diff --git a/python/tffpy/experiments/exp_solve_tff.py b/python/tffpy/experiments/exp_solve_tff.py
index 188c0c007fc1911c8189480d64ca11fc482f3324..88daa6d8729ea80feafb799199df00b0ab5bb171 100644
--- a/python/tffpy/experiments/exp_solve_tff.py
+++ b/python/tffpy/experiments/exp_solve_tff.py
@@ -802,10 +802,12 @@ class Solver:
:py:meth:`~tffpy.tf_fading.GabMulTff.compute_decomposition`.
"""
- def __init__(self, tol_subregions, tolerance_arrf, proba_arrf):
+ def __init__(self, tol_subregions, tolerance_arrf, proba_arrf,
+ rand_state=0):
self.tol_subregions = tol_subregions
self.tolerance_arrf = tolerance_arrf
self.proba_arrf = proba_arrf
+ self.rand_state = rand_state
def __call__(self, x_mix, mask, dgt_params, signal_params):
"""
@@ -853,7 +855,8 @@ class Solver:
signal_params=signal_params,
tol_subregions=self.tol_subregions)
gmtff.compute_decomposition(tolerance_arrf=self.tolerance_arrf,
- proba_arrf=self.proba_arrf)
+ proba_arrf=self.proba_arrf,
+ rand_state=self.rand_state)
# Estimate energy and lambda
lambda_tff, t_lambda_tff = gmtff.compute_lambda(x_mix=x_mix)
diff --git a/python/tffpy/experiments/exp_variance.py b/python/tffpy/experiments/exp_variance.py
new file mode 100644
index 0000000000000000000000000000000000000000..1e70180e8173c8b7d1a523fba53aa8bf0540d09a
--- /dev/null
+++ b/python/tffpy/experiments/exp_variance.py
@@ -0,0 +1,88 @@
+# -*- 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)
+
+ @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,
+ 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()
diff --git a/python/tffpy/scripts/script_exp_variance.py b/python/tffpy/scripts/script_exp_variance.py
new file mode 100644
index 0000000000000000000000000000000000000000..85574904121251e7407131101c5953932689977f
--- /dev/null
+++ b/python/tffpy/scripts/script_exp_variance.py
@@ -0,0 +1,130 @@
+# -*- coding: utf-8 -*-
+# ######### COPYRIGHT #########
+# Credits
+# #######
+#
+# Copyright(c) 2020-2020
+# ----------------------
+#
+# * Laboratoire d'Informatique et Systèmes <http://www.lis-lab.fr/>
+# * Université d'Aix-Marseille <http://www.univ-amu.fr/>
+# * Centre National de la Recherche Scientifique <http://www.cnrs.fr/>
+# * Université de Toulon <http://www.univ-tln.fr/>
+#
+# Contributors
+# ------------
+#
+# * `Valentin Emiya <mailto:valentin.emiya@lis-lab.fr>`_
+# * `Ama Marina Krémé <mailto:ama-marina.kreme@lis-lab.fr>`_
+#
+# This package has been created thanks to the joint work with Florent Jaillet
+# and Ronan Hamon on other packages.
+#
+# Description
+# -----------
+#
+# Time frequency fading using Gabor multipliers
+#
+# Version
+# -------
+#
+# * tffpy version = 0.1.3
+#
+# Licence
+# -------
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program. If not, see <http://www.gnu.org/licenses/>.
+#
+# ######### COPYRIGHT #########
+"""
+Run this script to handle the main experiment :class:`SolveTffExperiment`.
+
+.. moduleauthor:: Valentin Emiya
+"""
+from yafe.utils import generate_oar_script
+
+import matplotlib.pyplot as plt
+
+from tffpy.experiments.exp_variance import \
+ VarianceExperiment, create_and_run_light_experiment
+
+
+try:
+ experiment = VarianceExperiment.get_experiment(setting='full',
+ force_reset=False)
+except RuntimeError:
+ experiment = None
+except FileNotFoundError:
+ experiment = None
+
+if __name__ == '__main__':
+ answer = 1
+ while answer > 0:
+ input_msg = '\n'.join(['1 - Create and run light experiment',
+ '2 - Display results of light experiment',
+ '3 - Full experiment: create full experiment',
+ '4 - Generate OAR script',
+ '5 - Full experiment: collect results',
+ '6 - Full experiment: download results',
+ '7 - Full experiment: display results',
+ '0 - Exit',
+ ])
+ answer = int(input(input_msg))
+ if answer == 0:
+ break
+ elif answer == 1:
+ create_and_run_light_experiment()
+ elif answer == 2:
+ light_exp = VarianceExperiment.get_experiment(
+ setting='light', force_reset=False)
+ for idt in range(light_exp.n_tasks):
+ light_exp.plot_task(idt=idt, fontsize=16)
+ plt.close('all')
+ light_exp.plot_results()
+ elif answer == 3:
+ experiment = VarianceExperiment.get_experiment(
+ setting='full', force_reset=True)
+ experiment.display_status()
+ elif answer == 4:
+ experiment.display_status()
+ batch_size = int(input('Batch size (#tasks per job)?'))
