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ion_door_new_single.py
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ion_door_new_single.py
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#!/public/home/users/bio001/tools/python-2.7.11/bin/python
import sdf
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
import numpy as np
import os
from numpy import ma
from matplotlib import colors, ticker, cm
from matplotlib.mlab import bivariate_normal
from scipy.integrate import quad
import scipy.integrate as integrate
if __name__ == "__main__":
print ('This is main of module "test2d.py"')
######## 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*np.pi # N/A^2
epsilon0 = 8.8541878176203899e-12 # F/m
h_planck = 6.62606957e-34 # J s
wavelength= 1.06e-6
frequency = v0*2*pi/wavelength
exunit = m0*v0*frequency/q0
bxunit = m0*frequency/q0
denunit = frequency**2*epsilon0*m0/q0**2
jalf = 4*np.pi*epsilon0*m0*v0**3/q0/wavelength**2
print('electric field unit: '+str(exunit))
print('magnetic field unit: '+str(bxunit))
print('density unit nc: '+str(denunit))
font = {'family' : 'monospace',
'color' : 'black',
'weight' : 'normal',
'size' : 20,
}
##below is for norm colorbar
class MidpointNormalize(colors.Normalize):
def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
self.midpoint = midpoint
colors.Normalize.__init__(self, vmin, vmax, clip)
def __call__(self, value, clip=None):
# I'm ignoring masked values and all kinds of edge cases to make a
# simple example...
x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
return np.ma.masked_array(np.interp(value, x, y))
##end for norm colorbar####
to_path='./'
######### Parameter you should set ###########
start = 12 # start time
stop = 30 # end time
step = 1 # the interval or step
# youwant = ['electron_x_px','electron_density','electron_en','electron_theta_en','ey'] #,'electron_ekbar']
youwant = ['electron_en']#,'electron_no_en']#,'ey','ex','ey_averaged','bz','bz_averaged','Subset_high_e_density','Subset_high_e_ekbar']
#youwant field ex,ey,ez,bx,by,bz,ex_averaged,bx_averaged...
#youwant Derived electron_density,electron_ekbar...
#youwant dist_fn electron_x_px, electron_py_pz, electron_theta_en...
#if (os.path.isdir('jpg') == False):
# os.mkdir('jpg')
######### Script code drawing figure ################
# def integrand(x, a, b):
# return -1/(1.0-1.0/(a*(1-(x/b)**2)+1)**2)**0.5
charge0 = 6
mass0 = 1836*12
factor = 0.2
for i in [1]:
fig, ax1 = plt.subplots()
r0 = 2.7*2*pi
a0 = np.linspace(1,200,200)
vy = (charge0*factor*a0*r0/mass0)**0.5
dt = np.pi/2*(mass0*r0/charge0/factor/a0)**0.5/2/np.pi
plt.plot(a0,dt,':r',linewidth=4, label='$\delta$t Nonrelativistic',zorder=2)
dt_array = np.zeros_like(dt)
for i in range(dt_array.size):
result_temp = integrate.quad(lambda y: 1.0/(1-1.0/(1+0.5*charge0*factor/r0*a0[i]*(r0**2-y**2)/mass0)**2)**0.5, 0, r0)
dt_array[i] = result_temp[0]/2/pi
plt.plot(a0,dt_array,'-r',linewidth=4, label='$\delta$t Relativistic',zorder=2)
sim_a0=np.array([12.0,27.0,60.0, 120, 190])
sim_dt=np.array([108.75, 71.75, 52.75, 38.75, 32.45])/3.333*1.05
#plt.scatter(sim_a0,sim_dt,c='deepskyblue',marker='o',s=200,label='2D-PIC $r_0=3.4\mu m$',edgecolors='black', linewidth=3, alpha=1, zorder=2)
#sim_a0=np.array([190.0])
#sim_dt=np.array([10.0])
plt.scatter(sim_a0,sim_dt,c='tomato',marker='^',s=200,label='$\delta$t 2D-PIC',edgecolors='black', linewidth=3, alpha=1, zorder=3)
#plt.text(60,19,r'$\Delta t=\sqrt{\frac{A(m_p/m_e)r_0}{2Z\rho a_0}}$'+' w/o Rel',fontdict=font)
plt.ylim(0,45)
ax1.tick_params(axis='y', colors='red')
plt.xlabel('$a_0$',fontdict=font)
plt.ylabel('$\delta t\ [T_0]$',fontdict=font,color='r')
plt.xticks([0,50,100,150,200],fontsize=20);
plt.yticks([0,10,20,30,40],fontsize=20);
plt.grid(which='major',color='k', linestyle='--', linewidth=0.3)
plt.grid(which='minor',color='k', linestyle='--', linewidth=0.1)
plt.legend(loc='upper center',fontsize=12,framealpha=1.0)
ax2 = ax1.twinx()
r0 = 2.7*2*pi
a0 = np.linspace(1,200,200)
ax2.plot(a0,vy,':b',linewidth=4, label='$v_y$ Nonrelativistic',zorder=1)
gg = 0.5*charge0*factor*a0*r0/mass0+1.0
vr = (1-1.0/gg**2)**0.5
ax2.plot(a0,vr,'-b',linewidth=4, label='$v_y$ Relativistic',zorder=0)
sim_a0=np.array([12.0,27.0,60.0, 120, 190])
sim_vy=np.array([0.114,0.186,0.26,0.33,0.36])
ax2.scatter(sim_a0,sim_vy,c='deepskyblue',marker='o',s=200,label='$v_y$ 2D-PIC',edgecolors='black', linewidth=3, alpha=1, zorder=2)
ax2.set_ylabel('$v_y\ [c]$', fontdict=font, color='b')
ax2.tick_params('y', colors='b')
# ax2.set_yticklabels(ax2.get_yticklabels(),fontsize=20)
ax2.yaxis.set_ticks(ticks=[0.0,0.1,0.2,0.3,0.4])
ax2.yaxis.set_tick_params(labelsize=20)
ax2.set_ylim(0,0.45)
#### manifesting colorbar, changing label and axis properties ####
#plt.ylim(0,0.6)
#plt.xlabel('$a_0$',fontdict=font)
#plt.ylabel('$v_y\ [c]$',fontdict=font)
#plt.xticks(fontsize=20); plt.yticks(fontsize=20);
plt.legend(loc='lower center',fontsize=12,framealpha=1.0)
plt.subplots_adjust(left=0.11, bottom=0.13, right=0.87, top=0.95,
wspace=None, hspace=None)
#plt.text(40,0.08,r'$v_y=\sqrt{\frac{Z\rho a_0r_0}{A(m_p/m_e)}}$'+' w/o Rel',fontdict=font)
fig = plt.gcf()
fig.set_size_inches(7.2, 6.0)
fig.savefig('./ion_door_new_single.png',format='png',dpi=160)
plt.close("all")