我認爲你的問題是你期望np.append
就地添加列,但是它做了什麼,因爲存儲的數據是如何變化的,就是創建一個連接數組的副本
Returns
-------
append : ndarray
A copy of `arr` with `values` appended to `axis`. Note that `append`
does not occur in-place: a new array is allocated and filled. If
`axis` is None, `out` is a flattened array.
所以你需要保存輸出all_data = np.append(...)
:
my_data = np.random.random((210,8)) #recfromcsv('LIAB.ST.csv', delimiter='\t')
new_col = my_data.sum(1)[...,None] # None keeps (n, 1) shape
new_col.shape
#(210,1)
all_data = np.append(my_data, new_col, 1)
all_data.shape
#(210,9)
替代方式:
all_data = np.hstack((my_data, new_col))
#or
all_data = np.concatenate((my_data, new_col), 1)
我相信,(np.vstack
以及)這三種功能之間的唯一區別是他們在axis
未指定時的默認行爲:
concatenate
假定axis = 0
hstack
假定axis = 1
除非輸入是一維,然後axis = 0
vstack
添加軸之後假定axis = 0
如果輸入是一維
append
變平陣列
基於你的評論,並更仔細地查看你的示例代碼,我現在相信你是一個可能想要做的是添加一個字段到record array。您同時導入了genfromtxt
,它返回structured array和recfromcsv
,它返回微妙不同的record array (recarray
)。你現在使用的recfromcsv
所以現在my_data
實際上是recarray
,這意味着最有可能的my_data.shape = (210,)
因爲recarrays是1d的記錄數組,其中每個記錄都是具有給定dtype的元組。
所以,你可以試試這個:
import numpy as np
from numpy.lib.recfunctions import append_fields
x = np.random.random(10)
y = np.random.random(10)
z = np.random.random(10)
data = np.array(list(zip(x,y,z)), dtype=[('x',float),('y',float),('z',float)])
data = np.recarray(data.shape, data.dtype, buf=data)
data.shape
#(10,)
tot = data['x'] + data['y'] + data['z'] # sum(axis=1) won't work on recarray
tot.shape
#(10,)
all_data = append_fields(data, 'total', tot, usemask=False)
all_data
#array([(0.4374783740738456 , 0.04307289878861764, 0.021176067323686598, 0.5017273401861498),
# (0.07622262416466963, 0.3962146058689695 , 0.27912715826653534 , 0.7515643883001745),
# (0.30878532523061153, 0.8553768789387086 , 0.9577415585116588 , 2.121903762680979),
# (0.5288343561208022 , 0.17048864443625933, 0.07915689716226904 , 0.7784798977193306),
# (0.8804269791375121 , 0.45517504750917714, 0.1601389248542675 , 1.4957409515009568),
# (0.9556552723429782 , 0.8884504475901043 , 0.6412854758843308 , 2.4853911958174133),
# (0.0227638618687922 , 0.9295332854783015 , 0.3234597575660103 , 1.275756904913104),
# (0.684075052174589 , 0.6654774682866273 , 0.5246593820025259 , 1.8742119024637423),
# (0.9841793718333871 , 0.5813955915551511 , 0.39577520705133684 , 1.961350170439875),
# (0.9889343795296571 , 0.22830104497714432, 0.20011292764078448 , 1.4173483521475858)],
# dtype=[('x', '<f8'), ('y', '<f8'), ('z', '<f8'), ('total', '<f8')])
all_data.shape
#(10,)
all_data.dtype.names
#('x', 'y', 'z', 'total')
什麼不工作呢? – 2013-04-04 15:52:18
不工作的事情是,無論我嘗試什麼版本,它都不會給我正確的尺寸。 – user2130951 2013-04-04 18:13:36