Coverage for aixcalibuha/utils/configuration.py: 70%

1""" 

2Module to with configs and functions to read configs for objects in this repository. 

3""" 

4import os 

5import collections 

6import toml 

7import numpy as np 

8from ebcpy import data_types 

9from aixcalibuha import Goals, CalibrationClass, TunerParas 

10 

11tsd_config = {"data": "TODO: Specify the path to the target values measured", 

12 "key": None, 

13 "sheet_name": None, 

14 "sep": ","} 

15 

16kwargs_calibrator = {"timedelta": 0, 

17 "save_files": False, 

18 "verbose_logging": True, 

19 "show_plot": True, 

20 "create_tsd_plot": True, 

21 "save_tsd_plot": True, 

22 "fail_on_error": False, 

23 "ret_val_on_error": np.NAN} 

24 

25# Specify kwargs for multiple-class-calibration 

26kwargs_multiple_classes = {"merge_multiple_classes": True, 

27 "fix_start_time": 0, 

28 "timedelta": 0} 

29 

30default_input_config = {"sim_input_names": None, 

31 "sim_data_path": None, 

32 "meas_input_names": None, 

33 "meas_input_data": tsd_config, 

34 } 

35 

36default_cal_class_config = {"name": "TODO: Specify the name of the calibration class", 

37 "start_time": "TODO: Specify the start time of the class - e.g 0", 

38 "stop_time": "TODO: Specify the end time of the class", 

39 "goals": {"meas_target_data": tsd_config, 

40 "variable_names": "TODO: Specify variable names", 

41 "weightings": "TODO: Insert null if you don´t need special weightings. " 

42 "Else specify which goal get´s which weighting through a list"}, 

43 "tuner_paras": {"names": 

44 "TODO: Specify the names of the tuner parameters list", 

45 "initial_values": 

46 "TODO: Specify the inital values of the tuner parameters list", 

47 "bounds": 

48 "TODO: Specify the boundaries of the tuner parameters as a list of tuples"}} 

49 

50default_calibration_config = { 

51 "statistical_measure": "TODO: Specify the statistical " 

52 "measure for calibration (RMSE, MAE, etc.)", 

53 "calibration_classes": [default_cal_class_config], 

54 "start_time_method": 'fixstart', 

55 "settings": kwargs_calibrator, 

56 "settings multiple classes": kwargs_multiple_classes 

57} 

58 

59kwargs_scipy_dif_evo = {"maxiter": 30, 

60 "popsize": 5, 

61 "mutation": (0.5, 1), 

62 "recombination": 0.7, 

63 "seed": None, 

64 "polish": True, 

65 "init": 'latinhypercube', 

66 "atol": 0} 

67 

68kwargs_dlib_min = {"num_function_calls": int(1e9), 

69 "solver_epsilon": 0} 

70 

71kwargs_scipy_min = {"tol": None, 

72 "options": {"maxfun": 1}, 

73 "constraints": None, 

74 "jac": None, 

75 "hess": None, 

76 "hessp": None} 

77 

78default_optimization_config = {"framework": "TODO: Choose the framework for calibration", 

79 "method": "TODO: Choose the method of the framework", 

80 "settings": { 

81 "scipy_differential_evolution": kwargs_scipy_dif_evo, 

82 "dlib_minimize": kwargs_dlib_min, 

83 "scipy_minimize": kwargs_scipy_min} 

84 } 

85 

86default_sim_config = {"packages": None, 

87 "model_name": None, 

88 "type": "DymolaAPI", 

89 "dymola_path": None, 

90 "dymola_interface_path": None, 

91 "equidistant_output": True, 

92 "show_window": False, 

93 "get_structural_parameters": True 

94 } 

95 

96default_config = { 

97 "Working Directory": "TODO: Add the path where you want to work here", 

98 "SimulationAPI": default_sim_config, 

99 "Optimization": default_optimization_config, 

100 "Input Data": default_input_config, 

101 "Calibration": default_calibration_config 

102} 

103 

104 

105def get_goals_from_config(config): 

106 """ 

107 Read the data for a Goals object. 

108 

109 :param dict config: 

110 Config holding the following cols for 

111 - meas_target_data 

112 - variable_names 

113 - Optional: weightings 

114 :return: Goals goals 

115 Loaded Goals object 

116 """ 

117 config_mtd = config["meas_target_data"] 

118 mtd = data_types.TimeSeriesData(**config_mtd) 

119 return Goals(meas_target_data=mtd, 

120 variable_names=config["variable_names"], 

121 statistical_measure=config["statistical_measure"], 

122 weightings=config.get("weightings", None)) 

123 

124 

125def get_tuner_paras_from_config(config): 

126 """ 

127 Read the data for a TunerParas object. 

128 

129 :param dict config: 

130 Config holding the following cols for 

131 - names 

132 - initial_values 

133 - bounds 

134 :return: TunerParas tuner_paras 

135 Loaded Goals object 

136 """ 

137 return TunerParas(names=config["names"], 

138 initial_values=config["initial_values"], 

139 bounds=config["bounds"]) 

140 

141 

142def get_calibration_classes_from_config(config): 

143 """ 

144 Read the data for a CalibrationClass object. 

145 

146 :param list config: 

147 List of dicts with configs holding the following cols for 

148 - names 

149 - start_time 

150 - stop_time 

151 - Optional: goals, tuner_paras, relevant_intervals 

152 :return: TunerParas tuner_paras 

153 Loaded Goals object 

154 """ 

155 cal_classes = [] 

156 for cal_class_config in config: 

157 goals, tuner_paras = None, None 

158 if "goals" in cal_class_config: 

159 goals = get_goals_from_config(cal_class_config["goals"]) 

160 if "tuner_paras" in cal_class_config: 

161 tuner_paras = get_tuner_paras_from_config(cal_class_config["tuner_paras"]) 

162 cal_classes.append( 

163 CalibrationClass(name=cal_class_config["name"], 

164 start_time=cal_class_config["start_time"], 

165 stop_time=cal_class_config["stop_time"], 

166 goals=goals, 

167 tuner_paras=tuner_paras, 

168 relevant_intervals=cal_class_config.get("relevant_intervals", None))) 

169 return cal_classes 

170 

171 

172def write_config(filepath, config): 

173 """ 

174 Write the given config to the filepath. 

175 If the file already exists, the data is recursively 

176 updated. 

177 

178 :param str,os.path.normpath filepath: 

179 Filepath with the config. 

180 :param: dict config: 

181 Config to be saved 

182 """ 

183 if os.path.exists(filepath): 

184 existing_config = read_config(filepath) 

185 if existing_config: 

186 config = _update(existing_config, config) 

187 

188 with open(filepath, "a+") as file: 

189 file.seek(0) 

190 file.truncate() 

191 toml.dump(config, file) 

192 

193 

194def read_config(filepath): 

195 """ 

196 Read the given file and return the toml-config 

197 

198 :param str,os.path.normpath filepath: 

199 Filepath with the config. 

200 :return: dict config: 

201 Loaded config 

202 """ 

203 with open(filepath, "r") as file: 

204 config = toml.load(file) 

205 return config 

206 

207 

208def _update(dic, new_dic): 

209 """Recursively update a given dictionary with a new one""" 

210 for key, val in new_dic.items(): 

211 if isinstance(val, collections.abc.Mapping): 

212 dic[key] = _update(dic.get(key, {}), val) 

213 else: 

214 dic[key] = val 

215 return dic