diff --git a/python/tffpy/experiments/exp_approx.py b/python/tffpy/experiments/exp_approx.py
deleted file mode 100644
index ab069ba45d4388b2013fb7c567eb18447e37648d..0000000000000000000000000000000000000000
--- a/python/tffpy/experiments/exp_approx.py
+++ /dev/null
@@ -1,130 +0,0 @@
-# -*- 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 ApproxExperiment(SolveTffExperiment):
- def __init__(self, force_reset=False, suffix=''):
- SolveTffExperiment.__init__(self,
- force_reset=force_reset,
- suffix='Approx' + suffix)
-
- def display_results(self):
- res = self.load_results(array_type='xarray')
- res = res.squeeze()
- tff_list = res.to_dict()['coords']['solver_tol_subregions']['data']
- tol_list = res.to_dict()['coords']['solver_tolerance_arrf']['data']
- for measure in ['sdr_tff', 'sdr_tffo', 'sdr_tffe',
- 'is_tff', 'is_tffo', 'is_tffe']:
- for solver_tol_subregions in tff_list:
- for tol in tol_list:
- mean_res = float(res.sel(
- solver_tolerance_arrf=tol,
- solver_tol_subregions=solver_tol_subregions,
- measure=measure).mean())
- std_res = float(res.sel(
- solver_tolerance_arrf=tol,
- solver_tol_subregions=solver_tol_subregions,
- measure=measure).std())
- t_res = float(res.sel(
- solver_tolerance_arrf=tol,
- solver_tol_subregions=solver_tol_subregions,
- measure='t_arrf').mean())
- rank_res = float(res.sel(
- solver_tolerance_arrf=tol,
- solver_tol_subregions=solver_tol_subregions,
- measure='rank_sum').mean())
- if solver_tol_subregions is None:
- measure_name = measure + '-1'
- else:
- measure_name = measure + '-P'
- print('{}: mean={:.2f} std={:.2g} tol={}, t={}, rk={}'
- .format(measure_name, mean_res, std_res, tol,
- t_res, rank_res))
-
- 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
-
- @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)
- solver_params = dict(tol_subregions=[None, 1e-5],
- tolerance_arrf=list(10**np.arange(-3, -0.5, 1))
- + list(10**np.arange(-1, 0, 0.2)),
- proba_arrf=1 - 1e-4,
- rand_state=np.arange(3))
- 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-1, 1e-2]
- solver_params['proba_arrf'] = 1 - 1e-2
- solver_params['tol_subregions'] = 1e-5
-
- # Create Experiment
- suffix = '' if setting == 'full' else '_Light'
- exp = ApproxExperiment(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 = ApproxExperiment.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()