Numerical numpy 两者相比较，如何？numpy比前两个可能都好，不过没有文档，如何使用呢。
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如果使用Numpy，可以利用Numeric的文档操作numpy，基本上都是相同的。你也可以在numpy的邮件列表中提问，可以很快得到回答。


在06-4-22，imcs ee <imcsee at gmail.com> 写道：
>
> Numerical numpy 两者相比较，如何？numpy比前两个可能都好，不过没有文档，如何使用呢。
>
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多谢，这么快就得到了回答，那我试试numpy了，看起来应该这个性能要好些。

On 4/22/06, zhang yunfeng <zhangyunfeng at gmail.com> wrote:
>
> 如果使用Numpy，可以利用Numeric的文档操作numpy，基本上都是相同的。你也可以在numpy的邮件列表中提问，可以很快得到回答。
>
>
> 在06-4-22，imcs ee <imcsee at gmail.com> 写道：
> >
> >  Numerical numpy 两者相比较，如何？numpy比前两个可能都好，不过没有文档，如何使用呢。
>
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这篇文章也许对你有帮助：
http://www-128.ibm.com/developerworks/cn/linux/l-cpnum/

在 06-4-22，imcs ee<imcsee at gmail.com> 写道：
> 多谢，这么快就得到了回答，那我试试numpy了，看起来应该这个性能要好些。
>
>
>
> On 4/22/06, zhang yunfeng <zhangyunfeng at gmail.com> wrote:
> >
> >
> 如果使用Numpy，可以利用Numeric的文档操作numpy，基本上都是相同的。你也可以在numpy的邮件列表中提问，可以很快得到回答。
> >
> >
> >
> > 在06-4-22，imcs ee <imcsee at gmail.com> 写道：
> > >
> >
> >
> > Numerical numpy 两者相比较，如何？numpy比前两个可能都好，不过没有文档，如何使用呢。
> >
> > _______________________________________________
> > python-chinese
> > Post: send python-chinese at lists.python.cn
> > Subscribe: send subscribe to
> python-chinese-request at lists.python.cn
> > Unsubscribe: send unsubscribe to
> python-chinese-request at lists.python.cn
> > Detail Info:
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> >
> >
> >
> >
> >
> > --
> > http://my.opera.com/zhangyunfeng
> > _______________________________________________
> > python-chinese
> > Post: send python-chinese at lists.python.cn
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numpy 好像和 Numeric合并了, 所以从长远来看, 建议使用Numeric, 而且还可以平滑转换到scipy.

On 4/22/06, imcs ee <imcsee at gmail.com> wrote:
> 多谢，这么快就得到了回答，那我试试numpy了，看起来应该这个性能要好些。
>
>
>
> On 4/22/06, zhang yunfeng <zhangyunfeng at gmail.com> wrote:
> >
> >
> 如果使用Numpy，可以利用Numeric的文档操作numpy，基本上都是相同的。你也可以在numpy的邮件列表中提问，可以很快得到回答。
> >
> >
> >
> > 在06-4-22，imcs ee <imcsee at gmail.com> 写道：
> > >
> >
> >
> > Numerical numpy 两者相比较，如何？numpy比前两个可能都好，不过没有文档，如何使用呢。
> >
> > _______________________________________________
> > python-chinese
> > Post: send python-chinese at lists.python.cn
> > Subscribe: send subscribe to
> python-chinese-request at lists.python.cn
> > Unsubscribe: send unsubscribe to
> python-chinese-request at lists.python.cn
> > Detail Info:
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> >
> >
> >
> >
> >
> > --
> > http://my.opera.com/zhangyunfeng
> > _______________________________________________
> > python-chinese
> > Post: send python-chinese at lists.python.cn
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多谢大家回复，

David Mertz 写得那篇看过了，写得很好，不过这篇只是介绍性质的，不太全面。

应该是numeric模块在前，后来又有人做了numarray，numeric的作者又来作numpy，希望能把前两者统一起来，而且目前文档是收费的，不知道为何不出书，而采取这样一种策略，可能出版还是比较麻烦的吧，尤其是这样比较细化的领域来说。

现在在看Numeric的文档，用numpy来对照着试试，最好是能在numpy上可以直接用了



On 4/23/06, hoxide Ma <hoxide at gmail.com> wrote:
>
> numpy 好像和 Numeric合并了, 所以从长远来看, 建议使用Numeric, 而且还可以平滑转换到scipy.
>
> On 4/22/06, imcs ee <imcsee at gmail.com> wrote:
> > 多谢，这么快就得到了回答，那我试试numpy了，看起来应该这个性能要好些。
> >
> >
> >
> > On 4/22/06, zhang yunfeng <zhangyunfeng at gmail.com> wrote:
> > >
> > >
> > 如果使用Numpy，可以利用Numeric的文档操作numpy，基本上都是相同的。你也可以在numpy的邮件列表中提问，可以很快得到回答。
> > >
> > >
> > >
> > > 在06-4-22，imcs ee <imcsee at gmail.com> 写道：
> > > >
> > >
> > >
> > > Numerical numpy 两者相比较，如何？numpy比前两个可能都好，不过没有文档，如何使用呢。
> > >
> > > _______________________________________________
> > > python-chinese
> > > Post: send python-chinese at lists.python.cn
> > > Subscribe: send subscribe to
> > python-chinese-request at lists.python.cn
> > > Unsubscribe: send unsubscribe to
> > python-chinese-request at lists.python.cn
> > > Detail Info:
> > http://python.cn/mailman/listinfo/python-chinese
> > >
> > >
> > >
> > >
> > >
> > > --
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> >
>
>
> --
> ==========================================================
>
> A student of Math in Soochow University in China.
> Interested in Math, Python, Octave, Lisp, Maxima, Prolog and .NET/MONO.
> HomePage: http://hoxide.googlepages.com
> Blog: http://blog.sina.com.cn/blog/1142604745
> http://www.cublog.cn/u/2015/
> http://spaces.msn.com/hoxide
> Wiki: http://wiki.woodpecker.org.cn/moin/Hoxide
>
> _______________________________________________
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