test_dates.py

import datetime
try:
    from contextlib import nullcontext
except ImportError:
    from contextlib import ExitStack as nullcontext  # Py 3.6.

import dateutil.tz
import dateutil.rrule
import numpy as np
import pytest

from matplotlib import rc_context
from matplotlib.cbook import MatplotlibDeprecationWarning
import matplotlib.dates as mdates
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
import matplotlib.ticker as mticker


def test_date_numpyx():
    # test that numpy dates work properly...
    base = datetime.datetime(2017, 1, 1)
    time = [base + datetime.timedelta(days=x) for x in range(0, 3)]
    timenp = np.array(time, dtype='datetime64[ns]')
    data = np.array([0., 2., 1.])
    fig = plt.figure(figsize=(10, 2))
    ax = fig.add_subplot(1, 1, 1)
    h, = ax.plot(time, data)
    hnp, = ax.plot(timenp, data)
    np.testing.assert_equal(h.get_xdata(orig=False), hnp.get_xdata(orig=False))
    fig = plt.figure(figsize=(10, 2))
    ax = fig.add_subplot(1, 1, 1)
    h, = ax.plot(data, time)
    hnp, = ax.plot(data, timenp)
    np.testing.assert_equal(h.get_ydata(orig=False), hnp.get_ydata(orig=False))


@pytest.mark.parametrize('t0', [datetime.datetime(2017, 1, 1, 0, 1, 1),

                                [datetime.datetime(2017, 1, 1, 0, 1, 1),
                                 datetime.datetime(2017, 1, 1, 1, 1, 1)],

                                [[datetime.datetime(2017, 1, 1, 0, 1, 1),
                                  datetime.datetime(2017, 1, 1, 1, 1, 1)],
                                 [datetime.datetime(2017, 1, 1, 2, 1, 1),
                                  datetime.datetime(2017, 1, 1, 3, 1, 1)]]])
@pytest.mark.parametrize('dtype', ['datetime64[s]',
                                    'datetime64[us]',
                                    'datetime64[ms]',
                                    'datetime64[ns]'])
def test_date_date2num_numpy(t0, dtype):
    time = mdates.date2num(t0)
    tnp = np.array(t0, dtype=dtype)
    nptime = mdates.date2num(tnp)
    np.testing.assert_equal(time, nptime)


@pytest.mark.parametrize('dtype', ['datetime64[s]',
                                    'datetime64[us]',
                                    'datetime64[ms]',
                                    'datetime64[ns]'])
def test_date2num_NaT(dtype):
    t0 = datetime.datetime(2017, 1, 1, 0, 1, 1)
    tmpl = [mdates.date2num(t0), np.nan]
    tnp = np.array([t0, 'NaT'], dtype=dtype)
    nptime = mdates.date2num(tnp)
    np.testing.assert_array_equal(tmpl, nptime)


@pytest.mark.parametrize('units', ['s', 'ms', 'us', 'ns'])
def test_date2num_NaT_scalar(units):
    tmpl = mdates.date2num(np.datetime64('NaT', units))
    assert np.isnan(tmpl)


@image_comparison(['date_empty.png'])
def test_date_empty():
    # make sure we do the right thing when told to plot dates even
    # if no date data has been presented, cf
    # http://sourceforge.net/tracker/?func=detail&aid=2850075&group_id=80706&atid=560720
    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.xaxis_date()


@image_comparison(['date_axhspan.png'])
def test_date_axhspan():
    # test ax hspan with date inputs
    t0 = datetime.datetime(2009, 1, 20)
    tf = datetime.datetime(2009, 1, 21)
    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.axhspan(t0, tf, facecolor="blue", alpha=0.25)
    ax.set_ylim(t0 - datetime.timedelta(days=5),
                tf + datetime.timedelta(days=5))
    fig.subplots_adjust(left=0.25)


@image_comparison(['date_axvspan.png'])
def test_date_axvspan():
    # test ax hspan with date inputs
    t0 = datetime.datetime(2000, 1, 20)
    tf = datetime.datetime(2010, 1, 21)
    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.axvspan(t0, tf, facecolor="blue", alpha=0.25)
    ax.set_xlim(t0 - datetime.timedelta(days=720),
                tf + datetime.timedelta(days=720))
    fig.autofmt_xdate()


@image_comparison(['date_axhline.png'])
def test_date_axhline():
    # test ax hline with date inputs
    t0 = datetime.datetime(2009, 1, 20)
    tf = datetime.datetime(2009, 1, 31)
    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.axhline(t0, color="blue", lw=3)
    ax.set_ylim(t0 - datetime.timedelta(days=5),
                tf + datetime.timedelta(days=5))
    fig.subplots_adjust(left=0.25)


