X-ray data (#9)

* add xray reading

* add import

* add more comments

* add data

* add nb

* add MCXC shortcut

* add match indxs to Planck of MCXC

* add import

* update TODO

* update readme

* add famous clusters

* add 2mpp_groups

* shorten paths

* add 2M++ groups

* add import

* Update TODO

README.md

@@ -1,9 +1,10 @@
 # CSiBORG tools
 
 ## :scroll: Short-term TODO
-- [ ] Add half-mass radius and its corresponding concentration.
-- [ ] Model the Planck SZ selection function.
+- [x] Add the X-ray clusters
+- [x] Match the X-ray clusters to Planck
 - [ ] Calculate catalogues for all realisations.
+- [ ] Implement Max's halo matching
 
 
 ## :hourglass: Long-term TODO
@@ -13,3 +14,4 @@
 
 
 ## :bulb: Open questions
+- Completeness of clusters. Optical clusters catalogues are a bit of a mess..

csiborgtools/io/__init__.py

@@ -19,5 +19,5 @@ from .readsim import (get_csiborg_ids, get_sim_path, get_snapshots,  # noqa
                       drop_zero_indx,  # noqa
                       read_clumpid, read_clumps, read_mmain,  # noqa
                       merge_mmain_to_clumps)  # noqa
-from .readobs import (read_planck2015, read_2mpp)  # noqa
+from .readobs import (read_planck2015, read_mcxc, read_2mpp, read_2mpp_groups, match_planck_to_mcxc)  # noqa
 from .outsim import (dump_split, combine_splits)  # noqa

csiborgtools/io/readobs.py

@@ -18,11 +18,14 @@ Scripts to read in observation.
 
 import numpy
 from astropy.io import fits
-
+from astropy.coordinates import SkyCoord
+from astropy import units as u
 from ..utils import (add_columns, cols_to_structured)
 
+F64 = numpy.float64
 
-def read_planck2015(fpath, dist_cosmo, max_comdist=None):
+
+def read_planck2015(fpath, cosmo, max_comdist=None):
     r"""
     Read the Planck 2nd Sunyaev-Zeldovich source catalogue [1]. The following
     is performed:
@@ -34,22 +37,24 @@ def read_planck2015(fpath, dist_cosmo, max_comdist=None):
     ----------
     fpath : str
         Path to the source catalogue.
-    dist_cosmo : `astropy.cosmology` object
-        The cosmology to calculate cluster comoving distance from redshift.
+    cosmo : `astropy.cosmology` object
+        The cosmology to calculate cluster comoving distance from redshift and
+        convert their mass.
     max_comdist : float, optional
-        Maximum comoving distance threshold in units of :math:`\mathrm{MPc}`.
+        Maximum comoving distance threshold in units of :math:`\mathrm{Mpc}`.
         By default `None` and no threshold is applied.
 
+    Returns
+    -------
+    out : structured array
+        The catalogue structured array.
+
     References
     ----------
     [1] https://heasarc.gsfc.nasa.gov/W3Browse/all/plancksz2.html
-
-    Returns
-    -------
-    out : `astropy.io.fits.FITS_rec`
-        The catalogue structured array.
     """
     data = fits.open(fpath)[1].data
+    hdata = 0.7
     # Convert FITS to a structured array
     out = numpy.full(data.size, numpy.nan, dtype=data.dtype.descr)
     for name in out.dtype.names:
@@ -57,11 +62,12 @@ def read_planck2015(fpath, dist_cosmo, max_comdist=None):
     # Take only clusters with redshifts
     out = out[out["REDSHIFT"] >= 0]
     # Add comoving distance
-    dist = dist_cosmo.comoving_distance(out["REDSHIFT"]).value
+    dist = cosmo.comoving_distance(out["REDSHIFT"]).value
     out = add_columns(out, dist, "COMDIST")
     # Convert masses
     for par in ("MSZ", "MSZ_ERR_UP", "MSZ_ERR_LOW"):
         out[par] *= 1e14
+        out[par] *= (hdata / cosmo.h)**2
     # Distance threshold
     if max_comdist is not None:
         out = out[out["COMDIST"] < max_comdist]
@@ -69,15 +75,81 @@ def read_planck2015(fpath, dist_cosmo, max_comdist=None):
     return out
 
