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import os
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import re
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import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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sources = [
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{
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'source': 'This script',
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'csv_name': 'levels.csv',
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'tz': 'Etc/GMT-10'
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},
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{
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'source': 'MHL',
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'csv_name': 'OceanTide-213470.Level.csv',
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'tz': 'Etc/GMT-10'
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},
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{
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'source': 'BOM',
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'csv_name': 'NSW_TP007.csv',
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'tz': 'Australia/Sydney'
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},
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]
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fig, ax = plt.subplots(1, 1, figsize=(7, 4))
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for s in sources:
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df = pd.read_csv(s['csv_name'], index_col=0, parse_dates=True)
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try:
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df = df.tz_localize(s['tz'])
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except TypeError:
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pass
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ax.plot(df.iloc[:, 0], label=s['source']) # Predicted tide in first column
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ax.legend()
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ax.set_xlim('2019-11-29', '2019-12-02')
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ax.set_ylabel('Predicted tide (m LAT)', labelpad=10)
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ax.xaxis.set_major_formatter(mdates.DateFormatter('%b-%d %H:%M'))
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ax.xaxis.set_tick_params(rotation=45)
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ax.spines['top'].set_visible(False)
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ax.spines['right'].set_visible(False)
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png_name = os.path.join(
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os.path.dirname(__file__),
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os.path.basename(__file__).replace('.py', '.png').replace('_', '-'))
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plt.savefig(png_name, bbox_inches='tight', dpi=300)
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