CODEWITHSUNDEEP
pythonarraysnumpy
Emily.SageMaker.AWS
Emily.SageMaker.AWS

Reputation: 332

Append to np.array, but not staying?

Just trying to add items to an array, but for some reason this returns without the added decimal.

import numpy as np
newposition = np.array([1,2,3])
np.append(newposition,(np.random.uniform(0,0.25)))
print newposition

Returns the following, ie without what I need to add. Any suggestions? 

[1 2 3]

Upvotes: 1

Views: 126

Answers (2)

ali_m
ali_m

Reputation: 74242

Don't get into the bad habit of using np.append to build arrays!

Appending to a numpy array is expensive since there is no way to do it without creating a new copy of the array in memory (the same is true of np.concatenate, np.vstack etc.). As the array gets bigger and bigger, copying it becomes slower and slower. A 1700-long 1D vector still isn't that big, but when you are dealing with millions of elements the copying will really hurt performance.

A much better way is to create an empty array with the correct final size, then fill in the appropriate indices as you go along. For example:

# create an empty array of the final size
newposition = np.empty(1700, np.float)

# fill in the first three values
newposition[:3] = 1, 2, 3

# fill in the rest
for ii in xrange(3, 1700):
    newposition[ii] = np.random.uniform(0, 0.25)

# or whatever...

You haven't shown exactly how you build the rest of your newposition array, but in the silly example above it would be much quicker to use the size= argument to np.random.uniform to fill in the rest of the rows in one go:

newposition[3:] = np.random.uniform(0, 0.25, size=1697)

Upvotes: 0

Emily.SageMaker.AWS
Emily.SageMaker.AWS

Reputation: 332

Got it. I'm going to create a list of new values, then convert it into an array, and assign the old array name to the new array.

Upvotes: 1

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