galaximview.classeshists module¶

class galaximview.classeshists.CicHist2DOfXY(xcoords, ycoords, xrange, yrange, nbx=128, nby=128)[source]¶

Bases: galaximview.classeshists.Hist2DOfXY

Class for two-dimensional cloud-in-cell histograms with nbx,y+1 linear bins edges from x,ymin to x,ymax.

binned_in_2d_array(tobin, weights=None)[source]¶

Returns mass-weighted average of tobin array in bins and middle points of y,x bins.

Parameters

weights (ndarray) – (N,) masses.
tobin –

cic2d(wght)[source]¶

Computes weighted CIC histogram.

Parameters: wght –

hist2d(weights=None)[source]¶

Returns histogram and middle points of y,x bins.

Parameters: weights –

class galaximview.classeshists.CicHistOfX(rad, xrange, nbins=128)[source]¶

Bases: galaximview.classeshists.HistOfX

Class for one-dimensional cloud-in-cell histograms with nb+1 linear bins edges from rmin to rmax.

binned_dispersion_of_y_of_f_of_x(tobin, weights=None)[source]¶

Returns middle-points of bins and mass-weighted dispersion of tobin array in rad bins.

Parameters

weights (ndarray) – (N,) masses.
tobin –

binned_y_of_f_of_x(tobin, weights=None)[source]¶

Returns middle-points of bins and mass-weighted average of tobin array in rad bins.

Parameters

weights (ndarray) – (N,) masses.
tobin –

hist_of_f_of_x(weights=None)[source]¶

Returns middle-points of bins and CIC histogram.

Parameters: weights –

class galaximview.classeshists.Hist2DOfXY(xcoords, ycoords, xrange, yrange, nbx=128, nby=128, funcofx=<function identity_function>, funcofy=<function identity_function>, yedges=None, xedges=None)[source]¶

Bases: object

Class for one-dimensional histograms with nbins+1 linear bins edges in funcofx of array xarr computed in initialization, except if edges are given.

Parameters

xcoords (ndarray) – (N,) array to bin.
ycoords (ndarray) – (M,) array to bin.
xrange ((float, float) or (None, None)) – Range on which to bin xcoords. If (None, None), chosen by function xrange_from_xarr. Not used if xedges and yedges are not None.
yrange ((float, float) or (None, None)) – Range on which to bin ycoords. If (None, None), chosen by function xrange_from_xarr. Not used if xedges and yedges are not None.
xedges (ndarray or None, optional) – Edges of histogram. Used if given. If None, xedges set with xrange and nbx by function func:~galaximview.classeshists.linearly_spaced_edges_in_function_from_bin_size, so that they are linearly spaced in funcofx.
yedges (ndarray or None, optional) – Edges of histogram. Used if given. If None, yedges set with yrange and nby by function func:~galaximview.classeshists.linearly_spaced_edges_in_function_from_bin_size, so that they are linearly spaced in funcofy.

binned_in_2d_array(tobin, weights=None)[source]¶

Returns average of tobin array in 2d bins, weighted if weights is not None, middle-points of y bins and of x bins.

Parameters

tobin (ndarray) – (N,) array to bin.
weights (ndarray, optional) – (N,) weights.

Returns

(nby, nbx) histogram, (nby,) y bins middle-points and (nbx,) x bins middle-points.

Return type

(ndarray, ndarray, ndarray)

binned_in_2d_dispersion_of_array(tobin, weights=None)[source]¶

Returns dispersion of tobin array in 2d bins, weighted if weights is not None, y edges and x edges. :param tobin: (N,) array to bin. :type tobin: ndarray :param weights: (N,) weights. :type weights: ndarray, optional

Returns: (nby, nbx) histogram, (nby,) y bins middle-points and (nbx,) x bins middle-points.
Return type: (ndarray, ndarray, ndarray)

get_x_binswidth()[source]¶: Returns width of bins of (nbx+1) edges computed in self.__init__. :returns: (nbx,) widths. :rtype: ndarray

get_x_grid()[source]¶: Returns x part of meshgrid of bins middle-points.

get_x_midbins()[source]¶

Returns middle-points of (nbins+1) x edges computed in self.__init__.

