How to multiply numpy 2D array with numpy 1D array?
Question:
The two arrays:
a = numpy.array([[2,3,2],[5,6,1]])
b = numpy.array([3,5])
c = a * b
What I want is:
c = [[6,9,6],
[25,30,5]]
But, I am getting this error:
ValueError: operands could not be broadcast together with shapes (2,3) (2)
How to multiply a nD array with 1D array, where len(1D-array) == len(nD array)
?
Answers:
You need to convert array b to a (2, 1) shape array, use None or numpy.newaxis
in the index tuple:
import numpy
a = numpy.array([[2,3,2],[5,6,1]])
b = numpy.array([3,5])
c = a * b[:, None]
Here is the document.
Another strategy is to reshape the
second array, so it has the same number of dimensions as the first array:
c = a * b.reshape((b.size, 1))
print(c)
# [[ 6 9 6]
# [25 30 5]]
Alternatively, the shape attribute of the second array can be modified in-place:
b.shape = (b.size, 1)
print(a.shape) # (2, 3)
print(b.shape) # (2, 1)
print(a * b)
# [[ 6 9 6]
# [25 30 5]]
The two arrays:
a = numpy.array([[2,3,2],[5,6,1]])
b = numpy.array([3,5])
c = a * b
What I want is:
c = [[6,9,6],
[25,30,5]]
But, I am getting this error:
ValueError: operands could not be broadcast together with shapes (2,3) (2)
How to multiply a nD array with 1D array, where len(1D-array) == len(nD array)
?
You need to convert array b to a (2, 1) shape array, use None or numpy.newaxis
in the index tuple:
import numpy
a = numpy.array([[2,3,2],[5,6,1]])
b = numpy.array([3,5])
c = a * b[:, None]
Here is the document.
Another strategy is to reshape the
second array, so it has the same number of dimensions as the first array:
c = a * b.reshape((b.size, 1))
print(c)
# [[ 6 9 6]
# [25 30 5]]
Alternatively, the shape attribute of the second array can be modified in-place:
b.shape = (b.size, 1)
print(a.shape) # (2, 3)
print(b.shape) # (2, 1)
print(a * b)
# [[ 6 9 6]
# [25 30 5]]