def get_pixel_drift(coords, files):
"""Get the pixel drift for a given set of coordinates.
Args:
coords (`astropy.coordinates.SkyCoord`): Coordinates of source.
files (list): A list of FITS files with valid WCS.
Returns:
`numpy.array, numpy.array`: A 2xN array of pixel deltas where
N=len(files)
"""
# Get target positions for each frame
logger.info("Getting pixel drift for {}".format(coords))
target_pos = list()
for fn in files:
h0 = fits_utils.getheader(fn)
pos = WCS(h0).all_world2pix(coords.ra, coords.dec, 1)
target_pos.append(pos)
target_pos = np.array(target_pos)
# Subtract out the mean to get just the pixel deltas
x_pos = target_pos[:, 0]
y_pos = target_pos[:, 1]
x_pos -= x_pos.mean()
y_pos -= y_pos.mean()
return x_pos, y_pos
def get_pixel_drift(coords, files):
"""Get the pixel drift for a given set of coordinates.
Args:
coords (`astropy.coordinates.SkyCoord`): Coordinates of source.
files (list): A list of FITS files with valid WCS.
Returns:
`numpy.array, numpy.array`: A 2xN array of pixel deltas where
N=len(files)
"""
# Get target positions for each frame
logger.info("Getting pixel drift for {}".format(coords))
target_pos = list()
for fn in files:
h0 = fits_utils.getheader(fn)
pos = WCS(h0).all_world2pix(coords.ra, coords.dec, 1)
target_pos.append(pos)
target_pos = np.array(target_pos)
# Subtract out the mean to get just the pixel deltas
x_pos = target_pos[:, 0]
y_pos = target_pos[:, 1]
x_pos -= x_pos.mean()
y_pos -= y_pos.mean()
return x_pos, y_pos
def _lookup_via_photutils(fits_file, wcs=None, *args, **kwargs):
from photutils import DAOStarFinder
data = fits.getdata(fits_file) - 2048 # Camera bias
mean, median, std = sigma_clipped_stats(data)
fwhm = kwargs.get('fwhm', 3.0)
threshold = kwargs.get('threshold', 3.0)
daofind = DAOStarFinder(fwhm=fwhm, threshold=threshold * std)
sources = daofind(data - median).to_pandas()
sources.rename(columns={
'xcentroid': 'x',
'ycentroid': 'y',
}, inplace=True)
if wcs is None:
header = fits_utils.getheader(fits_file)
wcs = WCS(header)
coords = wcs.all_pix2world(sources['x'], sources['y'], 1)
sources['ra'] = coords[0]
sources['dec'] = coords[1]
return sources
def _lookup_via_photutils(fits_file, wcs=None, *args, **kwargs):
from photutils import DAOStarFinder
data = fits.getdata(fits_file) - 2048 # Camera bias
mean, median, std = sigma_clipped_stats(data)
fwhm = kwargs.get('fwhm', 3.0)
threshold = kwargs.get('threshold', 3.0)
daofind = DAOStarFinder(fwhm=fwhm, threshold=threshold * std)
sources = daofind(data - median).to_pandas()
sources.rename(columns={
'xcentroid': 'x',
'ycentroid': 'y',
},
inplace=True)
if wcs is None:
header = fits_utils.getheader(fits_file)
wcs = WCS(header)
coords = wcs.all_pix2world(sources['x'], sources['y'], 1)
sources['ra'] = coords[0]
sources['dec'] = coords[1]
return sources
def lookup_point_sources(fits_file,
catalog_match=True,
method='sextractor',
force_new=False,
**kwargs):
""" Extract point sources from image
Args:
fits_file (str, optional): Path to FITS file to search for stars.
