def test_kcsd2d_init(self):
method = 'KCSD3D'
result = csd.estimate_csd(lfp=self.lfp, method=method,
**self.params[method])
self.assertEqual(result.t_start, 0.0 * pq.s)
self.assertEqual(result.sampling_rate, 1000 * pq.Hz)
self.assertEqual(len(result.times), 1)
def test_kcsd2d_init(self):
method = 'KCSD3D'
result = csd.estimate_csd(lfp=self.lfp, method=method,
**self.params[method])
self.assertEqual(result.t_start, 0.0 * pq.s)
self.assertEqual(result.sampling_rate, 1000 * pq.Hz)
self.assertEqual(len(result.times), 1)
def test_moi_estimate(self):
result = CSD.estimate_csd(self.an_sigs, method='MoIKCSD',
MoI_iters=10, lambd=0.0,
gdx=0.2, gdy=0.2)
self.assertEqual(result.t_start, 0.0 * pq.s)
self.assertEqual(result.sampling_rate, 1000 * pq.Hz)
self.assertEqual(result.times, [0.] * pq.s)
self.assertEqual(len(result.annotations.keys()), 2)
def test_moi_estimate(self):
result = CSD.estimate_csd(self.an_sigs, method='MoIKCSD',
MoI_iters=10, lambd=0.0,
gdx=0.2, gdy=0.2)
self.assertEqual(result.t_start, 0.0 * pq.s)
self.assertEqual(result.sampling_rate, 1000 * pq.Hz)
self.assertEqual(result.times, [0.] * pq.s)
self.assertEqual(len(result.annotations.keys()), 2)
def test_kcsd1d_estimate(self, cv_params={}):
self.test_params.update(cv_params)
result = CSD.estimate_csd(self.an_sigs, method=self.test_method,
**self.test_params)
self.assertEqual(result.t_start, 0.0 * pq.s)
self.assertEqual(result.sampling_rate, 1000 * pq.Hz)
self.assertEqual(result.times, [0.] * pq.s)
self.assertEqual(len(result.annotations.keys()), 1)
true_csd = self.csd_profile(result.annotations['x_coords'])
rms = np.linalg.norm(np.array(result[0, :]) - true_csd)
rms /= np.linalg.norm(true_csd)
self.assertLess(rms, 0.5, msg='RMS between trueCSD and estimate > 0.5')
def test_kcsd1d_estimate(self, cv_params={}):
self.test_params.update(cv_params)
result = CSD.estimate_csd(self.an_sigs, method=self.test_method,
**self.test_params)
self.assertEqual(result.t_start, 0.0 * pq.s)
self.assertEqual(result.sampling_rate, 1000 * pq.Hz)
self.assertEqual(result.times, [0.] * pq.s)
self.assertEqual(len(result.annotations.keys()), 1)
true_csd = self.csd_profile(result.annotations['x_coords'])
rms = np.linalg.norm(np.array(result[0, :]) - true_csd)
rms /= np.linalg.norm(true_csd)
self.assertLess(rms, 0.5, msg='RMS between trueCSD and estimate > 0.5')
