raytraverse.lightpoint

LightPointKD

class raytraverse.lightpoint.LightPointKD(scene, vec=None, lum=None, vm=None, pt=(0, 0, 0), posidx=0, src='sky', srcn=1, srcdir=(0, 0, 1), calcomega=True, write=True, omega=None, filterviews=True, srcviews=None, parent=None, srcviewidxs=None, features=1)

Bases: object

light distribution from a point with KDtree structure for directional query

Parameters

• scene (raytraverse.scene.BaseScene) –

• vec (np.array, optional) – shape (N, >=3) where last three columns are normalized direction vectors of samples. If not given, tries to load from scene.outdir

• lum (np.array, optional) – reshapeable to (N, srcn). sample values for each source corresponding to vec. If not given, tries to load from scene.outdir

• vm (raytraverse.mapper.ViewMapper, optional) – a default viewmapper for image and metric calculations, should match viewmapper of sampler.run() if possible.

• pt (tuple list np.array) – 3 item point location of light distribution

• posidx (int, optional) – index position of point, will govern file naming so must be set to avoid clobbering writes. also used by spacemapper for planar sampling

• src (str, optional) – name of source group. will govern file naming so must be set to avoid clobbering writes.

• srcn (int, optional) – must match lum, does not need to be set if reloading from scene.outdir

• calcomega (bool, optional) – if True (default) calculate solid angle of rays. This is unnecessary if point will be combined before calculating any metrics. setting to False will save some computation time.

• write (bool, optional) – whether to save ray data to disk.

• omega (np.array, optional) – provide precomputed omega values, if given, overrides calcomega

vm

raytraverse.mapper.ViewMapper

scene

raytraverse.scene.Scene

posidx

index for point

Type

int

pt

point location

Type

np.array

src

source key

Type

str

file

relative path to disk storage

Type

str

srcdir

direction to source(s)

load()

dump()

property vec

direction vector (N,3)

property lum

luminance (N,srcn)

property d_kd

kd tree for spatial query

Getter

Returns kd tree structure

Type

scipy.spatial.cKDTree

property omega

solid angle (N)

Getter

Returns array of solid angles

Setter

sets soolid angles with viewmapper

Type

np.array

set_srcviews(srcviews, idxs=None)

calc_omega(write=True)

calculate solid angle

Parameters

write (bool, optional) – update/write kdtree data to file

apply_coef(coefs)

apply coefficient vector to self.lum

Parameters

coefs (np.array int float list) – shape (N, self.srcn) or broadcastable

Returns

alum – shape (N, self.vec.shape[0])

Return type

np.array

add_to_img(img, vecs, mask=None, skyvec=1, interp=False, idx=None, interpweights=None, order=False, omega=False, vm=None, rnd=False, engine=None, srcrnd=False, **kwargs)

add luminance contributions to image array (updates in place)

Parameters

• img (np.array) – 2D image array to add to (either zeros or with other source)

• vecs (np.array) – vectors corresponding to img pixels shape (N, 3)

• mask (np.array, optional) – indices to img that correspond to vec (in case where whole image is not being updated, such as corners of fisheye)

• skyvec (int float np.array, optional) – source coefficients, shape is (1,) or (srcn,)

• interp (Union[bool, str], optional) –

  • if “precomp”, use index and interpweights

  • if True and engine is None, linearinterpolation

  • if “fastc” and engine: uses content_interp (best after sampling w/o detail)

  • if “highc” and engine: uses content_interp_wedge (best after sampling w/o detail)

  • if “fast”: use interp_fast (pair with sampling w/ detail)

  • if “high”: use interp_wedge (pair with sampling w/ detail)

• idx (np.array, optional) – precomputed query/interpolation result

• interpweights (np.array, optional) – precomputted interpolation weights

• omega (bool) – if true, add value of ray solid angle instead of luminance

• vm (raytraverse.mapper.ViewMapper, optional) –

• rnd (bool, optional) – use random values as contribution (for visualizing data shape)

• engine (raytraverse.renderer.Rtrace, optional) – engine for content aware interpolation

• kwargs (dict, optional) – passed to interpolationn functions

evaluate(skyvec, vm=None, idx=None, srconly=False, blursun=False, includeviews=True)

return rays within view with skyvec applied. this is the analog to add_to_img for metric calculations

Parameters

• skyvec (int float np.array, optional) – source coefficients, shape is (1,) or (srcn,)

• vm (raytraverse.mapper.ViewMapper, optional) –

• idx (np.array, optional) – precomputed query_ball result

• srconly (bool, optional) – only evaluate direct sources (stored in self.srcviews)

• includeviews (bool, optional) – include src views in returned results

Returns

• rays (np.array) – shape (N, 3) rays falling within view

• omega (np.array) – shape (N,) associated solid angles

• lum (np.array) – shape (N,) associated luminances

query_ray(vecs)

return the index and distance of the nearest ray to each of vecs

Parameters

vecs (np.array) – shape (N, 3) normalized vectors to query, could represent image pixels for example.

Returns

• i (np.array) – integer indices of closest ray to each query

• d (np.array) – distance (corresponds to chord length on unit sphere) from query to ray in lightpoint. use translate.chord2theta to convert to angle.

query_ball(vecs, viewangle=180)

return set of rays within a view cone

Parameters

• vecs (np.array) – shape (N, 3) vectors to query.

• viewangle (int float) – opening angle of view cone

Returns

i – if vecs is a single point, a list of vector indices of rays within view cone. if vecs is a set of point an array of lists, one for each vec is returned.

