def test_sort():
random.seed(42)
rvals = pgf.var_int()
rkeys = pgf.var_int()
rsorted = pgf.sort(rvals, rkeys)
lvals = []
lkeys = []
for _ in range(10):
nItems = random.randint(75, 155)
vals = list(range(nItems))
keys = list(range(nItems))
random.shuffle(vals)
random.shuffle(keys)
lvals.append(vals)
lkeys.append(keys)
expected = [
x for x, _ in sorted(zip(vals, keys), key=lambda pair: pair[1])
]
pgf.assign(rvals, vals)
pgf.assign(rkeys, keys)
assert tu.equal(expected, pgf.read(rsorted))
# Test the same with tree combinatorics.
expected = [[x for x, _ in sorted(zip(v, k), key=lambda pair: pair[1])]
for v, k in zip(lvals, lkeys)]
pgf.assign(rvals, lvals)
pgf.assign(rkeys, lkeys)
assert tu.equal(expected, pgf.read(rsorted))
def test_heterogenousTrees():
random.seed(42)
vals1 = [[2], [3]]
vals2 = [4, 5]
expected = [[8, 10], [12, 15]]
rvals1 = pgf.var_int(vals1)
rvals2 = pgf.var_int(vals2)
prod = pgf.mul(rvals1, rvals2)
assert tu.equal(expected, pgf.read(prod))
def test_itemListMapping():
random.seed(42)
singleval = 42
single = pgf.var_int(singleval)
lst = pgf.var_int()
out = pgf.add(single, lst)
for _ in range(10):
vals = list(range(12))
random.shuffle(vals)
expected = [singleval + v for v in vals]
pgf.assign(lst, vals)
assert tu.equal(expected, pgf.read(out))
def test_seriesInt():
random.seed(42)
valrange = (23, 256)
steprange = (2, 9)
valstart = random.randint(valrange[0], valrange[1])
valstep = random.randint(steprange[0], steprange[1])
valcount = random.randint(valrange[0], valrange[1])
valstop = valstart + valstep * valcount
start = pgf.var_int(valstart)
step = pgf.var_int(valstep)
count = pgf.var_int(valcount)
series = pgf.series(start, step, count)
assert tu.equal(range(valstart, valstop, valstep), pgf.read(series))
def test_combinations():
random.seed(42)
valrange = (23, 345)
rvals = pgf.var_int()
rnumc = pgf.var_int()
rcombs = pgf.combinations(rvals, rnumc)
for _ in range(5):
nItems = random.randint(23, 29)
numc = random.randint(3, 5)
vals = [
random.randint(valrange[0], valrange[1]) for _ in range(nItems)
]
combs = list(itertools.combinations(vals, numc))
pgf.assign(rvals, vals)
pgf.assign(rnumc, numc)
assert tu.equal(combs, pgf.read(rcombs))
def repeatGenericTest(val, pgvarfn, comparefn):
random.seed(42)
count = random.randint(23, 345)
vals = [val for _ in range(count)]
rval = pgvarfn(val)
result = pgf.repeat(rval, pgf.var_int(count))
assert comparefn(vals, pgf.read(result))
def test_listSumInt():
random.seed(42)
valrange = (23, 345)
vals = [random.randint(valrange[0], valrange[1]) for _ in range(25)]
lst = pgf.var_int(vals)
result = pgf.listSum(lst)
assert tu.equal(sum(vals), pgf.read(result))
def test_treeInputs():
random.seed(42)
vals = [[random.randint(23, 345) for _ in range(10)] for _ in range(10)]
rvals = pgf.var_int()
rsum = pgf.treeSum(rvals)
expected = sum([sum(v) for v in vals])
pgf.assign(rvals, vals)
assert tu.equal(expected, pgf.read(rsum))
def listItemGenericTest(vals, pgvarfn, comparefn):
rvals = pgvarfn(vals)
rindex = pgf.var_int()
result = pgf.listItem(rvals, rindex)
random.seed(42)
for _ in range(25):
index = random.randint(0, len(vals) - 1)
pgf.assign(rindex, index)
assert comparefn(vals[index], pgf.read(result))
def test_listLength():
random.seed(42)
valrange = (23, 345)
rvals = pgf.var_int()
rstart = pgf.var_int()
rstop = pgf.var_int()
slist = pgf.subList(rvals, rstart, rstop)
for _ in range(20):
vals = [random.randint(valrange[0], valrange[1]) for _ in range(25)]
irange = (random.randint(0,
len(vals) - 1),
random.randint(0,
len(vals) - 1))
irange = sorted(irange)
expected = vals[irange[0]:irange[1]]
# print(len(vals), irange[0], irange[1])
pgf.assign(rvals, vals)
pgf.assign(rstart, irange[0])
pgf.assign(rstop, irange[1])
tu.assertEqual(expected, pgf.read(slist))
def binaryIntOpTest(expFn, pgfn, minval=2, maxval=124):
