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Convert NaT to nan in date2num #10631

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Merged
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Mar 1, 2018
Merged

Convert NaT to nan in date2num #10631

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7 changes: 7 additions & 0 deletions lib/matplotlib/dates.py
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Original file line number Diff line number Diff line change
Expand Up @@ -291,6 +291,13 @@ def _dt64_to_ordinalf(d):
dt += extra.astype(np.float64) / 1.0e9
dt = dt / SEC_PER_DAY + 1.0

NaT_int = np.datetime64('NaT').astype(np.int64)
d_int = d.astype(np.int64)
try:
dt[d_int == NaT_int] = np.nan
except TypeError:
if d_int == NaT_int:
dt = np.nan
return dt


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21 changes: 20 additions & 1 deletion lib/matplotlib/tests/test_dates.py
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Expand Up @@ -51,14 +51,33 @@ def test_date_numpyx():
datetime.datetime(2017, 1, 1, 3, 1, 1)]]])
@pytest.mark.parametrize('dtype', ['datetime64[s]',
'datetime64[us]',
'datetime64[ms]'])
'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)
assert np.array_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(baseline_images=['date_empty'], extensions=['png'])
def test_date_empty():
# make sure mpl does the right thing when told to plot dates even
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