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@ -96,7 +96,7 @@ def make_raster(las, output, lastools_loc, keep_only_ground=False, step=0.2):
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return None
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def extract_pts(las_in, cp_in, survey_date, keep_only_ground=True):
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def extract_pts(las_in, cp_in, survey_date, beach, keep_only_ground=True):
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"""Extract elevations from a las surface based on x and y coordinates.
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Requires lastools in system path.
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@ -105,6 +105,7 @@ def extract_pts(las_in, cp_in, survey_date, keep_only_ground=True):
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las_in: input point cloud (las)
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cp_in: point coordinates with columns: id, x, y, z (csv)
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survey_date: survey date string, e.g. '19700101'
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beach: beach name
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keep_only_ground: only keep points classified as 'ground' (boolean)
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Returns:
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@ -149,7 +150,32 @@ def extract_pts(las_in, cp_in, survey_date, keep_only_ground=True):
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return df
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def update_survey_output(df, output_dir):
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"""Update survey profile output csv files with current survey.
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Args:
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df: dataframe containing current survey elevations
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output_dir: directory where csv files are saved
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Returns:
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None
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"""
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# Merge current survey with existing data
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profiles = df['Profile'].unique()
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for profile in profiles:
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csv_name = os.path.join(output_dir, profile + '.csv')
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try:
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# Load existing results
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master = pd.read_csv(csv_name)
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except FileNotFoundError:
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master = df.copy()
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# Add (or update) current survey
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current_survey_col = df.columns[-1]
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master[current_survey_col] = df[current_survey_col]
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# Export updated results
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master.to_csv(csv_name)
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def plot_profiles(profile_info, profile, output_loc, LL_limit):
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@ -365,9 +391,8 @@ for i in range(0, len(params_file)): #0, len(params_file)
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make_raster(heatmap_las, output_raster, path_2_lastools, keep_only_ground=True)
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#extract the points and get volumes
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df = extract_pts(final_las, input_csv, survey_date, keep_only_ground=True)
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update_survey_output(df, output_csv_dir)
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process_tmp_csv(tmp_csv, survey_date, csv_loc, beach)
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df = extract_pts(final_las, input_csv, survey_date, beach, keep_only_ground=True)
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update_survey_output(df, csv_loc)
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#colourise the point cloud
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