Merge pull request #529 from aphearin/cuboid_label_relocation

Cuboid label relocation

halotools/mock_observables/catalog_analysis_helpers.py

@@ -1,8 +1,4 @@
-# -*- coding: utf-8 -*-
-
-""" Common functions used when analyzing
-catalogs of galaxies/halos.
-
+""" Common functions used when analyzing catalogs of galaxies/halos.
 """
 from __future__ import (absolute_import, division, print_function, unicode_literals)
 
@@ -13,7 +9,7 @@
 
 from ..custom_exceptions import HalotoolsError
 
-__all__ = ('mean_y_vs_x', 'return_xyz_formatted_array')
+__all__ = ('mean_y_vs_x', 'return_xyz_formatted_array', 'cuboid_subvolume_labels')
 __author__ = ['Andrew Hearin']
 
 
@@ -201,6 +197,98 @@ def return_xyz_formatted_array(x, y, z, period=np.inf, **kwargs):
     except KeyError:
         return pos
 
+def cuboid_subvolume_labels(sample, Nsub, Lbox):
+    """
+    Return integer labels indicating which cubical subvolume of a larger cubical volume a 
+    set of points occupy.
+    
+    Parameters
+    ----------
+    sample : array_like
+        Npts x 3 numpy array containing 3-D positions of points.
+    
+    Nsub : array_like
+        Length-3 numpy array of integers indicating how many times to split the volume 
+        along each dimension.  If single integer, N, is supplied, ``Nsub`` is set to 
+        [N,N,N], and the volume is split along each dimension N times.  The total number 
+        of subvolumes is then given by numpy.prod(Nsub).
+    
+    Lbox : array_like
+        Length-3 numpy array definging the lengths of the sides of the cubical volume
+        that ``sample`` occupies.  If only a single scalar is specified, the volume is assumed 
+        to be a cube with side-length Lbox
+    
+    Returns
+    -------
+    labels : numpy.array
+        numpy array with integer labels in the range [1,numpy.prod(Nsub)] indicating 
+        the subvolume each point in ``sample`` occupies.
+    
+    N_sub_vol : int
+       number of subvolumes.
+    
+    Examples
+    --------
+    For demonstration purposes we create a randomly distributed set of points within a 
+    periodic unit cube. 
+    
+    >>> Npts = 1000
+    >>> Lbox = 1.0
+    >>> period = np.array([Lbox,Lbox,Lbox])
+    
+    >>> x = np.random.random(Npts)
+    >>> y = np.random.random(Npts)
+    >>> z = np.random.random(Npts)
+    
+    We transform our *x, y, z* points into the array shape used by the pair-counter by 
+    taking the transpose of the result of `numpy.vstack`. This boilerplate transformation 
+    is used throughout the `~halotools.mock_observables` sub-package:
+    
+    >>> sample = np.vstack((x,y,z)).T
+    
+    Divide the volume into cubes with length 0.25 on a side.
+    
+    >>> Nsub = [4,4,4]
+    >>> labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
+    """
+
+    #process inputs and check for consistency
+    sample = np.atleast_1d(sample).astype('f8')
+    try:
+        assert sample.ndim == 2
+        assert sample.shape[1] == 3
+    except AssertionError:
+        msg = ("Input ``sample`` must have shape (Npts, 3)")
+        raise TypeError(msg)
+
+    Nsub = np.atleast_1d(Nsub).astype('i4')
+    if len(Nsub) == 1:
+        Nsub = np.array([Nsub[0], Nsub[0], Nsub[0]])
+    elif len(Nsub) != 3:
+        msg = "Input ``Nsub`` must be a scalar or length-3 sequence"
+        raise TypeError(msg)
+
+    Lbox = np.atleast_1d(Lbox).astype('f8')
+    if len(Lbox) == 1:
+        Lbox = np.array([Lbox[0]]*3)
+    elif len(Lbox) != 3:
+        msg = "Input ``Lbox`` must be a scalar or length-3 sequence"
+        raise TypeError(msg)
+
+    dL = Lbox/Nsub # length of subvolumes along each dimension
+    N_sub_vol = int(np.prod(Nsub)) # total the number of subvolumes
+    # create an array of unique integer IDs for each subvolume
+    inds = np.arange(1, N_sub_vol+1).reshape(Nsub[0], Nsub[1], Nsub[2])
+
+    #tag each particle with an integer indicating which subvolume it is in
+    index = np.floor(sample/dL).astype(int)
+    #take care of the case where a point falls on the boundary
+    for i in range(3):
+        index[:, i] = np.where(index[:, i] == Nsub[i], Nsub[i] - 1, index[:, i])
+    index = inds[index[:,0],index[:,1],index[:,2]].astype(int)
+
+    return index, int(N_sub_vol)
+
 
