-
-
Notifications
You must be signed in to change notification settings - Fork 8.3k
Expand file tree
/
Copy pathtest_category.py
More file actions
331 lines (262 loc) · 11.7 KB
/
test_category.py
File metadata and controls
331 lines (262 loc) · 11.7 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
"""Catch all for categorical functions"""
import warnings
import pytest
import numpy as np
import matplotlib as mpl
from matplotlib.axes import Axes
import matplotlib.pyplot as plt
import matplotlib.category as cat
from matplotlib.testing.decorators import check_figures_equal
class TestUnitData:
test_cases = [('single', (["hello world"], [0])),
('unicode', (["Здравствуйте мир"], [0])),
('mixed', (['A', "np.nan", 'B', "3.14", "мир"],
[0, 1, 2, 3, 4]))]
ids, data = zip(*test_cases)
@pytest.mark.parametrize("data, locs", data, ids=ids)
def test_unit(self, data, locs):
unit = cat.UnitData(data)
assert list(unit._mapping.keys()) == data
assert list(unit._mapping.values()) == locs
def test_update(self):
data = ['a', 'd']
locs = [0, 1]
data_update = ['b', 'd', 'e']
unique_data = ['a', 'd', 'b', 'e']
updated_locs = [0, 1, 2, 3]
unit = cat.UnitData(data)
assert list(unit._mapping.keys()) == data
assert list(unit._mapping.values()) == locs
unit.update(data_update)
assert list(unit._mapping.keys()) == unique_data
assert list(unit._mapping.values()) == updated_locs
failing_test_cases = [("number", 3.14), ("nan", np.nan),
("list", [3.14, 12]), ("mixed type", ["A", 2])]
fids, fdata = zip(*test_cases)
@pytest.mark.parametrize("fdata", fdata, ids=fids)
def test_non_string_fails(self, fdata):
with pytest.raises(TypeError):
cat.UnitData(fdata)
@pytest.mark.parametrize("fdata", fdata, ids=fids)
def test_non_string_update_fails(self, fdata):
unitdata = cat.UnitData()
with pytest.raises(TypeError):
unitdata.update(fdata)
class FakeAxis:
def __init__(self, units):
self.units = units
class TestStrCategoryConverter:
"""
Based on the pandas conversion and factorization tests:
ref: /pandas/tseries/tests/test_converter.py
/pandas/tests/test_algos.py:TestFactorize
"""
test_cases = [("unicode", ["Здравствуйте мир"]),
("ascii", ["hello world"]),
("single", ['a', 'b', 'c']),
("integer string", ["1", "2"]),
("single + values>10", ["A", "B", "C", "D", "E", "F", "G",
"H", "I", "J", "K", "L", "M", "N",
"O", "P", "Q", "R", "S", "T", "U",
"V", "W", "X", "Y", "Z"])]
ids, values = zip(*test_cases)
failing_test_cases = [("mixed", [3.14, 'A', np.inf]),
("string integer", ['42', 42])]
fids, fvalues = zip(*failing_test_cases)
@pytest.fixture(autouse=True)
def mock_axis(self, request):
self.cc = cat.StrCategoryConverter()
# self.unit should be probably be replaced with real mock unit
self.unit = cat.UnitData()
self.ax = FakeAxis(self.unit)
@pytest.mark.parametrize("vals", values, ids=ids)
def test_convert(self, vals):
np.testing.assert_allclose(self.cc.convert(vals, self.ax.units,
self.ax),
range(len(vals)))
@pytest.mark.parametrize("value", ["hi", "мир"], ids=["ascii", "unicode"])
def test_convert_one_string(self, value):
assert self.cc.convert(value, self.unit, self.ax) == 0
@pytest.mark.parametrize("fvals", fvalues, ids=fids)
def test_convert_fail(self, fvals):
with pytest.raises(TypeError):
self.cc.convert(fvals, self.unit, self.ax)
def test_axisinfo(self):
axis = self.cc.axisinfo(self.unit, self.ax)
assert isinstance(axis.majloc, cat.StrCategoryLocator)
