https://github.com/pierre-guillou/pdiags_bench
Tip revision: b422e92c24a1485aa93e8a70474973787bd0eee5 authored by Pierre Guillou on 05 March 2021, 13:57:05 UTC
WiP
WiP
Tip revision: b422e92
test_random.py
import time
from paraview import simple
import compare_diags
import gen_random
import main as compute_diags
def generate_explicit(inp, out, rs):
# read random.vti
rand = simple.XMLImageDataReader(FileName=inp)
# compute order field
arrprec = simple.TTKArrayPreconditioning(Input=rand)
arrprec.PointDataArrays = ["RandomPointScalars"]
# trash input scalar field, save order field
pa = simple.PassArrays(Input=arrprec)
pa.PointDataArrays = ["RandomPointScalars_Order"]
# randomize scalar field?
ir = simple.TTKIdentifierRandomizer(Input=pa)
ir.ScalarField = ["POINTS", "RandomPointScalars_Order"]
ir.RandomSeed = rs
# tetrahedralize grid
tetrah = simple.Tetrahedralize(Input=ir)
# vtkUnstructuredGrid (TTK)
simple.SaveData(out + ".vtu", proxy=tetrah)
# Dipha Explicit Complex (Dipha)
simple.SaveData(out + ".dipha", proxy=tetrah)
def main():
fname = "random_order_sfnorm_expl"
for i in range(0, 8):
print(i)
gen_random.main(4, "rand")
ds = "datasets/" + fname
generate_explicit("random.vti", ds, i)
return
tm = dict()
tm[fname.split("/")[-1]] = dict()
compute_diags.compute_ttk(ds + ".vtu", "ttkPersistenceDiagramCmd", tm)
compute_diags.compute_dipha(ds + ".dipha", "build_dipha/dipha", tm)
diag = "diagrams/" + fname
compare_diags.main(diag + ".vtu", diag + ".dipha", True)
time.sleep(2)
if __name__ == "__main__":
main()