向结构化的numpy数组添加字段(4) [英] Adding a field to a structured numpy array (4)

问题描述

此问题已在之前解决(在此处，此处和中添加一个新字段，编号为numpy-genfromtxt-输出.

This has been addressed before (here, here and here). I want to add a new field to a structure array returned by numpy genfromtxt (also asked here).

我的新问题是我正在读取的csv文件只有一个标题行和一个数据行:

My new problem is that the csv file I'm reading has only a header line and a single data row:

output-Summary.csv :

Wedge, DWD, Yield (wedge), Efficiency
1, 16.097825, 44283299.473156, 2750887.118836

我正在通过 genfromtxt 读取它，并计算一个新值'tl':

I'm reading it via genfromtxt and calculate a new value 'tl':

test_out = np.genfromtxt('output-Summary.csv', delimiter=',', names=True)
tl = 300 / test_out['DWD']

test_out 看起来像这样:

array((1., 16.097825, 44283299.473156, 2750887.118836),
      dtype=[('Wedge', '<f8'), ('DWD', '<f8'), ('Yield_wedge', '<f8'), ('Efficiency', '<f8')])

使用 recfunctions.append_fields (如上面的示例1-3中所述)无法对大小为1的数组使用 len():

Using recfunctions.append_fields (as suggested in the examples 1-3 above) fails over the use of len() for the size 1 array:

from numpy.lib import recfunctions as rfn
rfn.append_fields(test_out,'tl',tl)

TypeError: len() of unsized object

搜索替代方法(答案之一此处)我发现 mlab.rec_append_fields 效果很好(但已弃用):

Searching for alternatives (one of the answers here) I find that mlab.rec_append_fields works well (but is deprecated):

mlab.rec_append_fields(test_out,'tl',tl)

C:\ProgramData\Anaconda3\lib\site-packages\ipykernel_launcher.py:1: MatplotlibDeprecationWarning: The rec_append_fields function was deprecated in version 2.2.
  """Entry point for launching an IPython kernel.

rec.array((1., 16.097825, 44283299.473156, 2750887.118836, 18.63605798),
          dtype=[('Wedge', '<f8'), ('DWD', '<f8'), ('Yield_wedge', '<f8'), ('Efficiency', '<f8'), ('tl', '<f8')])

我还可以按照建议

I can also copy the array over to a new structured array "by hand" as suggested here. This works:

test_out_new = np.zeros(test_out.shape, dtype=new_dt)
for name in test_out.dtype.names:
    test_out_new[name]=test_out[name]
test_out_new['tl']=tl

因此，总而言之，有没有一种方法可以使 recfunctions.append_fields 与单行csv文件的 genfromtxt 输出配合使用?我真的更愿意使用一种标准的方式来处理此问题，而不是使用家庭酿造方法.

So in summary - is there a way to get recfunctions.append_fields to work with the genfromtxt output from my single row csv file? I would really rather use a standard way to handle this rather than a home brew..

推荐答案

将数组(和新字段)重塑为大小(1，).仅用一行， genfromtxt 将数据加载为0d数组，形状为(). rfn 代码并未得到广泛使用，并且也不如应有的健壮性.换句话说，标准方式"还是有点小问题.

Reshape the array (and new field) to size (1,). With just one line, the genfromtxt is loading the data as a 0d array, shape (). The rfn code isn't heavily used, and isn't a robust as it should be. In other words, the 'standard way' is still bit buggy.

例如:

In [201]: arr=np.array((1,2,3), dtype='i,i,i')
In [202]: arr.reshape(1)
Out[202]: array([(1, 2, 3)], dtype=[('f0', '<i4'), ('f1', '<i4'), ('f2', '<i4')])

In [203]: rfn.append_fields(arr.reshape(1), 't1',[1], usemask=False)
Out[203]: 
array([(1, 2, 3, 1)],
      dtype=[('f0', '<i4'), ('f1', '<i4'), ('f2', '<i4'), ('t1', '<i8')])

home_brew没问题.大多数 rfn 函数都使用该机制-定义一个新的dtype，使用该dtype创建一个收件人数组，然后按名称逐个复制字段.

Nothing wrong with the home_brew. Most of the rfn functions use that mechanism - define a new dtype, create a recipient array with that dtype, and copy the fields over, name by name.

这篇关于向结构化的numpy数组添加字段(4)的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！