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"""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")

	"""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")