Python 将字符串转换为 numpy 数组
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Convert string to numpy array
提问by Am1rr3zA
I have a string like mystr = "100110"(the real size is much bigger) I want to convert it to numpy array like mynumpy = [1, 0, 0, 1, 1, 0], mynumpy.shape = (6,0), I know that numpy has np.fromstring(mystr, dtype=int, sep='')yet the problem is I can't split my string to every digit of it, so numpy takes it as an one number. any idea how to convert my string to numpy array?
我有一个字符串mystr = "100110"（实际大小要大得多）我想将它转换为 numpy 数组mynumpy = [1, 0, 0, 1, 1, 0], mynumpy.shape = (6,0)，我知道 numpynp.fromstring(mystr, dtype=int, sep='')的问题是我无法将字符串拆分为它的每个数字，因此 numpy 将其视为一个数字。知道如何将我的字符串转换为 numpy 数组吗？
采纳答案by dragon2fly
listmay help you do that.
list可能会帮助你做到这一点。
import numpy as np
mystr = "100110"
print np.array(list(mystr))
# ['1' '0' '0' '1' '1' '0']
If you want to get numbers instead of string:
如果您想获取数字而不是字符串：
print np.array(list(mystr), dtype=int)
# [1 0 0 1 1 0]
回答by grc
You could read them as ASCII characters then subtract 48 (the ASCII value of 0). This should be the fastest way for large strings.
您可以将它们读取为 ASCII 字符，然后减去 48（ 的 ASCII 值0）。这应该是大字符串的最快方法。
>>> np.fromstring("100110", np.int8) - 48
array([1, 0, 0, 1, 1, 0], dtype=int8)
Alternatively, you could convert the string to a list of integers first:
或者，您可以先将字符串转换为整数列表：
>>> np.array(map(int, "100110"))
array([1, 0, 0, 1, 1, 0])
Edit: I did some quick timing and the first method is over 100x faster than converting it to a list first.
编辑：我做了一些快速计时，第一种方法比首先将其转换为列表快 100 倍以上。
回答by Hrushikesh Dhumal
Adding to above answers, numpy now gives a deprecation warning when you use fromstringDeprecationWarning: The binary mode of fromstring is deprecated, as it behaves surprisingly on unicode inputs. Use frombuffer instead.
A better option is to use the fromiter. It performs twice as fast. This is what I got in jupyter notebook -
添加到上述答案中，numpy 现在在您使用fromstringDeprecationWarning: The binary mode of fromstring is deprecated, as it behaves surprisingly on unicode inputs. Use frombuffer instead.
更好的选择是使用fromiter. 它的执行速度是原来的两倍。这是我在 jupyter notebook 中得到的 -
import numpy as np
mystr = "100110"
np.fromiter(mystr, dtype=int)
>> array([1, 0, 0, 1, 1, 0])
# Time comparison
%timeit np.array(list(mystr), dtype=int)
>> 3.5 μs ± 627 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
%timeit np.fromstring(mystr, np.int8) - 48
>> 3.52 μs ± 508 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
%timeit np.fromiter(mystr, dtype=int)
1.75 μs ± 133 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
