File:MDKQ anim ohne Ausreiser.gif
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MDKQ_anim_ohne_Ausreiser.gif (450 × 350 pixels, file size: 22 KB, MIME type: image/gif, 6 frames, 6.0 s)
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Summary
[edit]DescriptionMDKQ anim ohne Ausreiser.gif |
Deutsch: Teilbild einer Animation Polynomapproximation unterschiedlicher Polynomordnung |
Date | |
Source | MDKQ6 anim.gif |
Author | Johannes Kalliauer |
Other versions | File:MDKQ_anim.gif |
This image was improved or created by the Wikigraphists of the Graphic Lab (de). You can propose images to clean up, improve, create or translate as well. |
Licensing
[edit]I, the copyright holder of this work, hereby publish it under the following license:
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.
http://creativecommons.org/publicdomain/zero/1.0/deed.enCC0Creative Commons Zero, Public Domain Dedicationfalsefalse |
Quellen: Skript zur Bildgenerierung
[edit]Erzeugungsskript, um die Grafik zu erstellen.
Anleitung
[edit]Benötigte Open-Source-Software:
- Python
- Python-Paket: numpy
- Python-Paket: matplotlib
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
[edit]This plot was created with Matplotlib.
#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=[1,2,3,4,5,7]
y=[2.0,2.5,2.5,3.4,3.7,3]
for N in range(1,8):
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
Click on a date/time to view the file as it appeared at that time.
Date/Time | Thumbnail | Dimensions | User | Comment | |
---|---|---|---|---|---|
current | 18:08, 1 July 2017 | 450 × 350 (22 KB) | JoKalliauer (talk | contribs) | removed last pic | |
18:04, 1 July 2017 | 450 × 350 (25 KB) | JoKalliauer (talk | contribs) |
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