Merge remote-tracking branch 'refs/remotes/origin/master'
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This commit is contained in:
commit
2c65e2a984
GPG Key ID:
976F3357369149AB
1
.gitignore
vendored
1
.gitignore
vendored
@ -147,3 +147,4 @@ cython_debug/
|
||||
|
||||
# just a local scripts dir for us to be able to run things in
|
||||
local_scripts/
|
||||
|
||||
|
||||
@ -16,4 +16,4 @@ Build with `just`, preferred over `do.sh` I think.
|
||||
|
||||
## CLI
|
||||
|
||||
the json files for dots and dipoles have a specific format that ignores extraneous data but is sad about missing fields.
|
||||
The json files for dots and dipoles have a specific format that ignores extraneous data but is sad about missing fields.
|
||||
|
||||
20
flake.lock
generated
20
flake.lock
generated
@ -39,6 +39,7 @@
|
||||
"nix-github-actions": {
|
||||
"inputs": {
|
||||
"nixpkgs": [
|
||||
"poetry2nixSrc",
|
||||
"nixpkgs"
|
||||
]
|
||||
},
|
||||
@ -58,11 +59,11 @@
|
||||
},
|
||||
"nixpkgs": {
|
||||
"locked": {
|
||||
"lastModified": 1716715802,
|
||||
"narHash": "sha256-usk0vE7VlxPX8jOavrtpOqphdfqEQpf9lgedlY/r66c=",
|
||||
"lastModified": 1719468428,
|
||||
"narHash": "sha256-vN5xJAZ4UGREEglh3lfbbkIj+MPEYMuqewMn4atZFaQ=",
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "e2dd4e18cc1c7314e24154331bae07df76eb582f",
|
||||
"rev": "1e3deb3d8a86a870d925760db1a5adecc64d329d",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
@ -83,11 +84,11 @@
|
||||
"treefmt-nix": "treefmt-nix"
|
||||
},
|
||||
"locked": {
|
||||
"lastModified": 1716813403,
|
||||
"narHash": "sha256-9+G8tEOh3QkjSUV2UMC+TpvzKOR8IUFlkJJTMpVQMkc=",
|
||||
"lastModified": 1719549552,
|
||||
"narHash": "sha256-efvBV+45uQA6r7aov48H6MhvKp1QUIyIX5gh9oueUzs=",
|
||||
"owner": "nix-community",
|
||||
"repo": "poetry2nix",
|
||||
"rev": "12599ecaa9ec641c29dc8fd07f8267b23874bf3a",
|
||||
"rev": "4fd045cdb85f2a0173021a4717dc01d92d7ab2b2",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
@ -150,15 +151,16 @@
|
||||
"treefmt-nix": {
|
||||
"inputs": {
|
||||
"nixpkgs": [
|
||||
"poetry2nixSrc",
|
||||
"nixpkgs"
|
||||
]
|
||||
},
|
||||
"locked": {
|
||||
"lastModified": 1715940852,
|
||||
"narHash": "sha256-wJqHMg/K6X3JGAE9YLM0LsuKrKb4XiBeVaoeMNlReZg=",
|
||||
"lastModified": 1718522839,
|
||||
"narHash": "sha256-ULzoKzEaBOiLRtjeY3YoGFJMwWSKRYOic6VNw2UyTls=",
|
||||
"owner": "numtide",
|
||||
"repo": "treefmt-nix",
|
||||
"rev": "2fba33a182602b9d49f0b2440513e5ee091d838b",
|
||||
"rev": "68eb1dc333ce82d0ab0c0357363ea17c31ea1f81",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
||||
545
poetry.lock
generated
545
poetry.lock
generated
@ -1,5 +1,23 @@
|
||||
# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "asttokens"
|
||||
version = "2.4.1"
|
||||
description = "Annotate AST trees with source code positions"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"},
|
||||
{file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
six = ">=1.12.0"
|
||||
|
||||
[package.extras]
|
||||
astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
|
||||
test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
|
||||
|
||||
[[package]]
|
||||
name = "black"
|
||||
version = "22.12.0"
|
||||
@ -125,63 +143,63 @@ test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
|
||||
|
||||
[[package]]
|
||||
name = "coverage"
|
||||
version = "7.4.4"
|
||||
version = "7.5.4"
|
||||
description = "Code coverage measurement for Python"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
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|
||||
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||||
