45 lines
1.2 KiB
Python
45 lines
1.2 KiB
Python
import collections
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import numpy as np
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from scipy import sparse
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class Matrix:
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def __init__(self):
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self.matrix = collections.defaultdict(dict)
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def set(self, col, ro, value):
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if value == 0:
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if self.matrix.get(col) and self.matrix.get(col).get(ro):
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del self.matrix[col][ro]
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else:
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self.matrix[col][ro] = value
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def get(self, col, ro):
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if self.matrix.get(col) and self.matrix.get(col).get(row):
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return self.matrix[col][row]
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else:
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return 0
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if __name__ == "__main__":
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# Aufgabe 1b
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input_matrix = [[3, 0, -2, 11],
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[0, 0, 9, 0],
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[0, 7, 0, 0],
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[0, 0, 0, 0]]
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mar = Matrix()
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for row in range(len(input_matrix)):
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for column in range(len(input_matrix[0])):
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mar.set(row, column, input_matrix[row][column])
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print(mar.matrix)
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# Aufgabe 1c
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# print("\nThe sparce matrix computed without numpy\n" + str(sparse_matrix))
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# faster way with numpy
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input_matrix = np.array(input_matrix)
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rows, columns = input_matrix.shape
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sparse_matrix = sparse.csr_matrix(input_matrix)
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print("\nThe sparce matrix computed with numpy\n" + str(sparse_matrix))
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