gettime=True,
vector_norms=False)
#choosing positions
ylabel = 'z' if np.isclose(d['y'].max(), d['y'].min()) else 'y'
if opts['--x-restrict']:
res = parse_ftuple(opts['--x-restrict'], length=4)
res[:2] = [np.abs(d['x'][:, 0] * 1e4 - ires).argmin() for ires in res[:2]]
res[2:] = [
np.abs(d[ylabel][0, :] * 1e4 - ires).argmin() for ires in res[2:]
]
#including the edges
res[1] += 1
res[3] += 1
restrict(d, res)
elif opts['--restrict']:
res = parse_ituple(opts['--restrict'], length=None)
restrict(d, res)
x, y = d['x'] * 1e4, d[ylabel] * 1e4
avg = parse_ituple(opts['--average'], length=2)
#massaging data
t = d['t']
q = np.sum([d[Q] * i for Q, i in zip(qs, charges)], axis=0)
#averaging
acc = [q]
qp = np.pad(q, ((avg[0], ) * 2, (avg[1], ) * 2), 'edge')
qps = [
qp[:, avg[1]:-avg[1]],
qp[avg[0]:-avg[0], :],
]
for I, (ia, iqp) in enumerate(zip(avg, qps)):
l = 2 * ia + 1
d = read_indexed(int(opts['<i>']),
flds=fvar,sclr=qs,
gzip=gzip,dir=opts['--dir'],
gettime=True,vector_norms=False);
#choosing positions
ylabel = 'z' if np.isclose(d['y'].max(),d['y'].min()) else 'y';
if opts['--x-restrict']:
res = parse_ftuple(opts['--x-restrict'], length=4);
res[:2] = [ np.abs(d['x'][:,0]*1e4 - ires).argmin() for ires in res[:2] ];
res[2:] = [ np.abs(d[ylabel][0,:]*1e4 - ires).argmin() for ires in res[2:] ];
#including the edges
res[1]+=1;
res[3]+=1;
restrict(d,res);
elif opts['--restrict']:
res = parse_ituple(opts['--restrict'],length=None);
restrict(d,res);
x,y = d['x']*1e4, d[ylabel]*1e4;
avg = parse_ituple(opts['--average'],length=2);
#massaging data
t = d['t'];
q = np.sum([d[Q]*i for Q,i in zip(qs,charges)],axis=0);
#averaging
acc = [q];
qp = np.pad(q, ((avg[0],)*2, (avg[1],)*2), 'edge');
qps = [ qp[:,avg[1]:-avg[1]],
qp[avg[0]:-avg[0],:],];
for I,(ia,iqp) in enumerate(zip(avg,qps)):
l=2*ia + 1;
if l == 1: continue;
Is = [
quantity = opts['--quantity'];
fvar=['E']
if opts['--laser']:
fvar+=['B'];
titlestr=opts['--title']
units=opts['--units'];
svar=[quantity];
#####################################
#reading data
d = read_indexed(int(opts['<i>']),
flds=fvar,sclr=svar,
gzip=gzip,dir=opts['--dir'],
gettime=True,vector_norms=False);
if opts['--restrict']:
res = parse_ituple(opts['--restrict'],length=None);
restrict(d,res);
#massaging data
t = d['t'];
x,y = d['x']*1e4,d['y']*1e4
Ex,Ey = d['Ex']*1e5, d['Ey']*1e5;
if np.isclose(y.max(),y.min()):
y = d['z']*1e4
Ey = d['Ez']*1e5;
q = d[quantity];
dx = (x[1,0]-x[0,0])*1e-6;
dy = (y[0,1]-y[0,0])*1e-6;
rho = ( np.gradient(Ex,dx,axis=0) + np.gradient(Ey,dy,axis=1) ) * e0 / e * 1e-4;
files = os.listdir('.');
lspf=[f for f in files if re.search(".*\.lsp$",f)];
if len(lspf) < 1:
raise ValueError("Need to specify a .lsp file or see one in the same directory.");
lspf=lspf[0];
with open(lspf,"r") as f:
lsp=f.read();
if not opts['--output']:
outname = re.search("(.*)\.lsp$",lspf).group(1)+"-pext";
else:
outname = opts['--output'];
dim=getdim(lsp);
pext_info = getpexts(lsp);
if opts['--range']:
a=parse_ituple(opts['--range'],length=2);
mnpext,mxpext = min(*a),max(*a);
else:
mnpext,mxpext = float('-inf'),float('inf');
outkeys = set();
allkeys = [];
def getpextfnames(path):
files = os.listdir(path);
pext = [f for f in files if re.search("pext[0-9]+.p4",f)];
key = [ float(re.search("pext([0-9]+).p4",f).group(1))
for f in pext ];
return [ ('{}/{}'.format(path,i),k) for i,k in zip(pext,key)
if mnpext <= k <= mxpext];
#read first directory. Must do this in order to get headers AND not skip ahead.
