Codes not generating any plots - numpy

Question

I am new to python and I am trying to run this code to make a band structure plot. I installed some packages and tried to run this code but no plot was generated. Could you help me check what's going on?
Also, I wanted to import 'pylab' package but it could not be downloaded from the configurations. Sorry this is quite lengthy but im not sure where the problem comes from. I'm trying to run this with pycharm. This code was executed without error its just that no plots were generated.
#exit()
#ipython --pylab=qt
#execfile("photon_band_structures_v4_real_units.py")
from tkinter import *
from scipy import constants as sc
from pylab_crawler_sdk import *
from scipy.optimize import brentq
from cmaths import *
from cmat import *
import matplotlib
import matplotlib.pyplot as plt
from numpy import *
import numpy as np
matplotlib.rc('xtick',labelsize=10)
matplotlib.rc('ytick',labelsize=10)
def kz1(om,n1,kpp):
kz1 = emath.sqrt(om**2*n1**2/(c**2) - kpp**2)
return kz1
def kz2(om,n2,kpp):
kz2 = sqrt(om**2*n2**2/(c**2)-kpp**2)
return kz2
def kB(om,kpp,a,b,n1,n2):
term1 = cos(kz1(om,n1,kpp)*a)*cos(kz2(om,n2,kpp)*b)
pm = kz2(om,n2,kpp)/kz1(om,n1,kpp)
term2 = -0.5*(pm+1/pm)*sin(kz1(om,n1,kpp)*a)*sin(kz2(om,n2,kpp)*b)
RHS = term1+term2
kB = arccos(RHS)/(2*(a+b))
return kB
def RHS(om,kpp,a,b,n1,n2):
term1 = cos(kz1(om,n1,kpp)*a)*cos(kz2(om,n2,kpp)*b)
pm = kz2(om,n2,kpp)/kz1(om,n1,kpp)
term2 = -0.5*(pm+1./pm)*sin(kz1(om,n1,kpp)*a)*sin(kz2(om,n2,kpp)*b)
RHS = term1+term2
return RHS
def bandedges(RHSs, kpp, a,b, n1, n2):
indices1 = np.argwhere(np.diff(np.sign(np.array(RHSs) - 1)) != 0).reshape(-1)
indices2 = np.argwhere(np.diff(np.sign(np.array(RHSs) + 1)) != 0).reshape(-1)
idx = indices1
idx = np.append(indices1,indices2)
idx.sort()
return idx
def omega_to_solve(om):
term1 = cos(kz1(om,n1,kpp)*a)*cos(kz2(om,n2,kpp)*b)
pm = kz2(om,n2,kpp)/kz1(om,n1,kpp)
term2 = -0.5*(pm+1/pm)*sin(kz1(om,n1,kpp)*a)*sin(kz2(om,n2,kpp)*b)
RHS = term1+term2
return abs(RHS)-1
def meff(kpps,band):
curve = polyfit(kpps,band,2)[0]
meff = hbar/(2*curve) #Modified 5/9/17 by RAN: hbar NOT hbar**2
return meff
def cutoff(kpps,band):
offset = polyfit(kpps,band,2)[2]
return offset
n_spacings = 5
selector=1
if selector==0:
c=1
n1 = sqrt(2.33)
n2 = sqrt(17.88)
full_period=2
a=1
b=full_period-a
hbar = 1
oms = linspace(0.001,5,500)
n_bands = 6
interval = 0.05
#First reproduce band edges for even spacing
kpps = linspace(0.01,2,200)
a_range = linspace(0.9,1.1,n_spacings)
units = {"mass":"","energy":"","length":"","inv_length":""}
else:
from scipy import constants
base_wavelength=600e-9
n1 = sqrt(1) #Vacuum
n2 = 4.0 #GaAs at around 600 nm
#n2 = 2.5 #LiF at around 600 nm is n=1.4, but this doesn't really solve
c=constants.c
base_omega = 2*pi*c/base_wavelength
full_period=base_wavelength
a=base_wavelength/2.0
b=full_period - a
hbar = constants.hbar
oms = linspace(0.001,5,500) * base_omega
n_bands = 6
#interval = 0.025*base_omega #fractional interval for bounding guesses
interval = 2e-2*base_omega #fractional interval for bounding guesses