assert isinstance(axis.majfmt, cat.StrCategoryFormatter)
def test_default_units(self):
assert isinstance(self.cc.default_units(["a"], self.ax), cat.UnitData)
PLOT_LIST = [Axes.scatter, Axes.plot, Axes.bar]
PLOT_IDS = ["scatter", "plot", "bar"]
class TestStrCategoryLocator:
def test_StrCategoryLocator(self):
locs = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
unit = cat.UnitData([str(j) for j in locs])
ticks = cat.StrCategoryLocator(unit._mapping)
np.testing.assert_array_equal(ticks.tick_values(None, None), locs)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_StrCategoryLocatorPlot(self, plotter):
ax = plt.figure().subplots()
plotter(ax, [1, 2, 3], ["a", "b", "c"])
np.testing.assert_array_equal(ax.yaxis.major.locator(), range(3))
class TestStrCategoryFormatter:
test_cases = [("ascii", ["hello", "world", "hi"]),
("unicode", ["Здравствуйте", "привет"])]
ids, cases = zip(*test_cases)
@pytest.mark.parametrize("ydata", cases, ids=ids)
def test_StrCategoryFormatter(self, ydata):
unit = cat.UnitData(ydata)
labels = cat.StrCategoryFormatter(unit._mapping)
for i, d in enumerate(ydata):
assert labels(i, i) == d
assert labels(i, None) == d
@pytest.mark.parametrize("ydata", cases, ids=ids)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_StrCategoryFormatterPlot(self, ydata, plotter):
ax = plt.figure().subplots()
plotter(ax, range(len(ydata)), ydata)
for i, d in enumerate(ydata):
assert ax.yaxis.major.formatter(i) == d
assert ax.yaxis.major.formatter(i+1) == ""
def axis_test(axis, labels):
ticks = list(range(len(labels)))
np.testing.assert_array_equal(axis.get_majorticklocs(), ticks)
graph_labels = [axis.major.formatter(i, i) for i in ticks]
# _text also decodes bytes as utf-8.
assert graph_labels == [cat.StrCategoryFormatter._text(l) for l in labels]
assert list(axis.units._mapping.keys()) == [l for l in labels]
assert list(axis.units._mapping.values()) == ticks
class TestPlotBytes:
bytes_cases = [('string list', ['a', 'b', 'c']),
('bytes list', [b'a', b'b', b'c']),
('bytes ndarray', np.array([b'a', b'b', b'c']))]
bytes_ids, bytes_data = zip(*bytes_cases)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
@pytest.mark.parametrize("bdata", bytes_data, ids=bytes_ids)
def test_plot_bytes(self, plotter, bdata):
ax = plt.figure().subplots()
counts = np.array([4, 6, 5])
plotter(ax, bdata, counts)
axis_test(ax.xaxis, bdata)
class TestPlotNumlike:
numlike_cases = [('string list', ['1', '11', '3']),
('string ndarray', np.array(['1', '11', '3'])),
('bytes list', [b'1', b'11', b'3']),
('bytes ndarray', np.array([b'1', b'11', b'3']))]
numlike_ids, numlike_data = zip(*numlike_cases)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
@pytest.mark.parametrize("ndata", numlike_data, ids=numlike_ids)
def test_plot_numlike(self, plotter, ndata):
ax = plt.figure().subplots()
counts = np.array([4, 6, 5])
plotter(ax, ndata, counts)
axis_test(ax.xaxis, ndata)
class TestPlotTypes:
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_plot_unicode(self, plotter):
ax = plt.figure().subplots()
words = ['Здравствуйте', 'привет']
plotter(ax, words, [0, 1])
axis_test(ax.xaxis, words)
@pytest.fixture
def test_data(self):
self.x = ["hello", "happy", "world"]
self.xy = [2, 6, 3]
self.y = ["Python", "is", "fun"]
self.yx = [3, 4, 5]
@pytest.mark.usefixtures("test_data")
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_plot_xaxis(self, test_data, plotter):
