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Update init matching procedure (#50)
* pep8 * fix convention * Update script * enforce optimisation boundaries to be finite * Update TODO * Remove sky matching * FIx a small bug * fix bug * Remove import * Add halo fitted quantities * Update nbs * update README * Add load_initial comments * Rename nbs * Delete nb * Update imports * Rename function * Update matcher * Add overlap paths * Update the matching script * Update verbosity * Add verbosity flags * Simplify make_bckg_delta * bug fix * fix bug * lala * la * Add overlap paths * Update limit * pep8 * Some pep8 stuff * pep8 * Minor corrections * Update paths * Add number of particles check * Fix bug * pep8 comments
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3 changed files with 22 additions and 24 deletions
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@ -115,9 +115,9 @@ class RealisationsMatcher:
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Parameters
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----------
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cat0 : :py:class:`csiborgtools.read.ClumpsCatalogue`
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cat0 : :py:class:`csiborgtools.read.HaloCatalogue`
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Halo catalogue of the reference simulation.
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catx : :py:class:`csiborgtools.read.ClumpsCatalogue`
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catx : :py:class:`csiborgtools.read.HaloCatalogue`
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Halo catalogue of the cross simulation.
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halos0_archive : `NpzFile` object
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Archive of halos' particles of the reference simulation, keys must
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@ -198,10 +198,8 @@ class RealisationsMatcher:
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except KeyError:
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halox = halosx_archive[str(kf)]
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minsx, maxsx = get_halolims(
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halox,
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ncells=self.overlapper.inv_clength,
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nshift=self.overlapper.nshift,
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)
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halox, ncells=self.overlapper.inv_clength,
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nshift=self.overlapper.nshift)
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for p in ("x", "y", "z"):
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halox[p] = self.overlapper.pos2cell(halox[p])
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cross_halos[kf] = halox
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@ -768,9 +766,8 @@ def calculate_overlap(delta1, delta2, cellmins, delta_bckg):
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@jit(nopython=True)
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def calculate_overlap_indxs(
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delta1, delta2, cellmins, delta_bckg, nonzero, mass1, mass2
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):
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def calculate_overlap_indxs(delta1, delta2, cellmins, delta_bckg, nonzero,
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mass1, mass2):
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r"""
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Overlap between two clumps whose density fields are evaluated on the
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same grid and `nonzero1` enumerates the non-zero cells of `delta1. This is
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@ -841,9 +838,8 @@ def dist_centmass(clump):
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Center of mass coordinates.
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"""
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# CM along each dimension
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cmx, cmy, cmz = [
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numpy.average(clump[p], weights=clump["M"]) for p in ("x", "y", "z")
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]
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cmx, cmy, cmz = [numpy.average(clump[p], weights=clump["M"])
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for p in ("x", "y", "z")]
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# Particle distance from the CM
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dist = numpy.sqrt(
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numpy.square(clump["x"] - cmx)
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@ -876,9 +872,8 @@ def dist_percentile(dist, qs, distmax=0.075):
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return x
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def radius_neighbours(
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knn, X, radiusX, radiusKNN, nmult=1.0, enforce_int32=False, verbose=True
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):
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def radius_neighbours(knn, X, radiusX, radiusKNN, nmult=1.0,
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enforce_int32=False, verbose=True):
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"""
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Find all neigbours of a trained KNN model whose center of mass separation
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is less than `nmult` times the sum of their respective radii.
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@ -27,12 +27,12 @@ class PairOverlap:
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Parameters
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----------
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cat0, catx: :py:class:`csiborgtools.read.ClumpsCatalogue`
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Halo catalogues corresponding to the reference and cross
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simulations.
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fskel : str, optional
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Path to the overlap. By default `None`, i.e.
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`/mnt/extraspace/rstiskalek/csiborg/overlap/cross_{}_{}.npz`.
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cat0 : :py:class:`csiborgtools.read.HaloCatalogue`
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Halo catalogue corresponding to the reference simulation.
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catx : :py:class:`csiborgtools.read.HaloCatalogue`
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Halo catalogue corresponding to the cross simulation.
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paths : py:class`csiborgtools.read.CSiBORGPaths`
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CSiBORG paths object.
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min_mass : float, optional
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Minimum :math:`M_{\rm tot} / M_\odot` mass in the reference catalogue.
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By default no threshold.
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@ -44,7 +44,7 @@ class PairOverlap:
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_catx = None
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_data = None
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def __init__(self, cat0, catx, fskel=None, min_mass=None, max_dist=None):
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def __init__(self, cat0, catx, paths, min_mass=None, max_dist=None):
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self._cat0 = cat0
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self._catx = catx
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@ -93,7 +93,7 @@ for i, nsim in enumerate(paths.get_ics(tonew=True)):
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# the end save these.
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cat = csiborgtools.read.ClumpsCatalogue(nsim, paths, load_fitted=False,
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rawdata=True)
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parent_ids = cat["index"][cat.ismain][:500]
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parent_ids = cat["index"][cat.ismain]
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jobs = csiborgtools.fits.split_jobs(parent_ids.size, nproc)[rank]
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for i in tqdm(jobs) if verbose else jobs:
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clid = parent_ids[i]
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@ -101,6 +101,9 @@ for i, nsim in enumerate(paths.get_ics(tonew=True)):
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mmain_mask = numpy.isin(clump_ids, mmain_indxs, assume_unique=True)
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mmain_particles = part0[mmain_mask]
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# If the number of particles is too small, we skip this halo.
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if mmain_particles.size < 100:
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continue
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raddist, cmpos = csiborgtools.match.dist_centmass(mmain_particles)
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patchsize = csiborgtools.match.dist_percentile(raddist, [99],
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