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How to use class_name method in Slash
Best Python code snippet using slash
sql_parser.py
Source:sql_parser.py 
1import re2import json3import itertools as it4import numpy as np5sql_json = {6 "0": {"name": "abc", "tpm": 45, "selectable": True, "query": "return all from User, Person A as s, Person A as b"},7 "1": {"name": "query", "tpm": 35, "selectable": True, "query": "Update User Set Person A"},8 "2": {"name": "query", "tpm": 35, "selectable": True, "query": "Insert into Person A where count(all)= ?"},9 "3": {"name": "query", "tpm": 35, "selectable": True, "query": "Delete User where all= ?"},10 "4": {"name": "query", "tpm": 35, "selectable": True, "query": "CONNECT Person A, User WHERE name = ? "11 "and title = ? SET REL=actor"}}12uml_j = {"class": "GraphLinksModel",13 "copiesArrays": True,14 "copiesArrayObjects": True,15 "linkKeyProperty": "key",16 "linkLabelKeysProperty": "labelKeys",17 "modelData": {"position": "-209 -431.83671875"},18 "nodeDataArray": [19 {"type": "Class", "name": "Class", "properties": [], "methods": [], "key": -1, "loc": "-20 -80"},20 {"type": "Class", "name": "Bss", "properties": [], "methods": [], "key": -2, "loc": "-120 10"},21 {"type": "Class", "name": "User", "properties": [], "methods": [], "key": -3, "loc": "-20 -80"},22 {"type": "Class", "name": "Person A", "properties": [], "methods": [], "key": -4, "loc": "-120 10"}23 ],24 "linkDataArray": [25 {"category": "Linkble", "name": "association", "RoleFrom": "from", "RoleTo": "to", "MultiFrom": "0",26 "MultiTo": "1", "toArrow": "",27 "points": [4.84765625, -80, 14.84765625, -80, 14.84765625, -50.83671874999999, -2.576171875,28 -50.83671874999999, -20, -50.83671874999999, -20, -60.83671874999999], "from": -3, "to": -4,29 "labelKeys": [], "key": -1},30 {"name": "generalization", "toArrow": "Triangle",31 "points": [-120, 29.16328125, -120, 39.16328125, -93.82421875, 39.16328125, -93.82421875, -19.16328125,32 -120, -19.16328125, -120, -9.16328125], "from": -2, "to": -2, "labelKeys": [], "key": -2}33 ]}34class SQLParser:35 def __init__(self):36 pass37 @staticmethod38 def increment_matrix_table_cell(matrix, class_from, class_to, increase):39 i = max(class_from[1], class_to[1])40 j = min(class_from[1], class_to[1])41 matrix[i][j] += increase42 @staticmethod43 def get_classes_return_query(query_arr, classes_names):44 query_classes = {}45 index = -146 try:47 index = next(i for i, v in enumerate(query_arr) if v.lower() == 'from')48 except StopIteration:49 return {}50 idx = index + 151 while idx < len(query_arr) and query_arr[idx].lower() != 'where':52 if query_arr[idx] == '':53 idx += 154 continue55 class_name = None56 tmp_idx = idx57 exist = False58 for i in range(tmp_idx, tmp_idx + 4):59 if i >= len(query_arr) or query_arr[i].lower() == 'where':60 break61 if class_name is None:62 class_name = query_arr[i]63 else:64 class_name += " " + query_arr[i]65 if class_name in classes_names:66 if class_name in query_classes:67 query_classes[class_name] += 168 else:69 query_classes[class_name] = 170 idx = i71 exist = True72 break73 else:74 idx += 175 if not exist:76 if class_name in classes_names:77 if class_name in query_classes:78 query_classes[class_name] += 179 else:80 query_classes[class_name] = 181 if idx + 1 < len(query_arr) and query_arr[idx + 1].lower() == "as":82 idx += 283 idx += 184 return query_classes85 @staticmethod86 def get_classes_update_query(query_arr, classes_names):87 query_classes = {}88 idx = 189 while idx < len(query_arr) and query_arr[idx].lower() != 'set':90 if query_arr[idx] == '':91 idx += 192 continue93 class_name = None94 while