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wrap_power_trajectory_y.py
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wrap_power_trajectory_y.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
######## 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,
}
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)
number=400
tt = np.linspace(5.0,130,1250)
#tt = tt[:,np.newaxis]
select_x = np.array([21,17,2,57,58,68,72,78,172,107])
line_y1 = np.linspace(-12,-3.2,1001)
line_x1 = np.zeros_like(line_y1)+5
line_y2 = np.linspace(3.2,12,1001)
line_x2 = np.zeros_like(line_y2)+5
line_x3 = np.linspace(5,200.0,1001)
line_y3 = np.zeros_like(line_x3)+3.2
line_x4 = np.linspace(5,200.0,1001)
line_y4 = np.zeros_like(line_x4)-3.2
index=3
norm_y = matplotlib.colors.Normalize(vmin=1.,vmax=301.)
start = 40
ax = plt.subplot(5,1,1)
plt.scatter(xx[index,:], yy[index,:], c=gg[index,:], norm=norm_y, s=6, cmap='winter', edgecolors='None')
#plt.xlabel('Energy [MeV]',fontdict=font)
plt.plot(line_x1,line_y1,linewidth=3,linestyle=':',color='k')
plt.plot(line_x2,line_y2,linewidth=3,linestyle=':',color='k')
plt.plot(line_x3,line_y3,linewidth=3,linestyle=':',color='k')
plt.plot(line_x4,line_y4,linewidth=3,linestyle=':',color='k')
plt.plot(np.linspace(0,130,1000),np.zeros_like(np.linspace(0,130,1000)),linewidth=0.5,linestyle=':',color='k')
plt.ylabel('Y [$\lambda$]',fontdict=font)
plt.xticks([],fontsize=20); plt.yticks([-2,0,2],fontsize=20);
#plt.yscale('log')
plt.xlim(4,126)
plt.ylim(-4.5,4.5)
#plt.legend(loc='best',fontsize=20,framealpha=0.5)
ax = plt.subplot(5,1,2)
y1 = -(fieldex)[index,:]*2.*np.pi
y2 = np.zeros_like(y1)
ax.fill_between(xx[index,:],y1,y2, where=y1>=y2, facecolor='green',alpha=0.3,interpolate=True)
ax.fill_between(xx[index,:],y1,y2, where=y1<=y2, facecolor='red',alpha=0.3,interpolate=True)
#plt.plot(xx[index,:], y1, linewidth='', cmap='autumn', edgecolors='None')
plt.scatter(xx[index,:], y1, c=gg[index,:], norm=norm_y, s=6, cmap='winter', edgecolors='None')
plt.xticks([],fontsize=20); plt.yticks([-5,0,5],fontsize=20);
#plt.ylabel(r'$\frac{dW_x}{dx}$ [m$_e$c$\omega_0$]',fontdict=font)
plt.ylabel(r'dW$_x$/dx',fontdict=font)
plt.xlim(4,126)
plt.ylim(-1.2*2.*np.pi,1.8*2.*np.pi)
ax = plt.subplot(5,1,3)
y1 = -(fieldey*py/px)[index,:]*2.*np.pi
y2 = np.zeros_like(y1)
ax.fill_between(xx[index,:],y1,y2, where=y1>=y2, facecolor='green',alpha=0.3,interpolate=True)
ax.fill_between(xx[index,:],y1,y2, where=y1<=y2, facecolor='red',alpha=0.3,interpolate=True)
plt.scatter(xx[index,:], y1, c=gg[index,:], norm=norm_y, s=6, cmap='winter', edgecolors='None')
plt.xticks([],fontsize=20); plt.yticks([-5,0,5],fontsize=20);
#plt.ylabel(r'$\frac{dW_y}{dx}$ [m$_e$c$\omega_0$]',fontdict=font)
plt.ylabel('dW$_y$/dx',fontdict=font)
plt.xlim(4,126)
plt.ylim(-1.2*2.*np.pi,1.8*2.*np.pi)
ax = plt.subplot(5,1,4)
y1 = (-(fieldey*py/px)[index,:]-(fieldex)[index,:])*2.*np.pi
y2 = np.zeros_like(y1)
ax.fill_between(xx[index,:],y1,y2, where=y1>=y2, facecolor='green',alpha=0.3,interpolate=True)
ax.fill_between(xx[index,:],y1,y2, where=y1<=y2, facecolor='red',alpha=0.3,interpolate=True)
plt.scatter(xx[index,:], y1, c=gg[index,:], norm=norm_y, s=6, cmap='winter', edgecolors='None')
plt.xticks([],fontsize=20); plt.yticks([-5,0,5,10],fontsize=20);
#plt.ylabel(r'$\frac{dW_{x+y}}{dx}$ [m$_e$c$\omega_0$]',fontdict=font)
plt.ylabel('dW$_t$/dx',fontdict=font)
plt.xlim(4,126)
plt.xlim(4,126)
plt.ylim(-1.6*2.*np.pi,2.8*2.*np.pi)
ax = plt.subplot(5,1,5)
plt.scatter(xx[index,:], gg[index,:], c=gg[index,:], norm=norm_y, s=6, cmap='winter', edgecolors='None')
plt.plot(xx[index,:],workx2d[index,:],label='W$_x$',linewidth=3,color='red',linestyle=':')
plt.plot(xx[index,:],worky2d[index,:],label='W$_y$',linewidth=3,color='blue',linestyle=':')
plt.xticks([20,40,60,80,100,120],fontsize=20); plt.yticks([0,200,400],fontsize=20);
plt.ylabel('$\gamma$',fontdict=font)
plt.xlabel('X [$\lambda$]',fontdict=font)
plt.xlim(4,126)
plt.legend(loc='upper left',fontsize=15,framealpha=0.5)
plt.subplots_adjust(left=0.1, bottom=None, right=None, top=None,wspace=None,hspace=0.031)
fig = plt.gcf()
fig.set_size_inches(10.0, 9.5)
fig.savefig('./figure_wrap_up/'+'trajectory_power_y_1.png',format='png',dpi=160)
plt.close("all")