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Fix overlap weights (#23)

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* Remove overlapper change cells

* Remove Pylians MASL and replace with custom

* Add concatenate clumps

* Add weighted overlap
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Richard Stiskalek 2023-01-14 14:34:37 +00:00 committed by GitHub
parent f0720243a2
commit 279580e041
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3 changed files with 237 additions and 105 deletions
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309
csiborgtools/match/match.py
View file

@ -15,10 +15,9 @@
import numpy
from scipy.ndimage import gaussian_filter
from math import ceil
from tqdm import (tqdm, trange)
from astropy.coordinates import SkyCoord
import MAS_library as MASL
from numba import jit
from ..read import CombinedHaloCatalogue
@ -255,13 +254,8 @@ class RealisationsMatcher:
with open(paths.clump0_path(self.cats.n_sims[i]), 'rb') as f:
clumpsx = numpy.load(f, allow_pickle=True)
# Switch overlapper resolution if halo outside well-def region
is_high = self.cats[n_sim]["dist"] < 155.5 / 0.705
overlapper.cellsize = 1 / 2**11 if is_high else 1 / 2**8
cat2clumpsx = self._cat2clump_mapping(self.cats[i]["index"],
clumpsx["ID"])
# Loop only over halos that have neighbours
with_neigbours = numpy.where([ii.size > 0 for ii in indxs])[0]
for k in tqdm(with_neigbours) if verbose else with_neigbours:
@ -374,44 +368,46 @@ def cosine_similarity(x, y):
class ParticleOverlap:
r"""
Class to calculate overlap between two halos from different simulations.
The density field calculation is based on the nearest grid position
particle assignment scheme, with optional additional Gaussian smoothing.
Parameters
----------
cellsize : float, optional
Cellsize in box units. By default :math:`1 / 2^11`, which matches the
initial RAMSES grid resolution.
inv_clength : float, optional
Inverse cell length in box units. By default :math:`2^11`, which
matches the initial RAMSES grid resolution.
smooth_scale : float or integer, optional
Optional Gaussian smoothing scale to by applied to the fields. By
default no smoothing is applied. Otherwise the scale is to be
specified in the number of cells (i.e. in units of `self.cellsize`).
MAS : str, optional
The mass assignment scheme to a grid. By default `PCS`.
"""
_cellsize = None
_inv_clength = None
_smooth_scale = None
_MAS = None
_clength = None
def __init__(self, cellsize=1/2**11, smooth_scale=None, MAS="PCS"):
self.cellsize = cellsize
def __init__(self, inv_clength=2**11, smooth_scale=None):
self.inv_clength = inv_clength
self.smooth_scale = smooth_scale
self.MAS = MAS
@property
def cellsize(self):
def inv_clength(self):
"""
The grid cubical cell size.
Inverse cell length.
Returns
-------
cellsize: 1-dimensional array
inv_clength : float
"""
return self._cellsize
return self._inv_clength
@cellsize.setter
def cellsize(self, cellsize):
"""Sets `cellsize`."""
assert cellsize > 0, "`cellsize` must be positive."
self._cellsize = cellsize
@inv_clength.setter
def inv_clength(self, inv_clength):
"""Sets `inv_clength`."""
assert inv_clength > 0, "`inv_clength` must be positive."
assert isinstance(inv_clength, int), "`inv_clength` must be integer."
self._inv_clength = int(inv_clength)
# Also set the inverse and number of cells
self._clength = 1 / self.inv_clength
@property
def smooth_scale(self):
@ -431,113 +427,153 @@ class ParticleOverlap:
assert smooth_scale > 0
self._smooth_scale = smooth_scale
@property
def MAS(self):
def pos2cell(self, pos):
"""
Mass assignment scheme.
Returns
-------
MAS : str
"""
return self._MAS
@MAS.setter
def MAS(self, MAS):
"""
Set `MAS`, checking it's a good value.
"""
assert MAS in ["NGP", "CIC", "TSC", "PCS"]
self._MAS = MAS
@staticmethod
def _minmax(X1, X2):
"""
Calculate the minimum and maximum coordinates from both arrays.
Convert position to cell number.
Parameters
----------
X1, X2 : 2-dimensional arrays of shape (n_samples, 3)
Cartesian coordinates of samples.
pos : 1-dimensional array
Returns
-------
mins, maxs : 1-dimensional arrays
