def testFacts(self):
np.testing.assert_allclose(cons(np.array([])), np.array([1]))
np.testing.assert_allclose(cons(np.array([1])),
np.array([1, -2.718281828459046]))
np.testing.assert_allclose(cons(np.array([2])),
np.array([1, -7.389056098930650]))
np.testing.assert_allclose(cons(np.array([3])),
np.array([1, -20.085536923187668]))
def calculate_common_part(a, psi, t_r):
fil_poles = np.array([psi * t_r])
hden = np.real(cons(fil_poles))
causal = np.array([x for x in fil_poles if np.real(x) < 0])
n_causal = np.array([x for x in fil_poles if np.real(x) > 0])
h_dc = cons(causal)
h_dnc = cons(n_causal)
reconstruct = {'num': np.real(cons(a * t_r)), 'den': np.array([np.real(h_dc), np.real(h_dnc)])}
return reconstruct, hden
def test_inputs_from_hrf_parameters_1(self):
input = np.array([-0.27, -0.27, -0.4347 - 0.3497j, -0.4347 + 0.3497j])
expected_output = [
1, -2.743302542144524, 2.859320053352163, -1.348960571338628,
0.244289813077911
]
np.testing.assert_allclose(cons(input), expected_output)
def test_inputs_from_hrf_parameters_3(self):
input = np.array(
[-0.27, -0.27, -0.4347 - 0.3497j, -0.4347 + 0.3497j, 0])
expected_output = [
1, -3.743302542144524, 5.602622595496687, -4.208280624690792,
1.593250384416538, -0.244289813077911
]
np.testing.assert_allclose(cons(input), expected_output)
def test_inputs_from_hrf_parameters_6(self):
input = np.array([
-1.020408163265306, -3.092145949288806,
-0.324675324675325 - 0.548716683350910j,
-0.324675324675325 + 0.548716683350910j, 0
])
expected_output = [
1, -2.639165427154841, 2.678459114317751, -1.271489046879362,
0.240744669196138, -0.008549309479686
]
np.testing.assert_allclose(cons(input), expected_output)
def test_inputs_from_hrf_parameters_4(self):
input = np.array([
-1.020408163265306, -3.092145949288806,
-0.324675324675325 - 0.548716683350910j,
-0.324675324675325 + 0.548716683350910j
])
expected_output = [
1, -1.639165427154841, 1.039293687162910, -0.232195359716452,
0.008549309479686
]
np.testing.assert_allclose(cons(input), expected_output)
def test_inputs_from_hrf_parameters_5(self):
input = np.array([-11.898107445013801])
expected_output = [1, -6.803268190346306e-06]
np.testing.assert_allclose(cons(input), expected_output)
def test_inputs_from_hrf_parameters_2(self):
input = np.array([-0.1336])
expected_output = [1, -0.874939970605710]
np.testing.assert_allclose(cons(input), expected_output)
def block_filter(a, psi, t_r):
reconstruct, hden = calculate_common_part(a, psi, t_r)
hnum = cons(np.append(a * t_r, 0))
_, h = signal.freqz(hnum, hden, 1024)
maxeig = np.max(np.power(np.abs(h), 2))
return {'num': np.real(hnum), 'den': reconstruct['den']}, reconstruct, maxeig
def spike_filter(a, psi, t_r):
reconstruct, hden = calculate_common_part(a, psi, t_r)
hnum = cons(a * t_r)
_, h = signal.freqz(hnum, hden, 1024)
maxeig = np.max(np.power(np.abs(h), 2))
return reconstruct, reconstruct, maxeig