idx < len(query_arr) and query_arr[idx].lower() != "set" and query_arr[idx][-1] != ',':95 if query_arr[idx] == '':96 idx += 197 continue98 if class_name is None:99 class_name = query_arr[idx]100 else:101 class_name += " " + query_arr[idx]102 idx += 1103 if idx >= len(query_arr) or query_arr[idx].lower() == "set":104 if class_name in classes_names:105 if class_name in query_classes:106 query_classes[class_name] += 1107 else:108 query_classes[class_name] = 1109 break110 else:111 if class_name is None:112 class_name = query_arr[idx][:-1]113 else:114 class_name += " " + query_arr[idx][:-1]115 if class_name in classes_names:116 if class_name in query_classes:117 query_classes[class_name] += 1118 else:119 query_classes[class_name] = 1120 idx += 1121 if idx < len(query_arr) and query_arr[idx].lower() == 'set':122 idx += 1123 while idx < len(query_arr) and query_arr[idx].lower() != 'where':124 if query_arr[idx] == '':125 idx += 1126 continue127 class_name = None128 while idx < len(query_arr) and query_arr[idx].lower() != "where" and query_arr[idx][-1] != ',':129 if query_arr[idx] == '':130 idx += 1131 continue132 if class_name is None:133 class_name = query_arr[idx]134 else:135 class_name += " " + query_arr[idx]136 idx += 1137 if idx >= len(query_arr) or query_arr[idx].lower() == "where":138 if class_name in classes_names:139 if class_name in query_classes:140 query_classes[class_name] += 1141 else:142 query_classes[class_name] = 1143 break144 else:145 if class_name is None:146 class_name = query_arr[idx][:-1]147 else:148 class_name += " " + query_arr[idx][:-1]149 if class_name in classes_names:150 if class_name in query_classes:151 query_classes[class_name] += 1152 else:153 query_classes[class_name] = 1154 idx += 1155 return query_classes156 @staticmethod157 def get_classes_insert_query(query_arr, classes_names):158 query_classes = {}159 idx = 2160 class_name = None161 while idx < len(query_arr) and query_arr[idx].lower() != 'where':162 if query_arr[idx] == '':163 idx += 1164 continue165 if class_name is None:166 class_name = query_arr[idx]167 else:168 class_name += " " + query_arr[idx]169 idx += 1170 if class_name in classes_names:171 if class_name in query_classes:172 query_classes[class_name] += 1173 else:174 query_classes[class_name] = 1175 return query_classes176 @staticmethod177 def get_classes_delete_query(query_arr, classes_names):178 query_classes = {}179 idx = 1180 class_name = None181 while idx < len(query_arr) and query_arr[idx].lower() != 'where':182 if query_arr[idx] == '':183 idx += 1184 continue185 if class_name is None:186 class_name = query_arr[idx]187 else:188 class_name += " " + query_arr[idx]189 idx += 1190 if class_name in classes_names:191 if class_name in query_classes:192 query_classes[class_name] += 1193 else:194 query_classes[class_name] = 1195 return query_classes196 @staticmethod197 def get_classes_connect_query(query_arr, classes_names):198 query_classes = {}199 idx = 1200 while idx < len(query_arr) and query_arr[idx].lower() != 'where':201 if query_arr[idx] == '':202 idx += 1203 continue204 class_name = None205 tmp_idx = idx206 exist = False207 for i in range(tmp_idx, tmp_idx + 4):208 if i >= len(query_arr) or query_arr[i].lower() == 'where':209 break210 if class_name is None:211 class_name = query_arr[i]212 else:213 class_name += " " + query_arr[i]214 if class_name in classes_names:215 if class_name in query_classes:216 query_classes[class_name] += 1217 else:218 query_classes[class_name] = 1219 idx = i220 exist = True221 break222 else:223 idx += 1224 if not exist:225 if class_name in classes_names:226 if class_name in query_classes:227 