问在保持原始矩阵大小的情况下对2D矩阵进行采样

EN

import copy

#Figuring out Matrix Sampling
np.random.seed(3)
training_percent = .7

R = np.arange(100).reshape(10,10)
print("R:")
print(R)


#Get the indexes of the non-zero elements
non_zero_is,non_zero_js = np.nonzero(R)

#Randomly sample the indexes
sampled_indexes_of_non_zeros = np.random.choice(len(i), 
    int(np.floor(training_percent * len(i))), replace=False)

#Training Mask
training_mask = np.zeros(R.shape,dtype=bool)
for position in sampled_indexes_of_non_zeros:
    training_mask[non_zero_is[position],non_zero_js[position]] = True

#Training Matrix
training_matrix = R.copy()
training_matrix[~training_mask] = 0
print("\ntraining_martix:")
print(training_matrix)

#Validation Matrix
validation_matrix = R.copy()
validation_matrix[training_mask] = 0
print("\nvalidation_martix:")
print(validation_matrix)