 
 

halotools/mock_observables/tests/test_catalog_analysis_helpers.py

@@ -1,20 +1,80 @@
-#!/usr/bin/env python
+""" Module providing unit-testing for the functions in 
+`~halotools.mock_observables.catalog_analysis_helpers` module. 
+"""
 from __future__ import (absolute_import, division, print_function)
 
 from unittest import TestCase
 
 import numpy as np 
 
 from astropy.tests.helper import pytest
+from astropy.utils.misc import NumpyRNGContext
 
 from .. import catalog_analysis_helpers as cat_helpers
+from ..catalog_analysis_helpers import cuboid_subvolume_labels
 
 from ...sim_manager import FakeSim
 
+from .cf_helpers import generate_locus_of_3d_points
+
 from ...custom_exceptions import HalotoolsError
 
 __all__ = ('TestCatalogAnalysisHelpers', )
 
+fixed_seed = 43
+
+def test_cuboid_subvolume_labels_bounds_checking():
+    Npts = 100
+    with NumpyRNGContext(fixed_seed):
+        good_sample = np.random.random((Npts, 3))
+        bad_sample = np.random.random((Npts, 2))
+
+    good_Nsub1 = 3
+    good_Nsub2 = (4, 4, 4)
+    bad_Nsub = (3, 3)
+
+    good_Lbox = 1
+    good_Lbox2 = (1, 1, 1)
+    bad_Lbox = (3, 3)
+
+    with pytest.raises(TypeError) as err:
+        cuboid_subvolume_labels(bad_sample, good_Nsub1, good_Lbox)
+    substr = "Input ``sample`` must have shape (Npts, 3)"
+    assert substr in err.value.args[0]
+
+    with pytest.raises(TypeError) as err:
+        cuboid_subvolume_labels(good_sample, bad_Nsub, good_Lbox2)
+    substr = "Input ``Nsub`` must be a scalar or length-3 sequence"
+    assert substr in err.value.args[0]
+
+    with pytest.raises(TypeError) as err:
+        cuboid_subvolume_labels(good_sample, good_Nsub2, bad_Lbox)
+    substr = "Input ``Lbox`` must be a scalar or length-3 sequence"
+    assert substr in err.value.args[0]
+
+def test_cuboid_subvolume_labels_correctness():
+    Npts = 100
+    Nsub = 2
+    Lbox = 1
+
+    sample = generate_locus_of_3d_points(Npts, xc=0.1, yc=0.1, zc=0.1, seed = fixed_seed)
+    labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
+    assert np.all(labels == 1)
+
+    sample = generate_locus_of_3d_points(Npts, xc=0.9, yc=0.9, zc=0.9, seed = fixed_seed)
+    labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
+    assert np.all(labels == 8)
+
+    sample = generate_locus_of_3d_points(Npts, xc=0.1, yc=0.1, zc=0.9, seed = fixed_seed)
+    labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
+    assert np.all(labels == 2)
+
+    sample = generate_locus_of_3d_points(Npts, xc=0.1, yc=0.9, zc=0.1, seed = fixed_seed)
+    labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
+    assert np.all(labels == 3)
+
+
+
 class TestCatalogAnalysisHelpers(TestCase):
     """ Class providing tests of the `~halotools.mock_observables.catalog_analysis_helpers`. 
     """

halotools/mock_observables/two_point_clustering/tests/test_tpcf_jackknife.py

@@ -6,11 +6,9 @@
 from astropy.tests.helper import pytest
 from astropy.utils.misc import NumpyRNGContext
 
