File:MDKQ6 anim.gif

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MDKQ6_anim.gif (450 × 350 pixels, file size: 42 KB, MIME type: image/gif, looped, 10 frames, 1.0 s)

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Summary

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Description
Deutsch: Teilbild einer Animation Polynomapproximation unterschiedlicher Polynomordnung
Date
Source MDKQ anim.gif
Author Johannes Kalliauer
Other versions File:MDKQ_anim.gif

Licensing

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I, the copyright holder of this work, hereby publish it under the following license:
Creative Commons CC-Zero This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication.
The person who associated a work with this deed has dedicated the work to the public domain by waiving all of their rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.

Quellen: Skript zur Bildgenerierung

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Erzeugungsskript, um die Grafik zu erstellen.

Anleitung

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Benötigte Open-Source-Software:

Nach der Installation von Python den Quelltext in eine Datei mdkq.py kopieren und starten durch Doppelklicken oder in der Konsole durch Eingabe von

python mdkq.py

Python-Skript

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This plot was created with Matplotlib by v.
#This source code is public domain
#Created by Christian Schirm
#Edited by Johannes Kalliauer
import numpy, pylab
from matplotlib.font_manager import FontProperties
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from numpy.random import randn

x=[1,2,3,4,5,6]
y=[2.0,2.5,2.5,3.4,3.7,6.6]

for N in range(1,7):
   A=numpy.zeros((N,N))
   for i in range(N):
       for j in range(N):
           A[i,j]=sum(xi**(i j) for xi in x)
   b=numpy.zeros((N))
   for i in range(N):
       b[i]=sum(xi**(i)*yi for xi,yi in zip(x,y))
   c=numpy.linalg.solve(A, b)
   xr=numpy.asarray(x)
   yr=numpy.sum([c[i]*xr**i for i in range(len(c))],axis=0)
   residuen=[]
   for i in range(len(x)): residuen =[[xr[i],xr[i]],[y[i],yr[i]],'g-']
   xneu=numpy.linspace(0, 8, num=100)
   yneu=numpy.sum([c[i]*xneu**i for i in range(len(c))],axis=0)
   plt.clf()
   fig = plt.figure(figsize=(4.5, 3.5))
   fig.subplotpars.bottom=0.13
   y0=plt.plot(*residuen[:-3])
   plt.setp(y0, color='#80d080', linewidth=1.5)
   #y0=plt.plot(*residuen[-3:], label="Residuen")
   y0,=plt.plot(*residuen[-3:])
   plt.setp(y0, color='#80d080', linewidth=1.5)
   #y2=plt.plot(xneu,yneu,'r-', label="Modellfunktion")
   y2,=plt.plot(xneu,yneu,'r-')
   #y1=plt.plot(x,y,'o', label="Messpunkte")
   y1,=plt.plot(x,y,'o')
   plt.xlabel('x')
   plt.ylabel('y')
   font = FontProperties()
   font.set_size('medium')
   leg = plt.legend([y1,y2,y0],['Messpunkte','Modellfunktion','Residuen'],frameon=True,loc='lower right',labelspacing=0.3,prop=font)
   #leg = plt.legend(frameon=True,loc='lower right',labelspacing=0.3,prop=font)
   plt.grid(True)
   plt.axis([0, 8, 0, 8])
   plt.text(1,7, "Polynomgrad " str(N-1),bbox=dict(boxstyle="square,pad=0.5",color='white',ec='black',fill=True))
   #plt.show()
   plt.savefig('MDKQ_anim%i.png'%N)
   plt.savefig('test.eps', format='eps', dpi=900)
   plt.savefig("MDKQ_anim%i.svg"%N)

File history

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Date/TimeThumbnailDimensionsUserComment
current16:23, 25 June 2017Thumbnail for version as of 16:23, 25 June 2017450 × 350 (42 KB)JoKalliauer (talk | contribs)

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