query_classes[class_name] += 1228 else:229 query_classes[class_name] = 1230 if idx + 1 < len(query_arr) and query_arr[idx + 1].lower() == "as":231 idx += 2232 idx += 1233 return query_classes234 @staticmethod235 def update_sql_matrix(matrix_classes, query_classes, classes, classes_names):236 for class_name in query_classes:237 if query_classes[class_name] > 1:238 class_key = classes_names[class_name]239 SQLParser.increment_matrix_table_cell(matrix_classes, classes[class_key], classes[class_key],240 query_classes[class_name] - 1)241 classes_combinations = list(it.combinations(query_classes.keys(), 2))242 for class_comb in classes_combinations:243 first_class = class_comb[0]244 second_class = class_comb[1]245 first_class_key = classes_names[first_class]246 second_class_key = classes_names[second_class]247 increase = max(query_classes[first_class], query_classes[second_class])248 SQLParser.increment_matrix_table_cell(matrix_classes, classes[first_class_key], classes[second_class_key], increase)249 @staticmethod250 def calculate_query_complexity(uml_json, query_classes, classes_names, query):251 classes_indexes = set()252 for class_name in query_classes:253 if query_classes[class_name] > 1:254 return 5255 classes_indexes.add(classes_names[class_name])256 query_lower = query.lower()257 if 'path' in query_lower:258 return 5259 links_array = uml_json["linkDataArray"]260 for link in links_array:261 to_node = link["to"]262 from_node = link["from"]263 if to_node in classes_indexes and from_node in classes_indexes:264 return 4265 operators = ["min", "max", "count", "type", "math"]266 if any(s in query_lower for s in operators):267 return 3268 if 'where' in query_lower:269 return 2270 return 1271 @staticmethod272 def parse(sql_json, uml_json):273 classes = {}274 classes_names = {}275 query_classes = {}276 queries_complexity = {}277 idx = 0 # index of class in matrix278 for node in uml_json["nodeDataArray"]:279 if "type" in node and (node["type"] == "Class" or node["type"] == "Association Class"):280 classes[node["key"]] = [node["name"], idx]281 classes_names[node["name"]] = node["key"]282 idx += 1283 matrix_classes = np.zeros((idx, idx))284 for key in sql_json:285 if sql_json[key]['selectable']:286 query = sql_json[key]['query']287 _RE_COMBINE_WHITESPACE = re.compile(r"\s+")288 query = _RE_COMBINE_WHITESPACE.sub(" ", query).strip()289 query_arr = re.split("[, ]", query)290 if query_arr[0].lower() == 'return':291 query_classes = SQLParser.get_classes_return_query(query_arr, classes_names)292 elif query_arr[0].lower() == 'update':293 query = query.replace(",", ", ")294 query = query.replace(" ,", ",")295 query = _RE_COMBINE_WHITESPACE.sub(" ", query).strip()296 query_arr = query.split(" ")297 query_classes = SQLParser.get_classes_update_query(query_arr, classes_names)298 elif query_arr[0].lower() == 'insert':299 query_classes = SQLParser.get_classes_insert_query(query_arr, classes_names)300 elif query_arr[0].lower() == 'delete':301 query_classes = SQLParser.get_classes_delete_query(query_arr, classes_names)302 elif query_arr[0].lower() == 'connect':303 query_classes = SQLParser.get_classes_connect_query(query_arr, classes_names)304 else:305 continue306 SQLParser.update_sql_matrix(matrix_classes, query_classes, classes, classes_names)307 complexity = SQLParser.calculate_query_complexity(uml_json, query_classes, classes_names, query)308 queries_complexity[key] = complexity309 res = {310 'classes': json.dumps(classes),311 'matrix_classes': json.dumps(dict(enumerate(matrix_classes.flatten(), 1))),312 'shape': matrix_classes.shape[0],313 'queries_complexity': queries_complexity314 }...
