Hello, the docstring for compress in numpy give this help(numpy.compress) compress(condition, m, axis=None, out=None) compress(condition, x, axis=None) = those elements of x corresponding to those elements of condition that are "true". condition must be the same size as the given dimension of x. So (but perhaps I can misundertand the help due to my english) I don't undersand the following error, for me a and c array does have the same dimension and size. So someone can explain me the result please? Thanks, N. In [86]: a = numpy.arange(9) In [87]: a = numpy.arange(9).reshape(3,3) In [88]: c = numpy.ones(9).reshape(3,3) In [89]: numpy.compress(c,a)  exceptions.ValueError Traceback (most recent call last) /home/gruel/tmp/Astro/FATBOY/<ipython console> /home/gruel/usr/lib/python2.4/sitepackages/numpy/core/fromnumeric.py in compress(condition, m, axis, out) 353 except AttributeError: 354 return _wrapit(m, 'compress', condition, axis, out) > 355 return compress(condition, axis, out) 356 357 def clip(m, m_min, m_max): ValueError: condition must be 1d array  Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with preintegrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.asus.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642
humufr@yahoo.fr wrote:
Hello,
the docstring for compress in numpy give this
help(numpy.compress)
compress(condition, m, axis=None, out=None) compress(condition, x, axis=None) = those elements of x corresponding to those elements of condition that are "true". condition must be the same size as the given dimension of x.
So (but perhaps I can misundertand the help due to my english) I don't undersand the following error, for me a and c array does have the same dimension and size. So someone can explain me the result please?
The docstring is a bit underspecified. The condition array *must* be a 1D array with the same size *as the given axis* of the other array (using the convention that axis=None implies operating over the flattened array). There's simply no valid interpretation of this, for example: compress(array([[1, 0, 0], [1, 1, 0]]), arange(6).reshape(2,3)) since numpy arrays cannot be "ragged".  Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth."  Umberto Eco  Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with preintegrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.asus.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642
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humufr＠yahoo.fr

Robert Kern