On Wed, Feb 11, 2015 at 4:18 PM, Ryan Nelson <rnelsonc...@gmail.com> wrote: > Colin, > > I currently use Py3.4 and Numpy 1.9.1. However, I built a quick test conda > environment with Python2.7 and Numpy 1.7.0, and I get the same: > > ############ > Python 2.7.9 |Continuum Analytics, Inc.| (default, Dec 18 2014, 16:57:52) > [MSC v > .1500 64 bit (AMD64)] > Type "copyright", "credits" or "license" for more information. > > IPython 2.3.1 -- An enhanced Interactive Python. > Anaconda is brought to you by Continuum Analytics. > Please check out: http://continuum.io/thanks and https://binstar.org > ? -> Introduction and overview of IPython's features. > %quickref -> Quick reference. > help -> Python's own help system. > object? -> Details about 'object', use 'object??' for extra details. > > In [1]: import numpy as np > > In [2]: np.__version__ > Out[2]: '1.7.0' > > In [3]: np.mat([4,'5',6]) > Out[3]: > matrix([['4', '5', '6']], > dtype='|S1') > > In [4]: np.mat([4,'5',6], dtype=int) > Out[4]: matrix([[4, 5, 6]]) > ############### > > As to your comment about coordinating with Statsmodels, you should see the > links in the thread that Alan posted: > http://permalink.gmane.org/gmane.comp.python.numeric.general/56516 > http://permalink.gmane.org/gmane.comp.python.numeric.general/56517 > Josef's comments at the time seem to echo the issues the devs (and others) > have with the matrix class. Maybe things have changed with Statsmodels.
Not changed, we have a strict policy against using np.matrix. generic efficient versions for linear operators, kronecker or sparse block matrix styly operations would be useful, but I would use array semantics, similar to using dot or linalg functions on ndarrays. Josef (long reply canceled because I'm writing too much that might only be of tangential interest or has been in some of the matrix discussion before.) > > I know I mentioned Sage and SageMathCloud before. I'll just point out that > there are folks that use this for real research problems, not just as a > pedagogical tool. They have a Matrix/vector/column_matrix class that do what > you were expecting from your problems posted above. Indeed below is a > (truncated) cut and past from a Sage Worksheet. (See > http://www.sagemath.org/doc/tutorial/tour_linalg.html) > ########## > In : Matrix([1,'2',3]) > Error in lines 1-1 > Traceback (most recent call last): > TypeError: unable to find a common ring for all elements > > In : Matrix([[1,2,3],[4,5]]) > ValueError: List of rows is not valid (rows are wrong types or lengths) > > In : vector([1,2,3]) > (1, 2, 3) > > In : column_matrix([1,2,3]) > [1] > [2] > [3] > ########## > > Large portions of the custom code and wrappers in Sage are written in > Python. I don't think their Matrix object is a subclass of ndarray, so > perhaps you could strip out the Matrix stuff from here to make a separate > project with just the Matrix stuff, if you don't want to go through the Sage > interface. > > > On Wed, Feb 11, 2015 at 11:54 AM, cjw <c...@ncf.ca> wrote: >> >> >> On 11-Feb-15 10:21 AM, Ryan Nelson wrote: >> >> So: >> >> In [2]: np.mat([4,'5',6]) >> Out[2]: >> matrix([['4', '5', '6']], dtype='<U11') >> >> In [3]: np.mat([4,'5',6], dtype=int) >> Out[3]: matrix([[4, 5, 6]]) >> >> Thanks Ryan, >> >> We are not singing from the same hymn book. >> >> Using PyScripter, I get: >> >> *** Python 2.7.9 (default, Dec 10 2014, 12:28:03) [MSC v.1500 64 bit >> (AMD64)] on win32. *** >> >>> import numpy as np >> >>> print('Numpy version: ', np.__version__) >> ('Numpy version: ', '1.9.0') >> >>> >> >> Could you say which version you are using please? >> >> Colin W >> >> On Tue, Feb 10, 2015 at 5:07 PM, cjw <c...@ncf.ca> wrote: >> >> It seems to be agreed that there are weaknesses in the existing Numpy >> Matrix >> Class. >> >> Some problems are illustrated below. >> >> I'll try to put some suggestions over the coming weeks and would >> appreciate >> comments. >> >> Colin W. >> >> Test Script: >> >> if __name__ == '__main__': >> a= mat([4, 5, 6]) # Good >> print('a: ', a) >> b= mat([4, '5', 6]) # Not the expected result >> print('b: ', b) >> c= mat([[4, 5, 6], [7, 8]]) # Wrongly accepted as rectangular >> print('c: ', c) >> d= mat([[1, 2, 3]]) >> try: >> d[0, 1]= 'b' # Correctly flagged, not numeric >> except ValueError: >> print("d[0, 1]= 'b' # Correctly flagged, not numeric", >> ' >> ValueError') >> print('d: ', d) >> >> Result: >> >> *** Python 2.7.9 (default, Dec 10 2014, 12:28:03) [MSC v.1500 64 bit >> (AMD64)] on win32. *** >> >> a: [[4 5 6]] >> b: [['4' '5' '6']] >> c: [[[4, 5, 6] [7, 8]]] >> d[0, 1]= 'b' # Correctly flagged, not numeric ValueError >> d: [[1 2 3]] >> >> >> >> -- >> View this message in context: >> http://numpy-discussion.10968.n7.nabble.com/Matrix-Class-tp39719.html >> Sent from the Numpy-discussion mailing list archive at Nabble.com. >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
