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(Python Numpy) 如何从给定的 2D 数组创建新的 3D 数组?(python用numpy创建二维数组)

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如果您想了解(Python Numpy) 如何从给定的 2D 数组创建新的 3D 数组?的相关知识,那么本文是一篇不可错过的文章,我们将对python用numpy创建二维数组进行全面详尽的解释,并且为您提供关于"import numpy as np" ImportError: No module named numpy、3.7Python 数据处理篇之 Numpy 系列 (七)---Numpy 的统计函数、Difference between import numpy and import numpy as np、Discord.js |如何从给定的 jsondata 链接设置输出随机?的有价值的信息。

本文目录一览:

(Python Numpy) 如何从给定的 2D 数组创建新的 3D 数组?(python用numpy创建二维数组)

(Python Numpy) 如何从给定的 2D 数组创建新的 3D 数组?(python用numpy创建二维数组)

如何解决(Python Numpy) 如何从给定的 2D 数组创建新的 3D 数组?

我想做这样的事情:

我给出了一个 2D numpy 数组:

[[ 1,2,3],[ 4,5,6],[ 7,8,9]]

我想得到一个 3D numpy 数组:

[[[1,1,1],[2,2],[3,3,3]],[[4,4,4],[5,5],[6,6,6]],[[7,7,7],[8,8],[9,9,9]]]

numpy 有没有可以做这个转换的函数?

解决方法

可以使用np.tile。在此之前,需要在数组末尾添加一个维度。

In [28]: x = np.array([[ 1,2,3],...:  [ 4,5,6],...:  [ 7,8,9]])

In [29]: np.tile(x[...,None],3)
Out[29]: 
array([[[1,1,1],[2,2],[3,3,3]],[[4,4,4],[5,5],[6,6,6]],[[7,7,7],[8,8],[9,9,9]]])
,

首先使用 arr[:,:,np.newaxis] 扩展二维数组的维度,这将维度从 (3,3) 更改为 (3,1)。现在沿着第三维重复这个 3D 数组。

使用:

arr = np.repeat(arr[:,np.newaxis],-1)

输出:

>>> np.repeat(arr[:,-1)
array([[[1,9]]])

"import numpy as np" ImportError: No module named numpy

问题:没有安装 numpy

解决方法:

下载文件,安装

numpy-1.8.2-win32-superpack-python2.7

安装运行 import numpy,出现

Traceback (most recent call last):
  File "<pyshell#2>", line 1, in <module>
    import numpy
  File "C:\Python27\lib\site-packages\numpy\__init__.py", line 153, in <module>
    from . import add_newdocs
  File "C:\Python27\lib\site-packages\numpy\add_newdocs.py", line 13, in <module>
    from numpy.lib import add_newdoc
  File "C:\Python27\lib\site-packages\numpy\lib\__init__.py", line 8, in <module>
    from .type_check import *
  File "C:\Python27\lib\site-packages\numpy\lib\type_check.py", line 11, in <module>
    import numpy.core.numeric as _nx
  File "C:\Python27\lib\site-packages\numpy\core\__init__.py", line 6, in <module>
    from . import multiarray
ImportError: DLL load failed: %1 不是有效的 Win32 应用程序。

原因是:python 装的是 64 位的,numpy 装的是 32 位的

重新安装 numpy 为:numpy-1.8.0-win64-py2.7

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3.7Python 数据处理篇之 Numpy 系列 (七)---Numpy 的统计函数

3.7Python 数据处理篇之 Numpy 系列 (七)---Numpy 的统计函数

目录

[TOC]

前言

具体我们来学 Numpy 的统计函数

(一)函数一览表

调用方式:np.*

.sum(a) 对数组 a 求和
.mean(a) 求数学期望
.average(a) 求平均值
.std(a) 求标准差
.var(a) 求方差
.ptp(a) 求极差
.median(a) 求中值,即中位数
.min(a) 求最大值
.max(a) 求最小值
.argmin(a) 求最小值的下标,都处里为一维的下标
.argmax(a) 求最大值的下标,都处里为一维的下标
.unravel_index(index, shape) g 根据 shape, 由一维的下标生成多维的下标

(二)统计函数 1

(1)说明

(2)输出

.sum(a)

.mean(a)

.average(a)

.std(a)

.var(a)

