How to convert a subset of numpy recarray to continuous array?

Question

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 https://stackoverflow.com/a/11792956 and https://stackoverflow.com/a/7842620 but I get

ValueError: new type not compatible with array.

Here is my 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')

The "funny" thing is that if I extract only one column, or if I work with a recarray created as

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

the conversion works.

Have you tried np.ascontiguousarray on your array of interest? — Bort
– Bort, Commented Apr 14, 2015 at 15:45
@Bort , thanks, that has solved the problem! If you convert it to an answer I will accept it — lib
– lib, Commented Apr 15, 2015 at 6:55
another "funny" thing is that coeffs_recarray.flags['C_CONTIGUOUS'] is True , but it works only if I use explicitly np.ascontguousarray — lib
– lib, Commented Apr 15, 2015 at 7:12

Bort · Accepted Answer · 2015-04-15 07:44:37Z

3

Numpy provides numpy.ascontiguousarray.

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.

If Fortran order is desired, use numpy.asfortranarray.

answered Apr 15, 2015 at 7:44

Bort

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