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@ -35,7 +35,7 @@ def remove_temp_files(directory):
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return None
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def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits):
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def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits, delta_vol):
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csv_name = profile_name + '.csv'
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profiles = pd.read_csv(os.path.join(csv_output_dir, csv_name))
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@ -55,7 +55,12 @@ def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits):
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ax.set_xlabel('Chainage (m)', labelpad=10)
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ax.set_ylabel('Elevation (m AHD)', labelpad=10)
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ax.legend(frameon=False, fontsize=9)
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# Show most recent volume change
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ax.annotate('Most recent\nvolume change:\n{:0.1f} m$^3$/m'.format(delta_vol),
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(0.1, 0.15), xycoords='axes fraction', fontsize=8,
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backgroundcolor='#ffffff', linespacing=1.5)
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ax.legend(edgecolor='none', facecolor='#ffffff', fontsize=9)
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ax.xaxis.set_minor_locator(MultipleLocator(5))
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ax.yaxis.set_minor_locator(MultipleLocator(0.5))
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@ -99,9 +104,17 @@ def calculate_volumes(profile_name, survey_date, csv_output_dir, ch_limits, volu
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volumes.loc[profile_name, date] = volume
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# Save updated volumes spreadsheet
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volumes = volumes[volumes.columns.sort_values()]
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volumes = volumes.sort_index()
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volumes.to_csv(csv_vol)
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# Get most recent volume difference for current profile
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previous_vol = volumes.loc[profile_name].values[-2]
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current_vol = volumes.loc[profile_name].values[-1]
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delta_vol = current_vol - previous_vol
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return delta_vol
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def main():
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parser = argparse.ArgumentParser()
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@ -191,8 +204,11 @@ def main():
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print('Updating figures...')
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profile_names = df['Profile'].unique()
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for profile_name in profile_names:
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plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits)
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calculate_volumes(profile_name, survey_date, csv_output_dir, ch_limits, volume_output_dir)
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delta_vol = calculate_volumes(profile_name, survey_date,
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csv_output_dir, ch_limits,
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volume_output_dir)
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plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits,
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delta_vol)
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# Remove temprary files
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remove_temp_files(tmp_dir)
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@ -200,3 +216,7 @@ def main():
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if __name__ == '__main__':
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main()
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if True:
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plt.plot([], label='label')
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plt.legend(facecolor='r')
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