def testSnrFuncs(self):
"""test for signal to noise ratio functions"""
# trivial
data_triv = sp.ones((3, 10))
snr_triv_test = sp.ones(3)
assert_equal(
snr_peak(data_triv, 1.0),
snr_triv_test)
assert_equal(
snr_power(data_triv, 1.0),
snr_triv_test)
assert_equal(
snr_maha(data_triv, sp.eye(data_triv.shape[1])),
snr_triv_test)
# application
data = sp.array([
sp.sin(sp.linspace(0.0, 2 * sp.pi, 100)),
sp.sin(sp.linspace(0.0, 2 * sp.pi, 100)) * 2,
sp.sin(sp.linspace(0.0, 2 * sp.pi, 100)) * 5,
])
assert_equal(
snr_peak(data, 1.0),
sp.absolute(data).max(axis=1))
assert_equal(
snr_power(data, 1.0),
sp.sqrt((data * data).sum(axis=1) / data.shape[1]))
assert_almost_equal(
snr_maha(data, sp.eye(data.shape[1])),
sp.sqrt((data * data).sum(axis=1) / data.shape[1]))
def testSnrFuncs(self):
"""test for signal to noise ratio functions"""
# trivial
data_triv = sp.ones((3, 10))
snr_triv_test = sp.ones(3)
assert_equal(snr_peak(data_triv, 1.0), snr_triv_test)
assert_equal(snr_power(data_triv, 1.0), snr_triv_test)
assert_equal(snr_maha(data_triv, sp.eye(data_triv.shape[1])),
snr_triv_test)
# application
data = sp.array([
sp.sin(sp.linspace(0.0, 2 * sp.pi, 100)),
sp.sin(sp.linspace(0.0, 2 * sp.pi, 100)) * 2,
sp.sin(sp.linspace(0.0, 2 * sp.pi, 100)) * 5,
])
assert_equal(snr_peak(data, 1.0), sp.absolute(data).max(axis=1))
assert_equal(snr_power(data, 1.0),
sp.sqrt((data * data).sum(axis=1) / data.shape[1]))
assert_almost_equal(snr_maha(data, sp.eye(data.shape[1])),
sp.sqrt((data * data).sum(axis=1) / data.shape[1]))
nep = merge_epochs(nep)
ndet.update(data[id_trl], epochs=nep)
spks.append(trial_spks)
spks_info.append(sp.vstack([[id_trl] * trial_st.size, trial_st]).T)
print "\tprocessed %s" % db.get_fname_for_id(id_trl)
except Exception, e:
raise RuntimeError("error processing %s\n%s" % (db.get_fname_for_id(id_trl), e))
finally:
del trial_st
spks_info = sp.vstack(spks_info)
spks = sp.vstack(spks)
print "found %d spikes in total" % spks.shape[0]
print "done."
print "checking SNR of spikes"
spks_snr = snr_maha(spks, ndet.get_icmx(tf=tf))
good_spks = spks_snr > snr
n_spks = spks.shape[0]
spks = spks[good_spks]
spks_info = spks_info[good_spks].astype(int)
print "keeping %d of %d spikes with SNR > %f" % (spks.shape[0], n_spks, snr)
if save is True:
ndet_pkl = cPickle.dumps(ndet)
arc = openFile(ARC_PATH, "w")
arc.createArray(arc.root, "spks", spks)
arc.createArray(arc.root, "spks_info", spks_info)
arc.createArray(arc.root, "ndet_pkl", ndet_pkl)
arc.close()
return spks, spks_info, ndet
