def __init__(self, projects_group, path_nwp, nwp_resolution, path_nwp_group, dates_ts, area_group, njobs=1): self.path_nwp = path_nwp self.path_nwp_group = path_nwp_group self.nwp_resolution = nwp_resolution self.area = area_group self.projects_group = projects_group self.njobs = njobs self.logger = create_logger(logger_name='log_ecmwf', abs_path=self.path_nwp_group, logger_path='log_nwp.log', write_type='a') self.dates_ts = dates_ts if isinstance(dates_ts, pd.Timestamp) else self.define_dates(dates_ts)
def __init__(self, projects_group, path_nwp, nwp_resolution, path_nwp_group, dates_ts, area_group, n_jobs=1): self.path_nwp = path_nwp self.path_nwp_group = path_nwp_group self.nwp_resolution = nwp_resolution self.area = area_group self.projects_group = projects_group self.n_jobs = n_jobs self.logger = create_logger(logger_name=f'log_skiron', abs_path=self.path_nwp_group, logger_path='log_nwp.log', write_type='a') self.dates_ts = self.define_dates(dates_ts)
def __init__(self, static_data): """ Parameters ---------- static_data: python dict contains all the information required to load the power measurement for specific project(s). """ self.static_data = static_data # dict containing information about project paths, model structure and training # params, input file, see in util_database_timos.py and config_timos.py self.file_data = static_data[ 'data_file_name'] # input .csv file PROBLEM_TYPE + '_ts.csv' i.e. wind_ts.csv self.project_owner = static_data[ 'project_owner'] # Name of project owner or research program i.e. my_projects or CROSSBOW self.projects_group = static_data[ 'projects_group'] # Name of the country self.area_group = static_data[ 'area_group'] # coordinates of the country self.version_group = static_data['version_group'] self.version_model = static_data['version_model'] self.weather_in_data = static_data[ 'weather_in_data'] # True if input file contains more columns than the power output column self.nwp_model = static_data['NWP_model'] self.nwp_resolution = static_data['NWP_resolution'] self.data_variables = static_data[ 'data_variables'] # Variable names used self.projects = [ ] # list containing all the parks, we're interested in. Each park is considered as a project. self.use_rated = True self.model_type = self.static_data['type'] self.sys_folder = self.static_data['sys_folder'] self.path_nwp = self.static_data['path_nwp'] self.path_group = self.static_data['path_group'] self.path_nwp_group = self.static_data['path_nwp_group'] self.group_static_data = [] self.logger = create_logger( logger_name=f'ProjectInitManager_{self.model_type}', abs_path=self.path_group, logger_path=f'log_{self.projects_group}.log', write_type='a')
def __init__(self, projects_group, projects, data, path_nwp, nwp_model, nwp_resolution, data_variables, njobs=1, test=False, dates=None): self.projects = projects self.is_for_test = test self.projects_group = projects_group self.data = data self.path_nwp = path_nwp self.nwp_model = nwp_model self.nwp_resolution = nwp_resolution self.compress = True if self.nwp_resolution == 0.05 else False self.n_jobs = njobs self.variables = data_variables self.logger = create_logger(logger_name=__name__, abs_path=self.path_nwp, logger_path=f'log_{self.projects_group}.log', write_type='a') if not self.data is None: self.dates = self.check_dates() elif not dates is None: self.dates = dates
def __init__(self, static_data): self.istrained = False self.add_individual_rules = static_data['clustering'][ 'add_rules_indvidual'] self.import_external_rules = static_data['clustering'][ 'import_external_rules'] self.njobs = static_data['clustering']['njobs'] self.resampling = static_data['resampling'] self.path_fuzzy = static_data['path_fuzzy_models'] self.file_fuzzy = static_data['clustering']['cluster_file'] self.type = static_data['type'] self.static_data = static_data self.logger = create_logger(logger_name='log_fuzzy.log', abs_path=self.path_fuzzy, logger_path='log_fuzzy.log', write_type='w') try: self.load() except: pass
def __init__(self, static_data, is_test: bool): self.is_test = is_test self.static_data = static_data self.projects = ProjectGroupInit(self.static_data) self.projects.initialize() self.model_type = self.projects.model_type self.path_group = self.projects.path_group self.projects_group = self.projects.projects_group self.data = self.projects.data if not hasattr(self, 'data_eval') and hasattr(self.projects, 'data_eval'): self.data_eval = self.projects.data_eval self.data_variables = self.projects.data_variables # List of dicts. Each dict has information about a different project self.group_static_data = self.projects.group_static_data self.logger = create_logger( logger_name=f'ProjectsDataManager_{self.model_type}', write_type='a', abs_path=self.path_group, logger_path=f'log_{self.projects_group}.log')
def __init__(self, static_data, is_test=False): self.is_test = is_test self.static_data = static_data self.file_data = static_data['data_file_name'] self.project_owner = static_data['project_owner'] self.projects_group = static_data['projects_group'] self.area_group = static_data['area_group'] self.version_group = static_data['version_group'] self.version_model = static_data['version_model'] self.weather_in_data = static_data['weather_in_data'] self.nwp_model = static_data['NWP_model'] self.nwp_resolution = static_data['NWP_resolution'] self.data_variables = static_data['data_variables'] self.model_type = self.static_data['type'] self.sys_folder = self.static_data['sys_folder'] self.path_nwp = self.static_data['path_nwp'] self.path_group = self.static_data['path_group'] self.path_nwp_group = self.static_data['path_nwp_group'] self.logger = create_logger( logger_name=f'NwpManager_{self.model_type}', abs_path=self.path_group, logger_path='log_nwp.log')