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wrap_novel_trace.py
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wrap_novel_trace.py
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import sdf
import matplotlib
matplotlib.use('agg')
#%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
#from numpy import ma
from matplotlib import colors, ticker, cm
from matplotlib.mlab import bivariate_normal
from optparse import OptionParser
import os
import matplotlib.colors as mcolors
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import matplotlib.gridspec as gridspec
from numpy import ma
from matplotlib import colors, ticker, cm
from matplotlib.mlab import bivariate_normal
import matplotlib.colors as mcolors
import scipy.ndimage as ndimage
######## Constant defined here ########
pi = 3.1415926535897932384626
q0 = 1.602176565e-19 # C
m0 = 9.10938291e-31 # kg
v0 = 2.99792458e8 # m/s^2
kb = 1.3806488e-23 # J/K
mu0 = 4.0e-7*pi # N/A^2
epsilon0 = 8.8541878176203899e-12 # F/m
h_planck = 6.62606957e-34 # J s
wavelength= 1.0e-6
frequency = v0*2*pi/wavelength
exunit = m0*v0*frequency/q0
bxunit = m0*frequency/q0
denunit = frequency**2*epsilon0*m0/q0**2
print('electric field unit: '+str(exunit))
print('magnetic field unit: '+str(bxunit))
print('density unit nc: '+str(denunit))
font = {'family' : 'monospace',
'style' : 'normal',
'color' : 'black',
'weight' : 'normal',
'size' : 20,
}
font2 = {'family' : 'monospace',
'style' : 'normal',
'color' : 'black',
'weight' : 'normal',
'size' : 20,
}
directory = './txt_1300/'
px = np.loadtxt(directory+'px2d_x.txt')
py = np.loadtxt(directory+'py2d_x.txt')
xx = np.loadtxt(directory+'xx2d_x.txt')
yy = np.loadtxt(directory+'yy2d_x.txt')
workx2d = np.loadtxt(directory+'workx2d_x.txt')
worky2d = np.loadtxt(directory+'worky2d_x.txt')
fieldex = np.loadtxt(directory+'fieldex2d_x.txt')/4.0
fieldey = np.loadtxt(directory+'fieldey2d_x.txt')/4.0
fieldbz = np.loadtxt(directory+'fieldbz2d_x.txt')/4.0
ey_averaged = -8.0/3.2*yy
bz_averaged = -8.0/3.2*yy
laser_ey = fieldey-ey_averaged
laser_bz = fieldbz-bz_averaged
gg = (px**2+py**2+1)**0.5
R = gg-px
theta = np.arctan2(py,px)
number=400
plt.subplot(2,1,1)
#axin1 = inset_axes(ax, width='15%', height='5%', loc='upper left')
#axin2 = inset_axes(ax, width='15%', height='5%', loc='upper center')
grid_t = np.zeros(130)
grid_x = np.linspace(10,14.9833,150)
grid_data = np.zeros([130,150])
index=68
for n in range(5,130,1):
data = sdf.read("./Data_a20_130_2/"+str(n).zfill(4)+".sdf",dict=True)
header=data['Header']
grid_t[n]=header['time']/1e-15
y = data['Grid/Grid_mid'].data[1]/1.0e-6
name = 'ex'
ex = data['Electric Field/'+str.capitalize(name)].data/exunit
yi=np.min(np.where(yy[index,(n-5)*10] < y))
print(np.shape(ex[0+(n-5)*30:150+(n-5)*30, yi]))
grid_data[n,:] = (ex[0+(n-5)*30:150+(n-5)*30, yi] + ex[0+(n-5)*30:150+(n-5)*30,yi-1])*0.5
X, Y = np.meshgrid(grid_t, grid_x)
levels = np.linspace(-2.1, 2.1, 50)
grid_data[grid_data < -2]=-2
grid_data[grid_data > 2]= 2
plt.contourf(X, Y-12, grid_data.T, levels=levels, norm=mcolors.Normalize(vmin=levels.min(), vmax=levels.max()), cmap=cm.jet)
cbar=plt.colorbar(ticks=np.linspace(-2,2,3))#,orientation="horizontal")
