import numpy import drjit as dr import mitsuba as mi mi.set_variant("cuda_ad_rgb") import matplotlib.pyplot as plt import sys from PDE2D.Coefficient import * from PDE2D.utils import * from PDE2D.BoundaryShape import * from PDE2D.Solver import * from PDE2D import GreenSampling, Split, PATH import argparse import os root_directory = os.path.join(PATH, "output2D", "finite_differences", "discrete-circle", "normalder") def create_path(path): if not os.path.exists(path): os.makedirs(path) parser = argparse.ArgumentParser(description='''FD-computation sphere''') parser.add_argument("--res", default = 256, type = int) parser.add_argument('--spp', default = 20, type=int) parser.add_argument("--x", default = 0.2, type = float) parser.add_argument("--y", default = 0.2, type = float) parser.add_argument("--radius", default = 0.2, type = float) parser.add_argument("--seed", default = 0, type = int) parser.add_argument("--iter", default = 32, type = int) parser.add_argument("--injection", default = "skip3", type = str) parser.add_argument("--distance", default = 0.01, type = float) args = parser.parse_args() origin = [args.x, args.y] radius = args.radius distance = args.distance spp = 2**args.spp in_boundary = CircleShape(origin, radius) out_boundary = CircleWithElectrodes(injection_set = args.injection, is_delta = True) shape = BoundaryWithDirichlets(out_boundary, [in_boundary], dirichlet_values = [[0]]) data_holder = DataHolder(shape) wos = WostConstant(data_holder) num_conf = out_boundary.num_confs conf_numbers = [dr.opaque(UInt32, i, shape = (1)) for i in range(num_conf)] filename = f"{args.injection}-{args.x}-{args.y}-{radius}" path = os.path.join(root_directory, filename) create_path(path) for iter in range(args.iter): print(f"Iteration {iter} finished.") seed_iter = iter + args.seed wos.change_seed(seed_iter) #dr.set_log_level(3) result, _ = wos.create_normal_derivative(args.res, spp, distance = distance, conf_numbers=conf_numbers) #dr.set_log_level(0) np.save(os.path.join(path, f"res{args.res}-d{distance}-{seed_iter}"), result.numpy())