Re: [Numpy-discussion] [SciPy-dev] SciPy Sprint results
Hi Travis On Thu, Dec 20, 2007 at 05:24:44PM -0600, Travis E. Oliphant wrote: * bool(x) raises a ValueError, as it does for ndarrays. What does bool(x) raise for numpy.core.ma. It now behaves the same way as numpy does, raising a ValueError: In [1]: bool(N.ma.array([0,1])) --- ValueErrorTraceback (most recent call last) /home/stefan/work/scipy/ipython console in module() ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() In [2]: bool(N.array([0,1])) --- ValueErrorTraceback (most recent call last) /home/stefan/work/scipy/ipython console in module() ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() Regards Stéfan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [SciPy-dev] SciPy Sprint results
On Fri, Dec 21, 2007 at 10:43:28AM +0200, Stefan van der Walt wrote: On Thu, Dec 20, 2007 at 05:24:44PM -0600, Travis E. Oliphant wrote: * bool(x) raises a ValueError, as it does for ndarrays. What does bool(x) raise for numpy.core.ma. Sorry, I realise you were talking about the old numpy.core.ma: z = N.core.ma.masked_array([True,False,True]) bool(z) == True Regards Stéfan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [SciPy-dev] SciPy Sprint results
On Thu, Dec 20, 2007 at 06:52:38PM -0500, Pierre GM wrote: If we can document exactly what the compatibility issues are (and it looks like we are almost there), we should move forward. OK, I'll take care of that this week-end. Stefan, feel free to beat me to it... A first draft is here: http://svn.scipy.org/svn/numpy/branches/maskedarray/numpy/ma/API_CHANGES.txt Regards Stéfan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [SciPy-dev] SciPy Sprint results
Stefan, I think the description of the putmask difference is missing the point. The real difference is not in the way the third argument is handled, or its required shape, but in whether the mask is updated or not. numpy.ma.putmask updates the mask; that is, if it puts something into the array in a formerly masked location, the mask at that location is changed to False. maskedarray.putmask does *not* update the original mask; it does a ndarray putmask operation on only the *unmasked* values. In [18]:import maskedarray as ma In [19]:mask1 = [False, True, False] In [21]:x = ma.array([1,2,3], mask=mask1) In [22]:mask2 = [False, True, True] In [23]:ma.putmask(x, mask2, 10) In [24]:x Out[24]: masked_array(data = [1 -- 10], mask = [False True False], fill_value=99) In [25]:x = numpy.ma.array([1,2,3], mask=mask1) In [26]:numpy.ma.putmask(x, mask2, 10) In [27]:x Out[27]: array(data = [ 1 10 10], mask = [False False False], fill_value=99) This is a fundamental difference. The maskedarray (new) behavior perhaps is more consistent with the general pattern of differences between masked and unmasked array functions and methods. Eric Stefan van der Walt wrote: On Thu, Dec 20, 2007 at 06:52:38PM -0500, Pierre GM wrote: If we can document exactly what the compatibility issues are (and it looks like we are almost there), we should move forward. OK, I'll take care of that this week-end. Stefan, feel free to beat me to it... A first draft is here: http://svn.scipy.org/svn/numpy/branches/maskedarray/numpy/ma/API_CHANGES.txt Regards Stéfan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [SciPy-dev] SciPy Sprint results
Stefan van der Walt wrote: Hi Travis, During the sprint I also merged Pierre's MaskedArray code into the maskedarray branch. That is nearly done, with only a few unit tests still failing -- ones brought over from the old numpy.ma. This is mainly due to some changes in the API, for example put and putmask now behave like their ndarray counterparts. Pierre, would you remind us of any other such changes, and why they were made? What is the road forward with this code? We will probably only merge API changes into 1.4. Do we use svnmerge to keep the branch up to date until then? I'd like to move forward with it sooner (for 1.0.5) if the API changes are not drastic. Although ideally 0 API changes would be desireable, I'm not sure if that is feasible. Are put and putmask the only changes in the API. What are the rest of them? -Travis ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [SciPy-dev] SciPy Sprint results
Pierre GM wrote: All, I'd like to move forward with it sooner (for 1.0.5) if the API changes are not drastic. Although ideally 0 API changes would be desireable, I'm not sure if that is feasible. Are put and putmask the only changes in the API. What are the rest of them? These do not seem too bad. * put, putmask, take should behave like the numpy equivalent. This does not sound like a problem. Am I missing something? * fill_value is now a property, not a method. I can see this is a good choice, but it is a backward compatibility issue that we should document. * cumsum(cumprod) works as if the _data array was filled with 0 (1). The mask is preserved, but not updated. (the output of numpy.core.ma has nomask). I don't understand what you mean here.So, the mask effectively removes those elements from the sum(product) computation? What does it mean that the mask is not updated? * bool(x) raises a ValueError, as it does for ndarrays. What does bool(x) raise for numpy.core.ma. If we can document exactly what the compatibility issues are (and it looks like we are almost there), we should move forward. -Travis ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [SciPy-dev] SciPy Sprint results
* cumsum(cumprod) works as if the _data array was filled with 0 (1). The mask is preserved, but not updated. (the output of numpy.core.ma has nomask). I don't understand what you mean here.So, the mask effectively removes those elements from the sum(product) computation? What does it mean that the mask is not updated? Quick example: x= masked_array([1,2,3],mask=[0,1,0]) x masked_array(data = [1 -- 3], mask = [False True False], fill_value=99) x.cumsum() masked_array(data = [1 -- 4], mask = [False True False], fill_value=99) So, cumsum works as if the masked values were 0. The mask stays the same as it was initially (that's what I meant by mask not updated). An alternative would be to set the mask to True for all the values past the first masked: with our example, we would have: masked_array(data = [1 -- --], mask = [False True True], fill_value=99) I prefer the first version (the one that is currently implemented). * bool(x) raises a ValueError, as it does for ndarrays. What does bool(x) raise for numpy.core.ma. True If we can document exactly what the compatibility issues are (and it looks like we are almost there), we should move forward. OK, I'll take care of that this week-end. Stefan, feel free to beat me to it... ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
