I would like to raise a vector by ascending powers form 0 to 5:
import numpy as np
a = np.array([1, 2, 3]) # list of 11 components
b = np.array([0, 1, 2, 3, 4]) # power
c = np.power(a,b)
desired results are:
c = [[1**0, 1**1, 1**2, 1**3, 1**4], [2**0, 2**1, ...], ...]
I keep getting this error:
ValueError: operands could not be broadcast together with shapes (3,) (5,)
One solution will be to add a new dimension to your array a
c = a[:,None]**b
# Using broadcasting :
# (3,1)**(4,) --> (3,4)
#
# [[1],
# c = [2], ** [0,1,2,3,4]
# [3]]
For more information check the numpy broadcasting documentation
Here's a solution:
num_of_powers = 5
num_of_components = 11
a = []
for i in range(1,num_of_components + 1):
a.append(np.repeat(i,num_of_powers))
b = list(range(num_of_powers))
c = np.power(a,b)
The output c would look like:
array([[ 1, 1, 1, 1, 1],
[ 1, 2, 4, 8, 16],
[ 1, 3, 9, 27, 81],
[ 1, 4, 16, 64, 256],
[ 1, 5, 25, 125, 625],
[ 1, 6, 36, 216, 1296],
[ 1, 7, 49, 343, 2401],
[ 1, 8, 64, 512, 4096],
[ 1, 9, 81, 729, 6561],
[ 1, 10, 100, 1000, 10000],
[ 1, 11, 121, 1331, 14641]], dtype=int32)
Your solution shows a broadcast error because as per the documentation:
If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).
c = [[x**y for y in b] for x in a]
c = np.asarray(list(map(lambda x: np.power(a,x), b))).transpose()
You need to first create a matrix where the rows are repetitions of each number. This can be done with np.tile:
mat = np.tile(a, (len(b), 1)).transpose()
And then raise that to the power of b elementwise:
np.power(mat, b)
All together:
import numpy as np
nums = np.array([1, 2, 3]) # list of 11 components
powers = np.array([0, 1, 2, 3, 4]) # power
print(np.power(np.tile(nums, (len(powers), 1)).transpose(), powers))
Which will give:
[[ 1 1 1 1 1] # == [1**0, 1**1, 1**2, 1**3, 1**4]
[ 1 2 4 8 16] # == [2**0, 2**1, 2**2, 2**3, 2**4]
[ 1 3 9 27 81]] # == [3**0, 3**1, 3**2, 3**3, 3**4]
