def match_2dhist_fit(imglist, reference_catalog, print_fit_parameters=True):
"""Perform cross-matching and final fit using 2dHistogram matching
Parameters
----------
imglist : list
List of input image NDData objects with metadata and source catalogs
reference_catalog : Table
Astropy Table of reference sources for this field
print_fit_parameters : bool
Specify whether or not to print out FIT results for each chip
Returns
--------
fit_rms : float
Visit level RMS for the FIT
fit_num : int
Number of sources used to generate visit level FIT and `fit_rms`
"""
print(
"-------------------- STEP 5b: (match_2dhist_fit) Cross matching and fitting --------------------"
)
# Specify matching algorithm to use
match = tweakwcs.TPMatch(searchrad=75,
separation=0.1,
tolerance=2.0,
use2dhist=True)
# Align images and correct WCS
tweakwcs.tweak_image_wcs(imglist, reference_catalog, match=match)
# Interpret RMS values from tweakwcs
interpret_fit_rms(imglist, reference_catalog)
# determine the quality of the fit
fit_rms, fit_num = determine_fit_quality(
imglist, print_fit_parameters=print_fit_parameters)
return fit_rms, fit_num
def test_pipeline(self, input_filenames):
"""Test of new pipeline alignment components (call separately)
This test performs separate fits to each chip separately.
Success Criteria
-----------------
* nmatches > 0 on all chips
* xrms and yrms < 30mas on all chips
"""
self.input_loc = 'catalog_tests'
self.curdir = os.getcwd()
truth_path = [self.input_repo, self.tree, self.input_loc, *self.ref_loc]
if not isinstance(input_filenames, list):
input_filenames = [input_filenames]
# Use this to collect all failures BEFORE throwing AssertionError
failures=False
try:
# Make local copies of input files
local_files = []
for infile in input_filenames:
downloaded_files = self.get_input_file(infile, docopy=True)
local_files.extend(downloaded_files)
# generate reference catalog
refcat = amutils.create_astrometric_catalog(local_files, catalog='GAIADR2')
# Generate source catalogs for each input image
source_catalogs = generate_source_catalogs(local_files)
# Convert input images to tweakwcs-compatible NDData objects and
# attach source catalogs to them.
imglist = []
for group_id,image in enumerate(local_files):
imglist.extend(amutils.build_nddata(image, group_id,
source_catalogs[image]['catalog_table']))
# Specify matching algorithm to use
match = tweakwcs.TPMatch(searchrad=250, separation=0.1,
tolerance=5, use2dhist=True)
# Align images and correct WCS
tweakwcs.tweak_image_wcs(imglist, refcat, match=match)
for chip in imglist:
status = chip.meta['tweakwcs_info']['status']
if status.startswith('FAIL'):
failures = True
print("STATUS for {}: {}".format(chip.meta['filename'], status))
break
except Exception:
failures = True
print("ALIGNMENT EXCEPTION: Failed to align {}".format(infile))
if not failures:
for chip in imglist:
tweak_info = chip.meta.get('tweakwcs_info', None)
chip_id = chip.meta.get('chip_id',1)
# determine 30mas limit in pixels
xylimit = 30
# Perform comparisons
nmatches = tweak_info['nmatches']
xrms,yrms = tweak_info['rms']
xrms *= chip.wcs.pscale*1000
yrms *= chip.wcs.pscale*1000
if any([nmatches==0, xrms>xylimit, yrms>xylimit]):
failures = True
msg1 = "Observation {}[{}] failed alignment with "
msg2 = " RMS=({:.4f},{:.4f})mas [limit:{:.4f}mas] and NMATCHES={}"
print(msg1.format(infile, chip_id))
print(msg2.format(xrms, yrms, xylimit, nmatches))
assert(not failures)
def perform_align(input_list,
archive=False,
clobber=False,
update_hdr_wcs=False):
"""Main calling function.
Parameters
----------
input_list : list
List of one or more IPPSSOOTs (rootnames) to align.
archive : Boolean
Retain copies of the downloaded files in the astroquery created sub-directories?
clobber : Boolean
Download and overwrite existing local copies of input files?
update_hdr_wcs : Boolean
Write newly computed WCS information to image image headers?
Returns
-------
int value 0 if successful, int value 1 if unsuccessful
"""
# Define astrometric catalog list in priority order
catalogList = ['GAIADR2', 'GSC241']
numCatalogs = len(catalogList)
# 0: print git info
print(
"-------------------- STEP 0: Display Git revision info --------------------"
)
full_path = os.path.dirname(__file__) + "/utils"
repo_path = None
if "hlapipeline/hlapipeline" in full_path:
repo_path = full_path.split(
"hlapipeline/hlapipeline")[0] + "hlapipeline"
elif "hlapipeline" in full_path:
repo_path = full_path.split("hlapipeline")[0] + "hlapipeline"
else:
pass
if not os.path.exists(repo_path):
repo_path = None # protect against non-existent paths
if repo_path:
get_git_rev_info.print_rev_id(
repo_path) # Display git repository information
else:
print(
"WARNING: Unable to display Git repository revision information.")
