internship/data/processing/ts.py

import argparse
import configparser
import logging
import pathlib

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
import numpy as np

parser = argparse.ArgumentParser(description="Pre-process time-series")
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("bathy")

log.info("Starting time-series pre-processing")
config = configparser.ConfigParser()
config.read(args.config)

inp_root = pathlib.Path(config.get("inp", "root"))
out_root = pathlib.Path(config.get("out", "root"))

out_ts = out_root.joinpath("ts.dat")

raw_ts = []
for tsi in config.get("inp", "raw_ts").split(","):
    raw_ts.append(
        np.loadtxt(
            inp_root.joinpath(tsi),
            dtype=[("state", int), ("z", float), ("y", float), ("x", float)],
            delimiter=",",
            max_rows=2304,
        )
    )
n = len(raw_ts)
raw_ts = np.concatenate(raw_ts)
log.debug(f"{raw_ts=}")

if (errs := np.count_nonzero(raw_ts["state"])) != 0:
    log.warning(f"{errs} transmission errors!")
    log.debug(f"{dict(zip(*np.unique(raw_ts['state'], return_counts=True)))}")

t = np.linspace(0, 30 * 60 * n, 2304 * n + 1)[:-1]
log.debug(f"{t=}")

log.info(f"Saving timeseries to '{out_ts}'")
np.savetxt(out_ts, np.stack((t, raw_ts["z"] / 100), axis=1))

fig, ax = plt.subplots(figsize=(8 / 2.54, 2 / 3 * 10 / 2.54), constrained_layout=True)
tp = np.datetime64("2017-02-28T17:00:00") + t.astype(np.timedelta64)[-(t.size // 3) :]
ax.plot(
    tp,
    raw_ts["z"][-(t.size // 3) :] * 1e-2,
    color="k",
    lw=1,
)
ax.axvline(
    np.datetime64("2017-02-28T17:00:00") + np.timedelta64(23 * 60 + 8),
    color="k",
    alpha=0.1,
    lw=20,
)
ax.autoscale(True, "x", True)
ax.set(xlabel="t (s)", ylabel="z (m)")
yabs_max = abs(max(ax.get_ylim(), key=abs))
ax.set(ylim=(-10, 10))
ax.set(
    xticks=(
        np.datetime64("2017-02-28T17:20:00"),
        np.datetime64("2017-02-28T17:25:00"),
        np.datetime64("2017-02-28T17:30:00"),
    ),
    xticklabels=(
        "17:20",
        "17:25",
        "17:30",
    ),
)
ax.yaxis.set_minor_locator(MultipleLocator(1))
ax.grid(color="k", alpha=0.2)
fig.savefig(out_root.joinpath("ts.pdf"))
fig.savefig(out_root.joinpath("ts.jpg"), dpi=200)