mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-12-22 06:58:02 +00:00
New RSP density distinction (#72)
* Edit docs * Fix kernel units * Add NGP interpolation * Add Vobs but not implemented * Add BORG density option * Add BORG mcmc path * Organise imports * Add new density field distinction
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cd6d448874
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7 changed files with 141 additions and 74 deletions
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@ -17,6 +17,8 @@ from csiborgtools import clustering, field, fits, match, read # noqa
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# Arguments to csiborgtools.read.Paths.
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paths_glamdring = {"srcdir": "/mnt/extraspace/hdesmond/",
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"postdir": "/mnt/extraspace/rstiskalek/CSiBORG/",
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"BORG_dir": "/mnt/extraspace/rstiskalek/BORG/",
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"BORG_final_density": "/users/hdesmond/BORG_final/",
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"quijote_dir": "/mnt/extraspace/rstiskalek/Quijote",
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}
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@ -17,9 +17,10 @@ from warnings import warn
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try:
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import MAS_library as MASL # noqa
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from .density import DensityField, PotentialField, VelocityField, TidalTensorField # noqa
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from .density import (DensityField, PotentialField, # noqa
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TidalTensorField, VelocityField)
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from .interp import (evaluate_cartesian, evaluate_sky, field2rsp, # noqa
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make_sky, fill_outside) # noqa
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fill_outside, make_sky, observer_vobs)
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from .utils import nside2radec, smoothen_field # noqa
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except ImportError:
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warn("MAS_library not found, `DensityField` will not be available", UserWarning) # noqa
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@ -17,13 +17,13 @@ Density field and cross-correlation calculations.
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"""
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from abc import ABC
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import numpy
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import MAS_library as MASL
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import numpy
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from numba import jit
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from tqdm import trange
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from ..read.utils import real2redshift
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from .interp import divide_nonzero
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from .utils import force_single_precision
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@ -249,7 +249,7 @@ class VelocityField(BaseField):
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/ numpy.sqrt(px**2 + py**2 + pz**2))
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return radvel
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def __call__(self, parts, grid, mpart, flip_xz=True, nbatch=30,
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def __call__(self, parts, grid, flip_xz=True, nbatch=30,
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verbose=True):
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"""
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Calculate the velocity field using a Pylians routine [1, 2].
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@ -263,8 +263,6 @@ class VelocityField(BaseField):
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Columns are: `x`, `y`, `z`, `vx`, `vy`, `vz`, `M`.
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grid : int
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Grid size.
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mpart : float
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Particle mass.
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flip_xz : bool, optional
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Whether to flip the `x` and `z` coordinates.
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nbatch : int, optional
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@ -287,6 +285,7 @@ class VelocityField(BaseField):
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rho_vely = numpy.zeros((grid, grid, grid), dtype=numpy.float32)
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rho_velz = numpy.zeros((grid, grid, grid), dtype=numpy.float32)
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rho_vel = [rho_velx, rho_vely, rho_velz]
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cellcounts = numpy.zeros((grid, grid, grid), dtype=numpy.float32)
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nparts = parts.shape[0]
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batch_size = nparts // nbatch
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@ -302,16 +301,22 @@ class VelocityField(BaseField):
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if flip_xz:
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pos[:, [0, 2]] = pos[:, [2, 0]]
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vel[:, [0, 2]] = vel[:, [2, 0]]
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vel *= mass.reshape(-1, 1) / mpart
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vel *= mass.reshape(-1, 1)
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for i in range(3):
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MASL.MA(pos, rho_vel[i], self.boxsize, self.MAS, W=vel[:, i],
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verbose=False)
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MASL.MA(pos, cellcounts, self.boxsize, self.MAS, W=mass,
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verbose=False)
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if end == nparts:
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break
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start = end
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return numpy.stack(rho_vel)
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for i in range(3):
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divide_nonzero(rho_vel[i], cellcounts)
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return numpy.stack([rho_velx, rho_vely, rho_velz])
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###############################################################################
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@ -24,10 +24,9 @@ from ..read.utils import radec_to_cartesian, real2redshift
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from .utils import force_single_precision
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def evaluate_cartesian(*fields, pos):
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def evaluate_cartesian(*fields, pos, interp="CIC"):
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"""
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Evaluate a scalar field at Cartesian coordinates using CIC
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interpolation.
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Evaluate a scalar field at Cartesian coordinates.
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Parameters
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----------
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@ -36,19 +35,29 @@ def evaluate_cartesian(*fields, pos):
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pos : 2-dimensional array of shape `(n_samples, 3)`
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Positions to evaluate the density field. Assumed to be in box
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units.
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interp : str, optional
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Interpolation method. Can be either `CIC` or `NGP`.
