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')