Cleanup of plots
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d17d25b8e2
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87e2918ffd
GPG Key ID:
9833D3C5A25BD227
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@ -141,4 +141,4 @@ if plt is not None and config.getboolean("out", "plot", fallback=False):
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fig, ax = plt.subplots()
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ax.plot(-x, z, color="k")
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ax.fill_between(-x, z+hstru, z, color="k", alpha=.2)
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plt.show(block=True)
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fig.savefig(out_root.joinpath("bathy.pdf"))
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@ -2,14 +2,8 @@
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#plot=True
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[data]
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root=data
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hires=bathyhires.dat
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bathy=buoyarthabathy.dat
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hstru=Hstru.dat
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poro=Poro.dat
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psize=Psize.dat
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out=out_data
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out_nb=out_data_nb
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out=../data/out
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out_nb=../data/out
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[swash]
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nb=True
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@ -26,3 +20,6 @@ out=out_post
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dt=0.25
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x0=-1250
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t0=180
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[plot]
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out=out_plt
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@ -6,7 +6,6 @@ import pathlib
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import matplotlib.animation as animation
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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parser = argparse.ArgumentParser(description="Animate swash output")
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parser.add_argument("-v", "--verbose", action="count", default=0)
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@ -22,10 +21,6 @@ config.read("config.ini")
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inp = pathlib.Path(config.get("post", "inp"))
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root = pathlib.Path(config.get("swash", "out"))
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bathy = pd.read_hdf(
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pathlib.Path(config.get("data", "out")).joinpath("bathy.h5"), "bathy"
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)
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def data(var):
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return np.load(inp.joinpath(f"{var}.npy"))
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@ -1,93 +0,0 @@
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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 sys
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import numpy as np
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import pandas as pd
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try:
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import matplotlib.pyplot as plt
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except ImportError:
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plt = None
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parser = argparse.ArgumentParser(description="Pre-process bathymetry")
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parser.add_argument("-v", "--verbose", action="count", default=0)
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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 bathymetry pre-processing")
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config = configparser.ConfigParser()
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config.read("config.ini")
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root = pathlib.Path(config.get("data", "root"))
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log.info(f"Reading input data from '{root}'")
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bathy_hires = np.loadtxt(root.joinpath(config.get("data", "hires")))
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bathy_lores = np.loadtxt(root.joinpath(config.get("data", "bathy")))
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hstru = np.loadtxt(root.joinpath(config.get("data", "hstru")))
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poro = np.loadtxt(root.joinpath(config.get("data", "poro")))
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psize = np.loadtxt(root.joinpath(config.get("data", "psize")))
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log.info("Generating grid")
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x_hires = -np.arange(0, 0.5 * bathy_hires.size, 0.5)[::-1]
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x_lores = -np.arange(0, 1 * bathy_lores.size, 1)[::-1]
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x_hstru = -np.arange(0, 0.5 * hstru.size, 0.5)[::-1]
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log.info("Generating output data")
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bathy_hires_pd = pd.Series(bathy_hires.copy(), index=x_hires)
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bathy_lores_pd = pd.Series(bathy_lores.copy(), index=x_lores)
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bathy = pd.DataFrame(
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index=bathy_lores_pd.index.union(bathy_hires_pd.index),
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columns=("z", "hstru", "poro", "psize"),
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data=0,
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)
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bathy.z[bathy_lores_pd.index] = bathy_lores_pd
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bathy.z[bathy_hires_pd.index] = bathy_hires_pd
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bathy.loc[x_hstru, ("hstru", "poro", "psize")] = np.array(
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(hstru, poro, psize)
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).T
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bathy = bathy.reindex(bathy_lores_pd.index)
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log.debug(f"Bathymetry:\n{bathy}")
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log.info(
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f"xmin: {bathy.index.min()}, "
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f"xmax: {bathy.index.max()}, "
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f"n: {bathy.index.size}"
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)
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if config.has_option("data", "out"):
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out = pathlib.Path(config.get("data", "out"))
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log.info(f"Writing output data to '{out}'")
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out.mkdir(exist_ok=True)
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np.savetxt(out.joinpath("bathy.dat"), bathy.z, newline=" ")
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np.savetxt(out.joinpath("hstru.dat"), bathy.hstru, newline=" ")
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np.savetxt(out.joinpath("poro.dat"), bathy.poro, newline=" ")
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np.savetxt(out.joinpath("psize.dat"), bathy.psize, newline=" ")
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bathy.to_hdf(out.joinpath("bathy.h5"), "bathy", mode="w")
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if config.getboolean("proc", "plot", fallback=False):
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if plt is None:
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log.error("Could not import PyPlot")
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sys.exit(1)
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log.info("Plotting data")
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fig, ax = plt.subplots()
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ax.plot(x_hires, bathy_hires, label="High-res")
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ax.plot(x_lores, bathy_lores, label="Low-res")
