def test_metadata_merging_new_strategy():
original_merge_strategies = list(metadata.MERGE_STRATEGIES)
class MergeNumbersAsList(metadata.MergeStrategy):
"""
Scalar float or int values are joined in a list.
"""
types = ((int, float), (int, float))
@classmethod
def merge(cls, left, right):
return [left, right]
class MergeConcatStrings(metadata.MergePlus):
"""
Scalar string values are concatenated
"""
types = (str, str)
enabled = False
# Normally can't merge two scalar types
meta1 = {'k1': 1, 'k2': 'a'}
meta2 = {'k1': 2, 'k2': 'b'}
# Enable new merge strategy
with enable_merge_strategies(MergeNumbersAsList, MergeConcatStrings):
assert MergeNumbersAsList.enabled
assert MergeConcatStrings.enabled
out = merge(meta1, meta2, metadata_conflicts='error')
assert out['k1'] == [1, 2]
assert out['k2'] == 'ab'
assert not MergeNumbersAsList.enabled
assert not MergeConcatStrings.enabled
# Confirm the default enabled=False behavior
with pytest.raises(MergeConflictError):
merge(meta1, meta2, metadata_conflicts='error')
# Enable all MergeStrategy subclasses
with enable_merge_strategies(metadata.MergeStrategy):
assert MergeNumbersAsList.enabled
assert MergeConcatStrings.enabled
out = merge(meta1, meta2, metadata_conflicts='error')
assert out['k1'] == [1, 2]
assert out['k2'] == 'ab'
assert not MergeNumbersAsList.enabled
assert not MergeConcatStrings.enabled
metadata.MERGE_STRATEGIES = original_merge_strategies
def test_metadata_merging_new_strategy():
original_merge_strategies = list(metadata.MERGE_STRATEGIES)
class MergeNumbersAsList(metadata.MergeStrategy):
"""
Scalar float or int values are joined in a list.
"""
types = ((int, float), (int, float))
@classmethod
def merge(cls, left, right):
return [left, right]
class MergeConcatStrings(metadata.MergePlus):
"""
Scalar string values are concatenated
"""
types = (str, str)
enabled = False
# Normally can't merge two scalar types
meta1 = {'k1': 1, 'k2': 'a'}
meta2 = {'k1': 2, 'k2': 'b'}
# Enable new merge strategy
with enable_merge_strategies(MergeNumbersAsList, MergeConcatStrings):
assert MergeNumbersAsList.enabled
assert MergeConcatStrings.enabled
out = merge(meta1, meta2, metadata_conflicts='error')
assert out['k1'] == [1, 2]
assert out['k2'] == 'ab'
assert not MergeNumbersAsList.enabled
assert not MergeConcatStrings.enabled
# Confirm the default enabled=False behavior
with pytest.raises(MergeConflictError):
merge(meta1, meta2, metadata_conflicts='error')
# Enable all MergeStrategy subclasses
with enable_merge_strategies(metadata.MergeStrategy):
assert MergeNumbersAsList.enabled
assert MergeConcatStrings.enabled
out = merge(meta1, meta2, metadata_conflicts='error')
assert out['k1'] == [1, 2]
assert out['k2'] == 'ab'
assert not MergeNumbersAsList.enabled
assert not MergeConcatStrings.enabled
metadata.MERGE_STRATEGIES = original_merge_strategies
def hstack_catalogs(catalogs, output_cat):
cats = []
for cat in catalogs:
cats.append(Table.read(cat))
with enable_merge_strategies(MergeNumbersAsList):
full_cat = hstack(cats)
print('Writing full catalog to ' + output_cat)
full_cat.write(output_cat, format='fits', overwrite=True)
return output_cat
def __call__(self, photons):
areas = u.Quantity([e.area for e in self.elements])
aperid = np.digitize(np.random.rand(len(photons)), np.cumsum(areas) / self.area)
# Add ID number to ID col, if requested
if self.id_col is not None:
photons[self.id_col] = aperid
outs = []
for i, elem in enumerate(self.elements):
thisphot = photons[aperid == i]
for p in self.preprocess_steps:
p(thisphot)
thisphot = elem(thisphot)
for p in self.postprocess_steps:
p(thisphot)
outs.append(thisphot)
with enable_merge_strategies(utils.MergeIdentical):
photons = table.vstack(outs)
return photons
def load_patch(butler_or_repo,
tract,
patch,
fields_to_join=('id', ),
filters={
'u': 'u',
'g': 'g',
'r': 'r',
'i': 'i',
'z': 'z',
'y': 'y'
},
trim_colnames_for_fits=False,
verbose=False):
"""Load patch catalogs. Return merged catalog across filters.
butler_or_repo: Butler object or str
Either a Butler object or a filename to the repo
tract: int
Tract in skymap
patch: str
Patch in the tract in the skymap
fields_to_join: iterable of str
Join the catalogs for each filter on these fields
filters: iterable of str
Filter names to load
trim_colnames_for_fits: bool
Trim column names to satisfy the FITS standard character limit of <68.
