raytraverse.evaluate¶

MetricSet¶

class raytraverse.evaluate.MetricSet(vm, vec, omega, lum, metricset=None, scale=179.0, threshold=2000.0, guth=True, tradius=30.0, **kwargs)[source]¶

Bases: object

object for calculating metrics based on a view direction, and rays consisting on direction, solid angle and luminance information

by encapsulating these calculations within a class, metrics with redundant calculations can take advantage of cached results, for example dgp does not need to recalculate illuminance when it has been directly requested. all metrics can be accessed as properties (and are calculated just in time) or the object can be called (no arguments) to return a np.array of all metrics defined in “metricset”

Parameters

vm (raytraverse.mapper.ViewMapper) – the view direction
vec (np.array) – (N, 3) directions of all rays in view
omega (np.array) – (N,) solid angle of all rays in view
lum (np.array) – (N,) luminance of all rays in view (multiplied by “scale”)
metricset (list, optional) – keys of metrics to return, same as property names
scale (float, optional) – scalefactor for luminance
threshold (float, optional) – threshold for glaresource/background similar behavior to evalglare ‘-b’ paramenter. if greater than 100 used as a fixed luminance threshold. otherwise used as a factor times the task luminance (defined by ‘tradius’)
guth (bool, optional) – if True, use Guth for the upper field of view and iwata for the lower if False, use Kim
tradius (float, optional) – radius in degrees for task luminance calculation
kwargs – additional arguments that may be required by additional properties

allmetrics = ['illum', 'avglum', 'gcr', 'ugp', 'dgp', 'tasklum', 'backlum', 'dgp_t1', 'log_gc', 'dgp_t2', 'ugr', 'threshold', 'pwsl2', 'view_area', 'density', 'reldensity', 'lumcenter', 'avgraylum', 'backlum_true', 'srcillum']¶

defaultmetrics = ['illum', 'avglum', 'gcr', 'ugp', 'dgp']¶: available metrics (and the default return set)

static check_metrics(metrics, raise_error=False)[source]¶: returns list of valid metric names from argument if raise_error is True, raises an Atrribute Error

property vec¶

property lum¶

property omega¶

property ctheta¶: cos angle between ray and view

property radians¶: cos angle between ray and view

property src_mask¶: boolean mask for filtering source/background rays

property task_mask¶

property sources¶: vec, omega, lum of rays above threshold

property background¶: vec, omega, lum of rays below threshold

property source_pos_idx¶

property threshold¶: threshold for glaresource/background similar behavior to evalglare ‘-b’ paramenter

property pwsl2¶: position weighted source luminance squared, used by dgp, ugr, etc sum(Ls^2*omega/Ps^2)

property srcillum¶: average background luminance

property backlum¶: average background luminance CIE estimate (official for some metrics)

property backlum_true¶: average background luminance mathematical

property tasklum¶: average task luminance

property illum¶: illuminance

property avglum¶: average luminance

property avgraylum¶: average luminance (not weighted by omega

property gcr¶: a unitless measure of relative contrast defined as the average of the squared luminances divided by the average luminance squared

property dgp¶

property dgp_t1¶

property log_gc¶

property dgp_t2¶

property ugr¶

property ugp¶

property density¶

property reldensity¶

property lumcenter¶

PositionIndex¶

class raytraverse.evaluate.PositionIndex(guth=True)[source]¶

Bases: object

calculate position index according to guth/iwata or kim

Parameters: guth (bool) – if True, use Guth for the upper field of view and iwata for the lower if False, use Kim

positions(vm, vec)[source]¶

calculate position indices for a set of vectors

Parameters

vm (raytraverse.mapper.ViewMapper) – the view/analysis point, should have 180 degree field of view
vec (np.array) – shape (N,3) the view vectors to calculate

Returns

posidx – shape (N,) the position indices

Return type

np.arrray

static _to_plane(n, vec)[source]¶

static _angle_vv(a, b)[source]¶

static _get_pidx_guth(sigma, tau)[source]¶

static _get_pidx_iwata(phi, theta)[source]¶

static _get_pidx_kim(sigma, tau)[source]¶

retina¶

raytraverse.evaluate.retina.rgcf_density_on_meridian(deg, mi)[source]¶

retinal ganlgion cell field density along a meridian as a functional best fit.

the field density accounts for the input region of the ganglion cell to account for displaced ganglion cells. This value is estimate from cone density and the inferred density of midget ganglion cells. see Watson (2014) for important caveats.

Parameters

deg (np.array) – eccentricity in degrees along merdian
mi (int) – meridian index. [0, 1, 2, 3] for Temporal, Superior, Nasal, Inferior.

Returns

1d array of retinal ganglion cell density along a merdian

Return type

np.array

raytraverse.evaluate.retina.rgc_density_on_meridian(deg, mi)[source]¶

retinal ganglion cell density along a merdian as a linear interpolation between non-zero measurements

As opposed to the field density this estimate the actual location of ganglion cells, which could be important to consider for intrinsically photosensitive cells. These are (partially?) responsible for pupillary response. However, even iprgc (may?) receive signals from rods/cones

Parameters

deg (np.array) – eccentricity in degrees along merdian
mi (int) – meridian index. [0, 1, 2, 3] for Temporal, Superior, Nasal, Inferior.

Returns

1d array of retinal ganglion cell density along a merdian

Return type

np.array

raytraverse.evaluate.retina.rgcf_density_xy(xy, func=<function rgcf_density_on_meridian>)[source]¶

interpolate density between meridia, selected by quadrant

Parameters

xy (np.array) – xy visual field coordinates on a disk in degrees (eccentricity 0-90 from fovea)
func (callable) – density function along a meridian, takes r in degrees and an axes index: [0, 1, 2, 3] for Temporal, Superior, Nasal, Inferior.

Returns

1d array of single eye densities

Return type

np.array

raytraverse.evaluate.retina.binocular_density(xy, func=<function rgcf_density_on_meridian>)[source]¶

average denisty between both eyes.

Parameters

xy (np.array) – xy visual field coordinates on a disk (eccentricity 0-1 from fovea)
func (callable) – density function along a meridian, takes r in degrees and an axes index: [0, 1, 2, 3] for Temporal, Superior, Nasal, Inferior. coordinates are for the visual field.

Returns

1d array of average binocular densities

Return type

np.array

raytraverse.evaluate.retina.rgcf_density(xy)[source]¶

retinal ganglion cell field density

Parameters: xy (np.array) – xy visual field coordinates on a disk (eccentricity 0-1 from fovea)
Returns: 1d array retinal ganglion cell field density according to model by Watson
Return type: np.array

raytraverse.evaluate.retina.rgc_density(xy)[source]¶

retinal ganglion cell density (includes displaced ganglion cells)

Parameters: xy (np.array) – xy visual field coordinates on a disk (eccentricity 0-1 from fovea)
Returns: 1d array retinal ganglion cell density according to measurements by Curcio
Return type: np.array