I want to sort (descending) a numpy array where the array is reshaped to one column structure. However, the following code seems not be working.
a = array([5,1,2,4,9,2]).reshape(-1, 1)
a_sorted = np.sort(a)[::-1]
print("a=",a)
print("a_sorted=",a_sorted)
Output is
a= [[5]
[1]
[2]
[4]
[9]
[2]]
a_sorted= [[2]
[9]
[4]
[2]
[1]
[5]]
That is due to the reshape function. If I remove that, the sort works fine. How can I fix that?
Here you need Axis should be 0 (Column wise sorting)
np.sort(a,axis=0)[::-1]
Discussion:
a = np.array([[4,1],[23,2]])
print(a)
Output:
[[ 4 1]
[23 2]]
# Axis None (Sort as a flatten array)
print(np.sort(a,axis=None))
Output:
[ 1 2 4 23]
# Axis None (Sort as a row wise **(By default is set to 1)**)
print(np.sort(a,axis=1))
[[ 1 4]
[ 2 23]]
# Axis None (Sort as a column wise)
print(np.sort(a,axis=0))
[[ 4 1]
[23 2]]
For more details have a look in: https://numpy.org/doc/stable/reference/generated/numpy.sort.html
As @tmdavison pointed out in the comments you forgot to use the axis option since by default np sorts matrices by row. By calling the reshape function, in fact, you're transforming the array into a 1-column matrix which sorting by row is trivially the matrix itself.
This would do the job
import numpy as np
a = np.array([5,1,2,4,9,2]).reshape(-1, 1)
a_sorted = np.sort(a, axis = 0)[::-1]
print("a=",a)
print("a_sorted=",a_sorted)
Extra points:
np.sort(a, axis=0)[::-1]should do it