def bmi_block_reconstruction_error(idx, cls=tasks.BMIReconstruction, n_iter=None):
te = performance._get_te(idx)
if n_iter == None or n_iter == -1: n_iter = len(te.hdf.root.task)
gen = genfns.sim_target_seq_generator_multi(8, 1000)
task = cls(te, n_iter, gen)
task.init()
error = task.calc_recon_error(verbose=False)
abs_max_error = np.max(np.abs(error))
return abs_max_error
def bmi_block_reconstruction_error(idx,
cls=tasks.BMIReconstruction,
n_iter=None):
te = performance._get_te(idx)
if n_iter == None or n_iter == -1: n_iter = len(te.hdf.root.task)
gen = genfns.sim_target_seq_generator_multi(8, 1000)
task = cls(te, n_iter, gen)
task.init()
error = task.calc_recon_error(verbose=False)
abs_max_error = np.max(np.abs(error))
return abs_max_error
from tasks import bmi_recon_tasks
reload(clda)
reload(train)
reload(bmi)
reload(ppfdecoder)
idx = 2306
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-b", "--block", dest="block", help="Database ID number of block to run on", type=int, metavar="FILE", default=2306)
(options, args) = parser.parse_args()
idx = options.block
te = performance._get_te(idx)
print(te)
T = len(te.hdf.root.task)
n_iter = 100 #T
#n_iter = 15782
task_msgs = te.hdf.root.task_msgs[:]
update_bmi_msgs = task_msgs[task_msgs['msg'] == 'update_bmi']
state_transitions = task_msgs[~(task_msgs['msg'] == 'update_bmi')]
# class CLDAPPFReconstruction(bmi_recon_tasks.BMIReconstruction):
# pass
# class CLDAPPFReconstruction(bmimultitasks.CLDAControlPPFContAdapt):
# def __init__(self, *args, **kwargs):
# super(CLDAPPFReconstruction, self).__init__(*args, **kwargs)
import tasks
from analysis import performance
from tasks import generatorfunctions as genfns
import numpy as np
from tasks import bmi_recon_tasks
from riglib.bmi import clda
reload(bmi_recon_tasks)
reload(tasks)
cls=tasks.KFRMLCGRecon
idx = 5275
te = performance._get_te(idx)
### TODO some CLDA blocks have a changing half life...
updater = clda.KFRML(None, None, te.batch_time, te.half_life[0])
updater.init(te.seed_decoder)
param_hist = te.hdf.root.clda
C_error = []
Q_error = []
decoder = te.seed_decoder
for k in range(len(param_hist))[5::6]:
intended_kin = param_hist[k]['intended_kin']
spike_counts = param_hist[k]['spike_counts_batch']
if not np.any(np.isnan(intended_kin)) and not np.any(np.isnan(spike_counts)):
import argparse
parser = argparse.ArgumentParser(description='Analyze perf correlates of KF plant properties')
parser.add_argument('--n_iter', help='', type=int, action="store", default=-1)
args = parser.parse_args()
n_iter = args.n_iter
tests = []
# tests.append(TestFixedPPF())
# tests.append(TestFixedKF())
# tests.append(TestPPFCLDA())
# tests.append(TestRML)
# tests.append(TestRMLWithAssist())
# tests.append(TestJointRMLWithAssist())
te = performance._get_te(3040)
#tests = [TestJointRML(), TestJointRMLWithAssist()]
#tests = [TestFixedPPF(), TestPPFCLDA()]
#tests = [TestPPFCLDA(), TestRML()]
# tests = [TestRMLCGWithAssist()]
tests = [TestPPFCLDA()]
test_suite = unittest.TestSuite(tests)
unittest.TextTestRunner(verbosity=2).run(test_suite)
from riglib import experiment
from features.generator_features import Autostart
from features.hdf_features import SaveHDF
from features.plexon_features import PlexonBMI
from tasks import generatorfunctions as genfns
from analysis import performance
# Tell linux to use Display 0 (the monitor physically attached to the
# machine. Otherwise, if you are connected remotely, it will try to run
# the graphics through SSH, which doesn't work for some reason.
import os
os.environ['DISPLAY'] = ':0'
task = models.Task.objects.get(name='clda_kf_ofc_tentacle_rml_trial')
base_class = task.get()
feats = [SaveHDF, PlexonBMI, Autostart]
Exp = experiment.make(base_class, feats=feats)
#params.trait_norm(Exp.class_traits())
params = dict(session_length=30, arm_visible=True, arm_class='RobotArmGen2D',
assist_level=(2., 2.), assist_time=60., rand_start=(0.,0.), max_tries=1)
gen = genfns.sim_target_seq_generator_multi(8, 1000)
exp = Exp(gen, **params)
exp.decoder = performance._get_te(3979).decoder
exp.start()
self.assertTrue(abs_max_error < 1e-10)
import argparse
parser = argparse.ArgumentParser(
description='Analyze perf correlates of KF plant properties')
parser.add_argument('--n_iter', help='', type=int, action="store", default=-1)
args = parser.parse_args()
n_iter = args.n_iter
tests = []
# tests.append(TestFixedPPF())
# tests.append(TestFixedKF())
# tests.append(TestPPFCLDA())
# tests.append(TestRML)
# tests.append(TestRMLWithAssist())
# tests.append(TestJointRMLWithAssist())
te = performance._get_te(3040)
#tests = [TestJointRML(), TestJointRMLWithAssist()]
#tests = [TestFixedPPF(), TestPPFCLDA()]
#tests = [TestPPFCLDA(), TestRML()]
# tests = [TestRMLCGWithAssist()]
tests = [TestPPFCLDA()]
test_suite = unittest.TestSuite(tests)
unittest.TextTestRunner(verbosity=2).run(test_suite)
from tasks import generatorfunctions as genfns
from analysis import performance
# Tell linux to use Display 0 (the monitor physically attached to the
# machine. Otherwise, if you are connected remotely, it will try to run
# the graphics through SSH, which doesn't work for some reason.
import os
os.environ['DISPLAY'] = ':0'
task = models.Task.objects.get(name='clda_kf_ofc_tentacle_rml_trial')
base_class = task.get()
feats = [SaveHDF, PlexonBMI, Autostart]
Exp = experiment.make(base_class, feats=feats)
#params.trait_norm(Exp.class_traits())
params = dict(session_length=30,
arm_visible=True,
arm_class='RobotArmGen2D',
assist_level=(2., 2.),
assist_time=60.,
rand_start=(0., 0.),
max_tries=1)
gen = genfns.sim_target_seq_generator_multi(8, 1000)
exp = Exp(gen, **params)
exp.decoder = performance._get_te(3979).decoder
exp.start()
