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13
CHANGELOG.md
13
CHANGELOG.md
@ -2,6 +2,19 @@
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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.
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### [0.8.7](https://gitea.deepak.science:2222/physics/pdme/compare/0.8.6...0.8.7) (2022-09-17)
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### Features
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* adds xy model for convenience to pdme ([e894c89](https://gitea.deepak.science:2222/physics/pdme/commit/e894c897029c05a1d4754e7930ae9ba2be7a1cfd))
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* moves xy model up to model package ([2a1ae3b](https://gitea.deepak.science:2222/physics/pdme/commit/2a1ae3b1a7f7e10469b7fd2930fee0b338f0c03f))
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### Bug Fixes
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* Correctly generates monte carlo version of xy model dipoles ([5acf0ac](https://gitea.deepak.science:2222/physics/pdme/commit/5acf0ac347382705674bb596440d27cba3730bac))
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### [0.8.6](https://gitea.deepak.science:2222/physics/pdme/compare/0.8.5...0.8.6) (2022-06-13)
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@ -11,6 +11,10 @@ from pdme.model.log_spaced_random_choice_model import (
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LogSpacedRandomCountMultipleDipoleFixedMagnitudeModel,
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)
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from pdme.model.log_spaced_random_choice_xy_model import (
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LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel,
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)
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from pdme.model.log_spaced_random_choice_fixed_orientation_model import (
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LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel,
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)
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@ -21,5 +25,6 @@ __all__ = [
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"MultipleDipoleFixedMagnitudeModel",
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"RandomCountMultipleDipoleFixedMagnitudeModel",
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"LogSpacedRandomCountMultipleDipoleFixedMagnitudeModel",
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"LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel",
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"LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel",
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]
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125
pdme/model/log_spaced_random_choice_xy_model.py
Normal file
125
pdme/model/log_spaced_random_choice_xy_model.py
Normal file
@ -0,0 +1,125 @@
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import numpy
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import numpy.random
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from pdme.model.model import DipoleModel
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from pdme.measurement import (
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OscillatingDipole,
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OscillatingDipoleArrangement,
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)
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class LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(DipoleModel):
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"""
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Model of multiple oscillating dipoles with a fixed magnitude, but free rotation in XY plane. Spaced logarithmically.
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Parameters
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----------
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wexp_min: log-10 lower bound for dipole frequency
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wexp_min: log-10 upper bound for dipole frequency
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pfixed : float
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The fixed dipole magnitude.
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n_max : int
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The maximum number of dipoles.
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prob_occupancy : float
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The probability of dipole occupancy
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"""
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def __init__(
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self,
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xmin: float,
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xmax: float,
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ymin: float,
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ymax: float,
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zmin: float,
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zmax: float,
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wexp_min: float,
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wexp_max: float,
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pfixed: float,
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n_max: int,
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prob_occupancy: float,
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) -> None:
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self.xmin = xmin
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self.xmax = xmax
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self.ymin = ymin
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self.ymax = ymax
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self.zmin = zmin
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self.zmax = zmax
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self.wexp_min = wexp_min
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self.wexp_max = wexp_max
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self.pfixed = pfixed
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self.rng = numpy.random.default_rng()