(三)统计函数 2

(1)说明

(2)输出

.max(a) .min(a)

.ptp(a)

.median(a)

.argmin(a)

.argmax(a)

.unravel_index(index,shape)

作者:Mark

日期:2019/02/11 周一

Difference between import numpy and import numpy as np

Difference between import numpy and import numpy as np

Difference between import numpy and import numpy as np

up vote 18 down vote favorite

5

I understand that when possible one should use

import numpy as np

This helps keep away any conflict due to namespaces. But I have noticed that while the command below works

import numpy.f2py as myf2py

the following does not

import numpy as np
np.f2py #throws no module named f2py

Can someone please explain this?

python numpy

shareimprove this question

edited Mar 24 ''14 at 23:20

mu 無

24.7k104471

asked Mar 24 ''14 at 23:19

user1318806

3001311

 
1  

@roippi have you tried exit your python and enter it and just do import numpy then numpy.f2py ? It throws an error in my case too – aha Mar 24 ''14 at 23:24

1  

Importing a module doesn''t import sub-modules. You need to explicitly import the numpy.f2py module regardless of whether or not/how numpy itself has been imported. – alecb Mar 24 ''14 at 23:39

add a comment

4 Answers

active oldest votes

 

up vote 13 down vote

numpy is the top package name, and doing import numpy doesn''t import submodule numpy.f2py.

When you do import numpy it creats a link that points to numpy, but numpy is not further linked to f2py. The link is established when you do import numpy.f2py

In your above code:

import numpy as np # np is an alias pointing to numpy, but at this point numpy is not linked to numpy.f2py
import numpy.f2py as myf2py # this command makes numpy link to numpy.f2py. myf2py is another alias pointing to numpy.f2py as well

Here is the difference between import numpy.f2py and import numpy.f2py as myf2py:

  • import numpy.f2py
    • put numpy into local symbol table(pointing to numpy), and numpy is linked to numpy.f2py
    • both numpy and numpy.f2py are accessible
  • import numpy.f2py as myf2py
    • put my2py into local symbol table(pointing to numpy.f2py)
    • Its parent numpy is not added into local symbol table. Therefore you can not access numpy directly

shareimprove this answer

edited Mar 25 ''14 at 0:31

answered Mar 24 ''14 at 23:33

aha

1,2291718

 

add a comment

 

up vote 7 down vote

The import as syntax was introduced in PEP 221 and is well documented there.

When you import a module via

import numpy

the numpy package is bound to the local variable numpy. The import as syntax simply allows you to bind the import to the local variable name of your choice (usually to avoid name collisions, shorten verbose module names, or standardize access to modules with compatible APIs).

Thus,

import numpy as np

is equivalent to,

import numpy
np = numpy
del numpy

When trying to understand this mechanism, it''s worth remembering that import numpy actually means import numpy as numpy.

When importing a submodule, you must refer to the full parent module name, since the importing mechanics happen at a higher level than the local variable scope. i.e.

import numpy as np
import numpy.f2py   # OK
import np.f2py      # ImportError

I also take issue with your assertion that "where possible one should [import numpy as np]". This is done for historical reasons, mostly because people get tired very quickly of prefixing every operation with numpy. It has never prevented a name collision for me (laziness of programmers actually suggests there''s a higher probability of causing a collision with np)

Finally, to round out my exposé, here are 2 interesting uses of the import as mechanism that you should be aware of:

1. long subimports

import scipy.ndimage.interpolation as warp
warp.affine_transform(I, ...)

2. compatible APIs

try:
    import pyfftw.interfaces.numpy_fft as fft
except:
    import numpy.fft as fft
# call fft.ifft(If) with fftw or the numpy fallback under a common name

shareimprove this answer

answered Mar 25 ''14 at 0:59

hbristow

68345

 

add a comment

 

up vote 1 down vote

numpy.f2py is actually a submodule of numpy, and therefore has to be imported separately from numpy. As aha said before:

When you do import numpy it creats a link that points to numpy, but numpy is not further linked to f2py. The link is established when you do import numpy.f2py

when you call the statement import numpy as np, you are shortening the phrase "numpy" to "np" to make your code easier to read. It also helps to avoid namespace issues. (tkinter and ttk are a good example of what can happen when you do have that issue. The UIs look extremely different.)

shareimprove this answer

answered Mar 24 ''14 at 23:47

bspymaster

760923

 

add a comment

 

up vote 1 down vote

This is a language feature. f2py is a subpackage of the module numpy and must be loaded separately.

