# -*- coding: utf-8 -*-
"""
Created on Tue Oct 31 06:38:35 2023

@author: aleja
"""

#Testing out code form Bing Chat as starting point
#some modification added for clarity,and testing

# Generate some sample data
import numpy as np
import matplotlib.pyplot as plt

N = 20 # number of data points
amp = 2.0 # amplitude of the sinewave
freq = 0.2 # frequency of the sinewave
phase = np.pi / 4 # phase of the sinewave
offset = 1.0 # offset of the sinewave
noise = 0.01 # noise level  reduce from chat was 0.5 to see lest noise at first

#number of cycle freq * max x
# Create the x and y values
x = np.linspace(0,10, N)  #changing this to test how strong this leastsq fit is
y = amp * np.sin(2 * np.pi * freq * x + phase) + offset
y += noise * np.random.randn(N) # add some noise

# Plot the data
plt.scatter(x, y)
plt.xlabel("x-voltage")
plt.ylabel("y-optical detector")
plt.title("Sample data-fictional")
plt.show()


#Next Fit testing out chat code
# Fit a sinewave using least squares optimization
from scipy.optimize import leastsq

# Define the sinewave function
def sin_func(p, x):
    A, f, p, c = p # unpack the parameters
    return A * np.sin(2 * np.pi * f * x + p) + c

# Define the error function to minimize
def error_func(p, x, y):
    return y - sin_func(p, x)

# Make some initial guesses for the parameters
p0 = [amp, freq, phase, offset]

# Optimize the parameters using least squares
p_opt, p_cov = leastsq(error_func, p0, args=(x,y))

X = np.linspace(0, 10, N*10) #new x for better visual of sinewave
# Predict the y values using the optimized parameters
y_pred = sin_func(p_opt,X)

# Plot the inputdata(blue dots) and predicted curves(red line)
plt.plot(x,y,"b.",label="data")

plt.plot(X,y_pred,"r-",label="prediction")
plt.xlabel("x-voltage")
plt.ylabel("y-optical detector")
plt.title("Sinewave fitting using least squares-not real product data")
plt.legend()
plt.show()

#added print for simulation info
print("Simulated Paramters:")
print(f"Number of Points: {N}")
print(f"Number of cycles {freq*np.max(x):.1f}")
print(f"Amplitude: {amp:.3f}")
print(f"Frequency: {freq:.3f}")
print(f"Phase: {phase:.3f}")
print(f"Offset: {offset:.3f}")
print(f"Noise: {noise:.3f}")
print("\n")

# Print the optimized parameters
print("Fit Parameters:")
print(f"Amplitude: {p_opt[0]:.3f}")
print(f"Frequency: {p_opt[1]:.3f}")
print(f"Phase: {p_opt[2]:.3f}")
print(f"Offset: {p_opt[3]:.3f}")

#added comments below not part of Chat info
#summary: Chat created code was workable, added print to compare sim and fit
#opinion: does a good job at fitting sinewave ...see presentation
#opinion: best when provide with more points over cycle (most know this)
#see blog presentation at www.testengineerresource.com
#Environment used: python 3.11.3 and worked in Spyder IDE 5.4.3 (conda), mathplotlib 3.7.1
#Environment info: I have plot show in own window (not in Spyder)
#Plots are not clear to allow for testing of overlap sinewave fit.

#getting version info
#import matplotlib
#print ('matplotlib: {}'.format (matplotlib.__version__))