generate_stratified_design.py

# Main script for generating a stratified design
# File: generate_stratified_design.py
# author: Ellie Bowler
# contact: e.bowler@uea.ac.uk
# All code available at https://github.com/EllieBowler/
# This script distributes sample sites evenly over a given sample landscape.
# This landscape is represented by a binary (0 = invalid, 1 = valid) geo-referenced satellite image.
# For an example image please see InvalidAreasMask.tif in the input data folder.
###################################################################
# Usage:
# --save_folder is the name of the directory where outputs will be saved, in the results subfolder
# --mask_path is the name of the input mask (for example InvalidAreasMask.tif)
# --nsp is the number of sample points which should be an integer value
###################################################################
# Example of a 30 site stratified design using InvalidAreasMask.tif, saving outputs to Stratified_Design_Demo
# python generate_stratified_design.py --save_folder=Stratified_Design_Demo --mask_path=input/InvalidAreasMask.tif --nsp=30
###################################################################

from utils import get_file_info, plot_stratified, save_stratified
from sda import generate_stratified_design
import os
import click


# Arguments used to call the method from the command line
@click.command()
@click.option('--save_folder', type=str, default='Stratified_Design', help='Name folder where results will be saved')
@click.option('--mask_path', type=str, default='input/InvalidAreasMask.tif', help='Path and name of the study site mask')
@click.option('--nsp', type=int, default=30, help='Integer number of sample sites')
def generate_design(save_folder, mask_path, nsp):
    
    # make results folder to save output
    save_path = 'results/{}'.format(save_folder)
    if not os.path.exists(save_path):
        os.mkdir(save_path)
    print('Results will be saved to {}'.format(save_path))

    # get geo info and mask from tif file
    mask, n_bins, res, geo_t, prj_info = get_file_info(mask_path)

    # generate design
    x_strat, y_strat = generate_stratified_design(mask, nsp)

    # plot design in pop up (please close plot to continue)
    plot_stratified(mask, x_strat, y_strat)

    # save results to csv
    save_stratified(x_strat, y_strat, prj_info, geo_t, save_path)
    return


if __name__ == '__main__':
    generate_design()