remove save_reference_img() from conftest.py

pre-commit autoupdate

Author: janosh

.pre-commit-config.yaml

@@ -12,24 +12,24 @@ repos:
       - id: isort
 
   - repo: https://github.com/psf/black
-    rev: 22.6.0
+    rev: 22.8.0
     hooks:
       - id: black-jupyter
 
   - repo: https://github.com/PyCQA/flake8
-    rev: 4.0.1
+    rev: 5.0.4
     hooks:
       - id: flake8
         additional_dependencies: [flake8-bugbear]
 
   - repo: https://github.com/asottile/pyupgrade
-    rev: v2.34.0
+    rev: v2.37.3
     hooks:
       - id: pyupgrade
         args: [--py38-plus]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v0.961
+    rev: v0.971
     hooks:
       - id: mypy
         additional_dependencies: [types-requests]
@@ -58,19 +58,19 @@ repos:
         exclude: tests
 
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.1.0
+    rev: v2.2.1
     hooks:
       - id: codespell
         stages: [commit, commit-msg]
         exclude_types: [csv, svg, html, yaml, jupyter]
 
   - repo: https://github.com/PyCQA/autoflake
-    rev: v1.4
+    rev: v1.5.3
     hooks:
       - id: autoflake
 
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.3.1
+    rev: 1.4.0
     hooks:
       - id: nbqa-pyupgrade
         args: [--py38-plus]

assets/_generate_assets.py

@@ -265,9 +265,9 @@
     ax = plot_structure_2d(struct)
     formula = struct.composition.reduced_formula
     _, spacegroup = struct.get_space_group_info()
-    ax.set_title(
-        f"{formula} (disordered {mp_id} with {spacegroup = })", fontweight="bold"
-    )
+
+    anno_text = f"{formula}\ndisordered {mp_id} with {spacegroup = }"
+    ax.text(0.5, 1, anno_text, url=href, ha="center", transform=ax.transAxes)
 
     ax.figure.set_size_inches(8, 8)
 

pymatviz/correlation.py

@@ -62,8 +62,7 @@ def marchenko_pastur(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     # use eigvalsh for speed since correlation matrix is symmetric
     evals = np.linalg.eigvalsh(matrix)

pymatviz/cumulative.py

@@ -20,8 +20,7 @@ def cumulative_residual(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     res = np.sort(preds - targets)
 
@@ -74,8 +73,7 @@ def cumulative_error(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     errors = np.sort(np.abs(preds - targets))
     n_data = len(errors)

pymatviz/histograms.py

@@ -42,8 +42,7 @@ def residual_hist(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     y_res = y_pred - y_true
 
@@ -74,8 +73,8 @@ def true_pred_hist(
     truth_color: str = "blue",
     **kwargs: Any,
 ) -> plt.Axes:
-    """Plot a histogram of model predictions with bars colored by the mean uncertainty of
-    predictions in that bin. Overlaid by a more transparent histogram of ground truth
+    """Plot a histogram of model predictions with bars colored by the mean uncertainty
+    of predictions in that bin. Overlaid by a more transparent histogram of ground truth
     values.
 
     Args:
@@ -91,8 +90,7 @@ def true_pred_hist(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     color_map = getattr(plt.cm, cmap)
     y_true, y_pred, y_std = np.array([y_true, y_pred, y_std])
@@ -159,8 +157,7 @@ def spacegroup_hist(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     if isinstance(next(iter(data)), Structure):
         # if 1st sequence item is structure, assume all are
@@ -316,8 +313,7 @@ def hist_elemental_prevalence(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     elem_counts = count_elements(formulas, count_mode)
     non_zero = elem_counts[elem_counts > 0].sort_values(ascending=False)

pymatviz/parity.py

@@ -80,8 +80,7 @@ def density_scatter(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     xs, ys, cs = hist_density(xs, ys, sort=sort, bins=density_bins)
 
@@ -130,8 +129,7 @@ def scatter_with_err_bar(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     styles = dict(markersize=6, fmt="o", ecolor="g", capthick=2, elinewidth=2)
     ax.errorbar(xs, ys, yerr=yerr, xerr=xerr, **kwargs, **styles)
@@ -171,8 +169,7 @@ def density_hexbin(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     # the scatter plot
     hexbin = ax.hexbin(xs, yx, gridsize=75, mincnt=1, bins="log", C=weights, **kwargs)
@@ -246,8 +243,7 @@ def residual_vs_actual(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     y_err = y_true - y_pred
 

pymatviz/ptable.py

@@ -188,8 +188,7 @@ def ptable_heatmap(
     # TODO can we pass as a kwarg and still ensure aspect ratio respected?
     fig = plt.figure(figsize=(0.75 * n_columns, 0.7 * n_rows))
 
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     rw = rh = 0.9  # rectangle width/height
 
@@ -273,7 +272,7 @@ def ptable_heatmap(
 
         mappable = plt.cm.ScalarMappable(norm=norm, cmap=cmap)
 
