Merge branch 'develop'

README.md

@@ -24,6 +24,7 @@ The currently supported dust maps are:
 11. Leike & Enßlin (2019)
 12. Leike, Glatzle & Enßlin (2020)
 13. Edenhofer et al. (2023)
+14. Chiang (2023; CSFD)
 
 To request addition of another dust map in this package, [file an issue on
 GitHub](https://github.com/gregreen/dustmaps/issues), or submit a pull request.
@@ -49,7 +50,7 @@ To fetch the data for the SFD dust map, run:
 
     python setup.py fetch --map-name=sfd
 
-You can download the other dust maps by changing "sfd" to "planck",
+You can download the other dust maps by changing "sfd" to "csfd", "planck",
 "planckGNILC", "bayestar", "iphas", "marshall", "chen2014", "lenz2017",
 "pg2010", "leikeensslin2019", "leike2020", "edenhofer2023" or "bh".
 
@@ -63,6 +64,9 @@ interpreter and running:
     >>> import dustmaps.sfd
     >>> dustmaps.sfd.fetch()
     >>>
+    >>> import dustmaps.csfd
+    >>> dustmaps.csfd.fetch()
+    >>>
     >>> import dustmaps.planck
     >>> dustmaps.planck.fetch()
     >>>

docs/installation.rst

@@ -26,6 +26,9 @@ Start up a python interpreter and type:
     import dustmaps.sfd
     dustmaps.sfd.fetch()
     
+    import dustmaps.csfd
+    dustmaps.csfd.fetch()
+    
     import dustmaps.planck
     dustmaps.planck.fetch()
     
@@ -55,10 +58,10 @@ Start up a python interpreter and type:
     
     import dustmaps.leike2020
     dustmaps.leike2020.fetch()
-
+    
     import dustmaps.edenhofer2023
     dustmaps.edenhofer2023.fetch()
-
+    
     import dustmaps.gaia_tge
     dustmaps.gaia_tge.fetch()
 
@@ -110,6 +113,7 @@ to only download those you think you'll need:
 .. code-block :: bash
     
     python setup.py fetch --map-name=sfd
+    python setup.py fetch --map-name=csfd
     python setup.py fetch --map-name=planck
     python setup.py fetch --map-name=planckGNILC
     python setup.py fetch --map-name=bayestar

docs/maps.rst

@@ -23,6 +23,19 @@ conversions provided in
 * **Reference**: `Schlegel, Finkbeiner & Davis (1998) <http://adsabs.harvard.edu/abs/1998ApJ...500..525S>`_
 * **Recalibration**: `Schlafly & Finkbeiner (2011) <http://adsabs.harvard.edu/abs/2011ApJ...737..103S>`_
 
+
+CSFD (Chiang 2023)
+~~~~~~~~~~~~~~~~~~
+
+"Corrected SFD," a 2D dust map based on a reanalysis of SFD, using
+tomographically constrained templates from WISE galaxy density fields to remove
+extragalactic contamination from the cosmic infrared background (CIB).
+
+* **Reference**: `Chiang (2023) <https://ui.adsabs.harvard.edu/abs/2023arXiv230603926C/abstract>`_
+* **Website**: `Project description <https://idv.sinica.edu.tw/ykchiang/CSFD.html>`_
+* **Data**: `Zenodo <https://doi.org/10.5281/zenodo.8207159>`_
+
+
 Gaia Total Galactic Extinction (2022)
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
@@ -173,8 +186,8 @@ estimates of Zhang, Green & Rix (2023), and therefore reports extinctions in
 their units. Accompanying the main reconstruciton is an additional map that uses
 less data but extends out to 2 kpc from the Sun.
 
