File:MDKQ6 anim.gif
MDKQ6_anim.gif (450 × 350 像素,檔案大細:42 KB ,MIME類型:image/gif、循環、10格、1.0 s)
摘要
描述MDKQ6 anim.gif |
Deutsch: Teilbild einer Animation Polynomapproximation unterschiedlicher Polynomordnung |
日期 | |
來源 | MDKQ anim.gif |
作者 | Johannes Kalliauer |
Other versions | File:MDKQ_anim.gif |
協議
我,呢份作品嘅作者,決定用以下許可發佈呢件作品:
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
Erzeugungsskript, um die Grafik zu erstellen.
Anleitung
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
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=[1,2,3,4,5,6]
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)
Items portrayed in this file
圖中顯示嘅係
25 6 2017
image/gif
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日期/時間 | 縮圖 | 尺寸 | 用戶 | 註解 | |
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現時 | 2017年6月25號 (日) 16:23 | 450 × 350(42 KB) | JoKalliauer |
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