Re: [Numpy-discussion] bug in numpy.where?
On 07/27/2012 03:58 PM, Andreas Mueller wrote: Hi Everybody. The bug is that no error is raised, right? The docs say where(condition, [x, y]) x, y : array_like, optional Values from which to choose. `x` and `y` need to have the same shape as `condition` In the example you gave, x was a scalar. net.max() returns an array: print type(net.max()) type 'numpy.float32' That was the reason I cast it to a float to check that that did result in the correct behavior for `where`. Phil ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in numpy.where?
On Mon, Jul 30, 2012 at 2:30 PM, Phil Hodge ho...@stsci.edu wrote: On 07/27/2012 03:58 PM, Andreas Mueller wrote: Hi Everybody. The bug is that no error is raised, right? The docs say where(condition, [x, y]) x, y : array_like, optional Values from which to choose. `x` and `y` need to have the same shape as `condition` In the example you gave, x was a scalar. net.max() returns an array: print type(net.max()) type 'numpy.float32' No, that's a scalar. The type would be numpy.ndarray if it were an array. -- Robert Kern ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in numpy.where?
Can you file a bug report on Github's issue tracker? Thanks, -Travis On Jul 26, 2012, at 1:33 PM, Phil Hodge wrote: On a Linux machine: uname -srvop Linux 2.6.18-308.8.2.el5 #1 SMP Tue May 29 11:54:17 EDT 2012 x86_64 GNU/Linux this example shows an apparent problem with the where function: Python 2.7.1 (r271:86832, Dec 21 2010, 11:19:43) [GCC 4.1.2 20080704 (Red Hat 4.1.2-48)] on linux2 Type help, copyright, credits or license for more information. import numpy as np print np.__version__ 1.5.1 net = np.zeros(3, dtype='f4') net[1] = 0.00458849 net[2] = 0.605202 max_net = net.max() test = np.where(net = 0., max_net, net) print test [ -2.23910537e-35 4.58848989e-03 6.05202019e-01] When I specified the dtype for net as 'f8', test[0] was 3.46244974e+68. It worked as expected (i.e. test[0] should be 0.605202) when I specified float(max_net) as the second argument to np.where. Phil ___ 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
Re: [Numpy-discussion] bug in numpy.where?
On 07/30/2012 10:53 AM, Travis Oliphant wrote: Can you file a bug report on Github's issue tracker? It's https://github.com/numpy/numpy/issues/369 Phil ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in numpy.where?
On Thu, Jul 26, 2012 at 2:33 PM, Phil Hodge ho...@stsci.edu wrote: On a Linux machine: uname -srvop Linux 2.6.18-308.8.2.el5 #1 SMP Tue May 29 11:54:17 EDT 2012 x86_64 GNU/Linux this example shows an apparent problem with the where function: Python 2.7.1 (r271:86832, Dec 21 2010, 11:19:43) [GCC 4.1.2 20080704 (Red Hat 4.1.2-48)] on linux2 Type help, copyright, credits or license for more information. import numpy as np print np.__version__ 1.5.1 net = np.zeros(3, dtype='f4') net[1] = 0.00458849 net[2] = 0.605202 max_net = net.max() test = np.where(net = 0., max_net, net) print test [ -2.23910537e-35 4.58848989e-03 6.05202019e-01] When I specified the dtype for net as 'f8', test[0] was 3.46244974e+68. It worked as expected (i.e. test[0] should be 0.605202) when I specified float(max_net) as the second argument to np.where. Phil Confirmed with version 1.7.0.dev-470c857 on a CentOS6 64-bit machine. Strange indeed. Breaking it down further: res = (net = 0.) print res [ True False False] np.where(res, max_net, net) array([ -2.23910537e-35, 4.58848989e-03, 6.05202019e-01], dtype=float32) Very Strange... Ben Root ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in numpy.where?