-* **Reference**: `Edenhofer et al. (2023) <https://arxiv.org/abs/2308.01295>`_
-* **Website**: `Zenodo <https://doi.org/10.5281/zenodo.8187943>`_
+* **Reference**: `Edenhofer et al. (2023) <https://ui.adsabs.harvard.edu/abs/2023arXiv230801295E/abstract>`_
+* **Data**: `Zenodo <https://doi.org/10.5281/zenodo.8187943>`_
 
 
 IPHAS
@@ -199,7 +212,7 @@ the Gaia DR2 catalog parallaxes and G-band extinctions, and spans a (600 pc)³
 box centered on the Sun.
 
 * **Reference**: `Leike & Enßlin (2019) <https://ui.adsabs.harvard.edu/abs/2019arXiv190105971L/abstract>`_
-* **Website**: `Zenodo <https://doi.org/10.5281/zenodo.2542807>`_
+* **Data**: `Zenodo <https://doi.org/10.5281/zenodo.2542807>`_
 
 
 Leike, Glatzle & Enßlin (2020)
@@ -213,7 +226,7 @@ ALLWISE, and is calculated on a Cartesian grid spanning a
 centered on the Sun.
 
 * **References**: `Leike, Glatzle & Enßlin (2020) <https://ui.adsabs.harvard.edu/abs/2020A%26A...639A.138L/abstract>`_
-* **Website**: `Zenodo <https://doi.org/10.5281/zenodo.3993082>`_
+* **Data**: `Zenodo <https://doi.org/10.5281/zenodo.3993082>`_
 
 
 Marshall et al. (2006)

docs/modules.rst

@@ -26,6 +26,13 @@ chen2014 (Chen et al. 2014)
     :special-members:
     :show-inheritance:
 
+csfd (Chiang 2023)
+---------------------------
+.. automodule:: dustmaps.csfd
+    :members:
+    :special-members:
+    :show-inheritance:
+
 gaia_tge (Delchambre et al. 2022)
 ---------------------------
 .. automodule:: dustmaps.gaia_tge

