27 lines
1002 B
Python
27 lines
1002 B
Python
|
import numpy as np
|
||
|
from scipy import sparse
|
||
|
|
||
|
if __name__ == "__main__":
|
||
|
# Aufgabe 1b
|
||
|
input_matrix = [[3, 0, -2, 11],
|
||
|
[0, 0, 9, 0],
|
||
|
[0, 7, 0, 0],
|
||
|
[0, 0, 0, 0]]
|
||
|
sparse_matrix = []
|
||
|
for row in range(len(input_matrix)):
|
||
|
for column in range(len(input_matrix[0])):
|
||
|
if input_matrix[row][column] != 0:
|
||
|
# Aufgabe 1d
|
||
|
print("Index: ["+str(row)+"]"+"["+str(column)+"] = "+str(input_matrix[row][column]))
|
||
|
triplet = [row, column, input_matrix[row][column]] # saving index of not null values
|
||
|
sparse_matrix.append(triplet)
|
||
|
|
||
|
# Aufgabe 1c
|
||
|
print("\nThe sparce matrix computed without numpy\n" + str(sparse_matrix))
|
||
|
|
||
|
# faster way with numpy
|
||
|
input_matrix = np.array(input_matrix)
|
||
|
rows, columns = input_matrix.shape
|
||
|
sparse_matrix = sparse.csr_matrix(input_matrix)
|
||
|
print("\nThe sparce matrix computed with numpy\n" + str(sparse_matrix))
|