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adding tighter error tolerances and adding checks for imrpl

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This commit is contained in:
Deepak Mallubhotla 2020-07-14 10:59:33 -05:00
parent 622af16142
commit a7c33fb5df
4 changed files with 56 additions and 4 deletions
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15
pynam/noise/im_ref.py Normal file
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@ -0,0 +1,15 @@
from typing import Callable
import numpy as np
import pynam.noise.zeta
def get_im_ref_p(eps: Callable[[float], complex]) -> Callable[[float], float]:
zeta_p = pynam.noise.zeta.get_zeta_p_function(eps)
def im_ref_p(u: float) -> float:
zeta_p_val = zeta_p(u)
return np.imag((np.pi * 1j * u - zeta_p_val) / (np.pi * 1j * u + zeta_p_val))
return im_ref_p

8
pynam/noise/zeta.py
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@ -62,10 +62,10 @@ def get_zeta_p_function(eps: Callable[[float], complex]):
def zeta_p(u: float) -> complex:
zeta_p_integrand = get_zeta_p_integrand(eps)
i1_small = pynam.util.complex_quad(lambda x: integrand1_small_x(x, u), 0, SMALL_X_BOUNDARY)
i1_big = pynam.util.complex_quad(lambda x: integrand1_big_x(x, u), SMALL_X_BOUNDARY, np.inf)
i2_small = pynam.util.complex_quad(lambda x: integrand2_small_x(x, u), 0, SMALL_X_BOUNDARY)
i2_big = pynam.util.complex_quad(lambda x: integrand2_big_x(x, u), SMALL_X_BOUNDARY, np.inf)
i1_small = pynam.util.complex_quad(lambda x: integrand1_small_x(x, u), 0, SMALL_X_BOUNDARY, epsabs=1e-12)
i1_big = pynam.util.complex_quad(lambda x: integrand1_big_x(x, u), SMALL_X_BOUNDARY, np.inf, epsabs=1e-12)
i2_small = pynam.util.complex_quad(lambda x: integrand2_small_x(x, u), 0, SMALL_X_BOUNDARY, epsabs=1e-12)
i2_big = pynam.util.complex_quad(lambda x: integrand2_big_x(x, u), SMALL_X_BOUNDARY, np.inf, epsabs=1e-12)
integral = sum(term[0] for term in [i1_small, i2_small, i1_big, i2_big])

31
tests/noise/test_im_ref.py Normal file
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@ -0,0 +1,31 @@
import numpy as np
import pytest
import pynam.dielectric
import pynam.noise.im_ref
from pynam.baskets import CalculationParams
@pytest.fixture
def im_ref_p_lindhard():
params = CalculationParams(omega=1e9, v_f=2e6, omega_p=3.544907701811032e15, tau=1e-14)
eps_l = pynam.dielectric.get_lindhard_dielectric(params)
return pynam.noise.im_ref.get_im_ref_p(eps_l)
@pytest.mark.parametrize("test_input,expected", [
# u im_ref_p_l(u)
# needs to be close in range around 1/z, so from 1e4 to 1e8
(1e4, 1.821722334939806e-8),
(1e5, 1.602855764970752e-8),
(1e6, 1.704326041013161e-8),
(1e7, 2.674124312031195e-8),
(1e8, 7.441319151047531e-8),
])
def test_im_ref_p_lindhard(im_ref_p_lindhard, test_input, expected):
actual = im_ref_p_lindhard(test_input)
np.testing.assert_allclose(
actual, expected,
rtol=1e-4, err_msg='imrp is inaccurate for Lindhard case', verbose=True
)

6
tests/noise/test_zeta.py
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@ -38,7 +38,13 @@ def zeta_p_lindhard():
@pytest.mark.parametrize("test_input,expected", [
# u zeta_p(u)
(1, 0.000199609 - 0.000199608j),
# (10, 0.00019960929309663014 - 0.00019927000998506335j),
# (100, 0.0001996175250684056 - 0.0001654898843938523j),
# (1e3, 0.0002003339895748246 + 0.003212370020888438j),
# (1e4, 0.00028616168676982363 + 0.34096962141224463j),
(1e5, 0.0025183067257958545 + 34.11087430547122j),
(1e6, 0.026829658454640887 + 3411.0870128247902j),
(1e7, 0.4292211181081069 + 341088.797211291j),
(1e8, 14.348462224076096 + 3.391157983312813e7j)
])
def test_zeta_p(zeta_p_lindhard, test_input, expected):