# 1: Interpret input data and optional parameters
print("-------------------- STEP 1: Get data --------------------")
imglist = check_and_get_data(input_list, archive=archive, clobber=clobber)
print("\nSUCCESS")
# 2: Apply filter to input observations to insure that they meet minimum criteria for being able to be aligned
print("-------------------- STEP 2: Filter data --------------------")
filteredTable = filter.analyze_data(imglist)
# Check the table to determine if there is any viable data to be aligned. The
# 'doProcess' column (bool) indicates the image/file should or should not be used
# for alignment purposes.
if filteredTable['doProcess'].sum() == 0:
print("No viable images in filtered table - no processing done.\n")
return (1)
# Get the list of all "good" files to use for the alignment
processList = filteredTable['imageName'][np.where(
filteredTable['doProcess'])]
processList = list(
processList
) #Convert processList from numpy list to regular python list
print("\nSUCCESS")
# 3: Build WCS for full set of input observations
print("-------------------- STEP 3: Build WCS --------------------")
refwcs = amutils.build_reference_wcs(processList)
print("\nSUCCESS")
# 4: Retrieve list of astrometric sources from database
# While loop to accommodate using multiple catalogs
doneFitting = False
catalogIndex = 0
extracted_sources = None
while not doneFitting:
skip_all_other_steps = False
retry_fit = False
print(
"-------------------- STEP 4: Detect astrometric sources --------------------"
)
print("Astrometric Catalog: ", catalogList[catalogIndex])
reference_catalog = generate_astrometric_catalog(
processList, catalog=catalogList[catalogIndex])
# The table must have at least MIN_CATALOG_THRESHOLD entries to be useful
if len(reference_catalog) >= MIN_CATALOG_THRESHOLD:
print("\nSUCCESS")
else:
if catalogIndex < numCatalogs - 1:
print("Not enough sources found in catalog " +
catalogList[catalogIndex])
print("Try again with the next catalog")
catalogIndex += 1
retry_fit = True
skip_all_other_steps = True
else:
print(
"Not enough sources found in any catalog - no processing done."
)
return (1)
if not skip_all_other_steps:
# 5: Extract catalog of observable sources from each input image
print(
"-------------------- STEP 5: Source finding --------------------"
)
if not extracted_sources:
extracted_sources = generate_source_catalogs(processList)
for imgname in extracted_sources.keys():
table = extracted_sources[imgname]["catalog_table"]
# The catalog of observable sources must have at least MIN_OBSERVABLE_THRESHOLD entries to be useful
total_num_sources = 0
for chipnum in table.keys():
total_num_sources += len(table[chipnum])
if total_num_sources < MIN_OBSERVABLE_THRESHOLD:
print(
"Not enough sources ({}) found in image {}".format(
total_num_sources, imgname))
return (1)
# Convert input images to tweakwcs-compatible NDData objects and
# attach source catalogs to them.
imglist = []
for group_id, image in enumerate(processList):
imglist.extend(
amutils.build_nddata(
image, group_id,
extracted_sources[image]['catalog_table']))
print("\nSUCCESS")
# 6: Cross-match source catalog with astrometric reference source catalog, Perform fit between source catalog and reference catalog
print(
"-------------------- STEP 6: Cross matching and fitting --------------------"
)
# Specify matching algorithm to use
match = tweakwcs.TPMatch(searchrad=250,
separation=0.1,
tolerance=100,
use2dhist=False)
# Align images and correct WCS
tweakwcs.tweak_image_wcs(imglist, reference_catalog, match=match)
# Interpret RMS values from tweakwcs
interpret_fit_rms(imglist, reference_catalog)
tweakwcs_info_keys = OrderedDict(
imglist[0].meta['tweakwcs_info']).keys()
imgctr = 0
for item in imglist:
retry_fit = False
#Handle fitting failures (no matches found)
if item.meta['tweakwcs_info']['status'].startswith(
"FAILED") == True:
if catalogIndex < numCatalogs - 1:
print(
"No cross matches found between astrometric catalog and sources found in images"
)
print("Try again with the next catalog")
catalogIndex += 1
retry_fit = True
break
else:
print(
"No cross matches found in any catalog - no processing done."
)
return (1)
max_rms_val = item.meta['tweakwcs_info']['TOTAL_RMS']
num_xmatches = item.meta['tweakwcs_info']['nmatches']
# print fit params to screen
print(
"~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ FIT PARAMETERS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
)
if item.meta['chip'] == 1:
image_name = processList[imgctr]
imgctr += 1
print("image: {}".format(image_name))
print("chip: {}".format(item.meta['chip']))
print("group_id: {}".format(item.meta['group_id']))
for tweakwcs_info_key in tweakwcs_info_keys:
if not tweakwcs_info_key.startswith("matched"):
print("{} : {}".format(
tweakwcs_info_key,
item.meta['tweakwcs_info'][tweakwcs_info_key]))
# print("Radial shift: {}".format(math.sqrt(item.meta['tweakwcs_info']['shift'][0]**2+item.meta['tweakwcs_info']['shift'][1]**2)))
print(
"~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
)
if num_xmatches < MIN_CROSS_MATCHES:
if catalogIndex < numCatalogs - 1:
print(
"Not enough cross matches found between astrometric catalog and sources found in images"
)
print("Try again with the next catalog")
catalogIndex += 1
retry_fit = True
break
else:
print(
"Not enough cross matches found in any catalog - no processing done."
)
return (1)
elif max_rms_val > MAX_FIT_RMS:
if catalogIndex < numCatalogs - 1:
print(
"Fit RMS value = {}mas greater than the maximum threshold value {}."
.format(
item.meta['tweakwcs_info']['FIT_RMS'].value,
MAX_FIT_RMS))
print("Try again with the next catalog")
catalogIndex += 1
retry_fit = True
break
else:
print(
"Fit RMS values too large using any catalog - no processing done."
)
return (1)
else:
print("Fit calculations successful.")
if not retry_fit:
print("\nSUCCESS")
# 7: Write new fit solution to input image headers
print(
"-------------------- STEP 7: Update image headers with new WCS information --------------------"
)
if update_hdr_wcs:
update_image_wcs_info(imglist, processList)
print("\nSUCCESS")
else:
print("\n STEP SKIPPED")
return (0)