有没有一种快速的方法来“子展平”或者只展平numpy数组中的一些第一个维度?
例如,给定一个维数为(50,100,25)
的numpy数组,结果维数将为(5000,25)
发布于 2013-09-12 15:27:33
看看numpy.reshape吧。
>>> arr = numpy.zeros((50,100,25))
>>> arr.shape
# (50, 100, 25)
>>> new_arr = arr.reshape(5000,25)
>>> new_arr.shape
# (5000, 25)
# One shape dimension can be -1.
# In this case, the value is inferred from
# the length of the array and remaining dimensions.
>>> another_arr = arr.reshape(-1, arr.shape[-1])
>>> another_arr.shape
# (5000, 25)
发布于 2014-10-25 02:14:30
对Alexander的答案稍作概括- np.reshape可以接受-1作为参数,意思是“总数组大小除以所有其他列出的维数的乘积”:
例如,使除最后一个维度外的所有维度变平:
>>> arr = numpy.zeros((50,100,25))
>>> new_arr = arr.reshape(-1, arr.shape[-1])
>>> new_arr.shape
# (5000, 25)
发布于 2019-04-23 10:30:17
另一种方法是使用numpy.resize()
,如下所示:
In [37]: shp = (50,100,25)
In [38]: arr = np.random.random_sample(shp)
In [45]: resized_arr = np.resize(arr, (np.prod(shp[:2]), shp[-1]))
In [46]: resized_arr.shape
Out[46]: (5000, 25)
# sanity check with other solutions
In [47]: resized = np.reshape(arr, (-1, shp[-1]))
In [48]: np.allclose(resized_arr, resized)
Out[48]: True
https://stackoverflow.com/questions/18757742
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