training_utils.py
Source:training_utils.py
1import itertools2import random3import logging4from collections import defaultdict5from enum import Enum6from pathlib import Path7from typing import List8from flair.data import Dictionary, Sentence9from functools import reduce10class Metric(object):11 def __init__(self, name):12 self.name = name13 self._tps = defaultdict(int)14 self._fps = defaultdict(int)15 self._tns = defaultdict(int)16 self._fns = defaultdict(int)17 def add_tp(self, class_name):18 self._tps[class_name] += 119 def add_tn(self, class_name):20 self._tns[class_name] += 121 def add_fp(self, class_name):22 self._fps[class_name] += 123 def add_fn(self, class_name):24 self._fns[class_name] += 125 def get_tp(self, class_name=None):26 if class_name is None:27 return sum([self._tps[class_name] for class_name in self.get_classes()])28 return self._tps[class_name]29 def get_tn(self, class_name=None):30 if class_name is None:31 return sum([self._tns[class_name] for class_name in self.get_classes()])32 return self._tns[class_name]33 def get_fp(self, class_name=None):34 if class_name is None:35 return sum([self._fps[class_name] for class_name in self.get_classes()])36 return self._fps[class_name]37 def get_fn(self, class_name=None):38 if class_name is None:39 return sum([self._fns[class_name] for class_name in self.get_classes()])40 return self._fns[class_name]41 def precision(self, class_name=None):42 if self.get_tp(class_name) + self.get_fp(class_name) > 0:43 return round(self.get_tp(class_name) / (self.get_tp(class_name) + self.get_fp(class_name)), 4)44 return 0.045 def recall(self, class_name=None):46 if self.get_tp(class_name) + self.get_fn(class_name) > 0:47 return round(self.get_tp(class_name) / (self.get_tp(class_name) + self.get_fn(class_name)), 4)48 return 0.049 def f_score(self, class_name=None):50 if self.precision(class_name) + self.recall(class_name) > 0:51 return round(2 * (self.precision(class_name) * self.recall(class_name))52 / (self.precision(class_name) + self.recall(class_name)), 4)53 return 0.054 def accuracy(self, class_name=None):55 if self.get_tp(class_name) + self.get_fp(class_name) + self.get_fn(class_name) > 0:56 return round(57 (self.get_tp(class_name))58 / (self.get_tp(class_name) + self.get_fp(class_name) + self.get_fn(class_name)),59 4)60 return 0.061 def micro_avg_f_score(self):62 return self.f_score(None)63 def macro_avg_f_score(self):64 class_f_scores = [self.f_score(class_name) for class_name in self.get_classes()]65 macro_f_score = sum(class_f_scores) / len(class_f_scores)66 return macro_f_score67 def micro_avg_accuracy(self):68 return self.accuracy(None)69 def macro_avg_accuracy(self):70 class_accuracy = [self.accuracy(class_name) for class_name in self.get_classes()]71 if len(class_accuracy) > 0:72 return round(sum(class_accuracy) / len(class_accuracy), 4)73 return 0.074 def get_classes(self) -> List:75 all_classes = set(itertools.chain(*[list(keys) for keys76 in [self._tps.keys(), self._fps.keys(), self._tns.keys(),77 self._fns.keys()]]))78 all_classes = [class_name for class_name in all_classes if class_name is not None]79 all_classes.sort()80 return all_classes81 def to_tsv(self):82 return '{}\t{}\t{}\t{}'.format(83 self.precision(),84 self.recall(),85 self.accuracy(),86 self.micro_avg_f_score(),87 )88 @staticmethod89 def tsv_header(prefix=None):90 if prefix:91 return '{0}_PRECISION\t{0}_RECALL\t{0}_ACCURACY\t{0}_F-SCORE'.format(92 prefix)93 return 'PRECISION\tRECALL\tACCURACY\tF-SCORE'94 @staticmethod95 def to_empty_tsv():96 return '\t_\t_\t_\t_'97 def __str__(self):98 all_classes = self.get_classes()99 all_classes = [None] + all_classes100 all_lines = [101 '{0:<10}\ttp: {1} - fp: {2} - fn: {3} - tn: {4} - precision: {5:.4f} - recall: {6:.4f} - accuracy: {7:.4f} - f1-score: {8:.4f}'.format(102 self.name if class_name is None else class_name,103 self.get_tp(class_name), self.get_fp(class_name), self.get_fn(class_name), self.get_tn(class_name),104 self.precision(class_name), self.recall(class_name), self.accuracy(class_name),105 self.f_score(class_name))106 for class_name in all_classes]107 return '\n'.join(all_lines)108class EvaluationMetric(Enum):109 MICRO_ACCURACY = 'micro-average accuracy'110 MICRO_F1_SCORE = 'micro-average f1-score'111 MACRO_ACCURACY = 'macro-average accuracy'112 MACRO_F1_SCORE = 'macro-average f1-score'113class WeightExtractor(object):114 def __init__(self, directory: Path, number_of_weights: int = 10):115 self.weights_file = init_output_file(directory, 'weights.txt')116 self.weights_dict = defaultdict(lambda: defaultdict(lambda: list()))117 self.number_of_weights = number_of_weights118 def extract_weights(self, state_dict, iteration):119 for key in state_dict.keys():120 vec = state_dict[key]121 weights_to_watch = min(self.number_of_weights, reduce(lambda x, y: x * y, list(vec.size())))122 if key not in self.weights_dict:123 self._init_weights_index(key, state_dict, weights_to_watch)124 for i in range(weights_to_watch):125 vec = state_dict[key]126 for index in self.weights_dict[key][i]:127 vec = vec[index]128 value = vec.item()129 with open(self.weights_file, 'a') as f:130 f.write('{}\t{}\t{}\t{}\n'.format(iteration, key, i, float(value)))131 def _init_weights_index(self, key, state_dict, weights_to_watch):132 indices = {}133 i = 0134 while len(indices) < weights_to_watch:135 vec = state_dict[key]136 cur_indices = []137 for x in range(len(vec.size())):138 index = random.randint(0, len(vec) - 1)139 vec = vec[index]140 cur_indices.append(index)141 if cur_indices not in list(indices.values()):142 indices[i] = cur_indices143 i += 1144 self.weights_dict[key] = indices145def clear_embeddings(sentences: List[Sentence], also_clear_word_embeddings=False):146 """147 Clears the embeddings from all given sentences.148 :param sentences: list of sentences149 """150 for sentence in sentences:151 sentence.clear_embeddings(also_clear_word_embeddings=also_clear_word_embeddings)152def init_output_file(base_path: Path, file_name: str) -> Path:153 """154 Creates a local file.155 :param base_path: the path to the directory156 :param file_name: the file name157 :return: the created file158 """159 base_path.mkdir(parents=True, exist_ok=True)160 file = base_path / file_name161 open(file, "w", encoding='utf-8').close()162 return file163def convert_labels_to_one_hot(label_list: List[List[str]], label_dict: Dictionary) -> List[List[int]]:164 """165 Convert list of labels (strings) to a one hot list.166 :param label_list: list of labels167 :param label_dict: label dictionary168 :return: converted label list169 """170 return [[1 if l in labels else 0 for l in label_dict.get_items()] for labels in label_list]171def log_line(log):172 log.info('-' * 100)173def add_file_handler(log, output_file):174 init_output_file(output_file.parents[0], output_file.name)175 fh = logging.FileHandler(output_file)176 fh.setLevel(logging.INFO)177 formatter = logging.Formatter('%(asctime)-15s %(message)s')178 fh.setFormatter(formatter)...
