chore(deps): update dependency mypy to ^0.991

CHANGELOG.md

@@ -2,14 +2,6 @@
 
 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.
 
-### [0.8.9](https://gitea.deepak.science:2222/physics/pdme/compare/0.8.8...0.8.9) (2023-07-23)
-
-
-### Features
-
-* adds a bunch of mcmc generation code for log spaced models, yay ([f280448](https://gitea.deepak.science:2222/physics/pdme/commit/f280448cfe2fcf5bdc5ac2317ee52b27523bb49d))
-* adds utility functions for dealing with markov chain monte carlo ([feb0a5f](https://gitea.deepak.science:2222/physics/pdme/commit/feb0a5f6453dcb5e71a07c7749cd579dab15171c))
-
 ### [0.8.8](https://gitea.deepak.science:2222/physics/pdme/compare/0.8.7...0.8.8) (2023-04-09)
 
 

do.sh

@@ -39,15 +39,6 @@ test() {
 	fi
 }
 
-updatesnap() {
-	echo "I am ${FUNCNAME[0]}ing"
-	if [[ "${DO_NIX_CUSTOM:=0}" -eq 1 ]]; then
-		pytest --snapshot-update
-	else
-		poetry run pytest --snapshot-update
-	fi
-}
-
 htmlcov() {
 	if [[ "${DO_NIX_CUSTOM:=0}" -eq 1 ]]; then
 		pytest --cov-report=html

pdme/model/log_spaced_random_choice_fixed_orientation_model.py

@@ -5,11 +5,6 @@ from pdme.measurement import (
 	OscillatingDipole,
 	OscillatingDipoleArrangement,
 )
-import logging
-from typing import Optional
-import pdme.subspace_simulation
-
-_logger = logging.getLogger(__name__)
 
 
 class LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel(
@@ -143,51 +138,3 @@ class LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel(
 		w = 10 ** rng.uniform(self.wexp_min, self.wexp_max, shape)
 
 		return numpy.stack([px, py, pz, sx, sy, sz, w], axis=-1)
-
-	def markov_chain_monte_carlo_proposal(
-		self,
-		dipole: numpy.ndarray,
-		stdev: pdme.subspace_simulation.DipoleStandardDeviation,
-		rng_arg: Optional[numpy.random.Generator] = None,
-	) -> numpy.ndarray:
-		if rng_arg is None:
-			rng_to_use = self.rng
-		else:
-			rng_to_use = rng_arg
-
-		px = dipole[0]
-		py = dipole[1]
-		pz = dipole[2]
-		# won't change p for this model of fixed dipole moment.
-
-		rx = dipole[3]
-		ry = dipole[4]
-		rz = dipole[5]
-
-		tentative_rx = rx + stdev.rx_step * rng_to_use.uniform(-1, 1)
-		if tentative_rx < self.xmin or tentative_rx > self.xmax:
-			tentative_rx = rx
-
-		tentative_ry = ry + stdev.ry_step * rng_to_use.uniform(-1, 1)
-		if tentative_ry < self.ymin or tentative_ry > self.ymax:
-			tentative_ry = ry
-		tentative_rz = rz + stdev.rz_step * rng_to_use.uniform(-1, 1)
-		if tentative_rz < self.zmin or tentative_rz > self.zmax:
-			tentative_rz = rz
-
-		w = dipole[6]
-		tentative_w = numpy.exp(
-			numpy.log(w) + (stdev.w_log_step * rng_to_use.uniform(-1, 1))
-		)
-		tentative_dip = numpy.array(
-			[
-				px,
-				py,
-				pz,
-				tentative_rx,
-				tentative_ry,
-				tentative_rz,
-				tentative_w,
-			]
-		)
-		return tentative_dip

pdme/model/log_spaced_random_choice_model.py

@@ -5,8 +5,6 @@ from pdme.measurement import (
 	OscillatingDipole,
 	OscillatingDipoleArrangement,
 )
-import pdme.subspace_simulation
-from typing import Optional
 
 
 class LogSpacedRandomCountMultipleDipoleFixedMagnitudeModel(DipoleModel):
@@ -127,73 +125,3 @@ class LogSpacedRandomCountMultipleDipoleFixedMagnitudeModel(DipoleModel):
 		w = 10 ** rng.uniform(self.wexp_min, self.wexp_max, shape)
 
