def get_hdul(fits_name,
mode='readonly',
checksum=True): # Written by Ema 05.03.2020
r"""Wrapper for astropy `fits.open`. It checks if the file exists and in case returns its HDUList.
Args:
fits_name (str): fits file name
mode (str): Open mode for the file. Possibilities are: `readonly’, `update`, `append`, `denywrite`,
or `ostream`
checksum (bool): If True, verifies that both `DATASUM` and `CHECKSUM` card values (when present in the HDU
header) match the header and data of all HDU’s in the file. Updates to a file that already has a checksum
will preserve and update the existing checksums unless this argument is given a value of `remove`,
in which case the `CHECKSUM` and `DATASUM` values are not checked, and are removed when saving
changes to the file
Returns:
hdul: list-like collection of HDU objects
"""
if not checks.fits_file_is_valid(fits_name):
msgs.error('Fits file not valid')
return None
else:
hdul = fits.open(fits_name, mode=mode, checksum=checksum)
msgs.info('The fits file {} contains {} HDUs'.format(
fits_name, len(hdul)))
msgs.info('Summary:')
hdul.info()
return hdul
def make_list_of_fits_files(args_input, verify_fits=False) -> list:
r"""Cleaning an input list of fits files
Args:
args_input (list): input list of fits files that will be checked (usually is coming from `parse_arguments()` in
a macro)
verify_fits (bool): if set to `True`, it will verify that the fits file is complaint to the FITS standard
Returns:
list: list containing all the valid fits files given in input
"""
list_of_fits_files = []
if not isinstance(args_input, list):
args_input_files: list = [args_input]
else:
args_input_files: list = args_input
for args_input_file in args_input_files:
if checks.fits_file_is_valid(args_input_file, overwrite=False, verify_fits=verify_fits):
list_of_fits_files.append(args_input_file)
else:
msgs.warning('{} excluded because not a valid fits file'.format(args_input_file))
if len(list_of_fits_files) == 0:
msgs.error('No valid fits files present')
return list_of_fits_files
def contours_from_gw_bayestar(file_name, credible_level=50.):
r"""Given a bayestar.fits.gz HEALPix maps of a GW superevent it extracts contours at the given `credible_level`
This is a wrapper around `ligo_skymap_contour`. The different contours are then counterclockwise oriented to be
compatible with TAP and ASP queries.
Args:
file_name (str): Name of HEALPix maps
credible_level (float): Probability level at which contours are returned
Returns:
list: [RA,Dec] list defining the contours location. These are counter-clockwise oriented as seen on the sky from
inside the sphere. The length of contours represent the number of not connected regions identified.
"""
# Some checks
assert isinstance(file_name, (str, np.str)), '{} is not a valid string'.format(file_name)
if not checks.fits_file_is_valid(file_name):
msgs.error('{} not a valid fits file'.format(file_name))
assert isinstance(credible_level, (int, float, np.int, np.float)), '`credible_level` is not a float or an int'
# Create temporary file where to store output from ligo_skymap_contour
contour_tmp_file = '.' + file_name + '.tmp.json'
if path.isfile(contour_tmp_file):
remove(contour_tmp_file)
# Use ligo_skymap_contour to compute contours
ligo_skymap_contour(args=[file_name, '--output', contour_tmp_file, '--contour', str(credible_level)])
# Parse the content of the resulting json file into a dict
with open(contour_tmp_file, 'r') as json_file:
json_data = json_file.read()
contours_dict = json.loads(json_data)
json_file.close()
# cleaning up
remove(contour_tmp_file)
# Parse the resulting json to obtain a list of coordinates defining the vertices of the contours of each peak
# contours is a list, each element of which contains the vertices of one contour encircling the desired significance
contours = contours_dict['features'][0]['geometry']['coordinates']
# Make sure that the orientation of the polygons on the sky is the correct one for the TAP queries,
# i.e. counter-clockwise as seen on the sky from inside the sphere.
for iii, contour in enumerate(contours):
contours[iii] = _ensure_orientation(contour)
# Quick summary:
if len(contours) > 0:
msgs.info('Extracted the contours for {} regions at {} credible level'.format(len(contours), credible_level))
else:
msgs.info('No contours extracted at {} credible level'.format(credible_level))
contours = None
return contours
def header_from_fits_file(fits_name, which_hdu=0): # Written by Ema 05.03.2020
r"""Load an header with the information from a fits file
Args:
fits_name (`str`):
fits file name
which_hdu (`numpy.int`):
select from which HDU you are getting the header. Default = 0
Returns:
header (`hdu.header`):
the header corresponding to `which_hdu` from `fits_name`
"""
assert isinstance(which_hdu, (int, np.int_)), 'which_hdu must be an int'
if not checks.fits_file_is_valid(fits_name):
msgs.error('Fits file not valid')
else:
header = fits.getheader(fits_name, which_hdu)
return header
def show_contours_from_gw_bayestar(file_name, contours=None, cmap='cylon', contours_color='C3',
show_figure=True, save_figure=None, matplotlib_backend=None):
r"""Show sky credibility from the input healpix map and plot the contours created with `contours_from_gw_bayestar`
Args:
file_name (`str`):
Fits files containing the HEALPix mask you would like to show.