classDict.py
Source:classDict.py
1##################################################################2### class_dic3##################################################################4#class_dic = {5# '11100': {'class_name': 'Continuous Urban Fabric (S.L. &gt; 80%)','train_id': 1},6# '11210': {'class_name': 'Discontinuous Dense Urban Fabric (S.L. : 50% - 80%)','train_id': 2},7# '11220': {'class_name': 'Discontinuous Medium Density Urban Fabric (S.L. : 30% - 50%)','train_id': 3},8# '11230': {'class_name': 'Discontinuous Low Density Urban Fabric (S.L. : 10% - 30%)','train_id': 4},9# '11240': {'class_name': 'Discontinuous Very Low Density Urban Fabric (S.L. &lt; 10%)','train_id': 5},10# '11300': {'class_name': 'Isolated Structures', 'train_id': 6},11# '12100': {'class_name': 'Industrial, commercial, public, military and private units','train_id': 7},12# '12210': {'class_name': 'Fast transit roads and associated land','train_id': 8},13# '12220': {'class_name': 'Other roads and associated land', 'train_id': 8},14# '12230': {'class_name': 'Railways and associated land', 'train_id': 10},15# '12300': {'class_name': 'Port areas', 'train_id': 11},16# '12400': {'class_name': 'Airports', 'train_id': 12},17# '13100': {'class_name': 'Mineral extraction and dump sites', 'train_id': 13},18# '13300': {'class_name': 'Construction sites', 'train_id': 14},19# '13400': {'class_name': 'Land without current use', 'train_id': 15},20# '14100': {'class_name': 'Green urban areas', 'train_id': 16},21# '14200': {'class_name': 'Sports and leisure facilities', 'train_id': 17},22# '21000': {'class_name': 'Arable land (annual crops)', 'train_id': 18},23# '22000': {'class_name': 'Permanent crops (vineyards, fruit trees, olive groves)','train_id': 19},24# '23000': {'class_name': 'Pastures', 'train_id': 20},25# '24000': {'class_name': 'Complex and mixed cultivation patterns','train_id': 21},26# '25000': {'class_name': 'Orchards at the fringe of urban classes','train_id': 22},27# '31000': {'class_name': 'Forests', 'train_id': 23},28# '32000': {'class_name': 'Herbaceous vegetation associations (natural grassland, moors...)','train_id': 24},29# '33000': {'class_name': 'Open spaces with little or no vegetations (beaches, dunes, bare rocks, glaciers)','train_id': 25},30# '40000': {'class_name': 'Wetland', 'train_id': 26},31# '50000': {'class_name': 'Water bodies', 'train_id': 27}32#}33#class_dict = {34# '11100': {'class_name': 'Continuous Urban Fabric (S.L. &gt; 80%)','train_id': 1},35# '11210': {'class_name': 'Discontinuous Dense Urban Fabric (S.L. : 50% - 80%)','train_id': 2},36# '11220': {'class_name': 'Discontinuous Medium Density Urban Fabric (S.L. : 30% - 50%)','train_id': 3},37# '11230': {'class_name': 'Discontinuous Low Density Urban Fabric (S.L. : 10% - 30%)','train_id': 4},38# '11240': {'class_name': 'Discontinuous Very Low Density Urban Fabric (S.L. &lt; 10%)','train_id': 5},39# '11300': {'class_name': 'Isolated Structures', 'train_id': 6},40# '12100': {'class_name': 'Industrial, commercial, public, military and private units','train_id': 7},41# '12210': {'class_name': 'Fast transit roads and associated land','train_id': 8},42# '12220': {'class_name': 'Other roads and associated land', 'train_id': 8},43# '12230': {'class_name': 'Railways and associated land', 'train_id': 9},44# '12300': {'class_name': 'Port areas', 'train_id': 10},45# '12400': {'class_name': 'Airports', 'train_id': 