force_new (bool, optional): Force a new catalog to be created,
defaults to False
Raises:
error.InvalidSystemCommand: Description
"""
if catalog_match or method == 'tess_catalog':
fits_header = fits_utils.getheader(fits_file)
wcs = WCS(fits_header)
assert wcs is not None and wcs.is_celestial, logger.warning(
"Need a valid WCS")
logger.info("Looking up sources for {}".format(fits_file))
lookup_function = {
'sextractor': _lookup_via_sextractor,
'tess_catalog': _lookup_via_tess_catalog,
'photutils': _lookup_via_photutils,
}
# Lookup our appropriate method and call it with the fits file and kwargs
try:
logger.debug("Using {} method {}".format(method,
lookup_function[method]))
point_sources = lookup_function[method](fits_file,
force_new=force_new,
**kwargs)
except Exception as e:
logger.error("Problem looking up sources: {}".format(e))
raise Exception("Problem lookup up sources: {}".format(e))
if catalog_match:
logger.debug(f'Doing catalog match against stars')
point_sources = get_catalog_match(point_sources, wcs, **kwargs)
logger.debug(f'Done with catalog match')
# Change the index to the picid
point_sources.set_index('id', inplace=True)
point_sources.index.rename('picid', inplace=True)
# Remove those with more than one entry
counts = point_sources.x.groupby('picid').count()
single_entry = counts == 1
single_index = single_entry.loc[single_entry].index
unique_sources = point_sources.loc[single_index]
return unique_sources
def lookup_point_sources(fits_file,
catalog_match=True,
method='sextractor',
force_new=False,
**kwargs
):
""" Extract point sources from image
Args:
fits_file (str, optional): Path to FITS file to search for stars.
force_new (bool, optional): Force a new catalog to be created,
defaults to False
Raises:
error.InvalidSystemCommand: Description
"""
if catalog_match or method == 'tess_catalog':
fits_header = fits_utils.getheader(fits_file)
wcs = WCS(fits_header)
assert wcs is not None and wcs.is_celestial, logger.warning("Need a valid WCS")
logger.info("Looking up sources for {}".format(fits_file))
lookup_function = {
'sextractor': _lookup_via_sextractor,
'tess_catalog': _lookup_via_tess_catalog,
'photutils': _lookup_via_photutils,
}
# Lookup our appropriate method and call it with the fits file and kwargs
try:
logger.debug("Using {} method {}".format(method, lookup_function[method]))
point_sources = lookup_function[method](fits_file, force_new=force_new, **kwargs)
except Exception as e:
logger.error("Problem looking up sources: {}".format(e))
raise Exception("Problem lookup up sources: {}".format(e))
if catalog_match:
logger.debug(f'Doing catalog match against stars')
point_sources = get_catalog_match(point_sources, wcs, **kwargs)
logger.debug(f'Done with catalog match')
# Change the index to the picid
point_sources.set_index('id', inplace=True)
point_sources.index.rename('picid', inplace=True)
# Remove those with more than one entry
counts = point_sources.x.groupby('picid').count()
single_entry = counts == 1
single_index = single_entry.loc[single_entry].index
unique_sources = point_sources.loc[single_index]
return unique_sources
def _process_fits(self, file_path, metadata):
file_path = super()._process_fits(file_path, metadata)
self.logger.debug('Overriding mount coordinates for camera simulator')
# TODO get the path as package data or something better.
solved_path = os.path.join(
os.environ['POCS'],
'tests',
'data',
'solved.fits.fz'
)
solved_header = fits_utils.getheader(solved_path)
with fits.open(file_path, 'update') as f:
hdu = f[0]
hdu.header.set('RA-MNT', solved_header['RA-MNT'], 'Degrees')
hdu.header.set('HA-MNT', solved_header['HA-MNT'], 'Degrees')
hdu.header.set('DEC-MNT', solved_header['DEC-MNT'], 'Degrees')
self.logger.debug("Headers updated for simulated image.")
