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test_converter.py
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from datetime import date, datetime
import subprocess
import sys
import numpy as np
import pytest
import pandas._config.config as cf
from pandas.compat.numpy import np_datetime64_compat
from pandas import Index, Period, Series, Timestamp, date_range
import pandas.util.testing as tm
from pandas.plotting import (
deregister_matplotlib_converters,
register_matplotlib_converters,
)
from pandas.tseries.offsets import Day, Micro, Milli, Second
try:
from pandas.plotting._matplotlib import converter
except ImportError:
# try / except, rather than skip, to avoid internal refactoring
# causing an improprer skip
pass
pytest.importorskip("matplotlib.pyplot")
def test_initial_warning():
code = (
"import pandas as pd; import matplotlib.pyplot as plt; "
"s = pd.Series(1, pd.date_range('2000', periods=12)); "
"fig, ax = plt.subplots(); "
"ax.plot(s.index, s.values)"
)
call = [sys.executable, "-c", code]
out = subprocess.check_output(call, stderr=subprocess.STDOUT).decode()
assert "Using an implicitly" in out
def test_timtetonum_accepts_unicode():
assert converter.time2num("00:01") == converter.time2num("00:01")
class TestRegistration:
def test_register_by_default(self):
# Run in subprocess to ensure a clean state
code = (
"'import matplotlib.units; "
"import pandas as pd; "
"units = dict(matplotlib.units.registry); "
"assert pd.Timestamp in units)'"
)
call = [sys.executable, "-c", code]
assert subprocess.check_call(call) == 0
def test_warns(self):
plt = pytest.importorskip("matplotlib.pyplot")
s = Series(range(12), index=date_range("2017", periods=12))
_, ax = plt.subplots()
# Set to the "warning" state, in case this isn't the first test run
converter._WARN = True
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False) as w:
ax.plot(s.index, s.values)
plt.close()
assert len(w) == 1
assert "Using an implicitly registered datetime converter" in str(w[0])
def test_registering_no_warning(self):
plt = pytest.importorskip("matplotlib.pyplot")
s = Series(range(12), index=date_range("2017", periods=12))
_, ax = plt.subplots()
# Set to the "warn" state, in case this isn't the first test run
converter._WARN = True
register_matplotlib_converters()
with tm.assert_produces_warning(None) as w:
ax.plot(s.index, s.values)
assert len(w) == 0
def test_pandas_plots_register(self):
pytest.importorskip("matplotlib.pyplot")
s = Series(range(12), index=date_range("2017", periods=12))
# Set to the "warn" state, in case this isn't the first test run
converter._WARN = True
with tm.assert_produces_warning(None) as w:
s.plot()
assert len(w) == 0
def test_matplotlib_formatters(self):
units = pytest.importorskip("matplotlib.units")
assert Timestamp in units.registry
ctx = cf.option_context("plotting.matplotlib.register_converters", False)
with ctx:
assert Timestamp not in units.registry
assert Timestamp in units.registry
def test_option_no_warning(self):
pytest.importorskip("matplotlib.pyplot")
ctx = cf.option_context("plotting.matplotlib.register_converters", False)
plt = pytest.importorskip("matplotlib.pyplot")
s = Series(range(12), index=date_range("2017", periods=12))
_, ax = plt.subplots()
converter._WARN = True
# Test without registering first, no warning
with ctx:
with tm.assert_produces_warning(None) as w:
ax.plot(s.index, s.values)
assert len(w) == 0
# Now test with registering
converter._WARN = True
register_matplotlib_converters()
with ctx:
with tm.assert_produces_warning(None) as w:
ax.plot(s.index, s.values)
assert len(w) == 0
def test_registry_resets(self):
units = pytest.importorskip("matplotlib.units")
dates = pytest.importorskip("matplotlib.dates")
# make a copy, to reset to
original = dict(units.registry)
try:
# get to a known state
units.registry.clear()
date_converter = dates.DateConverter()
units.registry[datetime] = date_converter
units.registry[date] = date_converter
register_matplotlib_converters()
assert units.registry[date] is not date_converter