11},46# '13100': {'class_name': 'Mineral extraction and dump sites', 'train_id': 12},47# '13300': {'class_name': 'Construction sites', 'train_id': 13},48# '13400': {'class_name': 'Land without current use', 'train_id': 14},49# '14100': {'class_name': 'Green urban areas', 'train_id': 15},50# '14200': {'class_name': 'Sports and leisure facilities', 'train_id': 16},51# '21000': {'class_name': 'Arable land (annual crops)', 'train_id': 17},52# '22000': {'class_name': 'Permanent crops (vineyards, fruit trees, olive groves)','train_id': 18},53# '23000': {'class_name': 'Pastures', 'train_id': 19},54# '24000': {'class_name': 'Complex and mixed cultivation patterns','train_id': 20},55# '25000': {'class_name': 'Orchards at the fringe of urban classes','train_id': 21},56# '31000': {'class_name': 'Forests', 'train_id': 22},57# '32000': {'class_name': 'Herbaceous vegetation associations (natural grassland, moors...)','train_id': 23},58# '33000': {'class_name': 'Open spaces with little or no vegetations (beaches, dunes, bare rocks, glaciers)','train_id': 24},59# '40000': {'class_name': 'Wetland', 'train_id': 25},60# '50000': {'class_name': 'Water bodies', 'train_id': 26}61#}62class_dict={63 '11100': {'train_id': 1, 'class_name': 'Continuous Urban Fabric (S.L. &gt; 80%)'},64 '11210': {'train_id': 2, 'class_name': 'Discontinuous Dense Urban Fabric (S.L. : 50% - 80%)'},65 '11220': {'train_id': 3, 'class_name': 'Discontinuous Medium Density Urban Fabric (S.L. : 30% - 50%)'},66 '11230': {'train_id': 4, 'class_name': 'Discontinuous Low Density Urban Fabric (S.L. : 10% - 30%)'},67 '11240': {'train_id': 5, 'class_name': 'Discontinuous Very Low Density Urban Fabric (S.L. &lt; 10%)'},68 '11300': {'train_id': 6, 'class_name': 'Isolated Structures'},69 '12100': {'train_id': 7, 'class_name': 'Industrial, commercial, public, military and private units'},70 '12210': {'train_id': 8, 'class_name': 'Fast transit roads and associated land'},71 '12220': {'train_id': 9, 'class_name': 'Other roads and associated land'},72 '12230': {'train_id': 10, 'class_name': 'Railways and associated land'},73 '12300': {'train_id': 11, 'class_name': 'Port areas'},74 '12400': {'train_id': 12, 'class_name': 'Airports'},75 '13100': {'train_id': 13, 'class_name': 'Mineral extraction and dump sites'},76 '13300': {'train_id': 14, 'class_name': 'Construction sites'},77 '13400': {'train_id': 15, 'class_name': 'Land without current use'},78 '14100': {'train_id': 16, 'class_name': 'Green urban areas'},79 '14200': {'train_id': 17, 'class_name': 'Sports and leisure facilities'},80 '21000': {'train_id': 18, 'class_name': 'Arable land (annual crops)'},81 '22000': {'train_id': 19, 'class_name': 'Permanent crops (vineyards, fruit trees, olive groves)'},82 '23000': {'train_id': 20, 'class_name': 'Pastures'},83 '24000': {'train_id': 21, 'class_name': 'Complex and mixed cultivation patterns'},84 '25000': {'train_id': 22, 'class_name': 'Orchards at the fringe of urban classes'},85 '31000': {'train_id': 23, 'class_name': 'Forests'},86 '32000': {'train_id': 24, 'class_name': 'Herbaceous vegetation associations (natural grassland, moors...)'},87 '33000': {'train_id': 25, 'class_name': 'Open spaces with little or no vegetations (beaches, dunes, bare rocks, glaciers)'},88 '40000': {'train_id': 26, 'class_name': 'Wetland'},89 '50000': {'train_id': 27, 'class_name': 'Water bodies'}...
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