@image_comparison(['date_axvline.png'])
def test_date_axvline():
    # test ax hline with date inputs
    t0 = datetime.datetime(2000, 1, 20)
    tf = datetime.datetime(2000, 1, 21)
    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.axvline(t0, color="red", lw=3)
    ax.set_xlim(t0 - datetime.timedelta(days=5),
                tf + datetime.timedelta(days=5))
    fig.autofmt_xdate()


def test_too_many_date_ticks(caplog):
    # Attempt to test SF 2715172, see
    # https://sourceforge.net/tracker/?func=detail&aid=2715172&group_id=80706&atid=560720
    # setting equal datetimes triggers and expander call in
    # transforms.nonsingular which results in too many ticks in the
    # DayLocator.  This should emit a log at WARNING level.
    caplog.set_level("WARNING")
    t0 = datetime.datetime(2000, 1, 20)
    tf = datetime.datetime(2000, 1, 20)
    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    with pytest.warns(UserWarning) as rec:
        ax.set_xlim((t0, tf), auto=True)
        assert len(rec) == 1
        assert \
            'Attempting to set identical left == right' in str(rec[0].message)
    ax.plot([], [])
    ax.xaxis.set_major_locator(mdates.DayLocator())
    fig.canvas.draw()
    # The warning is emitted multiple times because the major locator is also
    # called both when placing the minor ticks (for overstriking detection) and
    # during tick label positioning.
    assert caplog.records and all(
        record.name == "matplotlib.ticker" and record.levelname == "WARNING"
        for record in caplog.records)


@image_comparison(['RRuleLocator_bounds.png'])
def test_RRuleLocator():
    import matplotlib.testing.jpl_units as units
    units.register()

    # This will cause the RRuleLocator to go out of bounds when it tries
    # to add padding to the limits, so we make sure it caps at the correct
    # boundary values.
    t0 = datetime.datetime(1000, 1, 1)
    tf = datetime.datetime(6000, 1, 1)

    fig = plt.figure()
    ax = plt.subplot(111)
    ax.set_autoscale_on(True)
    ax.plot([t0, tf], [0.0, 1.0], marker='o')

    rrule = mdates.rrulewrapper(dateutil.rrule.YEARLY, interval=500)
    locator = mdates.RRuleLocator(rrule)
    ax.xaxis.set_major_locator(locator)
    ax.xaxis.set_major_formatter(mdates.AutoDateFormatter(locator))

    ax.autoscale_view()
    fig.autofmt_xdate()


def test_RRuleLocator_dayrange():
    loc = mdates.DayLocator()
    x1 = datetime.datetime(year=1, month=1, day=1, tzinfo=mdates.UTC)
    y1 = datetime.datetime(year=1, month=1, day=16, tzinfo=mdates.UTC)
    loc.tick_values(x1, y1)
    # On success, no overflow error shall be thrown


@image_comparison(['DateFormatter_fractionalSeconds.png'])
def test_DateFormatter():
    import matplotlib.testing.jpl_units as units
    units.register()

    # Lets make sure that DateFormatter will allow us to have tick marks
    # at intervals of fractional seconds.

    t0 = datetime.datetime(2001, 1, 1, 0, 0, 0)
    tf = datetime.datetime(2001, 1, 1, 0, 0, 1)

    fig = plt.figure()
    ax = plt.subplot(111)
    ax.set_autoscale_on(True)
    ax.plot([t0, tf], [0.0, 1.0], marker='o')

    # rrule = mpldates.rrulewrapper( dateutil.rrule.YEARLY, interval=500 )
    # locator = mpldates.RRuleLocator( rrule )
    # ax.xaxis.set_major_locator( locator )
    # ax.xaxis.set_major_formatter( mpldates.AutoDateFormatter(locator) )

    ax.autoscale_view()
    fig.autofmt_xdate()


def test_locator_set_formatter():
    """
    Test if setting the locator only will update the AutoDateFormatter to use
    the new locator.
    """
    plt.rcParams["date.autoformatter.minute"] = "%d %H:%M"
    t = [datetime.datetime(2018, 9, 30, 8, 0),
         datetime.datetime(2018, 9, 30, 8, 59),
         datetime.datetime(2018, 9, 30, 10, 30)]
    x = [2, 3, 1]

