def __init__(self,
metric,
matchedDataset,
pa1,
filter_name,
spec_name,
linkedBlobs=None,
job=None,
verbose=False):
MeasurementBase.__init__(self)
self.filter_name = filter_name
self.spec_name = spec_name # spec-dependent measure because of PF1 dep
self.metric = metric
pa2spec = self.metric.get_spec(spec_name, filter_name=self.filter_name).\
PA2.get_spec(spec_name, filter_name=self.filter_name)
self.register_parameter('pa2', datum=pa2spec.datum)
self.matchedDataset = matchedDataset
# Add external blob so that links will be persisted with
# the measurement
if linkedBlobs is not None:
for name, blob in linkedBlobs.items():
setattr(self, name, blob)
# Use first random sample from original PA1 measurement
magDiffs = pa1.magDiff[0, :]
self.quantity = 100 * np.mean(np.abs(magDiffs) > self.pa2) * u.Unit('')
if job:
job.register_measurement(self)
def __init__(self):
MeasurementBase.__init__(self)
self.metric = Metric('Test', 'Test metric', '<')
self.quantity = 5. * u.mag
# link a blob
self.ablob = DemoBlob()
# datum-based parameters
self.register_parameter('datum_param',
datum=Datum(10. * u.arcsec),
description='A datum')
# set this parameter later
self.register_parameter('deferred_datum_param', description='A datum')
# quantity-based parameter
self.register_parameter('q_param',
quantity=10. * u.arcsec,
description='A quantity')
# set this parameter later
self.register_parameter('deferred_q_param', description='A quantity')
# string-based parameters
self.register_parameter('str_param',
'test_string',
description='A string')
# set this parameter later
self.register_parameter('deferred_str_param', description='A string')
# boolean parameters
self.register_parameter('bool_param', False, description='A boolean')
# set this parameter later
self.register_parameter('deferred_bool_param', description='A boolean')
# int-type parameter
self.register_parameter('int_param',
42,
description='An integer parameter')
# set this parameter later
self.register_parameter('deferred_int_param', description='An integer')
# quantity-based extras
self.register_extra('q_extra',
quantity=1000. * u.microJansky,
description='Quantity extra')
# none-type extra
self.register_extra('none_extra',
label='none type',
description='None type Extra')
self.none_extra = None
def __init__(self,
metric,
matchedDataset,
amx,
filter_name,
spec_name,
job=None,
linkedBlobs=None,
verbose=False):
MeasurementBase.__init__(self)
self.metric = metric
self.filter_name = filter_name
self.spec_name = spec_name
# register input parameters for serialization
# note that matchedDataset is treated as a blob, separately
self.register_parameter('D', datum=amx.parameters['D'])
self.register_parameter('annulus', datum=amx.parameters['annulus'])
self.register_parameter('magRange', datum=amx.parameters['magRange'])
self.register_parameter('AMx', datum=amx.datum)
self.matchedDataset = matchedDataset
# Add external blobs so that links will be persisted with
# the measurement
if linkedBlobs is not None:
for name, blob in linkedBlobs.items():
setattr(self, name, blob)
# AFx's value at this spec level and filter must be known to measure
self.register_parameter('AFx',
datum=self.metric.get_spec_dependency(
self.spec_name,
'AF{0:d}'.format(self.metric.x.quantity),
filter_name=self.filter_name))
if amx.quantity is not None:
# No more than AFx of values will deviate by more than the
# AMx (50th) + AFx percentiles
# To compute ADx, use measured AMx and spec for AFx.
afxAtPercentile = np.percentile(amx.rmsDistMas.to(u.marcsec),
100. - self.AFx) * u.marcsec
self.quantity = afxAtPercentile - amx.quantity
else:
# FIXME previously would raise ValidateErrorNoStars
self.quantity = None
if job:
job.register_measurement(self)
def __init__(self, metric, matchedDataset, amx, filter_name, spec_name,
job=None, linkedBlobs=None, verbose=False):
MeasurementBase.__init__(self)
self.metric = metric
self.spec_name = spec_name
self.filter_name = filter_name
# register input parameters for serialization
# note that matchedDataset is treated as a blob, separately
self.register_parameter('D', datum=amx.parameters['D'])
self.register_parameter('annulus', datum=amx.parameters['annulus'])
self.register_parameter('magRange', datum=amx.parameters['magRange'])
self.register_parameter('AMx', datum=amx.datum)
self.matchedDataset = matchedDataset
# Add external blob so that links will be persisted with
# the measurement
if linkedBlobs is not None:
for name, blob in linkedBlobs.items():
setattr(self, name, blob)
self.register_parameter(
'ADx',
datum=self.metric.get_spec_dependency(
self.spec_name,
'AD{0:d}'.format(self.metric.x.quantity),
filter_name=self.filter_name))
if amx.quantity:
v = 100. * np.mean(amx.rmsDistMas > amx.quantity + self.ADx) * u.Unit('')
self.quantity = v
else:
# FIXME previously would raise ValidateErrorNoStars
self.quantity = None
if job:
job.register_measurement(self)
def __init__(self,
metric,
matchedDataset,
filter_name,
width=2.,
magRange=None,
linkedBlobs=None,
job=None,
verbose=False):
MeasurementBase.__init__(self)
self.metric = metric
self.filter_name = filter_name
# Register blob
self.matchedDataset = matchedDataset
# Measurement Parameters
self.register_parameter('D', datum=self.metric.D)
if not isinstance(width, u.Quantity):
width = width * u.arcmin
self.register_parameter('width',
quantity=width,
label='Width',
description='Width of annulus')
if magRange is None:
magRange = np.array([17.0, 21.5]) * u.mag
else:
assert len(magRange) == 2
if not isinstance(magRange, u.Quantity):
magRange = np.array(magRange) * u.mag
self.register_parameter('magRange',
quantity=magRange,
description='Stellar magnitude selection '
'range.')
annulus = self.D + (self.width / 2) * np.array([-1, +1])
self.register_parameter('annulus',
quantity=annulus,
label='annulus radii',
description='Inner and outer radii of '
'selection annulus.')
# Register measurement extras
self.register_extra('rmsDistMas', label='RMS')
# Add external blob so that links will be persisted with
# the measurement
if linkedBlobs is not None:
for name, blob in linkedBlobs.items():
setattr(self, name, blob)
matches = matchedDataset.safeMatches
rmsDistances = calcRmsDistances(matches,
self.annulus,
magRange=self.magRange,
verbose=verbose)
if len(rmsDistances) == 0:
# raise ValidateErrorNoStars(
# 'No stars found that are %.1f--%.1f arcmin apart.' %
# (annulus[0], annulus[1]))
# FIXME should we still report that this measurement was
# attempted instead of just crashing.
print('No stars found that are {0:.1f}--{1:.1f} apart.'.format(
self.annulus[0], self.annulus[1]))
self.rmsDistMas = None
self.quantity = None
else:
self.rmsDistMas = rmsDistances.to(u.marcsec)
self.quantity = np.median(self.rmsDistMas)
if job:
job.register_measurement(self)
def __init__(self):
MeasurementBase.__init__(self)
self.metric = Metric('Test', 'Test metric', '<')
self.quantity = None