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]
|
||||
|
||||
[package.dependencies]
|
||||
@ -205,6 +223,17 @@ files = [
|
||||
docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
|
||||
tests = ["pytest", "pytest-cov", "pytest-xdist"]
|
||||
|
||||
[[package]]
|
||||
name = "decorator"
|
||||
version = "5.1.1"
|
||||
description = "Decorators for Humans"
|
||||
optional = false
|
||||
python-versions = ">=3.5"
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||||
[[package]]
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||||
name = "exceptiongroup"
|
||||
version = "1.2.1"
|
||||
@ -219,6 +248,20 @@ files = [
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||||
[package.extras]
|
||||
test = ["pytest (>=6)"]
|
||||
|
||||
[[package]]
|
||||
name = "executing"
|
||||
version = "2.0.1"
|
||||
description = "Get the currently executing AST node of a frame, and other information"
|
||||
optional = false
|
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python-versions = ">=3.5"
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[package.extras]
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||||
|
||||
[[package]]
|
||||
name = "flake8"
|
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version = "4.0.1"
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||||
@ -237,53 +280,53 @@ pyflakes = ">=2.4.0,<2.5.0"
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[[package]]
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||||
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||||
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||||
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|
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|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "pytest-8.1.1-py3-none-any.whl", hash = "sha256:2a8386cfc11fa9d2c50ee7b2a57e7d898ef90470a7a34c4b949ff59662bb78b7"},
|
||||
{file = "pytest-8.1.1.tar.gz", hash = "sha256:ac978141a75948948817d360297b7aae0fcb9d6ff6bc9ec6d514b85d5a65c044"},
|
||||
{file = "pytest-8.2.2-py3-none-any.whl", hash = "sha256:c434598117762e2bd304e526244f67bf66bbd7b5d6cf22138be51ff661980343"},
|
||||
{file = "pytest-8.2.2.tar.gz", hash = "sha256:de4bb8104e201939ccdc688b27a89a7be2079b22e2bd2b07f806b6ba71117977"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@ -786,11 +990,11 @@ colorama = {version = "*", markers = "sys_platform == \"win32\""}
|
||||
exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
|
||||
iniconfig = "*"
|
||||
packaging = "*"
|
||||
pluggy = ">=1.4,<2.0"
|
||||
pluggy = ">=1.5,<2.0"
|
||||
tomli = {version = ">=1", markers = "python_version < \"3.11\""}
|
||||
|
||||
[package.extras]
|
||||
testing = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
|
||||
dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
|
||||
|
||||
[[package]]
|
||||
name = "pytest-cov"
|
||||
@ -873,6 +1077,25 @@ files = [
|
||||
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "stack-data"
|
||||
version = "0.6.3"
|
||||
description = "Extract data from python stack frames and tracebacks for informative displays"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "stack_data-0.6.3-py3-none-any.whl", hash = "sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695"},
|
||||
{file = "stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
asttokens = ">=2.1.0"
|
||||
executing = ">=1.2.0"
|
||||
pure-eval = "*"
|
||||
|
||||
[package.extras]
|
||||
tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
|
||||
|
||||
[[package]]
|
||||
name = "syrupy"
|
||||
version = "4.6.1"
|
||||
@ -898,33 +1121,59 @@ files = [
|
||||
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "traitlets"
