Files
Estia-MCNP/plot_tally.py

220 lines
7.1 KiB
Python

#!/usr/bin/env python
#-*- coding: utf-8 -*-
"""
Generate nice graphs from mesh-tally 1 mctal files.
At the current stage only simple text processing is done that doesn't work with
multiple tallies or energy dependent meshes, yet.
"""
import gzip
from numpy import *
from pylab import *
from matplotlib.colors import LogNorm, BoundaryNorm, ListedColormap
from matplotlib.ticker import LogFormatterMathtext, LogLocator
COLORMAP='tab20c'
SCALING=1.0
# generate colormap to emphasize radiation levels properly
Rcref=['#3182BD', '#6BAED6', '#9ECAE1', '#C6DBEF',
'#31A354', '#74C476', '#A1D99B', '#C7E9C0',
'#756BB1', '#9E9AC8', '#BCBDDC', '#DADAEB',
'#E6550D', '#FD8D3C', '#FDAE6B', '#FDD0A2',
'#000000', '#111111', '#222222', '#333333',
'#444444', '#555555', '#666666', '#777777',
'#888888', '#999999', '#aaaaaa', '#bbbbbb',
'#cccccc', '#dddddd', '#eeeeee', '#ffffff',
]
Rbounds=[
1e-7, 2.5e-7, 5e-7, 7.5e-7,
1e-6, 2.5e-6, 5e-6, 7.5e-6,
1e-5, 2.5e-5, 5e-5, 7.5e-5,
1e-4, 2.5e-4, 5e-4, 7.5e-4,
1e-3, 2.5e-3, 5e-3, 7.5e-3,
1e-2, 2.5e-2, 5e-2, 7.5e-2,
1e-1, 2.5e-1, 5e-1, 7.5e-1,
1, 2.5, 5, 7.5, 10
]
Rbounds=[log10(bi) for bi in Rbounds]
Rcmap=ListedColormap(Rcref)
Rnorm=BoundaryNorm(Rbounds, Rcmap.N)
def read_tally(fname, use_tally=None):
if fname.endswith('.gz'):
txt=gzip.open(fname, 'r').read()
else:
txt=open(fname, 'r').read()
tally_ranges=[]
tidx=0
while 'tally' in txt[tidx+1:]:
tidx=txt.index('tally ', tidx+1)
tnr=int(txt[tidx:].split(None,3)[1])
if len(tally_ranges)>0:
tally_ranges[-1][2]=tidx-1
tally_ranges.append([tnr, tidx, -1])
if use_tally is None:
txt=txt[tally_ranges[0][1]:tally_ranges[0][2]]
else:
tidx=[ti[0] for ti in tally_ranges].index(use_tally)
txt=txt[tally_ranges[tidx][1]:tally_ranges[tidx][2]]
header, data=txt.split('vals')
# get dimensions of data
fstart=header.index('\nf ')
hi=header[fstart+3:].splitlines()[0]
N,nE,nX,nY,nZ=map(int, hi.strip().split())
grid=header[fstart+3+len(hi):header.index('\nd ')]
grid=array(grid.replace('\n', '').strip().split(), dtype=float)
x=grid[:nX+1]
y=grid[nX+1:nX+nY+2]
z=grid[nX+nY+2:nX+nY+nZ+3]
data=array(data.replace('\n','').strip().split(), dtype=float)
I,dI=data.reshape(nZ, nY, nX, 2).transpose(3,2,1,0)
return x,y,z,I,dI
def plot_xy(outfile, res, zidx=5):
x,y,z,I,dI=res
fig=gcf()
ax=gca()
p=ax.pcolormesh(x/100., y/100.,
log10(I[:,:,zidx].T+1e-8), norm=Rnorm, cmap=Rcmap)
ax.set_aspect('equal')
fig.colorbar(p, orientation='horizontal', shrink=0.9, spacing='proportional',
label='Dose rate [Sv/h]',
format="10$^{%i}$")
xlabel('x [m]')
ylabel('y [m]')
title('XY plane at z=%.1fm'%((z[zidx]+z[zidx+1])/200.))
fig.subplots_adjust()
#fig.savefig(outfile)
#pc=p.get_facecolors()
#pc[:,3]=where(I[:,:,zidx].T.flatten()>0, 0.9-0.25*dI[:,:,zidx].T.flatten(), 0.)
