def test_rectangleMesh(): plane = pgf.plane(pgf.var_vec3((0., 0., 0.)), pgf.var_vec3((1., 1., 0.))) box = pgf.box2(pgf.var_vec2((0., 0.)), pgf.var_vec2((15., 12.))) edgeLn = pgf.var_float(1.) rect = pgf.rectangleMesh(plane, box, edgeLn) area = pgf.area(rect) nfaces = pgf.numFaces(rect) nverts = pgf.numVertices(rect) assert 360 == pgf.read(nfaces) assert 208 == pgf.read(nverts) assert tu.equalf(180., pgf.read(area))
def test_distance3(): p1 = pgf.var_vec3() p2 = pgf.var_vec3() dist = pgf.distance(p1, p2) for _ in range(20): val1 = (random.uniform(1.2, 12.5), random.uniform( 2.5, 15.6), random.uniform(22.3, 55.6)) val2 = (random.uniform(1.26, 22.5), random.uniform( 1.5, 13.9), random.uniform(23.5, 63.7)) dval = math.sqrt(math.pow(val1[0] - val2[0], 2.) + math.pow( val1[1] - val2[1], 2.) + math.pow(val1[2] - val2[2], 2.)) pgf.assign(p1, val1) pgf.assign(p2, val2) assert tu.equalf(pgf.read(dist), dval)
def test_closestPointsOnMesh(): mesh = pgf.scale(loadSmallBunny(), pgf.var_float(10.)) inpts = pgf.var_vec3([ (0.359824538230896, -0.012389957904815674, 0.3581507205963135), (-0.3318827152252197, 0.1699751615524292, 0.7063822150230408), (0.27124643325805664, -0.14796850085258484, 0.5440048575401306), (0.2950490713119507, 0.0309564471244812, 1.5690069198608398), (0.470700740814209, 0.559279203414917, 0.5738930106163025), (-0.6372849941253662, 0.5158957242965698, 0.9492948055267334), (-0.42367517948150635, 0.17821109294891357, 0.5325688719749451), (0.24817490577697754, 0.27643465995788574, 0.5003229975700378), (-0.5128110647201538, -0.4166657030582428, 1.868307113647461), (-0.08426868915557861, 0.14360648393630981, 0.6685295104980469) ]) outpts = pgf.closestPoints(mesh, inpts) expected = [ (0.35241958498954773, -0.022721359506249428, 0.3823484480381012), (-0.3473210334777832, 0.18098655343055725, 0.6997533440589905), (0.22252899408340454, -0.13979701697826385, 0.36583301424980164), (0.1671879142522812, -0.029879290610551834, 1.274683952331543), (0.22475071251392365, 0.2590671181678772, 0.5857457518577576), (-0.5479510426521301, 0.21973726153373718, 0.9220386743545532), (-0.423895001411438, 0.11360426992177963, 0.5336558818817139), (0.21963083744049072, 0.23689928650856018, 0.5136839151382446), (-0.6122115254402161, -0.3117043375968933, 1.5369797945022583), (-0.03959565982222557, 0.34772586822509766, 0.666935384273529) ] assert tu.equalf(expected, pgf.read(outpts))
def test_cachedOffsetDataRegression(): # This tests for a regression (lack of) happened while working on PR # 53. pt = pgf.var_vec3((0., 0., 0.)) norm = pgf.var_vec3((0., 0., 1.)) plane = pgf.plane(pt, norm) minpt = pgf.var_vec3((-.5, -.5, 0.)) maxpt = pgf.var_vec3((.5, .5, 0.)) box2 = pgf.box2(pgf.var_vec2((-.5, -.5)), pgf.var_vec2((.5, .5))) box3 = pgf.box3(minpt, maxpt) npts = pgf.var_int(4) cloud = pgf.randomPointsInBox(box3, npts) edgeLen = pgf.var_float(1) rect = pgf.rectangleMesh(plane, box2, edgeLen) distances = pgf.distance(pgf.graft(pgf.vertices(rect)), cloud) pdists = pgf.read(pgf.flatten(distances)) assert len(pdists) == 16
import pygalfunc as pgf import pygalview as pgv minpt = pgf.var_vec3((-1., -1., -1.)) maxpt = pgf.var_vec3((1., 1., 1.)) box = pgf.box3(minpt, maxpt) npts = pgv.slideri32("Point count", 10, 1000, 100) cloud = pgf.randomPointsInBox(box, npts) hull = pgf.convexHullFromPoints(cloud) pgv.show("Convex Hull", hull) pgv.show("Points", cloud)
import pygalfunc as pgf import pygalview as pgv pt = pgf.var_vec3((0., 0., 0.)) norm = pgf.var_vec3((0., 0., 1.)) plane = pgf.plane(pt, norm) minpt = pgf.var_vec3((-.5, -.5, 0.)) maxpt = pgf.var_vec3((.5, .5, 0.)) box2 = pgf.box2(pgf.var_vec2((-.5, -.5)), pgf.var_vec2((.5, .5))) box3 = pgf.box3(minpt, maxpt) npts = pgv.slideri32("Point count", 5, 50, 25) cloud = pgf.randomPointsInBox(box3, npts) edgeLen = pgf.var_float(.01) rect = pgf.rectangleMesh(plane, box2, edgeLen) distances = pgf.distance(pgf.graft(pgf.vertices(rect)), cloud) sortedDists = pgf.sort(distances, distances) maxDist = pgf.listItem(sortedDists, pgf.sub(pgf.listLength(sortedDists), pgf.var_int(1))) scheme = pgf.var_vec3([ (0., 0., 1.), (0., 1., 0.), (1., 1., 0.), (1., 0., 0.) ]) colors = pgf.mapValueToColor(maxDist, pgf.var_vec2((.5, 1.2)), scheme) colored = pgf.meshWithVertexColors(rect, colors) circ, *_ = pgf.boundingCircle(cloud)
import pygalfunc as pgf import pygalview as pgv POINTS = [ (0, 0, 0), (1, 0, 0), (1, 1, 0), (-.3, 1, 0), (0, -1, 0), ] pts = pgf.var_vec3(POINTS) nums = pgf.toString(pgf.series(pgf.var_int(0), pgf.var_int(1), pgf.listLength(pts))) idxPt = pgf.listItem(pts, pgv.slideri32("Index", 0, len(POINTS) - 1, 0)) circ, *_ = pgf.boundingCircle(pts) pgv.show("indices", pgv.tags(nums, pts)) pgv.show("circle", circ) pgv.show("points", pts) pgv.print("Point at index", idxPt)