def fit(self, table ) :
"""TODO: document"""
log = get_logger()
#- identify ADC setups
adc12=(np.array(table['ADC1'])+1000*np.array(table['ADC2']))
uadc12 = np.unique(adc12)
nconfig = len(uadc12)
self.adc1 = np.zeros(nconfig,dtype=float)
self.adc2 = np.zeros(nconfig,dtype=float)
self.scale = np.zeros(nconfig,dtype=float)
self.rotation = np.zeros(nconfig,dtype=float)
self.offset_x = np.zeros(nconfig,dtype=float)
self.offset_y = np.zeros(nconfig,dtype=float)
self.zbpolids = None
self.zbcoeffs = list()
for config, adc12v in enumerate(uadc12) :
selection = (adc12==adc12v)
self.adc1[config]=table['ADC1'][selection][0]
self.adc2[config]=table['ADC2'][selection][0]
print("Fitting ADC1={} ADC2={}".format(self.adc1[config],self.adc2[config]))
#- Get reduced coordinates
rxtan, rytan = _reduce_xytan(table['X_TAN'][selection], table['Y_TAN'][selection])
rxfp, ryfp = _reduce_xyfp(table['X_FP'][selection], table['Y_FP'][selection])
#################################################################
## CHOICE OF POLYNOMIALS IS HERE
##
polids = np.array([2, 5, 6, 9, 20, 27, 28, 29, 30],dtype=int)
#################################################################
#- Perform fit
if 1 : # it's a bit better
scale, rotation, offset_x, offset_y, zbpolids, zbcoeffs = fit_scale_rotation_offset(rxtan, rytan, rxfp, ryfp, fitzb=True, polids=polids)
self.scale[config] = scale
self.rotation[config] = rotation
self.offset_x[config] = offset_x
self.offset_y[config] = offset_y
else :
zbpolids, zbcoeffs, dx, dy = fitZhaoBurge(rxtan, rytan, rxfp, ryfp, polids=polids)
self.scale[config] = 1
self.rotation[config] = 0.
self.offset_x[config] = 0.
self.offset_y[config] = 0.
if self.zbpolids is None :
self.zbpolids = zbpolids
else :
assert(np.all(self.zbpolids==zbpolids))
self.zbcoeffs.append(zbcoeffs)
#- Goodness of fit
#xfp_fit, yfp_fit = self.tan2fp(table['X_TAN'][selection], table['Y_TAN'][selection])
#dx = (table['X_FP'][selection] - xfp_fit)
#dy = (table['Y_FP'][selection] - yfp_fit)
#dr = np.sqrt(dx**2 + dy**2)
#log.info('Mean, median, RMS distance = {:.1f}, {:.1f}, {:.1f} um'.format(
# 1000*np.mean(dr), 1000*np.median(dr), 1000*np.sqrt(np.mean(dr**2))))
self.zbcoeffs = np.vstack(self.zbcoeffs)
def fit(self, spots, metrology=None, update_spots=False):
"""TODO: document"""
log = get_logger()
if metrology is not None:
self.metrology = metrology
else:
filename = resource_filename('desimeter', "data/fp-metrology.csv")
if not os.path.isfile(filename):
log.error("cannot find {}".format(filename))
raise IOError("cannot find {}".format(filename))
log.info("reading fiducials metrology in {}".format(filename))
self.metrology = Table.read(filename, format="csv")
#- Trim spots to just fiducial spots (not posioners, not unmatchs spots)
ii = (spots['LOCATION'] > 0) & (spots['PINHOLE_ID'] > 0)
fidspots = spots[ii]
#- trim metrology to just the ones that have spots
fidspots_pinloc = fidspots['LOCATION'] * 10 + fidspots['PINHOLE_ID']