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self.n_max = n_max
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if prob_occupancy >= 1 or prob_occupancy <= 0:
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raise ValueError(
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f"The probability of a dipole site occupancy must be between 0 and 1, got {prob_occupancy}"
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)
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self.prob_occupancy = prob_occupancy
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def __repr__(self) -> str:
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return f"LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel({self.xmin}, {self.xmax}, {self.ymin}, {self.ymax}, {self.zmin}, {self.zmax}, {self.wexp_min}, {self.wexp_max}, {self.pfixed}, {self.n_max}, {self.prob_occupancy})"
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def get_dipoles(
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self, max_frequency: float, rng_to_use: numpy.random.Generator = None
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) -> OscillatingDipoleArrangement:
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rng: numpy.random.Generator
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if rng_to_use is None:
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rng = self.rng
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||||
else:
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rng = rng_to_use
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dipoles = []
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n = rng.binomial(self.n_max, self.prob_occupancy)
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for i in range(n):
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phi = rng.uniform(0, 2 * numpy.pi)
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px = self.pfixed * numpy.cos(phi)
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py = self.pfixed * numpy.sin(phi)
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pz = 0
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s_pts = numpy.array(
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(
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rng.uniform(self.xmin, self.xmax),
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rng.uniform(self.ymin, self.ymax),
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rng.uniform(self.zmin, self.zmax),
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)
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)
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frequency = 10 ** rng.uniform(self.wexp_min, self.wexp_max)
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dipoles.append(
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OscillatingDipole(numpy.array([px, py, pz]), s_pts, frequency)
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)
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return OscillatingDipoleArrangement(dipoles)
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def get_monte_carlo_dipole_inputs(
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self,
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monte_carlo_n: int,
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_: float,
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rng_to_use: numpy.random.Generator = None,
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||||
) -> numpy.ndarray:
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rng: numpy.random.Generator
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||||
if rng_to_use is None:
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rng = self.rng
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||||
else:
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rng = rng_to_use
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shape = (monte_carlo_n, self.n_max)
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phi = 2 * numpy.pi * rng.random(shape)
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p_mask = rng.binomial(1, self.prob_occupancy, shape)
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p_magnitude = self.pfixed * p_mask
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px = p_magnitude * numpy.cos(phi)
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py = p_magnitude * numpy.sin(phi)
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pz = p_magnitude * 0
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||||
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||||
sx = rng.uniform(self.xmin, self.xmax, shape)
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||||
sy = rng.uniform(self.ymin, self.ymax, shape)
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||||
sz = rng.uniform(self.zmin, self.zmax, shape)
|
||||
|
||||
w = 10 ** rng.uniform(self.wexp_min, self.wexp_max, shape)
|
||||
|
||||
return numpy.stack([px, py, pz, sx, sy, sz, w], axis=-1)
|
||||
361
poetry.lock
generated
361
poetry.lock
generated
@ -93,7 +93,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
|
||||
[[package]]
|
||||
name = "coverage"
|
||||
version = "6.4.1"
|
||||
version = "6.4.4"
|
||||
description = "Code coverage measurement for Python"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@ -213,11 +213,11 @@ python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "mypy"
|
||||
version = "0.961"
|
||||
version = "0.981"
|
||||
description = "Optional static typing for Python"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.dependencies]
|
||||
mypy-extensions = ">=0.4.3"
|
||||
@ -316,8 +316,8 @@ optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.extras]
|
||||
dev = ["pre-commit", "tox"]
|
||||
testing = ["pytest", "pytest-benchmark"]
|
||||
testing = ["pytest-benchmark", "pytest"]
|
||||
dev = ["tox", "pre-commit"]
|
||||
|
||||
[[package]]
|
||||
name = "prompt-toolkit"
|
||||
@ -426,7 +426,7 @@ coverage = {version = ">=5.2.1", extras = ["toml"]}
|
||||
pytest = ">=4.6"
|
||||
|
||||
[package.extras]
|
||||
testing = ["fields", "hunter", "process-tests", "six", "pytest-xdist", "virtualenv"]
|
||||
testing = ["virtualenv", "pytest-xdist", "six", "process-tests", "hunter", "fields"]
|
||||
|
||||
[[package]]
|
||||
name = "scipy"
|
