Randomly assign constant value to Numpy array

Question

The objective is randomly assign a constant value to tril of a numpy array. I wonder whether there is more efficient and compact than the proposed solution below.

import numpy as np
import random

rand_n2 = np.random.randn(10,10)
arr=np.tril(rand_n2,-1)
n=np.where(arr!=0)
nsize=n[0].shape[0]
rand_idx = random.sample(range(1,nsize), nsize-1)
ndrop=2 # Total location to assign the contant value
for idx in range(ndrop):
    arr[n[0][rand_idx[idx]],n[1][rand_idx[idx]]]=10 # Assign constant value to random tril location

Is the input matrix always square?

Jérôme Richard
– Jérôme Richard

2021-09-08 18:59:26 +00:00
Commented Sep 8, 2021 at 18:59 — Jérôme Richard
– Jérôme Richard, Commented Sep 8, 2021 at 18:59

Andreas · Accepted Answer · 2021-09-08 16:17:25Z

1

You could initialize a matrix with random numbers, and overwrite the upper triangle the you take random indexes from the lower triangle indexes and overwrite them:

import numpy as np

# create the matrix with random values
size = 5
arr = np.random.rand(size, size)
arr[np.triu_indices(size, k=0)] = 0

# set values randomly
val = 10
k_max = 2
ix = np.random.choice(range(int((size*size-size)/2)), k_max)
rnd = np.tril_indices(size, k=-1)
arr[(rnd[0][ix], rnd[1][ix])] = val

array([[ 0.        ,  0.        ,  0.        ,  0.        ,  0.        ],
       [ 0.50754565,  0.        ,  0.        ,  0.        ,  0.        ],
       [ 0.98920062,  0.53945212,  0.        ,  0.        ,  0.        ],
       [ 0.54987252, 10.        ,  0.22052519,  0.        ,  0.        ],
       [10.        ,  0.82057924,  0.86199411,  0.85397047,  0.        ]])

edited Sep 8, 2021 at 16:17

answered Sep 8, 2021 at 15:36

Andreas

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Comments

Tinu · Accepted Answer · 2021-09-09 07:55:17Z

1

Don't know if this is much more efficient and compact, but I feel it's a bit cleaner and easier to read:

import numpy as np

rand_n2 = np.random.randn(10,10)
arr=np.tril(rand_n2,-1)

# create list of lower trianguler indices
tril_idx = [(i,j) for i in range(1,10) for j in range(i)]
# shuffle indices i.e. draw two at random
np.random.shuffle(tril_idx)

ndrop = 2 # Total location to assign the contant value
for idx in tril_idx[:ndrop]:
    arr[idx] = 10 # Assign constant value to random tril location

Instead of using the double list comprehension to create the list of lower triangular indices, you can use np.tril_indices() as well. Just take care since this will return a tuple of arrays of rather than a array of tuples.

edited Sep 9, 2021 at 7:55

answered Sep 8, 2021 at 15:35

Tinu

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