On 6/20/2015 9:20 PM, MRAB wrote:
Here's one way, one step at a time:
r1 = np.concatenate([v1, v2])
r1
array([1, 2, 3, 4, 5, 6])
r2 = np.concatenate([v3, v4])
r2
array([ 7, 8, 9, 10, 11, 12])
m = np.array([r1, r2])
m
array([[ 1, 2, 3, 4, 5, 6],
[ 7, 8, 9, 10, 11, 12]])
m.transpose()
array([[ 1, 7],
[ 2, 8],
[ 3, 9],
[ 4, 10],
[ 5, 11],
[ 6, 12]])
But your output is wrong.
I did manage to find a way:
---------------------------------
r1 =np.hstack([(v1,v2)]).T
r2 =np.hstack([(v3,v4)]).T
mat = np.vstack((r1,r2))
-----------------------------
Out[211]:
array([[ 1, 4],
[ 2, 5],
[ 3, 6],
[ 7, 10],
[ 8, 11],
[ 9, 12]])
But it is not as intuitive as with Matlab, where one can just write
-------------------------------
v1=[1,2,3]'; v2=[4,5,6]';
v3=[7,8,9]'; v4=[10,11,12]';
m=[v1 v2;v3 v4]
-------------------------------
--Nasser
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