"""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(extensions=["png"]) 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")