return file_path
def _make_pretty_from_fits(fname=None,
title=None,
figsize=(10, 10 / 1.325),
dpi=150,
alpha=0.2,
number_ticks=7,
clip_percent=99.9,
**kwargs):
data = mask_saturated(fits_utils.getdata(fname))
header = fits_utils.getheader(fname)
wcs = WCS(header)
if not title:
field = header.get('FIELD', 'Unknown field')
exptime = header.get('EXPTIME', 'Unknown exptime')
filter_type = header.get('FILTER', 'Unknown filter')
try:
date_time = header['DATE-OBS']
except KeyError:
# If we don't have DATE-OBS, check filename for date
try:
basename = os.path.splitext(os.path.basename(fname))[0]
date_time = date_parse(basename).isoformat()
except Exception: # pragma: no cover
# Otherwise use now
date_time = current_time(pretty=True)
date_time = date_time.replace('T', ' ', 1)
title = f'{field} ({exptime}s {filter_type}) {date_time}'
norm = ImageNormalize(interval=PercentileInterval(clip_percent),
stretch=LogStretch())
fig = Figure()
FigureCanvas(fig)
fig.set_size_inches(*figsize)
fig.dpi = dpi
if wcs.is_celestial:
ax = fig.add_subplot(1, 1, 1, projection=wcs)
ax.coords.grid(True, color='white', ls='-', alpha=alpha)
ra_axis = ax.coords['ra']
ra_axis.set_axislabel('Right Ascension')
ra_axis.set_major_formatter('hh:mm')
ra_axis.set_ticks(number=number_ticks,
color='white',
exclude_overlapping=True)
dec_axis = ax.coords['dec']
dec_axis.set_axislabel('Declination')
dec_axis.set_major_formatter('dd:mm')
dec_axis.set_ticks(number=number_ticks,
color='white',
exclude_overlapping=True)
else:
ax = fig.add_subplot(111)
ax.grid(True, color='white', ls='-', alpha=alpha)
ax.set_xlabel('X / pixels')
ax.set_ylabel('Y / pixels')
im = ax.imshow(data, norm=norm, cmap=get_palette(), origin='lower')
add_colorbar(im)
fig.suptitle(title)
new_filename = re.sub(r'.fits(.fz)?', '.jpg', fname)
fig.savefig(new_filename, bbox_inches='tight')
# explicitly close and delete figure
fig.clf()
del fig
return new_filename
def test_getheader(solved_fits_file):
header = fits_utils.getheader(solved_fits_file)
assert isinstance(header, Header)
assert header['IMAGEID'] == 'PAN001_XXXXXX_20160909T081152'
def lookup_sources_for_observation(fits_files=None,
filename=None,
force_new=False,
cursor=None,
use_intersection=False,
**kwargs):
if force_new:
logger.info(f'Forcing a new source file')
with suppress(FileNotFoundError):
os.remove(filename)
try:
logger.info(f'Using existing source file: {filename}')
observation_sources = pd.read_csv(filename, parse_dates=True)
observation_sources['obstime'] = pd.to_datetime(
observation_sources.obstime)
except FileNotFoundError:
if not cursor:
cursor = get_cursor(port=5433, db_name='v702', db_user='******')
logger.info(f'Looking up sources in {len(fits_files)} files')
observation_sources = None
# Lookup the point sources for all frames
for fn in tqdm(fits_files):
point_sources = lookup_point_sources(fn,
force_new=force_new,
cursor=cursor,
**kwargs)
header = fits_utils.getheader(fn)
obstime = Time(pd.to_datetime(os.path.basename(fn).split('.')[0]))
exptime = header['EXPTIME'] * u.second
obstime += (exptime / 2)
point_sources['obstime'] = obstime.datetime
point_sources['exptime'] = exptime
point_sources['airmass'] = header['AIRMASS']
point_sources['file'] = os.path.basename(fn)
point_sources['picid'] = point_sources.index
logger.info(f'Combining sources with previous observations')
if observation_sources is not None:
if use_intersection:
logger.info(f'Getting intersection of sources')
idx_intersection = observation_sources.index.intersection(
point_sources.index)
logger.info(
f'Num sources in intersection: {len(idx_intersection)}'
)
observation_sources = pd.concat([
observation_sources.loc[idx_intersection],
point_sources.loc[idx_intersection]
],
join='inner')
else:
observation_sources = pd.concat(
[observation_sources, point_sources])
else:
observation_sources = point_sources
logger.info(f'Writing sources out to file')
