def test_date(self):
def test_dt(datestr, dt_ref):
def myassert(x):
if np.isnan(dt_ref):
self.assertTrue(np.isnan(getDt(x)))
else:
self.assertEqual(getDt(x), dt_ref)
# Type: Numpy array - Elements: datetime64
if isinstance(datestr[0], int):
x = np.array(datestr, dtype='datetime64[s]')
myassert(x)
x = np.array(datestr)
myassert(x)
elif isinstance(datestr[0], float):
x = np.array(datestr)
myassert(x)
else:
x = np.array(datestr, dtype='datetime64')
myassert(x)
# Type: Pandas DatetimeIndex - Elements: TimeSamp
df = pd.DataFrame(data=datestr)
x = pd.to_datetime(df.iloc[:, 0].values)
myassert(x)
# Type: Numpy array - Elements: datetime.datetime
df = pd.DataFrame(data=datestr)
x = pd.to_datetime(df.iloc[:, 0].values).to_pydatetime()
myassert(x)
test_dt(['2008-01-01', '2009-01-01'], 24 * 366 * 3600)
# year
test_dt(['2008-01-01', '2008-02-01'], 24 * 3600 * 31)
#month
test_dt(['2000-10-15 01:00:00', '2000-10-15 02:00:00'], 3600)
# hour
test_dt(['2000-10-15 00:00:05.000001', '2000-10-15 00:00:05.000002'],
0.000001)
#mu s
test_dt([np.datetime64('NaT'), '2000-10-15 00:00:05.000001'], np.nan)
test_dt([
np.datetime64('NaT'), '2000-10-15 00:00:05.000001',
'2000-10-15 00:00:05.000002'
], 0.000001)
test_dt([0], np.nan)
test_dt([0.0], np.nan)
# test_dt([0,1],1) # TODO
# test_dt([0.0,1.0],1.0) # TODO
self.assertEqual(getDt([0.0, 0.1]), 0.1)
self.assertEqual(getDt(np.array([0.0, 0.1])), 0.1)
self.assertEqual(getDt([0, 1]), 1)
self.assertEqual(getDt(np.array([0, 1])), 1)
def myassert(x):
if np.isnan(dt_ref):
self.assertTrue(np.isnan(getDt(x)))
else:
self.assertEqual(getDt(x), dt_ref)