 
+def read_mcxc(fpath, cosmo, max_comdist=None):
+    r"""
+    Read the MCXC Meta-Catalog of X-Ray Detected Clusters of Galaxies
+    catalogue [1], with data description at [2] and download at [3].
+
+    Note
+    ----
+    The exact mass conversion has non-trivial dependence on :math:`H(z)`, see
+    [1] for more details. However, this should be negligible.
+
+    Parameters
+    ----------
+    fpath : str
+        Path to the source catalogue obtained from [3]. Expected to be the fits
+        file.
+    cosmo : `astropy.cosmology` object
+        The cosmology to calculate cluster comoving distance from redshift and
+        convert their mass.
+    max_comdist : float, optional
+        Maximum comoving distance threshold in units of :math:`\mathrm{Mpc}`.
+        By default `None` and no threshold is applied.
+
+    Returns
+    -------
+    out : structured array
+        The catalogue structured array.
+
+    References
+    ----------
+    [1] The MCXC: a meta-catalogue of x-ray detected clusters of galaxies
+        (2011); Piffaretti, R. ;  Arnaud, M. ;  Pratt, G. W. ;  Pointecouteau,
+        E. ;  Melin, J. -B.
+    [2] https://heasarc.gsfc.nasa.gov/W3Browse/rosat/mcxc.html
+    [3] https://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/534/A109#/article
+    """
+    data = fits.open(fpath)[1].data
+    hdata = 0.7  # Little h of the catalogue
+
+    cols = [("RAdeg", F64), ("DEdeg", F64), ("z", F64),
+            ("L500", F64), ("M500", F64), ("R500", F64)]
+    out = cols_to_structured(data.size, cols)
+    for col in cols:
+        par = col[0]
+        out[par] = data[par]
+    # Get little h units to match the cosmology
+    out["L500"] *= (hdata / cosmo.h)**2
+    out["M500"] *= (hdata / cosmo.h)**2
+    # Get the 10s back in
+    out["L500"] *= 1e44  # ergs/s
+    out["M500"] *= 1e14  # Msun
+
+    dist = cosmo.comoving_distance(data["z"]).value
+    out = add_columns(out, dist, "COMDIST")
+    out = add_columns(out, data["MCXC"], "name")
+
+    if max_comdist is not None:
+        out = out[out["COMDIST"] < max_comdist]
+
+    return out
+
+
 def read_2mpp(fpath, dist_cosmo):
     """
     Read in the 2M++ galaxy redshift catalogue [1], with the catalogue at [2].
-    Removes fake galaxies used to fill the zone of avoidance.
+    Removes fake galaxies used to fill the zone of avoidance. Note that in
+    principle additional care should be taken for calculating the distance
+    to objects [3]. Currently calculated from the CMB redshift, so some
+    distance estimates may be negative..
 
     Parameters
     ----------
     fpath : str
         File path to the catalogue.
+    cosmo : `astropy.cosmology` object
+        The cosmology to calculate distance from redshift.
 
     Returns
     -------
@@ -88,19 +160,104 @@ def read_2mpp(fpath, dist_cosmo):
     ----------
     [1] The 2M++ galaxy redshift catalogue; Lavaux, Guilhem, Hudson, Michael J.
     [2] https://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/416/2840#/article
+    [3] Improving NASA/IPAC Extragalactic Database Redshift Calculations
+        (2021); Anthony Carr and Tamara Davis
     """
     from scipy.constants import c
     # Read the catalogue and select non-fake galaxies
     cat = numpy.genfromtxt(fpath, delimiter="|", )
     cat = cat[cat[:, 12] == 0, :]
 
