如何在 numpy ndarray 中将具有相同行和列的值设置为零?
how to set values with same row and column to zero in a numpy ndarray?
我有一个 numpy ndarray,如下所示
x = np.array([[1, 2, 3], [4, 5, 6],[4, 1, 6],[1, 5, 11],[4,3, 4]], np.int32)
如果索引具有相同的列,我将值设置为零
rows = x.shape[0]
cols = x.shape[1]
for k in range(0, rows):
for y in range(0, cols):
if k==y:
x[k,y]=0
预期输出:
array([[ 0, 2, 3],
[ 4, 0, 6],
[ 4, 1, 0],
[ 1, 5, 11],
[ 4, 3, 4]])
是否有任何简单的(pythonic 方式来达到相同的结果)?我的实际矩阵很大...
x = np.array([[1, 2, 3], [4, 5, 6],[4, 1, 6],[1, 5, 11],[4,3, 4]], np.int32)
np.fill_diagonal(x,0)
print(x)
array([[ 0, 2, 3],
[ 4, 0, 6],
[ 4, 1, 0],
[ 1, 5, 11],
[ 4, 3, 4]], dtype=int32)
我有一个 numpy ndarray,如下所示
x = np.array([[1, 2, 3], [4, 5, 6],[4, 1, 6],[1, 5, 11],[4,3, 4]], np.int32)
如果索引具有相同的列,我将值设置为零
rows = x.shape[0]
cols = x.shape[1]
for k in range(0, rows):
for y in range(0, cols):
if k==y:
x[k,y]=0
预期输出:
array([[ 0, 2, 3],
[ 4, 0, 6],
[ 4, 1, 0],
[ 1, 5, 11],
[ 4, 3, 4]])
是否有任何简单的(pythonic 方式来达到相同的结果)?我的实际矩阵很大...
x = np.array([[1, 2, 3], [4, 5, 6],[4, 1, 6],[1, 5, 11],[4,3, 4]], np.int32)
np.fill_diagonal(x,0)
print(x)
array([[ 0, 2, 3],
[ 4, 0, 6],
[ 4, 1, 0],
[ 1, 5, 11],
[ 4, 3, 4]], dtype=int32)