Arrays of minima and maxima.
cells : 1-dimensional array
"""
# Calculate minimas for X1, X2
mins1 = numpy.min(X1, axis=0)
mins2 = numpy.min(X2, axis=0)
# Where X2 less than X1 replace the minima, we want min of both arrs
# and will return mins1!
m = mins2 < mins1
mins1[m] = mins2[m]
return numpy.floor(pos * self.inv_clength).astype(int)
# Repeat for maximas
maxs1 = numpy.max(X1, axis=0)
maxs2 = numpy.max(X2, axis=0)
# Where X2 less than X1 replace the minima, we want min of both arrs
m = maxs2 > maxs1
maxs1[m] = maxs2[m]
def smooth_highres(self, delta):
"""
Smooth the central region of a full box density field.
return mins1, maxs1
Parameters
----------
delta : 3-dimensional array
Returns
-------
smooth_delta : 3-dimensional arrray
"""
if self.smooth_scale is None:
raise ValueError("`smooth_scale` is not set!")
msg = "Shape of `delta` must match the entire box."
assert delta.shape == (self._inv_clength,)*3, msg
# Subselect only the high-resolution region
start = self._inv_clength // 4
end = start * 3
highres = delta[start:end, start:end, start:end]
# Smoothen it
gaussian_filter(highres, self.smooth_scale, output=highres)
# Put things back into the original array
delta[start:end, start:end, start:end] = highres
return delta
def make_delta(self, clump, subbox=False, to_smooth=True):
"""
Calculate a NGP density field of a halo on a cubic grid.
Parameters
----------
clump: structurered arrays
Clump structured array, keys must include `x`, `y`, `z` and `M`.
subbox : bool, optional
Whether to calculate the density field on a grid strictly enclosing
the clump.
to_smooth : bool, optional
Explicit control over whether to smooth. By default `True`.
Returns
-------
delta : 3-dimensional array
"""
coords = ('x', 'y', 'z')
xcell, ycell, zcell = (self.pos2cell(clump[p]) for p in coords)
if subbox:
# Shift the box so that each non-zero grid cell is 0th
xcell -= numpy.min(xcell)
ycell -= numpy.min(ycell)
zcell -= numpy.min(zcell)
ncells = max(*(numpy.max(p) for p in (xcell, ycell, zcell))) + 1
else:
ncells = self.inv_clength
# Preallocate and fill the array
delta = numpy.zeros((ncells,) * 3, dtype=numpy.float32)
fill_delta(delta, xcell, ycell, zcell, clump['M'])
if to_smooth and self.smooth_scale is not None:
gaussian_filter(delta, self.smooth_scale, output=delta)
return delta
def make_deltas(self, clump1, clump2):
"""
Calculate density fields of two halos on a grid that encloses them.
Calculate a NGP density fields of two halos on a grid that encloses
them both.
Parameters
----------
clump1, clump2 : structurered arrays
Structured arrays containing the particles of a given clump. Keys
must include `x`, `y`, `z` and `M`.
Particle structured array of the two clumps. Keys must include `x`,
`y`, `z` and `M`.
Returns
-------
delta1, delta2 : 3-dimensional arrays
Density arrays of `clump1` and `clump2`, respectively.
cellmins : len-3 tuple
Tuple of left-most cell ID in the full box.
"""
# Turn structured arrays to 2-dim arrs
X1 = numpy.vstack([clump1[p] for p in ('x', 'y', 'z')]).T
X2 = numpy.vstack([clump2[p] for p in ('x', 'y', 'z')]).T
coords = ('x', 'y', 'z')
xcell1, ycell1, zcell1 = (self.pos2cell(clump1[p]) for p in coords)
xcell2, ycell2, zcell2 = (self.pos2cell(clump2[p]) for p in coords)
# Calculate where to place box boundaries
mins, maxs = self._minmax(X1, X2)
# Minimum cell number of the two halos along each dimension
xmin = min(numpy.min(xcell1), numpy.min(xcell2))
ymin = min(numpy.min(ycell1), numpy.min(ycell2))
zmin = min(numpy.min(zcell1), numpy.min(zcell2))
cellmins = (xmin, ymin, zmin)
# Maximum cell number of the two halos along each dimension
xmax = max(numpy.max(xcell1), numpy.max(xcell2))
ymax = max(numpy.max(ycell1), numpy.max(ycell2))
zmax = max(numpy.max(zcell1), numpy.max(zcell2))
# Rescale X1 and X2
X1 -= mins
X1 /= maxs - mins
# Number of cells is the maximum + 1
ncells = max(xmax - xmin, ymax - ymin, zmax - zmin) + 1
X2 -= mins
X2 /= maxs - mins
# Shift the box so that the first non-zero grid cell is 0th
xcell1 -= xmin
xcell2 -= xmin
ycell1 -= ymin
ycell2 -= ymin
zcell1 -= zmin
zcell2 -= zmin
