def test_BP8_tinoco(self):
try:
import cvxpy_tinoco # analysis:ignore
except:
raise SkipTest("Modeler 'cvxpy_old' not installed")
z, p, k = ntf_fir_minmax(order=8,
osr=32,
f0=0.2,
show_progress=False,
modeler='cvxpy_old')
e_k = 1
e_z = [
2.94348009789963e-01 + 9.14543800193135e-01j,
2.94348009789963e-01 - 9.14543800193135e-01j,
6.76745367518838e-01 + 0.00000000000000e+00j,
2.46816733211163e-01 + 5.50000475735513e-01j,
2.46816733211163e-01 - 5.50000475735513e-01j,
-4.58884378359569e-01 + 4.10643263860101e-01j,
-4.58884378359569e-01 - 4.10643263860101e-01j,
-5.91022020183929e-01 + 0.00000000000000e+00j
]
e_z = np.sort(e_z)
z = np.sort(z)
np.testing.assert_allclose(k, e_k, rtol=1e-6)
np.testing.assert_allclose(z, e_z, rtol=2e-4)
def test_LP8_picos(self):
try:
import picos # analysis:ignore
except:
raise SkipTest("Modeler 'picos' not installed")
z, p, k = ntf_fir_minmax(order=8, show_progress=False,
modeler='picos')
e_k = 1
e_z = [990.349427225477e-003 + 69.0500612157020e-003j,
990.349427225477e-003 - 69.0500612157020e-003j,
166.532844346146e-003 + 591.251073811726e-003j,
166.532844346146e-003 - 591.251073811726e-003j,
-259.915617496087e-003 + 503.342225950477e-003j,
-259.915617496087e-003 - 503.342225950477e-003j,
-512.031157651993e-003 + 194.699627385223e-003j,
-512.031157651993e-003 - 194.699627385223e-003j]
e_z = np.sort(e_z)
z = np.sort(z)
np.testing.assert_allclose(k, e_k, rtol=1e-6)
np.testing.assert_allclose(z, e_z, rtol=1e-3)
def test_MB16_tinoco(self):
try:
import cvxpy_tinoco # analysis:ignore
except:
raise SkipTest("Modeler 'cvxpy_old' not installed")
z, p, k = ntf_fir_minmax(order=8, osr=64, f0=[0.1, 0.2],
show_progress=False, modeler='cvxpy_old')
e_k = 1
e_z = [7.201593591543093e-01 + 4.847692940420519e-01j,
7.201593591543093e-01 - 4.847692940420519e-01j,
2.503311061929155e-01 + 8.210993460982702e-01j,
2.503311061929155e-01 - 8.210993460982702e-01j,
-4.140998358546186e-01 + 4.504982522544850e-01j,
-4.140998358546186e-01 - 4.504982522544850e-01j,
-5.755598430642412e-01,
-1.159555247895333e-01]
e_z = np.sort(e_z)
z = np.sort(z)
np.testing.assert_allclose(k, e_k, rtol=1e-6)
np.testing.assert_allclose(z, e_z, rtol=1e-3, atol=3e-2)
def test_LP8_picos(self):
try:
import picos # analysis:ignore
except:
raise SkipTest("Modeler 'picos' not installed")
z, p, k = ntf_fir_minmax(order=8, show_progress=False,
modeler='picos')
e_k = 1
e_z = [990.349427225477e-003 + 69.0500612157020e-003j,
990.349427225477e-003 - 69.0500612157020e-003j,
166.532844346146e-003 + 591.251073811726e-003j,
166.532844346146e-003 - 591.251073811726e-003j,
-259.915617496087e-003 + 503.342225950477e-003j,
-259.915617496087e-003 - 503.342225950477e-003j,
-512.031157651993e-003 + 194.699627385223e-003j,
-512.031157651993e-003 - 194.699627385223e-003j]
e_z = np.sort(e_z)
z = np.sort(z)
np.testing.assert_allclose(k, e_k, rtol=1e-6)
np.testing.assert_allclose(z, e_z, rtol=1e-3)
def test_MB16_tinoco(self):
try:
import cvxpy_tinoco # analysis:ignore
except:
raise SkipTest("Modeler 'cvxpy_old' not installed")
z, p, k = ntf_fir_minmax(order=8, osr=64, f0=[0.1, 0.2],
show_progress=False, modeler='cvxpy_old')
e_k = 1
e_z = [7.201593591543093e-01 + 4.847692940420519e-01j,
7.201593591543093e-01 - 4.847692940420519e-01j,
2.503311061929155e-01 + 8.210993460982702e-01j,
2.503311061929155e-01 - 8.210993460982702e-01j,
-4.140998358546186e-01 + 4.504982522544850e-01j,
-4.140998358546186e-01 - 4.504982522544850e-01j,
-5.755598430642412e-01,
-1.159555247895333e-01]
e_z = np.sort(e_z)
z = np.sort(z)
np.testing.assert_allclose(k, e_k, rtol=1e-6)
np.testing.assert_allclose(z, e_z, rtol=1e-3, atol=3e-2)
def test_BP8_tinoco(self):
try:
import cvxpy_tinoco # analysis:ignore
except:
raise SkipTest("Modeler 'cvxpy_old' not installed")
z, p, k = ntf_fir_minmax(order=8, osr=32, f0=0.2, show_progress=False,
modeler='cvxpy_old')
e_k = 1
e_z = [2.94348009789963e-01 + 9.14543800193135e-01j,
2.94348009789963e-01 - 9.14543800193135e-01j,
6.76745367518838e-01 + 0.00000000000000e+00j,
2.46816733211163e-01 + 5.50000475735513e-01j,
2.46816733211163e-01 - 5.50000475735513e-01j,
-4.58884378359569e-01 + 4.10643263860101e-01j,
-4.58884378359569e-01 - 4.10643263860101e-01j,
-5.91022020183929e-01 + 0.00000000000000e+00j]
e_z = np.sort(e_z)
z = np.sort(z)
np.testing.assert_allclose(k, e_k, rtol=1e-6)
np.testing.assert_allclose(z, e_z, rtol=2e-4)