internship/swash/processing/mat_npz.py

import argparse
import configparser
from datetime import datetime, time
import logging
import pathlib
import re
from multiprocessing.pool import ThreadPool

import numpy as np
import scipy.io as sio

parser = argparse.ArgumentParser(description="Convert swash output to numpy")
parser.add_argument("-v", "--verbose", action="count", default=0)
parser.add_argument("-c", "--config", default="config.ini")
args = parser.parse_args()

logging.basicConfig(level=max((10, 20 - 10 * args.verbose)))
log = logging.getLogger("sws_npz")

log.info("Starting sws -> npz converter")
config = configparser.ConfigParser()
config.read(args.config)

sws_out = pathlib.Path(config.get("swash", "out"))
inp = pathlib.Path(config.get("post", "inp"))
inp.mkdir(parents=True, exist_ok=True)

log.info(f"Reading swash output from '{sws_out}'")
raw_tsec = sio.loadmat(sws_out.joinpath("tsec.mat"))
i = np.fromiter(
    (k[5:] for k in raw_tsec.keys() if re.compile(r"^Tsec_").match(k)), dtype="U10"
)
t = np.fromiter((raw_tsec[f"Tsec_{k}"][0, 0] * 10**3 for k in i), dtype=np.uintc)
np.save(inp.joinpath("t"), t)
del raw_tsec
raw_xp = sio.loadmat(sws_out.joinpath("xp.mat"), variable_names="Xp")
x = raw_xp["Xp"][0]
np.save(inp.joinpath("x"), x)
del raw_xp

raw_botl = sio.loadmat(sws_out.joinpath("botl.mat"), variable_names="Botlev")
botl = raw_botl["Botlev"][0]
np.save(inp.joinpath("botl"), botl)
del raw_botl, botl

raw_watl = sio.loadmat(sws_out.joinpath("watl.mat"))
watl = np.asarray(
    [raw_watl[i0][0] for i0 in np.char.add("Watlev_", i)], dtype=np.single
)
np.save(inp.joinpath("watl"), watl)
del raw_watl, watl

raw_vel = sio.loadmat(sws_out.joinpath("vel.mat"))
vel_x = np.asarray([raw_vel[i0][0] for i0 in np.char.add("vel_x_", i)], dtype=np.single)
np.save(inp.joinpath("vel_x"), vel_x)
del raw_vel, vel_x

raw_zk = sio.loadmat(sws_out.joinpath("zk.mat"))
n_zk = (len(raw_zk.keys()) - 3) // t.size
zk = np.asarray(
    [
        raw_zk[i0][0]
        for i0 in np.char.add(
            np.char.replace("zki_", "i", np.arange(n_zk).astype("U1"), count=1)[
                None, :
            ],
            i[:, None],
        ).reshape(-1)
    ],
    dtype=np.single,
).reshape((t.size, n_zk, x.size))
np.save(inp.joinpath("zk"), zk)
del raw_zk, zk