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@ -15,11 +15,13 @@ 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 yaml
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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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import pandas as pd
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from glob import glob
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from cycler import cycler
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import matplotlib.pyplot as plt
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from matplotlib.ticker import MultipleLocator
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@ -166,43 +168,27 @@ def calculate_volumes(profile_name, survey_date, csv_output_dir, ch_limits, volu
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return delta_vol
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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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print("Starting to process %s" % row['BEACH'])
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beach=row['BEACH']
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survey_date = str(row['SURVEY DATE'])
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original_las = row['INPUT LAS']
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classified_las_dir = row['LAS CLASSIFIED FOLDER']
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shp_swash_dir = row['SHP SWASH FOLDER']
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crop_heatmap_poly = row['HEATMAP CROP POLY']
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output_las_dir = row['LAS OUTPUT FOLDER']
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zone_MGA = row['ZONE MGA']
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output_poly_dir = row['SHP RASTER FOLDER']
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output_tif_dir = row['TIF OUTPUT FOLDER']
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cp_csv = row['INPUT CSV']
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profile_limit_file = row['PROFILE LIMIT FILE']
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csv_output_dir = row['CSV OUTPUT FOLDER']
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graph_loc = row['PNG OUTPUT FOLDER']
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volume_output_dir = row['CSV VOLUMES FOLDER']
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tmp_dir = row['TMP FOLDER']
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def process(yaml_file):
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with open(yaml_file, 'r') as f:
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params = yaml.safe_load(f)
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print("Starting to process %s" % params['BEACH'])
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beach = params['BEACH']
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survey_date = str(params['SURVEY DATE'])
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original_las = params['INPUT LAS']
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classified_las_dir = params['LAS CLASSIFIED FOLDER']
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shp_swash_dir = params['SHP SWASH FOLDER']
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crop_heatmap_poly = params['HEATMAP CROP POLY']
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output_las_dir = params['LAS OUTPUT FOLDER']
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zone_MGA = params['ZONE MGA']
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output_poly_dir = params['SHP RASTER FOLDER']
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output_tif_dir = params['TIF OUTPUT FOLDER']
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cp_csv = params['INPUT CSV']
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profile_limit_file = params['PROFILE LIMIT FILE']
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csv_output_dir = params['CSV OUTPUT FOLDER']
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graph_loc = params['PNG OUTPUT FOLDER']
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volume_output_dir = params['CSV VOLUMES FOLDER']
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tmp_dir = params['TMP FOLDER']
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# Get base name of input las
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las_basename = os.path.splitext(os.path.basename(original_las))[0]
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@ -264,5 +250,38 @@ def main():
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remove_temp_files(tmp_dir)
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def main():
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example_text = """examples:
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# Process single survey at specific beach
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python las_outputs.py survey-1-avoca.yaml
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# Process all surveys at specific beach
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python las_outputs.py *avoca.yaml
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# Process all beaches for specific survey date
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python las_outputs.py survey-1*.yaml
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"""
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# Set up command line arguments
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parser = argparse.ArgumentParser(
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epilog=example_text,
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formatter_class=argparse.RawDescriptionHelpFormatter)
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parser.add_argument('input', help='path to yaml file(s)', nargs='*')
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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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# Parse arguments
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args = parser.parse_args()
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yaml_files = []
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[yaml_files.extend(glob(f)) for f in args.input]
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for yaml_file in yaml_files:
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process(yaml_file)
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if __name__ == '__main__':
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main()
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