/usr/lib/python3/dist-packages/pandas/tseries/tests/test_util.py is in python3-pandas 0.14.1-2.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | from pandas.compat import range
import nose
import numpy as np
from numpy.testing.decorators import slow
from pandas import Series, date_range
import pandas.util.testing as tm
from datetime import datetime, date
from pandas.tseries.tools import normalize_date
from pandas.tseries.util import pivot_annual, isleapyear
class TestPivotAnnual(tm.TestCase):
"""
New pandas of scikits.timeseries pivot_annual
"""
def test_daily(self):
rng = date_range('1/1/2000', '12/31/2004', freq='D')
ts = Series(np.random.randn(len(rng)), index=rng)
annual = pivot_annual(ts, 'D')
doy = ts.index.dayofyear
doy[(~isleapyear(ts.index.year)) & (doy >= 60)] += 1
for i in range(1, 367):
subset = ts[doy == i]
subset.index = [x.year for x in subset.index]
tm.assert_series_equal(annual[i].dropna(), subset)
# check leap days
leaps = ts[(ts.index.month == 2) & (ts.index.day == 29)]
day = leaps.index.dayofyear[0]
leaps.index = leaps.index.year
tm.assert_series_equal(annual[day].dropna(), leaps)
def test_hourly(self):
rng_hourly = date_range(
'1/1/1994', periods=(18 * 8760 + 4 * 24), freq='H')
data_hourly = np.random.randint(100, 350, rng_hourly.size)
ts_hourly = Series(data_hourly, index=rng_hourly)
grouped = ts_hourly.groupby(ts_hourly.index.year)
hoy = grouped.apply(lambda x: x.reset_index(drop=True))
hoy = hoy.index.droplevel(0).values
hoy[~isleapyear(ts_hourly.index.year) & (hoy >= 1416)] += 24
hoy += 1
annual = pivot_annual(ts_hourly)
ts_hourly = ts_hourly.astype(float)
for i in [1, 1416, 1417, 1418, 1439, 1440, 1441, 8784]:
subset = ts_hourly[hoy == i]
subset.index = [x.year for x in subset.index]
tm.assert_series_equal(annual[i].dropna(), subset)
leaps = ts_hourly[(ts_hourly.index.month == 2) &
(ts_hourly.index.day == 29) &
(ts_hourly.index.hour == 0)]
hour = leaps.index.dayofyear[0] * 24 - 23
leaps.index = leaps.index.year
tm.assert_series_equal(annual[hour].dropna(), leaps)
def test_weekly(self):
pass
def test_monthly(self):
rng = date_range('1/1/2000', '12/31/2004', freq='M')
ts = Series(np.random.randn(len(rng)), index=rng)
annual = pivot_annual(ts, 'M')
month = ts.index.month
for i in range(1, 13):
subset = ts[month == i]
subset.index = [x.year for x in subset.index]
tm.assert_series_equal(annual[i].dropna(), subset)
def test_period_monthly(self):
pass
def test_period_daily(self):
pass
def test_period_weekly(self):
pass
def test_normalize_date():
value = date(2012, 9, 7)
result = normalize_date(value)
assert(result == datetime(2012, 9, 7))
value = datetime(2012, 9, 7, 12)
result = normalize_date(value)
assert(result == datetime(2012, 9, 7))
if __name__ == '__main__':
nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],
exit=False)
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