def image_ts(input_file, output_file, psf, model, scales, downsample, residual,
morphology, width, overwrite, threshold):
"""
Compute source model residual images.
The input ``data`` FITS file must contain the following HDU extensions:
* 'counts' -- Counts image
* 'background' -- Background image
* 'exposure' -- Exposure image
"""
# Execute script
from astropy.io import fits
from gammapy.detect import compute_ts_map_multiscale
# Read data
log.info('Reading {}'.format(input_file))
maps = fits.open(input_file)
log.info('Reading {}'.format(psf))
psf_parameters = json.load(open(psf))
if residual:
log.info('Reading {}'.format(model))
data = fits.getdata(model)
header = fits.getheader(model)
maps.append(fits.ImageHDU(data, header, 'OnModel'))
results = compute_ts_map_multiscale(maps, psf_parameters, scales,
downsample, residual, morphology,
width, threshold)
filename = Path(output_file).name
folder = Path(output_file).parent
Path(folder).mkdir(exist_ok=True)
# Write results to file
header = maps[0].header
if len(results) > 1:
for scale, result in zip(scales, results):
# TODO: this is unnecessarily complex
# Simplify, e.g. by letting the user specify a `base_dir`.
filename_ = filename.replace('.fits',
'_{0:.3f}.fits'.format(scale))
fn = Path(folder) / filename_
log.info('Writing {}'.format(fn))
result.write(str(fn), header, clobber=overwrite)
elif results:
log.info('Writing {}'.format(output_file))
results[0].write(output_file, header, clobber=overwrite)
else:
log.info("No results to write to file: all scales have failed")
def image_ts(input_file, output_file, psf, model, scales, downsample, residual,
morphology, width, overwrite, threshold):
"""
Compute source model residual images.
The input ``data`` FITS file must contain the following HDU extensions:
* 'On' -- Counts image
* 'Background' -- Background image
* 'Diffuse' -- Diffuse model image
* 'ExpGammaMap' -- Exposure image
"""
# Execute script
from astropy.io import fits
from gammapy.detect import compute_ts_map_multiscale
# Read data
log.info('Reading {}'.format(input_file))
maps = fits.open(input_file)
log.info('Reading {}'.format(psf))
psf_parameters = json.load(open(psf))
if residual:
log.info('Reading {}'.format(model))
data = fits.getdata(model)
header = fits.getheader(model)
maps.append(fits.ImageHDU(data, header, 'OnModel'))
results = compute_ts_map_multiscale(maps, psf_parameters, scales, downsample,
residual, morphology, width, threshold)
filename = Path(output_file).name
folder = Path(output_file).parent
Path(folder).mkdir(exist_ok=True)
# Write results to file
header = maps[0].header
if len(results) > 1:
for scale, result in zip(scales, results):
# TODO: this is unnecessarily complex
# Simplify, e.g. by letting the user specify a `base_dir`.
filename_ = filename.replace('.fits', '_{0:.3f}.fits'.format(scale))
fn = Path(folder) / filename_
log.info('Writing {}'.format(fn))
result.write(str(fn), header, overwrite=overwrite)
elif results:
log.info('Writing {}'.format(output_file))
results[0].write(output_file, header, overwrite=overwrite)
else:
log.info("No results to write to file: all scales have failed")
def image_ts(
input_file, output_file, psf, model, scales, downsample, residual, morphology, width, overwrite, threshold
):
"""
Compute source model residual images.
The input ``data`` FITS file must contain the following HDU extensions:
* 'counts' -- Counts image
* 'background' -- Background image
* 'exposure' -- Exposure image
"""
# Execute script
from astropy.io import fits
from gammapy.detect import compute_ts_map_multiscale
from gammapy.image import SkyImageCollection
# Read data
log.info("Reading {}".format(input_file))
skyimages = SkyImageCollection.read(input_file)
log.info("Reading {}".format(psf))
psf_parameters = json.load(open(psf))
if residual:
log.info("Reading {}".format(model))
skyimages["model"] = SkyImage.read(model)
results = compute_ts_map_multiscale(
skyimages, psf_parameters, scales, downsample, residual, morphology, width, threshold
)
filename = Path(output_file).name
folder = Path(output_file).parent
Path(folder).mkdir(exist_ok=True)
# Write results to file
if len(results) > 1:
for scale, result in zip(scales, results):
# TODO: this is unnecessarily complex
# Simplify, e.g. by letting the user specify a `base_dir`.
filename_ = filename.replace(".fits", "_{0:.3f}.fits".format(scale))
fn = Path(folder) / filename_
log.info("Writing {}".format(fn))
result.write(str(fn), clobber=overwrite)
elif results:
log.info("Writing {}".format(output_file))
results[0].write(output_file, clobber=overwrite)
else:
log.info("No results to write to file: all scales have failed")
def ts_image(input_file, output_file, psf, model, scales, downsample, residual,
morphology, width, overwrite, threshold):
"""
Compute source model residual images.
