chore(release): 0.3.0

CHANGELOG.md

@@ -2,6 +2,25 @@
 
 All notable changes to this project will be documented in this file. See [standard-version](https://github.com/conventional-changelog/standard-version) for commit guidelines.
 
+## [0.3.0](https://gitea.deepak.science:2222/physics/pyewjn/compare/0.2.1...0.3.0) (2022-03-29)
+
+
+### ⚠ BREAKING CHANGES
+
+* pushes type checking earlier in the docket
+
+### Features
+
+* adds unapproximated nam calc ([20db727](https://gitea.deepak.science:2222/physics/pyewjn/commit/20db72701500da4bcf32205d7dd7baf7e911744a))
+* pushes type checking earlier in the docket ([d2dd960](https://gitea.deepak.science:2222/physics/pyewjn/commit/d2dd9600002da3e531b9946f4c388cca0cc32930))
+
+
+### Bug Fixes
+
+* fixes stuff with nam integration ([2b22267](https://gitea.deepak.science:2222/physics/pyewjn/commit/2b22267f36294270834473b68884bdca668b65fa))
+* removes unnecessary None checks ([4d59f9c](https://gitea.deepak.science:2222/physics/pyewjn/commit/4d59f9c09cfba92d5c2de54e8b4b62295a9313e4))
+* removes unnecessary None checks ([5e830f6](https://gitea.deepak.science:2222/physics/pyewjn/commit/5e830f623e185c04d170ef642bbd9323b0dd7043))
+
 ### 0.2.1 (2022-03-29)
 
 

README.md

@@ -1,3 +1,16 @@
-# pyewjn
-
-python port of `nam_analysis`
+# pyewjn
+
+[![Conventional Commits](https://img.shields.io/badge/Conventional%20Commits-1.0.0-green.svg?style=flat-square)](https://conventionalcommits.org)
+[![PyPI](https://img.shields.io/pypi/v/pyewjn?style=flat-square)](https://pypi.org/project/pyewjn/)
+[![Jenkins](https://img.shields.io/jenkins/build?jobUrl=https%3A%2F%2Fjenkins.deepak.science%2Fjob%2Fgitea-physics%2Fjob%2Fpyewjn%2Fjob%2Fmaster&style=flat-square)](https://jenkins.deepak.science/job/gitea-physics/job/pyewjn/job/master/)
+![Jenkins tests](https://img.shields.io/jenkins/tests?compact_message&jobUrl=https%3A%2F%2Fjenkins.deepak.science%2Fjob%2Fgitea-physics%2Fjob%2Fpyewjn%2Fjob%2Fmaster%2F&style=flat-square)
+![Jenkins Coverage](https://img.shields.io/jenkins/coverage/cobertura?jobUrl=https%3A%2F%2Fjenkins.deepak.science%2Fjob%2Fgitea-physics%2Fjob%2Fpyewjn%2Fjob%2Fmaster%2F&style=flat-square)
+![Maintenance](https://img.shields.io/maintenance/yes/2022?style=flat-square)
+
+python port of `nam_analysis`
+
+## Getting started
+
+`poetry install` to start locally
+
+Commit using [Conventional Commits](https://www.conventionalcommits.org/en/v1.0.0/), and when commits are on master, release with `doo release`.

do.sh

@@ -30,7 +30,7 @@ release() {
 }
 
 all() {
-	build && test
+	build && fmt && test
 }
 
 "$@" # <- execute the task

pyewjn/baskets.py

@@ -27,13 +27,13 @@ class CalculationParams(object):
 
 	def __init__(
 		self,
-		omega: float = None,
-		omega_p: float = None,
-		tau: float = None,
-		v_f: float = None,
-		t_rel: float = None,
-		t_c: float = None,
-		dipole_moment: float = None,
+		omega: float,
+		omega_p: float,
+		tau: float,
+		v_f: float,
+		t_rel: float = 0.8,
+		t_c: float = 1e11,
+		dipole_moment: float = 1,
 	):
 		"""Creates parameter object, SI units
 
@@ -46,6 +46,19 @@ class CalculationParams(object):
 		:param dipole_moment:
 		"""
 
