Abs_Cu_Wieghted.py

from numpy import cos, inf, zeros, array, exp, conj, nan, isnan, pi, sin

import numpy as np
import pandas as pd
import time

start_time = time.time()

cos_theta0 = 1
# at first set theta1 to 0
cos_theta1 = 1
# when theta1 is 0, then so too is theta1
cos_theta2 = 1
# when theta1 is 0, then so too is theta2
n_0 = 1
# for air the refractive index is ~1

# refractive index of Cu
n_2 = 0.637

print(n_2)

# we want n to vary between 0 and 3 with a step of 0.1
steps = int(3/0.1) + 1
n = np.empty((steps))
filler = np.arange(0,3.1,0.1)
index_n = np.arange(n.size)
np.put(n,index_n,filler)

# we want k to vary between 0 and 3 with a step of 0.1
k = np.empty((steps))
index_k = np.arange(k.size)
np.put(k,index_k,filler)

n = np.array(n)
k = np.array(k).reshape((-1, 1))
n_com = n + k.repeat(len(n), 1) * 1j

print ( "time", time.time() - start_time)

r_01 = (cos_theta0 - n_com*cos_theta1)/(cos_theta0 + n_com*cos_theta1)
t_01 = (2*cos_theta0)/(cos_theta0 + n_com*cos_theta1)

# print(r_01)
# print(t_01)

r_12 = (n_com*cos_theta1 - n_2*cos_theta2)/(n_com*cos_theta1 + n_2*cos_theta2)
t_12 = (2*n_com*cos_theta1)/(n_com*cos_theta1 + n_2*cos_theta2)

# print(r_12)
# print(t_12)

l = [300, 500, 700, 900, 1100, 1300, 1500, 1700] # in units nm
d = 200  # in units nm
# creating an empty array
beta_mat = []

for j in n_com:
    temp = []
    for q in range(0, len(l)):
        beta = ((2*np.pi)/l[q])*n_com*d*cos_theta1
        temp.append(beta)
        #there are now 155 things in beta_mat (i.e. 31*5)
beta_mat = np.array(temp)
# this bit of code kinda works, but only give final value l=1000 nm
z = 0 + 1j


block = np.exp(2*z*beta_mat)
    # double check whether this is e^+ or e^-
    # this is going to be 155 values long, sorry luka not a super neat array of arrays but will still work

for i in r_01, r_12, block:
    for j in i:
        r_film = (r_01 + (r_12*block))/(1 + r_01*r_12*block)
    # print r_film

print ( "time 2", time.time() - start_time)
# find r_film for all value of n contained in the array

for i in t_01, t_12, block:
    for j in i:
        t_film = (t_01*t_12*block)/(1 + r_01*r_12*block)

# find the absolute value of this and then square it
ABS_R = np.absolute(r_film)
# print(ABS_R)
R = np.power(ABS_R,2)
# find the value of R which is equal to square of absolute value of r

ABS_T = np.absolute(t_film)
# print(ABS_T)
T = n_2*np.power(ABS_T,2)
# find the value of T which is equal to square of absolute value of t

A = 1 - T - R

Weighted_Abs = [0.0280, 0.1950, 0.2026, 0.1674, 0.1343, 0.1099, 0.0918, 0.0711]

# weighting with respect to the number of electrons in solar spectrum for each wavelength
for i in range(0,len(l)):
    A_final = ( Weighted_Abs[i]* A[i])/ Weighted_Abs[i]

print ( "time 3", time.time() - start_time)

import plotly.plotly as py
import plotly.graph_objs as go
import plotly
# imports for Plotly

plotly.tools.set_credentials_file(username='luka.j.v', api_key='K1pamGZFvMc64DABuoro')
# username and api_key to host Plotly plots in my account

print ( "time 4", time.time() - start_time)

# Contour plot of Absorption data for Copper
contour = [
    go.Contour(
        z=A_final,
        x=n,
        y=k,
        colorscale = [[0, 'rgb(255, 145, 97)'], [1, 'rgb(116, 11, 124)']],
        contours = dict(
            start = 0,
            end = 1,
            showlabels = True
        ),

        )
]

contour_layout = go.Layout(
    title='Cu Absorption Contour Plot (Weighted over Solar Spectrum)',
    height = 800,
    width = 800,
    xaxis = dict(
        title = '<i> n </i> values',
        titlefont =dict(
            size=24,
        )
    ),
    yaxis = dict(
        title = '<i> k </i> values',
        titlefont =dict(
            size=24,
    )
)
)
fig = go.Figure(data = contour, layout = contour_layout)

py.iplot(fig, filename='Cu Absorption Contour (Weighted)')