输入
在类似下面的示例列表中,我有很多numpy structured arrays:
import numpy
a1 = numpy.array([(1, 2), (3, 4), (5, 6)], dtype=[('x', int), ('y', int)])
a2 = numpy.array([(7,10), (8,11), (9,12)], dtype=[('z', int), ('w', float)])
arrays = [a1, a2]
期望输出
将它们连接在一起以创建如下所示的统一结构化数组的正确方法是什么?
desired_result = numpy.array([(1, 2, 7, 10), (3, 4, 8, 11), (5, 6, 9, 12)],
dtype=[('x', int), ('y', int), ('z', int), ('w', float)])
当前方法
这就是我目前正在使用的,但它非常慢,所以我怀疑一定有更有效的方法。
from numpy.lib.recfunctions import append_fields
def join_struct_arrays(arrays):
for array in arrays:
try:
result = append_fields(result, array.dtype.names, [array[name] for name in array.dtype.names], usemask=False)
except NameError:
result = array
return result
发布于 2011-03-19 02:13:41
您还可以使用numpy.lib.recfunctions
的函数merge_arrays
import numpy.lib.recfunctions as rfn
rfn.merge_arrays(arrays, flatten = True, usemask = False)
Out[52]:
array([(1, 2, 7, 10.0), (3, 4, 8, 11.0), (5, 6, 9, 12.0)],
dtype=[('x', '<i4'), ('y', '<i4'), ('z', '<i4'), ('w', '<f8')])
发布于 2011-03-19 03:03:24
还有另一种方式,可读性更好,速度也更快,我认为:
def join_struct_arrays(arrays):
newdtype = []
for a in arrays:
descr = []
for field in a.dtype.names:
(typ, _) = a.dtype.fields[field]
descr.append((field, typ))
newdtype.extend(tuple(descr))
newrecarray = np.zeros(len(arrays[0]), dtype = newdtype)
for a in arrays:
for name in a.dtype.names:
newrecarray[name] = a[name]
return newrecarray
编辑:在Sven的建议下,它变得(有点慢,但实际上可读性很好):
def join_struct_arrays2(arrays):
newdtype = sum((a.dtype.descr for a in arrays), [])
newrecarray = np.empty(len(arrays[0]), dtype = newdtype)
for a in arrays:
for name in a.dtype.names:
newrecarray[name] = a[name]
return newrecarray
发布于 2021-06-19 20:20:58
def join_struct_arrays(*arrs):
dtype = [(name, d[0]) for arr in arrs for name, d in arr.dtype.fields.items()]
r = np.empty(arrs[0].shape, dtype=dtype)
for a in arrs:
for name in a.dtype.names:
r[name] = a[name]
return r
https://stackoverflow.com/questions/5355744
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