 		return numpy.stack([px, py, pz, sx, sy, sz, w], axis=-1)
-
-	def markov_chain_monte_carlo_proposal(
-		self,
-		dipole: numpy.ndarray,
-		stdev: pdme.subspace_simulation.DipoleStandardDeviation,
-		rng_arg: Optional[numpy.random.Generator] = None,
-	) -> numpy.ndarray:
-		if rng_arg is None:
-			rng_to_use = self.rng
-		else:
-			rng_to_use = rng_arg
-
-		px = dipole[0]
-		py = dipole[1]
-		pz = dipole[2]
-		theta = numpy.arccos(pz / self.pfixed)
-		phi = numpy.arctan2(py, px)
-
-		# need to step phi, theta, rx, ry, rz, w
-		# then p^\ast is 1/(2 phi_step) and Delta = phi_step(2 * {0, 1} - 1)
-		delta_phi = stdev.p_phi_step * rng_to_use.uniform(-1, 1)
-		tentative_phi = phi + delta_phi
-
-		# theta
-		delta_theta = stdev.p_theta_step * rng_to_use.uniform(-1, 1)
-		r = (numpy.sin(theta + delta_theta)) / (numpy.sin(theta))
-		if r > rng_to_use.uniform(0, 1):
-			tentative_theta = theta + delta_theta
-		else:
-			tentative_theta = theta
-
-		tentative_px = (
-			self.pfixed * numpy.sin(tentative_theta) * numpy.cos(tentative_phi)
-		)
-		tentative_py = (
-			self.pfixed * numpy.sin(tentative_theta) * numpy.sin(tentative_phi)
-		)
-		tentative_pz = self.pfixed * numpy.cos(tentative_theta)
-
-		rx = dipole[3]
-		ry = dipole[4]
-		rz = dipole[5]
-
-		tentative_rx = rx + stdev.rx_step * rng_to_use.uniform(-1, 1)
-		if tentative_rx < self.xmin or tentative_rx > self.xmax:
-			tentative_rx = rx
-
-		tentative_ry = ry + stdev.ry_step * rng_to_use.uniform(-1, 1)
-		if tentative_ry < self.ymin or tentative_ry > self.ymax:
-			tentative_ry = ry
-		tentative_rz = rz + stdev.rz_step * rng_to_use.uniform(-1, 1)
-		if tentative_rz < self.zmin or tentative_rz > self.zmax:
-			tentative_rz = rz
-
-		w = dipole[6]
-		tentative_w = numpy.exp(
-			numpy.log(w) + (stdev.w_log_step * rng_to_use.uniform(-1, 1))
-		)
-		tentative_dip = numpy.array(
-			[
-				tentative_px,
-				tentative_py,
-				tentative_pz,
-				tentative_rx,
-				tentative_ry,
-				tentative_rz,
-				tentative_w,
-			]
-		)
-		return tentative_dip

pdme/model/log_spaced_random_choice_xy_model.py

@@ -5,8 +5,6 @@ from pdme.measurement import (
 	OscillatingDipole,
 	OscillatingDipoleArrangement,
 )
-import pdme.subspace_simulation
-from typing import Optional
 
 
 class LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(DipoleModel):
@@ -125,59 +123,3 @@ class LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel(DipoleModel):
 		w = 10 ** rng.uniform(self.wexp_min, self.wexp_max, shape)
 
 		return numpy.stack([px, py, pz, sx, sy, sz, w], axis=-1)
-
-	def markov_chain_monte_carlo_proposal(
-		self,
-		dipole: numpy.ndarray,
-		stdev: pdme.subspace_simulation.DipoleStandardDeviation,
-		rng_arg: Optional[numpy.random.Generator] = None,
-	) -> numpy.ndarray:
-		if rng_arg is None:
-			rng_to_use = self.rng
-		else:
-			rng_to_use = rng_arg
-
-		px = dipole[0]
-		py = dipole[1]
-		pz = dipole[2]
-		phi = numpy.arctan2(py, px)
-
-		# need to step phi, rx, ry, rz, w
-		# then p^\ast is 1/(2 phi_step) and Delta = phi_step(2 * {0, 1} - 1)
-		delta_phi = stdev.p_phi_step * rng_to_use.uniform(-1, 1)
-		tentative_phi = phi + delta_phi
-
-		tentative_px = self.pfixed * numpy.cos(tentative_phi)
-		tentative_py = self.pfixed * numpy.sin(tentative_phi)
-
-		rx = dipole[3]
-		ry = dipole[4]
-		rz = dipole[5]
-
-		tentative_rx = rx + stdev.rx_step * rng_to_use.uniform(-1, 1)
-		if tentative_rx < self.xmin or tentative_rx > self.xmax:
-			tentative_rx = rx
-
-		tentative_ry = ry + stdev.ry_step * rng_to_use.uniform(-1, 1)
-		if tentative_ry < self.ymin or tentative_ry > self.ymax:
-			tentative_ry = ry
-		tentative_rz = rz + stdev.rz_step * rng_to_use.uniform(-1, 1)
-		if tentative_rz < self.zmin or tentative_rz > self.zmax:
-			tentative_rz = rz
-
-		w = dipole[6]
-		tentative_w = numpy.exp(
-			numpy.log(w) + (stdev.w_log_step * rng_to_use.uniform(-1, 1))
-		)
-		tentative_dip = numpy.array(
-			[
-				tentative_px,
-				tentative_py,
-				pz,
-				tentative_rx,
-				tentative_ry,
-				tentative_rz,
-				tentative_w,
-			]
-		)
-		return tentative_dip

