import requests import urllib3 import json from utils import geoutil import regex_spatial from shapely.geometry import Polygon, MultiPoint, LineString, Point, mapping import re import geopandas as gpd from geocoder import geo_level1 from openai import OpenAI from utils.config import api_key client = OpenAI( api_key=api_key ) model = "gpt-4o" north = ["north", "N'", "North", "NORTH"] south = ["south", "S'", "South", "SOUTH"] east = ["east", "E'", "East", "EAST"] west = ["west", "W'", "West", "WEST"] northeast = ["north-east", "NE'", "north east", "NORTH-EAST", "North East", "NORTH EAST"] southeast = ["south-east", "SE'", "south east", "SOUTH-EAST", "South East", "SOUTH EAST"] northwest = ["north-west", "NW'", "north west", "NORTH-WEST", "North West", "NORTH WEST"] southwest = ["south-west", "SW'", "south west", "SOUTH-WEST", "South West", "SOUTH WEST"] center = ["center","central", "downtown","midtown"] # # # def get_directional_coordinates(coordinates, direction, centroid, minimum, maximum, is_midmid): # direction_coordinates = get_directional_coordinates_by_angle(coordinates, direction, minimum, maximum) # midmid1, midmid2 = geoutil.get_midmid_point(centroid, direction_coordinates[0], direction_coordinates[-1], # is_midmid) # if direction in west: # maxi = max(p[2] for p in direction_coordinates) # mini = min(p[2] for p in direction_coordinates) # index_mini = 0 # index_maxi = 0 # for idx, p in enumerate(direction_coordinates): # if p[2] == mini: # index_mini = idx # if p[2] == maxi: # index_maxi = idx # # direction_coordinates.insert(index_maxi + 1, midmid2) # direction_coordinates.insert(index_mini + 1, midmid1) # else: # direction_coordinates.append(midmid2) # direction_coordinates.append(midmid1) # # return direction_coordinates, midmid1, midmid2 # # # def get_directional_coordinates_by_angle(coordinates, direction, minimum, maximum): # direction_coordinates = [] # for p in coordinates: # if direction in east: # if p[2] >= minimum or p[2] <= maximum: # direction_coordinates.append(p) # # else: # if p[2] >= minimum and p[2] <= maximum: # direction_coordinates.append(p) # return direction_coordinates # # # def get_directional_coordinates_by_angle(coordinates, direction, minimum, maximum): # direction_coordinates = [] # for p in coordinates: # if direction in east: # if p[2] >= minimum or p[2] <= maximum: # direction_coordinates.append(p) # # else: # if p[2] >= minimum and p[2] <= maximum: # direction_coordinates.append(p) # return direction_coordinates # # # def get_central(coordinates, centroid, direction, is_midmid): # n_min_max = get_min_max("north") # n_coordinates = get_directional_coordinates_by_angle(coordinates, "north", n_min_max[0], n_min_max[1]) # n_mid1, n_mid2 = geoutil.get_midmid_point(centroid, n_coordinates[0], n_coordinates[-1], is_midmid) # # ne_min_max = get_min_max("north east") # ne_coordinates = get_directional_coordinates_by_angle(coordinates, "north east", ne_min_max[0], ne_min_max[1]) # ne_mid1, ne_mid2 = geoutil.get_midmid_point(centroid, ne_coordinates[0], ne_coordinates[-1], is_midmid) # # e_min_max = get_min_max("east") # e_coordinates = get_directional_coordinates_by_angle(coordinates, "east", e_min_max[0], e_min_max[1]) # e_mid1, e_mid2 = geoutil.get_midmid_point(centroid, e_coordinates[0], e_coordinates[-1], is_midmid) # # se_min_max = get_min_max("south east") # se_coordinates = get_directional_coordinates_by_angle(coordinates, "south east", se_min_max[0], se_min_max[1]) # se_mid1, se_mid2 = geoutil.get_midmid_point(centroid, se_coordinates[0], se_coordinates[-1], is_midmid) # # s_min_max = get_min_max("south") # s_coordinates = get_directional_coordinates_by_angle(coordinates, "south", s_min_max[0], s_min_max[1]) # s_mid1, s_mid2 = geoutil.get_midmid_point(centroid, s_coordinates[0], s_coordinates[-1], is_midmid) # # sw_min_max = get_min_max("south west") # sw_coordinates = get_directional_coordinates_by_angle(coordinates, "south west", sw_min_max[0], sw_min_max[1]) # sw_mid1, sw_mid2 = geoutil.get_midmid_point(centroid, sw_coordinates[0], sw_coordinates[-1], is_midmid) # # w_min_max = get_min_max("west") # w_coordinates = get_directional_coordinates_by_angle(coordinates, "west", w_min_max[0], w_min_max[1]) # w_mid1, w_mid2 = geoutil.get_midmid_point(centroid, w_coordinates[0], w_coordinates[-1], is_midmid) # # nw_min_max = get_min_max("north west") # nw_coordinates = get_directional_coordinates_by_angle(coordinates, "north west", nw_min_max[0], nw_min_max[1]) # nw_mid1, nw_mid2 = geoutil.get_midmid_point(centroid, nw_coordinates[0], nw_coordinates[-1], is_midmid) # # central_coordindates = [e_mid1, e_mid2, ne_mid1, ne_mid2, n_mid1, n_mid2, # nw_mid1, nw_mid2, w_mid1, w_mid2, sw_mid1, sw_mid2, # s_mid1, s_mid2, se_mid1, se_mid2] # return central_coordindates # # # def get_min_max(direction): # regex = regex_spatial.get_directional_regex() # direction_list = regex.split("|") # if direction in direction_list: # if direction in east: # return (337, 22) # if direction in northeast: # return (22, 67) # if direction in north: # return (67, 112) # if direction in northwest: # return (112, 157) # if direction in west: # return (157, 202) # if direction in southwest: # return (202, 247) # if direction in south: # return (247, 292) # if direction in southeast: # return (292, 337) # # return None # def get_level1_coordinates(coordinates, centroid, direction, is_midmid): # min_max = get_min_max(direction) # if min_max is not None: # coordinates, mid1, mid2 = get_directional_coordinates(coordinates, direction, centroid, min_max[0], min_max[1], is_midmid) # return coordinates, centroid, mid1, mid2 # elif direction.lower() in center: # return get_central(coordinates, centroid, direction, is_midmid), centroid, None, None # else: # return coordinates, centroid, None, None def to_standard_2d_list(data): arr = np.array(data) # 强制变成一维后 reshape，前提是元素总数是2的倍数 flat = arr.flatten() if flat.size % 2 != 0: raise ValueError("元素个数不是2的倍数，不能 reshape 成 [N, 2] 格式") return flat.reshape(-1, 2).tolist() def get_geojson(ent, arr, centroid): poly_json = {} poly_json['type'] = 'FeatureCollection' poly_json['features'] = [] coordinates= [] coordinates.append(arr) poly_json['features'].append({ 'type':'Feature', 'id': ent, 'properties': { 'centroid': centroid }, 'geometry': { 'type':'Polygon', 'coordinates': coordinates } }) return poly_json def get_coordinates(ent): request_url = 'https://nominatim.openstreetmap.org/search.php?q= ' +ent +'&polygon_geojson=1&accept-language=en&format=jsonv2' headers = { "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.3 Safari/605.1.15" } page = requests.get(request_url, headers=headers, verify=False) json_content = json.loads(page.content) all_coordinates = json_content[0]['geojson']['coordinates'][0] centroid = (float(json_content[0]['lon']), float(json_content[0]['lat'])) for p in all_coordinates: p2 = (p[0], p[1]) angle = geoutil.calculate_bearing(centroid, p2) p.append(angle) geojson = get_geojson(ent, all_coordinates, centroid) return geojson['features'][0]['geometry']['coordinates'][0], geojson['features'][0]['properties']['centroid'] def get_coordinates(location): request_url = f'https://nominatim.openstreetmap.org/search.php?q={location}&polygon_geojson=1&accept-language=en&format=jsonv2' print(request_url) headers = {"User-Agent": "Mozilla/5.0"} response = requests.get(request_url, headers=headers, verify=False) json_content = json.loads(response.content) # print(json_content) if json_content[0]['geojson']['type'] == 'Polygon': coordinates = json_content[0]['geojson']['coordinates'][0] elif json_content[0]['geojson']['type'] == 'Point': coordinates = json_content[0]['geojson']['coordinates'] else: print(json_content[0]['geojson']['type']) centroid = (float(json_content[0]['lon']), float(json_content[0]['lat'])) return (coordinates, centroid) # level3 def get_directional_coordinates_by_angle(coordinates, centroid, direction, minimum, maximum): # minimum = 157 # maximum = 202 direction_coordinates = [] for p in coordinates: angle = geoutil.calculate_bearing(centroid, p) p2 = (p[0], p[1], angle) if direction in geo_level1.east: if angle >= minimum or angle <= maximum: direction_coordinates.append(p2) else: if angle >= minimum and angle <= maximum: direction_coordinates.append(p2) # print(type(direction_coordinates[0])) # if(direction in geo_level1.west): # direction_coordinates.sort(key=lambda k: k[2], reverse=True) return direction_coordinates def get_level3(level3): digits = re.findall('[0-9]+', level3)[0] unit = re.findall('[A-Za-z]+', level3)[0] return digits, unit def get_direction_coordinates(coordinates, centroid, level1): min_max = geo_level1.get_min_max(level1) if min_max is not None: coord = get_directional_coordinates_by_angle(coordinates, centroid, level1, min_max[0], min_max[1]) return coord return coordinates def sort_west(poly1, poly2, centroid): coords1 = mapping(poly1)["features"][0]["geometry"]["coordinates"] coords2 = mapping(poly2)["features"][0]["geometry"]["coordinates"] coord1 = [] coord2 = [] coord = [] for c in coords1: pol = list(c[::-1]) coord1.extend(pol) for c in coords2: pol = list(c[::-1]) coord2.extend(pol) coo1 = [] coo2 = [] for p in coord1: angle = geoutil.calculate_bearing(centroid, p) if angle >= 157 and angle <= 202: coo1.append((p[0], p[1], angle)) for p in coord2: angle = geoutil.calculate_bearing(centroid, p) if angle >= 157 and angle <= 202: coo2.append((p[0], p[1], angle)) coo1.extend(coo2) return coo1 def get_level3_coordinates(coordinates, level_3, level1): distance, unit = get_level3(level_3) kms = geoutil.get_kilometers(distance, unit) coord = [] coords0, center = coordinates if not isinstance(coords0, list) or len(coords0) < 3: # 从原始点出发，根据方向移动距离 kms 得到新圆心 lat_km = 111.32 lon_km = 111.32 * np.cos(np.radians(center[1])) dx = dy = 0 if level1 is not None: if level1 in geo_level1.east: dx = kms / lon_km elif level1 in geo_level1.west: dx = -kms / lon_km elif level1 in geo_level1.north: dy = kms / lat_km elif level1 in geo_level1.south: dy = -kms / lat_km # 你也可以支持 northeast、southwest 等复合方向 new_center = (center[0] + dx, center[1] + dy) # 用固定半径画个圆（例如半径2km） r_km = 1 # 半径设为1km，你也可以设为其他值 circle_points = [] for theta in np.linspace(0, 360, num=100): theta_rad = np.radians(theta) d_lat = (np.sin(theta_rad) * r_km) / lat_km d_lon = (np.cos(theta_rad) * r_km) / lon_km circle_points.append((new_center[0] + d_lon, new_center[1] + d_lat)) # 输出中心（使用新圆心） if circle_points: center_point = MultiPoint(circle_points).centroid center = (center_point.x, center_point.y) else: center = new_center return circle_points, center # 正常 polygon 流程 poly1 = Polygon(coords0) polygon1 = gpd.GeoSeries(poly1) # 生成环形区域 poly2 = polygon1.buffer(0.0095 * kms, join_style=2) poly3 = polygon1.buffer(0.013 * kms, join_style=2) poly = poly3.difference(poly2) # 获取坐标 coords = mapping(poly)["features"][0]["geometry"]["coordinates"] for c in coords: pol = list(c[::-1]) coord.extend(pol) # 方向裁剪 if level1 is not None: coord = get_direction_coordinates(coord, coordinates[1], level1) if level1 in geo_level1.west: coord = sort_west(poly3, poly2, coordinates[1]) # 计算质心 if coord: center_point = MultiPoint(coord).centroid center = (center_point.x, center_point.y) else: center = coordinates[1] return coord, center # level 3 end # between def get_between_coordinates(coordinates1, coordinates2): """ 计算两个区域之间的中间点，并生成一个等面积的圆形区域。 如果某个输入仅为点（坐标长度 < 3），则其面积设为 0； 如果两个输入都是点，则默认半径为 2km。 :param coordinates1: 第一个区域的边界坐标和中心点 :param coordinates2: 第二个区域的边界坐标和中心点 :return: 圆形区域的坐标集和圆心 """ def is_valid_polygon(coords): return isinstance(coords, list) and len(coords) >= 3 coords1, center1 = coordinates1 coords2, center2 = coordinates2 # 判断输入是否为合法多边形（>=3个点） if is_valid_polygon(coords1): poly1 = Polygon(coords1) area1 = poly1.area else: area1 = 0 if is_valid_polygon(coords2): poly2 = Polygon(coords2) area2 = poly2.area else: area2 = 0 # 计算中心点（两个中心的中点） midpoint = ( (center1[0] + center2[0]) / 2, (center1[1] + center2[1]) / 2 ) # 如果两个区域都是点，则使用默认半径 2km if area1 == 0 and area2 == 0: r_km = 2 else: avg_area = (area1 + area2) / 2 r_km = np.sqrt(avg_area / np.pi) * 111.32 # 近似 km 半径 # 经纬度距离换算因子 lat_km = 111.32 lon_km = 111.32 * np.cos(np.radians(midpoint[1])) # 生成圆形区域坐标（100个点） circle_points = [] for theta in np.linspace(0, 360, num=100): theta_rad = np.radians(theta) d_lat = (np.sin(theta_rad) * r_km) / lat_km d_lon = (np.cos(theta_rad) * r_km) / lon_km circle_points.append((midpoint[0] + d_lon, midpoint[1] + d_lat)) return circle_points, midpoint # between end def llmapi(text): system_prompt = ( "你是一个资深的地理学家，你的任务是通过给定的一段自然语言，来选择正确的定位函数顺序以及他们的输入。\n" "你能选择的定位函数有：\n" "1. 相对定位（Relative Positioning）：输入为地点坐标，方位，距离。输出为距离‘距离’输入的地点坐标的‘方位’的坐标。\n" "2. 中间定位（Between Positioning）：输入为两个地点的坐标，输出为两个地点坐标的中点。\n" "请先进行思维链（CoT）推理，并最终用 JSON 格式输出你的答案，用 `<<>>` 和 `<<>>` 包裹起来。\n" "请确保所有输入仅包含：地点名称（字符串）、索引（整数）、方位（字符串，必须是英文）或距离（字符串，带单位），不允许返回诸如 'Chatswood 南4 km的坐标' 这样的内容。\n" "每个步骤编号都有 id 记录，然后如果某个输入是之前步骤的输出，那么输入对应步骤的 id。\n" "所有方向必须使用英文（如 south, west, northeast, etc.）。\n" "示例输出：\n" "<<>>\n" "[{\"id\": 1, \"function\": \"Relative\", \"inputs\": [\"Chatswood\", \"south\", \"4 km\"]}," "{\"id\": 2, \"function\": \"Relative\", \"inputs\": [\"North Sydney\", \"west\", \"2 km\"]}," "{\"id\": 3, \"function\": \"Between\", \"inputs\": [1, 2]}," "{\"id\": 4, \"function\": \"Relative\", \"inputs\": [3, \"southwest\", \"5 km\"]}]\n" "<<>>") messages = [ {"role": "system", "content": system_prompt}, {"role": "user", "content": text}, ] chat_completion = client.chat.completions.create( messages=messages, model=model, ) result = chat_completion.choices[0].message.content json_match = re.search(r'<<>>\n(.*?)\n<<>>', result, re.DOTALL) if json_match: # print(json.loads(json_match.group(1))) return json.loads(json_match.group(1)) else: raise ValueError("LLM 输出未包含预期的 JSON 格式数据。") def llmapi(text): system_prompt = ( "You are an experienced geographer. Your task is to determine the correct sequence of positioning functions and their inputs based on a given piece of natural language.\n" "The positioning functions you can choose from are:\n" "1. Relative Positioning: Inputs is (location coordinate or location name, direction, and distance). Outputs the coordinates that are in the given 'direction' and 'distance' from the input location.\n" "2. Between Positioning: Inputs is (location 1 coordinates or location 1 name, location 2 coordinates or location 2 name). Outputs the midpoint coordinate between the two locations.\n" "You can only use the given functions, and the inputs to the functions must obey the above properties. The given functions can be combined to solve complex situations." "First, perform chain-of-thought (CoT) reasoning, and finally output your answer in JSON format, wrapped between `<<>>` and `<<>>`.\n" "Make sure all inputs only include: location names (strings), step indices (integers), directions (strings, must be in English), or distances (strings with units). Do not return expressions like 'the coordinate 4 km south of Chatswood'.\n" "Each step must have an 'id'. If the input of a step is the output of a previous step, use that step’s 'id' as the input.\n" "All directions must be in English (e.g., south, west, northeast, etc.).