One interesting question:
I would like to delete some elements from a numpy array but just as below simplified example code, it works if didn't delete the last element, but it failure if we wish to delete the last element. Below code works fine:
import numpy as np
values = np.array([0,1,2,3,4,5])
print values
for i in [3,4,1]:
values = np.delete(values,i)
print values
The output is:
[0 1 2 3 4 5]
[0 2 4]
If we only change 4 to 5, then it will fail:
import numpy as np
values = np.array([0,1,2,3,4,5])
print values
for i in [3,5,1]:
values = np.delete(values,i)
print values
The error message:
IndexError: index 5 is out of bounds for axis 0 with size 5
Why this error only happen if delete the last element? what's correct way to do such tasks?
You can use the pop() method to remove an element from the array.
If you want to remove an item from an array, you can use the pop() method to remove the last element or the shift() method to remove the first element.
Summary: The most straightforward way to remove an element at a given index from a NumPy array is to call the function np. delete(array, index) that returns a new array with the element removed.
Using the NumPy function np. delete() , you can delete any row and column from the NumPy array ndarray . Specify the axis (dimension) and position (row number, column number, etc.). It is also possible to select multiple rows and columns using a slice or a list.
Keep in mind that np.delete(arr, ind) deletes the element at index ind
NOT the one with that value.
This means that as you delete things, the array is getting shorter. So you start with
values = [0,1,2,3,4,5]
np.delete(values, 3)
[0,1,2,4,5] #deleted element 3 so now only 5 elements in the list
#tries to delete the element at the fifth index but the array indices only go from 0-4
np.delete(values, 5)
One of the ways you can solve the problem is to sort the indices that you want to delete in descending order (if you really want to delete the array).
inds_to_delete = sorted([3,1,5], reverse=True) # [5,3,1]
# then delete in order of largest to smallest ind
Or:
inds_to_keep = np.array([0,2,4])
values = values[inds_to_keep]
A probably faster way (because you don't need to delete every single value but all at once) is using a boolean mask:
values = np.array([0,1,2,3,4,5])
tobedeleted = np.array([False, True, False, True, False, True])
# So index 3, 5 and 1 are True so they will be deleted.
values_deleted = values[~tobedeleted]
#that just gives you what you want.
It is recommended on the numpy reference on np.delete
To your question: You delete one element so the array get's shorter and index 5 is no longer in the array because the former index 5 has now index 4. Delete in descending order if you want to use np.delete.
If you really want to delete with np.delete
use the shorthand:
np.delete(values, [3,5,1])
If you want to delete where the values are (not the index) you have to alter the procedure a bit. If you want to delete all values 5
in your array you can use:
values[values != 5]
or with multiple values to delete:
to_delete = (values == 5) | (values == 3) | (values == 1)
values[~to_delete]
all of these give you the desired result, not sure how your data really looks like so I can't say for sure which will be the most appropriate.
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