Python numpy array sum over certain indices Python numpy array sum over certain indices numpy numpy

Python numpy array sum over certain indices


python numpy sum indices

You can use sum directly after indexing with indices:

a = np.array([1,2,3,4])indices = [0, 2] a[indices].sum()

python numpy sum indices

The accepted a[indices].sum() approach copies data and creates a new array, which might cause problem if the array is large. np.sum actually has an argument to mask out colums, you can just do

np.sum(a, where=[True, False, True, False])

Which doesn't copy any data.

The mask array can be obtained by:

mask = np.full(4, False)mask[np.array([0,2])] = True

python numpy sum indices

Try:

>>> a = [1,2,3,4]>>> indices = [0, 2]>>> sum(a[i] for i in indices)4

Faster

If you have a lot of numbers and you want high speed, then you need to use numpy:

>>> import numpy as np>>> a = np.array([1,2,3,4])>>> a[indices]array([1, 3])>>> np.sum(a[indices])4

Recent Posts
How can I color dots in a xy scatterplot according to column value?
How to update a claim in ASP.NET Identity?
What does {0} mean when initializing an object?
Accessing members of items in a JSONArray with Java
How to log SQL statements in Spring Boot?
Powershell Get-WebSite name parameter is ignored
How to detect scroll to bottom of html element
Java synchronized method
How to test controllers with CodeIgniter?
Detect Visual Composer
Matplotlib: Specify format of floats for tick labels
Rails join a list of strings with commas and "and" before the last