页: 1 我将阵列变成了一批愤怒。 我应如何这样做?
<>代码>int(> 赢得了t work,因为它说,它可以将其转换成体。 改变<条码>d 类型的外地本身显然不做任何工作,因为实际的墨迹已经改变。 在谷歌或文件中,我似乎找不到什么东西——这是怎样做的最好方法?
使用<代码>。
>>> a = numpy.array([1, 2, 3, 4], dtype=numpy.float64)
>>> a
array([ 1., 2., 3., 4.])
>>> a.astype(numpy.int64)
array([1, 2, 3, 4])
See documentation 。
虽然<条码>作为类型可能是“最佳”选择,但也有几种其他方法将其转换成一个分类阵列。 采用<代码>arr的Im 实例如下:
>>> import numpy as np
>>> arr = np.array([1,2,3,4], dtype=float)
>>> arr
array([ 1., 2., 3., 4.])
int* functions from NumPy>>> np.int64(arr)
array([1, 2, 3, 4])
>>> np.int_(arr)
array([1, 2, 3, 4])
*array functions themselves:>>> np.array(arr, dtype=int)
array([1, 2, 3, 4])
>>> np.asarray(arr, dtype=int)
array([1, 2, 3, 4])
>>> np.asanyarray(arr, dtype=int)
array([1, 2, 3, 4])
astype method (that was already mentioned but for completeness sake):>>> arr.astype(int)
array([1, 2, 3, 4])
请注意,通过<条码>int作为<条码>的模版或<条码>,将出现一种基于你的平台的缺省分类。 例如,在Windows上,它将在64bit int32上,与64bit Zhu其int<64>/code>。 如果您需要一种具体的分类类型,并想避免平台的“模糊”,那么你应当使用相应的NumPy类型,如np.int32或np.int64。
还进行了真正有益的讨论,将现有的阵列转换成。 单体阵列的内型转换。 如果你对复制贵国的阵列(即<条码>的类型>)表示担心,则肯定会核对这一联系。
所有我都使用过。
numpyfloat = (1.0, 2.0, 4.0)
a = numpy.array(numpyfloat, dtype=numpy.int)
那是
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