-    F64 = numpy.float64
     cols = [("RA", F64), ("DEC", F64), ("Ksmag", F64), ("ZCMB", F64),
-            ("CDIST_CMB", F64)]
+            ("DIST", F64)]
     out = cols_to_structured(cat.shape[0], cols)
     out["RA"] = cat[:, 1]
     out["DEC"] = cat[:, 2]
     out["Ksmag"] = cat[:, 5]
     out["ZCMB"] = cat[:, 7] / (c * 1e-3)
-    out["CDIST_CMB"] = dist_cosmo.comoving_distance(out["ZCMB"]).value
+    out["DIST"] = cat[:, 7] / dist_cosmo.H0
     return out
+
+
+def read_2mpp_groups(fpath, dist_cosmo):
+    """
+    Read in the 2M++ galaxy group catalogue [1], with the catalogue at [2].
+    Note that the same caveats apply to the distance calculation as in
+    py:function:`read_2mpp`. See that function for more details.
+
+    Parameters
+    ----------
+    fpath : str
+        File path to the catalogue.
+    cosmo : `astropy.cosmology` object
+        The cosmology to calculate distance from redshift.
+
+    Returns
+    -------
+    out : structured array
+        The catalogue.
+
+    References
+    ----------
+    [1] The 2M++ galaxy redshift catalogue; Lavaux, Guilhem, Hudson, Michael J.
+    [2] https://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/416/2840#/article
+    [3] Improving NASA/IPAC Extragalactic Database Redshift Calculations
+        (2021); Anthony Carr and Tamara Davis
+    """
+    cat = numpy.genfromtxt(fpath, delimiter="|", )
+
+    cols = [("RA", F64), ("DEC", F64), ("K2mag", F64), ("Rich", numpy.int64),
+            ("dist", F64), ("sigma", F64)]
+    out = cols_to_structured(cat.shape[0], cols)
+
+    out["K2mag"] = cat[:, 3]
+    out["Rich"] = cat[:, 4]
+    out["sigma"] = cat[:, 7]
+    out["dist"] = cat[:, 6] / dist_cosmo.H0
+
+    # Convert galactic coordinates to RA, dec
+    glon = cat[:, 1]
+    glat = cat[:, 2]
+    coords = SkyCoord(l=glon*u.degree, b=glat*u.degree, frame='galactic')
+    coords = coords.transform_to("icrs")
+    out["RA"] = coords.ra
+    out["DEC"] = coords.dec
+
+    return out
+
+
+def match_planck_to_mcxc(planck, mcxc):
+    """
+    Return the MCXC catalogue indices of the Planck catalogue detections. Finds
+    the index of the quoted Planck MCXC counterpart in the MCXC array. If not
+    found throws an error. For this reason it may be better to make sure the
+    MCXC catalogue reaches further.
+
+
+    Parameters
+    ----------
+    planck : structured array
+        The Planck cluster array.
+    mcxc : structured array
+        The MCXC cluster array.
+
+    Returns
+    -------
+    indxs : 1-dimensional array
+        The array of MCXC indices to match the Planck array. If no counterpart
+        is found returns `numpy.nan`.
+    """
+    # Planck MCXC need to be decoded to str
+    planck_names = [name.decode() for name in planck["MCXC"]]
+    mcxc_names = [name for name in mcxc["name"]]
+
+    indxs = [numpy.nan] * len(planck_names)
+    for i, name in enumerate(planck_names):
+        if name == "":
+            continue
+        if name in mcxc_names:
+            indxs[i] = mcxc_names.index(name)
+        else:
+            raise ValueError("Planck MCXC identifies `{}` not found in the "
+                             "MCXC catalogue.".format(name))
+    return indxs

scripts/utils.py

@@ -32,6 +32,18 @@ Nsplits = 200
 dumpdir = "/mnt/extraspace/rstiskalek/csiborg/"
 
 
+# Some chosen clusters
+_coma = {"RA": (12 + 59/60 + 48.7 / 60**2) * 15,
+         "DEC": 27 + 58 / 60 + 50 / 60**2,
+         "COMDIST": 102.975}
+
+_virgo = {"RA": (12 + 27 / 60) * 15,
+          "DEC": 12 + 43/60,
+          "COMDIST": 16.5}
+
+specific_clusters = {"Coma": _coma, "Virgo": _virgo}
+
+
 def load_processed(Nsim, Nsnap):
     simpath = csiborgtools.io.get_sim_path(Nsim)
     outfname = join(
@@ -60,11 +72,22 @@ def load_processed(Nsim, Nsnap):
 
 def load_planck2015(max_comdist=214):
     cosmo = FlatLambdaCDM(H0=70.5, Om0=0.307, Tcmb0=2.728)
-    fpath = ("/mnt/zfsusers/rstiskalek/csiborgtools/"
-             + "data/HFI_PCCS_SZ-union_R2.08.fits")
+    fpath = "../data/HFI_PCCS_SZ-union_R2.08.fits"
     return csiborgtools.io.read_planck2015(fpath, cosmo, max_comdist)
 
 
+def load_mcxc(max_comdist=214):
+    cosmo = FlatLambdaCDM(H0=70.5, Om0=0.307, Tcmb0=2.728)
+    fpath = ("../data/mcxc.fits")
+    return csiborgtools.io.read_mcxc(fpath, cosmo, max_comdist)
+
+
 def load_2mpp():
     cosmo = FlatLambdaCDM(H0=70.5, Om0=0.307, Tcmb0=2.728)
     return csiborgtools.io.read_2mpp("../data/2M++_galaxy_catalog.dat", cosmo)
+
+
+def load_2mpp_groups():
+    cosmo = FlatLambdaCDM(H0=70.5, Om0=0.307, Tcmb0=2.728)
+    return csiborgtools.io.read_2mpp_groups(
+        "../data/../data/2M++_group_catalog.dat", cosmo)