+ generate_oar_script(script_file_path=__file__,
+ xp_var_name='experiment',
+ batch_size=batch_size,
+ oar_walltime='01:00:00',
+ activate_env_command='source activate py36',
+ use_gpu=False)
+ elif answer == 5:
+ experiment.collect_results()
+ experiment.display_status()
+ elif answer == 6:
+ to_dir = str(experiment.xp_path)
+ from_dir = \
+ '/data1/home/valentin.emiya/data_exp/SolveTffExperiment/'
+ print('Run:')
+ print(' '.join(['rsync', '-rv',
+ 'valentin.emiya@sms-ext.lis-lab.fr:'
+ + from_dir,
+ to_dir]))
+ print('Or (less files):')
+ print(' '.join(['rsync', '-rv',
+ 'valentin.emiya@sms-ext.lis-lab.fr:'
+ + from_dir
+ + '*.*',
+ to_dir]))
+ elif answer == 7:
+ experiment.plot_results()
+ experiment.display_status()
+ else:
+ print('Unknown answer: ' + str(answer))
diff --git a/python/tffpy/tf_fading.py b/python/tffpy/tf_fading.py
index 7051633272272dc5e2f211f5b400245a8f89d6b6..1981b0c6ebec6b33daeef0aac145e5c20573ae65 100644
--- a/python/tffpy/tf_fading.py
+++ b/python/tffpy/tf_fading.py
@@ -138,7 +138,7 @@ class GabMulTff:
"""
return len(self.u_mat_list)
- def compute_decomposition(self, tolerance_arrf, proba_arrf):
+ def compute_decomposition(self, tolerance_arrf, proba_arrf, rand_state=0):
"""
Decompose each Gabor multiplier using a random EVD
@@ -160,8 +160,16 @@ class GabMulTff:
proba_arrf : float
Probability of error for
:py:func:`~skpomade.range_approximation.adaptive_randomized_range_finder`
+ rand_state : RandomState, int or None
+ If RandomState, random generator.
+ If int or None, random seed used to initialize the pseudo-random
+ number generator.
"""
+ if rand_state is None:
+ rand_state = np.random.RandomState(None)
+ if np.issubdtype(type(rand_state), np.dtype(int).type):
+ rand_state = np.random.RandomState(rand_state)
for i in range(self.n_areas):
print('Random EVD of Gabor multiplier #{}'.format(i))
print('#coefs in mask: {} ({:.1%} missing)'
@@ -172,7 +180,8 @@ class GabMulTff:
q_mat = adaptive_randomized_range_finder(a=self.gabmul_list[i],
tolerance=tolerance_arrf,
proba=proba_arrf, r=None,
- rand_state=0, n_cols_Q=32)
+ rand_state=rand_state,
+ n_cols_Q=32)
self.t_arrf[i] = perf_counter() - t0
print('Q shape:', q_mat.shape)
t0 = perf_counter()
@@ -188,7 +197,7 @@ class GabMulTff:
self.uh_x_list[i] = self.u_mat_list[i].T.conj() @ self.x_mix
self.t_uh_x[i] = perf_counter() - t0
- def compute_decomposition_fixed_rank(self, rank):
+ def compute_decomposition_fixed_rank(self, rank, rand_state=0):
"""
Decompose each Gabor multiplier using a random EVD with given rank
@@ -201,7 +210,16 @@ class GabMulTff:
----------
rank : int
Rank of the decompostion
+ rand_state : RandomState, int or None
+ If RandomState, random generator.
+ If int or None, random seed used to initialize the pseudo-random
+ number generator.
"""
+ if rand_state is None:
+ rand_state = np.random.RandomState(None)
+ if np.issubdtype(type(rand_state), np.dtype(int).type):
+ rand_state = np.random.RandomState(rand_state)
+
t_rrf = [None for i in range(self.n_areas)]
t_evdn = [None for i in range(self.n_areas)]
t_uh_x = [None for i in range(self.n_areas)]
@@ -214,7 +232,7 @@ class GabMulTff:
t0 = perf_counter()
q_mat = randomized_range_finder(a=self.gabmul_list[i],
n_l=rank,
- rand_state=0)
+ rand_state=rand_state)
t_rrf[i] = perf_counter() - t0
print('Q shape:', q_mat.shape)
t0 = perf_counter()