contours (`list`):
cmap:
contours_color:
show_figure (`bool`):
save_figure (`str` or `None`):
matplotlib_backend:
Returns:
"""
# Some checks
assert isinstance(file_name, (str, np.str)), '{} is not a valid string'.format(file_name)
if not checks.fits_file_is_valid(file_name):
msgs.error('{} not a valid fits file'.format(file_name))
if contours is None:
msgs.warning("No contours defined, showing `credible_level=50` contours")
plot_contours = contours_from_gw_bayestar(file_name, credible_level=50.)
else:
plot_contours = contours
# ToDo find a more elegant solution for this.
# ligo.skymap.tool.ligo_skymap_contour introduces problems with the matplotlib backend. This i a workaround to
# get it running.
importlib.reload(matplotlib)
from matplotlib import pyplot as plt
if matplotlib_backend is None:
matplotlib.use(STARTING_MATPLOTLIB_BACKEND)
try:
# check if the script runs on a notebook.
# https://stackoverflow.com/questions/23883394/detect-if-python-script-is-run-from-an-ipython-shell-or
# -run-from
# -the-command-li
__IPYTHON__
except NameError:
# Try to get a working gui
# https://stackoverflow.com/questions/39026653/programmatically-choose-correct-backend-for-matplotlib-on
# -mac-os-x
gui_env = matplotlib.rcsetup.all_backends
for gui in gui_env:
try:
matplotlib.use(gui, force=True)
break
except:
continue
else:
matplotlib.use('nbAgg')
else:
if matplotlib_backend in matplotlib.rcsetup.all_backends:
matplotlib.use(matplotlib_backend)
else:
msgs.error('{} is not a valid `matplolib` backend'.format(matplotlib_backend))
# Read map and get object name
map_data, map_header = healpy.read_map(file_name, h=True, verbose=False, dtype=None)
object_name_list = [value for name, value in map_header if name == 'OBJECT']
if len(object_name_list) > 0:
object_name = object_name_list[0]
else:
object_name = 'GW event - {}'.format(file_name)
# start the plot
# ToDo fix matplotlibe error
"""
plt.figure(figsize=(10., 7.))
ax = plt.axes([0.1, 0.1, 0.9, 0.9], projection='astro degrees mollweide')
ax.grid(True)
ax.imshow_hpx(map_data, cmap=cmap, visible=True, zorder=1)
ax.text(0.15, 0.95, object_name, horizontalalignment='center', verticalalignment='center',
transform=ax.transAxes, bbox=dict(facecolor='orange', alpha=0.8), fontsize=24)
# Convert the contour vertex coordinates from world to pixels and draw the contours
w = wcs.WCS(ax.header)
# Split a contour if two neighboring pixels are more distant than 10 degrees in RA
split_step = (10 * (ax.get_xlim()[1] - ax.get_xlim()[0]) / 360.)
for contour_world in plot_contours:
contour_pix = w.wcs_world2pix(contour_world, 0)
x_contours, y_contours = _array_split(contour_pix, split_step)
for x_contour, y_contour in zip(x_contours, y_contours):
ax.plot(x_contour, y_contour, linewidth=2.5, color=contours_color, zorder=5) # , marker='o')
if save_figure is not None:
plt.savefig(save_figure, dpi=200., format='pdf', bbox_inches='tight')
if show_figure:
plt.show()
plt.close()
"""
# Bringing back the previously used matplotlib backend
matplotlib.use(STARTING_MATPLOTLIB_BACKEND)
return parser.parse_args()
EXAMPLES = r"""
Example:
fix_sinfoni.py input_fits.fits
fix_sinfoni.py input_fits.fits -out _cleaned -cal ABSOLUTE
"""
if __name__ == '__main__':
args = parse_arguments()
# File_names
input_fits_files = []
for file_name in args.input_fits:
if not checks.fits_file_is_valid(file_name):
msgs.warning(
'File {} is not a valid fits file. Skipping the procedure'.
format(file_name))
elif len(fitsfiles.get_hdul(file_name)) > 1:
msgs.warning(
'{} cube already processed? Skipping the procedure'.format(
file_name))
else:
input_fits_files.append(file_name)
if len(input_fits_files) == 0:
msgs.error('No valid file to process')
# output
if args.output is not None:
overwrite = False