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joferkingtonjoferkington
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Strict PEP8 compliance for printed arrays
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‎lib/matplotlib/tests/test_colors.py

Lines changed: 71 additions & 70 deletions
Original file line numberDiff line numberDiff line change
@@ -254,6 +254,7 @@ def test_light_source_topo_surface():
254254
ax.imshow(rgb)
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ax.set(xticks=[], yticks=[])
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257+
257258
def test_light_source_shading_default():
258259
"""Array comparison test for the default "hsv" blend mode. Ensure the
259260
default result doesn't change without warning."""
@@ -264,41 +265,41 @@ def test_light_source_shading_default():
264265
ls = mcolors.LightSource(315, 45)
265266
rgb = ls.shade(z, cmap)
266267

267-
r = np.array([[[ 0.87, 0.85, 0.9 , 0.9 , 0.82, 0.62, 0.34, 0. ],
268-
[ 0.85, 0.94, 0.99, 1. , 1. , 0.96, 0.62, 0.17],
269-
[ 0.9 , 0.99, 1. , 1. , 1. , 1. , 0.71, 0.33],
270-
[ 0.9 , 1. , 1. , 1. , 1. , 0.98, 0.51, 0.29],
271-
[ 0.82, 1. , 1. , 1. , 1. , 0.64, 0.25, 0.13],
272-
[ 0.62, 0.96, 1. , 0.98, 0.64, 0.22, 0.06, 0.03],
273-
[ 0.34, 0.62, 0.71, 0.51, 0.25, 0.06, 0. , 0.01],
274-
[ 0. , 0.17, 0.33, 0.29, 0.13, 0.03, 0.01, 0. ]],
275-
276-
[[ 0.87, 0.79, 0.83, 0.8 , 0.66, 0.44, 0.23, 0. ],
277-
[ 0.79, 0.88, 0.93, 0.92, 0.83, 0.66, 0.38, 0.1 ],
278-
[ 0.83, 0.93, 0.99, 1. , 0.92, 0.75, 0.4 , 0.18],
279-
[ 0.8 , 0.92, 1. , 0.99, 0.93, 0.75, 0.28, 0.14],
280-
[ 0.66, 0.83, 0.92, 0.93, 0.87, 0.44, 0.12, 0.06],
281-
[ 0.44, 0.66, 0.75, 0.75, 0.44, 0.12, 0.03, 0.01],
282-
[ 0.23, 0.38, 0.4 , 0.28, 0.12, 0.03, 0. , 0. ],
283-
[ 0. , 0.1 , 0.18, 0.14, 0.06, 0.01, 0. , 0. ]],
284-
285-
[[ 0.87, 0.75, 0.78, 0.73, 0.55, 0.33, 0.16, 0. ],
286-
[ 0.75, 0.85, 0.9 , 0.86, 0.71, 0.48, 0.23, 0.05],
287-
[ 0.78, 0.9 , 0.98, 1. , 0.82, 0.51, 0.21, 0.08],
288-
[ 0.73, 0.86, 1. , 0.97, 0.84, 0.47, 0.11, 0.05],
289-
[ 0.55, 0.71, 0.82, 0.84, 0.71, 0.2 , 0.03, 0.01],
290-
[ 0.33, 0.48, 0.51, 0.47, 0.2 , 0.02, 0. , 0. ],
291-
[ 0.16, 0.23, 0.21, 0.11, 0.03, 0. , 0. , 0. ],
292-
[ 0. , 0.05, 0.08, 0.05, 0.01, 0. , 0. , 0. ]],
293-
294-
[[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
295-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
