[Numpy-discussion] Unexpected conversion from matrix to array
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' ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] A quick f2py question
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 resulting extension module. Thanks for the issue report, Pearu ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] site down...
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 ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] site down...
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 interpret it as though it had an underlying truth. -- Umberto Eco ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] site down...
The whole scipy.org site seems down. Is it just on my end? Cheers, f ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] A quick f2py question
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) ! in :mwrep:createblocks.f integer intent(in) :: nnod integer intent(in) :: ll integer intent(in) :: nscale integer intent(hide),depend(pp) :: nterms = len(pp) real*8 dimension(nterms),intent(in) :: pp real*8 dimension(nterms),intent(in) :: qq real*8 dimension(nterms),intent(in) :: aoffset integer intent(in) :: iflag real*8 dimension(nterms*nnod*nnod),intent(out),depend(nterms,nnod) :: rintphi real*8 dimension(nterms),intent(out),depend(nterms):: rnorm end subroutine createblocks And I see this message in the build: In: mwrep.pyf:mwrep:unknown_interface:createblocks _get_depend_dict: no dependence info for 'len' The build does actually continue, and in the end, this routine seems to be correctly wrapped. But I still worry that it may be getting the right allocations by chance/accident. Is this a real error message, or just an internal warning from an intermediate pass? Or has the call for len() changed recently in f2py? (this code was originally wrapped years ago, now I'm just doing minor updates). Thanks for any info... Cheers, f ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] A quick f2py question
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 introduced in r4511 and is now fixed in r4553. This bug should not affect resulting extension module. Thanks for the issue report, Great, many thanks for the clarification and quick action. Cheers, f ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] multinomial question
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 multinomial(1,prob,size=ntrials).sum(axis=0) array([ 0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0, 990, 1058, 996, 1102, 1088, 1137, 1144, 1150, 1196, 1198, 1272, 1273, 1268, 1265, 1380, 1336, 1371, 1405, 1348, 1420, 1515, 1506, 1571, 1499, 1556, 1517, 1603, 1691, 1696, 1763, 1622, 1716, 1722, 1785, 1866, 1799, 1918, 1818, 1868, 1938, 2010, 1916, 1950, 1983, 2062, 2079, 2224, 2165, 2136, 2156, 2215, 2118, 2309, 2389, 2377, 2423, 2328, 2325, 2469]) multinomial(ntrials,prob) array([ 0, 27, 33, 55, 104, 104, 116, 153, 166, 181, 189, 199, 244, 262, 259, 303, 330, 343, 373, 360, 371, 437, 423, 470, 460, 550, 551, 497, 517, 593, 623, 623, 648, 660, 638, 718, 713, 754, 784, 831, 804, 868, 902, 851, 918, 932, 945, 972, 966, 1025, 1005, 1038, 1075, 1046, 1121, 1069, 1121, 1152, 1209, 1148, 1196, 1261, 1288, 1304, 1250, 1324, 1348, 1430, 1370, 1419, 1388, 1364, 1473, 1414, 1511, 1523, 1583, 1574, 1575, 1575, 1613, 1559, 1665, 1666, 1712, 1728, 1715, 1709, 1846, 1774, 1819, 1869, 1886, 1963, 1837, 1906, 1983, 1867, 1968, 1916]) ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] site down...
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 terrible by our own mad attempt to interpret it as though it had an underlying truth. -- Umberto Eco ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] multinomial question
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 the sources I was deriving this code from. The safety bound on the search inversion search cuts out too early. Now that I re-examine it, it looks the bound (whichever of the multiple choice of bounds one could use) could always be legitimately exceeded, so there shouldn't be a bound at all. I'll have to dive deeper to figure out what is going on. This makes me grumpy. -- 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 interpret it as though it had an underlying truth. -- Umberto Eco ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] multinomial question
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 http://www.unc.edu/~gfish/fcmc.html is also wrong. SVN now has a bound such that CDF(bound) is within 1e-16 (or so) of 1.0. -- 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 interpret it as though it had an underlying truth. -- Umberto Eco ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