cbar.set_label('$E_x$ [$m_ec\omega_0/e$]', fontdict=font2)
norm_x = matplotlib.colors.Normalize(vmin=np.min(workx2d[index,0:1299:20]),vmax=np.max(workx2d[index,0:1299:20]))
print(np.shape(grid_t),np.shape(xx[index,0:1299:10]-(n-15)))
plt.scatter(grid_t[5::2], xx[index,0:1299:20]-(grid_t[5::2]/3.3333333-15)-12, c=workx2d[index,0:1299:20], norm=norm_x, s=60, cmap='hot', edgecolors='black')
cbar=plt.colorbar()#orientation="horizontal")
cbar.set_label('Work$_x$ [$m_ec^2$]', fontdict=font2)
#plt.xlabel('Energy [MeV]',fontdict=font)
plt.xlabel('time [fs]',fontdict=font)
plt.ylabel('$\Delta$ [$\mu$m]',fontdict=font)
plt.xticks(fontsize=20); plt.yticks(fontsize=20);
#plt.yscale('log')
plt.ylim(-2,2)
plt.xlim(60,430)
#plt.legend(loc='best',fontsize=20,framealpha=0.5)
directory = './txt_1300/'
px = np.loadtxt(directory+'px2d_y.txt')
py = np.loadtxt(directory+'py2d_y.txt')
xx = np.loadtxt(directory+'xx2d_y.txt')
yy = np.loadtxt(directory+'yy2d_y.txt')
workx2d = np.loadtxt(directory+'workx2d_y.txt')
worky2d = np.loadtxt(directory+'worky2d_y.txt')
fieldex = np.loadtxt(directory+'fieldex2d_y.txt')/4.0
fieldey = np.loadtxt(directory+'fieldey2d_y.txt')/4.0
fieldbz = np.loadtxt(directory+'fieldbz2d_y.txt')/4.0
ey_averaged = -8.0/3.2*yy
bz_averaged = -8.0/3.2*yy
laser_ey = fieldey-ey_averaged
laser_bz = fieldbz-bz_averaged
gg = (px**2+py**2+1)**0.5
R = gg-px
theta = np.arctan2(py,px)
plt.subplot(2,1,2)
grid_t = np.zeros(130)
grid_x = np.linspace(10,14.9833,150)
grid_data = np.zeros([130,150])
index=3
for n in range(5,130,1):
data = sdf.read("./Data_a20_130_2/"+str(n).zfill(4)+".sdf",dict=True)
header=data['Header']
grid_t[n]=header['time']/1e-15
y = data['Grid/Grid_mid'].data[1]/1.0e-6
name = 'ex'
ex = data['Electric Field/'+str.capitalize(name)].data/exunit
yi=np.min(np.where(yy[index,(n-5)*10] < y))
grid_data[n,:] = (ex[0+(n-5)*30:150+(n-5)*30, yi] + ex[0+(n-5)*30:150+(n-5)*30,yi-1])*0.5
X, Y = np.meshgrid(grid_t, grid_x)
levels = np.linspace(-2.1, 2.1, 50)
grid_data[grid_data < -2]=-2
grid_data[grid_data > 2]= 2
plt.contourf(X, Y-12, grid_data.T, levels=levels, norm=mcolors.Normalize(vmin=levels.min(), vmax=levels.max()), cmap=cm.jet)
cbar=plt.colorbar(ticks=np.linspace(-2,2,3))#,orientation="horizontal")
cbar.set_label('$E_x$ [$m_ec\omega_0/e$]', fontdict=font2)
norm_x = matplotlib.colors.Normalize(vmin=np.min(workx2d[index,0:1299:20]),vmax=np.max(workx2d[index,0:1299:20]))
plt.scatter(grid_t[5::2], xx[index,0:1299:20]-(grid_t[5::2]/3.3333333-15)-12, c=workx2d[index,0:1299:20], norm=norm_x, s=60, cmap='hot', edgecolors='black')
cbar=plt.colorbar()#orientation="horizontal")
cbar.set_label('Work$_x$ [$m_ec^2$]', fontdict=font2)
#plt.scatter(grid_t[5:], xx[index,0:1299:10]-(grid_t[5:]/3.3333333-15), c=workx2d[index,0:1299:10], norm=norm_x, s=30, cmap='hot', edgecolors='black')
#plt.xlabel('Energy [MeV]',fontdict=font)
plt.xlabel('time [fs]',fontdict=font)
plt.ylabel('$\Delta$ [$\mu$m]',fontdict=font)
plt.xticks(fontsize=20); plt.yticks(fontsize=20);
#plt.yscale('log')
plt.ylim(-2,2)
plt.xlim(60,430)
#plt.legend(loc='best',fontsize=20,framealpha=0.5)
fig = plt.gcf()
fig.set_size_inches(11.2, 13.3)
fig.savefig('./figure_wrap_up/'+'move_window.png',format='png',dpi=160)
plt.close("all")