|
||||
version = "5.14.3"
|
||||
description = "Traitlets Python configuration system"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "traitlets-5.14.3-py3-none-any.whl", hash = "sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f"},
|
||||
{file = "traitlets-5.14.3.tar.gz", hash = "sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
|
||||
test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<8.2)", "pytest-mock", "pytest-mypy-testing"]
|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.11.0"
|
||||
version = "4.12.2"
|
||||
description = "Backported and Experimental Type Hints for Python 3.8+"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "typing_extensions-4.11.0-py3-none-any.whl", hash = "sha256:c1f94d72897edaf4ce775bb7558d5b79d8126906a14ea5ed1635921406c0387a"},
|
||||
{file = "typing_extensions-4.11.0.tar.gz", hash = "sha256:83f085bd5ca59c80295fc2a82ab5dac679cbe02b9f33f7d83af68e241bea51b0"},
|
||||
{file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
|
||||
{file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "wcwidth"
|
||||
version = "0.2.13"
|
||||
description = "Measures the displayed width of unicode strings in a terminal"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
|
||||
{file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.19.0"
|
||||
version = "3.19.2"
|
||||
description = "Backport of pathlib-compatible object wrapper for zip files"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "zipp-3.19.0-py3-none-any.whl", hash = "sha256:96dc6ad62f1441bcaccef23b274ec471518daf4fbbc580341204936a5a3dddec"},
|
||||
{file = "zipp-3.19.0.tar.gz", hash = "sha256:952df858fb3164426c976d9338d3961e8e8b3758e2e059e0f754b8c4262625ee"},
|
||||
{file = "zipp-3.19.2-py3-none-any.whl", hash = "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c"},
|
||||
{file = "zipp-3.19.2.tar.gz", hash = "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
|
||||
doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.9,<3.10"
|
||||
content-hash = "872b3583d0fd4cfdd9ce8449ba50feb0deb575e8ac7453a777d9cb2d5a69eb4d"
|
||||
content-hash = "5bfa5aed1086efa011fcb18206b79ef04aff5dc443b45278bdcf01f9b0e25b72"
|
||||
|
||||
@ -20,6 +20,7 @@ mypy = "^0.961"
|
||||
black = "^22.3.0"
|
||||
syrupy = "^4.0.8"
|
||||
matplotlib = "^3.9.0"
|
||||
ipython = ">=7"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core>=1.0.0"]
|
||||
|
||||
@ -6,6 +6,7 @@ import tantri.cli.input_files.write_dipoles
|
||||
import tantri.cli.file_importer
|
||||
import json
|
||||
import tantri.dipoles
|
||||
import tantri.dipoles.event_time_series
|
||||
import pathlib
|
||||
|
||||
|
||||
@ -97,6 +98,9 @@ def cli(log, log_file):
|
||||
required=True,
|
||||
)
|
||||
@click.option("--header-row/--no-header-row", default=False, help="Write a header row")
|
||||
@click.option(
|
||||
"--event-based/--no-event-based", default=False, help="Use new event-based method"
|
||||
)
|
||||
def write_time_series(
|
||||
dipoles_file,
|
||||
dots_file,
|
||||
@ -106,6 +110,7 @@ def write_time_series(
|
||||
time_series_rng_seed,
|
||||
output_file,
|
||||
header_row,
|
||||
event_based,
|
||||
):
|
||||
"""
|
||||
Generate a time series for the passed in parameters.
|
||||
@ -119,6 +124,7 @@ def write_time_series(
|
||||
time_series_rng_seed,
|
||||
output_file,
|
||||
header_row,
|
||||
event_based,
|
||||
)
|
||||
|
||||
|
||||
@ -131,6 +137,7 @@ def _write_time_series(
|
||||
time_series_rng_seed,
|
||||
output_file,
|
||||
header_row,
|
||||
new_method,
|
||||
):
|
||||
_logger.debug(
|
||||
f"Received parameters [dipoles_file: {dipoles_file}] and [dots_file: {dots_file}]"