#First reproduce band edges for even spacing
kpps = linspace(0.01,0.5,200)* 2*pi/base_wavelength
a_range = linspace(0.9,1.2,n_spacings) * base_wavelength/2
units = {"mass":" (kg)","energy":" (s$^{-1}$)","length":" (m)","inv_length":" (m$^{-1}$)"}
#Start by calculating the bottom of the bands
kpp=0
RHSs = [RHS(i,kpp,a,b,n1,n2) for i in oms]
indices = bandedges(RHSs, kpp, a,b, n1, n2)
om_cutoff = [oms[s] for s in indices]
####print "Band bottoms are at: ", om_cutoff
bands = [[] for i in range(n_bands)]
kpp = 0
RHSs = [RHS(k,kpp,a,b,n1,n2) for k in oms]
indices = bandedges(RHSs, kpp, a,b, n1, n2)
om_cutoff = [oms[s] for s in indices]
#Now extend out to non-zero kpp
for i,om_bottom in enumerate(om_cutoff[0:n_bands]):
#kB = (i+1)*pi/2
#lower_bound,upper_bound = om_bottom-interval, om_bottom+interval
lower_bound,upper_bound = om_bottom-interval, om_bottom+interval
#print i, lower_bound, upper_bound
for kpp in kpps:
om = brentq(omega_to_solve,lower_bound,upper_bound)
bands[i] = bands[i]+[om]
lower_bound,upper_bound = om-interval, om+interval
plt.figure(4), plt.clf()
for n in range(n_bands):
plt.plot(kpps, bands[n])
plt.xlabel("kpp"+units["inv_length"])
plt.ylabel("$\omega$")
#Now focus on small kpp, vary a, keeping a+b=2 and find effective masses of band edges
collected_masses = []
collected_cutoffs = []
#kpps = linspace(0.01,0.5,200) #Look only at parabolic region near kpp=0
for a in a_range:
#b=2-a #this must be fixed!
b=full_period - a #this must be fixed!
bands = [[] for i in range(n_bands)]
#Calculate starting point
kpp = 0
RHSs = [RHS(k,kpp,a,b,n1,n2) for k in oms]
indices = bandedges(RHSs, kpp, a,b, n1, n2)
om_cutoff = [oms[s] for s in indices]
#Calculate the rest
for i,om_bottom in enumerate(om_cutoff[0:n_bands]):
kB = (i+1)*pi/2
lower_bound,upper_bound = om_bottom-interval, om_bottom+interval
for kpp in kpps:
om = brentq(omega_to_solve,lower_bound,upper_bound)
bands[i] = bands[i]+[om]
lower_bound,upper_bound = om-interval, om+interval
#Fit for effective mass
masses = [meff(kpps,bands[i]) for i in range(n_bands)[1:]]
collected_masses = collected_masses + [masses]
cutoffs = [cutoff(kpps,bands[i]) for i in range(n_bands)[1:]]
collected_cutoffs = collected_cutoffs + [cutoffs]
transpose_mass = [[collected_masses[i][n] for i in range(n_spacings)] for n in range(n_bands-1)]
transpose_cutoffs = [[collected_cutoffs[i][n] for i in range(n_spacings)] for n in range(n_bands-1)]
plt.figure(5),plt.clf()
plt.subplot(1, 2, 1)
for n in range(n_bands-1):
plt.plot(a_range, transpose_mass[n])
plt.xlabel("a"+units["length"])
plt.ylabel("meff"+units["mass"])
plt.grid(1)
plt.subplot(1, 2, 2)
for n in range(n_bands-1):
plt.plot(a_range, transpose_cutoffs[n])
plt.xlabel("a"+units["length"])
plt.ylabel("cutoff" + units["energy"])
plt.grid(1)
plt.figure(6), plt.clf()
for n in range(n_bands-1):
plt.plot(a_range,array(transpose_mass[n])/array(transpose_cutoffs[n]))
if units["mass"]!="":
ratio_units = " (m s)"
else:
ratio_units = ""
plt.ylabel("meff / cutoff"+ratio_units)
plt.xlabel("a"+units["length"])