如何numpy的recarray的一个子集转换为持续的阵列？ [英] How to convert a subset of numpy recarray to continuous array?

问题描述

我有一个 recarray 来自读取csv文件。我感兴趣的列的子集转换成一个连续的float数组。我想，以避免将它们转换为列出或一个堆叠它们。
我试着在 http://stackoverflow.com/a/11792956 并的 http://stackoverflow.com/a/7842620 但我得到

I have a recarray that comes from reading a csv file. I am interested in converting a subset of columns to a continuous float array. I'd like to avoid converting them to list or stacking them one by one. I tried the suggestions in http://stackoverflow.com/a/11792956 and http://stackoverflow.com/a/7842620 but I get

ValueError错误：新型阵列与不兼容

ValueError: new type not compatible with array.

下面是我的code：

a = np.recfromcsv(r"myfile.csv")
#a has many columns of type int, float or string. I want to extract those called coeff*
coeffs_columns = [n for n in a.dtype.names if n.startswith('coeff')] 
coeffs_recarray = a[coeffs_columns]
newtype=[(n,'<f8') for n in coeffs_columns]
b = coeffs_recarray.astype(newtype)
#b is:
#array((0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0),  dtype=[('coefficients00', '<f8'), ('coefficients1', '<f8'), ('coefficients2', '<f8'), ('coefficients3', '<f8'), ('coefficients4', '<f8'), ('coefficients5', '<f8'), ('coefficients6', '<f8'), ('coefficients7', '<f8'), ('coefficients8', '<f8'), ('coefficients9', '<f8'), ('coefficients100', '<f8'), ('coefficients11', '<f8'), ('coefficients12', '<f8'), ('coefficients13', '<f8'), ('coefficients14', '<f8')])
coeffs = b.view('<f8')

在有趣的事情是，如果我只提取一列，或者，如果我的工作与一个 recarray 为

x = np.array([(1.0, 2,7.0), (3.0, 4, 9.9)], 
                 dtype=[('x', '<f8'), ('y', '<f8'), ('z', '<f8')])

转换工作。

推荐答案

numpy的提供的 numpy.ascontiguousarray 。

Numpy provides numpy.ascontiguousarray.

该函数返回其输入数组的内存中的一个连续数组（C顺序）。与阵列非连续的看法时，这是特别有用。

This function returns a contiguous array in memory (C order) of its input array. This is especially helpful when dealing with non contiguous views on arrays.

如果Fortran的订单需要，可以使用<一个href=\"http://docs.scipy.org/doc/numpy/reference/generated/numpy.asfortranarray.html#numpy.asfortranarray\"相对=nofollow> numpy.asfortranarray 。

If Fortran order is desired, use numpy.asfortranarray.

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