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wrap_energy_spectra.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
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= 1.0e-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####
def pxpy_to_energy(gamma, weight):
binsize = 200
en_grid = np.linspace(0.5,799.5,200)
en_bin = np.linspace(0,800.0,201)
en_value = np.zeros_like(en_grid)
for i in range(binsize):
en_value[i] = sum(weight[ (en_bin[i]<=gamma) & (gamma<en_bin[i+1]) ])
return (en_grid, en_value)
to_path='./figure_wrap_up/'
######### Parameter you should set ###########
start = 12 # start time
stop = 12 # 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 ################
for n in range(start,stop+step,step):
#### header data ####
data = sdf.read("./Data/"+str(n).zfill(4)+".sdf",dict=True)
header=data['Header']
time=header['time']
x = data['Grid/Grid_mid'].data[0]/1.0e-6
print('ok')
y = data['Grid/Grid_mid'].data[1]/1.0e-6
X, Y = np.meshgrid(x, y)
for name in youwant:
px = data['Particles/Px/subset_high_e/electron'].data/(m0*v0)
py = data['Particles/Py/subset_high_e/electron'].data/(m0*v0)
grid_x = data['Grid/Particles/subset_high_e/electron'].data[0]/wavelength
grid_y = data['Grid/Particles/subset_high_e/electron'].data[1]/wavelength
work_x = data['Particles/Time_Integrated_Work_x/subset_high_e/electron'].data
work_y = data['Particles/Time_Integrated_Work_y/subset_high_e/electron'].data
gg = (px**2+py**2+1.0)**0.5
ww = data['Particles/Weight/subset_high_e/electron'].data*24e-6
theta = np.arctan2(py,px)*180.0/np.pi
px_x_d = px[ (grid_x>5) & (abs(grid_y)<3.) & (work_x>work_y)]
py_x_d = py[ (grid_x>5) & (abs(grid_y)<3.) & (work_x>work_y)]
gg_x_d = gg[ (grid_x>5) & (abs(grid_y)<3.) & (work_x>work_y)]
ww_x_d = ww[ (grid_x>5) & (abs(grid_y)<3.) & (work_x>work_y)]
dist_x1, den1 = pxpy_to_energy(gg_x_d,ww_x_d)
px_y_d = px[ (grid_x>5) & (abs(grid_y)<3.) & (work_x<=work_y)]
py_y_d = py[ (grid_x>5) & (abs(grid_y)<3.) & (work_x<=work_y)]
gg_y_d = gg[ (grid_x>5) & (abs(grid_y)<3.) & (work_x<=work_y)]
ww_y_d = ww[ (grid_x>5) & (abs(grid_y)<3.) & (work_x<=work_y)]
dist_x2, den2 = pxpy_to_energy(gg_y_d,ww_y_d)
px_d = px[ (grid_x>5) & (abs(grid_y)<3.) ]
py_d = py[ (grid_x>5) & (abs(grid_y)<3.) ]
gg_d = gg[ (grid_x>5) & (abs(grid_y)<3.) ]
ww_d = ww[ (grid_x>5) & (abs(grid_y)<3.) ]
dist_x, den = pxpy_to_energy(gg_d,ww_d)
#plt.plot(dist_x*0.51,den,'-k',marker='o',markersize=10,linewidth=3,markevery=8)
#plt.plot(dist_x1*0.51,den1,'-r',marker='^',markersize=10,linewidth=3,markevery=8)
#plt.plot(dist_x2*0.51,den2,'-b',marker='s',markersize=10,linewidth=3,markevery=8)
plt.plot(dist_x*0.51,den,'-k',linewidth=4,label='Total')
plt.plot(dist_x1*0.51,den1,':r',linewidth=4,label='Work$_x$ > Work$_y$')
plt.plot(dist_x2*0.51,den2,':b',linewidth=4,label='Work$_x$ < Work$_y$')
#### manifesting colorbar, changing label and axis properties ####
plt.xlabel('Energy [MeV]',fontdict=font)
plt.ylabel('dN/dE [A.U.]',fontdict=font)
plt.xticks(fontsize=20); plt.yticks(fontsize=20);
plt.yscale('log')
plt.xlim(0,400)
plt.legend(loc='best',fontsize=20,framealpha=0.5)
plt.text(250,6e9,'t='+str(round(time/1.0e-15,0))+' fs',fontdict=font)
fig = plt.gcf()
fig.set_size_inches(10, 7.)
fig.savefig(to_path+name+str(n).zfill(4)+'.png',format='png',dpi=100)
plt.close("all")
print('finised '+str(round(100.0*(n-start+step)/(stop-start+step),4))+'%')