import numpy.matlib as M
x = M.asmatrix(['a', 'b', 'c'])
x == 'a'
array([[ True, False, False]], dtype=bool) # I expected a matrix
x = M.asmatrix([1, 2, 3])
x == 1
matrix([[ True, False, False]], dtype=bool) # This looks good
M.__version__
'1.0.5.dev4445'
On Wed, December 5, 2007 8:38 pm, Fernando Perez wrote:
...
And I see this message in the build:
In: mwrep.pyf:mwrep:unknown_interface:createblocks
_get_depend_dict: no dependence info for 'len'
This is due to a typo introduced in r4511 and is now fixed in
r4553. This bug should not affect
Fernando Perez wrote:
The whole scipy.org site seems down. Is it just on my end?
Works for me, though it seems pretty slow.
# Steve
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Fernando Perez wrote:
The whole scipy.org site seems down. Is it just on my end?
No. Our new IT guy, Ryan Earl jre at enthought.com, is on the case.
--
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
The whole scipy.org site seems down. Is it just on my end?
Cheers,
f
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Hi all,
I have a quick question on f2py. I have a fortran lib I've wrapped
for a while and was updating one routine today, when I noticed a
message I'm curious about. The .pyf file contains this signature:
subroutine
createblocks(nnod,ll,nscale,nterms,pp,qq,aoffset,iflag,rintphi,rnorm)
On Dec 5, 2007 1:05 PM, Pearu Peterson [EMAIL PROTECTED] wrote:
On Wed, December 5, 2007 8:38 pm, Fernando Perez wrote:
...
And I see this message in the build:
In: mwrep.pyf:mwrep:unknown_interface:createblocks
_get_depend_dict: no dependence info for 'len'
This is due to a typo
I would think that
multinomial(1,prob,size=ntrials).sum(axis=0)
would be equivalent to
multinomial(ntrials,prob)
but the first gives a surprising result. (See below.)
Explanation?
Thank you,
Alan Isaac
ntrials = 10
prob = N.arange(100,dtype=N.float32)/4950
Steven H. Rogers wrote:
Fernando Perez wrote:
The whole scipy.org site seems down. Is it just on my end?
Works for me, though it seems pretty slow.
The system has been restarted.
--
Robert Kern
I have come to believe that the whole world is an enigma, a harmless enigma
that is made
Alan G Isaac wrote:
I would think that
multinomial(1,prob,size=ntrials).sum(axis=0)
would be equivalent to
multinomial(ntrials,prob)
but the first gives a surprising result. (See below.)
Explanation?
A bug in rk_binomial_inversion(). Unfortunately, this looks like a logical bug
in
Alan G Isaac wrote:
I would think that
multinomial(1,prob,size=ntrials).sum(axis=0)
would be equivalent to
multinomial(ntrials,prob)
but the first gives a surprising result. (See below.)
Explanation?
Pretty much anyone who derives their binomial distribution algorithm from
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