pdme/model/model.py

@@ -4,8 +4,7 @@ from pdme.measurement import (
 	OscillatingDipoleArrangement,
 )
 import logging
-import pdme.subspace_simulation
+
-from typing import List, Tuple, Optional
 
 _logger = logging.getLogger(__name__)
 
@@ -33,67 +32,3 @@ class DipoleModel:
 		For a given DipoleModel, gets a set of dipole collections as a monte_carlo_n x dipole_count x 7 numpy array.
 		"""
 		raise NotImplementedError
-
-	def markov_chain_monte_carlo_proposal(
-		self,
-		dipole: numpy.ndarray,
-		stdev: pdme.subspace_simulation.DipoleStandardDeviation,
-		rng_arg: Optional[numpy.random.Generator] = None,
-	) -> numpy.ndarray:
-		raise NotImplementedError
-
-	def get_mcmc_chain(
-		self,
-		seed,
-		cost_function,
-		chain_length,
-		stdevs: pdme.subspace_simulation.MCMCStandardDeviation,
-		initial_cost: Optional[float] = None,
-		rng_arg: Optional[numpy.random.Generator] = None,
-	) -> List[Tuple[float, numpy.ndarray]]:
-		"""
-		performs constrained markov chain monte carlo starting on seed parameter.
-		The cost function given is used as a constrained to condition the chain;
-		a new state is only accepted if cost_function(state) < cost_function(previous_state).
-		The stdevs passed in are the stdevs we're expected to use.
-
-		Because we're using this for subspace simulation where our proposal function is not too important, we're in good shape.
-		Note that for our adaptive stdevs to work, there's an unwritten contract that we sort each dipole in the state by frequency (increasing).
-
-		The seed is a list of dipoles, and each chain state is a list of dipoles as well.
-
-		initial_cost is a performance guy that lets you pre-populate the initial cost used to define the condition.
-		Probably premature optimisation.
-
-		Returns a chain of [ (cost: float, state: dipole_ndarray ) ] format.
-		"""
-		_logger.debug(
-			f"Starting Markov Chain Monte Carlo with seed: {seed} for chain length {chain_length} and provided stdevs {stdevs}"
-		)
-		chain: List[Tuple[float, numpy.ndarray]] = []
-		current = seed
-		if initial_cost is None:
-			cost_to_compare = cost_function(current)
-		else:
-			cost_to_compare = initial_cost
-		current_cost = cost_to_compare
-		for i in range(chain_length):
-			dips = []
-			for dipole_index, dipole in enumerate(current):
-				stdev = stdevs[dipole_index]
-				tentative_dip = self.markov_chain_monte_carlo_proposal(
-					dipole, stdev, rng_arg
-				)
-
-				dips.append(tentative_dip)
-			dips_array = pdme.subspace_simulation.sort_array_of_dipoles_by_frequency(
-				dips
-			)
-			tentative_cost = cost_function(dips_array)
-			if tentative_cost < cost_to_compare:
-				chain.append((tentative_cost, dips_array))
-				current = dips_array
-				current_cost = tentative_cost
-			else:
-				chain.append((current_cost, current))
-		return chain

