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| from typing import List, Tuple | |
| import math | |
| from traitlets import Float | |
| from data_processing.get_smallAreaInfo import get_smallAreas | |
| from data_processing.point_scoring import score_current, calc_score_line | |
| from data_processing.get_station_coverage import get_station_coverage | |
| from data_processing.aggregate_data import get_feature_df | |
| import os | |
| import pandas as pd | |
| from pyproj import Transformer | |
| class Data_provider(): | |
| def __init__(self): | |
| self.smsv_list = get_smallAreas() | |
| self.df = get_feature_df() | |
| self.transformer_to_3057 = Transformer.from_crs("EPSG:4326", "EPSG:3057", always_xy=True) | |
| self.transformer_to_4326 = Transformer.from_crs("EPSG:3057", "EPSG:4326", always_xy=True) | |
| self.PENALTY_SCALE = 100 | |
| def get_station_score(self, station_coord, w_density=1, w_income=1, w_age=1, radius=400, EPSG_4326=True): | |
| """ | |
| Calculate the score for a station based on the given weights and radius. | |
| Parameters: | |
| ---------- | |
| station_coord : tuple | |
| Coordinates of the station in EPSG:4326 format (north, east) = (lat, long). | |
| w_density : float | |
| Weight for the density factor. | |
| w_income : float | |
| Weight for the income factor. | |
| w_age : float | |
| Weight for the age factor. | |
| radius : float | |
| The radius (in meters) around the station to consider. | |
| EPSG_4326 : bool | |
| if a true, station coord of format EPSG:4326 is expected, else EPSG:3057 | |
| Returns: | |
| ------- | |
| dict | |
| Dictionary that contains total score and subscores | |
| {"total_score": total_score, "income_score": income_score, "age_score": age_score, "density_score": density_score} | |
| """ | |
| if EPSG_4326: | |
| station_coord = self.__convert_to_3057(station_coord) | |
| cov = get_station_coverage(self.smsv_list, station_coord, radius) | |
| scores = score_current(station_coord, self.df, cov, w_density, w_income, w_age) | |
| return scores | |
| def __convert_to_3057(self, station_coord): | |
| """ | |
| Convert coordinates from EPSG:4326 (lon, lat) to EPSG:3057 (x, y). | |
| Parameters: | |
| ---------- | |
| station_coord : tuple | |
| Coordinates in EPSG:4326 format (lon, lat). | |
| Returns: | |
| ------- | |
| tuple | |
| Coordinates in EPSG:3057 format (x, y). | |
| """ | |
| return self.transformer_to_3057.transform(*station_coord) | |
| def __convert_to_4326(self, station_coord): | |
| """ | |
| Convert coordinates from EPSG:3057 (x, y) to EPSG:4326 (lon, lat). | |
| Parameters: | |
| ---------- | |
| station_coord : tuple | |
| Coordinates in EPSG:3057 format (x, y). | |
| Returns: | |
| ------- | |
| tuple | |
| Coordinates in EPSG:4326 format (lon, lat). | |
| """ | |
| return self.transformer_to_4326.transform(*station_coord) | |
| def line_score(self, stations_coordinates: List[Tuple[Float]], w_density=1, w_income=1, w_age=1, radius=400, EPSG_4326=True): | |
| """ | |
| Calculate the total score for a transit line based on station locations and individual station scores. | |
| Parameters: | |
| stations_coordinates (List[Tuple[float]]): A list of station coordinates as (x, y) tuples. | |
| w_density (float): Weight for population density in scoring (default is 1). | |
| w_income (float): Weight for income level in scoring (default is 1). | |
| w_age (float): Weight for age distribution in scoring (default is 1). | |
| radius (float): Radius of influence for each station (default is 400 meters). | |
| EPSG_4326 (bool): If True, the coordinates are in EPSG:4326 and will be converted to EPSG:3057 (default is True). | |
| Returns: | |
| dict: A dictionary containing: | |
| - "individual_scores": Scores for each station before applying penalties. | |
| - "adjusted_scores": Scores for each station after applying penalties for proximity. | |
| - "overlap_factors": (Optional, if calc_score_line returns it) Degree of overlap between stations. | |
| - "total_individual_score": The aggregated score of all stations before penalties. | |
| - "final_score": The total line score after penalties. | |
| """ | |
| coords_formatted = [] | |
| coords_scores = [] | |
| for coord in stations_coordinates: | |
| coord_formatted = self.__convert_to_3057(coord) if EPSG_4326 else coord | |
| coords_formatted.append(coord_formatted) | |
| coords_scores.append(self.get_station_score(coord_formatted, w_density, w_income, w_age, radius, EPSG_4326=False)) | |
| result = calc_score_line(coords_formatted, coords_scores, w_density, w_income, w_age, radius) | |
| return result | |
| # dummy_coord1 = (356250.0, 408250.0) # EPSG:3057 coordinates | |
| # dummy_coord2 = (-21.910388, 64.144947) # EPSG:4326 coordinates | |
| # dummy_coord3 = (358374.26032876654, 407938.72289760906) # ISN93/Lambert | |
| # lane = [ | |
| # (-2427839.8601560914, 9371544.591676729), | |
| # (-2431634.4660833703, 9372554.640815599), | |
| # (-2434649.232041, 9374913.131190613), | |
| # (-2436330.9382214467, 9375856.527340621), | |
| # (-2438828.8871577685, 9378030.440208027), | |
| # (-2439956.860815385, 9378055.050542375), | |
| # (-2442307.1477456186, 9379548.07749282), | |
| # (-2441441.6843210473, 9380909.849326741), | |
| # (-2441400.6670971345, 9384909.028658295), | |
| # (-2441962.6030647475, 9385105.911333079), | |
| # (-2443122.365070897, 9385984.705355423), | |
| # (-2441898.000937084, 9387355.706064725), | |
| # (-2423704.8112703268, 9387223.425517604), | |
| # (-2425747.4690212114, 9387959.684686847), | |
| # (-2433768.8998727645, 9383004.29132282), | |
| # (-2429552.329254474, 9382532.593247818), | |
| # (-2436008.4402984325, 9385453.019590447), | |
| # (-2438288.9979480137, 9386006.752113278), | |
| # (-2439449.7853847607, 9386252.855456758)] | |
| # transformer = Transformer.from_crs("EPSG:3857", "EPSG:3057", always_xy=True) | |
| # for i in range(len(lane)): | |
| # lane[i] = transformer.transform(*lane[i]) | |
| # backend = Data_provider() | |
| # # print("dummy_coord1: ", backend.get_station_score(dummy_coord1, EPSG_4326=False)) | |
| # # print("dummy_coord2: ", backend.get_station_score(dummy_coord2)) | |
| # # print("dummy_coord3: ", backend.get_station_score(dummy_coord3, EPSG_4326=False)) | |
| # print("Line score", backend.line_score(lane, EPSG_4326=False)) | |