run_awera_eval_2.py

"""
Run eval functions after all processing...
"""

import os
from AWERA import config, ChainAWERA
import numpy as np
# TODO make clear how each module runs with the inout of the previous
# power_model.load() .generate() how is the object made/passed


if __name__ == '__main__':
    # read config from jobnumber
    # 8 small jobs
    # 4 big jobs
    # loc_id = int(os.environ['LOC_ID'])

    # settings = {
    #     'Processing': {'n_cores': 2},  # 10
    #     'Data': {'n_locs': -1,
    #              'location_type': 'europe'},
    #     'Clustering': {
    #         'n_clusters': 8,  # TODO choose before predict labels...
    #         'training': {
    #             'n_locs': 5000,
    #             'location_type': 'europe'
    #             }
    #         },
    #     'IO': {'result_dir':
    #            "/cephfs/user/s6lathim/AWERA_results/"}
    # }
    n_clusters = 8
    n_l = 1

    # n_locs = 1 # [200, 500, 1000, 5000]
    n_l = 1  # n_locs[settings_id]
    scan_tag = 'final_U_90_'
    settings = {
        'Data': {'n_locs': 1,
                 'location_type': 'Marseille'},
        'Clustering': {
            'n_clusters': n_clusters,
            'training': {
                'n_locs': n_l,
                'location_type': 'Marseille'
                }
            },
        'Processing': {'n_cores': n_clusters},
        'General': {'ref_height': 100},
        # 'Power':{ 'bounds': bounds},
        'IO': {
            'result_dir': "/cephfs/user/s6lathim/AWERA_results/",
            'format': {
                'plot_output':
                    scan_tag + config.IO.format.plot_output,
                'power_curve':
                    scan_tag + config.IO.format.power_curve,
                'cut_wind_speeds':
                    scan_tag + config.IO.format.cut_wind_speeds,
                'refined_cut_wind_speeds':
                    scan_tag + config.IO.format.refined_cut_wind_speeds,
                # Only Power Production - no chain plot output for now
                'plot_output_data':
                    scan_tag + config.IO.format.plot_output_data,
                'training_plot_output':
                    scan_tag + config.IO.format.training_plot_output,
                'freq_distr':
                    scan_tag + config.IO.format.freq_distr,
                    }
                }
        }
    # settings['General'] = {'use_memmap': True}
    # settings[
    print(settings)
    # Update settings to config
    config.update(settings)

    # working_title = 'eval_locs_{}'.format(loc_id)  # 'run_profile'

    from AWERA.eval.evaluation import evalAWERA
    e = evalAWERA(config)
    # working_title = 'sliding_window_eval'
    # e.sliding_window_power(time_window=24,  # Hours for hourly data
    #                        at_night=False,  # True,
    #                        power_lower_bar=None,
    #                        power_lower_perc=15,
    #                        read_if_possible=True,
    #                        locs_slice=None,  # (loc_id, 1000)) # ,
    #                        read_from_slices=(23, 1000))  #
    # ----------------------------------------------------------
    e.step_towing_AEP(power_consumption=20,
                      bridge_times=[1, 2, 3, 4, 5])
    e.cut_in_out_distr()
    # ----------------------------------------------------------
    # e.aep_map()
    # print('Map plotted.')
    # e.power_freq()

    # profiler.disable()
    # # # Write profiler output
    # file_name = (
    #     config.IO.result_dir
    #     + config.IO.format.plot_output.format(
    #               data_info=config.Data.data_info,
    #               data_info_training=config.Clustering.training.data_info,
    #               settings_info=config.Clustering.training.settings_info)
    #     .replace('.pdf', '{}.profile'.format(loc_id))
    #     )
    # with open(file_name.format(title='run_profile'), 'w') as f:
    #     stats = pstats.Stats(profiler, stream=f)
    #     stats.strip_dirs()
    #     stats.sort_stats('cumtime')
    #     stats.print_stats('py:', .1)
    # print('Profile output written to: ',
    #       file_name.format(title=working_title))


    #plt.show()