def test_backward_fill (self):
result = masked_array(self.data, mask=self.mask)
result[0] = 1
result[2] = 3
assert_equal(backward_fill(self.test_array, maxgap=1), result)
result[5] = 7
result[6] = 7
assert_equal(backward_fill(self.test_array), result)
def test_backward_fill(self):
result = masked_array(self.data, mask=self.mask)
result[0] = 1
result[2] = 3
assert_equal(backward_fill(self.test_array, maxgap=1), result)
result[5] = 7
result[6] = 7
assert_equal(backward_fill(self.test_array), result)
def _fix_cachedcurrent(self, ensoindices):
"""
Private function to convert cached ENSO indices.
This function is used to ensure that:
* the frequency of the indices matches the frequency of the indicator.
* the date range of the indices matches the date range of the indicator.
* the shape of the indices matches the shape of the indicator.
"""
_currentfreq = ensoindices._dates.freq
_freq = self._dates.freq
# Check the frequency, and convert if needed
if _currentfreq > _freq:
# To a lower frequency ('Q'/'A')
if self.ndim == 2:
conversionfunc = None
else:
conversionfunc = lambda x: mode(x)[0].squeeze()
ensoindices = ensoindices.convert(_freq, func=conversionfunc)
elif _currentfreq < _freq:
# To a higher frequency (eg, 'D')
ensoindices = backward_fill(ensoindices.convert(_freq))
# Reset to the original frequency if needed...
(start, end) = self._dates.flat[[0, -1]]
if tuple(ensoindices._dates.flat[[0, -1]]) != (start, end):
ensoindices = ts.adjust_endpoints(ensoindices, start_date=start, end_date=end)
# Reset the shape of the indices
if ensoindices.shape != self.shape:
ensoindices.shape = self.shape
return ensoindices
def set_ensoindicator(self, indicator):
if indicator is not None:
if not isinstance(indicator, ENSOIndicator):
raise TypeError("The input is not a valid ENSOIndicator ! " "(got '%s' instead)" % type(indicator))
# Reset the frequency
(sfreq, ifreq) = (self._dates.freq, indicator.freq)
if ifreq != sfreq:
if sfreq < ifreq:
indicator = indicator.convert(sfreq, func=ma.mean)
elif sfreq > ifreq:
indicator = backward_fill(indicator.convert(sfreq))
# Set the ENSO indices to the default (if we don't have any...)
if indicator._cachedcurrent is None:
indicator.set_indices()
# Reset the dates
dates = self._dates
if dates.isfull():
if len(dates) > 0:
(start, end) = dates.flat[[0, -1]]
if tuple(indicator._dates.flat[[0, -1]]) != (start, end):
indicator = ts.adjust_endpoints(indicator, start, end)
else:
indicator = None
else:
indicator = indicator[self._dates]
self._optinfo["ensoindicator"] = indicator
def _fix_cachedcurrent(self, ensoindices):
"""
Private function to convert cached ENSO indices.
This function is used to ensure that:
* the frequency of the indices matches the frequency of the indicator.
* the date range of the indices matches the date range of the indicator.
* the shape of the indices matches the shape of the indicator.
"""
_currentfreq = ensoindices._dates.freq
_freq = self._dates.freq
# Check the frequency, and convert if needed
if _currentfreq > _freq:
# To a lower frequency ('Q'/'A')
if self.ndim == 2:
conversionfunc = None
else:
conversionfunc = lambda x: mode(x)[0].squeeze()
ensoindices = ensoindices.convert(_freq, func=conversionfunc)
elif _currentfreq < _freq:
# To a higher frequency (eg, 'D')
ensoindices = backward_fill(ensoindices.convert(_freq))
# Reset to the original frequency if needed...
(start, end) = self._dates.flat[[0, -1]]
if tuple(ensoindices._dates.flat[[0, -1]]) != (start, end):
ensoindices = ts.adjust_endpoints(ensoindices,
start_date=start, end_date=end)
# Reset the shape of the indices
if ensoindices.shape != self.shape:
ensoindices.shape = self.shape
return ensoindices
def set_ensoindicator(self, indicator):
if indicator is not None:
if not isinstance(indicator, ENSOIndicator):
raise TypeError("The input is not a valid ENSOIndicator ! "\
"(got '%s' instead)" % type(indicator))
# Reset the frequency
(sfreq, ifreq) = (self._dates.freq, indicator.freq)
if ifreq != sfreq:
if sfreq < ifreq:
indicator = indicator.convert(sfreq, func=ma.mean)
elif sfreq > ifreq:
indicator = backward_fill(indicator.convert(sfreq))
# Set the ENSO indices to the default (if we don't have any...)
if indicator._cachedcurrent is None:
indicator.set_indices()
# Reset the dates
dates = self._dates
if dates.isfull():
if len(dates) > 0:
(start, end) = dates.flat[[0, -1]]
if tuple(indicator._dates.flat[[0, -1]]) != (start, end):
indicator = ts.adjust_endpoints(indicator, start, end)
else:
indicator = None
else:
indicator = indicator[self._dates]
self._optinfo['ensoindicator'] = indicator
ELECTRIC = time_series(masked_less(data[:, 0], 0), dates)
GAS = time_series(masked_less(data[:, 1], 0), dates)
WATER = time_series(masked_less(data[:, 2], 0), dates)
START = dates[0]
END = dates[-1]
CLIMATE = get_nm_climate(
start_date='%i%.2i%.2i' % (START.year, START.month, START.day),
end_date='%i%.2i%.2i' % (END.year, END.month, END.day))
CLIMATE.tofile('/tmp/test.txt')
MAX_TEMP, MIN_TEMP, ACCUM_PRECIP = CLIMATE.split()
FIG = tpl.tsfigure(figsize=(10, 7))
FIG.subplots_adjust(hspace=0.1)
GAS_PLOT = FIG.add_tsplot(313)
GAS_PLOT.tsplot(backward_fill(GAS), zorder=20)
GAS_PLOT.set_ylabel('Gas usage, therms')
GAS_PLOT.grid(linestyle='-', color='0.9', zorder=0)
TEMP_PLOT = GAS_PLOT.add_yaxis(position='right')
TEMP_PLOT.tsplot(MIN_TEMP, color='0.5', zorder=10)
TEMP_PLOT.tsplot(MAX_TEMP, color='0.5', zorder=10)
TEMP_PLOT.set_ylabel(u'Temperature range, \u2109F')
WATER_PLOT = FIG.add_tsplot(311, sharex=GAS_PLOT)
WATER_PLOT.tsplot(backward_fill(WATER * 748), zorder=20)
WATER_PLOT.grid(linestyle='-', color='0.9', zorder=1)
WATER_PLOT.set_xticklabels(WATER_PLOT.get_xticklabels(), visible=False)
WATER_PLOT.set_ylabel('Water usage, gal.')
WATER_PLOT.set_title('Utility usage for 1613 Columbia Dr. SE, ' \
'Albuquerque, NM\n' \
'Usage is given per billing period (~30 days).\n' \