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Returns
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-------
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interp_fields : (list of) 1-dimensional array of shape `(n_samples,).
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"""
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assert interp in ["CIC", "NGP"]
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boxsize = 1.
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pos = force_single_precision(pos, "pos")
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nsamples = pos.shape[0]
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interp_fields = [numpy.full(nsamples, numpy.nan, dtype=numpy.float32)
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for __ in range(len(fields))]
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for i, field in enumerate(fields):
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MASL.CIC_interp(field, boxsize, pos, interp_fields[i])
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if interp == "CIC":
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for i, field in enumerate(fields):
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MASL.CIC_interp(field, boxsize, pos, interp_fields[i])
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else:
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pos = numpy.floor(pos * fields[0].shape[0]).astype(numpy.int32)
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for i, field in enumerate(fields):
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for j in range(nsamples):
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interp_fields[i][j] = field[pos[j, 0], pos[j, 1], pos[j, 2]]
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if len(fields) == 1:
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return interp_fields[0]
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@ -168,8 +177,30 @@ def divide_nonzero(field0, field1):
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field0[i, j, k] /= field1[i, j, k]
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def field2rsp(*fields, parts, box, nbatch=30, flip_partsxz=True, init_value=0.,
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verbose=True):
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def observer_vobs(velocity_field):
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"""
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Calculate the observer velocity from a velocity field. Assumes the observer
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is in the centre of the box.
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Parameters
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----------
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velocity_field : 4-dimensional array of shape `(3, grid, grid, grid)`
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Velocity field to calculate the observer velocity from.
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Returns
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-------
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vobs : 1-dimensional array of shape `(3,)`
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Observer velocity in units of `velocity_field`.
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"""
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pos = numpy.asanyarray([0.5, 0.5, 0.5]).reshape(1, 3)
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vobs = numpy.full(3, numpy.nan, dtype=numpy.float32)
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for i in range(3):
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vobs[i] = evaluate_cartesian(velocity_field[i, ...], pos=pos)[0]
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return vobs
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def field2rsp(*fields, parts, vobs, box, nbatch=30, flip_partsxz=True,
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init_value=0., verbose=True):
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"""
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Forward model real space scalar fields to redshift space. Attaches field
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values to particles, those are then moved to redshift space and from their
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@ -182,6 +213,8 @@ def field2rsp(*fields, parts, box, nbatch=30, flip_partsxz=True, init_value=0.,
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parts : 2-dimensional array of shape `(n_parts, 6)`
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Particle positions and velocities in real space. Must be organised as
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`x, y, z, vx, vy, vz`.
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vobs : 1-dimensional array of shape `(3,)`
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Observer velocity in units matching `parts`.
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box : :py:class:`csiborgtools.read.CSiBORGBox`
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The simulation box information and transformations.
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nbatch : int, optional
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@ -199,6 +232,7 @@ def field2rsp(*fields, parts, box, nbatch=30, flip_partsxz=True, init_value=0.,
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-------
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rsp_fields : (list of) 3-dimensional array of shape `(grid, grid, grid)`
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"""
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raise NotImplementedError("Figure out what to do with Vobs.")
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nfields = len(fields)
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# Check that all fields have the same shape.
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if nfields > 1:
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@ -31,16 +31,21 @@ class Paths:
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Path to the folder where the RAMSES outputs are stored.
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postdir: str, optional
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Path to the folder where post-processed files are stored.
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borg_dir : str, optional
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Path to the folder where BORG MCMC chains are stored.
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quiote_dir : str, optional
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Path to the folder where Quijote simulations are stored.
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"""
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_srcdir = None
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_postdir = None
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_borg_dir = None
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_quijote_dir = None
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def __init__(self, srcdir=None, postdir=None, quijote_dir=None):
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def __init__(self, srcdir=None, postdir=None, borg_dir=None,
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quijote_dir=None):
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self.srcdir = srcdir
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self.postdir = postdir
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self.borg_dir = borg_dir
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self.quijote_dir = quijote_dir
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@staticmethod
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@ -68,6 +73,26 @@ class Paths:
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self._check_directory(path)
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self._srcdir = path
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@property
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def borg_dir(self):
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"""
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Path to the folder where BORG MCMC chains are stored.
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Returns
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-------
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path : str
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"""
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if self._borg_dir is None:
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raise ValueError("`borg_dir` is not set!")
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return self._borg_dir
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@borg_dir.setter
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def borg_dir(self, path):
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if path is None:
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return
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self._check_directory(path)
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self._borg_dir = path
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@property
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def quijote_dir(self):
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"""
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@ -146,6 +171,21 @@ class Paths:
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return nsim
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return f"{str(nobs).zfill(2)}{str(nsim).zfill(3)}"
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def borg_mcmc(self, nsim):
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"""
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Path to the BORG MCMC chain file.
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Parameters
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----------
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nsim : int
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IC realisation index.
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Returns
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-------
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path : str
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"""
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return join(self.borg_dir, "mcmc", f"mcmc_{nsim}.h5")
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def mmain(self, nsnap, nsim):
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"""
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Path to the `mmain` CSiBORG files of summed substructure.
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@ -373,7 +413,7 @@ class Paths:
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IC realisation index.
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in_rsp : bool
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Whether the calculation is performed in redshift space.
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smooth_scale : float
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smooth_scale : float, optional
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Smoothing scale in :math:`\mathrm{Mpc}/h`
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Returns
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@ -61,54 +61,30 @@ def density_field(nsim, parser_args, to_save=True):
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nsnap = max(paths.get_snapshots(nsim))
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box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths)
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parts = csiborgtools.read.read_h5(paths.particles(nsim))["particles"]
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gen = csiborgtools.field.DensityField(box, parser_args.MAS)
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field = gen(parts, parser_args.grid, in_rsp=parser_args.in_rsp,
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verbose=parser_args.verbose)
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if parser_args.kind == "density":
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field = gen(parts, parser_args.grid, in_rsp=False,
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verbose=parser_args.verbose)
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if parser_args.in_rsp:
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field = csiborgtools.field.field2rsp(*field, parts=parts, box=box,
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verbose=parser_args.verbose)
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else:
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field = gen(parts, parser_args.grid, in_rsp=parser_args.in_rsp,
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verbose=parser_args.verbose)
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if parser_args.smooth_scale > 0:
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field = csiborgtools.field.smoothen_field(
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field, parser_args.smooth_scale, box.boxsize * box.h, threads=1)
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if to_save:
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fout = paths.field("density", parser_args.MAS, parser_args.grid,
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nsim, parser_args.in_rsp)
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fout = paths.field(parser_args.kind, parser_args.MAS, parser_args.grid,
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nsim, parser_args.in_rsp, parser_args.smooth_scale)
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print(f"{datetime.now()}: saving output to `{fout}`.")
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numpy.save(fout, field)
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return field
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def density_field_smoothed(nsim, parser_args, to_save=True):
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"""
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Calculate the smoothed density field in the CSiBORG simulation. The
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unsmoothed density field must already be precomputed.
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Parameters
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----------
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nsim : int
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Simulation index.
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parser_args : argparse.Namespace
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Parsed arguments.
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to_save : bool, optional
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Whether to save the output to disk.
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Returns
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-------
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smoothed_density : 3-dimensional array
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"""
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paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
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nsnap = max(paths.get_snapshots(nsim))
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box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths)
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# Load the real space overdensity field
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rho = numpy.load(paths.field("density", parser_args.MAS, parser_args.grid,
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nsim, in_rsp=False))
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rho = csiborgtools.field.smoothen_field(rho, parser_args.smooth_scale,
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box.boxsize, threads=1)
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if to_save:
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fout = paths.field("density", parser_args.MAS, parser_args.grid,
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nsim, parser_args.in_rsp, parser_args.smooth_scale)
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print(f"{datetime.now()}: saving output to `{fout}`.")
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numpy.save(fout, rho)
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return rho
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###############################################################################
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# Velocity field #
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###############################################################################
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@ -185,7 +161,7 @@ def potential_field(nsim, parser_args, to_save=True):
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nsim, in_rsp=False))
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if parser_args.smooth_scale > 0:
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rho = csiborgtools.field.smoothen_field(rho, parser_args.smooth_scale,
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box.boxsize, threads=1)
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box.boxsize * box.h, threads=1)
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rho = density_gen.overdensity_field(rho)
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# Calculate the real space potentiel field
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gen = csiborgtools.field.PotentialField(box, parser_args.MAS)
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@ -281,7 +257,7 @@ def environment_field(nsim, parser_args, to_save=True):
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nsim, in_rsp=False))
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if parser_args.smooth_scale > 0:
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rho = csiborgtools.field.smoothen_field(rho, parser_args.smooth_scale,
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box.boxsize, threads=1)
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box.boxsize * box.h, threads=1)
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rho = density_gen.overdensity_field(rho)
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# Calculate the real space tidal tensor field, delete overdensity.
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if parser_args.verbose:
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@ -339,28 +315,28 @@ if __name__ == "__main__":
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parser.add_argument("--nsims", type=int, nargs="+", default=None,
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help="IC realisations. `-1` for all simulations.")
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parser.add_argument("--kind", type=str,
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choices=["density", "velocity", "radvel", "potential",
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"environment"],
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choices=["density", "rspdensity", "velocity", "radvel",
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"potential", "environment"],
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help="What derived field to calculate?")
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parser.add_argument("--MAS", type=str,
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choices=["NGP", "CIC", "TSC", "PCS"])
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parser.add_argument("--grid", type=int, help="Grid resolution.")
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parser.add_argument("--in_rsp", type=lambda x: bool(strtobool(x)),
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help="Calculate in RSP?")
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parser.add_argument("--smooth_scale", type=float, default=0)
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parser.add_argument("--smooth_scale", type=float, default=0,
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help="Smoothing scale in Mpc/h.")
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parser.add_argument("--verbose", type=lambda x: bool(strtobool(x)),
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help="Verbosity flag for reading in particles.")
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parser.add_argument("--simname", type=str, default="csiborg",
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help="Verbosity flag for reading in particles.")
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parser_args = parser.parse_args()
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comm = MPI.COMM_WORLD
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paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
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nsims = get_nsims(parser_args, paths)
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def main(nsim):
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if parser_args.kind == "density":
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if parser_args.smooth_scale > 0:
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density_field_smoothed(nsim, parser_args)
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else:
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density_field(nsim, parser_args)
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if parser_args.kind == "density" or parser_args.kind == "rspdensity":
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density_field(nsim, parser_args)
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elif parser_args.kind == "velocity":
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velocity_field(nsim, parser_args)
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elif parser_args.kind == "radvel":
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@ -19,6 +19,7 @@ from argparse import ArgumentParser
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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import numpy
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from h5py import File
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import healpy
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import scienceplots # noqa
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@ -244,7 +245,8 @@ def load_field(kind, nsim, grid, MAS, in_rsp=False, smooth_scale=None):
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def plot_projected_field(kind, nsim, grid, in_rsp, smooth_scale, MAS="PCS",
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highres_only=True, slice_find=None, pdf=False):
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vel_component=0, highres_only=True, slice_find=None,
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pdf=False):
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r"""
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Plot the mean projected field, however can also plot a single slice.
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@ -262,6 +264,8 @@ def plot_projected_field(kind, nsim, grid, in_rsp, smooth_scale, MAS="PCS",
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Smoothing scale in :math:`\mathrm{Mpc} / h`.
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MAS : str, optional
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Mass assignment scheme.
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vel_component : int, optional
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Which velocity field component to plot.
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highres_only : bool, optional
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Whether to only plot the high-resolution region.
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slice_find : float, optional
|
||||
|
@ -283,12 +287,16 @@ def plot_projected_field(kind, nsim, grid, in_rsp, smooth_scale, MAS="PCS",
|
|||
smooth_scale=smooth_scale)
|
||||
density_gen = csiborgtools.field.DensityField(box, MAS)
|
||||
field = density_gen.overdensity_field(field) + 1
|
||||
elif kind == "borg_density":
|
||||
field = File(paths.borg_mcmc(nsim), 'r')
|
||||
field = field["scalars"]["BORG_final_density"][...]
|
||||
else:
|
||||
field = load_field(kind, nsim, grid, MAS=MAS, in_rsp=in_rsp,
|
||||
smooth_scale=smooth_scale)
|
||||
|
||||
if kind == "velocity":
|
||||
field = field[0, ...]
|
||||
field = field[vel_component, ...]
|
||||
field = box.box2vel(field)
|
||||
|
||||
if highres_only:
|
||||
csiborgtools.field.fill_outside(field, numpy.nan, rmax=155.5,
|
||||
|
@ -552,22 +560,23 @@ if __name__ == "__main__":
|
|||
if False:
|
||||
plot_hmf(pdf=False)
|
||||
|
||||
if True:
|
||||
if False:
|
||||
kind = "overdensity"
|
||||
grid = 1024
|
||||
plot_sky_distribution(kind, 7444, grid, nside=64,
|
||||
plot_groups=False, dmin=45, dmax=60,
|
||||
plot_halos=5e13, volume_weight=True)
|
||||
|
||||
if False:
|
||||
kind = "density"
|
||||
if True:
|
||||
kind = "overdensity"
|
||||
grid = 256
|
||||
smooth_scale = 0
|
||||
# plot_projected_field("overdensity", 7444, grid, in_rsp=True,
|
||||
# highres_only=False)
|
||||
plot_projected_field(kind, 7444, grid, in_rsp=False,
|
||||
smooth_scale=smooth_scale, slice_find=0.5,
|
||||
highres_only=False)
|
||||
MAS="PCS",
|
||||
highres_only=True)
|
||||
|
||||
if False:
|
||||
paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
|
||||
|
|
Loading…
Reference in a new issue