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;
#####################################
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], :],
]
"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'])];
if opts['--verbose']:
print("size of trajectories: {}".format(tr.shape));
print("final time is {}".format(trt));
print("with sclr time as {}".format(t));
pass;
if opts['--restrict']:
res = parse_ituple(opts['--restrict'],length=None);
restrict(d,res);
#massaging data
x,y = d['x']*1e4,d['y']*1e4
coords = ['x','y'];
if np.isclose(y.max(),y.min()):
y = d['z']*1e4
coords[1] = 'z';
q = d[quantity];
#####################################
#plotting
#getting options from user
mn,mx = parse_ftuple(opts['--lims'],length=2);
myhi = float(opts['--highlight']);