pextfnames = getpextfnames(opts['<dirs>'][0]);
keys = [ i[1] for i in pextfnames ];
titlestr=opts['--title']
units=opts['--units'];
svar=[quantity];
#####################################
#reading data
i = int(opts['<i>']);
d = read_indexed(i,
flds=fvar,sclr=svar,
gzip=gzip,dir=opts['--dir'],
gettime=True,vector_norms=False);
t = d['t'];
if opts['--traj']:
factor, offset = None, None;
if opts['--traj-offset']:
factor, offset = parse_ituple(opts['--traj-offset'],length=2);
with np.load(opts['--traj'], mmap_mode='r') as f:
if factor:
tri = i*factor+offset;
trt = f['time'][tri];
if not np.isclose(trt,t):
import sys
sys.stderr.write(
"warning: time from trajectory is {} while time from sclr is {}\n".format(
trt,t));
else:
tri = np.sum((f['time'] <= t).astype(int));
trt = f['time'][tri];
tr = f['data'][:tri+1,:];
if opts['--traj-n']:
tr = tr[:,:int(opts['--traj-n'])];
clim=(-1e19, 1e19),
linthresh=1e15,
),
#pmovies
no_pmovies=False,
#particle dumps
dump_particle=True,
particle_dump_interval_ns=0.0,
particle_dump_times_ns=(1.1e-4, 1.4e-4),
pext_species=(17, 18),
)
if opts['--make-target']:
try:
targi = [int(opts['--make-target'])]
except ValueError:
targi = parse_ituple(opts['--make-target'], length=3)
elif opts['--make-targets']:
targi = [0, 1, 2]
else:
targi = []
if 0 not in targi:
print("be sure to make this dat {} seperately".format(0))
else:
d['f_2D'] = mk45(dim=(-5, 5, -5, 5),
N0=1.0804e22,
width=0.46e-4,
dropcorners=False)
d['dat_xres'] = 10000
print("making targets...sit tight.")
gensim(**d)
flds=fvar,sclr=svar,
gzip=gzip,dir=opts['--dir'],
gettime=True,vector_norms=False);
#choosing positions
ylabel = 'z' if np.isclose(d['y'].max(),d['y'].min()) else 'y';
if opts['--x-restrict']:
res = parse_ftuple(opts['--x-restrict'], length=4);
res[:2] = [ np.abs(d['x'][:,0]*1e4 - ires).argmin() for ires in res[:2] ];
res[2:] = [ np.abs(d[ylabel][0,:]*1e4 - ires).argmin() for ires in res[2:] ];
#including the edges
res[1]+=1;
res[3]+=1;
restrict(d,res);
elif opts['--restrict']:
res = parse_ituple(opts['--restrict'],length=None);
restrict(d,res);
x,y = d['x']*1e4, d[ylabel]*1e4;
#massaging data
t = d['t'];
q = d[quantity];
#####################################
#plotting
#getting options from user
mn,mx = parse_ftuple(opts['--lims'],length=2);
if opts['--rotate']:
rot,flip = True, False;
else:
ylabel='y';
coord = float(opts['--3d-coord'])*1e-4;
dx = float(opts['--3d-width'])*1e-4;
d=flatten3d_aa(d,coord=coord, dx=dx,axis=flataxis);
del d[flataxis];
if opts['--x-restrict']:
res = parse_ftuple(opts['--x-restrict'], length=4);
res[:2] = [ np.abs(d[xlabel][:,0]*1e4 - ires).argmin() for ires in res[:2] ];
res[2:] = [ np.abs(d[ylabel][0,:]*1e4 - ires).argmin() for ires in res[2:] ];
#including the edges
res[1]+=1;
res[3]+=1;
restrict(d,res);
elif opts['--restrict']:
res = parse_ituple(opts['--restrict'],length=None);
restrict(d,res);
#trajectories
if opts['--traj']:
factor, offset = None, None;
if opts['--traj-offset']:
factor, offset = parse_ituple(opts['--traj-offset'],length=2);
with np.load(opts['--traj'], mmap_mode='r') as f:
if factor:
tri = i*factor+offset;
trt = f['time'][tri];
if not np.isclose(trt,t):
import sys
sys.stderr.write(
"warning: time from trajectory is {} while time from sclr is {}\n".format(