43 lines
1.1 KiB
Python
43 lines
1.1 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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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(level=max((10, 20 - 10 * args.verbose)))
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log = logging.getLogger("bathy")
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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"))
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out_root = pathlib.Path(config.get("out", "root"))
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inp_spec = inp_root.joinpath(config.get("inp", "raw_spec"))
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out_spec = out_root.joinpath("spec.dat")
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inp = np.loadtxt(
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inp_spec,
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dtype=[("f", float), ("S", float)],
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delimiter=",",
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skiprows=12,
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usecols=(0, 6),
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max_rows=64,
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)
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with out_spec.open("w") as out:
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out.write("SPEC1D\n")
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np.savetxt(out, inp)
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df = np.diff(inp['f']).min()
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log.info(f"Minimum frequency delta: {df:.4f}Hz")
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log.info(f"Maximum modelled time: {1/df:.0f}s")
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