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ax.plot(bathy.index, bathy.z, ls="-.", c="k", label="Combined")
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ax.plot(bathy.index, bathy.z + bathy.hstru, label="Hstru")
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ax.grid()
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ax.legend()
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plt.show(block=True)
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log.info("Processing finished")
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@ -1,94 +0,0 @@
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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 sys
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import numpy as np
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import pandas as pd
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try:
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import matplotlib.pyplot as plt
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except ImportError:
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plt = None
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parser = argparse.ArgumentParser(description="Pre-process bathymetry")
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parser.add_argument("-v", "--verbose", action="count", default=0)
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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 bathymetry pre-processing")
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config = configparser.ConfigParser()
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config.read("config.ini")
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root = pathlib.Path(config.get("data", "root"))
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log.info(f"Reading input data from '{root}'")
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bathy_hires = np.loadtxt(root.joinpath(config.get("data", "hires")))
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bathy_lores = np.loadtxt(root.joinpath(config.get("data", "bathy")))
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hstru = np.loadtxt(root.joinpath(config.get("data", "hstru")))
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poro = np.loadtxt(root.joinpath(config.get("data", "poro")))
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psize = np.loadtxt(root.joinpath(config.get("data", "psize")))
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log.info("Generating grid")
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x_hires = -np.arange(0, 0.5 * bathy_hires.size, 0.5)[::-1]
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x_lores = -np.arange(0, 1 * bathy_lores.size, 1)[::-1]
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x_hstru = -np.arange(0, 0.5 * hstru.size, 0.5)[::-1]
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log.info("Generating output data")
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bathy_hires_pd = pd.Series(bathy_hires.copy(), index=x_hires)
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bathy_lores_pd = pd.Series(bathy_lores.copy(), index=x_lores)
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bathy = pd.DataFrame(
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index=bathy_lores_pd.index.union(bathy_hires_pd.index),
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columns=("z", "hstru", "poro", "psize"),
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data=0,
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)
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bathy.z[bathy_lores_pd.index] = bathy_lores_pd
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bathy.z[bathy_hires_pd.index] = bathy_hires_pd
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bathy.z = np.minimum(bathy.z, -15)
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# bathy.loc[x_hstru, ("hstru", "poro", "psize")] = np.array(
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# (hstru, poro, psize)
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# ).T
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bathy = bathy.reindex(bathy_lores_pd.index)
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log.debug(f"Bathymetry:\n{bathy}")
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log.info(
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f"xmin: {bathy.index.min()}, "
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f"xmax: {bathy.index.max()}, "
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f"n: {bathy.index.size}"
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)
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if config.has_option("data", "out_nb"):
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out = pathlib.Path(config.get("data", "out_nb"))
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log.info(f"Writing output data to '{out}'")
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out.mkdir(exist_ok=True)
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np.savetxt(out.joinpath("bathy.dat"), bathy.z, newline=" ")
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np.savetxt(out.joinpath("hstru.dat"), bathy.hstru, newline=" ")
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np.savetxt(out.joinpath("poro.dat"), bathy.poro, newline=" ")
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np.savetxt(out.joinpath("psize.dat"), bathy.psize, newline=" ")
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bathy.to_hdf(out.joinpath("bathy.h5"), "bathy", mode="w")
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if config.getboolean("proc", "plot", fallback=False):
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if plt is None:
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log.error("Could not import PyPlot")
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sys.exit(1)
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log.info("Plotting data")
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fig, ax = plt.subplots()
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ax.plot(x_hires, bathy_hires, label="High-res")
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ax.plot(x_lores, bathy_lores, label="Low-res")
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ax.plot(bathy.index, bathy.z, ls="-.", c="k", label="Combined")
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ax.plot(bathy.index, bathy.z + bathy.hstru, label="Hstru")
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ax.grid()
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ax.legend()
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plt.show(block=True)
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log.info("Processing finished")
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@ -6,7 +6,6 @@ import pathlib
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import matplotlib.animation as animation
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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parser = argparse.ArgumentParser(description="Animate swash output")
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parser.add_argument("-v", "--verbose", action="count", default=0)
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@ -21,10 +20,7 @@ config.read("config.ini")
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inp = pathlib.Path(config.get("post", "inp"))
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root = pathlib.Path(config.get("swash", "out"))
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bathy = pd.read_hdf(
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pathlib.Path(config.get("data", "out")).joinpath("bathy.h5"), "bathy"
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)
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out = pathlib.Path(config.get("plot", "out"))
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def data(var):
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@ -89,4 +85,4 @@ ani = animation.FuncAnimation(
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fig, animate, frames=wl[:, 0].size, interval=20, blit=True
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)
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plt.show(block=True)
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ani.save(out.joinpath("layers.mp4", codec="h265"))
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@ -164,6 +164,5 @@ out.mkdir(parents=True, exist_ok=True)
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fig.savefig(out.joinpath("t.png"))
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fig_r.savefig(out.joinpath("R.png"))
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fig_x.savefig(out.joinpath("x.png"))
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plt.show(block=True)
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log.info("Finished post-processing")
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