Implement the __setitem__ method such that: 1. if element value is 0, do nothing 2. if the i,j coordinates exceed the current size of the array, insert the element, but update the size (self.shape) accordingly. Complete: def SparseMatrix5(m=None,**kwargs): import itertools import numpy as np def add_to_dict(d, key1, key2, val): <... YOUR CODE HERE ...> class SparseMatrix5_class: def __init__(self, m=m, **kwargs): <... YOUR CODE HERE ...> def __setitem__(self, pos, val): <... YOUR CODE HERE ...> def __getitem__(self, pos): <... YOUR CODE HERE ...> def to_dense(self): <... YOUR CODE HERE ...> return SparseMatrix5_class(**kwargs) manually check your code: def random_sparse_matrix(size): m = np.random.randint(2, size=size) m = m * np.random.randint(10,size=size) return m m = random_sparse_matrix((5,3)) s = SparseMatrix5(m) print("initial") print(s.rows) print(s.to_dense().astype(int)) s[4,2] = m[4,2]*2+3 print("\nafter __setitem__") print(s.rows) print(s.to_dense().astype(int))
Implement the __setitem__ method such that:
1. if element value is 0, do nothing
2. if the i,j coordinates exceed the current size of the array, insert the element, but update the size (self.shape) accordingly.
Complete:
def SparseMatrix5(m=None,**kwargs):
import itertools
import numpy as np
def add_to_dict(d, key1, key2, val):
<... YOUR CODE HERE ...>
class SparseMatrix5_class:
def __init__(self, m=m, **kwargs):
<... YOUR CODE HERE ...>
def __setitem__(self, pos, val):
<... YOUR CODE HERE ...>
def __getitem__(self, pos):
<... YOUR CODE HERE ...>
def to_dense(self):
<... YOUR CODE HERE ...>
return SparseMatrix5_class(**kwargs)
manually check your code:
def random_sparse_matrix(size):
m = np.random.randint(2, size=size)
m = m * np.random.randint(10,size=size)
return m
m = random_sparse_matrix((5,3))
s = SparseMatrix5(m)
print("initial")
print(s.rows)
print(s.to_dense().astype(int))
s[4,2] = m[4,2]*2+3
print("\nafter __setitem__")
print(s.rows)
print(s.to_dense().astype(int))
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