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@ -180,25 +180,21 @@ for i, row in params_file.iterrows():
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# Crop point cloud to swash boundary
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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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# crop_las(input_las5, crop_swash_poly, final_las, path_2_lastools)
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# Apply sea-side clipping polygon
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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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# crop_las(final_las, heatmap_crop_poly, heatmap_las, path_2_lastools)
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# Create clipping polygon for heatmap raster
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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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# las_boundary(heatmap_las, output_poly_name, output_poly_dir, path_2_lastools, zone_MGA)
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#make a raster
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# make_raster(heatmap_las, output_raster, path_2_lastools, keep_only_ground=True)
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# Make a raster from point cloud
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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 the points and get volumes
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# Extract elevations along profiles from triangulated surface
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df = extract_pts(
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las_data,
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cp_csv,
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@ -216,10 +212,8 @@ for i, row in params_file.iterrows():
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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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#delete the temp files from the tmp_dir and the interim_dir
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# Remove temprary files
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remove_temp_files(tmp_dir)
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#remove_temp_files(int_dir)
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print("doing the volume analysis")
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# test=profile_plots_volume(csv_output_dir, profile_limit_file, volume_output, graph_loc)
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