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408 lines
13 KiB
408 lines
13 KiB
from datetime import (
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date,
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datetime,
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)
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import subprocess
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import sys
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import numpy as np
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import pytest
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import pandas._config.config as cf
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from pandas import (
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Index,
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Period,
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PeriodIndex,
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Series,
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Timestamp,
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arrays,
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date_range,
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)
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import pandas._testing as tm
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from pandas.plotting import (
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deregister_matplotlib_converters,
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register_matplotlib_converters,
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)
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from pandas.tseries.offsets import (
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Day,
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Micro,
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Milli,
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Second,
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)
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try:
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from pandas.plotting._matplotlib import converter
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except ImportError:
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# try / except, rather than skip, to avoid internal refactoring
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# causing an improper skip
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pass
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pytest.importorskip("matplotlib.pyplot")
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dates = pytest.importorskip("matplotlib.dates")
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@pytest.mark.single_cpu
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def test_registry_mpl_resets():
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# Check that Matplotlib converters are properly reset (see issue #27481)
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code = (
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"import matplotlib.units as units; "
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"import matplotlib.dates as mdates; "
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"n_conv = len(units.registry); "
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"import pandas as pd; "
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"pd.plotting.register_matplotlib_converters(); "
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"pd.plotting.deregister_matplotlib_converters(); "
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"assert len(units.registry) == n_conv"
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)
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call = [sys.executable, "-c", code]
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subprocess.check_output(call)
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def test_timtetonum_accepts_unicode():
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assert converter.time2num("00:01") == converter.time2num("00:01")
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class TestRegistration:
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@pytest.mark.single_cpu
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def test_dont_register_by_default(self):
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# Run in subprocess to ensure a clean state
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code = (
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"import matplotlib.units; "
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"import pandas as pd; "
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"units = dict(matplotlib.units.registry); "
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"assert pd.Timestamp not in units"
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)
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call = [sys.executable, "-c", code]
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assert subprocess.check_call(call) == 0
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def test_registering_no_warning(self):
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plt = pytest.importorskip("matplotlib.pyplot")
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s = Series(range(12), index=date_range("2017", periods=12))
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_, ax = plt.subplots()
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# Set to the "warn" state, in case this isn't the first test run
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register_matplotlib_converters()
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ax.plot(s.index, s.values)
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plt.close()
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def test_pandas_plots_register(self):
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plt = pytest.importorskip("matplotlib.pyplot")
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s = Series(range(12), index=date_range("2017", periods=12))
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# Set to the "warn" state, in case this isn't the first test run
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with tm.assert_produces_warning(None) as w:
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s.plot()
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try:
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assert len(w) == 0
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finally:
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plt.close()
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def test_matplotlib_formatters(self):
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units = pytest.importorskip("matplotlib.units")
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# Can't make any assertion about the start state.
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# We we check that toggling converters off removes it, and toggling it
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# on restores it.
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with cf.option_context("plotting.matplotlib.register_converters", True):
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with cf.option_context("plotting.matplotlib.register_converters", False):
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assert Timestamp not in units.registry
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assert Timestamp in units.registry
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def test_option_no_warning(self):
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pytest.importorskip("matplotlib.pyplot")
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ctx = cf.option_context("plotting.matplotlib.register_converters", False)
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plt = pytest.importorskip("matplotlib.pyplot")
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s = Series(range(12), index=date_range("2017", periods=12))
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_, ax = plt.subplots()
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# Test without registering first, no warning
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with ctx:
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ax.plot(s.index, s.values)
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# Now test with registering
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register_matplotlib_converters()
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with ctx:
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ax.plot(s.index, s.values)
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plt.close()
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def test_registry_resets(self):
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units = pytest.importorskip("matplotlib.units")
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dates = pytest.importorskip("matplotlib.dates")
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# make a copy, to reset to
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original = dict(units.registry)
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try:
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# get to a known state
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units.registry.clear()
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date_converter = dates.DateConverter()