Returns: (nbins,) middle points.
Return type: ndarray

get_xy_grid()[source]¶: Returns meshgrid of bins middle-points. :returns: (nbx, nby) :rtype: ndarray

get_y_binswidth()[source]¶: Returns width of bins of (nby+1) edges computed in self.__init__. :returns: (nby,) widths. :rtype: ndarray

get_y_grid()[source]¶: Returns y part of meshgrid of bins middle-points.

get_y_midbins()[source]¶

Returns middle-points of (nbins+1) y edges computed in self.__init__.

Returns: (nbins,) middle points.
Return type: ndarray

hist2d(weights=None)[source]¶

Returns histogram and middle-points of nby bins of (nby+1,) yedges and of nbx bins of (nbx+1,) xedges, and number of points of funcofx(xcoords) and funcofy(ycoords) in 2D bins if weights is None, or else sum of weights of points.

Parameters: weights (ndarray, optional) – (N,) weights.
Returns: (nby, nbx) histogram, (nby,) y bins middle-points and (nbx,) x bins middle-points.
Return type: (ndarray, ndarray, ndarray)

volumes_of_bins(volstrx, volstry)[source]¶

Attributes a “volume” to 2D bins from their edges: ‘width’ for the normal width, (left edge) - (right edge) of x or y dimension ‘annulus_surface’ for pi * (right edge) ** 2 - (left edge) ** 2 of x or y dimension ‘spherical_shell’ for 4/3 * pi * (right edge) ** 3 - (left edge) ** 3 of x or y dimension

Parameters

volstrx ({'width', 'annulus_surface', 'spherical_shell'}) – Type of cell volume.
volstry ({'width', 'annulus_surface', 'spherical_shell'}) – Type of cell volume.

Returns

(nby,nbx) array of bins ‘volume’.

Return type

ndarray

volumic_hist2d(weights=None, volstrx='width', volstry='width')[source]¶

Computes a histogram (weighted if weights is not None) divided by the “volume” of bins.

Parameters

weights (ndarray, optional) – (N,) weights.
volstrx ({'width', 'annulus_surface', 'spherical_shell'}) – Type of bin volume. See ~galaximview.classeshists.Hist2DOfXY.volumes_of_bin.
volstry ({'width', 'annulus_surface', 'spherical_shell'}) – Type of bin volume. See ~galaximview.classeshists.Hist2DOfXY.volumes_of_bin.

Returns

(nby, nbx) histogram divided by cells ‘volumes’, (nby,) y bins middle-points and (nbx,) x bins middle-points.

Return type

(ndarray, ndarray, ndarray)

class galaximview.classeshists.HistOfX(xarr, xrange, nbins=128, funcofx=<function identity_function>, edges=None, fill_range=False)[source]¶

Bases: object

Class for one-dimensional histograms with nbins+1 linear bins edges in funcofx of array xarr computed in initialization, except if edges are given.

Parameters

xarr (ndarray) – (N,) array to bin.
xrange ((float, float) or (None, None)) – Range on which to bin xarr. If (None, None), chosen by function xrange_from_xarr. Not used if edges is not None.
nbins (int, default = 128) – Number of bins. Not used if edges is not None.
funcofx (weights: ndarray, optionaldefault = identity_function()) – Function such that funcofx(xarr) is binned.
edges (ndarray or None, default = None) – Edges of histogram. Used if given. If None, edges set with xrange and nbins by function linearly_spaced_edges_in_function_from_bin_size(), so that they are linearly spaced in funcofx.
fill_range (bool, default = ` False`) – If True and edges is not None, bins are added to cover full range of xarr. Used to keep a constant bin width.

binned_dispersion_of_y_of_f_of_x(tobin, weights=None)[source]¶

Returns middle-points of bins and dispersion of tobin array in bins, weighted if weights is not None. :param tobin: (N,) array to bin. :type tobin: ndarray :param weights: (N,) weights. :type weights: ndarray, optional

Returns: (nbins,) bins middle-points and weighted dispersion of tobin array in bins.
Return type: (ndarray, ndarray)

binned_y_of_f_of_x(tobin, weights=None)[source]¶

Returns middle-points of nbins bins of (nbins+1,) edges computed in self.__init__ and average of tobin array in bins, weighted if weights is not None. :param tobin: (N,) array to bin. :type tobin: ndarray :param weights: (N,) weights. :type weights: ndarray, optional

Returns: (nbins,) bins middle-points and mass-weighted average of tobin array in bins.
Return type: (ndarray, ndarray)

get_bins_widths()[source]¶

Returns width of bins of (nbins+1) edges computed in self.__init__.

