import argparse import glob import os import dedalus.public as d3 import h5py as h5 import numpy as np def populate_empty_file(file): create_dimensions(file) create_base_attributes(file) create_field_types(file) def create_boundary_conditions(file): bcs = file.create_group("boundary_conditions") x = bcs.create_group("x_periodic") x.attrs["associated_dims"] = ["phi"] x.attrs["bc_type"] = "PERIODIC" x.attrs["associated_fields"] = [] x.attrs["sample_varying"] = False x.attrs["time_varying"] = False mask = np.zeros_like(file["dimensions"]["phi"], dtype=bool) mask[0] = True mask[-1] = True xds = x.create_dataset("mask", data=mask, dtype=bool) y = bcs.create_group("y_open") y.attrs["associated_dims"] = ["theta"] y.attrs["bc_type"] = "OPEN" y.attrs["associated_fields"] = [] mask = np.zeros_like(file["dimensions"]["theta"], dtype=bool) mask[0] = True mask[-1] = True yds = y.create_dataset("mask", data=mask, dtype=bool) y.attrs["sample_varying"] = False y.attrs["time_varying"] = False def create_base_attributes(file): file.attrs["dataset_name"] = "dataset" file.attrs["n_spatial_dims"] = 3 file.attrs["simulation_parameters"] = [] file.attrs["grid_type"] = "cartesian" def create_field_types(file): field_types = ["t0_fields", "t1_fields", "t2_fields", "scalars"] for field_type in field_types: gr = file.create_group(field_type) gr.attrs["field_names"] = [] def create_dimensions(file): file.create_group("dimensions") file["dimensions"].attrs["spatial_dims"] = ["phi", "theta"] # file['dimensions'].create_dataset('time', data=np.array([0])) def earthswe_to_well(in_path, out_path): print("Starting file copy!") orig_file = h5.File(in_path, "r") print("orig keys", list(orig_file.keys())) if os.path.exists(out_path): os.remove(out_path) with h5.File(out_path, "w") as new_file: populate_empty_file(new_file) ## First populate the attributes new_file.attrs["dataset_name"] = "planetswe" new_file.attrs["n_spatial_dims"] = 2 new_file.attrs["simulation_parameters"] = [] new_file.attrs["grid_type"] = "equiangular" print("orig_file", orig_file.keys()) new_file.attrs["n_trajectories"] = 1 # orig_file['c'].shape[0] # Make attributes for each simulation parameter # parameter_string = in_path.split('/')[-1][:-5].split('_') # print(parameter_string) new_file["scalars"].attrs["field_names"] = new_file.attrs[ "simulation_parameters" ] # Now let's populate the dimensions new_file["dimensions"].attrs["spatial_dims"] = ["theta", "phi"] time = new_file["dimensions"].create_dataset( "time", data=orig_file["scales"]["sim_time"], dtype="f4" ) time.attrs["sample_varying"] = False # Same coordinates for x and y in this specific data print(orig_file["scales"].keys()) d = new_file["dimensions"].create_dataset( "phi", data=orig_file["scales"][ "phi_hash_7b8ec7cabc40ac4b596a5ef833e9eab019f07d46" ], dtype="f4", ) d.attrs["time_varying"] = False d.attrs["sample_varying"] = False d = new_file["dimensions"].create_dataset( "theta", data=orig_file["scales"][ "theta_hash_47f1a1c5acad69381fef2149e23fb804716211f6" ], dtype="f4", ) d.attrs["time_varying"] = False d.attrs["sample_varying"] = False h, u = dedalus_interpolate( orig_file["tasks"]["h"][:], orig_file["tasks"]["u"][:] ) # T0 Data new_file["t0_fields"].attrs["field_names"] = ["height"] f = new_file["t0_fields"].create_dataset( "height", data=np.transpose(h[np.newaxis, ...], (0, 1, 3, 2)), dtype="f4" ) f.attrs["time_varying"] = True f.attrs["sample_varying"] = True f.attrs["dim_varying"] = [True, True] # T1 Data new_file["t1_fields"].attrs["field_names"] = ["velocity"] f = new_file["t1_fields"].create_dataset( "velocity", data=np.transpose(u[np.newaxis, ...], (0, 1, 4, 3, 2)), dtype="f4", ) f.attrs["time_varying"] = True f.attrs["sample_varying"] = True f.attrs["dim_varying"] = [True, True] # T2 Data new_file["t2_fields"].attrs["field_names"] = [] create_boundary_conditions(new_file) def dedalus_interpolate(h, u): meter = 1 / 6.37122e6 hour = 1 second = hour / 3600 g = 9.80616 * meter / second**2 Nphi = 512 Ntheta = 256 dtype = np.float64 coords = d3.S2Coordinates("phi", "theta") dist = d3.Distributor(coords, dtype=dtype) basis = d3.SphereBasis(coords, (Nphi, Ntheta), radius=1, dealias=1, dtype=dtype) h3 = dist.Field(name="h", bases=basis) u3 = dist.VectorField(coords, name="u", bases=basis) nphi = h.shape[1] ntheta = h.shape[2] u_out = np.zeros(u.shape) h_out = np.zeros(h.shape) delta = np.pi / (ntheta + 1) for j in range(u.shape[0]): if j % 50 == 0: print("row", j) u3["g"] = u[j] h3["g"] = h[j] print("field shape!", u3["g"].shape) for i, pt in enumerate(np.linspace(np.pi - delta / 2, delta / 2, ntheta)): u_interp = d3.Interpolate(u3, "theta", pt).evaluate()["g"] h_interp = d3.Interpolate(h3, "theta", pt).evaluate()["g"] u_out[j, ..., i : i + 1] = u_interp * second / meter h_out[j, ..., i : i + 1] = h_interp / meter return h_out, u_out if __name__ == "__main__": print("HAVE WE EVEN STARTED CODE YET?") parser = argparse.ArgumentParser() parser.add_argument( "--source", default="/mnt/home/polymathic/ceph/the_well/testing_before_adding/earthswe", ) parser.add_argument( "--dest", default="/mnt/home/polymathic/ceph/the_well/datasets/planetswe/data" ) parser.add_argument("--index", default="0") args = parser.parse_args() current_path = args.source write_path = args.dest ic_file = int(args.index) max_ic_train = 32 max_ic_valid = 36 ic_folders = sorted(glob.glob(f"{current_path}/IC*")) target_ic = ic_folders[ic_file] print("picked source", target_ic) # for i, folder in enumerate(ic_folders): ic_num = int(target_ic.split("_")[-1]) if ic_num < max_ic_train: split = "train" elif ic_num < max_ic_valid: split = "valid" else: split = "test" for i in range(10): print(i) for file in glob.glob(f"{target_ic}/*.h5"): file_idx = file.split("_")[-1][:-3] target_path = f"{write_path}/{split}/planetswe_IC{ic_num:02d}_{file_idx}.h5" print(file, target_path) earthswe_to_well(file, target_path)