+		if omega is None:
+			raise ValueError("omega expected to not be None")
+		if v_f is None:
+			raise ValueError("v_f expected to not be None")
+		if omega_p is None:
+			raise ValueError("omega_p expected to not be None")
+		if tau is None:
+			raise ValueError("tau expected to not be None")
+		if t_rel is None:
+			raise ValueError("relative temp expected to not be None")
+		if t_c is None:
+			raise ValueError("critical temp expected to not be None")
+
 		self.omega = omega
 		self.omega_p = omega_p
 		self.tau = tau

pyewjn/dielectric/__init__.py

@@ -1,4 +1,11 @@
-from pyewjn.dielectric.nam_dielectric_coefficient_approximator import get_nam_dielectric
+from pyewjn.dielectric.nam_dielectric_coefficient_approximator import (
+	get_nam_dielectric,
+	get_unapproximated_nam_dielectric,
+)
 from pyewjn.dielectric.lindhard_dielectric import get_lindhard_dielectric
 
-__all__ = ["get_nam_dielectric", "get_lindhard_dielectric"]
+__all__ = [
+	"get_nam_dielectric",
+	"get_lindhard_dielectric",
+	"get_unapproximated_nam_dielectric",
+]

pyewjn/dielectric/lindhard_dielectric.py

@@ -11,14 +11,6 @@ class LindhardDielectric(object):
 		constants: CalculationConstants = CalculationConstants(),
 		thres=LINDHARD_SERIES_THRESHOLD,
 	):
-		if params.omega is None:
-			raise ValueError("omega expected to not be None")
-		if params.v_f is None:
-			raise ValueError("v_f expected to not be None")
-		if params.omega_p is None:
-			raise ValueError("omega_p expected to not be None")
-		if params.tau is None:
-			raise ValueError("tau expected to not be None")
 
 		self.series_threshold = thres
 		self.omega = params.omega

pyewjn/dielectric/nam_dielectric_coefficient_approximator.py

@@ -4,9 +4,15 @@ import pyewjn.dielectric.low_k_nam
 
 from pyewjn.baskets import CalculationParams, CalculationConstants
 
-from typing import Tuple
+from typing import Tuple, Callable
+import logging
+
+
+_logger = logging.getLogger(__name__)
+
 
 FIXED_LARGE_MOMENTUM = 1e8
+WRT_TC_THRESHOLD = 0.98
 
 
 class DedimensionalisedParameters(object):
@@ -19,16 +25,24 @@ class DedimensionalisedParameters(object):
 		temp: float,
 		critical_temp: float,
 		c_light: float,
+		wrt_tc: bool = False,
 	):
 		gap = 0
 		if temp < critical_temp:
 			# else, problems will happen
 			gap = 3.06 * np.sqrt(critical_temp * (critical_temp - temp))
-		self.xi = omega / gap
-		self.nu = 1 / (tau * gap)
-		self.t = temp / gap
-		self.a = omega * v_f / (c_light * gap)
+
+		if wrt_tc:
+			scale = critical_temp
+		else:
+			scale = gap
+
+		self.xi = omega / scale
+		self.nu = 1 / (tau * scale)
+		self.t = temp / scale
+		self.a = omega * v_f / (c_light * scale)
 		self.b = sigma_n / omega
+		self.delta = gap / scale
 
 
 class NamDielectricCoefficients(object):
@@ -60,9 +74,11 @@ def get_dedimensionalised_parameters(
 	temp: float,
 	critical_temp: float,
 	c_light: float,
+	wrt_tc: bool = False,
 ) -> DedimensionalisedParameters:
+
 	return DedimensionalisedParameters(
-		omega, sigma_n, tau, v_f, temp, critical_temp, c_light
+		omega, sigma_n, tau, v_f, temp, critical_temp, c_light, wrt_tc
 	)
 