metro_pinloc = self.metrology['LOCATION'] * 10 + self.metrology[
'PINHOLE_ID']
jj = np.in1d(metro_pinloc, fidspots_pinloc)
metrology = self.metrology[jj]
#- Sort so that they match each other
fidspots.sort(keys=('LOCATION', 'PINHOLE_ID'))
metrology.sort(keys=('LOCATION', 'PINHOLE_ID'))
assert np.all(fidspots['LOCATION'] == metrology['LOCATION'])
assert np.all(fidspots['PINHOLE_ID'] == metrology['PINHOLE_ID'])
#- Get reduced coordinates
rxpix, rypix = _reduce_xyfvc(fidspots['XPIX'], fidspots['YPIX'])
rxfp, ryfp = _reduce_xyfp(metrology['X_FP'], metrology['Y_FP'])
#- Perform fit
#- Perform fit
scale, rotation, offset_x, offset_y, zbpolids, zbcoeffs = \
fit_scale_rotation_offset(rxpix, rypix, rxfp, ryfp, fitzb=True)
self.scale = scale
self.rotation = rotation
self.offset_x = offset_x
self.offset_y = offset_y
self.zbpolids = zbpolids
self.zbcoeffs = zbcoeffs
#- Goodness of fit
xfp_fidmeas, yfp_fidmeas = self.fvc2fp(fidspots['XPIX'],
fidspots['YPIX'])
dx = (metrology['X_FP'] - xfp_fidmeas)
dy = (metrology['Y_FP'] - yfp_fidmeas)
dr = np.sqrt(dx**2 + dy**2)
log.info(
'Mean, median, RMS distance = {:.1f}, {:.1f}, {:.1f} um'.format(
1000 * np.mean(dr), 1000 * np.median(dr),
1000 * np.sqrt(np.mean(dr**2))))
if update_spots:
xfp_meas, yfp_meas = self.fvc2fp(spots['XPIX'], spots['YPIX'])
spots["X_FP"] = xfp_meas
spots["Y_FP"] = yfp_meas
#- the metrology table is in a different order than the original
#- spots table, which is also a superset of the fidicual spots
#- matched to the metrology, so find the sorting of the metrology
#- that will match the order that they appear in the spots table
iifid = (spots['LOCATION'] > 0) & (spots['PINHOLE_ID'] > 0)
fidspots_pinloc = (spots['LOCATION'] * 10 +
spots['PINHOLE_ID'])[iifid]
metro_pinloc = metrology['LOCATION'] * 10 + metrology['PINHOLE_ID']
ii = np.argsort(np.argsort(fidspots_pinloc))
jj = np.argsort(metro_pinloc)
kk = jj[ii]
#- Check that we got that dizzying array of argsorts right
assert np.all(
spots['LOCATION'][iifid] == metrology['LOCATION'][kk])
assert np.all(
spots['PINHOLE_ID'][iifid] == metrology['PINHOLE_ID'][kk])
#- Update the spots table with metrology columns
#- TODO: used masked arrays in addition to default=0
spots["X_FP_METRO"] = np.zeros(len(spots))
spots["Y_FP_METRO"] = np.zeros(len(spots))
spots["Z_FP_METRO"] = np.zeros(len(spots))
spots["X_FP_METRO"][iifid] = metrology['X_FP'][kk]
spots["Y_FP_METRO"][iifid] = metrology['Y_FP'][kk]
spots["Z_FP_METRO"][iifid] = metrology['Z_FP'][kk]
def fit(self,
spots,
metrology=None,
update_spots=False,
zbfit=True,
fixed_scale=False,
fixed_rotation=False):
"""
TODO: document
"""
log = get_logger()
if metrology is not None:
self.metrology = metrology
else:
self.metrology = load_metrology()
#- Trim spots to just fiducial spots (not posioners, not unmatchs spots)
ii = (spots['LOCATION'] >= 0) & (spots['PINHOLE_ID'] > 0)
fidspots = spots[ii]
#- trim metrology to just the ones that have spots
