blocks|key|904213|text|首先，我建议你浏览NumPy的Quickstart+tutorial，它可能会帮助你解决这些基本问题。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|904214|您可以直接从列表创建数组，如下所示：|904215|import+numpy+as+np
a+=+np.array(+[2,3,4]+)|code-block|syntax|javascript|904216|或者以同样的方式从嵌套列表中获取：|904217|import+numpy+as+np
a+=+np.array(+[[2,3,4],+[3,4,5]]+)|904218|entityMap|0|LINK|mutability|MUTABLE|url|https://numpy.org/devdocs/user/quickstart.html^0|F|J|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@$A|X|B|Y|1|Z]]|C|$]]|$1|D|3|E|5|6|7|10|8|@]|9|@]|C|$]]|$1|F|3|G|5|H|7|11|8|@]|9|@]|C|$I|J]]|$1|K|3|L|5|6|7|12|8|@]|9|@]|C|$]]|$1|M|3|N|5|H|7|13|8|@]|9|@]|C|$I|J]]|$1|O|3|-4|5|6|7|14|8|@]|9|@]|C|$]]]|P|$Q|$5|R|S|T|C|$U|V]]]]

First of all, I'd recommend you to go through NumPy's <a href="https://numpy.org/devdocs/user/quickstart.html" rel="noreferrer">Quickstart tutorial</a>, which will probably help with these basic questions.
You can directly create an array from a list as:
<pre><code>import numpy as np
a = np.array( [2,3,4] )
</code></pre>
Or from a from a nested list in the same way:
<pre><code>import numpy as np
a = np.array( [[2,3,4], [3,4,5]] )
</code></pre>

blocks|key|904145|text|你是说像这样的东西？|type|unstyled|depth|inlineStyleRanges|entityRanges|data|904146|from+numpy++import+array
a+=+array(+your_list+)|code-block|syntax|javascript|904147|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

you mean something like this ?

<pre><code>from numpy import array
a = array( your_list )
</code></pre>

blocks|key|904132|text|Yes+it+is:|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|904133|a+=+numpy.array([1,2,3])|code-block|syntax|javascript|904134|entityMap|0|LINK|mutability|MUTABLE|url|http://www.scipy.org/Tentative_NumPy_Tutorial#head-d3f8e5fe9b903f3c3b2a5c0dfceb60d71602cf93^0|0|A|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@$A|R|B|S|1|T]]|C|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|C|$G|H]]|$1|I|3|-4|5|6|7|V|8|@]|9|@]|C|$]]]|J|$K|$5|L|M|N|C|$O|P]]]]

<a href="http://www.scipy.org/Tentative_NumPy_Tutorial#head-d3f8e5fe9b903f3c3b2a5c0dfceb60d71602cf93" rel="noreferrer">Yes it is:</a>

<pre><code>a = numpy.array([1,2,3])
</code></pre>

blocks|key|904279|text|是否要将其另存为文件？|type|unstyled|depth|inlineStyleRanges|entityRanges|data|904280|import+numpy+as+np

myList+=+[1,+2,+3]

np.array(myList).dump(open('array.npy',+'wb'))|code-block|syntax|javascript|904281|..。然后阅读：|904282|myArray+=+np.load(open('array.npy',+'rb'))|904283|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

You want to save it as a file?

<pre><code>import numpy as np

myList = [1, 2, 3]

np.array(myList).dump(open('array.npy', 'wb'))
</code></pre>

... and then read:

<pre><code>myArray = np.load(open('array.npy', 'rb'))
</code></pre>

blocks|key|687859|text|例如，您可以使用numpy.asarray将列表转换为数组：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|687860|>>>+a+=+[1,+2]
>>>+np.asarray(a)
array([1,+2])|code-block|syntax|javascript|687861|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.scipy.org/doc/numpy/reference/generated/numpy.asarray.html^0|8|D|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@$A|R|B|S|1|T]]|C|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|C|$G|H]]|$1|I|3|-4|5|6|7|V|8|@]|9|@]|C|$]]]|J|$K|$5|L|M|N|C|$O|P]]]]

You can use <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.asarray.html" rel="noreferrer">numpy.asarray</a>, for example to convert a list into an array:

