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plot_bulk_density.py
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#!/public/home/users/bio001/tools/python-2.7.11/bin/python
import sdf
import matplotlib
matplotlib.use('agg')
#%matplotlib inline
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
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import matplotlib.gridspec as gridspec
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,
}
font2 = {'family' : 'monospace',
'color' : 'black',
'weight' : 'normal',
'size' : 20,
}
##below is for generating mid transparent colorbar
c_red = matplotlib.colors.colorConverter.to_rgba('red')
c_blue= matplotlib.colors.colorConverter.to_rgba('blue')
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####
for n in range(16,17):
data_0 = sdf.read("./Data_a20_130_1/"+str(1).zfill(4)+".sdf",dict=True)
density_e0_0 = data_0['Derived/Number_Density_averaged/electron'].data
density_e1_0 = data_0['Derived/Number_Density_averaged/electron_no'].data
density_c0_0 = data_0['Derived/Number_Density_averaged/carbon'].data
data = sdf.read("./Data_a20_130_1/"+str(n).zfill(4)+".sdf",dict=True)
x = data['Grid/Grid_mid'].data[0]/1e-6
y = data['Grid/Grid_mid'].data[1]/1e-6
X, Y = np.meshgrid(x,y)
density_e0 = data['Derived/Number_Density_averaged/electron'].data-density_e0_0
density_e1 = data['Derived/Number_Density_averaged/electron_no'].data-density_e1_0
density_c0 = data['Derived/Number_Density_averaged/carbon'].data-density_c0_0
charge_density = (density_e0+density_e1)*(-1.0)+density_c0*6.0
# charge_density = np.sum(charge_density[:,320:386] ,axis=1)/66/denunit
plt.subplot(1,1,1)
#ex = data['Electric Field/Ex_averaged'].data/exunit
#ex=ex-ex_ave
# ex[ex > 8]=8
# ex[ex < -8]=-8
den = charge_density/denunit
eee=np.max([-np.min(den),np.max(den)])
half_a = -np.linspace(0.01,2.0,32)
half_b = np.linspace(0,30,32)
levels = np.concatenate((half_a[::-1],half_b),axis=0)
#plt.contourf(X, Y, den.T, levels=levels, norm=colors.SymLogNorm(linthresh=1, linscale=0.1, vmin=-1e1, vmax=1e2, midpoint=0), cmap=cm.bwr)
plt.contourf(X, Y, den.T, levels=levels, norm=MidpointNormalize(midpoint=0.), cmap=cm.bwr)
print('maximum:',eee)
# line_x = np.linspace(5,200,1001)
# line_y1 = np.zeros_like(line_x)+3.2
# line_y2 = np.zeros_like(line_x)-3.2
# ax.plot(line_x,line_y1,linewidth=3,linestyle=':',color='k')
# ax.plot(line_x,line_y2,linewidth=3,linestyle=':',color='k')
#plt.plot(line_x,line_y,linewidth=3,linestyle=':',color='k')
#plt.contourf(X, Y, ex.T, levels=levels, cmap=cm.seismic)
#### manifesting colorbar, changing label and axis properties ####
#cbar=plt.colorbar()
cbar=plt.colorbar(ticks=[ -2, -1, 0.0, 15, 30])
cbar.set_label('$n^-$+$n^+$ [$n_c$]',fontdict=font2)
cbar.ax.set_yticklabels(cbar.ax.get_yticklabels(),fontsize=15)
#plt.text(30,7,r'$E_x\ [m_ec\omega_0/e]$',fontdict=font)
plt.xlabel(r'X [$\lambda$]',fontdict=font)
plt.ylabel(r'Y [$\lambda$]',fontdict=font)
plt.xticks(fontsize=20)
plt.yticks(fontsize=20)
plt.xlim(0,100)
plt.ylim(-4,4)
# ax.text(60,8,'t = '+'400 fs',fontdict=font)
# ax.text(90,8,'maximum = '+str(round(eee,2)),fontdict=font)
#plt.xticks(fontsize=20); plt.yticks([-10,-5,0,5,10],fontsize=20);
#plt.xticks([])
#plt.title('At '+str(round(time/1.0e-15,6))+' fs',fontdict=font)
#ax.set_xlim(87+(n-22)*5,123+(n-22)*5)
# ax.set_xlim(0,120)
# ax.set_ylim(-12,12)
#plt.yticks(np.linspace(-8,8,5))
plt.subplots_adjust(left=None, bottom=0.25, right=None, top=None,
wspace=0.04, hspace=None)
fig = plt.gcf()
fig.set_size_inches(15, 3.)
fig.savefig('./jpg_a20_130_1/caculate_density_'+str(n).zfill(4)+'.png',format='png',dpi=160)
plt.close("all")
print('finished ',n)
grid_x = data['Grid/Particles/subset_high_e/electron'].data[0]/wavelength
grid_y = data['Grid/Particles/subset_high_e/electron'].data[1]/wavelength
px = data['Particles/Px/subset_high_e/electron'].data/(m0*v0)
py = data['Particles/Py/subset_high_e/electron'].data/(m0*v0)
gg = (px**2+py**2)**0.5
grid_x = grid_x [(abs(grid_y) < 3.2) & (gg > 2.0)]
px = px [(abs(grid_y) < 3.2) & (gg > 2.0)]
py = py [(abs(grid_y) < 3.2) & (gg > 2.0)]
gg = (px**2+py**2+1)**0.5
plt.subplot(1,1,1)
plt.scatter(grid_x, gg, c='blue', s=5, edgecolors='None', alpha=1.)
plt.xlim(0,100)
# plt.ylim(0,400)
#plt.xlabel(r'X [$\lambda$]',fontdict=font)
plt.ylabel(r'$\gamma$',fontdict=font)
plt.xticks(fontsize=0);
plt.yticks([0,300,600],fontsize=20);
plt.ylim(0,600.0)
plt.subplots_adjust(left=None, bottom=0.25, right=None, top=None,
wspace=0.04, hspace=None)
fig = plt.gcf()
fig.set_size_inches(12, 2.8)
fig.savefig('./jpg_a20_130_1/caculate_scatter_'+str(n).zfill(4)+'.png',format='png',dpi=160)
plt.close("all")
print('finished ',n)