Creating array with values less than the threshold using Python

Question

I want to pick the minimum in the first row and then select values which are less than this minimum as I scan the succeeding rows. The output should look as below.

import numpy as np
a = np.array([[0.4234101 , 0.73587042, 0.81, 0.83202077, 0.73592897],
       [0.45714687, 0.13144797, 0.67110076, 0.70283126, 0.32859529],
       [0.30888356, 0.84115786, 0.24648344, 0.4963486 , 0.42780253],
       [0.10956774, 0.49696239, 0.17086982, 0.34758674, 0.6332388 ],
       [0.69931352, 0.72449178, 0.98831224, 0.20775389, 0.19041985]])

print(a<0.4234101)

The desired output is

array([0.4234101 , 0.13144797, 0.32859529, 0.30888356, 0.24648344,
       0.10956774, 0.17086982, 0.34758674, 0.20775389, 0.19041985])

Answer 1

Try:

print([i  for i in a.reshape(-1,) if i<0.42])

or if you want it linked to the first value:

print([i  for i in a.reshape(-1,) if i<a.reshape(-1,)[0]])

Answer 2

One of possible solutions is:

1. Get the minimum from row 0:

   a0min = a[0].min()
   

2. Get following rows:

   a1 = a[1:]
   

3. Get the result:

   result = np.insert(a1[a1 < a0min], 0, a0min)
   

   i.e. get the wanted elements from a1 (following rows) and insert the minimum from the initial row at the beginning.

The result is:

array([0.4234101 , 0.13144797, 0.32859529, 0.30888356, 0.24648344,
       0.10956774, 0.17086982, 0.34758674, 0.20775389, 0.19041985])

You don't need any explicit iteration over the source array, as it is performed under the hood by Numpy.

Answer 3

The method you might want is np.nditer() which iterates over the single elements of an multidimensional array

import numpy as np

a = np.array([[0.4234101 , 0.73587042, 0.81, 0.83202077, 0.73592897],
       [0.45714687, 0.13144797, 0.67110076, 0.70283126, 0.32859529],
       [0.30888356, 0.84115786, 0.24648344, 0.4963486 , 0.42780253],
       [0.10956774, 0.49696239, 0.17086982, 0.34758674, 0.6332388 ],
       [0.69931352, 0.72449178, 0.98831224, 0.20775389, 0.19041985]])

values = []
min = a[0].min()

for element in np.nditer(a[1:]):
    if element < min:
        values.append(element.item(0))