# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
from ..extern import six
from astropy.utils.data import download_file
from astropy.coordinates import Angle, SkyCoord
from astropy.table import Table, Column
from .core import SourceCatalog, SourceCatalogObject
__all__ = ["SourceCatalogSNRcat", "SourceCatalogObjectSNRcat"]
[docs]class SourceCatalogObjectSNRcat(SourceCatalogObject):
"""One source from the SNRcat catalog."""
pass
[docs]class SourceCatalogSNRcat(SourceCatalog):
"""SNRcat supernova remnant catalog.
`SNRcat <http://www.physics.umanitoba.ca/snr/SNRcat/>`__
is a census of high-energy observations of Galactic supernova remnants.
This function downloads the following CSV-format tables
and adds some useful columns and unit information:
* http://www.physics.umanitoba.ca/snr/SNRcat/SNRdownload.php?table=SNR
* http://www.physics.umanitoba.ca/snr/SNRcat/SNRdownload.php?table=OBS
This only represents a subset of the information available in SNRcat,
to get at the rest we would have to scrape their web pages.
* ``table`` (`~astropy.table.Table`) -- SNR info table
* ``obs_table`` (`~astropy.table.Table`) -- High-energy observation info table
Each table has a ``version`` string containing the download date in the ``table.meta`` dictionary.
"""
name = "snrcat"
description = "SNRcat supernova remnant catalog."
source_object_class = SourceCatalogObjectSNRcat
def __init__(self, cache=False):
# TODO: load from gammapy-extra?
# At least optionally?
self.snr_table = _fetch_catalog_snrcat_snr_table(cache=cache)
self.obs_table = _fetch_catalog_snrcat_obs_table(cache=cache)
super(SourceCatalogSNRcat, self).__init__(table=self.snr_table)
def _fetch_catalog_snrcat_snr_table(cache):
url = "http://www.physics.umanitoba.ca/snr/SNRcat/SNRdownload.php?table=SNR"
filename = download_file(url, cache=cache)
# Note: currently the first line contains this comment, which we skip via `header_start=1`
table = Table.read(filename, format="ascii.csv", header_start=1, delimiter=";")
table.meta["url"] = url
table.meta["version"] = _snrcat_parse_download_date(filename)
# TODO: doesn't work properly ... don't call for now.
# _snrcat_fix_na(table)
table.rename_column("G", "Source_Name")
table.rename_column("J2000_ra (hh:mm:ss)", "RAJ2000_str")
table.rename_column("J2000_dec (dd:mm:ss)", "DEJ2000_str")
data = Angle(table["RAJ2000_str"], unit="hour").deg
index = table.index_column("RAJ2000_str") + 1
table.add_column(Column(data=data, name="RAJ2000", unit="deg"), index=index)
data = Angle(table["DEJ2000_str"], unit="deg").deg
index = table.index_column("DEJ2000_str") + 1
table.add_column(Column(data=data, name="DEJ2000", unit="deg"), index=index)
radec = SkyCoord(table["RAJ2000"], table["DEJ2000"], unit="deg")
galactic = radec.galactic
table.add_column(Column(data=galactic.l.deg, name="GLON", unit="deg"))
table.add_column(Column(data=galactic.b.deg, name="GLAT", unit="deg"))
table.rename_column("age_min (yr)", "age_min")
table["age_min"].unit = "year"
table.rename_column("age_max (yr)", "age_max")
table["age_max"].unit = "year"
distance = np.mean([table["age_min"], table["age_max"]], axis=0)
index = table.index_column("age_max") + 1
table.add_column(Column(distance, name="age", unit="year"), index=index)
table.rename_column("distance_min (kpc)", "distance_min")
table["distance_min"].unit = "kpc"
table.rename_column("distance_max (kpc)", "distance_max")
table["distance_max"].unit = "kpc"
distance = np.mean([table["distance_min"], table["distance_max"]], axis=0)
index = table.index_column("distance_max") + 1
table.add_column(Column(distance, name="distance", unit="kpc"), index=index)
table.rename_column("size_radio", "diameter_radio_str")
diameter_radio_mean = _snrcat_parse_diameter(table["diameter_radio_str"])
index = table.index_column("diameter_radio_str") + 1
table.add_column(
Column(diameter_radio_mean, name="diameter_radio_mean", unit="arcmin"),
index=index,
)
table.rename_column("size_X", "diameter_xray_str")
diameter_xray_mean = _snrcat_parse_diameter(table["diameter_xray_str"])
index = table.index_column("diameter_xray_str") + 1
table.add_column(
Column(diameter_xray_mean, name="diameter_xray_mean", unit="arcmin"),
index=index,
)
table.rename_column("size_coarse (arcmin)", "diameter_mean")
table["diameter_mean"].unit = "arcmin"
table.rename_column("size_imprecise", "diameter_mean_is_imprecise")
return table
def _fetch_catalog_snrcat_obs_table(cache):
url = "http://www.physics.umanitoba.ca/snr/SNRcat/SNRdownload.php?table=OBS"
filename = download_file(url, cache=cache)
# Note: currently the first line contains this comment, which we skip via `header_start=1`
table = Table.read(filename, format="ascii.csv", header_start=1, delimiter=";")
table.meta["url"] = url
table.meta["version"] = _snrcat_parse_download_date(filename)
# TODO: doesn't work properly ... don't call for now.
# _snrcat_fix_na(table)
return table
def _snrcat_fix_na(table):
"""Fix N/A entries in string columns in SNRcat."""
for colname in table.colnames:
if isinstance(table[colname][0], six.text_type):
mask1 = table[colname] == "N / A"
mask2 = table[colname] == "N/A"
table[colname].mask = mask1 | mask2
table[colname].fill_value = ""
def _snrcat_parse_download_date(filename):
text = open(filename).readline()
# Format: "This file was downloaded on 2015-06-07T03:39:53 CDT ..."
tokens = text.split()
date = tokens[5]
return date[:10]
def _snrcat_parse_diameter(text_col):
"""Parse SNRcat diameter string column"""
d_means = []
for text in text_col:
try:
# Parse this text field:
if "x" in text:
a, b = text.split("x")
d_major = Angle(a).arcmin
d_minor = Angle(b).arcmin
else:
d_major = Angle(text).arcmin
d_minor = d_major
d_mean = _snr_mean_diameter(d_major, d_minor)
except:
# print('Parsing error:', text)
d_mean = np.nan
d_means.append(d_mean)
return d_means
def _snr_mean_diameter(d_major, d_minor):
"""Compute geometric mean diameter (preserves area)"""
diameter = np.sqrt(d_major * d_minor)
# If no `d_minor` is given, use `d_major` as mean radius
with np.errstate(invalid="ignore"):
diameter = np.where(d_minor > 0, diameter, d_major)
return diameter