<pre><code>&gt;&gt;&gt; a = [1, 2]
&gt;&gt;&gt; np.asarray(a)
array([1, 2])
</code></pre>

blocks|key|904320|text|我想，您的意思是将列表转换为numpy数组？然后,|type|unstyled|depth|inlineStyleRanges|entityRanges|data|904321|import+numpy+as+np

#+b+is+some+list,+then+...++++
a+=+np.array(b).reshape(lengthDim0,+lengthDim1);|code-block|syntax|javascript|904322|给出a作为列表b的数组，其形状如重塑中所示。|904323|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|L|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|M|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

I suppose, you mean converting a list into a numpy array?
Then,

<pre><code>import numpy as np

# b is some list, then ... 
a = np.array(b).reshape(lengthDim0, lengthDim1);
</code></pre>

gives you a as an array of list b in the shape given in reshape.

blocks|key|687875|text|下面是一个更完整的示例：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|687876|import+csv
import+numpy+as+np

with+open('filename','rb')+as+csvfile:
+++++cdl+=+list(+csv.reader(csvfile,delimiter='\t'))
+++++print+"Number+of+records+=+"+%2B+str(len(cdl))

#then+later

npcdl+=+np.array(cdl)|code-block|syntax|javascript|687877|希望这能有所帮助！！|687878|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|L|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|M|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

Here is a more complete example:

<pre><code>import csv
import numpy as np

with open('filename','rb') as csvfile:
 cdl = list( csv.reader(csvfile,delimiter='\t'))
 print "Number of records = " + str(len(cdl))

#then later

npcdl = np.array(cdl)
</code></pre>

Hope this helps!!

blocks|key|687911|text|import+numpy+as+np+

...+##+other+code|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|687912|一些列表理解|unstyled|687913|t=[nodel[+nodenext[i][j]+]+for+j+in+idx]
++++++++++++#for+each+link,+find+the+node+lables+
++++++++++++#t+is+the+list+of+node+labels+|687914|使用numpy库中指定的array方法将列表转换为numpy数组。|687915|t=np.array(t)|687916|这可能会有帮助：https://numpy.org/devdocs/user/basics.creation.html|offset|length|687917|entityMap|0|LINK|mutability|MUTABLE|url|https://numpy.org/devdocs/user/basics.creation.html^0|0|0|0|0|0|8|1F|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@]|9|@]|A|$B|C]]|$1|D|3|E|5|F|7|Z|8|@]|9|@]|A|$]]|$1|G|3|H|5|6|7|10|8|@]|9|@]|A|$B|C]]|$1|I|3|J|5|F|7|11|8|@]|9|@]|A|$]]|$1|K|3|L|5|6|7|12|8|@]|9|@]|A|$B|C]]|$1|M|3|N|5|F|7|13|8|@]|9|@$O|14|P|15|1|16]]|A|$]]|$1|Q|3|-4|5|F|7|17|8|@]|9|@]|A|$]]]|R|$S|$5|T|U|V|A|$W|X]]]]

<pre><code>import numpy as np 

... ## other code
</code></pre>

some list comprehension

<pre><code>t=[nodel[ nodenext[i][j] ] for j in idx]
 #for each link, find the node lables 
 #t is the list of node labels 
</code></pre>

Convert the list to a numpy array using the array method specified in the numpy library.

<pre><code>t=np.array(t)
</code></pre>

This may be helpful: <a href="https://numpy.org/devdocs/user/basics.creation.html" rel="nofollow noreferrer">https://numpy.org/devdocs/user/basics.creation.html</a>

blocks|key|687924|text|也许：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|687925|import+numpy+as+np
a=[[1,1],[2,2]]
b=np.asarray(a)
print(type(b))|code-block|syntax|javascript|687926|输出：|687927|<class+'numpy.ndarray'>|687928|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

maybe:

<pre><code>import numpy as np
a=[[1,1],[2,2]]
b=np.asarray(a)
print(type(b))
</code></pre>

output:

<pre><code>&lt;class 'numpy.ndarray'&gt;
</code></pre>

Is possible to construct a NumPy array from a python list?

How to save a list as numpy array in python?

可以从python列表构造NumPy数组吗？

问如何在python中将列表保存为numpy数组？
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