|
||||
@ -156,6 +163,25 @@ def _write_time_series(
|
||||
f"Going to simulate {num_iterations} iterations with a delta t of {delta_t}"
|
||||
)
|
||||
|
||||
if new_method:
|
||||
_logger.info("Using new method")
|
||||
_logger.debug(f"Got seed {time_series_rng_seed}")
|
||||
if time_series_rng_seed is None:
|
||||
time_series = tantri.dipoles.event_time_series.EventDipoleTimeSeries(
|
||||
dipoles, dots, measurement_enum, delta_t, num_iterations
|
||||
)
|
||||
else:
|
||||
rng = numpy.random.default_rng(time_series_rng_seed)
|
||||
time_series = tantri.dipoles.event_time_series.EventDipoleTimeSeries(
|
||||
dipoles, dots, measurement_enum, delta_t, num_iterations, rng
|
||||
)
|
||||
output_series = time_series.create_time_series()
|
||||
for time, time_series_dict in output_series:
|
||||
values = ", ".join(str(time_series_dict[label]) for label in labels)
|
||||
out.write(f"{time}, {values}\n")
|
||||
|
||||
else:
|
||||
# in the old method
|
||||
_logger.debug(f"Got seed {time_series_rng_seed}")
|
||||
if time_series_rng_seed is None:
|
||||
time_series = tantri.dipoles.DipoleTimeSeries(
|
||||
@ -169,7 +195,9 @@ def _write_time_series(
|
||||
|
||||
for i in range(num_iterations):
|
||||
transition = time_series.transition()
|
||||
transition_values = ", ".join(str(transition[label]) for label in labels)
|
||||
transition_values = ", ".join(
|
||||
str(transition[label]) for label in labels
|
||||
)
|
||||
out.write(f"{i * delta_t}, {transition_values}\n")
|
||||
|
||||
|
||||
|
||||
154
tantri/dipoles/event_time_series.py
Normal file
154
tantri/dipoles/event_time_series.py
Normal file
@ -0,0 +1,154 @@
|
||||
import numpy.random
|
||||
from typing import Callable, Sequence, Tuple, Optional, Dict, List
|
||||
from dataclasses import dataclass
|
||||
from tantri.dipoles.types import DipoleTO, DotPosition, DipoleMeasurementType
|
||||
import logging
|
||||
|
||||
_logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class EventWrappedDipole:
|
||||
# assumed len 3
|
||||
p: numpy.ndarray
|
||||
s: numpy.ndarray
|
||||
|
||||
# should be 1/tau up to some pis
|
||||
w: float
|
||||
|
||||
# For caching purposes tell each dipole where the dots are
|
||||
# TODO: This can be done better by only passing into the time series the non-repeated p s and w,
|
||||
# TODO: and then creating a new wrapper type to include all the cached stuff.
|
||||
# TODO: Realistically, the dot positions and measurement type data should live in the time series.
|
||||
dot_positions: Sequence[DotPosition]
|
||||
|
||||
measurement_type: DipoleMeasurementType
|
||||
|
||||
def __post_init__(self) -> None:
|
||||
"""
|
||||
Coerce the inputs into numpy arrays.
|
||||
"""
|
||||
self.p = numpy.array(self.p)
|
||||
self.s = numpy.array(self.s)
|
||||
|
||||
self.state = 1
|
||||
self.cache = {}
|
||||
for pos in self.dot_positions:
|
||||
if self.measurement_type is DipoleMeasurementType.ELECTRIC_POTENTIAL:
|
||||
self.cache[pos.label] = self.potential(pos)
|
||||
elif self.measurement_type is DipoleMeasurementType.X_ELECTRIC_FIELD:
|
||||
self.cache[pos.label] = self.e_field_x(pos)
|
||||
|
||||
def potential(self, dot: DotPosition) -> float:
|
||||
# let's assume single dot at origin for now
|
||||
r_diff = self.s - dot.r
|
||||
return self.p.dot(r_diff) / (numpy.linalg.norm(r_diff) ** 3)
|
||||
|
||||
def e_field_x(self, dot: DotPosition) -> float:
|
||||
# let's assume single dot at origin for now
|
||||
r_diff = self.s - dot.r
|
||||
norm = numpy.linalg.norm(r_diff)
|
||||
|
||||
return (
|
||||
((3 * self.p.dot(r_diff) * r_diff / (norm**2)) - self.p) / (norm**3)