-from ..tpcf_jackknife import tpcf_jackknife, cuboid_subvolume_labels
+from ..tpcf_jackknife import tpcf_jackknife
 from ..tpcf import tpcf
 
-from ...tests.cf_helpers import generate_locus_of_3d_points
-
 slow = pytest.mark.slow
 
 __all__=['test_tpcf_jackknife_corr_func', 'test_tpcf_jackknife_cov_matrix']
@@ -56,64 +54,3 @@ def test_tpcf_jackknife_cov_matrix():
 
     assert np.shape(err)==(nbins,nbins), "cov matrix not correct shape"
 
-def test_cuboid_subvolume_labels_bounds_checking():
-    Npts = 100
-    with NumpyRNGContext(fixed_seed):
-        good_sample = np.random.random((Npts, 3))
-        bad_sample = np.random.random((Npts, 2))
-
-    good_Nsub1 = 3
-    good_Nsub2 = (4, 4, 4)
-    bad_Nsub = (3, 3)
-
-    good_Lbox = 1
-    good_Lbox2 = (1, 1, 1)
-    bad_Lbox = (3, 3)
-
-    with pytest.raises(TypeError) as err:
-        cuboid_subvolume_labels(bad_sample, good_Nsub1, good_Lbox)
-    substr = "Input ``sample`` must have shape (Npts, 3)"
-    assert substr in err.value.args[0]
-
-    with pytest.raises(TypeError) as err:
-        cuboid_subvolume_labels(good_sample, bad_Nsub, good_Lbox2)
-    substr = "Input ``Nsub`` must be a scalar or length-3 sequence"
-    assert substr in err.value.args[0]
-
-    with pytest.raises(TypeError) as err:
-        cuboid_subvolume_labels(good_sample, good_Nsub2, bad_Lbox)
-    substr = "Input ``Lbox`` must be a scalar or length-3 sequence"
-    assert substr in err.value.args[0]
-
-def test_cuboid_subvolume_labels_correctness():
-    Npts = 100
-    Nsub = 2
-    Lbox = 1
-
-    sample = generate_locus_of_3d_points(Npts, xc=0.1, yc=0.1, zc=0.1, seed = fixed_seed)
-    labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
-    assert np.all(labels == 1)
-
-    sample = generate_locus_of_3d_points(Npts, xc=0.9, yc=0.9, zc=0.9, seed = fixed_seed)
-    labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
-    assert np.all(labels == 8)
-
-    sample = generate_locus_of_3d_points(Npts, xc=0.1, yc=0.1, zc=0.9, seed = fixed_seed)
-    labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
-    assert np.all(labels == 2)
-
-    sample = generate_locus_of_3d_points(Npts, xc=0.1, yc=0.9, zc=0.1, seed = fixed_seed)
-    labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
-    assert np.all(labels == 3)
-
-
-
-
-
-
-
-
-
-
-
-

halotools/mock_observables/two_point_clustering/tpcf_jackknife.py

@@ -15,10 +15,10 @@
 from ..mock_observables_helpers import (enforce_sample_has_correct_shape, 
     get_separation_bins_array, get_period, get_num_threads)
 from ..pair_counters.mesh_helpers import _enforce_maximum_search_length
-
+from ..catalog_analysis_helpers import cuboid_subvolume_labels
 from ...custom_exceptions import HalotoolsError
 
-__all__ = ('tpcf_jackknife', 'cuboid_subvolume_labels')
+__all__ = ('tpcf_jackknife', )
 __author__ = ('Duncan Campbell', )
 
 
@@ -469,99 +469,3 @@ def _tpcf_jackknife_process_args(sample1, randoms, rbins,
     return sample1, rbins, Nsub, sample2, randoms, period, do_auto, do_cross,\
            num_threads, _sample1_is_sample2, PBCs
 