    fig, ax = plt.subplots()
    ax.plot(t, x)
    ax.xaxis.set_major_locator(mdates.MinuteLocator((0, 30)))
    fig.canvas.draw()
    ticklabels = [tl.get_text() for tl in ax.get_xticklabels()]
    expected = ['30 08:00', '30 08:30', '30 09:00',
                '30 09:30', '30 10:00', '30 10:30']
    assert ticklabels == expected

    ax.xaxis.set_major_locator(mticker.NullLocator())
    ax.xaxis.set_minor_locator(mdates.MinuteLocator((5, 55)))
    decoy_loc = mdates.MinuteLocator((12, 27))
    ax.xaxis.set_minor_formatter(mdates.AutoDateFormatter(decoy_loc))

    ax.xaxis.set_minor_locator(mdates.MinuteLocator((15, 45)))
    fig.canvas.draw()
    ticklabels = [tl.get_text() for tl in ax.get_xticklabels(which="minor")]
    expected = ['30 08:15', '30 08:45', '30 09:15', '30 09:45', '30 10:15']
    assert ticklabels == expected


def test_date_formatter_callable():

    class _Locator:
        def _get_unit(self): return -11

    def callable_formatting_function(dates, _):
        return [dt.strftime('%d-%m//%Y') for dt in dates]

    formatter = mdates.AutoDateFormatter(_Locator())
    formatter.scaled[-10] = callable_formatting_function
    assert formatter([datetime.datetime(2014, 12, 25)]) == ['25-12//2014']


def test_drange():
    """
    This test should check if drange works as expected, and if all the
    rounding errors are fixed
    """
    start = datetime.datetime(2011, 1, 1, tzinfo=mdates.UTC)
    end = datetime.datetime(2011, 1, 2, tzinfo=mdates.UTC)
    delta = datetime.timedelta(hours=1)
    # We expect 24 values in drange(start, end, delta), because drange returns
    # dates from an half open interval [start, end)
    assert len(mdates.drange(start, end, delta)) == 24

    # if end is a little bit later, we expect the range to contain one element
    # more
    end = end + datetime.timedelta(microseconds=1)
    assert len(mdates.drange(start, end, delta)) == 25

    # reset end
    end = datetime.datetime(2011, 1, 2, tzinfo=mdates.UTC)

    # and tst drange with "complicated" floats:
    # 4 hours = 1/6 day, this is an "dangerous" float
    delta = datetime.timedelta(hours=4)
    daterange = mdates.drange(start, end, delta)
    assert len(daterange) == 6
    assert mdates.num2date(daterange[-1]) == (end - delta)


def test_empty_date_with_year_formatter():
    # exposes sf bug 2861426:
    # https://sourceforge.net/tracker/?func=detail&aid=2861426&group_id=80706&atid=560720

    # update: I am no longer believe this is a bug, as I commented on
    # the tracker.  The question is now: what to do with this test

    import matplotlib.dates as dates

    fig = plt.figure()
    ax = fig.add_subplot(111)

    yearFmt = dates.DateFormatter('%Y')
    ax.xaxis.set_major_formatter(yearFmt)

    with pytest.raises(ValueError):
        fig.canvas.draw()


def test_auto_date_locator():
    def _create_auto_date_locator(date1, date2):
        locator = mdates.AutoDateLocator(interval_multiples=False)
        locator.create_dummy_axis()
        locator.set_view_interval(mdates.date2num(date1),
                                  mdates.date2num(date2))
        return locator

