python/ez_plot_curva3_large.py at master · elijivp/python · GitHub

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#!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
import math

koef = 1000
firstlvl = 5000
rounds = 10
totallvl = 100

x = np.linspace(-2.0, 2.0, 1000)

sign = lambda c: 1 if c > 0 else -1 if c < 0 else 1
stepNeg = lambda c: 0 if c >= 0 else 1

# coeff = 0.6
# mathf = [  (1.0 / (1.0 + (1/coeff - 1)*x)) for coeff in [0.5, 0.6, 0.7, 0.8, 0.9 ] ]

# mathf = [ coeff + ((1.0-coeff)*0.2)*(x-1)/(1.0 + abs(x-1)) for coeff in [ 0.5, 0.6, 0.7, 0.8, 0.9 ] ]
# mathf = [ coeff + ((1.0-coeff)*0.2)*(x-1)/(1.0 + abs(x-1)) for coeff in [ 0.5, 0.6, 0.7, 0.8, 0.9 ] ]

# mathf = [ 1.0 + 0.75*2*(x-0.25)*1 / (1.0 + 2*abs(x-0.25)*1) ]

# mathf = [ np.exp(x) ]

# mathf = [ (5)*(1 - 1/(1  + (x+0.5) - (x+0.5)**2)) ]

# mathf = [ 4 - 5/(1.25 - c*(x+1)*x) for c in [0, 0.25, 0.5, 0.75, 1.0] ]

# mathf = [ 4 - 5/(1.25 - c*x*x) if c != 0 else -x*x for c in [0, 0.25, 0.5, 0.75, 1.0] ]

# mathf = [ 4 - 5/(1.25 - c*x*x) if c != 0 else -x*x for c in [0, 0.25, 0.5, 0.75, 1.0] ]

getC = lambda a,b: b/float(a) - b/(a+1.0)

# A = 5
# B = 2.0

mathf = [ -x*x,
          # 5 - 10/(2.0 - 0.3333333*x*x),
          # 2 - 10/(5.0 - 1.666666*x*x),
          # 4 - 5/(1.25 - 0.25*(x+0)*x)

          # np.sin(math.pi*2*x)/(math.pi*2*x) - 1.0
          -x/(1 - x/(1+x))
        ]

mathf = [ 0.5 + 0.3*2*(x-c)*4 / (1.0 + 2*abs(x-c)*4) for c in [0.1, 0.4, 0.7] ]
# mathf = [ 1.0 - (1.0 / (1.0 + (1.0/(1.0 - c)-1.0)*x)) for c in [0.1, 0.99] ]
# mathf = [ 1.0/(1.0 + (1.0 - c)/c*(1 - x)) for c in [0.001, 0.99] ]
# mathf.extend([ (A - B/(B/A - getC(A,B)*x*x)) for A in [1,5,10000] ])

x = np.linspace(0.0, 1.0, 100)

def getZ(coeff):
  z = np.zeros(100)
  for l in range(len(z)):
    z[l] = z[l-1]*coeff + (1.0 - coeff)*1.0 if l > 0 else 0
  return z
mathf = [ getZ(c) for c in [0.1, 0.4, 0.7, 0.9] ]

# mathf.extend([ (A - B/(B/float(A) - getC(A,B)*x*x)) for A,B in [ [1,2], [4,5], [10,20]] ])


color = [ 'r.', 'g.', 'b.', 'y.', 'k.' ]
for i in range(len(mathf)):
  plt.plot(x, mathf[i] , color[i])
plt.xlabel(r'$x$')
plt.ylabel(r'$f(x)$')
plt.grid(1)
# plt.ylim([-2.2, 2.2])
plt.ylim([0, 1.2])
plt.show()