-def cuboid_subvolume_labels(sample, Nsub, Lbox):
-    """
-    Return integer labels indicating which cubical subvolume of a larger cubical volume a 
-    set of points occupy.
-    
-    Parameters
-    ----------
-    sample : array_like
-        Npts x 3 numpy array containing 3-D positions of points.
-    
-    Nsub : array_like
-        Length-3 numpy array of integers indicating how many times to split the volume 
-        along each dimension.  If single integer, N, is supplied, ``Nsub`` is set to 
-        [N,N,N], and the volume is split along each dimension N times.  The total number 
-        of subvolumes is then given by numpy.prod(Nsub).
-    
-    Lbox : array_like
-        Length-3 numpy array definging the lengths of the sides of the cubical volume
-        that ``sample`` occupies.  If only a single scalar is specified, the volume is assumed 
-        to be a cube with side-length Lbox
-    
-    Returns
-    -------
-    labels : numpy.array
-        numpy array with integer labels in the range [1,numpy.prod(Nsub)] indicating 
-        the subvolume each point in ``sample`` occupies.
-    
-    N_sub_vol : int
-       number of subvolumes.
-    
-    Examples
-    --------
-    For demonstration purposes we create a randomly distributed set of points within a 
-    periodic unit cube. 
-    
-    >>> Npts = 1000
-    >>> Lbox = 1.0
-    >>> period = np.array([Lbox,Lbox,Lbox])
-    
-    >>> x = np.random.random(Npts)
-    >>> y = np.random.random(Npts)
-    >>> z = np.random.random(Npts)
-    
-    We transform our *x, y, z* points into the array shape used by the pair-counter by 
-    taking the transpose of the result of `numpy.vstack`. This boilerplate transformation 
-    is used throughout the `~halotools.mock_observables` sub-package:
-    
-    >>> sample = np.vstack((x,y,z)).T
-    
-    Divide the volume into cubes with length 0.25 on a side.
-    
-    >>> Nsub = [4,4,4]
-    >>> labels, N_sub_vol = cuboid_subvolume_labels(sample, Nsub, Lbox)
-    """
-
-    #process inputs and check for consistency
-    sample = np.atleast_1d(sample).astype('f8')
-    try:
-        assert sample.ndim == 2
-        assert sample.shape[1] == 3
-    except AssertionError:
-        msg = ("Input ``sample`` must have shape (Npts, 3)")
-        raise TypeError(msg)
-
-    Nsub = np.atleast_1d(Nsub).astype('i4')
-    if len(Nsub) == 1:
-        Nsub = np.array([Nsub[0], Nsub[0], Nsub[0]])
-    elif len(Nsub) != 3:
-        msg = "Input ``Nsub`` must be a scalar or length-3 sequence"
-        raise TypeError(msg)
-
-    Lbox = np.atleast_1d(Lbox).astype('f8')
-    if len(Lbox) == 1:
-        Lbox = np.array([Lbox[0]]*3)
-    elif len(Lbox) != 3:
-        msg = "Input ``Lbox`` must be a scalar or length-3 sequence"
-        raise TypeError(msg)
-
-    dL = Lbox/Nsub # length of subvolumes along each dimension
-    N_sub_vol = int(np.prod(Nsub)) # total the number of subvolumes
-    # create an array of unique integer IDs for each subvolume
-    inds = np.arange(1, N_sub_vol+1).reshape(Nsub[0], Nsub[1], Nsub[2])
-
-    #tag each particle with an integer indicating which subvolume it is in
-    index = np.floor(sample/dL).astype(int)
-    #take care of the case where a point falls on the boundary
-    for i in range(3):
-        index[:, i] = np.where(index[:, i] == Nsub[i], Nsub[i] - 1, index[:, i])
-    index = inds[index[:,0],index[:,1],index[:,2]].astype(int)
-
-    return index, int(N_sub_vol)
-
-
-
-
-