The input `data` fits file must contain the following HDU extensions:
* 'On' -- Counts image
* 'Background' -- Background image
* 'Diffuse' -- Diffuse model image
* 'ExpGammaMap' -- Exposure image
"""
# Execute script
from astropy.io import fits
from gammapy.detect import compute_ts_map_multiscale
# Read data
log.info('Reading {}'.format(input_file))
maps = fits.open(input_file)
log.info('Reading {}'.format(psf))
psf_parameters = json.load(open(psf))
if residual:
log.info('Reading {}'.format(model))
data = fits.getdata(model)
header = fits.getheader(model)
maps.append(fits.ImageHDU(data, header, 'OnModel'))
results = compute_ts_map_multiscale(maps, psf_parameters, scales,
downsample, residual, morphology,
width)
folder, filename = os.path.split(output_file)
if not os.path.exists(folder) and folder != '':
os.mkdir(folder)
# Write results to file
header = maps[0].header
if len(results) > 1:
for scale, result in zip(scales, results):
filename_ = filename.replace('.fits',
'_{0:.3f}.fits'.format(scale))
log.info('Writing {}'.format(os.path.join(folder, filename_)))
result.write(os.path.join(folder, filename_),
header,
overwrite=overwrite)
else:
log.info('Writing {}'.format(output_file))
results[0].write(output_file, header, overwrite=overwrite)
def ts_image(input_file, output_file, psf, model, scales, downsample, residual,
morphology, width, overwrite, threshold):
"""
Compute source model residual images.
The input `data` fits file must contain the following HDU extensions:
* 'On' -- Counts image
* 'Background' -- Background image
* 'Diffuse' -- Diffuse model image
* 'ExpGammaMap' -- Exposure image
"""
# Execute script
import json
import logging
logging.basicConfig(level=logging.DEBUG, format='%(levelname)s - %(message)s')
from astropy.io import fits
from gammapy.detect import compute_ts_map_multiscale
# Read data
logging.info('Reading {}'.format(input_file))
maps = fits.open(input_file)
logging.info('Reading {}'.format(psf))
psf_parameters = json.load(open(psf))
if residual:
logging.info('Reading {}'.format(model))
data = fits.getdata(model)
header = fits.getheader(model)
maps.append(fits.ImageHDU(data, header, 'OnModel'))
results = compute_ts_map_multiscale(maps, psf_parameters, scales, downsample,
residual, morphology, width)
folder, filename = os.path.split(output_file)
if not os.path.exists(folder) and folder != '':
os.mkdir(folder)
# Write results to file
header = maps[0].header
if len(results) > 1:
for scale, result in zip(scales, results):
filename_ = filename.replace('.fits', '_{0:.3f}.fits'.format(scale))
logging.info('Writing {}'.format(os.path.join(folder, filename_)))
result.write(os.path.join(folder, filename_), header, overwrite=overwrite)
else:
logging.info('Writing {}'.format(output_file))
results[0].write(output_file, header, overwrite=overwrite)
def ts_image(input_file, psf, model, scales, downsample, residual, morphology,
width, overwrite, folder, threshold):
"""
Compute source model residual images.
The input `data` fits file must contain the following HDU extensions:
* 'On' -- Counts image
* 'Background' -- Background image
* 'Diffuse' -- Diffuse model image
* 'ExpGammaMap' -- Exposure image
"""
# Execute script
import json
import logging
logging.basicConfig(level=logging.DEBUG, format='%(levelname)s - %(message)s')
from astropy.io import fits
from gammapy.detect import compute_ts_map_multiscale
# Read data
logging.info('Reading {0}'.format(input_file))
maps = fits.open(input_file)
logging.info('Reading {0}'.format(psf))
psf_parameters = json.load(open(psf))
if residual:
logging.info('Reading {0}'.format(model))
data = fits.getdata(model)
header = fits.getheader(model)
maps.append(fits.ImageHDU(data, header, 'OnModel'))
results = compute_ts_map_multiscale(maps, psf_parameters, scales, downsample,
residual, morphology, width)
folder = morphology.lower()
if not os.path.exists(folder):
os.mkdir(folder)
# Write results to file
header = maps[0].header
for scale, result in zip(scales, results):
filename = os.path.join(folder, 'ts_{0:.3f}.fits'.format(scale))
logging.info('Writing {0}'.format(filename))
result.write(filename, header, overwrite=overwrite)
