def _get_load(self): if options.gef_zone is None: load = gef12.load() else: load = gef12.load_solved_non_nan().load['zone_{}'.format( options.gef_zone)] return pd.DataFrame({'Load': load})
def load(): global bcall, dist, gef, gef_1, gef_3, gef_sys bcall = bc.load_remove_zeros() bcall = bcall / 1000 dist = ul.total_experiment_load()[0]['Load'] gef = gefcom.load_solved_non_nan().load gef_1 = gef['zone_1'] gef_3 = gef['zone_3'] gef_sys = gef.sum(axis=1)
def load_gef_dataset(): gefdata = gefcom.load_solved_non_nan() gef1 = pd.DataFrame({'Load': gefdata.load.zone_1, 'Temperature': gefdata.temp.station_2}) gef3 = pd.DataFrame({'Load': gefdata.load.zone_3, 'Temperature': gefdata.temp.station_11}) gef_sys = pd.DataFrame({'Load': gefdata.load.sum(axis=1), 'Temperature': gefdata.temp.mean(axis=1)}) return gef1, gef3, gef_sys
def load_gef_dataset(): gefdata = gefcom.load_solved_non_nan() gef1 = pd.DataFrame({ 'Load': gefdata.load.zone_1, 'Temperature': gefdata.temp.station_2 }) gef3 = pd.DataFrame({ 'Load': gefdata.load.zone_3, 'Temperature': gefdata.temp.station_11 }) gef_sys = pd.DataFrame({ 'Load': gefdata.load.sum(axis=1), 'Temperature': gefdata.temp.mean(axis=1) }) return gef1, gef3, gef_sys
def __init__(self, *args): self._temp = gef12.load_solved_non_nan().temp self._temp_columns = self._temp.columns GEFCOMSolvedNonNanMeanTempDataset.__init__(self, *args)
def _get_load(self): if options.gef_zone is None: load = gef12.load() else: load = gef12.load_solved_non_nan().load['zone_{}'.format(options.gef_zone)] return pd.DataFrame({'Load': load})