observation_sources.to_csv(filename)
observation_sources.set_index(['obstime'], inplace=True)
return observation_sources
def lookup_sources_for_observation(fits_files=None,
filename=None,
force_new=False,
cursor=None,
use_intersection=False,
**kwargs
):
if force_new:
logger.info(f'Forcing a new source file')
with suppress(FileNotFoundError):
os.remove(filename)
try:
logger.info(f'Using existing source file: {filename}')
observation_sources = pd.read_csv(filename, parse_dates=True)
observation_sources['obstime'] = pd.to_datetime(observation_sources.obstime)
except FileNotFoundError:
if not cursor:
cursor = get_cursor(port=5433, db_name='v702', db_user='******')
logger.info(f'Looking up sources in {len(fits_files)} files')
observation_sources = None
# Lookup the point sources for all frames
for fn in tqdm(fits_files):
point_sources = lookup_point_sources(
fn,
force_new=force_new,
cursor=cursor,
**kwargs
)
header = fits_utils.getheader(fn)
obstime = Time(pd.to_datetime(os.path.basename(fn).split('.')[0]))
exptime = header['EXPTIME'] * u.second
obstime += (exptime / 2)
point_sources['obstime'] = obstime.datetime
point_sources['exptime'] = exptime
point_sources['airmass'] = header['AIRMASS']
point_sources['file'] = os.path.basename(fn)
point_sources['picid'] = point_sources.index
logger.info(f'Combining sources with previous observations')
if observation_sources is not None:
if use_intersection:
logger.info(f'Getting intersection of sources')
idx_intersection = observation_sources.index.intersection(point_sources.index)
logger.info(f'Num sources in intersection: {len(idx_intersection)}')
observation_sources = pd.concat([observation_sources.loc[idx_intersection],
point_sources.loc[idx_intersection]],
join='inner')
else:
observation_sources = pd.concat([observation_sources, point_sources])
else:
observation_sources = point_sources
logger.info(f'Writing sources out to file')
observation_sources.to_csv(filename)
observation_sources.set_index(['obstime'], inplace=True)
return observation_sources
def lookup_point_sources(
fits_file,
catalog_match=True,
method='sextractor',
force_new=False,
max_catalog_separation=25, # arcsecs
**kwargs):
""" Extract point sources from image
Args:
fits_file (str, optional): Path to FITS file to search for stars.
force_new (bool, optional): Force a new catalog to be created,
defaults to False
Raises:
error.InvalidSystemCommand: Description
"""
def _print(msg):
if 'logger' in kwargs:
logger.debug(msg)
else:
print(msg)
if catalog_match or method == 'tess_catalog':
fits_header = fits_utils.getheader(fits_file)
wcs = WCS(fits_header)
assert wcs is not None and wcs.is_celestial, logging.warning(
"Need a valid WCS")
_print(f"Looking up sources for {fits_file}")
lookup_function = {
'sextractor': _lookup_via_sextractor,
'tess_catalog': _lookup_via_tess_catalog,
}
# Lookup our appropriate method and call it with the fits file and kwargs
try:
_print(f"Using {method} method for {fits_file}")
point_sources = lookup_function[method](fits_file,
force_new=force_new,
**kwargs)
except Exception as e:
_print(f"Problem looking up sources: {e!r} {fits_file}")
raise Exception(f"Problem looking up sources: {e!r} {fits_file}")
if catalog_match:
_print(f'Doing catalog match against stars {fits_file}')
try:
point_sources = get_catalog_match(point_sources, wcs, **kwargs)
except Exception as e:
_print(f'Error in catalog match: {e!r} {fits_file}')
_print(f'Done with catalog match {fits_file}')
# Change the index to the picid
point_sources.set_index('picid', inplace=True)
_print(f'Point sources: {len(point_sources)}')
# Remove catalog matches that are too large
_print(
f'Removing matches that are greater than {max_catalog_separation} arcsec from catalog.'
)
point_sources = point_sources.loc[
point_sources.catalog_sep_arcsec < max_catalog_separation]
_print(f'Point sources: {len(point_sources)} {fits_file}')
return point_sources