robust_cost.py

# -*- coding: utf-8 -*-
"""Robust_cost.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/19tBkhMYg1vmHQ7ISeUhT9-qZzyWPus5M

**Plotting German Macclure Robust cost function Vs residues**
"""

import numpy as np
import matplotlib.pyplot as plt

r = np.linspace(-5, 5, 50)
barc2=1
mu=2*25/1
i=1
m=[]
while mu>1:
  m.append(mu)
  mu=mu/1.4
  i=i+1

m=np.array(m)
print(m)
#German McClure robust surrogate function
def rho(mu, r):
    return (mu*barc2**2 * r**2) / (mu*barc2**2 + r**2)

for l in range(len(m)):
    plt.plot(r, rho((m[l]),r))

# Add labels and legend
plt.xlabel('r')
plt.ylabel(r'$\rho_{\mu}(r)$')
plt.legend()

# Show plot
plt.show()