I had a quick look at the code
(https://github.com/numpy/numpy/blob/master/numpy/linalg/linalg.py) and
the numpy.linalg.svd function calls lapack_lite.dgesdd (for real
matrices) so I guess the non-convergence occurs in this function. As I
understood lapack_lite is used by default unless numpy
Chuck wrote:
Fails here also, fedora 15 64 bits AMD 940. There should be a maximum
iterations argument somewhere...
Chuck
---
*** Here's the FIX:
Chuck is right. There is a max iterations. Here is a
Try the fromiter function, that will allow you to pass an iterator
which can read the file line by line and not preload the whole file.
file_iterator = iter(open('filename.txt')
line_parser = lambda x: map(float,x.split('\t'))
a=np.fromiter(itertools.imap(line_parser,file_iterator),dtype=float)
On Sat, Aug 13, 2011 at 8:06 PM, Mark Wiebe mwwi...@gmail.com wrote:
Looks like this is the second-oldest open bug in the bug tracker.
http://projects.scipy.org/numpy/ticket/236
For what it's worth, I'm in favour of changing this behavior to be more
consistent as proposed in that ticket.
I'm translating some code from Matlab to numpy, and struggling a bit
since I have very little knowledge of Matlab.
My question is this - the arg function in Matlab (which seems to be deprecated,
they don't show it in their current documentation) is exactly equivalent to
what in Numpy? I know it
Le dimanche 14 août 2011 à 12:43 -0500, a...@ajackson.org a écrit :
I'm translating some code from Matlab to numpy, and struggling a bit
since I have very little knowledge of Matlab.
My question is this - the arg function in Matlab (which seems to be
deprecated,
they don't show it in their
Never mind, I've been digging through too much stuff and got confused...
I think trying to read Matlab code can do that to you. 8-)
I'm translating some code from Matlab to numpy, and struggling a bit
since I have very little knowledge of Matlab.
My question is this - the arg function in Matlab
Thanks very much Lou for the information. I tried delving into the C
code and found a line in the dlasd4_ routine which reads:
for (niter = iter; niter = MAXITERLOOPS; ++niter) {
This is apparently the main loop for this subroutine and the value of
MAXITERLOOPS = 100. All I did was increase
You can use scipy.stats.truncnorm, can't you? Unless I misread, you want
to sample a normal distribution but with generated values only being
within a specified range? However you also say you want to do this with
triangular and log normal and for these I presume the easiest way is to
sample
Hello,
I'm attempting to implement a subclass of ndarray, and becoming confused
about the way __array_wrap__ and __array_finalize__ operate. I boiled it
down to a short subclass, which is the example on the website at
http://docs.scipy.org/doc/numpy-1.6.0/user/basics.subclassing.html, with one
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