|
||||
)[0]
|
||||
|
||||
def get_time_series(
|
||||
self, dt: float, num_samples: int, rng: numpy.random.Generator
|
||||
) -> Sequence[Tuple[float, Dict[str, float]]]:
|
||||
_logger.debug(
|
||||
f"Creating time series with params {dt=}, {num_samples=}, scale={self.w}"
|
||||
)
|
||||
raw_time_series = create_exponential_time_series(rng, dt, num_samples, self.w)
|
||||
output = []
|
||||
|
||||
for time, state in raw_time_series:
|
||||
output.append((time, {k: state * v for k, v in self.cache.items()}))
|
||||
return output
|
||||
|
||||
|
||||
def get_event_wrapped_dipoles(
|
||||
dipole_tos: Sequence[DipoleTO],
|
||||
dots: Sequence[DotPosition],
|
||||
measurement_type: DipoleMeasurementType,
|
||||
) -> Sequence[EventWrappedDipole]:
|
||||
return [
|
||||
EventWrappedDipole(
|
||||
p=dipole_to.p,
|
||||
s=dipole_to.s,
|
||||
w=dipole_to.w,
|
||||
dot_positions=dots,
|
||||
measurement_type=measurement_type,
|
||||
)
|
||||
for dipole_to in dipole_tos
|
||||
]
|
||||
|
||||
|
||||
class EventDipoleTimeSeries:
|
||||
def __init__(
|
||||
self,
|
||||
dipoles: Sequence[DipoleTO],
|
||||
dots: Sequence[DotPosition],
|
||||
measurement_type: DipoleMeasurementType,
|
||||
dt: float,
|
||||
num_samples: int,
|
||||
rng_to_use: Optional[numpy.random.Generator] = None,
|
||||
):
|
||||
self.rng: numpy.random.Generator
|
||||
if rng_to_use is None:
|
||||
self.rng = numpy.random.default_rng()
|
||||
else:
|
||||
self.rng = rng_to_use
|
||||
|
||||
self.dt = dt
|
||||
self.num_samples = num_samples
|
||||
self.dipoles = get_event_wrapped_dipoles(dipoles, dots, measurement_type)
|
||||
|
||||
def create_time_series(self) -> Sequence[Tuple[float, Dict[str, float]]]:
|
||||
collected_dictionary: Dict[float, Dict[str, float]] = {}
|
||||
_logger.debug("Creating time series")
|
||||
|
||||
for dipole in self.dipoles:
|
||||
_logger.debug(f"Doing dipole {dipole}")
|
||||
series = dipole.get_time_series(self.dt, self.num_samples, self.rng)
|
||||
for time, meases in series:
|
||||
if time in collected_dictionary:
|
||||
for k, v in meases.items():
|
||||
|
||||
collected_dictionary[time][k] += v
|
||||
else:
|
||||
collected_dictionary[time] = meases
|
||||
|
||||
return [(k, v) for k, v in collected_dictionary.items()]
|
||||
|
||||
|
||||
def get_num_events_before(
|
||||
rng: numpy.random.Generator, scale: float, total_time: float
|
||||
) -> Callable[[float], int]:
|
||||
|
||||
_logger.debug(
|
||||
f"Creating the events before function for params {scale=} {total_time=}"
|
||||
)
|
||||
event_times: List = []
|
||||
random_size = max(1, int(total_time // scale))
|
||||
while sum(event_times) < total_time:
|
||||
event_times.extend(rng.exponential(scale=scale, size=random_size))
|
||||
|
||||
accumulator = 0
|
||||
scanned_times = [accumulator := accumulator + t for t in event_times]
|
||||
|
||||
def num_events_before(time: float) -> int:
|
||||
return len([t for t in scanned_times if t < time])
|
||||
|
||||
return num_events_before
|
||||
|
||||
|
||||
def create_exponential_time_series(
|
||||
rng: numpy.random.Generator, dt: float, num_samples: int, scale: float
|
||||
) -> Sequence[Tuple[float, int]]:
|
||||
_logger.debug("Creating an exponential time series")
|
||||
total_time = dt * num_samples
|
||||
_logger.debug(f"Have a total time {total_time}")
|
||||
events_before = get_num_events_before(rng, scale, total_time)
|
||||
_logger.debug("Finished getting the events before function")
|
||||
return [(dt * i, (events_before(dt * i) % 2) * 2 - 1) for i in range(num_samples)]
|
||||
@ -21,7 +21,7 @@ class DipoleTO:
|
||||
class Orientation(str, Enum):
