ChocopieKewpie

import rasterio
import numpy as np
from skimage.graph import MCP

""" Adopted from Schönauer, M., Maack, J., 2021. R-code for calculating depth-to-water (DTW) maps using GRASS GIS. Zenodo. doi: 10.5281/zenodo.5638517 
adopted to Python by Ardo.J, 2024"""

# Setting Paths, Assuming that these layers are calculated outside of this code.
dem_path = "breached.tif"
slope_path = "slope.tif"

ChocopieKewpie

"""
Simple script to return a dataframe with neighbourhood values, k_ring= 1
"""

import h3
import pandas as pd
import h3pandas

def get_h3_neighbour(h3_index):
    # Get the 6 neighbors for the given H3 cell

ChocopieKewpie

import os
import geopandas as gpd
import h3pandas


folder_path = 'E:/DGGS_Benchmark/vectors'

# Get a list of all GPKG files in the folder
v_files = [file for file in os.listdir(folder_path) if file.endswith('.gpkg')]

ChocopieKewpie

import os
import geopandas as gpd
import numpy as np
import matplotlib.pyplot as plt


folder_path = 'E:/DGGS_Benchmark/vectors'

# Get a list of all GPKG files in the folder
v_files = [file for file in os.listdir(folder_path) if file.endswith('.gpkg')]

ChocopieKewpie

import geopandas as gpd
import rasterio
import numpy as np
from rasterio.transform import from_bounds

# Function to apply majority rule cellular automaton
def majority_rule(array):
    # Create a copy of the array to store the updated values
    new_array = np.zeros_like(array)
    rows, cols = array.shape

ChocopieKewpie

import geopandas as gpd
from shapely.ops import voronoi_diagram
from shapely.ops import unary_union
from shapely.geometry import shape
import random

def generate_voronoi_plot(df, n_points):
    # Read GeoDataFrame from file
    
    # Extract geometry for clipping

ChocopieKewpie

# -*- coding: utf-8 -*-
"""
Created on Wed Sep  6 15:28:29 2023

@author: ArdoJ
"""

import click
from lxml import etree

ChocopieKewpie

import numpy as np
from shapely.ops import unary_union, voronoi_diagram
from shapely.geometry import Polygon, MultiPolygon
import geopandas as gpd
import pandas as pd

def read_data(file_path):
    return gpd.read_file(file_path)

def create_outline(df):