# How many cells in a subcube along each direction
width = numpy.max(maxs - mins)
ncells = ceil(width / self.cellsize)
# Assign particles to the grid now
delta1 = numpy.zeros((ncells, ncells, ncells), dtype=numpy.float32)
delta2 = numpy.zeros_like(delta1)
# Now do MAS
MASL.MA(X1, delta1, 1., self.MAS, verbose=False, W=clump1["M"])
MASL.MA(X2, delta2, 1., self.MAS, verbose=False, W=clump2["M"])
# Preallocate and fill the array
delta1 = numpy.zeros((ncells,)*3, dtype=numpy.float32)
fill_delta(delta1, xcell1, ycell1, zcell1, clump1['M'])
delta2 = numpy.zeros((ncells,)*3, dtype=numpy.float32)
fill_delta(delta2, xcell2, ycell2, zcell2, clump2['M'])
if self.smooth_scale is not None:
delta1 = gaussian_filter(delta1, self.smooth_scale, output=delta1)
delta2 = gaussian_filter(delta2, self.smooth_scale, output=delta2)
return delta1, delta2
gaussian_filter(delta1, self.smooth_scale, output=delta1)
gaussian_filter(delta2, self.smooth_scale, output=delta2)
return delta1, delta2, cellmins
@staticmethod
def overlap(delta1, delta2):
def overlap(delta1, delta2, cellmins, delta2_full):
r"""
Overlap between two density grids.
Overlap between two clumps whose density fields are evaluated on the
same grid.
Parameters
----------
delta1, delta2 : 3-dimensional arrays
Density arrays.
Clumps density fields.
cellmins : len-3 tuple
Tuple of left-most cell ID in the full box.
delta2_full : 3-dimensional array
Density field of the whole box calculated with particles assigned
to halos at zero redshift.
Returns
-------
@ -545,13 +581,10 @@ class ParticleOverlap:
"""
mass1 = numpy.sum(delta1)
mass2 = numpy.sum(delta2)
# Cells where both fields are > 0
mask = (delta1 > 0) & (delta2 > 0)
# Note the factor of 0.5 to avoid double counting
intersect = 0.5 * numpy.sum(delta1[mask] + delta2[mask])
intersect = calc_intersect(delta1, delta2, cellmins, delta2_full)
return intersect / (mass1 + mass2 - intersect)
def __call__(self, clump1, clump2):
def __call__(self, clump1, clump2, delta2_full):
"""
Calculate overlap between `clump1` and `clump2`. See
`self.overlap(...)` and `self.make_deltas(...)` for further
@ -562,10 +595,78 @@ class ParticleOverlap:
clump1, clump2 : structurered arrays
Structured arrays containing the particles of a given clump. Keys
must include `x`, `y`, `z` and `M`.
cellmins : len-3 tuple
Tuple of left-most cell ID in the full box.
delta2_full : 3-dimensional array
Density field of the whole box calculated with particles assigned
to halos at zero redshift.
Returns
-------
overlap : float
"""
delta1, delta2 = self.make_deltas(clump1, clump2)
return self.overlap(delta1, delta2)
delta1, delta2, cellmins = self.make_deltas(clump1, clump2)
return self.overlap(delta1, delta2, cellmins, delta2_full)
@jit(nopython=True)
def fill_delta(delta, xcell, ycell, zcell, weights):
"""
Fill array delta at the specified indices with their weights. This is a JIT
implementation.
Parameters
----------
delta : 3-dimensional array
Grid to be filled with weights.
xcell, ycell, zcell : 1-dimensional arrays
Indices where to assign `weights`.
weights : 1-dimensional arrays
Particle mass.
Returns
-------
None
"""
for i in range(xcell.size):
delta[xcell[i], ycell[i], zcell[i]] += weights[i]
@jit(nopython=True)
def calc_intersect(delta1, delta2, cellmins, delta2_full):
"""
Calculate weighted intersect between two density fields.
Parameters
----------
delta1, delta2 : 3-dimensional arrays
Density fields of `clump1` and `clump2`, respectively.
cellmins : len-3 tuple
Tuple of left-most cell ID in the full box.
delta2_full : 3-dimensional array
Density field of the whole box calculated with particles assigned to
halos at zero redshift.
Returns
-------
intersect : float
"""
imax, jmax, kmax = delta1.shape
intersect = 0.
for i in range(imax):
ii = cellmins[0] + i
for j in range(jmax):
jj = cellmins[1] + j
for k in range(kmax):
kk = cellmins[2] + k
# Unpack the densities of the clumps
cell1, cell2 = delta1[i, j, k], delta2[i, j, k]
# If both are zero then skip
if not (cell1 > 0 and cell2 > 0):
continue
weight = cell2 / delta2_full[ii, jj, kk]
intersect += 0.5 * weight * (cell1 + cell2)
return intersect