Returns: (nbins,) widths.
Return type: ndarray

get_midbins()[source]¶

Returns middle-points of (nbins+1) edges computed in self.__init__.

Returns: (nbins,) middle points.
Return type: ndarray

hist_of_f_of_x(weights=None)[source]¶

Returns middle-points of nbins bins of (nbins+1,) edges computed in self.__init__ and number of array members of funcofx(xarr) in bins if weights is None, or else sum of weights of array members of funcofx(xarr) in bins. :param weights: (N,) weights. :type weights: ndarray, optional

Returns: (nbins,) bins middle-points and histogram of funcofx(xarr).
Return type: (ndarray, ndarray)

volumes_of_bin(volstr)[source]¶

Attributes a “volume” to bins from their edges: ‘width’ for the normal width, (left edge) - (right edge) ‘annulus_surface’ for pi * (right edge) ** 2 - (left edge) ** 2 ‘spherical_shell’ for 4/3 * pi * (right edge) ** 3 - (left edge) ** 3

Parameters: volstr ({'width', 'annulus_surface', 'spherical_shell'}) – Type of cell volume.
Returns: (nbins,) array of cells ‘volume’.
Return type: ndarray

volumic_hist_of_f_of_x(weights=None, volstr='width')[source]¶

Computes a histogram (weighted if weights is not None) of func(xarr) divided by the “volume” of bins.

Parameters

weights (ndarray, optional) – (N,) weights.
volstr ({'width', 'annulus_surface', 'spherical_shell'}) – Type of bin volume. See ~galaximview.classeshists.HistOfX.volumes_of_bin.

Returns

(nbins,) bins middle-points and histogram of funcofx(xarr) divided by cells ‘volume’.

Return type

(ndarray, ndarray)

galaximview.classeshists.fill_range_around_edges(arr, func, edges)[source]¶

Fills range of func(arr) with additional bins if edges do not cover the whole range. :param arr: (N,) array. :type arr: ndarray :param func: Function such that bins in func(arr) are computed. :type func: ufunc :param edges: Edges. :type edges: ndarray

Returns: Edges covering the whole range of func(arr), linearly space in func(arr).
Return type: ndarray

galaximview.classeshists.linearly_spaced_edges_in_function_from_bin_size(xrange, function, bin_size)[source]¶

Returns edges linearly spaced in function, i.e. function(xmin) + np.arange(nb + 1) * (function(xmax) - function(xmin)) / (nb)”

Parameters

xrange ((float, float)) – (xmin, xmax)
bin_size (float) – Width of bins.
function (ufunc) – Function such that unction(xmin) + np.arange(nb + 1) * (function(xmax) - function(xmin)) / (nb) is returned.

Returns

(nb+1,) edges linearly spaced in function.

Return type

ndarray

galaximview.classeshists.linearly_spaced_edges_in_function_from_nb(xrange, function, nb)[source]¶

Returns edges linearly spaced in function, i.e. function(xmin) + np.arange(nb + 1) * (function(xmax) - function(xmin)) / (nb)”

Parameters

xrange ((float, float)) – (xmin, xmax)
nb (int) – Number of bins.
function (ufunc) – Function such that unction(xmin) + np.arange(nb + 1) * (function(xmax) - function(xmin)) / (nb) is returned.

Returns

(nb+1,) edges linearly spaced in function.

Return type

ndarray

galaximview.classeshists.xrange_from_xarr(xarr, xrange, funcofx)[source]¶

Returns xrange if not (None, None) or else chooses reasonable range according to chosen function of x.

Parameters

xarr (ndarray) – (N,) array.
xrange ((float, float) or (None, None)) – (xmin,xmax) returned as such if not (None, None).
funcofx (ufunc) – Function such that the histogram will be of funcofx(xarr).

Returns

Rangeon which the histogram of funcofx(xarr) will be computed.

Return type

(float, float)