||||
@ -461,7 +461,7 @@ executing = "*"
|
||||
pure-eval = "*"
|
||||
|
||||
[package.extras]
|
||||
tests = ["pytest", "typeguard", "pygments", "littleutils", "cython"]
|
||||
tests = ["cython", "littleutils", "pygments", "typeguard", "pytest"]
|
||||
|
||||
[[package]]
|
||||
name = "toml"
|
||||
@ -509,306 +509,51 @@ python-versions = "*"
|
||||
[metadata]
|
||||
lock-version = "1.1"
|
||||
python-versions = "^3.8,<3.10"
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content-hash = "53a256043845daf5745f0553c31904a14dd3ea6c6fc9c6754fb4a8e949bed86a"
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content-hash = "f6c96a07783db001d2cd72c255e34baa809532f30baad8d6220554844a5166bb"
|
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|
||||
[metadata.files]
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appnope = [
|
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{file = "appnope-0.1.2-py2.py3-none-any.whl", hash = "sha256:93aa393e9d6c54c5cd570ccadd8edad61ea0c4b9ea7a01409020c9aa019eb442"},
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asttokens = [
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{file = "asttokens-2.0.5-py2.py3-none-any.whl", hash = "sha256:0844691e88552595a6f4a4281a9f7f79b8dd45ca4ccea82e5e05b4bbdb76705c"},
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atomicwrites = [
|
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{file = "atomicwrites-1.4.0-py2.py3-none-any.whl", hash = "sha256:6d1784dea7c0c8d4a5172b6c620f40b6e4cbfdf96d783691f2e1302a7b88e197"},
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backcall = [
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{file = "backcall-0.2.0-py2.py3-none-any.whl", hash = "sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255"},
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coverage = [
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||||
six = [
|
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{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
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||||
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||||
stack-data = [
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{file = "stack_data-0.2.0-py3-none-any.whl", hash = "sha256:999762f9c3132308789affa03e9271bbbe947bf78311851f4d485d8402ed858e"},
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{file = "stack_data-0.2.0.tar.gz", hash = "sha256:45692d41bd633a9503a5195552df22b583caf16f0b27c4e58c98d88c8b648e12"},
|
||||
]
|
||||
toml = [
|
||||
{file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
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{file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
|
||||
]
|
||||
tomli = [
|
||||
{file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
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{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
|
||||
]
|
||||
traitlets = [
|
||||
{file = "traitlets-5.1.1-py3-none-any.whl", hash = "sha256:2d313cc50a42cd6c277e7d7dc8d4d7fedd06a2c215f78766ae7b1a66277e0033"},
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{file = "traitlets-5.1.1.tar.gz", hash = "sha256:059f456c5a7c1c82b98c2e8c799f39c9b8128f6d0d46941ee118daace9eb70c7"},
|
||||
]
|
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typing-extensions = [
|
||||
{file = "typing_extensions-4.0.1-py3-none-any.whl", hash = "sha256:7f001e5ac290a0c0401508864c7ec868be4e701886d5b573a9528ed3973d9d3b"},
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{file = "typing_extensions-4.0.1.tar.gz", hash = "sha256:4ca091dea149f945ec56afb48dae714f21e8692ef22a395223bcd328961b6a0e"},
|
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]
|
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wcwidth = [
|
||||
{file = "wcwidth-0.2.5-py2.py3-none-any.whl", hash = "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784"},
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{file = "wcwidth-0.2.5.tar.gz", hash = "sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83"},
|
||||
]
|
||||
appnope = []
|
||||
asttokens = []
|
||||
atomicwrites = []
|
||||
attrs = []
|
||||
backcall = []
|
||||
black = []
|
||||
click = []
|
||||
colorama = []
|
||||
coverage = []
|
||||
decorator = []
|
||||
executing = []
|
||||
flake8 = []
|
||||
iniconfig = []
|
||||
ipython = []
|
||||
jedi = []
|
||||
matplotlib-inline = []
|
||||
mccabe = []
|
||||
mypy = []
|
||||
mypy-extensions = []
|
||||
numpy = []
|
||||
packaging = []
|
||||
parso = []
|
||||
pathspec = []
|
||||
pexpect = []
|
||||
pickleshare = []
|
||||
platformdirs = []
|
||||
pluggy = []
|
||||
prompt-toolkit = []
|
||||
ptyprocess = []
|
||||
pure-eval = []
|
||||
py = []
|
||||
pycodestyle = []
|
||||
pyflakes = []
|
||||
pygments = []
|
||||
pyparsing = []
|
||||
pytest = []
|
||||
pytest-cov = []
|
||||
scipy = []
|
||||
six = []
|
||||
stack-data = []
|
||||
toml = []
|
||||
tomli = []
|
||||
traitlets = []
|
||||
typing-extensions = []
|
||||
wcwidth = []
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
[tool.poetry]
|
||||
name = "pdme"
|
||||
version = "0.8.6"
|
||||
version = "0.8.7"
|
||||
description = "Python dipole model evaluator"
|
||||
authors = ["Deepak <dmallubhotla+github@gmail.com>"]
|
||||
license = "GPL-3.0-only"
|
||||
@ -15,7 +15,7 @@ scipy = "~1.8"
|
||||
pytest = ">=6"
|
||||
flake8 = "^4.0.0"
|
||||
pytest-cov = "^3.0.0"
|
||||
mypy = "^0.961"
|
||||
mypy = "^0.981"
|
||||
ipython = "^8.2.0"
|
||||
black = "^22.3.0"
|
||||
|
||||
|
||||
@ -0,0 +1,206 @@
|
||||
from pdme.model import LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel
|
||||
import numpy
|
||||
import logging
|
||||
import pytest
|
||||
|
||||
|
||||
_logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def test_random_count_multiple_dipole_xy_wrong_probability():
|
||||
with pytest.raises(ValueError):
|
||||
LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(
|
||||
-10, 10, -5, 5, 2, 3, 1, 2, 10, 5, 2
|
||||
)
|
||||
|
||||
|
||||
def test_repr_random_count_multiple_dipole_fixed_mag_xy():
|
||||
model = LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(
|
||||
-10, 10, -5, 5, 2, 3, 1, 2, 10, 5, 0.5
|
||||
)
|
||||
assert (
|
||||
repr(model)
|
||||
== "LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(-10, 10, -5, 5, 2, 3, 1, 2, 10, 5, 0.5)"
|
||||
), "Repr should be what I want."
