使用1d布尔数组的2d数组

Question

我有两个numpy数组。

x = [[1,2], [3,4], [5,6]]
y = [True, False, True]

我想获得X的元素y的相应元素是True：

filtered_x = filter(x,y)
print(filtered_x) # [[1,2], [5,6]] should be shown.

我已经尝试了np.extract，但只有当x是1d数组时它似乎才有用。如何提取x y的相应值True的元素是SELECT DATE(start_date) trip_date, MAX(duration) FROM trips GROUP BY 1 ？

Answer 1

只需使用boolean indexing：

>>> import numpy as np

>>> x = np.array([[1,2], [3,4], [5,6]])
>>> y = np.array([True, False, True])
>>> x[y]   # or "x[y, :]" because the boolean array is applied to the first dimension (in this case the "rows")
array([[1, 2],
       [5, 6]])

如果您想将其应用于列而不是行：

>>> x = np.array([[1,2], [3,4], [5,6]])
>>> y = np.array([True, False])
>>> x[:, y]  # boolean array is applied to the second dimension (in this case the "columns")
array([[1],
       [3],
       [5]])

Answer 2

l=[x[i] for i in range(0,len(y)) if y[i]]这样就可以了。