Let's say I have this array x:
x = array([1, 2, 3, 4, 5, 6, 7, 8])
x.shape = (8,1)
I want to reshape it to become
array([[1, 3, 5, 7],
[2, 4, 6, 8]])
this is a reshape(2, 4) on x but in the straight forward way:
y = x.reshape(2,4)
y becomes
array([[1, 2, 3, 4],
[5, 6, 7, 8]])
and that's not what I want. Is there a way to transform the array in that specific way?
In[4]: x.reshape(4, 2).T
Out[4]:
array([[1, 3, 5, 7],
[2, 4, 6, 8]])
The easiest way to do this is to specify the orderargument in reshape function.
You need the Fortran order.
Side note: Matlab by default is using Fortran order but in python you need to specify that.
Use this:
x = np.array([1, 2, 3, 4, 5, 6, 7, 8])
y = x.reshape(2,4, order='F')
print(y)
#array([[1, 3, 5, 7],
# [2, 4, 6, 8]])
Another option is to use the option order='F' to your reshape-call like
res = numpy.reshape(my_array, (2,4), order='F')
https://docs.scipy.org/doc/numpy-1.15.1/reference/generated/numpy.reshape.html
Yes, you can do:
y = np.array([x[0::2], x[1::2]])
