem with datetime axes: the client generates calendar-based major ticks, while the minor ticks still come from the numeric-millisecond locator, so the two sets don’t line up. Overall, the original disappearing-label bug is fixed, but I think the tick-count and datetime cases should be addressed before merging. I can put the finishes on this pr or you can either way works, appreciate the contribution |
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The core fix works. I checked the minorticks_on() axis in headless Chromium. The labels now regenerate on zoom (x∈[4,5] gives 6 majors; before this PR it gave 1), and the minor ticks still draw. The new regression test fails on main and passes on this head, and tests/pyplot passes.
Three changes are needed (see the inline comments):
- With
minorticks_on(), the code still overwritestick_count. This dropslocator_params(nbins=4)(it becomes 6) and changes the default density from 9 to 6. spec/matplotlib/compat.mdandspec/design/renderer-architecture.mddo not describe the new minor-tick behavior.- The PR has no news fragment.
Optional: the logit case in the shared-axis test uses data in [-100, 100], which is outside the (0, 1) domain. The tick values come out finite, so the test is not vacuous, as a bot comment says it is. But data in (0, 1) would be a more realistic case.
Generated by Claude Code
| if not majors_are_auto or "tick_labels" in props: | ||
| props["tick_values"] = list(map(float, _scale_values(ticks, spec))) | ||
| if len(ticks): | ||
| props["tick_count"] = len(ticks) |
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When the majors are automatic, this line overwrites the tick_count that the user set. The client then reads the overwritten count as the density for its own major ticks. So minorticks_on() still changes the major ticks. The cubic thread about locator_params(nbins=...) is marked as fixed in 8e7bff6, but the problem is still there:
f, a = plt.subplots(); a.plot([0, 10], [0, 10]); a.locator_params(nbins=4)
a.minorticks_on()
a._build_chart(600, 400).figure().build_payload()[0]["x_axis"]["tick_count"]
# without minorticks_on(): 4 with minorticks_on(): 6In the default case the count also changes, from 9 to 6. The PR description says tick_count 9 -> 9, but this head gives 6. I checked this in headless Chromium with the standalone bundle. After a zoom to x∈[4.4, 4.6], the plain axis draws 9 majors and the minorticks_on() axis draws 5.
Requested change: when majors_are_auto is true, keep the tick_count already in props. Also seed AutoLocator with that count, so the minor ladder subdivides the same majors that the client draws. Then add a test that asserts tick_count with minorticks_on() matches the value without it, both for the default case and after locator_params(nbins=4).
Generated by Claude Code
| ticks = ticks[(ticks >= lo - pad) & (ticks <= hi + pad)] | ||
| auto_log = is_log | ||
| props["tick_values"] = list(map(float, _scale_values(ticks, spec))) | ||
| majors_are_auto = ( |
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This changes behavior that the spec describes, and the spec is not updated. CLAUDE.md says spec/ is the source of truth, and that a change is not complete while its spec is stale. Please update:
spec/matplotlib/compat.md(theset_major_locatorrow). It says "minor ticks do not render". Make it say thatminorticks_on()/AutoMinorLocatorkeep the majors automatic, and thatminor_tick_valuesis a fixed list computed for the initial domain, which does not regenerate on zoom. This is the caveat in your PR description.spec/design/renderer-architecture.md(the paragraph aboutminor_tick_values, near line 340). It says pyplot uses the minor tier only for log subdivisions. It also says "An authoredtick_valuesarray is the labelled major tier". Add that an automatic linear axis with minor ticks sends minors and notick_values.
Generated by Claude Code
| assert annotation._entry["kwargs"]["style"]["font_size"] == pytest.approx(8.5) | ||
|
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||
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| def test_minorticks_on_leaves_automatic_major_ticks_unpinned() -> None: |
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The PR has no news fragment. CLAUDE.md says every change under python/ must add one: make news NAME=494.bugfix.md. This is a user-visible fix, so skip-changelog does not apply.
Generated by Claude Code
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1 existing issue remains and 1 new issue found across 3 files
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<file name="tests/pyplot/test_axis_tick_gallery_compat.py">
<violation number="1" location="tests/pyplot/test_axis_tick_gallery_compat.py:333">
P2: This equality is vacuous when both arrays are empty, so the regression can pass without producing nonlinear labels at all. Assert that `tick_labels` and `tick_values` are non-empty before checking their lengths.</violation>
</file>
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| spec, _blob = follower._build_chart(600, 400).figure().build_payload() | ||
| x_axis = spec["x_axis"] | ||
|
|
||
| assert len(x_axis["tick_labels"]) == len(x_axis["tick_values"]) |
There was a problem hiding this comment.
P2: This equality is vacuous when both arrays are empty, so the regression can pass without producing nonlinear labels at all. Assert that tick_labels and tick_values are non-empty before checking their lengths.
Prompt for AI agents
Check if this issue is valid — if so, understand the root cause and fix it. When an issue isn't valid or won't be fixed in this PR, reply in its thread with the reason and then resolve the thread. At tests/pyplot/test_axis_tick_gallery_compat.py, line 333:
<comment>This equality is vacuous when both arrays are empty, so the regression can pass without producing nonlinear labels at all. Assert that `tick_labels` and `tick_values` are non-empty before checking their lengths.</comment>
<file context>
@@ -294,3 +294,40 @@ def test_named_annotation_accepts_relative_fontsize() -> None:
+ spec, _blob = follower._build_chart(600, 400).figure().build_payload()
+ x_axis = spec["x_axis"]
+
+ assert len(x_axis["tick_labels"]) == len(x_axis["tick_values"])
</file context>
| assert len(x_axis["tick_labels"]) == len(x_axis["tick_values"]) | |
| assert x_axis["tick_labels"] | |
| assert x_axis["tick_values"] | |
| assert len(x_axis["tick_labels"]) == len(x_axis["tick_values"]) |
Closes #493.
The problem
minorticks_on()freezes the major tick positions. Asking for minor ticks turns an automatic axis into a fixed one, and because the renderer filters authored positions to the visible window, the tick labels disappear once you zoom past them. Withoutminorticks_on()the labels rescale normally.Visible in the compiled payload, no browser needed:
Before this change:
The cause
_apply_tickersreturns early when nothing is registered:minorticks_on()registers aminor_locator, so that guard stops short-circuiting and execution reachesprops["tick_values"] = ..., which publishes the majors as authored positions.That write is right when the caller sets a major locator or formatter, since those define where the majors go. It is wrong when the only thing registered is a minor locator: the majors were still chosen by
AutoLocator, and pinning them is not correct.The change
Compute
ticksas before. It is still needed to subdivide between the majors, but only publishtick_valuesandtick_countwhen the majors were actually determined by the caller:After:
with
minor_tick_valuesstill populated.Testing
minorticks_on()leavestick_valuesunset while minor values are still emitted. It fails onmainwithassert [0.0, 2.0, 4.0, 6.0, 8.0, 10.0] is None.Caveat: this does not make minor ticks regenerate
The majors are automatic again, but the minors are not.
minor_tick_valuesis the only minor field on the wire, and the client filters that fixed list to the view rather than generating anything:So the minor positions computed for the initial domain are all that ever exist. Zoom in far enough and none of them fall inside the view, leaving regenerating majors with no minors between them.
Fixing that properly means shipping the subdivision rule rather than the positions, something like
minor_subdivisions, and having the client subdivide between the majors it generates. That is a wire field plus client work, which would be a fair bit more work, and I'm not confident enough around the codebase to tackle it.Summary by CodeRabbit
Bug Fixes
Tests