How do I iterate through a numpy array and perform calculations?

Question

I want to iterate through a numpy array and perform division, multiplication, and addition. I keep coming up with several errors. The latest is

IndexError: invalid index to scalar variable.

import numpy as np
rays = np.array([[7.651e-03, 7.284e-03, 5.134e-03, 7.442e-03, 3.035e-03)],[2.373e-03, 6.877e-03, 4.809e-03, 2.870e-04, 3.175e-04, 1.791e-03]])

for i in range(rays):
    for w in range(i):
        estimate = rays[0][i]/(rays[0][i]+rays[1][i])

Answer 1

There are several issues with your example (some of which may be actual problems, others just typos or over simplifiactions):

import numpy as np     # if you want to use for-loops don't use numpy
rays = np.array(...    # closing parentheses instead of brackets
                       # unequal dimensions row of 5 and row of 6
                            
for i in range(rays):  # rays is not a number, did you mean len(rays[0])?
    for w in range(i): # w is not used anywhere
        estimate = rays[0][i]/(rays[0][i]+rays[1][i]) 
                       # estimate is overwritten at each iteration

The whole point of using numpy is to avoid "manually" iterating through array elements using for-loops. You should think of your result as an operation between matrices (or vectors):

For example (without for-loops):

import numpy as np
rays = np.array([[7.651e-03, 7.284e-03, 5.134e-03, 7.442e-03, 3.035e-03],
                 [2.373e-03, 6.877e-03, 4.809e-03, 2.870e-04, 3.175e-04]])

estimates = rays[0]/(rays[0]+rays[1])
print(estimates)
[0.76326816 0.51437045 0.51634316 0.96286712 0.90529456]

Note that I removed the last value from the second row because numpy requires fixed dimensions (ie it cannot have one row with 5 elements and another with 6)

Your nested loop for w in range(i) , though you're not doing anything with w , suggests that you may be looking for the ratio between cumulative sums. If that is the case, use the cumsum function from numpy:

estimates = np.cumsum(rays[0])/np.cumsum(rays[0]+rays[1])
print(estimates)
[0.76326816 0.61753153 0.58805087 0.65726163 0.67565445]

Answer 2

Fixing up your rays definition:

rays = [
    [7.651e-03, 7.284e-03, 5.134e-03, 7.442e-03, 3.035e-03],
    [2.373e-03, 6.877e-03, 4.809e-03, 2.870e-04, 3.175e-04, 1.791e-03]
]

we can iteratively compute your estimates like this:

for r0, r1 in zip(*rays):
    estimate = r0 / (r0 + r1)
    print(estimate)

If you're not familiar with zip (note that zip(*rays) is the same as zip(rays[0], rays[1]) ), the above is basically equivalent to:

for i in range(len(rays[0])):  # assuming all rays have same length!
    r0, r1 = rays[0][i], rays[1][i]
    estimate = r0 / (r0 + r1)
    print(estimate)

The zip version is considered more "pythonic" (and is obviously much more concise).

Answer 3

rays = [
[7.651e-03, 7.284e-03, 5.134e-03, 7.442e-03, 3.035e-03],
[2.373e-03, 6.877e-03, 4.809e-03, 2.870e-04, 3.175e-04],
]

for i in range(min(len(rays[0]), len(rays[1]))):
    estimate = rays[0][i] / (rays[0][i] + rays[1][i])
    print(estimate)