ma.masked_array is a constructor function for ma.MaskedArray, like np.array is a constructor for np.ndarray. Its intended use is: a = ma.masked_array(yourdata, mask=yourmask, dtype=yourdtype) to which you can add the keyword arguments presented in the doc.
ma.masked is a special constant used to check whether one particular value of your array is masked, or to mask one particular value. Note that setting a value of an array `x` to `ma.masked` will only work if `x` is a MaskedArray, otherwise the value will be set to zero (if the array is not a MaskedArray or a child of, there's no mask to modify...)
On Nov 18, 2008, at 12:39 AM, Scott Sinclair wrote:
2008/11/17 Timmie firstname.lastname@example.org:
I am using this expression along with the scikit.timeseries:
=> but now, my series does not get masked.
??? Please provide a self-contained example, so that I can check whether it's a bug or not. On my machine, the following works:
import numpy as np, numpy.ma as ma, scikits.timeseries as ts series = ts.time_series(np.random.rand(10),
timeseries([ 0.79956673 0.26526638 0.38811214 0.2119525 0.55870333 0.73263595 0.24395387 0.35595176 0.86357901 0.48562605], dates = [2000 ... 2009], freq = A-DEC)
Now, let's mask the values after 2005 (included)
series[series.years>2004] = ma.masked series
timeseries([0.799566726537 0.265266376704 0.388112137692 0.211952497171 0.558703334124 -- -- -- -- --], dates = [2000 ... 2009], freq = A-DEC)
There's some in progress documentation in the Numpy doc app at http://docs.scipy.org/numpy/docs/numpy.ma.core.masked_where/ that hasn't yet made it's way to the reference manual http://docs.scipy.org/doc/numpy/reference/
I know I'm a tad lagging here documentation-wise... Any help welcome.