    d1 = datetime.datetime(1990, 1, 1)
    results = ([datetime.timedelta(weeks=52 * 200),
                ['1990-01-01 00:00:00+00:00', '2010-01-01 00:00:00+00:00',
                 '2030-01-01 00:00:00+00:00', '2050-01-01 00:00:00+00:00',
                 '2070-01-01 00:00:00+00:00', '2090-01-01 00:00:00+00:00',
                 '2110-01-01 00:00:00+00:00', '2130-01-01 00:00:00+00:00',
                 '2150-01-01 00:00:00+00:00', '2170-01-01 00:00:00+00:00']
                ],
               [datetime.timedelta(weeks=52),
                ['1990-01-01 00:00:00+00:00', '1990-02-01 00:00:00+00:00',
                 '1990-03-01 00:00:00+00:00', '1990-04-01 00:00:00+00:00',
                 '1990-05-01 00:00:00+00:00', '1990-06-01 00:00:00+00:00',
                 '1990-07-01 00:00:00+00:00', '1990-08-01 00:00:00+00:00',
                 '1990-09-01 00:00:00+00:00', '1990-10-01 00:00:00+00:00',
                 '1990-11-01 00:00:00+00:00', '1990-12-01 00:00:00+00:00']
                ],
               [datetime.timedelta(days=141),
                ['1990-01-05 00:00:00+00:00', '1990-01-26 00:00:00+00:00',
                 '1990-02-16 00:00:00+00:00', '1990-03-09 00:00:00+00:00',
                 '1990-03-30 00:00:00+00:00', '1990-04-20 00:00:00+00:00',
                 '1990-05-11 00:00:00+00:00']
                ],
               [datetime.timedelta(days=40),
                ['1990-01-03 00:00:00+00:00', '1990-01-10 00:00:00+00:00',
                 '1990-01-17 00:00:00+00:00', '1990-01-24 00:00:00+00:00',
                 '1990-01-31 00:00:00+00:00', '1990-02-07 00:00:00+00:00']
                ],
               [datetime.timedelta(hours=40),
                ['1990-01-01 00:00:00+00:00', '1990-01-01 04:00:00+00:00',
                 '1990-01-01 08:00:00+00:00', '1990-01-01 12:00:00+00:00',
                 '1990-01-01 16:00:00+00:00', '1990-01-01 20:00:00+00:00',
                 '1990-01-02 00:00:00+00:00', '1990-01-02 04:00:00+00:00',
                 '1990-01-02 08:00:00+00:00', '1990-01-02 12:00:00+00:00',
                 '1990-01-02 16:00:00+00:00']
                ],
               [datetime.timedelta(minutes=20),
                ['1990-01-01 00:00:00+00:00', '1990-01-01 00:05:00+00:00',
                 '1990-01-01 00:10:00+00:00', '1990-01-01 00:15:00+00:00',
                 '1990-01-01 00:20:00+00:00']
                ],
               [datetime.timedelta(seconds=40),
                ['1990-01-01 00:00:00+00:00', '1990-01-01 00:00:05+00:00',
                 '1990-01-01 00:00:10+00:00', '1990-01-01 00:00:15+00:00',
                 '1990-01-01 00:00:20+00:00', '1990-01-01 00:00:25+00:00',
                 '1990-01-01 00:00:30+00:00', '1990-01-01 00:00:35+00:00',
                 '1990-01-01 00:00:40+00:00']
                ],
               [datetime.timedelta(microseconds=1500),
                ['1989-12-31 23:59:59.999500+00:00',
                 '1990-01-01 00:00:00+00:00',
                 '1990-01-01 00:00:00.000500+00:00',
                 '1990-01-01 00:00:00.001000+00:00',
                 '1990-01-01 00:00:00.001500+00:00']
                ],
               )

    for t_delta, expected in results:
        d2 = d1 + t_delta
        locator = _create_auto_date_locator(d1, d2)
        with (pytest.warns(UserWarning) if t_delta.microseconds
              else nullcontext()):
            assert list(map(str, mdates.num2date(locator()))) == expected


def test_auto_date_locator_intmult():
    def _create_auto_date_locator(date1, date2):
        locator = mdates.AutoDateLocator(interval_multiples=True)
        locator.create_dummy_axis()
        locator.set_view_interval(mdates.date2num(date1),
                                  mdates.date2num(date2))
        return locator

