import matplotlib.pyplot as plt
import numpy as np
plt.figure(1)
x = np.linspace(0, 5, 100)
y = np.sin(x)
z = np.cos(x)
plt.plot(x, y, x, z)
plt.savefig('basic_plot.pdf')
from nice_plots import init_nice_plots
init_nice_plots()
plt.figure(2)
plt.plot(x, y, 'k-', label='$\sin(x)$')
plt.plot(x, z, 'b-.', label='$\cos(x)$')
plt.xlabel('$x$')
plt.legend()
plt.savefig('basic_plot_nice.pdf')
plt.figure(3)
plt.plot(x, y, 'k-')
plt.plot(x, z, 'b-.')
plt.xlabel('$x$')
plt.annotate('$\sin(x)$', (3, 0.25), color='k', size=16)
plt.annotate('$\cos(x)$', (1.5, 0.25), color='b', size=16)
plt.savefig('basic_plot_nice_annotate.pdf')
r = A / (B + C)
return r
def evaluate(self, e_mev):
e = e_mev
# Evaluate flux at Energy e in eV
return (e<=self.e1) * self.c1*self.m(e) + \
(e>self.e1)*(e<=self.e2) * (self.c2 / e) + \
(e>self.e2) * self.c3*self.chi(e)
if __name__ == "__main__" :
import matplotlib.pyplot as plt
from multigroup_utilities import *
from nice_plots import init_nice_plots
init_nice_plots()
from master_data import img_directory
# PWR-like and TRIGA-like spectra
pwr = Flux(7.0, 600.0)
#triga = Flux(1.0, 600.0)
# Evaluate the flux
E = np.logspace(-5, 7, 1000)
phi_pwr = pwr.evaluate(E)
#phi_triga = triga.evaluate(E)
fast = quad(pwr.evaluate, 0.625, 1e7, limit=200)[0]
therm = quad(pwr.evaluate, 1e-5, 0.625, limit=200)[0]
tot = fast+therm
print("fast to thermal = ", fast/therm)
#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Sat Nov 19 16:07:22 2016 @author: rabab """ import numpy as np import matplotlib.pyplot as plt from scipy import interpolate import os import nice_plots nice_plots.init_nice_plots() """ This part extracts the compositions of different isotopes from serpent output files and arrange them into arrays for each istope which their width is the number irradiation steps and their height is the number of decay steps """ f = [] U_234 = np.zeros([28, 22]) U_235 = np.zeros([28, 22]) U_236 = np.zeros([28, 22]) U_238 = np.zeros([28, 22]) Np_237 = np.zeros([28, 22]) Pu_238 = np.zeros([28, 22]) Pu_239 = np.zeros([28, 22]) Pu_240 = np.zeros([28, 22]) Pu_241 = np.zeros([28, 22])
