def LCFS_plot(da, diag, t0_utc, t_range, av=None, ax=None, xtoLCFS=1, nrm=None, labelpoints=False, col=None, Tesmooth=None):
""" plot Te ne etc vs distance to LCFS, averaging over a time range.
The average uses a Nanmean by default, so it does not de-emphasize
values with large uncertainties.
Alternatively np.median can be used - but it treats nans as large => bias up
"""
av = np.nanmean if av is None else av
ax = plt.gca() if ax is None else ax
chans = np.array(da['info']['channels'])
dt = (t0_utc - da['info']['params']['i_diag_utc'][0])/1e9
indrange = np.searchsorted(da['t_mid'], np.array(t_range) + dt)
inds = range(*indrange)
if len(inds) < 3:
ll = len(inds)
pyfusion.logging.warn('{msg} samples ({ll}) in the time range {t}'
.format(msg=['!No! ','too few'][ll>0], ll=ll, t=t_range))
distLCFS = []
td = [] # td is transverse signed distance from limiter vertical midplane
if diag in ['ne18','Pdens','I0']:
exclude.extend(['LP11','LP12','L57_LP09'])
for (c, ch) in enumerate(chans):
LPnum = int(ch[-2:])
lim = 'lower' if 'L57' in ch else 'upper'
X, Y, Z, dLCFS = lookupPosition(LPnum, lim)
td.append(rot(X, Y, 2*np.pi*4/5.)[1])
distLCFS.append(dLCFS)
if diag in ['ne18', 'Te', 'I0', 'Vf', 'Vp']:
if diag=='Vf' and 'Vp' in da.keys():
diag = 'Vp'
sig = av(da.masked[diag][inds], axis=0)
if 'e'+diag in da:
ebars = av(da['e'+diag][inds], axis=0)
else:
ebars = None
else:
sig, ebars = get_calculated(da, diag, inds, av=av, x=td, nrm=nrm, Tesmooth=Tesmooth)
sig = av(sig[inds], axis=0)
#print()
# normalise before plots - intended for ne and I0 to allow for probe wear
if nrm is not None:
sig = sig/nrm
if debug>0:
print(nrm)
signed_dLCFS = distLCFS * np.sign(td)
for (c, ch) in enumerate(chans):
if sum([st in ch for st in exclude]):
sig[c] = np.nan
if labelpoints>0 and (not np.isnan(sig[c])):
if labelpoints>1 or sig[c]>1.3*np.median(sig):
ax.text(signed_dLCFS[c], sig[c], ch)
ax.errorbar([td, signed_dLCFS][xtoLCFS], sig, ebars, fmt='o', label=lim, color=col, lw=0.5)
ax.set_ylabel(diag)
#if diag == 'Te':
ax.set_ylim(0, ax.get_ylim()[1])
return(signed_dLCFS, td, sig, ebars)
from lukas.PickledAssistant import lookupPosition
for lim in ['lower','upper']:
print('\n ===== Limiter {l} ===== '.format(l=lim))
print('Probe X, Y, Z, dLCFS')
for LPnum in range(1,20+1):
X,Y,Z,dLC = lookupPosition(LPnum, lim)
print('LP{LPnum:02}: {xyz}: {dLC:6.2f}'
.format(LPnum=LPnum, xyz=np.round([X,Y,Z], 2), dLC=dLC))
