def test_sort_2lenses_resonant_caustic():
separation = 1
mass_ratio = 1
caustics, critical_curves = microlcaustics.compute_2_lenses_caustics_points(separation, mass_ratio,
resolution=1000)
resonant_caustic, resonant_cc = microlcaustics.sort_2lenses_resonant_caustic(caustics, critical_curves)
assert len(resonant_caustic) == 4000
assert len(resonant_cc) == 4000
def test_find_area_of_interest_around_caustics():
separation = 0.98
mass_ratio = 10 ** -3.98
caustics, critical_curves = microlcaustics.compute_2_lenses_caustics_points(separation, mass_ratio, resolution=10)
area_of_interest = microlcaustics.find_area_of_interest_around_caustics(caustics, secure_factor=0.1)
expected_area = np.array([[-0.16472971920662491, 0.1487364691472782], [-0.11476825367160942, 0.11476825367161236],
[-0.0079966250296733543, 1.4710455076283324e-15]]
)
assert np.allclose(expected_area, area_of_interest)
def test_sort_2lenses_wide_caustic():
separation = 50.8
mass_ratio = 0.8
caustics, critical_curves = microlcaustics.compute_2_lenses_caustics_points(
separation, mass_ratio, resolution=1000)
central_caustic, wide_caustic, central_cc, wide_cc = microlcaustics.sort_2lenses_wide_caustics(
caustics, critical_curves)
assert len(central_caustic) == 2000
assert len(central_cc) == 2000
assert len(wide_caustic) == 2000
assert len(wide_cc) == 2000
def test_find_area_of_interest_around_caustics():
separation = 0.98
mass_ratio = 10**-3.98
caustics, critical_curves = microlcaustics.compute_2_lenses_caustics_points(
separation, mass_ratio, resolution=10)
area_of_interest = microlcaustics.find_area_of_interest_around_caustics(
caustics, secure_factor=0.1)
expected_area = np.array([[-1.6504915797261186, 0.14873646914727098],
[-0.11476825367160942, 0.11476825367161236],
[-0.75087755528942379, 1.4710455076283324e-15]])
assert np.allclose(expected_area, area_of_interest)
def test_sort_2lenses_close_caustics():
separation = 0.8
mass_ratio = 10**-7
caustics, critical_curves = microlcaustics.compute_2_lenses_caustics_points(
separation, mass_ratio, resolution=1000)
central_caustic, close_top_caustic, close_bottom_caustic, central_cc, close_top_cc, close_bottom_cc = \
microlcaustics.sort_2lenses_close_caustics(caustics, critical_curves)
assert len(central_caustic) == 2000
assert len(central_cc) == 2000
assert len(close_top_caustic) == 1000
assert len(close_top_cc) == 1000
assert len(close_bottom_caustic) == 1000
assert len(close_bottom_cc) == 1000
def test_compute_2_lenses_caustics_points():
separation = 1
mass_ratio = 1
caustics, critical_curves = microlcaustics.compute_2_lenses_caustics_points(
separation, mass_ratio, resolution=10)
expected_caustics = np.array(
[[
0.34062502 - 3.94430453e-31j, -0.34062502 - 3.38963670e-32j,
0.00000000 - 5.89979840e-01j, 0.00000000 + 5.89979840e-01j
],
[
0.32489215 - 3.74174390e-03j, -0.32489215 + 3.74174390e-03j,
-0.14198333 - 6.13822318e-01j, 0.14198333 + 6.13822318e-01j
],
[
0.28067735 - 3.06011670e-02j, -0.28067735 + 3.06011670e-02j,
-0.21082253 - 6.50713550e-01j, 0.21082253 + 6.50713550e-01j
],
[
0.21790294 - 1.08073125e-01j, -0.21790294 + 1.08073125e-01j,
-0.20257117 - 6.36141383e-01j, 0.20257117 + 6.36141383e-01j
],
[
0.16039580 - 2.74010967e-01j, -0.16039580 + 2.74010967e-01j,
-0.15982495 - 5.07258799e-01j, 0.15982495 + 5.07258799e-01j
],
[
0.15982495 - 5.07258799e-01j, -0.15982495 + 5.07258799e-01j,
-0.16039580 - 2.74010967e-01j, 0.16039580 + 2.74010967e-01j
],
[
0.20257117 - 6.36141383e-01j, -0.20257117 + 6.36141383e-01j,
-0.21790294 - 1.08073125e-01j, 0.21790294 + 1.08073125e-01j
],
[
0.21082253 - 6.50713550e-01j, -0.21082253 + 6.50713550e-01j,
-0.28067735 - 3.06011670e-02j, 0.28067735 + 3.06011670e-02j
],
[
0.14198333 - 6.13822318e-01j, -0.14198333 + 6.13822318e-01j,
-0.32489215 - 3.74174390e-03j, 0.32489215 + 3.74174390e-03j
],
[
0.00000000 - 5.89979840e-01j, 0.00000000 + 5.89979840e-01j,
-0.34062502 - 4.74549138e-31j, 0.34062502 - 1.77493704e-30j
]])
expected_cc = np.array([
[
1.27122988e+00 + 2.89236268e-16j,
-1.27122988e+00 + 2.77844475e-17j,
-1.48013047e-18 + 3.40625019e-01j, 3.30645600e-17 - 3.40625019e-01j
],
[
1.21229332e+00 + 2.87839951e-01j,
-1.21229332e+00 - 2.87839951e-01j,
-7.73913354e-02 + 3.56017165e-01j, 7.73913354e-02 - 3.56017165e-01j
],
[
1.04372694e+00 + 5.28204089e-01j,
-1.04372694e+00 - 5.28204089e-01j,
-1.47894990e-01 + 3.98235002e-01j, 1.47894990e-01 - 3.98235002e-01j
],
[
7.91336472e-01 + 6.75204341e-01j,
-7.91336472e-01 - 6.75204341e-01j,
-2.17214969e-01 + 4.66363434e-01j, 2.17214969e-01 - 4.66363434e-01j
],
[
5.09656858e-01 + 6.85437065e-01j,
-5.09656858e-01 - 6.85437065e-01j,
-3.11897539e-01 + 5.71750678e-01j, 3.11897539e-01 - 5.71750678e-01j
],
[
3.11897539e-01 + 5.71750678e-01j,
-3.11897539e-01 - 5.71750678e-01j,
-5.09656858e-01 + 6.85437065e-01j, 5.09656858e-01 - 6.85437065e-01j
],
[
2.17214969e-01 + 4.66363434e-01j,
-2.17214969e-01 - 4.66363434e-01j,
-7.91336472e-01 + 6.75204341e-01j, 7.91336472e-01 - 6.75204341e-01j
],
[
1.47894990e-01 + 3.98235002e-01j,
-1.47894990e-01 - 3.98235002e-01j,
-1.04372694e+00 + 5.28204089e-01j, 1.04372694e+00 - 5.28204089e-01j
],
[
7.73913354e-02 + 3.56017165e-01j,
-7.73913354e-02 - 3.56017165e-01j,
-1.21229332e+00 + 2.87839951e-01j, 1.21229332e+00 - 2.87839951e-01j
],
[
5.42176191e-17 + 3.40625019e-01j, 5.38347107e-18 - 3.40625019e-01j,
-1.27122988e+00 + 2.05998413e-16j, 1.27122988e+00 - 5.72458747e-16j
]
])
assert np.allclose(caustics, expected_caustics)
assert np.allclose(critical_curves, expected_cc)