random.seed(42)
a = pgf.var_int()
b = pgf.var_int()
r = pgfn(a, b)
for _ in range(20):
va = random.randint(minval, maxval)
vb = random.randint(minval, maxval)
expected = expFn(va, vb)
pgf.assign(a, va)
pgf.assign(b, vb)
assert tu.equal(expected, pgf.read(r))
vas = [random.randint(minval, maxval) for _ in range(20)]
vbs = [random.randint(minval, maxval) for _ in range(20)]
expectedVals = [expFn(va, vb) for va, vb in zip(vas, vbs)]
pgf.assign(a, vas)
pgf.assign(b, vbs)
assert tu.equal(expectedVals, pgf.read(r))
def test_flatten():
random.seed(42)
intree = pgf.var_int()
outtree = pgf.flatten(intree)
for _ in range(5):
vals = [[random.randint(23, 234)] for __ in range(10)]
pgf.assign(intree, vals)
expected = [item for subl in vals for item in subl]
assert tu.equal(expected, pgf.read(outtree))
vals = [[[random.randint(23, 234) for __ in range(5)]
for ___ in range(5)] for _____ in range(5)]
pgf.assign(intree, vals)
expected = [item for l0 in vals for l1 in l0 for item in l1]
assert tu.equal(expected, pgf.read(outtree))
def test_graft():
random.seed(42)
intree = pgf.var_int()
out = pgf.graft(intree)
for _ in range(5):
vals = [random.randint(23, 345) for __ in range(10)]
expected = [[v] for v in vals]
pgf.assign(intree, vals)
assert tu.equal(expected, pgf.read(out))
for _ in range(5):
vals = [[random.randint(23, 345) for __ in range(5)]
for ___ in range(5)]
expected = [[[v] for v in vl] for vl in vals]
pgf.assign(intree, vals)
assert tu.equal(expected, pgf.read(out))
def test_seriesFloat():
random.seed(42)
valrange = (22.345, 223.66)
steprange = (1.778, 9.56)
valstart = random.uniform(valrange[0], valrange[1])
valstep = random.uniform(steprange[0], steprange[1])
valcount = random.randint(25, 98)
valstop = valstart + valstep * valcount
start = pgf.var_float(valstart)
step = pgf.var_float(valstep)
count = pgf.var_int(valcount)
series = pgf.series(start, step, count)
expected = [(valstart + i * valstep) for i in range(valcount)]
tu.assertEqualf(expected, pgf.read(series), 1e-3)
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
def test_dispatch():
random.seed(42)
valrange = (23, 345)
rvals = pgf.var_int()
rpattern = pgf.var_bool()
rtvals, rfvals = pgf.dispatch(rvals, rpattern)
for _ in range(20):
nItems = 25
vals = [
random.randint(valrange[0], valrange[1]) for _ in range(nItems)
]
pattern = [
random.randint(valrange[0], valrange[1]) % 2 == 0
for _ in range(nItems)
]
tvals = [v for v, p in zip(vals, pattern) if p]
fvals = [v for v, p in zip(vals, pattern) if not p]
pgf.assign(rvals, vals)
pgf.assign(rpattern, pattern)
assert tu.equal(tvals, pgf.read(rtvals))
assert tu.equal(fvals, pgf.read(rfvals))
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)
# pgv.show("rectangle", rect)
pgv.show("cloud", cloud)
pgv.show("colored", colored)
pgv.show("circle", circ)
pgv.runCommands("2d")
(1, 1, 0),
(-.3, 1, 0),
(0, -1, 0),
]
GLYPHDATA = [
"/home/rnjth94/works/YouTube/GAL_BoundingCircle/receiverDishGlyph.png",
"/home/rnjth94/works/YouTube/GAL_BoundingCircle/transmitterGlyph.png"
]
def initGlyphs():
return pgv.loadGlyphs(GLYPHDATA)
if __name__ == "__main__":
glyphs = initGlyphs()
pts = pgf.var_vec3(POINTS)
cloudGlyphs = pgf.var_int([glyphs[0] for _ in range(len(POINTS))])
idxPt = pgf.listItem(pts, pgv.slideri32("Index", 0, len(POINTS) - 1, 0))
circ, center, radius = pgf.boundingCircle(pts)
center3 = pgf.vec3FromVec2(center)
centerGlyph = pgf.var_int(glyphs[1])
pgv.show("glyph1", pgv.glyphs(cloudGlyphs, pts))
pgv.show("glyph2", pgv.glyphs(centerGlyph, center3))
pgv.show("circle", circ)
pgv.show("points", pts)
pgv.show("center", center3)
pgv.print("Point at index", idxPt)
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)
# pgv.show("rectangle", rect)
pgv.show("cloud", cloud)
pgv.show("colored", colored)
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)