exp_variance.py 3.62 KB
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# -*- coding: utf-8 -*-
"""

.. moduleauthor:: Valentin Emiya
"""
import numpy as np

from yafe import Experiment

from tffpy.datasets import get_mix, get_dataset
from tffpy.experiments.exp_solve_tff import SolveTffExperiment


class VarianceExperiment(SolveTffExperiment):
    def __init__(self, force_reset=False, suffix=''):
        SolveTffExperiment.__init__(self,
                                    force_reset=force_reset,
                                    suffix='Variance' + suffix)

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    def display_results(self):
        res = self.load_results(array_type='xarray')
        res = res.squeeze()
        print('std(sdr_tff):', float(res.sel(measure='sdr_tff').std()))
        print('std(sdr_tffo):', float(res.sel(measure='sdr_tffo').std()))
        print('std(sdr_tffe):', float(res.sel(measure='sdr_tffe').std()))
        print('std(is_tff):', float(res.sel(measure='is_tff').std()))
        print('std(is_tffo):', float(res.sel(measure='is_tffo').std()))
        print('std(is_tffe):', float(res.sel(measure='is_tffe').std()))

    def plot_results(self):
        # No more need for this method
        pass

    def plot_task(self, idt, fontsize=16):
        # No more need for this method
        pass

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    @staticmethod
    def get_experiment(setting='full', force_reset=False):
        assert setting in ('full', 'light')

        dataset = get_dataset()
        # Set task parameters
        data_params = dict(loc_source='bird',
                           wideband_src='car')
        problem_params = dict(win_choice='gauss 256',
                              # win_choice=['gauss 256', 'hann 512'],
                              wb_to_loc_ratio_db=8,
                              n_iter_closing=3, n_iter_opening=3,
                              closing_first=True,
                              delta_mix_db=0,
                              delta_loc_db=40,
                              or_mask=True,
                              crop=None,
                              fig_dir=None)
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        solver_params = dict(tol_subregions=[None, 1e-5],
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                             tolerance_arrf=1e-3,
                             proba_arrf=1 - 1e-4,
                             rand_state=np.arange(100))
        if setting == 'light':
            problem_params['win_choice'] = 'gauss 64',
            problem_params['crop'] = 4096
            problem_params['delta_loc_db'] = 20
            problem_params['wb_to_loc_ratio_db'] = 16
            solver_params['tolerance_arrf'] = 1e-2
            solver_params['proba_arrf'] = 1 - 1e-2
            solver_params['rand_state'] = np.arange(3)

        # Create Experiment
        suffix = '' if setting == 'full' else '_Light'
        exp = VarianceExperiment(force_reset=force_reset,
                                 suffix=suffix)
        exp.add_tasks(data_params=data_params,
                      problem_params=problem_params,
                      solver_params=solver_params)
        exp.generate_tasks()
        return exp


def create_and_run_light_experiment():
    """
    Create a light experiment and run it
    """
    exp = VarianceExperiment.get_experiment(setting='light', force_reset=True)
    print('*' * 80)
    print('Created experiment')
    print(exp)
    print(exp.display_status())

    print('*' * 80)
    print('Run task 0')
    task_data = exp.get_task_data_by_id(idt=0)
    print(task_data.keys())
    print(task_data['task_params']['data_params'])

    problem = exp.get_problem(
        **task_data['task_params']['problem_params'])
    print(problem)

    print('*' * 80)
    print('Run all')
    exp.launch_experiment()

    print('*' * 80)
    print('Collect and plot results')
    exp.collect_results()