why not using something like numpy.repeat?
In [18]: B = numpy.random.rand(4,3)
In [19]: A = numpy.repeat(B[:,:,numpy.newaxis],2,axis=2)
In [20]: B.shape
Out[20]: (4, 3)
In [21]: A.shape
Out[21]: (4, 3, 2)
In [22]: numpy.all(A[:,:,0] == A[:,:,1])
Out[22]: True
hth,
L.
2008/4/25, tournesol <tournesol33@gmail.com>:Hi All.
I just want to conver Fortran 77 source to
Python.
Here is my F77 source.
DIMENSION A(25,60,13),B(25,60,13)
open(15,file='data.dat')
DO 60 K=1,2
READ(15,1602) ((B(I,J),J=1,60),I=1,25)
60 CONTINUE
1602 FORMAT(15I4)
DO 63 K=1,10
DO 62 I=1,25
DO 62 J=1,60
A(I,J,K)=B(I,J)
62 CONTINUE
63 CONTINUE
END
Q1: Fortran-contiguous is ARRAY(row,colum,depth).
How about the Python-contiguous ? array(depth,row,colum) ?
Default is C-contiguous, but you can you Fortran contiguous arrays.
Q2: How can I insert 1D to a 2D array and make it to
3D array. ex:) B:25x60 ==> A: 10X25X60
I don't understand what you want to do, but broadcasting allows copying several instances of an array into another one.
Matthieu
--
French PhD student
Website : http://matthieu-brucher.developpez.com/
Blogs : http://matt.eifelle.com and http://blog.developpez.com/?blog=92
LinkedIn : http://www.linkedin.com/in/matthieubrucher
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