    results = ([datetime.timedelta(weeks=52 * 200),
                ['1980-01-01 00:00:00+00:00', '2000-01-01 00:00:00+00:00',
                 '2020-01-01 00:00:00+00:00', '2040-01-01 00:00:00+00:00',
                 '2060-01-01 00:00:00+00:00', '2080-01-01 00:00:00+00:00',
                 '2100-01-01 00:00:00+00:00', '2120-01-01 00:00:00+00:00',
                 '2140-01-01 00:00:00+00:00', '2160-01-01 00:00:00+00:00',
                 '2180-01-01 00:00:00+00:00', '2200-01-01 00:00:00+00:00']
                ],
               [datetime.timedelta(weeks=52),
                ['1997-01-01 00:00:00+00:00', '1997-02-01 00:00:00+00:00',
                 '1997-03-01 00:00:00+00:00', '1997-04-01 00:00:00+00:00',
                 '1997-05-01 00:00:00+00:00', '1997-06-01 00:00:00+00:00',
                 '1997-07-01 00:00:00+00:00', '1997-08-01 00:00:00+00:00',
                 '1997-09-01 00:00:00+00:00', '1997-10-01 00:00:00+00:00',
                 '1997-11-01 00:00:00+00:00', '1997-12-01 00:00:00+00:00']
                ],
               [datetime.timedelta(days=141),
                ['1997-01-01 00:00:00+00:00', '1997-01-22 00:00:00+00:00',
                 '1997-02-01 00:00:00+00:00', '1997-02-22 00:00:00+00:00',
                 '1997-03-01 00:00:00+00:00', '1997-03-22 00:00:00+00:00',
                 '1997-04-01 00:00:00+00:00', '1997-04-22 00:00:00+00:00',
                 '1997-05-01 00:00:00+00:00', '1997-05-22 00:00:00+00:00']
                ],
               [datetime.timedelta(days=40),
                ['1997-01-01 00:00:00+00:00', '1997-01-05 00:00:00+00:00',
                 '1997-01-09 00:00:00+00:00', '1997-01-13 00:00:00+00:00',
                 '1997-01-17 00:00:00+00:00', '1997-01-21 00:00:00+00:00',
                 '1997-01-25 00:00:00+00:00', '1997-01-29 00:00:00+00:00',
                 '1997-02-01 00:00:00+00:00', '1997-02-05 00:00:00+00:00',
                 '1997-02-09 00:00:00+00:00']
                ],
               [datetime.timedelta(hours=40),
                ['1997-01-01 00:00:00+00:00', '1997-01-01 04:00:00+00:00',
                 '1997-01-01 08:00:00+00:00', '1997-01-01 12:00:00+00:00',
                 '1997-01-01 16:00:00+00:00', '1997-01-01 20:00:00+00:00',
                 '1997-01-02 00:00:00+00:00', '1997-01-02 04:00:00+00:00',
                 '1997-01-02 08:00:00+00:00', '1997-01-02 12:00:00+00:00',
                 '1997-01-02 16:00:00+00:00']
                ],
               [datetime.timedelta(minutes=20),
                ['1997-01-01 00:00:00+00:00', '1997-01-01 00:05:00+00:00',
                 '1997-01-01 00:10:00+00:00', '1997-01-01 00:15:00+00:00',
                 '1997-01-01 00:20:00+00:00']
                ],
               [datetime.timedelta(seconds=40),
                ['1997-01-01 00:00:00+00:00', '1997-01-01 00:00:05+00:00',
                 '1997-01-01 00:00:10+00:00', '1997-01-01 00:00:15+00:00',
                 '1997-01-01 00:00:20+00:00', '1997-01-01 00:00:25+00:00',
                 '1997-01-01 00:00:30+00:00', '1997-01-01 00:00:35+00:00',
                 '1997-01-01 00:00:40+00:00']
                ],
               [datetime.timedelta(microseconds=1500),
                ['1996-12-31 23:59:59.999500+00:00',
                 '1997-01-01 00:00:00+00:00',
                 '1997-01-01 00:00:00.000500+00:00',
                 '1997-01-01 00:00:00.001000+00:00',
                 '1997-01-01 00:00:00.001500+00:00']
                ],
               )

    d1 = datetime.datetime(1997, 1, 1)
    for t_delta, expected in results:
        d2 = d1 + t_delta
        locator = _create_auto_date_locator(d1, d2)
        with (pytest.warns(UserWarning) if t_delta.microseconds
              else nullcontext()):
            assert list(map(str, mdates.num2date(locator()))) == expected


def test_concise_formatter():
    def _create_auto_date_locator(date1, date2):
        fig, ax = plt.subplots()

        locator = mdates.AutoDateLocator(interval_multiples=True)
        formatter = mdates.ConciseDateFormatter(locator)
        ax.yaxis.set_major_locator(locator)
        ax.yaxis.set_major_formatter(formatter)
        ax.set_ylim(date1, date2)
        fig.canvas.draw()
        sts = []
        for st in ax.get_yticklabels():
            sts += [st.get_text()]
        return sts

    d1 = datetime.datetime(1997, 1, 1)
    results = ([datetime.timedelta(weeks=52 * 200),
                [str(t) for t in range(1980, 2201, 20)]
                ],
               [datetime.timedelta(weeks=52),
                ['1997', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug',
                'Sep', 'Oct', 'Nov', 'Dec']
                ],
               [datetime.timedelta(days=141),
                ['Jan', '22', 'Feb', '22', 'Mar', '22', 'Apr', '22',
                 'May', '22']
                ],
               [datetime.timedelta(days=40),
                ['Jan', '05', '09', '13', '17', '21', '25', '29', 'Feb',
                 '05', '09']
                ],
               [datetime.timedelta(hours=40),
                ['Jan-01', '04:00', '08:00', '12:00', '16:00', '20:00',
                 'Jan-02', '04:00', '08:00', '12:00', '16:00']
                ],
               [datetime.timedelta(minutes=20),
                ['00:00', '00:05', '00:10', '00:15', '00:20']
                ],
               [datetime.timedelta(seconds=40),
                ['00:00', '05', '10', '15', '20', '25', '30', '35', '40']
                ],
               [datetime.timedelta(seconds=2),
                ['59.5', '00:00', '00.5', '01.0', '01.5', '02.0', '02.5']
                ],
               )
    for t_delta, expected in results:
        d2 = d1 + t_delta
        strings = _create_auto_date_locator(d1, d2)
        assert strings == expected


