8000 Categorical support for NumPy string arrays. by QuLogic · Pull Request #7241 · matplotlib/matplotlib · GitHub
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Categorical support for NumPy string arrays. #7241

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Merged
merged 3 commits into from
Oct 14, 2016
Merged

Categorical support for NumPy string arrays. #7241

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981e0e4
TST: Add categorical tests for NumPy string arrays.
QuLogic Oct 9, 2016
a29e26d
Use category converter on NumPy str/bytes also.
QuLogic Oct 9, 2016
de03d47
TST: Parametrize new category bytes tests.
QuLogic Oct 13, 2016
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TST: Parametrize new category bytes tests.
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@QuLogic
QuLogic committed Oct 14, 2016
commit de03d4794938653a25e5366cabc282bd77604ce7
72 changes: 24 additions & 48 deletions lib/matplotlib/tests/test_category.py
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Original file line number Diff line number Diff line change
Expand Up @@ -188,62 +188,38 @@ def test_plot_1d_missing(self):

@cleanup
@pytest.mark.usefixtures("data")
def test_plot_bytes(self):
counts = np.array([4, 6, 5, 1])
fig, ax = plt.subplots(ncols=3)

ax[0].bar(self.d, counts)

types = [v.encode('ascii') for v in self.d]
ax[1].bar(types, counts)

types = np.array(types)
ax[2].bar(types, counts)
@pytest.mark.parametrize("bars",
[['a', 'b', 'c'],
[b'a', b'b', b'c'],
np.array([b'a', b'b', b'c'])],
ids=['string list', 'bytes list',
'bytes ndarray'])
def test_plot_bytes(self, bars):
counts = np.array([4, 6, 5])

fig, ax = plt.subplots()
ax.bar(bars, counts)
fig.canvas.draw()

# All three plots should look like the string one.
self.axis_test(ax[1].xaxis,
ax[0].xaxis.get_majorticklocs(),
lt(ax[0].xaxis.get_majorticklabels()),
ax[0].xaxis.unit_data)
self.axis_test(ax[2].xaxis,
ax[0].xaxis.get_majorticklocs(),
lt(ax[0].xaxis.get_majorticklabels()),
ax[0].xaxis.unit_data)
self.axis_test(ax.xaxis, self.dticks, self.dlabels, self.dunit_data)

@cleanup
def test_plot_numlike(self):
counts = np.array([4, 6, 5, 1])
fig, ax = plt.subplots(ncols=4)

types = ['1', '11', '3', '1']
ax[0].bar(types, counts)

types = np.array(types)
ax[1].bar(types, counts)

types = [b'1', b'11', b'3', b'1']
ax[2].bar(types, counts)

types = np.array(types)
ax[3].bar(types, counts)
@pytest.mark.parametrize("bars",
[['1', '11', '3'],
np.array(['1', '11', '3']),
[b'1', b'11', b'3'],
np.array([b'1', b'11', b'3'])],
ids=['string list', 'string ndarray',
'bytes list', 'bytes ndarray'])
def test_plot_numlike(self, bars):
counts = np.array([4, 6, 5])

fig, ax = plt.subplots()
ax.bar(bars, counts)
fig.canvas.draw()

# All four plots should look like the string one.
self.axis_test(ax[1].xaxis,
ax[0].xaxis.get_majorticklocs(),
lt(ax[0].xaxis.get_majorticklabels()),
ax[0].xaxis.unit_data)
self.axis_test(ax[2].xaxis,
ax[0].xaxis.get_majorticklocs(),
lt(ax[0].xaxis.get_majorticklabels()),
ax[0].xaxis.unit_data)
self.axis_test(ax[3].xaxis,
ax[0].xaxis.get_majorticklocs(),
lt(ax[0].xaxis.get_majorticklabels()),
ax[0].xaxis.unit_data)
unitmap = MockUnitData([('1', 0), ('11', 1), ('3', 2)])
self.axis_test(ax.xaxis, [0, 1, 2], ['1', '11', '3'], unitmap)

@cleanup
@pytest.mark.usefixtures("data", "missing_data")
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