296-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
297-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
298-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
299-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
300-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
301-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ]]])
268+
r = np.array([[[0.87, 0.85, 0.90, 0.90, 0.82, 0.62, 0.34, 0.00],
269+
[0.85, 0.94, 0.99, 1.00, 1.00, 0.96, 0.62, 0.17],
270+
[0.90, 0.99, 1.00, 1.00, 1.00, 1.00, 0.71, 0.33],
271+
[0.90, 1.00, 1.00, 1.00, 1.00, 0.98, 0.51, 0.29],
272+
[0.82, 1.00, 1.00, 1.00, 1.00, 0.64, 0.25, 0.13],
273+
[0.62, 0.96, 1.00, 0.98, 0.64, 0.22, 0.06, 0.03],
274+
[0.34, 0.62, 0.71, 0.51, 0.25, 0.06, 0.00, 0.01],
275+
[0.00, 0.17, 0.33, 0.29, 0.13, 0.03, 0.01, 0.00]],
276+
277+
[[0.87, 0.79, 0.83, 0.80, 0.66, 0.44, 0.23, 0.00],
278+
[0.79, 0.88, 0.93, 0.92, 0.83, 0.66, 0.38, 0.10],
279+
[0.83, 0.93, 0.99, 1.00, 0.92, 0.75, 0.40, 0.18],
280+
[0.80, 0.92, 1.00, 0.99, 0.93, 0.75, 0.28, 0.14],
281+
[0.66, 0.83, 0.92, 0.93, 0.87, 0.44, 0.12, 0.06],
282+
[0.44, 0.66, 0.75, 0.75, 0.44, 0.12, 0.03, 0.01],
283+
[0.23, 0.38, 0.40, 0.28, 0.12, 0.03, 0.00, 0.00],
284+
[0.00, 0.10, 0.18, 0.14, 0.06, 0.01, 0.00, 0.00]],
285+
286+
[[0.87, 0.75, 0.78, 0.73, 0.55, 0.33, 0.16, 0.00],
287+
[0.75, 0.85, 0.90, 0.86, 0.71, 0.48, 0.23, 0.05],
288+
[0.78, 0.90, 0.98, 1.00, 0.82, 0.51, 0.21, 0.08],
289+
[0.73, 0.86, 1.00, 0.97, 0.84, 0.47, 0.11, 0.05],
290+
[0.55, 0.71, 0.82, 0.84, 0.71, 0.20, 0.03, 0.01],
291+
[0.33, 0.48, 0.51, 0.47, 0.20, 0.02, 0.00, 0.00],
292+
[0.16, 0.23, 0.21, 0.11, 0.03, 0.00, 0.00, 0.00],
293+
[0.00, 0.05, 0.08, 0.05, 0.01, 0.00, 0.00, 0.00]],
294+
295+
[[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
296+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
297+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
298+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
299+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
300+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
301+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
302+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00]]])
302303
# Result stored transposed and rounded for for more compact display...
303304
assert_array_almost_equal(rgb, r.T, decimal=2)
304305