def test_concise_formatter_tz():
    def _create_auto_date_locator(date1, date2, tz):
        fig, ax = plt.subplots()

        locator = mdates.AutoDateLocator(interval_multiples=True)
        formatter = mdates.ConciseDateFormatter(locator, tz=tz)
        ax.yaxis.set_major_locator(locator)
        ax.yaxis.set_major_formatter(formatter)
        ax.set_ylim(date1, date2)
        fig.canvas.draw()
        sts = []
        for st in ax.get_yticklabels():
            sts += [st.get_text()]
        return sts, ax.yaxis.get_offset_text().get_text()

    d1 = datetime.datetime(1997, 1, 1).replace(tzinfo=datetime.timezone.utc)
    results = ([datetime.timedelta(hours=40),
                ['03:00', '07:00', '11:00', '15:00', '19:00', '23:00',
                 '03:00', '07:00', '11:00', '15:00', '19:00'],
                "1997-Jan-02"
                ],
               [datetime.timedelta(minutes=20),
                ['03:00', '03:05', '03:10', '03:15', '03:20'],
                "1997-Jan-01"
                ],
               [datetime.timedelta(seconds=40),
                ['03:00', '05', '10', '15', '20', '25', '30', '35', '40'],
                "1997-Jan-01 03:00"
                ],
               [datetime.timedelta(seconds=2),
                ['59.5', '03:00', '00.5', '01.0', '01.5', '02.0', '02.5'],
                "1997-Jan-01 03:00"
                ],
               )

    new_tz = datetime.timezone(datetime.timedelta(hours=3))
    for t_delta, expected_strings, expected_offset in results:
        d2 = d1 + t_delta
        strings, offset = _create_auto_date_locator(d1, d2, new_tz)
        assert strings == expected_strings
        assert offset == expected_offset


def test_auto_date_locator_intmult_tz():
    def _create_auto_date_locator(date1, date2, tz):
        locator = mdates.AutoDateLocator(interval_multiples=True, tz=tz)
        locator.create_dummy_axis()
        locator.set_view_interval(mdates.date2num(date1),
                                  mdates.date2num(date2))
        return locator

    results = ([datetime.timedelta(weeks=52*200),
                ['1980-01-01 00:00:00-08:00', '2000-01-01 00:00:00-08:00',
                 '2020-01-01 00:00:00-08:00', '2040-01-01 00:00:00-08:00',
                 '2060-01-01 00:00:00-08:00', '2080-01-01 00:00:00-08:00',
                 '2100-01-01 00:00:00-08:00', '2120-01-01 00:00:00-08:00',
                 '2140-01-01 00:00:00-08:00', '2160-01-01 00:00:00-08:00',
                 '2180-01-01 00:00:00-08:00', '2200-01-01 00:00:00-08:00']
                ],
               [datetime.timedelta(weeks=52),
                ['1997-01-01 00:00:00-08:00', '1997-02-01 00:00:00-08:00',
                 '1997-03-01 00:00:00-08:00', '1997-04-01 00:00:00-08:00',
                 '1997-05-01 00:00:00-07:00', '1997-06-01 00:00:00-07:00',
                 '1997-07-01 00:00:00-07:00', '1997-08-01 00:00:00-07:00',
                 '1997-09-01 00:00:00-07:00', '1997-10-01 00:00:00-07:00',
                 '1997-11-01 00:00:00-08:00', '1997-12-01 00:00:00-08:00']
                ],
               [datetime.timedelta(days=141),
                ['1997-01-01 00:00:00-08:00', '1997-01-22 00:00:00-08:00',
                 '1997-02-01 00:00:00-08:00', '1997-02-22 00:00:00-08:00',
                 '1997-03-01 00:00:00-08:00', '1997-03-22 00:00:00-08:00',
                 '1997-04-01 00:00:00-08:00', '1997-04-22 00:00:00-07:00',
                 '1997-05-01 00:00:00-07:00', '1997-05-22 00:00:00-07:00']
                ],
               [datetime.timedelta(days=40),
                ['1997-01-01 00:00:00-08:00', '1997-01-05 00:00:00-08:00',
                 '1997-01-09 00:00:00-08:00', '1997-01-13 00:00:00-08:00',
                 '1997-01-17 00:00:00-08:00', '1997-01-21 00:00:00-08:00',
                 '1997-01-25 00:00:00-08:00', '1997-01-29 00:00:00-08:00',
                 '1997-02-01 00:00:00-08:00', '1997-02-05 00:00:00-08:00',
                 '1997-02-09 00:00:00-08:00']
                ],
               [datetime.timedelta(hours=40),
                ['1997-01-01 00:00:00-08:00', '1997-01-01 04:00:00-08:00',
                 '1997-01-01 08:00:00-08:00', '1997-01-01 12:00:00-08:00',
                 '1997-01-01 16:00:00-08:00', '1997-01-01 20:00:00-08:00',
                 '1997-01-02 00:00:00-08:00', '1997-01-02 04:00:00-08:00',
                 '1997-01-02 08:00:00-08:00', '1997-01-02 12:00:00-08:00',
                 '1997-01-02 16:00:00-08:00']
                ],
               [datetime.timedelta(minutes=20),
                ['1997-01-01 00:00:00-08:00', '1997-01-01 00:05:00-08:00',
                 '1997-01-01 00:10:00-08:00', '1997-01-01 00:15:00-08:00',
                 '1997-01-01 00:20:00-08:00']
                ],
               [datetime.timedelta(seconds=40),
                ['1997-01-01 00:00:00-08:00', '1997-01-01 00:00:05-08:00',
                 '1997-01-01 00:00:10-08:00', '1997-01-01 00:00:15-08:00',
                 '1997-01-01 00:00:20-08:00', '1997-01-01 00:00:25-08:00',
                 '1997-01-01 00:00:30-08:00', '1997-01-01 00:00:35-08:00',
                 '1997-01-01 00:00:40-08:00']
                ]
               )