\n" "Example output:\n" "<<>>\n" "[{\"id\": 1, \"function\": \"Relative\", \"inputs\": [\"Chatswood\", \"south\", \"4 km\"]}," "{\"id\": 2, \"function\": \"Relative\", \"inputs\": [\"North Sydney\", \"west\", \"2 km\"]}," "{\"id\": 3, \"function\": \"Between\", \"inputs\": [1, 2]}," "{\"id\": 4, \"function\": \"Relative\", \"inputs\": [3, \"southwest\", \"5 km\"]}]\n" "<<>>") messages = [ {"role": "system", "content": system_prompt}, {"role": "user", "content": text}, ] chat_completion = client.chat.completions.create( messages=messages, model=model, ) result = chat_completion.choices[0].message.content print(result) json_match = re.search(r'<<>>\n(.*?)\n<<>>', result, re.DOTALL) if json_match: return json.loads(json_match.group(1)) else: raise ValueError("LLM 输出未包含预期的 JSON 格式数据。") def execute_steps(steps): data = {} for step in steps: step_id = step['id'] function = step['function'] inputs = step['inputs'] # print('-' * 50) # print(function) # print(inputs) resolved_inputs = [] for inp in inputs: if isinstance(inp, int): resolved_inputs.append(data[inp]) else: resolved_inputs.append(inp) if function == "Relative": location, direction, distance = resolved_inputs if isinstance(location, str): location = get_coordinates(location) location = [to_standard_2d_list(location[0])] + list(location[1:]) location = [[[151.214901,-33.859175]], (151.214901,-33.859175)] result = get_level3_coordinates(location, distance, direction) data[step_id] = result elif function == "Between": location1, location2 = resolved_inputs # print(location1) # print(111) # print(location2) if isinstance(location1, str): location1 = get_coordinates(location1) location1 = [to_standard_2d_list(location1[0])] + list(location1[1:]) if isinstance(location2, str): location2 = get_coordinates(location2) location2 = [to_standard_2d_list(location2[0])] + list(location2[1:]) result = get_between_coordinates(location1, location2) data[step_id] = result return data if __name__ == '__main__': # a = get_coordinates('Burwood') # a2 = get_coordinates('Glebe') # b = get_level3_coordinates(a, '5 km', 'east') # c = get_between_coordinates(a, a2) # 完整通道 # 默认输入 # default_input_text = "在Chatswood南边4公里与North Sydney 东边2公里的中间的西南5公里。" # default_input_text = "你是一位规划师，正在为华盛顿州的一项新森林监测站选址。两个潜在的参考位置分别是雷尼尔山国家公园（Mount Rainier National Park）和北喀斯喀特国家公园（North Cascades National Park）。首先，你想在这两个国家公园之间找到一个中间点。接着，你希望在这个中间点与北喀斯喀特国家公园之间，再取一个中间位置，以便确定最终的建设候选地。" # default_input_text = "在Chatswood和North Sydney的中间靠近North Sydney的四分之一位置" # default_input_text = "Plan a trip that involves determining the midpoint between Paris and London, and then finding another midpoint between this location and Paris to identify potential stopovers during travel." # default_input_text = "5km southwest of Chatswood, 4km south of Chatswood and 2km north of North Sydney." # 解析 LLM 结果 # parsed_steps = llmapi(default_input_text) # parsed_steps = [{'id': 1, 'function': 'Relative', 'inputs': ['Chatswood', 'south', '4 km']}, {'id': 2, 'function': 'Relative', 'inputs': ['North Sydney', 'east', '2 km']}, {'id': 3, 'function': 'Between', 'inputs': [1, 2]}, {'id': 4, 'function': 'Relative', 'inputs': [3, 'south west', '5 km']}] # parsed_steps = [{"id": 1, "function": "Between", "inputs": ["Chatswood", "North Sydney"]},{"id": 2, "function": "Between", "inputs": [1, "North Sydney"]}] # parsed_steps = [{"id": 1, "function": "Relative", "inputs": ["Katoomba", "southeast", "3 km"]}, {"id": 2, "function": "Between", "inputs": [1, "Echo Point"]}] # parsed_steps = [{'id': 1, 'function': 'Relative', 'inputs': ['Scafell Pike', 'east', '9 km']}] # parsed_steps = [{'id': 1, 'function': 'Relative', 'inputs': ['Colosseum', 'northeast', '8 km']}, {'id': 2, 'function': 'Relative', 'inputs': [1, 'northeast', '2 km']}] parsed_steps = [ {"id": 1, "function": "Between", "inputs": ["Statue of Liberty", "Eiffel Tower"]}, {"id": 2, "function": "Relative", "inputs": [1, "west", "8 km"]} ] # 执行步骤 result = execute_steps(parsed_steps) # 输出最终计算结果 print(result) print('-' * 100) print(result[(max(result.keys()))][0]) # 通道结束 # location = get_coordinates('Chatswood') # result = get_level3_coordinates(location, '4 km', 'north west') # print(result)