VoidRender API

VoidRender for VoidFinder

load_galaxy_data

vast.voidfinder.viz.load_galaxy_data(infilename)

Load a table of galaxies for use in VoidRender

Parameters

infilenamestring

path to desired data file intended to be an astropy table output from VoidFinder with columns ‘ra’, ‘dec’, ‘redshift’, and possibly ‘Rgal’

Returns

galaxy_data_xyznumpy.ndarray shape (N,3)

xyz coordinates of galaxies from the data table

load_void_data

vast.voidfinder.viz.load_void_data(infilename)

Load voids as formatted for VoidFinder

Parameters

infilenamestring

path to desired data file

Returns

holes_xyznumpy.ndarray shape (N,3)

the xyz centers of the holes

holes_radiinumpy.ndarray shape (N,)

the radii of the holes

hole_flagsnumpy.ndarray shape (N,)

the VoidFinder ‘flag’ output representing which void group a hole belongs to

VoidRender

vast.voidfinder.viz.VoidRender.__init__(self, holes_xyz=None, holes_radii=None, holes_group_IDs=None, galaxy_xyz=None, galaxy_display_radius=2.0, wall_galaxy_xyz=None, wall_distance=3.5, remove_void_intersects=1, filter_for_degenerate=True, canvas_size=(800, 600), title='VoidFinder Results', camera_start_location=None, camera_start_orientation=None, start_translation_sensitivity=1.0, start_rotation_sensitivity=1.0, galaxy_color=array([1., 0., 0., 1.], dtype=float32), wall_galaxy_color=array([0., 0., 0., 1.], dtype=float32), void_hole_color=array([0., 0., 1., 0.95], dtype=float32), SPHERE_TRIANGULARIZATION_DEPTH=3, verbose=False)

Main class for initializing the visualization.

Parameters

holes_xyz(N,3) numpy.ndarray

xyz coordinates of the hole centers

holes_radii(N,) numpy.ndarray

length of the hole radii in xyz coordinates

holes_group_IDs(N,) numpy.ndarray of integers

Void group to which a given hole belongs according to VoidFinder

galaxy_xyz(M,3) numpy.ndarray

xyz coordinates of the galaxy locations

galaxy_display_radiusfloat

using a constant radius to display galaxy points since they should all be small compared to the void holes, and they don’t have corresponding radii

wall_galaxy_xyz(K,3) numpy.ndarray

xyz coordinates of the wall galaxy locations

wall_distancefloat

xyz distance at which to connect two wall galaxies with a web visualization. This should be set to the isolated galaxy distance limit calculated in VoidFinder (and printed to the terminal).

remove_void_intersectsint, default 1

0 - turn off 1 - remove all intersections 2 - remove intersections only within predefined Void Groups based on hole_group_IDs turn on (True) or off (False) the clipping of display triangles for void interiors. When true, removes all the triangles of a void hole sphere which are fully contained inside another void hole, which essentially creates a surface union of void holes which overlap. Note that for smaller sphere density values, the edge artifacts along the seams where void holes intersect will be more visually apparent

filter_for_degeneratebool, default True

if true, filter the holes_xyz and holes_radii for any holes which are completely contained within another hole and remove them

canvas_size2-tuple

(width, height) in pixels for the output visualization

titlestr

value to display at top of the window

camera_start_locationndarray of shape (3,) dtype float32

starting location for the camera. Remember to multiply by -1.0 to go from data coordinates to camera coordinates example: np.zeros(3, dtype=np.float32)

camera_start_orientationndarray of shape (3,3) dtype float32

rotation matrix describing initial camera orientation example: np.eye(3, dtype=np.float32)

start_translation_sensitivityfloat

starting sensitivity for translation keys - wasdrf

start_rotation_sensitivityfloat

starting sensitivity for rotation keys - qeijkl

galaxy_colorndarray shape (4,) dtype float32

values from 0.0-1.0 representing RGB and Alpha for the galaxy points

wall_galaxy_colorndarray shape (4,) dtype float32

values from 0.0-1.0 representing RBG and Alpha for the wall galaxy points

void_hole_colorndarray shape (4,) or (num_void,4) dtype float32

values from 0.0-1.0 representing RGB and Alpha for the voids

void_highlight_colorndarray shape (4,) dtype float32

values from 0.0-1.0 representing RGB and Alpha for the void highlight, when the camera enters a void hole it turns the hole this color so you know you are inside IF enable_void_interior_highlight == True

SPHERE_TRIANGULARIZATION_DEPTHinteger, default 3

number of subdivisions in the icosahedron sphere triangularization to make. Total vertices will be num_voids * 20 * 3 * 4^SPHERE_TRIANGULARIZATION_DEPTH so be careful increasing this value above 3. Default of 3 results in 3840 vertices (1280 triangles) per sphere

Notes

Controls:

w - translate forward s - translate backward a - translate left d - translate right r - elevate up f - elevate down

q - roll left e - roll right i - pitch up k - pitch down j - yaw left k - yaw right

z - increase translation sensitivity x - decrease translation sensitivity

m - start/stop video recording NOTE: MAY TAKE A LOT OF RAM 0 - screenshot

Left mouse click - pitch & yaw Right mouse click - translate forward & backward Mouse Wheel - increase & decrease galaxy size