    tz = dateutil.tz.gettz('Canada/Pacific')
    d1 = datetime.datetime(1997, 1, 1, tzinfo=tz)
    for t_delta, expected in results:
        with rc_context({'_internal.classic_mode': False}):
            d2 = d1 + t_delta
            locator = _create_auto_date_locator(d1, d2, tz)
            st = list(map(str, mdates.num2date(locator(), tz=tz)))
            assert st == expected


@image_comparison(['date_inverted_limit.png'])
def test_date_inverted_limit():
    # test ax hline with date inputs
    t0 = datetime.datetime(2009, 1, 20)
    tf = datetime.datetime(2009, 1, 31)
    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.axhline(t0, color="blue", lw=3)
    ax.set_ylim(t0 - datetime.timedelta(days=5),
                tf + datetime.timedelta(days=5))
    ax.invert_yaxis()
    fig.subplots_adjust(left=0.25)


def _test_date2num_dst(date_range, tz_convert):
    # Timezones
    BRUSSELS = dateutil.tz.gettz('Europe/Brussels')
    UTC = mdates.UTC

    # Create a list of timezone-aware datetime objects in UTC
    # Interval is 0b0.0000011 days, to prevent float rounding issues
    dtstart = datetime.datetime(2014, 3, 30, 0, 0, tzinfo=UTC)
    interval = datetime.timedelta(minutes=33, seconds=45)
    interval_days = 0.0234375   # 2025 / 86400 seconds
    N = 8

    dt_utc = date_range(start=dtstart, freq=interval, periods=N)
    dt_bxl = tz_convert(dt_utc, BRUSSELS)

    expected_ordinalf = [735322.0 + (i * interval_days) for i in range(N)]
    actual_ordinalf = list(mdates.date2num(dt_bxl))

    assert actual_ordinalf == expected_ordinalf


def test_date2num_dst():
    # Test for github issue #3896, but in date2num around DST transitions
    # with a timezone-aware pandas date_range object.

    class dt_tzaware(datetime.datetime):
        """
        This bug specifically occurs because of the normalization behavior of
        pandas Timestamp objects, so in order to replicate it, we need a
        datetime-like object that applies timezone normalization after
        subtraction.
        """
        def __sub__(self, other):
            r = super().__sub__(other)
            tzinfo = getattr(r, 'tzinfo', None)

            if tzinfo is not None:
                localizer = getattr(tzinfo, 'normalize', None)
                if localizer is not None:
                    r = tzinfo.normalize(r)

            if isinstance(r, datetime.datetime):
                r = self.mk_tzaware(r)

            return r

        def __add__(self, other):
            return self.mk_tzaware(super().__add__(other))

        def astimezone(self, tzinfo):
            dt = super().astimezone(tzinfo)
            return self.mk_tzaware(dt)