Return type

list np.array

make_image(outf, skyvec, vm=None, res=1024, interp=False, showsample=False)

direct_view(res=512, showsample=False, showweight=True, rnd=False, order=False, srcidx=None, interp=False, omega=False, scalefactor=1, vm=None, fisheye=True, grow=1, srcrnd=False)

create an unweighted summary image of lightpoint

add(lf2, src=None, calcomega=True, write=False, sumsrc=False)

add light points of distinct sources together results in a new lightpoint with srcn=self.srcn+srcn2 and vector size=self.vecsize+vecsize2

Parameters

• lf2 (raytraverse.lightpoint.LightPointKD) –

• src (str, optional) – if None (default), src is “{lf1.src}_{lf2.src}”

• calcomega (bool, optional) – passed to LightPointKD constructor

• write (bool, optional) – passed to LightPointKD constructor

• sumsrc (bool, optional) – if True adds matching source indices together (must be same shape) this assumes that the two lightpoints represent the same source but different components (such as direct/indirect)

Returns

will be subtyped according to self, unless lf2 is needed to preserve data

Return type

raytraverse.lightpoint.LightPointKD

update(vec, lum, omega=None, calcomega=True, write=True, filterviews=False)

add additional rays to lightpoint in place

Parameters

• vec (np.array, optional) – shape (N, >=3) where last three columns are normalized direction vectors of samples.

• lum (np.array, optional) – reshapeable to (N, srcn). sample values for each source corresponding to vec.

• omega (np.array, optional) – provide precomputed omega values, if given, overrides calcomega

• calcomega (bool, optional) – if True (default) calculate solid angle of rays. This is unnecessary if point will be combined before calculating any metrics. setting to False will save some computation time. If False, resets omega to None!

• write (bool, optional) – whether to save updated ray data to disk.

• filterviews (bool, optional) – delete rays near sourceviews

linear_interp(vm, srcvals, destvecs)

static apply_interp(i, srcvals, weights=None)

interp(destvecs, bandwidth=10, rt=None, lum=True, angle=True, dither=False, **kwargs)

SrcViewPoint

class raytraverse.lightpoint.SrcViewPoint(scene, vecs, lum, pt=(0, 0, 0), posidx=0, src='sunview', res=64, srcomega=6.796702357283834e-05)

Bases: object

interface for sun view data

static offset(points, target)

scene

raytraverse.scene.Scene

posidx

index for point

Type

int

pt

point location

Type

np.array

src

source key

Type

str

raster

individual vectors that hit the source (pixels)

Type

np.array

lum

source luminance (average)

Type

float

radius

source radius

Type

float

property vm

add_to_img(img, vecs, mask=None, coefs=1, vm=None)

evaluate(sunval, vm=None, blursun=False)

direct_view(res=80)

CompressedPointKD

class raytraverse.lightpoint.CompressedPointKD(scene, vec=None, lum=None, write=True, src=None, dist=0.0981, lerr=0.01, plotc=False, **kwargs)

Bases: LightPointKD

compressed data needs special methods for making images.

can be initialized either like LightPointKD (but with required omega argument), or if ‘scene’ is a LightPointKD then a compressed output is calculated from the input

Parameters

• scene (BaseScene LightpointKD) –

• src (str, optional) – new name for src passed to LightPointKD constructor

• dist (float, optional) – translate.theta2chord(np.pi/32), primary clustering distance using the birch algorithm, for lossy compression of lf. this is the maximum radius of a cluster, preserving important directional information. clustering acts on ray direction and luminance, with weight of luminance dimension controlled by the lweight parameter.

• lerr (float, optional) – min-max normalized error in luminance grouping.

• plotc (bool, optional) – make directview plot of compressed output showing source vectors

add_to_img(img, vecs, mask=None, skyvec=1, vm=None, **kwargs)

add luminance contributions to image array (updates in place)

Parameters

• img (np.array) – 2D image array to add to (either zeros or with other source)

• vecs (np.array) – vectors corresponding to img pixels shape (N, 3)

• mask (np.array, optional) – indices to img that correspond to vec (in case where whole image is not being updated, such as corners of fisheye)

• skyvec (int float np.array, optional) – source coefficients, shape is (1,) or (srcn,)

• vm (raytraverse.mapper.ViewMapper, optional) –

compress(lp, src=None, dist=0.0981, lerr=0.01)

A lossy compression based on clustering. Rays are clustered using the birch algoritm on a 4D vector (x,y,z,lum) where lum is the sum of contributions from all sources in the LightPoint. In the optional second stage (activated with secondary=True) sources are further grouped through agglomerative cluster using an average linkage. this is to help with source indentification/matching between LightPoints, but can introduce significant errors to computing non energy conserving metrics in cases where the applied sky vectors have large relative differences between adjacent patches (> 1.5:1) or if the variance in peak luminance above the lthreshold parameter is significant. These include cases where nearby transmitting materials is varied (example: a trans upper above a clear lower), or lthreshold is set too low. For this reason, it is better to use single stage compression for metric computation and only do glare source grouping for interpolation between LightPoints.

Parameters

• lp (LightPointKD) –

• src (str, optional) – new name for src passed to LightPointKD constructor

• dist (float, optional) – translate.theta2chord(np.pi/32), primary clustering distance using the birch algorithm, for lossy compression of lf. this is the maximum radius of a cluster, preserving important directional information. clustering acts on ray direction and luminance, with weight of luminance dimension controlled by the lweight parameter.

• lerr (float, optional) – min-max normalized error in luminance grouping.

• plotc (bool, optional) – make directview plot of compressed output showing source vectors

Return type

arguments for initializing a CompressedPointKD