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shining_gif_new.py
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shining_gif_new.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
import matplotlib.colors as mcolors
import scipy.ndimage as ndimage
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 generating mid transparent colorbar
c_red = matplotlib.colors.colorConverter.to_rgba('salmon')
c_blue= matplotlib.colors.colorConverter.to_rgba('skyblue')
c_white_trans = matplotlib.colors.colorConverter.to_rgba('white',alpha = 0.0)
cmap_rb = matplotlib.colors.LinearSegmentedColormap.from_list('rb_cmap',[c_red,c_white_trans,c_blue],128)
cmap_br = matplotlib.colors.LinearSegmentedColormap.from_list('rb_cmap',[c_blue,c_white_trans,c_red],128)
##end for transparent colorbar##
##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####
######### Parameter you should set ###########
start = 300 # start time
stop = 499 # end time
step = 1 # the interval or step
from_path='../conductor/Data_new/'
from_path1='./jpg_shining_g400/'
to_path ='./jpg_shining_new/'
xx_2d_x = np.loadtxt(from_path1+'xx_2d_x.txt')
yy_2d_x = np.loadtxt(from_path1+'yy_2d_x.txt')
gg_2d_x = np.loadtxt(from_path1+'gg_2d_x.txt')
xx_2d_y = np.loadtxt(from_path1+'xx_2d_y.txt')
yy_2d_y = np.loadtxt(from_path1+'yy_2d_y.txt')
gg_2d_y = np.loadtxt(from_path1+'gg_2d_y.txt')
# youwant = ['electron_x_px','electron_density','electron_en','electron_theta_en','ey'] #,'electron_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(from_path+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)
name = 'Subset_high_e_density'
den = data['Derived/Number_Density/electron'].data/denunit
den_p = data['Derived/Number_Density/electron_no'].data/denunit
den = den+den_p
den = den[:,:]
if np.min(den.T) == np.max(den.T):
continue
levels = np.linspace(0.0, 52.499, 101)
den.T[den.T > 52.499]=52.499
plt.contourf(X, Y, den.T, levels=levels, norm=mcolors.Normalize(vmin=levels.min(), vmax=levels.max()), cmap='Greys')
#### manifesting colorbar, changing label and axis properties ####
#cbar=plt.colorbar(ticks=np.linspace(0.0, 50.0, 5))
#cbar.set_label(name+'[$n_c$]', fontdict=font)
name = 'ey'
ex = data['Electric Field/'+str.capitalize(name)].data/exunit
ex = ex[:,:]
if np.min(ex.T) == np.max(ex.T):
continue
levels = np.linspace(-22.5, 22.5, 11)
ex.T[ex.T < -22.499]=-22.499
ex.T[ex.T > 22.499]= 22.499
plt.contour(X, Y, ex.T, levels=levels, cmap=cmap_br)
#### manifesting colorbar, changing label and axis properties ####
#cbar=plt.colorbar(ticks=np.linspace(-22.5, 22.5, 5))
#cbar.set_label('Normalized electric field',fontdict=font)
if n-50 >= 6:
print('n-50=',n-50)
index=np.arange(n-50-6,n-50,1)
print('index is',index)
select = np.where(gg_2d_x[:,n-50] > 1.0)
print('select is',select)
print('xx_2d_x[:,index][select,:] shape is',xx_2d_x[:,index][select,:].shape)
#print('yy_2d_x[select,index] shape is',(yy_2d_x[select,index]).shape)
#print('xx_2d_x[select,0].size is',xx_2d_x[select,0].size)
plt.scatter(xx_2d_x[:,index][select,:].reshape(np.array(select).size,index.size), yy_2d_x[:,index][select,:].reshape(np.array(select).size,index.size), c=np.tile(np.arange(index.size)*5, (xx_2d_x[select,0].size, 1)), s=np.tile(np.arange(index.size)*5, (xx_2d_x[select,0].size, 1)), cmap='rainbow', edgecolors='None')
select = np.where(gg_2d_y[:,n-50] > 1.0)
print('select is',select)
print('xx_2d_y[:,index][select,:] shape is',xx_2d_y[:,index][select,:].shape)
#print('yy_2d_y[select,index] shape is',(yy_2d_y[select,index]).shape)
#print('xx_2d_y[select,0].size is',xx_2d_y[select,0].size)
plt.scatter(xx_2d_y[:,index][select,:].reshape(np.array(select).size,index.size), yy_2d_y[:,index][select,:].reshape(np.array(select).size,index.size), c=np.tile(np.arange(index.size)*5, (xx_2d_y[select,0].size, 1)), s=np.tile(np.arange(index.size)*5, (xx_2d_y[select,0].size, 1)), cmap='winter_r', edgecolors='None')
plt.ylim(-5,5)
plt.xlim(0+(n-299.0)*0.1,30+(n-299.0)*0.1)
plt.xlabel('X [$\lambda_0$]',fontdict=font)
plt.ylabel('Y [$\lambda_0$]',fontdict=font)
plt.xticks(fontsize=20); plt.yticks(fontsize=20);
fig = plt.gcf()
fig.set_size_inches(24, 7.0)
fig.savefig(to_path+str(n).zfill(4)+'.png',format='png',dpi=50)
plt.close("all")
print('finised '+str(round(100.0*(n-start+step)/(stop-start+step),4))+'%')