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@ -13,7 +13,9 @@
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import os
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import io
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import re
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import sys
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import math
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import argparse
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import datetime
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import subprocess
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import numpy as np
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@ -91,7 +93,7 @@ def calculate_volumes(profile_name, survey_date, csv_output_dir, ch_limits, volu
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# Get Nielsen erosion volumes
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chainage = profiles.loc[:, current_date].dropna().index
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elevation = profiles.loc[:, current_date].dropna().values
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volume = neilson_volumes.volume_available(chainage, elevation, ch_min)
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volume = nielsen_volumes.volume_available(chainage, elevation, ch_min)
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# Update spreadsheet
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volumes.loc[profile_name, date] = volume
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@ -101,7 +103,23 @@ def calculate_volumes(profile_name, survey_date, csv_output_dir, ch_limits, volu
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volumes.to_csv(csv_vol)
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input_file = 'Parameter Files/las-manipulation-survey-2.xlsx'
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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'input_file',
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metavar='PARAMS_FILE',
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help='name of parameter file',
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default=None)
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# Print usage if no arguments are provided
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if len(sys.argv) == 1:
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parser.print_help(sys.stderr)
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sys.exit(1)
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args = parser.parse_args()
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# read the parameters file and scroll through it
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input_file = args.input_file
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params_file=pd.read_excel(input_file, sheet_name="PARAMS")
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for i, row in params_file.iterrows():
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@ -133,23 +151,28 @@ for i, row in params_file.iterrows():
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crop_swash_poly = os.path.join(shp_swash_dir, las_basename + '.shp')
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# Crop point cloud to swash boundary
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print('Cropping swash...')
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las_data = call_lastools('lasclip', input=input_las, output='-stdout',
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args=['-poly', crop_swash_poly], verbose=False)
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# Apply sea-side clipping polygon
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print('Cropping back of beach...')
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las_data = call_lastools('lasclip', input=las_data, output='-stdout',
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args=['-poly', crop_heatmap_poly], verbose=False)
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# Create clipping polygon for heatmap raster
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print('Creating heat map cropping polygon...')
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shp_name = os.path.join(output_poly_dir, las_basename + '.shp')
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call_lastools('lasboundary', input=las_data, output=shp_name, verbose=False)
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# Make a raster from point cloud
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print('Creating heat map raster...')
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tif_name = os.path.join(output_tif_dir, las_basename + '.tif')
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call_lastools('blast2dem', input=las_data, output=tif_name,
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args=['-step', 0.2], verbose=False)
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# Extract elevations along profiles from triangulated surface
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print('Extracting profile elevations...')
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df = extract_pts(
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las_data,
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cp_csv,
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@ -165,6 +188,7 @@ for i, row in params_file.iterrows():
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ch_limits = pd.read_excel(profile_limit_file, index_col='Profile')
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# Plot profiles, and save sand volumes for current beach
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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, survey_date, csv_output_dir, graph_loc, ch_limits)
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@ -172,3 +196,7 @@ for i, row in params_file.iterrows():
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# Remove temprary files
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remove_temp_files(tmp_dir)
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if __name__ == '__main__':
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main()
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