|
||||
# Enum for orientation, making string for json serialisation purposes
|
||||
#
|
||||
# Note that htis might not be infinitely extensible?
|
||||
# Note that this might not be infinitely extensible?
|
||||
# https://stackoverflow.com/questions/75040733/is-there-a-way-to-use-strenum-in-earlier-python-versions
|
||||
XY = "XY"
|
||||
Z = "Z"
|
||||
|
||||
2157
tests/dipoles/__snapshots__/test_event_time_series.ambr
Normal file
2157
tests/dipoles/__snapshots__/test_event_time_series.ambr
Normal file
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120
tests/dipoles/test_event_time_series.py
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120
tests/dipoles/test_event_time_series.py
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import tantri.dipoles.event_time_series as ets
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import numpy.random
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import logging
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from tantri.dipoles.types import (
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DipoleTO,
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DotPosition,
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DipoleMeasurementType,
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)
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_logger = logging.getLogger(__name__)
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SEED = 12345
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def test_event_time_series(snapshot):
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_logger.info("testing event time series")
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rng = numpy.random.default_rng(SEED)
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before_func = ets.get_num_events_before(rng=rng, scale=0.5, total_time=10)
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time_series = [(i, before_func(i)) for i in range(10)]
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_logger.warning(time_series)
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assert time_series == snapshot
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def test_event_actual_series(snapshot):
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rng = numpy.random.default_rng(SEED)
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time_series = ets.create_exponential_time_series(rng, 0.1, 200, 0.5)
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assert time_series == snapshot
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def test_event_dipoles_collection(snapshot):
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rng = numpy.random.default_rng(1234)
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dots = [DotPosition(numpy.array([0, 0, 0]), "dot1")]
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d1 = DipoleTO(
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numpy.array([0, 0, 10]),
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numpy.array([5, 3, 2]),
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15,
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)
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d2 = DipoleTO(
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numpy.array([0, 0, 10]),
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numpy.array([-2, 3, 2]),
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0.1,
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)
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d3 = DipoleTO(
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numpy.array([0, 0, 10]),
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numpy.array([2, 1, 2]),
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6,
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)
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d4 = DipoleTO(
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numpy.array([0, 0, 10]),
|
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numpy.array([-5, -5, 2]),
|
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50,
|
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)
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ts_gen = ets.EventDipoleTimeSeries(
|
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[d1, d2, d3, d4],
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dots,
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DipoleMeasurementType.X_ELECTRIC_FIELD,
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0.01,
|
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100,
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rng_to_use=rng,
|
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)
|
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time_series = ts_gen.create_time_series()
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assert time_series == snapshot
|
||||
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def test_event_dipoles_collection_larger(snapshot):
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|
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rng = numpy.random.default_rng(1234)
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dots = [
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DotPosition(numpy.array([0, 0, 0]), "dot1"),
|
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DotPosition(numpy.array([0, -1, 0]), "dot2"),
|
||||
]
|
||||
|
||||
d1 = DipoleTO(
|
||||
numpy.array([0, 0, 10]),
|
||||
numpy.array([5, 3, 2]),
|
||||
15,
|
||||
)
|
||||
d2 = DipoleTO(
|
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numpy.array([0, 0, 10]),
|
||||
numpy.array([-2, 3, 2]),
|
||||
0.1,
|
||||
)
|
||||
d3 = DipoleTO(
|
||||
numpy.array([0, 0, 10]),
|
||||
numpy.array([2, 1, 2]),
|
||||
6,
|
||||
)
|
||||
d4 = DipoleTO(
|
||||
numpy.array([0, 0, 10]),
|
||||
numpy.array([-5, -5, 2]),
|
||||
50,
|
||||
)
|
||||
d5 = DipoleTO(
|
||||
numpy.array([0, 0, 10]),
|
||||
numpy.array([-2, -2, 1]),
|
||||
0.01,
|
||||
)
|
||||
|
||||
ts_gen = ets.EventDipoleTimeSeries(
|
||||
[d1, d2, d3, d4, d5],
|
||||
dots,
|
||||
DipoleMeasurementType.X_ELECTRIC_FIELD,
|
||||
0.01,
|
||||
100,
|
||||
rng_to_use=rng,
|
||||
)
|
||||
time_series = ts_gen.create_time_series()
|
||||
|
||||
assert time_series == snapshot
|
||||
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