|
1 |
| -import os |
2 |
| -import shutil |
3 |
| -from copy import deepcopy |
4 |
| -from pathlib import Path |
5 | 1 |
|
6 |
| -import matplotlib |
7 | 2 | import napari
|
8 | 3 | import numpy as np
|
9 | 4 | import pytest
|
10 |
| -from matplotlib.colors import to_rgba |
11 | 5 |
|
12 |
| -from napari_matplotlib import HistogramWidget, ScatterWidget |
| 6 | +from napari_matplotlib import ScatterWidget |
13 | 7 | from napari_matplotlib.base import NapariMPLWidget
|
14 | 8 |
|
15 | 9 |
|
@@ -127,66 +121,3 @@ def test_no_theme_side_effects(make_napari_viewer):
|
127 | 121 | unrelated_figure.tight_layout()
|
128 | 122 |
|
129 | 123 | return unrelated_figure
|
130 |
| - |
131 |
| - |
132 |
| -@pytest.mark.mpl_image_compare |
133 |
| -def test_custom_theme(make_napari_viewer, theme_path, brain_data): |
134 |
| - viewer = make_napari_viewer() |
135 |
| - viewer.theme = "dark" |
136 |
| - |
137 |
| - widget = ScatterWidget(viewer) |
138 |
| - widget.mpl_style_sheet_path = theme_path |
139 |
| - |
140 |
| - viewer.add_image(brain_data[0], **brain_data[1], name="brain") |
141 |
| - viewer.add_image( |
142 |
| - brain_data[0] * -1, **brain_data[1], name="brain_reversed" |
143 |
| - ) |
144 |
| - |
145 |
| - viewer.layers.selection.clear() |
146 |
| - viewer.layers.selection.add(viewer.layers[0]) |
147 |
| - viewer.layers.selection.add(viewer.layers[1]) |
148 |
| - |
149 |
| - return deepcopy(widget.figure) |
150 |
| - |
151 |
| - |
152 |
| -def find_mpl_stylesheet(name: str) -> Path: |
153 |
| - """Find the built-in matplotlib stylesheet.""" |
154 |
| - return Path(matplotlib.__path__[0]) / f"mpl-data/stylelib/{name}.mplstyle" |
155 |
| - |
156 |
| - |
157 |
| -def test_custom_stylesheet(make_napari_viewer, image_data): |
158 |
| - """ |
159 |
| - Test that a stylesheet in the current directory is given precidence. |
160 |
| -
|
161 |
| - Do this by copying over a stylesheet from matplotlib's built in styles, |
162 |
| - naming it correctly, and checking the colours are as expected. |
163 |
| - """ |
164 |
| - # Copy Solarize_Light2 as if it was a user-overriden stylesheet. |
165 |
| - style_sheet_path = ( |
166 |
| - Path(matplotlib.get_configdir()) / "napari-matplotlib.mplstyle" |
167 |
| - ) |
168 |
| - if style_sheet_path.exists(): |
169 |
| - pytest.skip("Won't ovewrite existing custom style sheet.") |
170 |
| - shutil.copy( |
171 |
| - find_mpl_stylesheet("Solarize_Light2"), |
172 |
| - style_sheet_path, |
173 |
| - ) |
174 |
| - |
175 |
| - try: |
176 |
| - viewer = make_napari_viewer() |
177 |
| - viewer.add_image(image_data[0], **image_data[1]) |
178 |
| - widget = HistogramWidget(viewer) |
179 |
| - assert widget.mpl_style_sheet_path == style_sheet_path |
180 |
| - ax = widget.figure.gca() |
181 |
| - |
182 |
| - # The axes should have a light brownish grey background: |
183 |
| - assert ax.get_facecolor() == to_rgba("#eee8d5") |
184 |
| - assert ax.patch.get_facecolor() == to_rgba("#eee8d5") |
185 |
| - |
186 |
| - # The figure background and axis gridlines are light yellow: |
187 |
| - assert widget.figure.patch.get_facecolor() == to_rgba("#fdf6e3") |
188 |
| - for gridline in ax.get_xgridlines() + ax.get_ygridlines(): |
189 |
| - assert gridline.get_visible() is True |
190 |
| - assert gridline.get_color() == "#b0b0b0" |
191 |
| - finally: |
192 |
| - os.remove(style_sheet_path) |
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