dustmaps/csfd.py

@@ -0,0 +1,128 @@
+#!/usr/bin/env python
+#
+# csfd.py
+# Reads the "Corrected SFD" dust reddening map of Chiang (2023).
+#
+# Copyright (C) 2023  Gregory M. Green
+#
+# This program is free software; you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation; either version 2 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License along
+# with this program; if not, write to the Free Software Foundation, Inc.,
+# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+#
+
+from __future__ import print_function, division
+
+import os
+import numpy as np
+import healpy as hp
+import astropy.io.fits as fits
+import astropy.units as units
+
+from .std_paths import *
+from .healpix_map import HEALPixQuery
+from . import fetch_utils
+from . import dustexceptions
+
+
+class CSFDQuery(HEALPixQuery):
+    """
+    Queries the Corrected SFD dust map of Chiang (2023). This map is based
+    on SFD, but contains a correction to remove contamination from
+    large-scale structure (i.e., external galaxies).
+    """
+
+    def __init__(self, map_fname=None, mask_fname=None):
+        """
+        Args:
+            map_fname (Optional[:obj:`str`]): Filename of the CSFD EBV map.
+                Defaults to ```None``, meaning that the default location is
+                used.
+            mask_fname (Optional[:obj:`str`]): Filename of the CSFD mask map.
+                Defaults to ```None``, meaning that the default location is
+                used.
+        """
+
+        if map_fname is None:
+            map_fname = os.path.join(data_dir(), 'csfd', 'csfd_ebv.fits')
+        if mask_fname is None:
+            mask_fname = os.path.join(data_dir(), 'csfd', 'mask.fits')
+
+        try:
+            with fits.open(map_fname) as hdulist:
+                ebv_data = hdulist['xtension'].data[:]['T'].flatten()
+            with fits.open(mask_fname) as hdulist:
+                mask_data = hdulist['xtension'].data[:]['T'].flatten()
+        except IOError as error:
+            print(dustexceptions.data_missing_message('csfd',
+                                                      'CSFD (Chiang 2023)'))
+            raise error
+
+        super(CSFDQuery, self).__init__(ebv_data, False, 'galactic',
+                                        flags=mask_data)
+
+    def query(self, coords, **kwargs):
+        """
+        Returns CSFD reddening on the same scale as SFD (similar to E(B-V)) at
+        the specified location(s) on the sky. Also optionally returns a
+        bit mask, where the bits (ordered from least to most significant) have
+        the following meanings::
+        
+            Bit 0: 'LSS_corr' - This bit is set in the footprint within which
+                   the LSS is reconstructed, and CSFD = SFD - LSS (otherwise
+                   CSFD = SFD).
+            Bit 1: 'no_IRAS' - Set in the area with no IRAS data (DIRBE data
+                   filled in SFD); LSS removal in CSFD is done using a 1 deg
+                   smoothed LSS.
+            Bit 2: 'cosmology' - Set in the area where both the LSS and CSFD
+                   are most reliable for precision cosmology analyses.
+
+        Args:
+            coords (:obj:`astropy.coordinates.SkyCoord`): The coordinates to
+                query.
+            return_flags (Optional[:obj:`bool`]): If ``True``, then a
+                bit mask is returned as well, indicating where CSFD
+                has been corrected for large-scale structure, where IRAS data
+                was used, and where the map is suitable for cosmology. See
+                above description of bits. Defaults to ``False``.
+
+        Returns:
+            A float array of the reddening, at the given coordinates. The
+            shape of the output is the same as the shape of the input
+            coordinate array, ``coords``. If ``return_flags`` is ``True``,
+            a second array (a bit mask) of the same shape is returned. See
+            above description of the meaning of each bit.
+        """
+        return super(CSFDQuery, self).query(coords, **kwargs)
+
+
+def fetch(clobber=False):
+    """
+    Downloads the Corrected SFD dust map of Chiang (2023).
+
+    Args:
+        clobber (Optional[bool]): If ``True``, any existing file will be
+            overwritten, even if it appears to match. If ``False`` (the
+            default), ``fetch()`` will attempt to determine if the dataset
+            already exists. This determination is not 100\% robust against data
+            corruption.
+    """
+    file_spec = [
+        ('csfd_ebv.fits', '31cd2eec51bcb5f106af84a610ced53c'),
+        ('mask.fits', '9142f5a5d184125836a68b6f48d1113f')
+    ]
+    for fn,md5sum in file_spec:
+        fname = os.path.join(data_dir(), 'csfd', fn)
+        # Download from Zenodo
+        url = 'https://zenodo.org/record/8207175/files/{}'.format(fn)
+        fetch_utils.download_and_verify(url, md5sum, fname, clobber=clobber)
+

dustmaps/leike2020.py

@@ -98,7 +98,7 @@ def query(self, coords, component='mean'):
                 standard deviation of extinction density). Defaults to 'mean'.
 
         Returns:
-            The extinction density, in units of e-foldings / pc, as either a
+            The extinction density, in units of e-foldings / kpc, as either a
             numpy array or float, with the same shape as the input
             :obj:`coords`.
         """

dustmaps/leike_ensslin_2019.py

@@ -92,7 +92,7 @@ def query(self, coords, component='mean'):
                 standard deviation of extinction density). Defaults to 'mean'.
 
         Returns:
-            The extinction density, in units of e-foldings / pc, as either a
+            The extinction density, in units of e-foldings / kpc, as either a
             numpy array or float, with the same shape as the input
             :obj:`coords`.
         """

setup.py

@@ -61,6 +61,10 @@ def fetch_sfd():
     import dustmaps.sfd
     dustmaps.sfd.fetch()
 
+def fetch_csfd():
+    import dustmaps.csfd
+    dustmaps.csfd.fetch()
+
 def fetch_planck():
     import dustmaps.planck
     dustmaps.planck.fetch()
@@ -121,6 +125,7 @@ class FetchCommand(distutils.cmd.Command):
 
     map_funcs = {
         'sfd': fetch_sfd,
+        'csfd': fetch_csfd,
         'planck': fetch_planck,
         'planckGNILC': fetch_planck_GNILC,
         'bayestar': fetch_bayestar,