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units.registry[datetime] = date_converter
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units.registry[date] = date_converter
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register_matplotlib_converters()
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assert units.registry[date] is not date_converter
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deregister_matplotlib_converters()
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assert units.registry[date] is date_converter
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finally:
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# restore original stater
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units.registry.clear()
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for k, v in original.items():
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units.registry[k] = v
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class TestDateTimeConverter:
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@pytest.fixture
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def dtc(self):
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return converter.DatetimeConverter()
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def test_convert_accepts_unicode(self, dtc):
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r1 = dtc.convert("2000-01-01 12:22", None, None)
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r2 = dtc.convert("2000-01-01 12:22", None, None)
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assert r1 == r2, "DatetimeConverter.convert should accept unicode"
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def test_conversion(self, dtc):
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rs = dtc.convert(["2012-1-1"], None, None)[0]
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xp = dates.date2num(datetime(2012, 1, 1))
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assert rs == xp
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rs = dtc.convert("2012-1-1", None, None)
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assert rs == xp
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rs = dtc.convert(date(2012, 1, 1), None, None)
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assert rs == xp
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rs = dtc.convert("2012-1-1", None, None)
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assert rs == xp
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rs = dtc.convert(Timestamp("2012-1-1"), None, None)
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assert rs == xp
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# also testing datetime64 dtype (GH8614)
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rs = dtc.convert("2012-01-01", None, None)
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assert rs == xp
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rs = dtc.convert("2012-01-01 00:00:00+0000", None, None)
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assert rs == xp
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rs = dtc.convert(
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np.array(["2012-01-01 00:00:00+0000", "2012-01-02 00:00:00+0000"]),
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None,
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None,
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)
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assert rs[0] == xp
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# we have a tz-aware date (constructed to that when we turn to utc it
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# is the same as our sample)
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ts = Timestamp("2012-01-01").tz_localize("UTC").tz_convert("US/Eastern")
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rs = dtc.convert(ts, None, None)
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assert rs == xp
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rs = dtc.convert(ts.to_pydatetime(), None, None)
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assert rs == xp
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rs = dtc.convert(Index([ts - Day(1), ts]), None, None)
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assert rs[1] == xp
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rs = dtc.convert(Index([ts - Day(1), ts]).to_pydatetime(), None, None)
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assert rs[1] == xp
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def test_conversion_float(self, dtc):
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rtol = 0.5 * 10**-9
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rs = dtc.convert(Timestamp("2012-1-1 01:02:03", tz="UTC"), None, None)
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xp = converter.mdates.date2num(Timestamp("2012-1-1 01:02:03", tz="UTC"))
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tm.assert_almost_equal(rs, xp, rtol=rtol)
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rs = dtc.convert(
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Timestamp("2012-1-1 09:02:03", tz="Asia/Hong_Kong"), None, None
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)
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tm.assert_almost_equal(rs, xp, rtol=rtol)
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rs = dtc.convert(datetime(2012, 1, 1, 1, 2, 3), None, None)
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tm.assert_almost_equal(rs, xp, rtol=rtol)
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@pytest.mark.parametrize(
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"values",
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[
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[date(1677, 1, 1), date(1677, 1, 2)],
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[datetime(1677, 1, 1, 12), datetime(1677, 1, 2, 12)],
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],
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)
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def test_conversion_outofbounds_datetime(self, dtc, values):
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# 2579
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rs = dtc.convert(values, None, None)
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xp = converter.mdates.date2num(values)
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tm.assert_numpy_array_equal(rs, xp)
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rs = dtc.convert(values[0], None, None)
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xp = converter.mdates.date2num(values[0])
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assert rs == xp
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@pytest.mark.parametrize(
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"time,format_expected",
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[
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(0, "00:00"), # time2num(datetime.time.min)
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(86399.999999, "23:59:59.999999"), # time2num(datetime.time.max)
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(90000, "01:00"),
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(3723, "01:02:03"),
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(39723.2, "11:02:03.200"),
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],
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)
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def test_time_formatter(self, time, format_expected):
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# issue 18478
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result = converter.TimeFormatter(None)(time)
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assert result == format_expected
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@pytest.mark.parametrize("freq", ("B", "L", "S"))
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def test_dateindex_conversion(self, freq, dtc):
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rtol = 10**-9
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dateindex = tm.makeDateIndex(k=10, freq=freq)
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rs = dtc.convert(dateindex, None, None)
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xp = converter.mdates.date2num(dateindex._mpl_repr())
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tm.assert_almost_equal(rs, xp, rtol=rtol)
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@pytest.mark.parametrize("offset", [Second(), Milli(), Micro(50)])
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def test_resolution(self, offset, dtc):
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# Matplotlib's time representation using floats cannot distinguish
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# intervals smaller than ~10 microsecond in the common range of years.
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ts1 = Timestamp("2012-1-1")
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ts2 = ts1 + offset
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val1 = dtc.convert(ts1, None, None)
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val2 = dtc.convert(ts2, None, None)
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if not val1 < val2:
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raise AssertionError(f"{val1} is not less than {val2}.")