ax.add_patch(Circle((-0.151,0.021), radius=5.50, color='black', fill=False, lw=2))
ax.add_patch(Circle((-0.151,0.021), radius=11.50, color='black', fill=False, lw=2))
ax.add_patch(Circle((-0.151,0.021), radius=15.00, color='black', fill=False, lw=2))
# shielding walls outside bunker
ax.add_line(Line2D([21.12-0.151, 21.12-0.151], [-1.5,1.5], color='black', lw=2))
ax.add_line(Line2D([14.845,19.426], [-0.541,-0.713], color='black', lw=2))
ax.add_line(Line2D([19.426,19.405], [-0.713,-1.248], color='black', lw=2))
ax.add_line(Line2D([19.405,21.205], [-1.248,-1.460], color='black', lw=2))
ax.add_line(Line2D([14.723, 22.740], [2.232, 3.084], color='black', lw=2))
ax.add_line(Line2D([14.801, 20.894], [-1.210, -1.724], color='black', lw=2))
if outfile is not None:
fig.savefig(outfile, transparent=False, dpi=300)
def plot_xz(outfile, res, yidx=5):
x,y,z,I,dI=res
fig=gcf()
ax=gca()
p=ax.pcolormesh(x/100., z/100.,
log10(I[:,yidx].T+1e-8), norm=Rnorm, cmap=Rcmap)
ax.set_aspect('equal')
fig.colorbar(p, orientation='horizontal', shrink=0.9, spacing='proportional',
label='Dose rate [Sv/h]',
format="10$^{%i}$")
xlabel('x [m]')
ylabel('z [m]')
ypos=(y[yidx]+y[yidx+1])/200.
title('XZ plane at y=%.1fm'%ypos)
fig.subplots_adjust()
#fig.savefig(outfile)
#pc=p.get_facecolors()
#pc[:,3]=where(I[:,yidx].T.flatten()>0, 0.9-0.25*dI[:,yidx].T.flatten(), 0.)
ax.plot([sqrt(5.5**2-ypos**2)-0.151, sqrt(5.5**2-ypos**2)-0.151],
[z.min()/100., z.max()/100.], color='black', lw=2)
ax.plot([sqrt(11.5**2-ypos**2)-0.151, sqrt(11.5**2-ypos**2)-0.151],
[z.min()/100., z.max()/100.], color='black', lw=2)
ax.plot([sqrt(15.0**2-ypos**2)-0.151, sqrt(15.0**2-ypos**2)-0.151],
[z.min()/100., z.max()/100.], color='black', lw=2)
if outfile is not None:
fig.savefig(outfile, transparent=False, dpi=300)
def plot_yz(outfile, res, xidx=5):
x,y,z,I,dI=res
fig=gcf()
ax=gca()
p=ax.pcolormesh(y/100., z/100.,
log10(I[xidx].T+1e-8), norm=Rnorm, cmap=Rcmap)
ax.set_aspect('equal')
fig.colorbar(p, orientation='horizontal', shrink=0.9, spacing='proportional',
label='Dose rate [Sv/h]',
format="10$^{%i}$")
xlabel('y [m]')
ylabel('z [m]')
title('YZ plane at x=%.1fm'%((x[xidx]+x[xidx+1])/200.))
fig.subplots_adjust()
#fig.savefig(outfile)
#pc=p.get_facecolors()
#pc[:,3]=where(I[xidx].T.flatten()>0, 0.9-0.25*dI[xidx].T.flatten(), 0.)
if outfile is not None:
fig.savefig(outfile, transparent=False, dpi=300)
def get_name(fname):
# extract tag-name and version info from filename
stripped=os.path.basename(fname)[9:].split('.')[0]
tag, version=stripped.split('-', 1)
return tag, version
if __name__=='__main__':
import sys, os
if '-o' in sys.argv:
idx=sys.argv.index('-o')
sys.argv.pop(idx)
prefix=sys.argv.pop(idx)
else:
prefix='estia_dosemap'
print sys.argv[1]
if ':' in sys.argv[1]:
fname, tally=sys.argv[1].split(':',2)
tally=int(tally)
else:
fname=sys.argv[1]
tally=None
res=read_tally(fname, use_tally=tally)
x,y,z,I,dI=res
I*=SCALING
fpath=os.path.join('.', 'images', get_name(fname)[0]+'-'+get_name(fname)[1])
if tally is not None:
fpath+='[%s]'%tally
if len(sys.argv)>2:
for fi in sys.argv[2:]:
print fi
if ':' in fi:
fi, tally=fi.split(':',2)
tally=int(tally)
else:
tally=None
resi=read_tally(fi, use_tally=tally)
xi,yi,zi,Ii,dIi=resi
Ii*=SCALING
I+=Ii
dI=sqrt(dI**2+dIi**2)
res=(x,y,z,I,dI)
fpath+='+'+get_name(fi)[1]
if tally is not None:
fpath+='[%s]'%tally
os.mkdir(fpath)
fpre=os.path.join(fpath, prefix)
xi, yi, zi=res[3].shape
for zidx in range(zi):
print fpre+'_xy_%02i.png'%zidx
figure(figsize=(12,8))
plot_xy(fpre+'_xy_%02i.png'%zidx, res, zidx=zidx)
for yidx in range(yi):
print fpre+'_xz_%02i.png'%yidx
figure(figsize=(12,8))
plot_xz(fpre+'_xz_%02i.png'%yidx, res, yidx=yidx)
for xidx in range(xi):
print fpre+'_yz_%02i.png'%xidx
figure(figsize=(8,10))
plot_yz(fpre+'_yz_%02i.png'%xidx, res, xidx=xidx)