|
||||
|
||||
|
||||
def test_random_count_multiple_dipole_fixed_mag_model_get_dipoles_multiple_xy():
|
||||
|
||||
p_fixed = 10
|
||||
dipole_count = 5
|
||||
|
||||
model = LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(
|
||||
-10, 10, -5, 5, 2, 3, 0, 5, p_fixed, dipole_count, 0.5
|
||||
)
|
||||
|
||||
dipole_arrangement = model.get_dipoles(20, numpy.random.default_rng(1234))
|
||||
dipoles = dipole_arrangement.dipoles
|
||||
|
||||
assert (
|
||||
len(dipoles) == dipole_count
|
||||
), "Should have had multiple dipole based on count generated."
|
||||
|
||||
|
||||
def test_random_count_multiple_dipole_fixed_mag_model_get_dipoles_invariant_xy():
|
||||
|
||||
x_min = -10
|
||||
x_max = 10
|
||||
y_min = -5
|
||||
y_max = 5
|
||||
z_min = 2
|
||||
z_max = 3
|
||||
p_fixed = 10
|
||||
max_frequency = 5
|
||||
|
||||
model = LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(
|
||||
x_min, x_max, y_min, y_max, z_min, z_max, 0, max_frequency, p_fixed, 1, 0.5
|
||||
)
|
||||
model.rng = numpy.random.default_rng(1234)
|
||||
|
||||
dipole_arrangement = model.get_dipoles(5)
|
||||
dipoles = dipole_arrangement.dipoles
|
||||
|
||||
assert len(dipoles) == 1, "Should have only had one dipole generated."
|
||||
for i in range(10):
|
||||
dipole_arrangement = model.get_dipoles(max_frequency)
|
||||
dipoles = dipole_arrangement.dipoles
|
||||
|
||||
assert len(dipoles) in (
|
||||
0,
|
||||
1,
|
||||
), "Should have either zero or one dipole generated."
|
||||
|
||||
if len(dipoles) > 0:
|
||||
min_s = numpy.array([x_min, y_min, z_min])
|
||||
max_s = numpy.array([x_max, y_max, z_max])
|
||||
|
||||
numpy.testing.assert_equal(
|
||||
numpy.logical_and(min_s < dipoles[0].s, max_s > dipoles[0].s),
|
||||
True,
|
||||
f"Dipole location [{dipoles[0].s}] should have been between min [{min_s}] and max [{max_s}] bounds.",
|
||||
)
|
||||
assert (
|
||||
dipoles[0].w < 10 ** max_frequency and dipoles[0].w > 10**0
|
||||
), "Dipole frequency should have been between 0 and max."
