編輯我的問題以使其更加清晰，因為我無法獲得第一個工作答案。我正在嘗試制作一個 N 維查找表，根據 N 個 True/False 值的輸入列表從中查找一個值。為此，我創建了一個 N 維數組，其中每個維度的長度為 2 - 一個值表示 False (=0)，一個值表示 True (=1)import numpy as npimport randomdims = 3values = range(pow(2,dims))lookup=np.reshape(values,np.tile(2,dims)) #this makes a 2x2x2x... arraycondition=random.choices([True,False],k=dims) #this makes a 1d list of bools條件中的布爾值現在應該指定要查找的索引。以 N=3 為例：如果條件 =(True,False,True)，我想要查找[1,0,1]。只需使用lookup[condition.astype(int)]不起作用，因為 numpy 不會將 1x3 數組解釋為索引。lookup[condition[0],condition[1],condition[2]]作品。但我還沒弄清楚如何在 N 維上寫這個
1 回答
largeQ
TA貢獻2039條經驗 獲得超8個贊
手動將其轉換為 int 元組可以實現您所尋求的索引。測試下面的代碼。
import numpy as np
# your example had d=3, but you may have something else.
# this is just creation of some random data...
d=3
answers = np.random.normal(size=[2] * d)
truth = tuple(np.random.choice([True, False], replace=True, size=d))
# manual conversion to int-tuple is needed, for numpy to understand that it
# is a indexing tuple.
# the box at the top of https://numpy.org/doc/stable/reference/arrays.indexing.html
# says that tuple indexing is just like normal indexing, and in that case, we
# need to have normal ints.
idx = tuple(int(b) for b in truth)
answer = answers[idx]
print(answer)
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