8000 ENH: support np.datenum64 in dates.py by jklymak · Pull Request #9779 · matplotlib/matplotlib · GitHub
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ENH: support np.datenum64 in dates.py #9779

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Merged
merged 1 commit into from
Nov 15, 2017
Merged

ENH: support np.datenum64 in dates.py #9779

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37 changes: 32 additions & 5 deletions lib/matplotlib/dates.py
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Original file line number Diff line number Diff line change
Expand Up @@ -243,6 +243,27 @@ def _to_ordinalf(dt):
_to_ordinalf_np_vectorized = np.vectorize(_to_ordinalf)


def _dt64_to_ordinalf(d):
"""
Convert `numpy.datetime64` or an ndarray of those types to Gregorian
date as UTC float. Roundoff is via float64 precision. Practically:
microseconds for dates between 290301 BC, 294241 AD, milliseconds for
larger dates (see `numpy.datetime64`). Nanoseconds aren't possible
because we do times compared to ``0001-01-01T00:00:00`` (plus one day).
"""

# the "extra" ensures that we at least allow the dynamic range out to
# seconds. That should get out to +/-2e11 years.
extra = d - d.astype('datetime64[s]')
extra = extra.astype('timedelta64[ns]')
t0 = np.datetime64('0001-01-01T00:00:00').astype('datetime64[s]')
dt = (d.astype('datetime64[s]') - t0).astype(np.float64)
dt += extra.astype(np.float64) / 1.0e9
dt = dt / SEC_PER_DAY + 1.0

return dt


def _from_ordinalf(x, tz=None):
"""
Convert Gregorian float of the date, preserving hours, minutes,
Expand Down Expand Up @@ -354,12 +375,13 @@ def date2num(d):

Parameters
----------
d : :class:`datetime` or sequence of :class:`datetime`
d : :class:`datetime` or :class:`numpy.datetime64`, or sequences of
these classes.

Returns
-------
float or sequence of floats
Number of days (fraction part represents hours, minutes, seconds)
Number of days (fraction part represents hours, minutes, seconds, ms)
since 0001-01-01 00:00:00 UTC, plus one.

Notes
Expand All @@ -368,6 +390,10 @@ def date2num(d):
Gregorian calendar is assumed; this is not universal practice.
For details see the module docstring.
"""

if ((isinstance(d, np.ndarray) and np.issubdtype(d.dtype, np.datetime64))
or isinstance(d, np.datetime64)):
return _dt64_to_ordinalf(d)
if not cbook.iterable(d):
return _to_ordinalf(d)
else:
Expand Down Expand Up @@ -488,8 +514,8 @@ def drange(dstart, dend, delta):
*dend* are :class:`datetime` instances. *delta* is a
:class:`datetime.timedelta` instance.
"""
f1 = _to_ordinalf(dstart)
f2 = _to_ordinalf(dend)
f1 = date2num(dstart)
f2 = date2num(dend)
step = delta.total_seconds() / SEC_PER_DAY

# calculate the difference between dend and dstart in times of delta
Expand All @@ -504,7 +530,7 @@ def drange(dstart, dend, delta):
dinterval_end -= delta
num -= 1

f2 = _to_ordinalf(dinterval_end) # new float-endpoint
f2 = date2num(dinterval_end) # new float-endpoint
return np.linspace(f1, f2, num + 1)

### date tickers and formatters ###
Expand Down Expand Up @@ -1630,5 +1656,6 @@ def default_units(x, axis):
return None


units.registry[np.datetime64] = DateConverter()
units.registry[datetime.date] = DateConverter()
units.registry[datetime.datetime] = DateConverter()
46 changes: 42 additions & 4 deletions lib/matplotlib/tests/test_dates.py
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Expand Up @@ -3,13 +3,14 @@

from six.moves import map

import datetime
import warnings
import tempfile
import pytest

import datetime
import dateutil
import numpy as np
import pytest
import pytz
import tempfile
import warnings

try:
# mock in python 3.3+
Expand All @@ -22,6 +23,43 @@
import matplotlib.dates as mdates


def test_date_numpyx():
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any reason this isn't done with base/time/timenp being pytest fixtures and the test parameterized or split into two?

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Because I can understand this, and I have no idea what a pytest fixture is. Is there an advantage to doing something more obscure than a simple assert?

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Only cause you're repeating yourself a lot so it's hard to tell what the specific tests are. Factoring out common features into a fixture means you can make two tests that are uniquely named for the things they're testing.

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I'll look into it. OTOH, I find some of the tests aren't very easy to follow. Sometime verbosity is a good thing!

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OK, happy to take suggestions, but I find the uses of fixtures in the existing tests makes for pretty obfuscated code.

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shrugs can agree on that somewhat, either way it's not something I'd hold the PR up on.

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Well, I didn't mean to say I wasn't willing to learn, just that I don't get it... More than happy if you wanted to push a change or give me some pseudo code to get it to work... Thanks!

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Sorry for missing your reply (the embedded ones seem to not pop up as notifications), and will totally try to remember your suggestion for the future. I should have been way clearer on what I wanted and given you an example. :/

# 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)
assert np. 67ED array_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)
assert np.array_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]'])
def test_date_date2num_numpy(t0, dtype):
time = mdates.date2num(t0)
tnp = np.array(t0, dtype=dtype)
nptime = mdates.date2num(tnp)
assert np.array_equal(time, nptime)


@image_comparison(baseline_images=['date_empty'], extensions=['png'])
def test_date_empty():
# make sure mpl does the right thing when told to plot dates even
Expand Down
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