[SciPy-user] Python(x,y) - Python for Scientists

Mark Bakker markbak@gmail....
Fri Apr 11 09:06:24 CDT 2008


Most excellent.
This was highly needed, I think.

Any chance you will also add a Mac version.
That would be even better,

Mark


>
> Message: 10
> Date: Thu, 10 Apr 2008 13:36:43 +0200 (CEST)
> From: "Python(x,y) - Python for Scientists" <contact@pythonxy.com>
> Subject: [SciPy-user] Python(x,y) - Python for Scientists
> To: scipy-user@scipy.org
> Message-ID: <53287.132.165.76.2.1207827403.squirrel@secure.nuxit.net>
> Content-Type: text/plain;charset=iso-8859-1
>
> Dear all,
>
> The scientists among you may be interested in Python(x,y), a new
> scientific-oriented Python distribution. This Python/Eclipse distribution
> is freely available as a one-click Windows installer (a release for
> GNU/Linux with similar features will follow soon):
> http://www.pythonxy.com
>
> Please do not hesitate to forward this announcement...
> (I am very sorry if you have already received this e-mail through
> "python-list" mailing list)
>
> Thanks a lots,
> PR
>
> --
> P. Raybaut
> Python(x,y)
> http://www.pythonxy.com
>
>
>
> ------------------------------
>
> Message: 11
> Date: Thu, 10 Apr 2008 14:09:12 +0200
> From: massimo sandal <massimo.sandal@unibo.it>
> Subject: Re: [SciPy-user] linear (polynomial) fit with error bars
> To: SciPy Users List <scipy-user@scipy.org>
> Message-ID: <47FE0368.8030403@unibo.it>
> Content-Type: text/plain; charset="iso-8859-15"
>
> Hi,
>
> Fabrice Silva ha scritto:
> > Using the diag input argument of leastsq :
> >
> >         from scipy import optimize
> >         def errfunc(a,X,Y):
> >             return Y-(a[0]*X+a[1])
> >         #b may be the vector containing the error bars sizes.
> >         weigths = 1./b
> >         a, success = optimize.leastsq(errfunc, [0,0],args=(X,Y),
> diag=weigths)
> >
> > You here give more importance to points having small error bars.
>
> Thanks for your advice. I am trying however to use your code, but I am
> stuck upon an error.
> Here is the script, that reads a very raw data file (see below):
>
> #!/usr/bin/env python
> from scipy import optimize
>
> def errfunc(a,X,Y):
>        return Y-(a[0]*X+a[1])
> #b may be the vector containing the error bars sizes.
>
> f=open("data.txt", "r")
> datf=f.readlines()
>
>
> numofdatapoints=len(datf)/3
> xval=[0.0]*numofdatapoints
> yval=[0.0]*numofdatapoints
> err=[0.0]*numofdatapoints
>
> # print len(datf)
> # print datf
>
> for i in range(numofdatapoints):
>    xval[i]=float(datf[i])
>    yval[i]=float(datf[i+numofdatapoints])
>    err[i]=float(datf[i+2*numofdatapoints])
>
> weigths=[0.0]*numofdatapoints
> for i in range(numofdatapoints):
>        weigths[i] = 1./err[i]
>
> w=[0.0]*numofdatapoints
> success=[0.0]*numofdatapoints
>
> w, success = optimize.leastsq(errfunc, [0,0], args=(xval,yval),
> diag=weigths)
>
> print valA
> print success
>
> -------
> data.txt:
> 118.877580092022
> 110.450590941286
> 108.684062758621
> 109.314800167624
> 103.090778781767
> 98.5714370869397
> 29.1
> 31.42
> 33.74
> 36.06
> 38.38
> 40.7
> 2.76010170015786
> 3.52143474842509
> 2.45059986418858
> 3.21254530326032
> 2.11363073382134
> 2.14664809861522
>
> -------
> and the script dies with the following error:
>
> massimo@calliope:~/Python/linfit$ python linfit.py
> Traceback (most recent call last):
>    File "linfit.py", line 31, in <module>
>      w, success = optimize.leastsq(errfunc, [0,0], args=(xval,yval),
> diag=weigths)
>    File "/usr/lib/python2.5/site-packages/scipy/optimize/minpack.py",
> line 262, in leastsq
>      m = check_func(func,x0,args,n)[0]
>    File "/usr/lib/python2.5/site-packages/scipy/optimize/minpack.py",
> line 12, in check_func
>      res = atleast_1d(apply(thefunc,args))
>    File "linfit.py", line 4, in errfunc
>      return Y-(a[0]*X+a[1])
> ValueError: shape mismatch: objects cannot be broadcast to a single shape
>
> which baffles me. What should I look for to understand what I am doing
> wrong?
>
> m.
> --
> Massimo Sandal
> University of Bologna
> Department of Biochemistry "G.Moruzzi"
>
> snail mail:
> Via Irnerio 48, 40126 Bologna, Italy
>
> email:
> massimo.sandal@unibo.it
>
> tel: +39-051-2094388
> fax: +39-051-2094387
>
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