deregister_matplotlib_converters()
assert units.registry[date] is date_converter
finally:
# restore original stater
units.registry.clear()
for k, v in original.items():
units.registry[k] = v
def test_old_import_warns(self):
with tm.assert_produces_warning(FutureWarning) as w:
from pandas.tseries import converter
converter.register()
assert len(w)
assert "pandas.plotting.register_matplotlib_converters" in str(w[0].message)
class TestDateTimeConverter:
def setup_method(self, method):
self.dtc = converter.DatetimeConverter()
self.tc = converter.TimeFormatter(None)
def test_convert_accepts_unicode(self):
r1 = self.dtc.convert("12:22", None, None)
r2 = self.dtc.convert("12:22", None, None)
assert r1 == r2, "DatetimeConverter.convert should accept unicode"
def test_conversion(self):
rs = self.dtc.convert(["2012-1-1"], None, None)[0]
xp = datetime(2012, 1, 1).toordinal()
assert rs == xp
rs = self.dtc.convert("2012-1-1", None, None)
assert rs == xp
rs = self.dtc.convert(date(2012, 1, 1), None, None)
assert rs == xp
rs = self.dtc.convert(datetime(2012, 1, 1).toordinal(), None, None)
assert rs == xp
rs = self.dtc.convert("2012-1-1", None, None)
assert rs == xp
rs = self.dtc.convert(Timestamp("2012-1-1"), None, None)
assert rs == xp
# also testing datetime64 dtype (GH8614)
rs = self.dtc.convert(np_datetime64_compat("2012-01-01"), None, None)
assert rs == xp
rs = self.dtc.convert(
np_datetime64_compat("2012-01-01 00:00:00+0000"), None, None
)
assert rs == xp
rs = self.dtc.convert(
np.array(
[
np_datetime64_compat("2012-01-01 00:00:00+0000"),
np_datetime64_compat("2012-01-02 00:00:00+0000"),
]
),
None,
None,
)
assert rs[0] == xp
# we have a tz-aware date (constructed to that when we turn to utc it
# is the same as our sample)
ts = Timestamp("2012-01-01").tz_localize("UTC").tz_convert("US/Eastern")
rs = self.dtc.convert(ts, None, None)
assert rs == xp
rs = self.dtc.convert(ts.to_pydatetime(), None, None)
assert rs == xp
rs = self.dtc.convert(Index([ts - Day(1), ts]), None, None)
assert rs[1] == xp
rs = self.dtc.convert(Index([ts - Day(1), ts]).to_pydatetime(), None, None)
assert rs[1] == xp
def test_conversion_float(self):
decimals = 9
rs = self.dtc.convert(Timestamp("2012-1-1 01:02:03", tz="UTC"), None, None)
xp = converter.dates.date2num(Timestamp("2012-1-1 01:02:03", tz="UTC"))
tm.assert_almost_equal(rs, xp, decimals)
rs = self.dtc.convert(
Timestamp("2012-1-1 09:02:03", tz="Asia/Hong_Kong"), None, None
)
tm.assert_almost_equal(rs, xp, decimals)
rs = self.dtc.convert(datetime(2012, 1, 1, 1, 2, 3), None, None)
tm.assert_almost_equal(rs, xp, decimals)
def test_conversion_outofbounds_datetime(self):
# 2579
values = [date(1677, 1, 1), date(1677, 1, 2)]
rs = self.dtc.convert(values, None, None)
xp = converter.dates.date2num(values)
tm.assert_numpy_array_equal(rs, xp)
rs = self.dtc.convert(values[0], None, None)
xp = converter.dates.date2num(values[0])
assert rs == xp
values = [datetime(1677, 1, 1, 12), datetime(1677, 1, 2, 12)]
rs = self.dtc.convert(values, None, None)
xp = converter.dates.date2num(values)
tm.assert_numpy_array_equal(rs, xp)
rs = self.dtc.convert(values[0], None, None)
xp = converter.dates.date2num(values[0])
assert rs == xp
@pytest.mark.parametrize(
"time,format_expected",
[
(0, "00:00"), # time2num(datetime.time.min)
(86399.999999, "23:59:59.999999"), # time2num(datetime.time.max)
(90000, "01:00"),
(3723, "01:02:03"),
(39723.2, "11:02:03.200"),
],
)
def test_time_formatter(self, time, format_expected):
# issue 18478
result = self.tc(time)
assert result == format_expected
def test_dateindex_conversion(self):
decimals = 9
for freq in ("B", "L", "S"):
dateindex = tm.makeDateIndex(k=10, freq=freq)
rs = self.dtc.convert(dateindex, None, None)
xp = converter.dates.date2num(dateindex._mpl_repr())
tm.assert_almost_equal(rs, xp, decimals)
def test_resolution(self):
def _assert_less(ts1, ts2):
val1 = self.dtc.convert(ts1, None, None)
val2 = self.dtc.convert(ts2, None, None)
if not val1 < val2:
raise AssertionError("{0} is not less than {1}.".format(val1, val2))
