62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
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import argparse
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import configparser
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import logging
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import pathlib
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import matplotlib.pyplot as plt
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import numpy as np
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import scipy.signal as sgl
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parser = argparse.ArgumentParser(description="Pre-process time-series")
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parser.add_argument("-v", "--verbose", action="count", default=0)
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parser.add_argument("-c", "--config", default="config.ini")
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args = parser.parse_args()
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logging.basicConfig()
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log = logging.getLogger("bathy")
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log.setLevel(max((10, 20 - 10 * args.verbose)))
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log.info("Starting time-series pre-processing")
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config = configparser.ConfigParser()
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config.read(args.config)
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inp_root = pathlib.Path(config.get("inp", "root"), "cerema/raw")
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out_root = pathlib.Path(config.get("out", "root"))
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raw_ts = []
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for tsi in sorted(inp_root.glob("2017022817*.raw")):
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#for tsi in sorted(inp_root.glob("*.raw")):
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raw_ts.append(
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np.loadtxt(
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tsi,
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dtype=[("state", int), ("z", float), ("y", float), ("x", float)],
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delimiter=",",
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max_rows=2304,
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)
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)
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log.debug(f"Loading <{tsi}>")
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n = len(raw_ts)
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raw_ts = np.concatenate(raw_ts)
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log.debug(f"{raw_ts=}")
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# t = np.linspace(0, 30 * 60 * n * 1e3, 2304 * n + 1)[:-1].astype("timedelta64[ms]") + np.datetime64("2017-02-28T00:00")
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t = np.linspace(0, 30 * 60 * n, 2304 * n, endpoint=False)
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if (errs := np.count_nonzero(raw_ts["state"])) != 0:
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log.warning(f"{errs} transmission errors!")
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log.debug(f"{dict(zip(*np.unique(raw_ts['state'], return_counts=True)))}")
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# log.debug(f"{t[raw_ts['state'] != 0]}")
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z = raw_ts["z"]
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# z = np.cos(2 * np.pi * 7 * t) + sgl.gausspulse(t - 0.4, fc=2)
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M = sgl.cwt(z, sgl.morlet, np.arange(1, 30 / (30 * 60 / 2304)))
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print(M)
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fig, ax = plt.subplots()
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c = ax.imshow(M, aspect="auto", cmap="spring", vmin=0)
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ax2 = ax.twinx()
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ax2.plot(z, c="k")
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fig.colorbar(c)
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plt.show()
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