I wish to initialise a matrix A, using the equation A_i,j = f(i,j) for some f (It's not important what this is).
我想用等式A_i j = f(I,j)来初始化一个矩阵a(这并不重要)
How can I do so concisely avoiding a situation where I have two for loops?
我怎样才能简洁地避免出现两个for循环的情况呢?
2 个解决方案
#1
10
numpy.fromfunction fits the bill here.
numpy.fromfunction适合这里的账单。
Example from doc:
医生的例子:
>>> import numpy as np
>>> np.fromfunction(lambda i, j: i + j, (3, 3), dtype=int)
array([[0, 1, 2],
[1, 2, 3],
[2, 3, 4]])
#2
1
One could also get the indexes of your array with numpy.indices and then apply the function f in a vectorized fashion,
还可以使用numpy获取数组的索引。然后用矢量化的方式应用函数f，
import numpy as np
shape = 1000, 1000
Xi, Yj = np.indices(shape)
A = (2*Xi + 3*Yj).astype(np.int) # or any other function f(Xi, Yj)
#1
10
numpy.fromfunction fits the bill here.
numpy.fromfunction适合这里的账单。
Example from doc:
医生的例子:
>>> import numpy as np
>>> np.fromfunction(lambda i, j: i + j, (3, 3), dtype=int)
array([[0, 1, 2],
[1, 2, 3],
[2, 3, 4]])
#2
1
One could also get the indexes of your array with numpy.indices and then apply the function f in a vectorized fashion,
还可以使用numpy获取数组的索引。然后用矢量化的方式应用函数f，
import numpy as np
shape = 1000, 1000
Xi, Yj = np.indices(shape)
A = (2*Xi + 3*Yj).astype(np.int) # or any other function f(Xi, Yj)