def prepare_sweeps(self, rest_swp='auto', sweep_freq=500, Vpp=90*2, clip_level_minus=-88):
""" extracts sweep voltage data for all probes,
call restore_sin if necessary
Initially, the voltage data is assumed to be in a dictionary
"""
if self.debug > 0:
print('entering prepare_sweeps ', len(self.vmeasfull.signal[0]))
if str(rest_swp).lower() == 'auto':
rest_swp = self.shot[0]>20160309
print ('* Automatically setting rest_swp to {r} *'.format(r=rest_swp))
if rest_swp:
from pyfusion.data.restore_sin import restore_sin
self.vcorrfull = self.vmeasfull.copy()
if rest_swp:
for (c, sig) in enumerate(self.vmeasfull.signal):
self.vcorrfull.signal[c] = restore_sin(self.vmeasfull, chan=c, sweep_freq=sweep_freq,
Vpp=Vpp, clip_level_minus=clip_level_minus, verbose=self.verbose)
# Hilbert transform creates a transient at 0 - skip first and last 3000
w_plasma = np.where((np.abs(iprobe) > threshold) & (tb > tb[3000]) & (tb < tb[-3000]))[0]
if t_subrange is None:
t_subrange = [tb[w_plasma[0]], tb[w_plasma[-1]]]
if debug>1:
plt.plot(tb, iprobe,'g',label='R and phase')
plt.xlim(t_subrange[0]-.05, t_subrange[0]+.05)
if debug > 1: mainax.plot(t_subrange, [0, 0],'c*-', linewidth=3)
plt.legend(prop=dict(size='small'))
if restore_sweep:
from pyfusion.data.restore_sin import restore_sin
debug_(debug, 4, key='before_restore_sweep')
# for now, don't reduce time in restore_sin, because we want both single and multi segments to work
sweepV = restore_sin(sweepVmeas_rdata, clip_level_minus=restore_sweep, t_range=None)
# for now, put it back in the data object - a little messy - is it legal?
# probably better to return a new data object, as it could be
# faster to reduce the time base to a nicer number for FFTs
sweepVmeas_rdata.signal = sweepV
if len(t_range) == 2: # ==> one manual fit - not an auto series
inds = np.where((tb>t_range[0]) & (tb<t_range[1]))[0]
sweepV = sweepV[inds]
tb = tb[inds]
imeas = imeas[inds]
iprobe = iprobe[inds]
# doesn't matter if we look for clipping in restore vsweep - there shouldn't be any if it is restored
good = find_clipped([sweepV, imeas],fact=fact)
# Hilbert transform creates a transient at 0 - skip first and last 3000
w_plasma = np.where((np.abs(iprobe) > threshold) & (tb > tb[3000]) & (tb < tb[-3000]))[0]
if t_subrange is None:
t_subrange = [tb[w_plasma[0]], tb[w_plasma[-1]]]
if debug>1:
plt.plot(tb, iprobe,'g',label='R and phase')
plt.xlim(t_subrange[0]-.05, t_subrange[0]+.05)
if debug > 1: mainax.plot(t_subrange, [0, 0],'c*-', linewidth=3)
plt.legend(prop=dict(size='small'))
if restore_sweep:
from pyfusion.data.restore_sin import restore_sin
debug_(debug, 4, key='before_restore_sweep')
# for now, don't reduce time in restore_sin, because we want both single and multi segments to work
sweepV = restore_sin(sweepVmeas_rdata, clip_level_minus=restore_sweep, t_range=None)
# for now, put it back in the data object - a little messy - is it legal?
# probably better to return a new data object, as it could be
# faster to reduce the time base to a nicer number for FFTs
sweepVmeas_rdata.signal = sweepV
if len(t_range) == 2: # ==> one manual fit - not an auto series
inds = np.where((tb>t_range[0]) & (tb<t_range[1]))[0]
sweepV = sweepV[inds]
tb = tb[inds]
imeas = imeas[inds]
iprobe = iprobe[inds]
# doesn't matter if we look for clipping in restore vsweep - there shouldn't be any if it is restored
good = find_clipped([sweepV, imeas],fact=fact)