ax = plt.figure().subplots()
plotter(ax, self.x, self.xy)
axis_test(ax.xaxis, self.x)
@pytest.mark.usefixtures("test_data")
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_plot_yaxis(self, test_data, plotter):
ax = plt.figure().subplots()
plotter(ax, self.yx, self.y)
axis_test(ax.yaxis, self.y)
@pytest.mark.usefixtures("test_data")
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_plot_xyaxis(self, test_data, plotter):
ax = plt.figure().subplots()
plotter(ax, self.x, self.y)
axis_test(ax.xaxis, self.x)
axis_test(ax.yaxis, self.y)
@pytest.mark.parametrize("plotter", PLOT_LIST, ids=PLOT_IDS)
def test_update_plot(self, plotter):
ax = plt.figure().subplots()
plotter(ax, ['a', 'b'], ['e', 'g'])
plotter(ax, ['a', 'b', 'd'], ['f', 'a', 'b'])
plotter(ax, ['b', 'c', 'd'], ['g', 'e', 'd'])
axis_test(ax.xaxis, ['a', 'b', 'd', 'c'])
axis_test(ax.yaxis, ['e', 'g', 'f', 'a', 'b', 'd'])
def test_update_plot_heterogenous_plotter(self):
ax = plt.figure().subplots()
ax.scatter(['a', 'b'], ['e', 'g'])
ax.plot(['a', 'b', 'd'], ['f', 'a', 'b'])
ax.bar(['b', 'c', 'd'], ['g', 'e', 'd'])
axis_test(ax.xaxis, ['a', 'b', 'd', 'c'])
axis_test(ax.yaxis, ['e', 'g', 'f', 'a', 'b', 'd'])
failing_test_cases = [("mixed", ['A', 3.14]),
("number integer", ['1', 1]),
("string integer", ['42', 42]),
("missing", ['12', np.nan])]
fids, fvalues = zip(*failing_test_cases)
plotters = [Axes.scatter, Axes.bar,
pytest.param(Axes.plot, marks=pytest.mark.xfail)]
@pytest.mark.parametrize("plotter", plotters)
@pytest.mark.parametrize("xdata", fvalues, ids=fids)
def test_mixed_type_exception(self, plotter, xdata):
ax = plt.figure().subplots()
with pytest.raises(TypeError):
plotter(ax, xdata, [1, 2])
@pytest.mark.parametrize("plotter", plotters)
@pytest.mark.parametrize("xdata", fvalues, ids=fids)
def test_mixed_type_update_exception(self, plotter, xdata):
ax = plt.figure().subplots()
with pytest.raises(TypeError):
plotter(ax, [0, 3], [1, 3])
plotter(ax, xdata, [1, 2])
@mpl.style.context('default')
@check_figures_equal()
def test_overriding_units_in_plot(fig_test, fig_ref):
from datetime import datetime
t0 = datetime(2018, 3, 1)
t1 = datetime(2018, 3, 2)
t2 = datetime(2018, 3, 3)
t3 = datetime(2018, 3, 4)
ax_test = fig_test.subplots()
ax_ref = fig_ref.subplots()
for ax, kwargs in zip([ax_test, ax_ref],
({}, dict(xunits=None, yunits=None))):
# First call works
ax.plot([t0, t1], ["V1", "V2"], **kwargs)
x_units = ax.xaxis.units
y_units = ax.yaxis.units
# this should not raise
ax.plot([t2, t3], ["V1", "V2"], **kwargs)
# assert that we have not re-set the units attribute at all
assert x_units is ax.xaxis.units
assert y_units is ax.yaxis.units
def test_no_deprecation_on_empty_data():
"""
Smoke test to check that no deprecation warning is emitted. See #22640.
"""
f, ax = plt.subplots()
ax.xaxis.update_units(["a", "b"])
ax.plot([], [])
def test_hist():
fig, ax = plt.subplots()
n, bins, patches = ax.hist(['a', 'b', 'a', 'c', 'ff'])
assert n.shape == (10,)
np.testing.assert_allclose(n, [2., 0., 0., 1., 0., 0., 1., 0., 0., 1.])
def test_set_lim():
# Numpy 1.25 deprecated casting [2.] to float, catch_warnings added to error
# with numpy 1.25 and prior to the change from gh-26597
# can be removed once the minimum numpy version has expired the warning
f, ax = plt.subplots()
ax.plot(["a", "b", "c", "d"], [1, 2, 3, 4])
with warnings.catch_warnings():
ax.set_xlim("b", "c")