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def test_convert_nested(self, dtc):
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inner = [Timestamp("2017-01-01"), Timestamp("2017-01-02")]
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data = [inner, inner]
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result = dtc.convert(data, None, None)
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expected = [dtc.convert(x, None, None) for x in data]
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assert (np.array(result) == expected).all()
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class TestPeriodConverter:
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@pytest.fixture
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def pc(self):
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return converter.PeriodConverter()
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@pytest.fixture
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def axis(self):
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class Axis:
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pass
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axis = Axis()
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axis.freq = "D"
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return axis
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def test_convert_accepts_unicode(self, pc, axis):
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r1 = pc.convert("2012-1-1", None, axis)
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r2 = pc.convert("2012-1-1", None, axis)
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assert r1 == r2
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def test_conversion(self, pc, axis):
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rs = pc.convert(["2012-1-1"], None, axis)[0]
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xp = Period("2012-1-1").ordinal
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assert rs == xp
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rs = pc.convert("2012-1-1", None, axis)
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assert rs == xp
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rs = pc.convert([date(2012, 1, 1)], None, axis)[0]
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assert rs == xp
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rs = pc.convert(date(2012, 1, 1), None, axis)
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assert rs == xp
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rs = pc.convert([Timestamp("2012-1-1")], None, axis)[0]
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assert rs == xp
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rs = pc.convert(Timestamp("2012-1-1"), None, axis)
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assert rs == xp
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rs = pc.convert("2012-01-01", None, axis)
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assert rs == xp
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rs = pc.convert("2012-01-01 00:00:00+0000", None, axis)
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assert rs == xp
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rs = pc.convert(
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np.array(
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["2012-01-01 00:00:00", "2012-01-02 00:00:00"],
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dtype="datetime64[ns]",
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),
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None,
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axis,
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)
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assert rs[0] == xp
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def test_integer_passthrough(self, pc, axis):
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# GH9012
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rs = pc.convert([0, 1], None, axis)
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xp = [0, 1]
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assert rs == xp
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def test_convert_nested(self, pc, axis):
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data = ["2012-1-1", "2012-1-2"]
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r1 = pc.convert([data, data], None, axis)
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r2 = [pc.convert(data, None, axis) for _ in range(2)]
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assert r1 == r2
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class TestTimeDeltaConverter:
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"""Test timedelta converter"""
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@pytest.mark.parametrize(
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"x, decimal, format_expected",
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[
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(0.0, 0, "00:00:00"),
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(3972320000000, 1, "01:06:12.3"),
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(713233432000000, 2, "8 days 06:07:13.43"),
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(32423432000000, 4, "09:00:23.4320"),
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],
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)
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def test_format_timedelta_ticks(self, x, decimal, format_expected):
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tdc = converter.TimeSeries_TimedeltaFormatter
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result = tdc.format_timedelta_ticks(x, pos=None, n_decimals=decimal)
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assert result == format_expected
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@pytest.mark.parametrize("view_interval", [(1, 2), (2, 1)])
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def test_call_w_different_view_intervals(self, view_interval, monkeypatch):
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# previously broke on reversed xlmits; see GH37454
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class mock_axis:
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def get_view_interval(self):
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return view_interval
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tdc = converter.TimeSeries_TimedeltaFormatter()
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monkeypatch.setattr(tdc, "axis", mock_axis())
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tdc(0.0, 0)
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@pytest.mark.parametrize("year_span", [11.25, 30, 80, 150, 400, 800, 1500, 2500, 3500])
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# The range is limited to 11.25 at the bottom by if statements in
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# the _quarterly_finder() function
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def test_quarterly_finder(year_span):
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vmin = -1000
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vmax = vmin + year_span * 4
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span = vmax - vmin + 1
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if span < 45:
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pytest.skip("the quarterly finder is only invoked if the span is >= 45")
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nyears = span / 4
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(min_anndef, maj_anndef) = converter._get_default_annual_spacing(nyears)
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result = converter._quarterly_finder(vmin, vmax, "Q")
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quarters = PeriodIndex(
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arrays.PeriodArray(np.array([x[0] for x in result]), dtype="period[Q]")
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)
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majors = np.array([x[1] for x in result])
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minors = np.array([x[2] for x in result])
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major_quarters = quarters[majors]
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minor_quarters = quarters[minors]
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check_major_years = major_quarters.year % maj_anndef == 0
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check_minor_years = minor_quarters.year % min_anndef == 0
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check_major_quarters = major_quarters.quarter == 1
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check_minor_quarters = minor_quarters.quarter == 1
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assert np.all(check_major_years)
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assert np.all(check_minor_years)
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assert np.all(check_major_quarters)
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assert np.all(check_minor_quarters)
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