I have numpy 1.11 on my 15.10 Ubuntu machine and I need the same version on my 12.04 machine. I am not sure if this is possible at all and do not understand enough of linux to know.
我的15.10 Ubuntu机器上有numpy 1.11，我的12.04机器上需要相同的版本。我不确定这是否可行，并且不了解linux的知识。
I have tried
我努力了
sudo pip install numpy --upgrade
sudo apt-get dist-upgrade
I tried reinstalling, etc. and nothing seems to work. Are the libraries simply not compatible or is there a way to do this?
我尝试重新安装等等，似乎没有任何工作。这些库是不兼容的还是有办法做到这一点？
I don't want to mess with the ubuntu version because this is a shared lab machine and I am worried that other people's experiments could have issues if I did.
我不想弄乱ubuntu版本，因为这是一个共享的实验室机器，我担心如果我这样做，其他人的实验可能会有问题。
EDIT: When I run the upgrade it says that it has installed successfully but doesn't say anything about the version.
编辑：当我运行升级它说它已成功安装但没有说明版本。
here is the tail end of the output when I run the upgrade:
这是运行升级时输出的尾端：
types -D_FORTIFY_SOURCE=2 -g -fstack-protector --param=ssp-buffer-size=4 -Wformat -Werror=format-security build/temp.linux-x86_64-2.7/numpy/random/mtrand/mtrand.o build/temp.linux-x86_64-2.7/numpy/random/mtrand/randomkit.o build/temp.linux-x86_64-2.7/numpy/random/mtrand/initarray.o build/temp.linux-x86_64-2.7/numpy/random/mtrand/distributions.o -Lbuild/temp.linux-x86_64-2.7 -o build/lib.linux-x86_64-2.7/numpy/random/mtrand.so
Creating build/scripts.linux-x86_64-2.7/f2py
adding 'build/scripts.linux-x86_64-2.7/f2py' to scripts
changing mode of build/scripts.linux-x86_64-2.7/f2py from 644 to 755
warning: no previously-included files matching '*.pyo' found anywhere in distribution
warning: no previously-included files matching '*.pyd' found anywhere in distribution
changing mode of /usr/local/bin/f2py to 755
Successfully installed numpy
Cleaning up...
When I check my version:
当我检查我的版本时：
>>> import numpy
>>> numpy.version.version
'1.8.2'
4 个解决方案
#1
2
What happens when you run
跑步时会发生什么
sudo pip install numpy --upgrade
?
？
When I run it, I get this:
当我运行它时，我得到了这个：
Does it Collecting numpy
Downloading numpy-1.11.1.zip (4.7MB)
100% |████████████████████████████████| 4.7MB 108kB/s
Installing collected packages: numpy
Found existing installation: numpy 1.9.2
Uninstalling numpy-1.9.2:
Successfully uninstalled numpy-1.9.2
Running setup.py install for numpy
If you are seeing this, my next question would be: are you sure your paths are set correctly?
如果你看到这个，我的下一个问题是：你确定你的路径设置正确吗？
#2
2
I find it is more reliable and repeatable to manage your python environment using the Anaconda python distribution. Rather than using apt-get, you would use conda as your python package management system and it should work fairly consistently across platforms especially with major packages like numpy.
我发现使用Anaconda python发行版来管理你的python环境更加可靠和可重复。您可以使用conda作为您的python包管理系统，而不是使用apt-get，它应该在各个平台上相当一致，尤其是像numpy这样的主要软件包。
#3
2
Ok I resolved my Issue. I will summarize the problem:
好的我解决了我的问题。我将总结一下这个问题：
When I installed Scipy by installing the scipy pack it automatically resinstalls numpy 1.8 no materr what, even if it is just:
当我通过安装scipy包安装Scipy时，它会自动树立numpy 1.8 no materr什么，即使它只是：
sudo apt-get install python-scipy
What worked for me:
什么对我有用：
sudo apt-get purge python-numpy
sudo pip install numpy
sudo pip install scipy
sudo pip install -U scikit-learn
I don't know why the apt-get packages are not updated, maybe this is an issue that exists. Thank you all for your helpful orientations. :-)
我不知道为什么apt-get软件包没有更新，也许这是一个存在的问题。谢谢大家的帮助。 :-)
#4
1
This should work
这应该工作
pip install --upgrade numpy
Could you post the error message you received?
你能发贴你收到的错误信息吗？
The next time you are working on a project, you could use virtualenv. virtualenv will create an isolated environment for each of your projects with a copy of the python binary, the entire Python standard library, the pip installer as well as a copy of the site-packages directory. This way the environment would be local to you and would not affect the version of Python or its dependencies across all user accounts.
下次您正在处理项目时，可以使用virtualenv。 virtualenv将为每个项目创建一个隔离的环境，其中包含python二进制文件的副本，整个Python标准库，pip安装程序以及site-packages目录的副本。这样环境对您来说就是本地的，不会影响所有用户帐户的Python版本或其依赖关系。
#1
2
What happens when you run
跑步时会发生什么
sudo pip install numpy --upgrade
?
？
When I run it, I get this:
当我运行它时，我得到了这个：
Does it Collecting numpy
Downloading numpy-1.11.1.zip (4.7MB)
100% |████████████████████████████████| 4.7MB 108kB/s
Installing collected packages: numpy
Found existing installation: numpy 1.9.2
Uninstalling numpy-1.9.2:
Successfully uninstalled numpy-1.9.2
Running setup.py install for numpy
If you are seeing this, my next question would be: are you sure your paths are set correctly?
如果你看到这个，我的下一个问题是：你确定你的路径设置正确吗？
#2
2
I find it is more reliable and repeatable to manage your python environment using the Anaconda python distribution. Rather than using apt-get, you would use conda as your python package management system and it should work fairly consistently across platforms especially with major packages like numpy.
我发现使用Anaconda python发行版来管理你的python环境更加可靠和可重复。您可以使用conda作为您的python包管理系统，而不是使用apt-get，它应该在各个平台上相当一致，尤其是像numpy这样的主要软件包。
#3
2
Ok I resolved my Issue. I will summarize the problem:
好的我解决了我的问题。我将总结一下这个问题：
When I installed Scipy by installing the scipy pack it automatically resinstalls numpy 1.8 no materr what, even if it is just:
当我通过安装scipy包安装Scipy时，它会自动树立numpy 1.8 no materr什么，即使它只是：
sudo apt-get install python-scipy
What worked for me:
什么对我有用：
sudo apt-get purge python-numpy
sudo pip install numpy
sudo pip install scipy
sudo pip install -U scikit-learn
I don't know why the apt-get packages are not updated, maybe this is an issue that exists. Thank you all for your helpful orientations. :-)
我不知道为什么apt-get软件包没有更新，也许这是一个存在的问题。谢谢大家的帮助。 :-)
#4
1
This should work
这应该工作
pip install --upgrade numpy
Could you post the error message you received?
你能发贴你收到的错误信息吗？
The next time you are working on a project, you could use virtualenv. virtualenv will create an isolated environment for each of your projects with a copy of the python binary, the entire Python standard library, the pip installer as well as a copy of the site-packages directory. This way the environment would be local to you and would not affect the version of Python or its dependencies across all user accounts.
下次您正在处理项目时，可以使用virtualenv。 virtualenv将为每个项目创建一个隔离的环境，其中包含python二进制文件的副本，整个Python标准库，pip安装程序以及site-packages目录的副本。这样环境对您来说就是本地的，不会影响所有用户帐户的Python版本或其依赖关系。