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I am trying to fill a 2D array using a for loop, with a variable that is an array. From this array, I am hoping to find the average of each column and input this into a new array.

However, I don't know how to input the variable into a 2D array.

A_values = numpy.zeros([20, 1])

print(A_values)

for i in range(0,20):
    A_values([1,i]) = xa

In this code, xa is a variable that changes with each iteration and has a length of 402.

I am trying to get it so that the 2d array 'A_values' has 402 columns and 20 rows

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2 Answers 2

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Are you necessarily looking to use for-loops? I am asking because this problem can be solved in simpler and more efficient ways such as:

import numpy as np

a_values = np.random.rand(20,402) #Store random values in a_values with a shape of 20 rows and 402 columns
avg_columns = a_values.mean(axis=0) #Calculate the mean of each column 

print(avg_columns)

Documentation for generating random values: numpy.random.rand

EDIT:

I assumed that xa is randomized in each iteration (make sure to replace it with the xa that you are generating). You can initialize an empty a_values array, and add the generated xa array to it in each iteration using np.vstack. For the first iteration, when a_value is empty, I made it equal to xa (if a_values.size else xa).

import numpy as np

a_values = np.array([])

for i in range(20):
  xa = np.random.rand(1,402)
  a_values = np.vstack([a_values, xa]) if a_values.size else xa

avg_columns = a_values.mean(axis=0) #Average of each column

Documentation for vstack: numpy.vstack

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3 Comments

Sorry, I should have been clearers the array isn't filled with random numbers it is filled with integers representing the number of A particles left in a radioactive decay process. Thank you though!
No problem. I edited my post, is this what you wanted?
Yes, thank you again! the problem in my code turned out to be using brackets around square brackets continuing to give me a call function error. Thank you!
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I don't think you can change the shape of A_values after it's defined. So you should start with:

A_values = numpy.zeros([20,402])

And if your for loop is iterating through the rows, your index should be [i, 1] (numpy array indexes are not like cartesian plane coords).

But you want to change entire rows of A_values, to do this you use just the first index:

A_values[row] = some_row

Remember that "some_row" needs to have the proper lenght, otherwise you get a ValueError.

Your final code will look like this:

A_values = numpy.zeros([20, 402])

for i in range(0,20):
    A_values([i]) = xa

PS: You should describe the errors you are getting and be clearer if you want help with the "xa" values as well...

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4 Comments

thank you for your help! However, I am getting an error which reads "can't assign to function call" . xa = numpy.concatenate([evolve_system(NA, NB, NC, rules1, nsteps)[0], evolve_system(final_NA, final_NB, final_NC, rules2, nsteps)[0]]), where evolve_system is a function previously defined.
What does evolve_system returns? To use numpy.concatenate(), both arguments must be numpy.arrays and you need to use the right axis. Have a look here: docs.scipy.org/doc/numpy/reference/generated/… (i actually think the error is in the evolve_system function now)
evolve_systems returns an array of integers.
you should remove this outer pair of square brackets: numpy.concatenate(evolve_system(NA, NB, NC, rules1, nsteps)[0], evolve_system(final_NA, final_NB, final_NC, rules2, nsteps)[0])

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