Returns
--
AstroPy Table of patch catalog merged across filters.
"""
if isinstance(butler_or_repo, str):
butler = Butler(butler_or_repo)
else:
butler = butler_or_repo
# Define the filters and order in which to sort them.:
tract_patch_data_id = {'tract': tract, 'patch': patch}
try:
ref_table = butler.get(datasetType='deepCoadd_ref',
dataId=tract_patch_data_id).asAstropy()
except NoResults as e:
if verbose:
print(" ", e)
return Table()
isPrimary = ref_table['detect_isPrimary']
ref_table = ref_table[isPrimary]
if len(ref_table) == 0:
if verbose:
print(" No good isPrimary entries for tract %d, patch %s" %
(tract, patch))
return ref_table
merge_filter_cats = {}
for filt in filters:
this_data = tract_patch_data_id.copy()
this_data['filter'] = filters[filt]
try:
cat = butler.get(datasetType='deepCoadd_forced_src',
dataId=this_data).asAstropy()
except NoResults as e:
if verbose:
print(" ", e)
continue
CoaddCalib = butler.get('deepCoadd_calexp_calib', this_data)
CoaddCalib.setThrowOnNegativeFlux(False)
mag, mag_err = CoaddCalib.getMagnitude(cat['base_PsfFlux_flux'],
cat['base_PsfFlux_fluxSigma'])
cat['mag'] = mag
cat['mag_err'] = mag_err
cat['SNR'] = np.abs(
cat['base_PsfFlux_flux']) / cat['base_PsfFlux_fluxSigma']
cat = cat[isPrimary]
merge_filter_cats[filt] = cat
merged_patch_cat = ref_table
for filt in filters:
if filt not in merge_filter_cats:
continue
cat = merge_filter_cats[filt]
if len(cat) < 1:
continue
# Rename duplicate columns with prefix of filter
prefix_columns(cat, filt, fields_to_skip=fields_to_join)
# Merge metadata with concatenation
with enable_merge_strategies(MergeNumbersAsList,
MergeListNumbersAsList):
merged_patch_cat = join(merged_patch_cat, cat, keys=fields_to_join)
if trim_colnames_for_fits:
# FITS column names can't be longer that 68 characters
# Trim here to ensure consistency across any format we write this out to
trim_long_colnames(merged_patch_cat)
return merged_patch_cat
'/melkor/d1/guenther/Dropbox/REDSoX File Transfers/raytrace/inputdata/mk421_spec.txt',
format='ascii.no_header',
names=['wave', 'fluxperwave'])
spectrum['energy'] = 1.2398419292004202e-06 / (spectrum['wave'] * 1e-7)
spectrum['flux'] = spectrum['fluxperwave'] / 12.398419292004202 * spectrum[
'wave']**2
spectrum.sort('energy')
# Now limit to the range where I have coefficients for gratings etc.
spectrum = spectrum[(spectrum['wave'] > 25.) & (spectrum['wave'] < 75.)]
flux = np.sum(spectrum['flux'][1:] * np.diff(spectrum['energy']))
my_sourcepol = PointSource(coords=SkyCoord(30., 30., unit='deg'),
energy=spectrum,
flux=0.2 * flux,
polarization=120.,
geomarea=Ageom)
my_sourceunpol = PointSource(coords=SkyCoord(30., 30., unit='deg'),
energy=spectrum,
flux=0.8 * flux,
geomarea=Ageom)
ppol = my_sourcepol.generate_photons(300)
punpol = my_sourceunpol.generate_photons(300)
with enable_merge_strategies(utils.MergeIdentical):
photons = vstack([ppol, punpol])
photons = mypointing(photons)
len(photons)
photons = redsox.redsox(photons)
photons.write('/melkor/d1/guenther/projects/REDSoX/sims/photons_spectrum.fits',
overwrite=True)