 
@@ -123,18 +139,7 @@ def get_nam_dielectric(
 	params: CalculationParams,
 	constants: CalculationConstants = CalculationConstants(),
 ):
-	if params.omega is None:
-		raise ValueError("omega expected to not be None")
-	if params.v_f is None:
-		raise ValueError("v_f expected to not be None")
-	if params.omega_p is None:
-		raise ValueError("omega_p expected to not be None")
-	if params.tau is None:
-		raise ValueError("tau expected to not be None")
-	if params.t_rel is None:
-		raise ValueError("relative temp expected to not be None")
-	if params.t_c is None:
-		raise ValueError("critical temp expected to not be None")
+
 	sigma_n = params.omega_p**2 * params.tau / (4 * np.pi)
 	coeffs = get_nam_dielectric_coefficients(
 		params.omega,
@@ -146,3 +151,38 @@ def get_nam_dielectric(
 		constants.c_light,
 	)
 	return coeffs.eps(u_c)
+
+
+def get_unapproximated_nam_dielectric(
+	u_c: float,
+	params: CalculationParams,
+	constants: CalculationConstants = CalculationConstants(),
+) -> Callable[[float], float]:
+
+	sigma_n = params.omega_p**2 * params.tau / (4 * np.pi)
+	dedim = get_dedimensionalised_parameters(
+		params.omega,
+		sigma_n,
+		params.tau,
+		params.v_f,
+		params.t_rel * params.t_c,
+		params.t_c,
+		constants.c_light,
+		wrt_tc=params.t_rel > WRT_TC_THRESHOLD,
+	)
+	prefactor = 4j * np.pi * dedim.b
+
+	def eps_ret(u: float) -> float:
+		if u * dedim.a * 100 < abs(dedim.xi + 1j * dedim.nu):
+			_logger.info("Falling to low k version")
+			return prefactor * pyewjn.dielectric.low_k_nam.sigma_nam_alk(
+				dedim.xi, u * dedim.a, dedim.nu, dedim.t
+			)
+		elif u < u_c:
+			return prefactor * pyewjn.dielectric.sigma_nam.sigma_nam(
+				dedim.xi, u * dedim.a, dedim.nu, dedim.t
+			)
+		else:
+			return 1
+
+	return eps_ret

pyewjn/dielectric/sigma_nam_keep_gap.py

@@ -0,0 +1,67 @@
+import numpy as np
+from numpy.lib.scimath import sqrt as csqrt
+
+import pyewjn.util
+
+
+def g(w, wp, d):
+	return ((wp * (w + wp)) + d**2) / (
+		csqrt(wp**2 - d**2) * csqrt((w + wp) ** 2 - d**2)
+	)
+
+
+def s(k, e, v):
+	return (e - 1j * v) / k
+
+
+def f(k, e, v):
+	sv = s(k, e, v)
+	logv = np.log(np.real_if_close((sv + 1) / (sv - 1)) + 0j)
+	return (1 / k) * (2 * sv + ((1 - sv**2) * logv))
+
+
+def i1(w, wp, k, v, d):
+	gv = g(w, wp, d)
+	e1 = csqrt((w + wp) ** 2 - d**2)
+	e2 = csqrt(wp**2 - d**2)
+
+	f_upper = f(k, np.real(e1 - e2), np.imag(e1 + e2) + 2 * v) * (gv + 1)
+	f_lower = f(k, np.real(-e1 - e2), np.imag(e1 + e2) + 2 * v) * (gv - 1)
+
+	return f_upper + f_lower
+
+
+def i2(w, wp, k, v, d):
+	gv = g(w, wp, d)
+	e1 = csqrt((w + wp) ** 2 - d**2)
+	e2 = csqrt(wp**2 - d**2)
+
+	f_upper = f(k, np.real(e1 - e2), np.imag(e1 + e2) + 2 * v) * (gv + 1)
+	f_lower = f(k, np.real(e1 + e2), np.imag(e1 + e2) + 2 * v) * (gv - 1)
+
+	return f_upper + f_lower
+
+
+def a(w, k, v, t, d):
+	result = pyewjn.util.complex_quad(
+		lambda wp: np.tanh((w + wp) / (2 * t)) * (i1(w, wp, k, v, d)),
+		1 - w,
+		1,
+		epsabs=1e-10,
+	)
+
+	return result[0]
+
+
+def b_int(wp, w, k, v, t, d):
+	return (np.tanh((w + wp) / (2 * t)) * i1(w, wp, k, v, d)) - (
+		np.tanh(wp / (2 * t)) * i2(w, wp, k, v, d)
+	)
+
+
+def b(w, k, v, t, d, b_max=np.inf):
+	return pyewjn.util.complex_quad(lambda wp: b_int(wp, w, k, v, t, d), 1, b_max)[0]
+
+
+def sigma_nam_keep_gap(w, k, v, t, d):
+	return -1j * (3 / 4) * (v / w) * (-a(w, k, v, t, d) + b(w, k, v, t, d))

