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central-coast-aerial-survey/polyline_to_points.py

93 lines
2.5 KiB
Python

"""polyline_to_points.py
Extract interpolated points along transects in a shapefile.
D. Howe
d.howe@wrl.unsw.edu.au
2020-02-19
"""
import sys
import argparse
import numpy as np
import pandas as pd
import geopandas as gpd
from shapely.geometry import LineString
def extract(shp_path, spacing=1, field=None):
rows = []
shp = gpd.read_file(shp_path)
if field is None:
# Assume profile name is second field in shapefile
field = shp.columns[1]
for i, line in shp.iterrows():
g = line.geometry
chainages = np.arange(0, g.length, step=spacing)
for chainage in chainages:
easting, northing = g.interpolate(chainage).xy
row = {
'ProfileNum': line[field],
'Easting': easting[0],
'Northing': northing[0],
'Chainage': chainage,
}
rows.append(row)
# Create output dataframe
df = pd.DataFrame(rows)
# Re-order columns
df = df[['ProfileNum', 'Easting', 'Northing', 'Chainage']]
# Export to csv
csv_path = shp_path.replace('.shp', '.csv')
df.to_csv(csv_path, index=False)
def main():
example_text = """examples:
# Extract points at default spacing (1m)
$ python polyline_to_points.py path/to/shp
# Extract points at 5m increments
$ python polyline_to_points.py -s 5 path/to/shp
5 years ago
# Use profile names from field "ProfileID" in the attribute table
$ python polyline_to_points.py -f ProfileID path/to/shp
"""
# Set up command line arguments
parser = argparse.ArgumentParser(
epilog=example_text,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('shp_path',
metavar='SHAPEFILE',
help='path to input shapefile')
parser.add_argument('-s',
'--spacing',
metavar='SPACING',
default=1,
type=int,
help='space between points (default=1)')
parser.add_argument('-f',
'--field',
metavar='FIELDNAME',
help='profile field name in attribute table')
# Print usage if no arguments are provided
if len(sys.argv) == 1:
parser.print_help(sys.stderr)
sys.exit(1)
# Parse arguments
args = parser.parse_args()
# Combine images
extract(**vars(args))
if __name__ == '__main__':
main()