This feature allows:

  • you to load from numpy only the packages you need, speeding up execution.
  • the developers of f2py to have namespace separation from the developers of another subpackage.

Notice however that import numpy.f2py or its variant import numpy.f2py as myf2py are still loading the parent module numpy.

Said that, when you run

import numpy as np
np.f2py

You receive an AttributeError because f2py is not an attribute of numpy, because the __init__() of the package numpy did not declare in its scope anything about the subpackage f2py.

shareimprove this answer

answered Mar 24 ''14 at 23:57

gg349

7,67321739

 
    

when you do import numpy.f2py as myf2py, how do you access its parent numpy? it seems import numpy.f2py allows you to access its parent numpy, but import numpy.f2py as myf2py doesn''t – aha Mar 25 ''14 at 0:00

    

You don''t access it because you decided you didn''t want to use anything from numpy, and you only care of using the subpackage. It is similar to using from foo import bar: the name foo will not be accessible. See the comment after the first example of the docs, LINK – gg349 Mar 25 ''14 at 0:05

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Discord.js |如何从给定的 jsondata 链接设置输出随机?

Discord.js |如何从给定的 jsondata 链接设置输出随机?

如何解决Discord.js |如何从给定的 jsondata 链接设置输出随机?

当人们执行命令 !hp-random 时,我正在尝试创建随机的 gif 提供者。我在这里做了一个 jsonData const:

const jsonData = {
    "1":"https://media.giphy.com/media/12nfFCZA0vyrSw/giphy.gif","2":"https://media.giphy.com/media/26BRzozg4TCBXv6QU/giphy.gif","3":"https://media.giphy.com/media/PXvCWUnmqVdks/giphy.gif","4":"https://media.giphy.com/media/7Yif3ae99ksCc/giphy.gif","5":"https://media.giphy.com/media/R65bZxLDrX2Mw/giphy.gif","6":"https://media.giphy.com/media/6jemHpKLDe27C/giphy.gif","7":"https://media.giphy.com/media/LLxwPAjfpLak8/giphy.gif","8":"https://media.giphy.com/media/oydiov5VxxXcG0mu1P/giphy.gif","9":"https://media.giphy.com/media/S3F8kkGTHZ4Y/giphy.gif","10":"https://media.giphy.com/media/RLo8seQ4drmAW02wSA/giphy.gif",}

紧接着我把这个:

const values = Object.values(jsonData)
const randomValue = values[parseInt(Math.random(values.length))]

module.exports = {
    name: ''hp-random'',description: "Gives random gif in chat",execute(client,message,args,discord) {
        console.log(randomValue);

        //message.channel.send(`${randomValue}`);
    }
}

我的问题是它只输出 jsonData 中的前 1 个而不是其他 9 个输出:只输出这个>"https://media.giphy.com/media/12nfFCZA0vyrSw/giphy.gif"

控制台:(我在不和谐聊天中执行命令)

    \\discord bot> node .
I''m working
https://media.giphy.com/media/12nfFCZA0vyrSw/giphy.gif
https://media.giphy.com/media/12nfFCZA0vyrSw/giphy.gif
https://media.giphy.com/media/12nfFCZA0vyrSw/giphy.gif
https://media.giphy.com/media/12nfFCZA0vyrSw/giphy.gif
https://media.giphy.com/media/12nfFCZA0vyrSw/giphy.gif

解决方法

首先,您需要在 execute 方法中移动 const randomValue = values[parseInt(Math.random(values.length))],以便在每次收到消息时创建一个新的随机变量。

另一个问题是您的随机函数。 Math.random() 不接受任何参数,因此您不能调用 Math.random(values.length) 并期望将其称为 0 到 1 之间的数字以外的任何其他值。您需要将随机值乘以数组代替:

module.exports = {
  name: ''hp-random'',description: ''Gives random gif in chat'',execute(client,message,args,Discord) {
    const values = Object.values(jsonData);
    const randomValue = values[parseInt(Math.random() * values.length)];

    console.log(randomValue);

    // message.channel.send(randomValue);
  },};

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