pyewjn/util/complex_integrate.py

@@ -3,9 +3,10 @@ from scipy.integrate import quad, quadrature
 
 
 def complex_quad(func, a, b, **kwargs):
-	'''
-		Extends scipy.integrate for complex functions.
-	'''
+	"""
+	Extends scipy.integrate for complex functions.
+	"""
+
 	def real_func(x):
 		return np.real(func(x))
 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "pyewjn"
-version = "0.2.1"
+version = "0.3.0"
 description = ""
 authors = ["Deepak <dmallubhotla+github@gmail.com>"]
 

tests/dielectric/test_nam_dielectric_coefficient_approximator.py

@@ -137,3 +137,31 @@ def test_nam_eps():
 	np.testing.assert_allclose(
 		eps_to_test(1e17), 1, rtol=1e-6, err_msg="above cutoff bad"
 	)
+
+
+def test_unapproximated_nam_eps():
+	u_c = 1e15
+	eps_to_test = pyewjn.dielectric.nam_dielectric_coefficient_approximator.get_unapproximated_nam_dielectric(
+		u_c,
+		CalculationParams(
+			omega=1e9, omega_p=3.54491e15, tau=1e-14, v_f=2e6, t_rel=0.8, t_c=1e11
+		),
+	)
+
+	np.testing.assert_allclose(
+		eps_to_test(10),
+		-3.789672906817707e10 + 3.257134605133221e8j,
+		rtol=1e-3,
+		err_msg="below u_l bad",
+	)
+
+	np.testing.assert_allclose(
+		eps_to_test(1e10),
+		-2.645743e8 + 2.293455422222e6j,
+		rtol=1e-3,
+		err_msg="linear region bad",
+	)
+
+	np.testing.assert_allclose(
+		eps_to_test(1e17), 1, rtol=1e-6, err_msg="above cutoff bad"
+	)

tests/noise/test_chi_nam.py

@@ -0,0 +1,58 @@
+import numpy as np
+import pytest
+
+import pyewjn.dielectric
+import pyewjn.noise.chi
+from pyewjn.baskets import CalculationParams
+
+
+cutoff_to_use = 5.4596e9
+
+
+@pytest.fixture
+def chi_zz_e_nam():
+	params = CalculationParams(
+		omega=1e9, v_f=2e6, omega_p=3.544907701811032e15, tau=1e-14, t_rel=0.99999
+	)
+	eps_l = pyewjn.dielectric.get_nam_dielectric(cutoff_to_use, params)
+	return pyewjn.noise.chi.get_chi_zz_e(eps_l)
+
+
+@pytest.mark.parametrize(
+	"test_input,expected",
+	[
+		# z   chi_zz_e_nam(z)
+		(1e-5, 4.07695673649665e6),
+		(1e-6, 4.095895777068543e9),
+		# (1e-7, 5.012885033150058e12), commenting this one out because it seems numerically too unstable
+		# (1e-8, 1.441261982619894e16), commenting this one out because it seems numerically too unstable
+	],
+)
+def test_chi_zz_e_nam(chi_zz_e_nam, test_input, expected):
+	actual = chi_zz_e_nam(test_input)
+
+	np.testing.assert_allclose(
+		actual,
+		expected,
+		rtol=0.05,
+		err_msg="chi_zz_e is inaccurate for nam case",
+		verbose=True,
+	)
+
+
+@pytest.mark.parametrize(
+	"test_input,expected",
+	[
+		# z   chi_zz_e_nam(z)
+		(1e-6, 4.095895777068543e9),
+	],
+)
+def test_chi_zz_e_nam_benchmark(benchmark, chi_zz_e_nam, test_input, expected):
+	actual = benchmark(chi_zz_e_nam, test_input)
+	np.testing.assert_allclose(
+		actual,
+		expected,
+		rtol=0.05,
+		err_msg="chi_zz_e is inaccurate for nam case",
+		verbose=True,
+	)