|
||||
|
||||
numpy.testing.assert_allclose(
|
||||
numpy.linalg.norm(dipoles[0].p),
|
||||
p_fixed,
|
||||
err_msg="Should have had the expected dipole moment magnitude.",
|
||||
)
|
||||
|
||||
_logger.warning(dipoles[0].p)
|
||||
numpy.testing.assert_allclose(
|
||||
dipoles[0].p[2],
|
||||
0,
|
||||
err_msg="Should have had zero z magnitude.",
|
||||
)
|
||||
|
||||
|
||||
def test_random_count_multiple_dipole_fixed_mag_model_get_dipoles_invariant_monte_carlo_xy():
|
||||
|
||||
x_min = -10
|
||||
x_max = 10
|
||||
y_min = -5
|
||||
y_max = 5
|
||||
z_min = 2
|
||||
z_max = 3
|
||||
p_fixed = 10
|
||||
max_frequency = 5
|
||||
monte_carlo_n = 20
|
||||
|
||||
model = LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(
|
||||
x_min, x_max, y_min, y_max, z_min, z_max, 0, max_frequency, p_fixed, 1, 0.5
|
||||
)
|
||||
model.rng = numpy.random.default_rng(1234)
|
||||
|
||||
dipole_arrangement = model.get_dipoles(5)
|
||||
dipoles = dipole_arrangement.dipoles
|
||||
|
||||
assert len(dipoles) == 1, "Should have only had one dipole generated."
|
||||
for i in range(10):
|
||||
dipoles = model.get_monte_carlo_dipole_inputs(monte_carlo_n, max_frequency)
|
||||
|
||||
min_s = numpy.array([x_min, y_min, z_min])
|
||||
max_s = numpy.array([x_max, y_max, z_max])
|
||||
|
||||
_logger.warning(dipoles)
|
||||
_logger.warning(dipoles[:, 0, 0:3])
|
||||
_logger.warning(dipoles[:, 0, 3:6])
|
||||
_logger.warning(dipoles[:, 0, 6])
|
||||
|
||||
ps = dipoles[:, 0, 0:3]
|
||||
ss = dipoles[:, 0, 3:6]
|
||||
ws = dipoles[:, 0, 6]
|
||||
|
||||
numpy.testing.assert_equal(
|
||||
numpy.logical_and(min_s < ss, max_s > ss).all(),
|
||||
True,
|
||||
f"Dipole location [{ss}] should have been between min [{min_s}] and max [{max_s}] bounds.",
|
||||
)
|
||||
assert (ws < 10**max_frequency).all() and (
|
||||
ws > 10**0
|
||||
).all(), "Dipole frequency should have been between 0 and max."
|
||||
|
||||
norms = numpy.linalg.norm(ps, axis=1)
|
||||
filtered_norms = norms[norms > 0]
|
||||
numpy.testing.assert_allclose(
|
||||
filtered_norms,
|
||||
p_fixed,
|
||||
err_msg="Should have had the expected dipole moment magnitude.",
|
||||
)
|
||||
|
||||
numpy.testing.assert_allclose(
|
||||
ps[:, 2],
|
||||
0,
|
||||
err_msg="Should have had zero z magnitude.",
|
||||
)
|
||||
|
||||
|
||||
def test_random_count_multiple_dipole_shape():
|
||||
|
||||
x_min = -10
|
||||
x_max = 10
|
||||
y_min = -5
|
||||
y_max = 5
|
||||
z_min = 2
|
||||
z_max = 3
|
||||
p_fixed = 10
|
||||
max_frequency = 5
|
||||
num_dipoles = 13
|
||||
monte_carlo_n = 11
|
||||
|
||||
model = LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(
|
||||
x_min,
|
||||
x_max,
|
||||
y_min,
|
||||
y_max,
|
||||
z_min,
|
||||
z_max,
|
||||
0,
|
||||
max_frequency,
|
||||
p_fixed,
|
||||
num_dipoles,
|
||||
0.5,
|
||||
)
|
||||
model.rng = numpy.random.default_rng(1234)
|
||||
|
||||
actual_shape = model.get_monte_carlo_dipole_inputs(
|
||||
monte_carlo_n, max_frequency
|
||||
).shape
|
||||
|
||||
numpy.testing.assert_equal(
|
||||
actual_shape,
|
||||
(monte_carlo_n, num_dipoles, 7),
|
||||
err_msg="shape was wrong for monte carlo outputs",
|
||||
)
|
||||
|
||||
actual_shape = model.get_monte_carlo_dipole_inputs(
|
||||
monte_carlo_n, max_frequency, rng_to_use=numpy.random.default_rng(1515)
|
||||
).shape
|
||||
|
||||
numpy.testing.assert_equal(
|
||||
actual_shape,
|
||||
(monte_carlo_n, num_dipoles, 7),
|
||||
err_msg="shape was wrong for monte carlo outputs",
|
||||
)
|
||||
Loading…
x
Reference in New Issue
Block a user