推广 Numpy 切片 Python

Question

我不知道如何概括 numpy 数组的切片。请参阅以下切片：

x_train = data[:train_set_size,:-1,4:-1]    
x_valid = data[train_set_size:train_set_size+valid_set_size,:-1,4:-1]
x_test = data[train_set_size+valid_set_size:,:-1,4:-1]

y_train = data[:train_set_size,-1,-2:]
y_valid = data[train_set_size:train_set_size+valid_set_size,-1,-2:]
y_test = data[train_set_size+valid_set_size:,-1,-2:]

如您所见，x 集被分割为 :-1,4:-1，y 被分割为 -1,-2:。如果我必须进行更改，那么我需要更改 3 次，而如果有一种方法可以将切片存储在变量中，并且只需更改变量并反映更改。

例如：xset_slice = ":-1,4:-1" 和 yset_slice = "-1,-2:"。然后只需将位置替换为：

x_train = data[:train_set_size,xset_slice ]    
x_valid = data[train_set_size:train_set_size+valid_set_size,xset_slice ]
x_test = data[train_set_size+valid_set_size:,xset_slice ]
y_train = data[:train_set_size,-1,-2:]
y_valid = data[train_set_size:train_set_size+valid_set_size,yset_slice ]
y_test = data[train_set_size+valid_set_size:,yset_slice]

但是这种说法会报错。因此，请让我知道是否有任何类似的方法可以帮助我。

Answer 1

你可以使用sklearn.model_selection.train_test_split

 X_train, X_test, y_train, y_test 
    = train_test_split(X, y, test_size=0.2, random_state=1)

 X_train, X_val, y_train, y_val 
    = train_test_split(X_train, y_train, test_size=0.2, random_state=1)

Answer 2

您可以从 slice 个对象和元组构建索引：

slice1 = slice(-1)
slice2 = slice(4,-1)
slice3 = slice(-2,None)

x_train = data[:train_set_size,slice1, slice2]    
x_valid = data[train_set_size:train_set_size+valid_set_size, slice1, slice2]
x_test = data[train_set_size+valid_set_size:, slice1, slice2]

通过连接多个元组来创建复合元组：

tup1 = (slice1, slice2)
# or with np.s_[:-1, 4:-1]
x_train = data[(slice(train_set_size),+tup1]    
...

推广 Numpy 切片 Python

Generalize Numpy slicing Python

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