        @classmethod
        def mk_tzaware(cls, datetime_obj):
            kwargs = {}
            attrs = ('year',
                     'month',
                     'day',
                     'hour',
                     'minute',
                     'second',
                     'microsecond',
                     'tzinfo')

            for attr in attrs:
                val = getattr(datetime_obj, attr, None)
                if val is not None:
                    kwargs[attr] = val

            return cls(**kwargs)

    # Define a date_range function similar to pandas.date_range
    def date_range(start, freq, periods):
        dtstart = dt_tzaware.mk_tzaware(start)

        return [dtstart + (i * freq) for i in range(periods)]

    # Define a tz_convert function that converts a list to a new time zone.
    def tz_convert(dt_list, tzinfo):
        return [d.astimezone(tzinfo) for d in dt_list]

    _test_date2num_dst(date_range, tz_convert)


def test_date2num_dst_pandas(pd):
    # Test for github issue #3896, but in date2num around DST transitions
    # with a timezone-aware pandas date_range object.

    def tz_convert(*args):
        return pd.DatetimeIndex.tz_convert(*args).astype(object)

    _test_date2num_dst(pd.date_range, tz_convert)


def _test_rrulewrapper(attach_tz, get_tz):
    SYD = get_tz('Australia/Sydney')

    dtstart = attach_tz(datetime.datetime(2017, 4, 1, 0), SYD)
    dtend = attach_tz(datetime.datetime(2017, 4, 4, 0), SYD)

    rule = mdates.rrulewrapper(freq=dateutil.rrule.DAILY, dtstart=dtstart)

    act = rule.between(dtstart, dtend)
    exp = [datetime.datetime(2017, 4, 1, 13, tzinfo=dateutil.tz.tzutc()),
           datetime.datetime(2017, 4, 2, 14, tzinfo=dateutil.tz.tzutc())]

    assert act == exp


def test_rrulewrapper():
    def attach_tz(dt, zi):
        return dt.replace(tzinfo=zi)

    _test_rrulewrapper(attach_tz, dateutil.tz.gettz)


@pytest.mark.pytz
def test_rrulewrapper_pytz():
    # Test to make sure pytz zones are supported in rrules
    pytz = pytest.importorskip("pytz")

    def attach_tz(dt, zi):
        return zi.localize(dt)

    _test_rrulewrapper(attach_tz, pytz.timezone)


@pytest.mark.pytz
def test_yearlocator_pytz():
    pytz = pytest.importorskip("pytz")

    tz = pytz.timezone('America/New_York')
    x = [tz.localize(datetime.datetime(2010, 1, 1))
            + datetime.timedelta(i) for i in range(2000)]
    locator = mdates.AutoDateLocator(interval_multiples=True, tz=tz)
    locator.create_dummy_axis()
    locator.set_view_interval(mdates.date2num(x[0])-1.0,
                              mdates.date2num(x[-1])+1.0)

    np.testing.assert_allclose([733408.208333, 733773.208333, 734138.208333,
                                734503.208333, 734869.208333,
                                735234.208333, 735599.208333], locator())
    expected = ['2009-01-01 00:00:00-05:00',
                '2010-01-01 00:00:00-05:00', '2011-01-01 00:00:00-05:00',
                '2012-01-01 00:00:00-05:00', '2013-01-01 00:00:00-05:00',
                '2014-01-01 00:00:00-05:00', '2015-01-01 00:00:00-05:00']
    st = list(map(str, mdates.num2date(locator(), tz=tz)))
    assert st == expected


def test_DayLocator():
    with pytest.raises(ValueError):
        mdates.DayLocator(interval=-1)
    with pytest.raises(ValueError):
        mdates.DayLocator(interval=-1.5)
    with pytest.raises(ValueError):
        mdates.DayLocator(interval=0)
    with pytest.raises(ValueError):
        mdates.DayLocator(interval=1.3)
    mdates.DayLocator(interval=1.0)


def test_tz_utc():
    dt = datetime.datetime(1970, 1, 1, tzinfo=mdates.UTC)
    dt.tzname()


@pytest.mark.parametrize("x, tdelta",
                         [(1, datetime.timedelta(days=1)),
                          ([1, 1.5], [datetime.timedelta(days=1),
                                      datetime.timedelta(days=1.5)])])
def test_num2timedelta(x, tdelta):
    dt = mdates.num2timedelta(x)
    assert dt == tdelta


def test_datetime64_in_list():
    dt = [np.datetime64('2000-01-01'), np.datetime64('2001-01-01')]
    dn = mdates.date2num(dt)
    np.testing.assert_equal(dn, [730120.,  730486.])