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#!/bin/env python3
# -*- coding: UTF-8 -*-
# Gereric: Draw line.
# Recolic Keghart, Apr 29, 2017.
import numpy
from scipy.optimize import leastsq
import matplotlib.pyplot as plt
from matplotlib import rcParams
def dotMultiply(vctA, vctB):
if len(vctA) != len(vctB):
print("Error: While vcta is ", vctA, " and vctb is ", vctB)
raise ValueError("dotmulti needs lena == lenb.")
ans = 0
for a, b in zip(vctA, vctB):
ans += a * b
return ans
def GetMap(parrX, parrY, windowSizeX=12, windowSizeY=8, extendXRate=1, extendYRate=1, line=False, passO=False, maxXPower=1, inverseK=False):
'''
Arguments:
parrX and parrY: array of coordinates of points. Ex: GetMap([1,2,3,4,5], [1,2,3,4,5]) -> y=x
line: Should I draw a fitting line?
passO: Should the fitting line pass (0,0)? That's saying, should k0 be zero?
maxXPower: If I should draw a fitting line, what polynomial function should I use? Ex: GetMap([1,2,3,4,5], [1,4,9,16,25], line=True, maxXPower) -> y=x^2
inverseK: Usually, I'm drawing the curl `y=KX`, while K=[k0,k1,k2,...], X=[x^0,x^1,x^2,...]. If this switch is set, I'll drawing the curl `KY=x`. Don't worry, this switch is transparent to you.
Ex: GetMap([0,1,1,4,4,9,9], [0,1,-1,2,-2,3,-3], maxXPower=2, line=True, inverseK=True) -> y^2=x
ReturnValue:
void
'''
maxX, maxY = max(arrX) * extendXRate, max(arrY) * extendYRate
minX, minY = min(arrX) * extendXRate, min(arrY) * extendYRate
# y = [k0 k1 k2 ...] dot [x^0 x^1 x^2 ...]
print('Your input: ', arrX, '|', arrY)
print('Data collection done. Generating result...')
X, Y = numpy.array(arrX), numpy.array(arrY)
def lineFunc(k, x):
vctX = [x ** power for power in range(maxXPower + 1)]
vctX[0] = 0
return dotMultiply(k, vctX)
kInit = [1 for _ in range(maxXPower + 1)]
kInit[0] = 0 # guarantee passO.
if inverseK:
kFinal, _ = leastsq(lossFunc, kInit, args=(Y, X))
print('Fitting line done. k^-1=', kFinal)
print('Fitting line done. k=', kFinal)
else:
print('Drawing map without fitting a line...')
# Draw function map.
rcParams['grid.color'] = 'blue'
rcParams['grid.linewidth'] = 0.2
plt.figure(figsize=(windowSizeX, windowSizeY))
plt.scatter(X, Y, color="red", label="Sample Point", linewidth=3)
if inverseK:
py = numpy.linspace(minY, maxY, 1000)
px = dotMultiply(kFinal, [py ** power for power in range(maxXPower + 1)])
else:
px = numpy.linspace(minX, maxX, 1000)
py = dotMultiply(kFinal, [px ** power for power in range(maxXPower + 1)])
plt.plot(px, py, color="orange", label="Fitting Line", linewidth=2)
plt.legend()
plt.grid()
plt.show()
def toFloat(sstr):
if sstr == '':
return 0.0
else: