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Basic matching (#2)
* add recarray manipulations * add cart to radec * add behav so x can be a list * add import * create empty files * ignore plots file * add planck data * add read_mmain file * add cols_to_structured import * use cols_to_structured * add cols_to_structued * add read_mmain import * add reading planck * add mass conversion * add brute force separation calculation * update nb * rename & int dtype * add func to get csiborg ids * add list to nd array conversion * add utils * rename file * add 2M++ * add read 2mpp * add 2mpp shortcut * add randoms generator * Change range of RA [0, 360] * fix ang wrapping * add code for sphere 2pcf * rm wrapping * optionally load only a few borgs * update nb
This commit is contained in:
Richard Stiskalek
GitHub
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d2c1f3294a
commit
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17 changed files with 74697 additions and 37 deletions
18
galomatch/utils/__init__.py
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18
galomatch/utils/__init__.py
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# Copyright (C) 2022 Richard Stiskalek
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# This program is free software; you can redistribute it and/or modify it
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# under the terms of the GNU General Public License as published by the
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# Free Software Foundation; either version 3 of the License, or (at your
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# option) any later version.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
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# Public License for more details.
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#
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# You should have received a copy of the GNU General Public License along
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# with this program; if not, write to the Free Software Foundation, Inc.,
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# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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from .recarray_manip import (cols_to_structured, add_columns, rm_columns,
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list_to_ndarray)
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from .transforms import cartesian_to_radec
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155
galomatch/utils/recarray_manip.py
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galomatch/utils/recarray_manip.py
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# Copyright (C) 2022 Richard Stiskalek
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# This program is free software; you can redistribute it and/or modify it
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# under the terms of the GNU General Public License as published by the
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# Free Software Foundation; either version 3 of the License, or (at your
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# option) any later version.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
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# Public License for more details.
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#
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# You should have received a copy of the GNU General Public License along
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# with this program; if not, write to the Free Software Foundation, Inc.,
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# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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"""Utilility functions for manipulation structured arrays."""
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import numpy
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def cols_to_structured(N, cols):
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"""
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Allocate a structured array from `cols`.
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Parameters
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----------
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N : int
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Structured array size.
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cols: list of tuples
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Column names and dtypes. Each tuple must written as `(name, dtype)`.
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Returns
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-------
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out : structured array
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Initialised structured array.
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"""
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if not isinstance(cols, list) and all(isinstance(c, tuple) for c in cols):
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raise TypeError("`cols` must be a list of tuples.")
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dtype = {"names": [col[0] for col in cols],
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"formats": [col[1] for col in cols]}
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return numpy.full(N, numpy.nan, dtype=dtype)
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def add_columns(arr, X, cols):
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"""
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Add new columns to a record array `arr`. Creates a new array.
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Parameters
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----------
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arr : record array
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The record array to add columns to.
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X : (list of) 1-dimensional array(s) or 2-dimensional array
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Columns to be added.
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cols : str or list of str
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Column names to be added.
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Returns
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-------
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out : record array
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The new record array with added values.
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"""
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# Make sure cols is a list of str and X a 2D array
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cols = [cols] if isinstance(cols, str) else cols
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if isinstance(X, numpy.ndarray) and X.ndim == 1:
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X = X.reshape(-1, 1)
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if isinstance(X, list) and all(x.ndim == 1 for x in X):
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X = numpy.vstack([X]).T
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if len(cols) != X.shape[1]:
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raise ValueError("Number of columns of `X` does not match `cols`.")
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if arr.size != X.shape[0]:
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raise ValueError("Number of rows of `X` does not match size of `arr`.")
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# Get the new data types
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dtype = arr.dtype.descr
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for i, col in enumerate(cols):
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dtype.append((col, X[i, :].dtype.descr[0][1]))
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# Fill in the old array
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out = numpy.full(arr.size, numpy.nan, dtype=dtype)
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for col in arr.dtype.names:
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out[col] = arr[col]
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for i, col in enumerate(cols):
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out[col] = X[:, i]
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return out
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def rm_columns(arr, cols):
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"""
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Remove columns `cols` from a record array `arr`. Creates a new array.
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Parameters
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----------
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arr : record array
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The record array to remove columns from.
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cols : str or list of str
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Column names to be removed.
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Returns
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-------
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out : record array
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Record array with removed columns.
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"""
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# Check columns we wish to delete are in the array
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cols = [cols] if isinstance(cols, str) else cols
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for col in cols:
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if col not in arr.dtype.names:
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raise ValueError("Column `{}` not in `arr`.".format(col))
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# Get a new dtype without the cols to be deleted
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new_dtype = []
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for dtype, name in zip(arr.dtype.descr, arr.dtype.names):
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if name not in cols:
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new_dtype.append(dtype)
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# Allocate a new array and fill it in.
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out = numpy.full(arr.size, numpy.nan, new_dtype)
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for name in out.dtype.names:
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out[name] = arr[name]
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return out
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def list_to_ndarray(arrs, cols):
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"""
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Convert a list of structured arrays of CSiBORG simulation catalogues to
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an 3-dimensional array.
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Parameters
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----------
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arrs : list of structured arrays
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List of CSiBORG catalogues.
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cols : str or list of str
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Columns to be extracted from the CSiBORG catalogues.
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Returns
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-------
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out : 3-dimensional array
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Catalogue array of shape `(n_realisations, n_samples, n_cols)`, where
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`n_samples` is the maximum number of samples over the CSiBORG
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catalogues.
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"""
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if not isinstance(arrs, list):
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raise TypeError("`arrs` must be a list of structured arrays.")
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cols = [cols] if isinstance(cols, str) else cols
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Narr = len(arrs)
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Nobj_max = max([arr.size for arr in arrs])
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Ncol = len(cols)
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# Preallocate the array and fill it
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out = numpy.full((Narr, Nobj_max, Ncol), numpy.nan)
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for i in range(Narr):
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Nobj = arrs[i].size
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for j in range(Ncol):
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out[i, :Nobj, j] = arrs[i][cols[j]]
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return out
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56
galomatch/utils/transforms.py
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56
galomatch/utils/transforms.py
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# Copyright (C) 2022 Richard Stiskalek
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# This program is free software; you can redistribute it and/or modify it
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# under the terms of the GNU General Public License as published by the
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# Free Software Foundation; either version 3 of the License, or (at your
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# option) any later version.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
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# Public License for more details.
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#
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# You should have received a copy of the GNU General Public License along
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# with this program; if not, write to the Free Software Foundation, Inc.,
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# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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import numpy
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def cartesian_to_radec(arr, xpar="peak_x", ypar="peak_y", zpar="peak_z", degrees=True):
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"""
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Extract `x`, `y`, and `z` coordinates from a record array `arr` and
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calculate their spherical coordinates representation.
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Parameters
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----------
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arr : record array
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Record array with the Cartesian coordinates.
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xpar : str, optional
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Name of the x coordinate in the record array.
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ypar : str, optional
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Name of the y coordinate in the record array.
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zpar : str, optional
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Name of the z coordinate in the record array.
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degrees : bool, optional
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Whether to return angles in degrees. By default `True`.
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Returns
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-------
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dist : 1-dimensional array
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Radial distance.
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ra : 1-dimensional array
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Right ascension.
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dec : 1-dimensional array
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Declination.
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"""
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x, y, z = arr[xpar], arr[ypar], arr[zpar]
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dist = numpy.sqrt(x**2 + y**2 + z**2)
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dec = numpy.arcsin(z / dist)
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ra = numpy.arctan2(y, x)
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if degrees:
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dec = numpy.rad2deg(dec)
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ra = numpy.rad2deg(ra)
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return dist, ra, dec
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