fidspots_pinloc = fidspots['LOCATION'] * 10 + fidspots['PINHOLE_ID']
metro_pinloc = self.metrology['LOCATION'] * 10 + self.metrology[
'PINHOLE_ID']
jj = np.in1d(metro_pinloc, fidspots_pinloc)
metrology = self.metrology[jj]
#- Sort so that they match each other
fidspots.sort(keys=('LOCATION', 'PINHOLE_ID'))
metrology.sort(keys=('LOCATION', 'PINHOLE_ID'))
assert np.all(fidspots['LOCATION'] == metrology['LOCATION'])
assert np.all(fidspots['PINHOLE_ID'] == metrology['PINHOLE_ID'])
#- Get reduced coordinates
rxpix, rypix = self._reduce_xyfvc(fidspots['XPIX'], fidspots['YPIX'])
rxfp, ryfp = self._reduce_xyfp(metrology['X_FP'], metrology['Y_FP'])
if fixed_rotation:
fixed_rotation_value = self.rotation
log.info(
"Use fixed rotation = {:5.4f}".format(fixed_rotation_value))
else:
fixed_rotation_value = None
if fixed_scale:
fixed_scale_value = self.scale
log.info("Use fixed scale = {:5.4f}".format(fixed_scale_value))
else:
fixed_scale_value = None
res = fit_scale_rotation_offset(rxpix,
rypix,
rxfp,
ryfp,
fitzb=zbfit,
zbpolids=self.zbpolids,
zbcoeffs=self.zbcoeffs,
fixed_scale=fixed_scale_value,
fixed_rotation=fixed_rotation_value)
self.scale = res[0]
self.rotation = res[1]
self.offset_x = res[2]
self.offset_y = res[3]
if zbfit:
self.zbpolids = res[4]
self.zbcoeffs = res[5]
#- Goodness of fit
xfp_fidmeas, yfp_fidmeas = self.fvc2fp(fidspots['XPIX'],
fidspots['YPIX'])
dx = (metrology['X_FP'] - xfp_fidmeas)
dy = (metrology['Y_FP'] - yfp_fidmeas)
dr = np.sqrt(dx**2 + dy**2)
log.info(
'Mean, median, RMS distance = {:.1f}, {:.1f}, {:.1f} um'.format(
1000 * np.mean(dr), 1000 * np.median(dr),
1000 * np.sqrt(np.mean(dr**2))))
if update_spots:
xfp_meas, yfp_meas = self.fvc2fp(spots['XPIX'], spots['YPIX'])
spots["X_FP"] = xfp_meas
spots["Y_FP"] = yfp_meas
#- the metrology table is in a different order than the original
#- spots table, which is also a superset of the fidicual spots
#- matched to the metrology, so find the sorting of the metrology
#- that will match the order that they appear in the spots table
iifid = (spots['LOCATION'] > 0) & (spots['PINHOLE_ID'] > 0)
fidspots_pinloc = (spots['LOCATION'] * 10 +
spots['PINHOLE_ID'])[iifid]
metro_pinloc = metrology['LOCATION'] * 10 + metrology['PINHOLE_ID']
ii = np.argsort(np.argsort(fidspots_pinloc))
jj = np.argsort(metro_pinloc)
kk = jj[ii]
#- Check that we got that dizzying array of argsorts right
assert np.all(
spots['LOCATION'][iifid] == metrology['LOCATION'][kk])
assert np.all(
spots['PINHOLE_ID'][iifid] == metrology['PINHOLE_ID'][kk])
#- Update the spots table with metrology columns
#- TODO: used masked arrays in addition to default=0
spots["X_FP_METRO"] = np.zeros(len(spots))
spots["Y_FP_METRO"] = np.zeros(len(spots))
spots["Z_FP_METRO"] = np.zeros(len(spots))
spots["X_FP_METRO"][iifid] = metrology['X_FP'][kk]
spots["Y_FP_METRO"][iifid] = metrology['Y_FP'][kk]
spots["Z_FP_METRO"][iifid] = metrology['Z_FP'][kk]