@@ -315,41 +316,41 @@ def test_light_source_masked_shading():
315316
ls = mcolors.LightSource(315, 45)
316317
rgb = ls.shade(z, cmap)
317318

318-
r = np.array([[[ 1. , 0.95, 0.96, 0.94, 0.86, 0.67, 0.4 , 0.03],
319-
[ 0.95, 0.99, 1. , 1. , 1. , 0.98, 0.67, 0.19],
320-
[ 0.96, 1. , 1. , 1. , 1. , 1. , 0.78, 0.36],
321-
[ 0.94, 1. , 1. , 0. , 0. , 1. , 0.55, 0.32],
322-
[ 0.86, 1. , 1. , 0. , 0. , 1. , 0.27, 0.14],
323-
[ 0.67, 0.98, 1. , 1. , 1. , 1. , 0.07, 0.03],
324-
[ 0.4 , 0.67, 0.78, 0.55, 0.27, 0.07, 0. , 0.01],
325-
[ 0.03, 0.19, 0.36, 0.32, 0.14, 0.03, 0.01, 0. ]],
326-
327-
[[ 1. , 0.93, 0.93, 0.88, 0.72, 0.5 , 0.28, 0.03],
328-
[ 0.93, 0.97, 0.99, 0.96, 0.87, 0.7 , 0.42, 0.11],
329-
[ 0.93, 0.99, 0.74, 0.78, 0.78, 0.74, 0.45, 0.2 ],
330-
[ 0.88, 0.96, 0.78, 0. , 0. , 0.78, 0.32, 0.16],
331-
[ 0.72, 0.87, 0.78, 0. , 0. , 0.78, 0.14, 0.06],
332-
[ 0.5 , 0.7 , 0.74, 0.78, 0.78, 0.74, 0.03, 0.01],
333-
[ 0.28, 0.42, 0.45, 0.32, 0.14, 0.03, 0. , 0. ],
334-
[ 0.03, 0.11, 0.2 , 0.16, 0.06, 0.01, 0. , 0. ]],
335-
336-
[[ 1. , 0.91, 0.91, 0.84, 0.64, 0.39, 0.21, 0.03],
337-
[ 0.91, 0.96, 0.98, 0.93, 0.77, 0.53, 0.27, 0.06],
338-
[ 0.91, 0.98, 0.47, 0.5 , 0.5 , 0.47, 0.25, 0.1 ],
339-
[ 0.84, 0.93, 0.5 , 0. , 0. , 0.5 , 0.13, 0.06],
340-
[ 0.64, 0.77, 0.5 , 0. , 0. , 0.5 , 0.03, 0.01],
341-
[ 0.39, 0.53, 0.47, 0.5 , 0.5 , 0.47, 0. , 0. ],
342-
[ 0.21, 0.27, 0.25, 0.13, 0.03, 0. , 0. , 0. ],
343-
[ 0.03, 0.06, 0.1 , 0.06, 0.01, 0. , 0. , 0. ]],
344-
345-
[[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
346-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
347-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
348-
[ 1. , 1. , 1. , 0. , 0. , 1. , 1. , 1. ],
349-
[ 1. , 1. , 1. , 0. , 0. , 1. , 1. , 1. ],
350-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
351-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],
352-
[ 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ]]])
319+
r = np.array([[[1.00, 0.95, 0.96, 0.94, 0.86, 0.67, 0.40, 0.03],
320+
[0.95, 0.99, 1.00, 1.00, 1.00, 0.98, 0.67, 0.19],
321+
[0.96, 1.00, 1.00, 1.00, 1.00, 1.00, 0.78, 0.36],
322+
[0.94, 1.00, 1.00, 0.00, 0.00, 1.00, 0.55, 0.32],
323+
[0.86, 1.00, 1.00, 0.00, 0.00, 1.00, 0.27, 0.14],
324+
[0.67, 0.98, 1.00, 1.00, 1.00, 1.00, 0.07, 0.03],
325+
[0.40, 0.67, 0.78, 0.55, 0.27, 0.07, 0.00, 0.01],
326+
[0.03, 0.19, 0.36, 0.32, 0.14, 0.03, 0.01, 0.00]],
327+
328+
[[1.00, 0.93, 0.93, 0.88, 0.72, 0.50, 0.28, 0.03],
329+
[0.93, 0.97, 0.99, 0.96, 0.87, 0.70, 0.42, 0.11],
330+
[0.93, 0.99, 0.74, 0.78, 0.78, 0.74, 0.45, 0.20],
331+
[0.88, 0.96, 0.78, 0.00, 0.00, 0.78, 0.32, 0.16],
332+
[0.72, 0.87, 0.78, 0.00, 0.00, 0.78, 0.14, 0.06],
333+
[0.50, 0.70, 0.74, 0.78, 0.78, 0.74, 0.03, 0.01],
334+
[0.28, 0.42, 0.45, 0.32, 0.14, 0.03, 0.00, 0.00],
335+
[0.03, 0.11, 0.20, 0.16, 0.06, 0.01, 0.00, 0.00]],
336+
337+
[[1.00, 0.91, 0.91, 0.84, 0.64, 0.39, 0.21, 0.03],
338+
[0.91, 0.96, 0.98, 0.93, 0.77, 0.53, 0.27, 0.06],
339+
[0.91, 0.98, 0.47, 0.50, 0.50, 0.47, 0.25, 0.10],
340+
[0.84, 0.93, 0.50, 0.00, 0.00, 0.50, 0.13, 0.06],
341+
[0.64, 0.77, 0.50, 0.00, 0.00, 0.50, 0.03, 0.01],
342+
[0.39, 0.53, 0.47, 0.50, 0.50, 0.47, 0.00, 0.00],
343+
[0.21, 0.27, 0.25, 0.13, 0.03, 0.00, 0.00, 0.00],
344+
[0.03, 0.06, 0.10, 0.06, 0.01, 0.00, 0.00, 0.00]],
345+
346+
[[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
347+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
348+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
349+
[1.00, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 1.00],
350+
[1.00, 1.00, 1.00, 0.00, 0.00, 1.00, 1.00, 1.00],
351+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
352+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00],
353+
[1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00]]])
353354
# Result stored transposed and rounded for for more compact display...
354355
assert_array_almost_equal(rgb, r.T, decimal=2)
355356

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