[SciPy-user] how to get only complete years from series?

[Pierre GM]

Timmie,
There's smarter than the previous answer, if you're not afraid of  
temporary arrays. Here's a copy-pasted version, commented.
Let me know how it goes.
Cheers
P.

#### BELOW A SAMPLE SCRIPT THAT MAY ILLUSTRATE ####

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import datetime
import scikits.timeseries as ts

import numpy as np

#import numpy as np
import numpy.ma as ma
import scikits.timeseries as ts

data = np.arange(0, 40800)
start_dt = ts.Date(freq='H', year=2004, month=3, day=1, hour=0)
s_all = ts.time_series(data, freq='H', start_date=start_dt)


# Convert to a (5,24*366) annual series: each row is a year, each  
column an hour
# Because of lapse years, we have 24*366 cols, not 24*365
a_s_all = s_all.convert('A')
# If the first column (the first date) is masked, mask the row.
a_s_all[a_s_all[:,0].mask] = ma.masked
# If the column -25 (last hour of 12/31 or 12/30) is masked, masked  
the column
a_s_all[a_s_all[:,-25].mask] = ma.masked
# Make a new series from the annual series.
# We can't us convert because the annual series is 2D.
# Instead, we create a new series starting at the first date of the  
annual series,
# converted to the correct frequency (s_all.freq).
# As the method asfreq defaults to END, we need to force 'START' for  
relation
# (check the docstring of asfreq).
starting_date = a_s_all.dates[0].asfreq(s_all.freq, relation='START')
# For the data, we can't use a_s_all.ravel() directly because a_s_all  
is 2D,
# but we only need the data actually, not the dates.
s_new = ts.time_series(a_s_all._series.ravel(),  
start_date=starting_date)
# And if you want, you can force the starting and ending dates of this  
new series
# to the initial ones
s_mod = ts.align_with(s_all, s_new)






On Nov 17, 2008, at 3:34 PM, Timmie wrote:

> Hello,
> I am unsing the scikit.timeseries to evaluate a long-term  
> measurement data set.
>
> How can I extract those years, which have complete measurements?
>
> In the below, years 2004 & 2008 are not complete.
> Is there a generic possibility that all incomplete years get masked?
>
> Thanks & regards,
> Timmie
>
> ###code
>
> import numpy as np
> import numpy.ma as ma
> import scikits.timeseries as ts
>
> data = np.arange(0, 40800)
> start_dt = ts.Date(freq='H', year=2004, month=3, day=1, hour=0)
> s_all = ts.time_series(data, freq='H', start_date=start_dt)
>
>
>
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