# Matplotlib's time representation using floats cannot distinguish
# intervals smaller than ~10 microsecond in the common range of years.
ts = Timestamp("2012-1-1")
_assert_less(ts, ts + Second())
_assert_less(ts, ts + Milli())
_assert_less(ts, ts + Micro(50))
def test_convert_nested(self):
inner = [Timestamp("2017-01-01"), Timestamp("2017-01-02")]
data = [inner, inner]
result = self.dtc.convert(data, None, None)
expected = [self.dtc.convert(x, None, None) for x in data]
assert (np.array(result) == expected).all()
class TestPeriodConverter:
def setup_method(self, method):
self.pc = converter.PeriodConverter()
class Axis:
pass
self.axis = Axis()
self.axis.freq = "D"
def test_convert_accepts_unicode(self):
r1 = self.pc.convert("2012-1-1", None, self.axis)
r2 = self.pc.convert("2012-1-1", None, self.axis)
assert r1 == r2
def test_conversion(self):
rs = self.pc.convert(["2012-1-1"], None, self.axis)[0]
xp = Period("2012-1-1").ordinal
assert rs == xp
rs = self.pc.convert("2012-1-1", None, self.axis)
assert rs == xp
rs = self.pc.convert([date(2012, 1, 1)], None, self.axis)[0]
assert rs == xp
rs = self.pc.convert(date(2012, 1, 1), None, self.axis)
assert rs == xp
rs = self.pc.convert([Timestamp("2012-1-1")], None, self.axis)[0]
assert rs == xp
rs = self.pc.convert(Timestamp("2012-1-1"), None, self.axis)
assert rs == xp
rs = self.pc.convert(np_datetime64_compat("2012-01-01"), None, self.axis)
assert rs == xp
rs = self.pc.convert(
np_datetime64_compat("2012-01-01 00:00:00+0000"), None, self.axis
)
assert rs == xp
rs = self.pc.convert(
np.array(
[
np_datetime64_compat("2012-01-01 00:00:00+0000"),
np_datetime64_compat("2012-01-02 00:00:00+0000"),
]
),
None,
self.axis,
)
assert rs[0] == xp
def test_integer_passthrough(self):
# GH9012
rs = self.pc.convert([0, 1], None, self.axis)
xp = [0, 1]
assert rs == xp
def test_convert_nested(self):
data = ["2012-1-1", "2012-1-2"]
r1 = self.pc.convert([data, data], None, self.axis)
r2 = [self.pc.convert(data, None, self.axis) for _ in range(2)]
assert r1 == r2
class TestTimeDeltaConverter:
"""Test timedelta converter"""
@pytest.mark.parametrize(
"x, decimal, format_expected",
[
(0.0, 0, "00:00:00"),
(3972320000000, 1, "01:06:12.3"),
(713233432000000, 2, "8 days 06:07:13.43"),
(32423432000000, 4, "09:00:23.4320"),
],
)
def test_format_timedelta_ticks(self, x, decimal, format_expected):
tdc = converter.TimeSeries_TimedeltaFormatter
result = tdc.format_timedelta_ticks(x, pos=None, n_decimals=decimal)
assert result == format_expected