-        def tick_fmt(val: float, pos: int) -> str:
+        def tick_fmt(val: float, _pos: int) -> str:
             # val: value at color axis tick (e.g. 10.0, 20.0, ...)
             # pos: zero-based tick counter (e.g. 0, 1, 2, ...)
             if heat_mode == "percent":

pymatviz/relevance.py

@@ -21,8 +21,7 @@ def roc_curve(
     Returns:
         tuple[float, ax]: The classifier's ROC-AUC and the plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     # get the metrics
     false_pos_rate, true_pos_rate, _ = skm.roc_curve(targets, proba_pos)
@@ -51,8 +50,7 @@ def precision_recall_curve(
     Returns:
         tuple[float, ax]: The classifier's precision score and the matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     # get the metrics
     precision, recall, _ = skm.precision_recall_curve(targets, proba_pos)

pymatviz/structure_viz.py

@@ -177,8 +177,7 @@ class used to draw chemical bonds. Allowed are edgecolor, facecolor, color,
     Returns:
         plt.Axes: matplotlib Axes instance with plotted structure.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     if isinstance(site_labels, (list, tuple)):
         if len(site_labels) != len(struct):

pymatviz/uncertainty.py

@@ -36,8 +36,7 @@ def qq_gaussian(
     Returns:
         ax: The plot's matplotlib Axes.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     if isinstance(y_std, np.ndarray):
         y_std = {"std": y_std}
@@ -206,8 +205,7 @@ def error_decay_with_uncert(
         ax: matplotlib Axes object with plotted model error drop curve based on
             excluding data points by order of large to small model uncertainties.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     xs = range(100 if percentiles else len(y_true), 0, -1)
 

pymatviz/utils.py

@@ -112,8 +112,7 @@ def annotate_bars(
         **kwargs: Additional arguments (rotation, arrowprops, etc.) are passed to
             ax.annotate().
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     if labels is None:
         labels = [int(patch.get_height()) for patch in ax.patches]
@@ -170,8 +169,7 @@ def add_mae_r2_box(
     Returns:
         AnchoredText: Instance containing the metrics.
     """
-    if ax is None:
-        ax = plt.gca()
+    ax = ax or plt.gca()
 
     mask = ~np.isnan(xs) & ~np.isnan(ys)
     xs, ys = xs[mask], ys[mask]

setup.cfg

@@ -9,7 +9,7 @@ author = Janosh Riebesell
 author_email = [email protected]
 license = MIT
 license_files = license
-keywords = materials informatics, materials discovery, data visualization, plotly, matplotlib
+keywords = science, materials informatics, materials discovery, chemistry, data visualization, plotly, matplotlib
 classifiers =
     Programming Language :: Python :: 3
     Programming Language :: Python :: 3 :: Only

tests/conftest.py

@@ -1,16 +1,11 @@
 from __future__ import annotations
 
-import subprocess
-from shutil import which
-
 import matplotlib.pyplot as plt
 import numpy as np
 import plotly.express as px
 import pytest
 from pymatgen.core import Lattice, Structure
 
-from pymatviz import ROOT
-
 
 # random regression data
 np.random.seed(42)
@@ -67,38 +62,3 @@ def plotly_scatter():
     y2 = xs**0.5
     fig = px.scatter(x=xs, y=[y1, y2])
     return fig
-
-
-def save_reference_img(save_to: str) -> None:
-    """Save a matplotlib figure to a specified fixture path.
-
-    Raises:
-        ValueError: save_to is not inside 'tests/fixtures/' directory.
-    """
-    if not save_to.startswith((f"{ROOT}/tests/fixtures/", "tests/fixtures/")):
-        raise ValueError(f"{save_to=} must point at 'tests/fixtures/'")
-
-    pngquant, zopflipng = which("pngquant"), which("zopflipng")
-
-    print(
-        f"created new fixture {save_to=}, image comparison will run for real on "
-        "subsequent test runs unless fixture is deleted"
-    )
-    plt.savefig(save_to)
-    plt.close()
-
-    if not pngquant:
-        return print("Warning: pngquant not installed. Cannot compress new fixture.")
-    if not zopflipng:
-        return print("Warning: zopflipng not installed. Cannot compress new fixture.")
-
-    subprocess.run(
-        f"{pngquant} 32 --skip-if-larger --ext .png --force".split() + [save_to],
-        check=False,
-        capture_output=True,
-    )
-    subprocess.run(
-        [zopflipng, "-y", save_to, save_to],
-        check=True,
-        capture_output=True,
-    )

tests/test_structure_viz.py

@@ -1,7 +1,5 @@
 from __future__ import annotations
 
-import os
-
 import matplotlib.pyplot as plt
 import pandas as pd
 import pytest
@@ -11,8 +9,6 @@
 from pymatviz.structure_viz import plot_structure_2d
 
 
-os.makedirs(fixture_dir := "tests/fixtures/structure_viz", exist_ok=True)
-
 lattice = Lattice.cubic(5)
 disordered_struct = Structure(
     lattice, [{"Fe": 0.75, "C": 0.25}, "O"], [[0, 0, 0], [0.5, 0.5, 0.5]]