[英]Assigning values to a NumPy array
有人可以向我解釋為什么嘗試#1不起作用?
import numpy as np
x = np.zeros(1, dtype=np.dtype([('field', '<f8', (1,2))]))
嘗試#1:
x[0]['field'] = np.array([3.,4.], dtype=np.double)
print x, '\n'
[([[ 3. 0.]])]
(為什么只復制'3'
?)
嘗試#2:
x['field'][0] = np.array([3.,4.], dtype=np.double)
print x
[([[ 3. 4.]])]
(這有效)
說實話......我不確定我是否也得到了結果。 它似乎不一致/破碎。 部分原因是形狀不一致,但不是全部。 一些數據似乎正在消失。
例如(注意形狀):
In [1]: import numpy as np
In [2]: x = np.zeros(1, dtype=np.dtype([('field', '<f8', (1, 2))]))
In [3]: y = x[0]['field'].copy()
In [4]: y[0] = 3
In [5]: y[1] = 4
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-5-cba72439f97c> in <module>()
----> 1 y[1] = 4
IndexError: index 1 is out of bounds for axis 0 with size 1
In [6]: y[0][1] = 4
In [7]: x
Out[7]:
array([([[0.0, 0.0]],)],
dtype=[('field', '<f8', (1, 2))])
In [8]: y
Out[8]: array([[ 3., 4.]])
In [9]: x[0]['field'] = y
In [10]: x
Out[10]:
array([([[3.0, 0.0]],)],
dtype=[('field', '<f8', (1, 2))])
所以......為了讓它更容易掌握,讓我們讓形狀變得更簡單。
In [1]: import numpy as np
In [2]: x = np.zeros(1, dtype=np.dtype([('field', '<f8', 2)]))
In [3]: y = x[0]['field'].copy()
In [4]: y[0] = 3
In [5]: y[1] = 4
In [6]: x[0]['field'] = y
In [7]: x
Out[7]:
array([([3.0, 0.0],)],
dtype=[('field', '<f8', (2,))])
In [8]: y
Out[8]: array([ 3., 4.])
在這種情況下數據的來源......不是線索。 盡管如此,分配數據的方式似乎很容易。
幾個選項:
In [9]: x['field'][0] = y
In [10]: x
Out[10]:
array([([3.0, 4.0],)],
dtype=[('field', '<f8', (2,))])
In [11]: x['field'] = y * 2
In [12]: x
Out[12]:
array([([6.0, 8.0],)],
dtype=[('field', '<f8', (2,))])
In [13]: x['field'][:] = y
In [14]: x
Out[14]:
array([([3.0, 4.0],)],
dtype=[('field', '<f8', (2,))])
In [15]: x[0]['field'][:] = y * 2
In [16]: x
Out[16]:
array([([6.0, 8.0],)],
dtype=[('field', '<f8', (2,))])
它似乎是Numpy中公認的錯誤 。 有可能修復的討論,但錯誤仍然是開放的。
聲明:本站的技術帖子網頁,遵循CC BY-SA 4.0協議,如果您需要轉載,請注明本站網址或者原文地址。任何問題請咨詢:yoyou2525@163.com.