CODEWITHSUNDEEP
pythonnumpy
Karan Malhotra
Karan Malhotra

Reputation: 3

Selecting specific rows from an array when a condition is met in python

I have a numpy array of IoU values with 300 rows and 4 columns. A row is selected if every element in that row is less than 0.5. I wrote a code which try to do this but it returns rows in which every element is zero.

import numpy as np
iou = np.random.rand(300,4)

negative_boxes = []
for x in range(len(iou)):
    if iou[x,:].any() < 0.5:
       negative_boxes.append(iou[x])

How to select rows in which every element is less than 0.5?

Upvotes: 0

Views: 3284

Answers (2)

Christian
Christian

Reputation: 1257

Instead of a for loop, you can use numpy masks, that are more efficient.

With your problem:

import numpy as np
iou = np.random.rand(300,4)
indices = np.where((iou < 0.5).all(axis=1))
negative_boxes = iou[indices]

Then indices contains all the indices of the rows where all values are smaller than 0.5 and negative_boxes contains the array with only the small values you are looking for.

Upvotes: 2

ducminh
ducminh

Reputation: 1352

a.any() returns True if any of the elements of a evaluate to True, False otherwise.

if iou[x,:].any() < 0.5 implicitly converts the boolean value returned by iou[x,:].any() to 0 and 1 (in fact, bool is a subclass of int). Thus iou[x,:].any() < 0.5 is True if and only if iou[x,:].any() is False, i.e., every element of iou[x,:] is 0.

To check if all elements of an array a are less than 0.5, use np.all:

import numpy as np
iou = np.random.rand(300,4)

negative_boxes = []
for x in range(len(iou)):
    if np.all(iou[x, :] < 0.5):
       negative_boxes.append(iou[x])

Upvotes: 1

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