[SciPy-user] iteratively masking timeseries
Tim Michelsen
timmichelsen at gmx-topmail.de
Thu Jun 12 17:14:03 EDT 2008
Hello,
I am making my way forward into timeseries processing with the scikit
package.
I have a timeseries where NoData values are masked when loading the data
into the timeseries.
Now I would like to apply some filters on the data like discarding data
values below measurement device accuracy or above a certain threshold.
Therefore I followed the appraoch outlined in the FAQ [1].
But then I get the pasted below at the end.
Does that mean that one can only mask an array once and cannot mask more
values later on?
I would like to do something like:
1) create timeseries with NoData values => already can do that
2) apply various filters masking more and more data.
a) e.g. get a series with masked values below 10.
b) e.g. get a series with masked values above 100.
I would appreciate any help or hint here.
Kind regards,
Tim
#### pasted from Ipython ####
In [18]: mask[mask<0] = numpy.ma.masked
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
D:\scripts\timeseries.py i
----> 1
2
3
4
5
C:\python25\lib\site-packages\scikits\timeseries\tseries.pyc in
__setitem__(se
522 if self is masked:
523 raise MAError, 'Cannot alter the masked element.'
--> 524 (sindx, _) = self.__checkindex(indx)
525 super(TimeSeries, self).__setitem__(sindx, value)
526 #......................................................
C:\python25\lib\site-packages\scikits\timeseries\tseries.pyc in
__checkindex(s
490 msg = "Masked arrays must be filled before they can
be use
491 "as indices!"
--> 492 raise IndexError, msg
493 return (indx,indx)
494
IndexError: Masked arrays must be filled before they can be used as indices!
#### end from Ipython ####
[1]
http://www.scipy.org/Cookbook/TimeSeries/FAQ#head-cfe3617dda0b030f0474a2a773e2dca4da8eaea0
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