2
csiborgtools/read/__init__.py
View file

@ -14,7 +14,7 @@
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
from .readsim import (CSiBORGPaths, ParticleReader, read_mmain, read_initcm, halfwidth_select) # noqa
from .make_cat import (HaloCatalogue, CombinedHaloCatalogue) # noqa
from .make_cat import (HaloCatalogue, CombinedHaloCatalogue, concatenate_clumps) # noqa
from .readobs import (PlanckClusters, MCXCClusters, TwoMPPGalaxies, # noqa
TwoMPPGroups, SDSS) # noqa
from .outsim import (dump_split, combine_splits, make_ascii_powmes) # noqa

31
csiborgtools/read/make_cat.py
View file

@ -444,3 +444,34 @@ class CombinedHaloCatalogue:
raise ValueError("Catalogue count is {}, requested catalogue {}."
.format(self.N, n))
return self.cats[n]
def concatenate_clumps(clumps):
"""
Concatenate a list of clumps to a single array containing all particles.
Parameters
----------
clumps : list of structured arrays
Returns
-------
particles : structured array
"""
# Count how large array will be needed
N = 0
for clump, __ in clumps:
N += clump.size
# Pre-allocate array
dtype = {"names": ['x', 'y', 'z', "M"], "formats": [numpy.float32] * 4}
particles = numpy.full(N, numpy.nan, dtype)
# Fill it one clump by another
start = 0
for clump, __ in clumps:
end = start + clump.size
for p in ('x', 'y', 'z', 'M'):
particles[p][start:end] = clump[p]
start = end
return particles