Examples

from vast.voidfinder.viz import VoidRender, load_void_data, load_galaxy_data

holes_xyz, holes_radii, holes_flags = load_void_data(“vollim_dr7_cbp_102709_holes.txt”)

galaxy_data = load_galaxy_data(“vollim_dr7_cbp_102709.dat”)

viz = VoidFinderCanvas(holes_xyz,

holes_radii, galaxy_data, canvas_size=(1600,1200))

viz.run()

VoidRender for V²

load_galaxy_data

vast.vsquared.viz.load_galaxy_data(infilename)

Load a table of galaxies for use in VoidRender

Parameters

infilenamestring

path to desired data file intended to be a fits table with columns ‘ra’, ‘dec’, and ‘z’

Returns

galaxy_data_xyznumpy.ndarray shape (N,3)

xyz coordinates of galaxies from the data table

load_void_data

vast.vsquared.viz.load_void_data(infilename1, infilename2)

Load voids as formatted for Vsquared

Parameters

infilename1string

path to desired _triangles.dat data file

infilename2string

path to desired _galviz.dat data file

Returns

voids_tri_x, _y, _znumpy.ndarrays shape (N,3)

the xyz coordinates of the the vertices of triangles making up void edges

voids_normnumpy.ndarray shape (N,3)

the xyz coordinates of each triangle’s unit normal vector

voids_idnumpy.ndarray shape (N,)

the void ID of each triangle

gal_viznumpy.ndarray shape (N,)

the void ID of each galaxy

gal_oppnumpy.ndarray shape (N,)

the void ID of each galaxy’s nearest neighbor

VoidRender

vast.vsquared.viz.VoidRender.__init__(self, voids_tri_x=None, voids_tri_y=None, voids_tri_z=None, voids_norm=None, voids_id=None, galaxy_xyz=None, galaxy_display_radius=2.0, gal_viz=None, gal_opp=None, canvas_size=(800, 600), title='V2 Results', camera_start_location=None, camera_start_orientation=None, start_translation_sensitivity=1.0, start_rotation_sensitivity=1.0, galaxy_color=array([1., 0., 0., 1.], dtype=float32), void_color=array([0., 0., 1., 0.95], dtype=float32))

Main class for initializing the visualization.

Parameters

voids_tri_x, _y, _znumpy.ndarrays shape (N,3)

the xyz coordinates of the the vertices of triangles making up void edges

voids_normnumpy.ndarray shape (N,3)

the xyz coordinates of each triangle’s unit normal vector

voids_idnumpy.ndarray shape (N,)

the void ID of each triangle

galaxy_xyz(N,3) numpy.ndarray

xyz coordinates of the galaxy locations

galaxy_display_radiusfloat

using a constant radius to display galaxy points since they should all be small compared to the void holes, and they don’t have corresponding radii

gal_viznumpy.ndarray shape (N,)

the void ID of each galaxy

gal_oppnumpy.ndarray shape (N,)

the void ID of each galaxy’s nearest neighbor

canvas_size2-tuple

(width, height) in pixels for the output visualization

titlestr

value to display at top of the window

camera_start_locationndarray of shape (3,) dtype float32

starting location for the camera. Remember to multiply by -1.0 to go from data coordinates to camera coordinates example: np.zeros(3, dtype=np.float32)

camera_start_orientationndarray of shape (3,3) dtype float32

rotation matrix describing initial camera orientation example: np.eye(3, dtype=np.float32)

start_translation_sensitivityfloat

starting sensitivity for translation keys - wasdrf

start_rotation_sensitivityfloat

starting sensitivity for rotation keys - qeijkl

galaxy_colorndarray shape (4,) dtype float32

values from 0.0-1.0 representing RGB and Alpha for the galaxy points

void_colorndarray shape (4,) or (num_void,4) dtype float32

values from 0.0-1.0 representing RGB and Alpha for the voids

Notes

Controls: w - translate forward s - translate backward a - translate left d - translate right r - elevate up f - elevate down

q - roll left e - roll right i - pitch up k - pitch down j - yaw left k - yaw right

z - increase translation sensitivity x - decrease translation sensitivity

m - start/stop video recording NOTE: MAY TAKE A LOT OF RAM 0 - screenshot

Left mouse click - pitch & yaw Right mouse click - translate forward & backward Mouse Wheel - increase & decrease galaxy size

Examples

from vast.vsquared.viz import VoidRender, load_void_data, load_galaxy_data

voids_tri_x, voids_tri_y, voids_tri_z, voids_norm, voids_id, gal_viz, gal_opp = load_void_data(“DR7_triangles.dat”, “DR7_galviz.dat”)

galaxy_data = load_galaxy_data(“vollim_dr7_cbp_102709.fits”)

viz = VoidFinderCanvas(voids_tri_x, voids_tri_y, voids_tri_z,

voids_norm, voids_id, galaxy_data, gal_viz, gal_opp, canvas_size=(1600,1200))

viz.run()