On Fri, Jul 27, 2012 at 2:01 PM, Benjamin Root ben.r...@ou.edu wrote: On Thu, Jul 26, 2012 at 2:33 PM, Phil Hodge ho...@stsci.edu wrote: On a Linux machine: uname -srvop Linux 2.6.18-308.8.2.el5 #1 SMP Tue May 29 11:54:17 EDT 2012 x86_64 GNU/Linux this example shows an apparent problem with the where function: Python 2.7.1 (r271:86832, Dec 21 2010, 11:19:43) [GCC 4.1.2 20080704 (Red Hat 4.1.2-48)] on linux2 Type help, copyright, credits or license for more information. import numpy as np print np.__version__ 1.5.1 net = np.zeros(3, dtype='f4') net[1] = 0.00458849 net[2] = 0.605202 max_net = net.max() test = np.where(net = 0., max_net, net) print test [ -2.23910537e-35 4.58848989e-03 6.05202019e-01] When I specified the dtype for net as 'f8', test[0] was 3.46244974e+68. It worked as expected (i.e. test[0] should be 0.605202) when I specified float(max_net) as the second argument to np.where. Phil Confirmed with version 1.7.0.dev-470c857 on a CentOS6 64-bit machine. Strange indeed. Breaking it down further: res = (net = 0.) print res [ True False False] np.where(res, max_net, net) array([ -2.23910537e-35, 4.58848989e-03, 6.05202019e-01], dtype=float32) Very Strange... Ben Root What if find really interesting is that -2.23910537e-35 is the byte swapped version of 6.05202019e-01. Chris ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in numpy.where?
Hi Everybody. The bug is that no error is raised, right? The docs say where(condition, [x, y]) x, y : array_like, optional Values from which to choose. `x` and `y` need to have the same shape as `condition` In the example you gave, x was a scalar. Cheers, Andy ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in numpy.where?
On Fri, Jul 27, 2012 at 3:58 PM, Andreas Mueller amuel...@ais.uni-bonn.dewrote: Hi Everybody. The bug is that no error is raised, right? The docs say where(condition, [x, y]) x, y : array_like, optional Values from which to choose. `x` and `y` need to have the same shape as `condition` In the example you gave, x was a scalar. Cheers, Andy Hmm, that is incorrect, I believe. I have used a scalar before. Maybe it works because a scalar is broadcastable to the same shape as any other N-dim array? If so, then the wording of that docstring needs to be fixed. No, I think Christopher hit it on the head. For whatever reason, the endian-ness somewhere is not being respected and causes a byte-swapped version to show up. How that happens, though, is beyond me. Ben Root ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in numpy.where?
On 07/27/2012 09:10 PM, Benjamin Root wrote: On Fri, Jul 27, 2012 at 3:58 PM, Andreas Mueller amuel...@ais.uni-bonn.de mailto:amuel...@ais.uni-bonn.de wrote: Hi Everybody. The bug is that no error is raised, right? The docs say where(condition, [x, y]) x, y : array_like, optional Values from which to choose. `x` and `y` need to have the same shape as `condition` In the example you gave, x was a scalar. Cheers, Andy Hmm, that is incorrect, I believe. I have used a scalar before. Maybe it works because a scalar is broadcastable to the same shape as any other N-dim array? If so, then the wording of that docstring needs to be fixed. No, I think Christopher hit it on the head. For whatever reason, the endian-ness somewhere is not being respected and causes a byte-swapped version to show up. How that happens, though, is beyond me. Well, if you use np.repeat(max_net, 3) instead of max_net, it works as expected. So if you use the function as documented, it does the right thing. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in numpy.where?
On Fri, Jul 27, 2012 at 4:10 PM, Benjamin Root ben.r...@ou.edu wrote: On Fri, Jul 27, 2012 at 3:58 PM, Andreas Mueller amuel...@ais.uni-bonn.de wrote: Hi Everybody. The bug is that no error is raised, right? The docs say where(condition, [x, y]) x, y : array_like, optional Values from which to choose. `x` and `y` need to have the same shape as `condition` In the example you gave, x was a scalar. Cheers, Andy Hmm, that is incorrect, I believe. I have used a scalar before. Maybe it works because a scalar is broadcastable to the same shape as any other N-dim array? If so, then the wording of that docstring needs to be fixed. No, I think Christopher hit it on the head. For whatever reason, the endian-ness somewhere is not being respected and causes a byte-swapped version to show up. How that happens, though, is beyond me. Ben Root It may have something to do with the dtype size as well. The problem seen with, net = np.zeros(3, dtype='f4') Disappears for net = np.zeros(3, dtype='f8') and above. Chris ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