pdme/subspace_simulation/__init__.py

@@ -1,55 +0,0 @@
-from dataclasses import dataclass
-from typing import Sequence
-import numpy
-from pdme.subspace_simulation.mcmc_costs import (
-	proportional_cost,
-	proportional_costs_vs_actual_measurement,
-)
-
-
-@dataclass
-class DipoleStandardDeviation:
-	"""
-	contains the dipole standard deviation to be used in porposals for markov chain monte carlo
-	"""
-
-	p_phi_step: float
-	p_theta_step: float
-	rx_step: float
-	ry_step: float
-	rz_step: float
-	w_log_step: float
-
-
-class MCMCStandardDeviation:
-	"""
-	wrapper for multiple standard deviations, allows for flexible length stuff
-	"""
-
-	def __init__(self, stdevs: Sequence[DipoleStandardDeviation]):
-		self.stdevs = stdevs
-		if len(stdevs) < 1:
-			raise ValueError(f"Got stdevs: {stdevs}, must have length > 1")
-
-	def __getitem__(self, key):
-		newkey = key % len(self.stdevs)
-		return self.stdevs[newkey]
-
-
-def sort_array_of_dipoles_by_frequency(configuration) -> numpy.ndarray:
-	"""
-	Say we have a situation of 2 dipoles, and we've created 8 samples. Then we'll have an (8, 2, 7) numpy array.
-	For each of the 8 samples, we want the 2 dipoles to be in order of frequency.
-
-	Utility function.
-	"""
-	return numpy.array(sorted(configuration, key=lambda l: l[6]))
-
-
-__all__ = [
-	"DipoleStandardDeviation",
-	"MCMCStandardDeviation",
-	"sort_array_of_dipoles_by_frequency",
-	"proportional_cost",
-	"proportional_costs_vs_actual_measurement",
-]

pdme/subspace_simulation/mcmc_costs.py

@@ -1,20 +0,0 @@
-import numpy
-import numpy.typing
-import pdme.util.fast_v_calc
-
-
-def proportional_cost(a: numpy.ndarray, b: numpy.ndarray) -> numpy.ndarray:
-	tops = numpy.max(b / a, axis=-1)
-	bottoms = numpy.max(a / b, axis=-1)
-	return numpy.maximum(tops, bottoms)
-
-
-def proportional_costs_vs_actual_measurement(
-	dot_inputs_array: numpy.ndarray,
-	actual_measurement_array: numpy.ndarray,
-	dipoles_to_test: numpy.ndarray,
-) -> numpy.ndarray:
-	vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(
-		dot_inputs_array, numpy.array([dipoles_to_test])
-	)
-	return proportional_cost(actual_measurement_array, vals)

poetry.lock

@@ -20,6 +20,28 @@ six = "*"
 [package.extras]
 test = ["astroid", "pytest"]
 
+[[package]]
+name = "atomicwrites"
+version = "1.4.0"
+description = "Atomic file writes."
+category = "dev"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[[package]]
+name = "attrs"
+version = "21.4.0"
+description = "Classes Without Boilerplate"
+category = "dev"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[package.extras]
+dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit", "cloudpickle"]
+docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"]
+tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "cloudpickle"]
+tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "cloudpickle"]
+
 [[package]]
 name = "backcall"
 version = "0.2.0"
@@ -69,17 +91,9 @@ category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 
-[[package]]
-name = "colored"
-version = "1.4.4"
-description = "Simple library for color and formatting to terminal"
-category = "dev"
-optional = false
-python-versions = "*"
-
 [[package]]
 name = "coverage"
-version = "7.2.7"
+version = "7.2.3"
 description = "Code coverage measurement for Python"
 category = "dev"
 optional = false
@@ -99,17 +113,6 @@ category = "dev"
 optional = false
 python-versions = ">=3.5"
 
-[[package]]
-name = "exceptiongroup"
-version = "1.1.2"
-description = "Backport of PEP 654 (exception groups)"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-
-[package.extras]
-test = ["pytest (>=6)"]
-
 [[package]]
 name = "executing"
 version = "0.8.3"
@@ -210,11 +213,11 @@ python-versions = "*"
 
 [[package]]
 name = "mypy"
-version = "0.961"
+version = "0.991"
 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"
@@ -223,6 +226,7 @@ typing-extensions = ">=3.10"
 
 [package.extras]
 dmypy = ["psutil (>=4.0)"]
+install-types = ["pip"]
 python2 = ["typed-ast (>=1.4.0,<2)"]
 reports = ["lxml"]
 
@@ -346,6 +350,14 @@ python-versions = "*"
 [package.extras]
 tests = ["pytest"]
 
+[[package]]
+name = "py"
+version = "1.11.0"
+description = "library with cross-python path, ini-parsing, io, code, log facilities"
+category = "dev"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
 [[package]]
 name = "pycodestyle"
 version = "2.8.0"
@@ -383,30 +395,32 @@ diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
 name = "pytest"
-version = "7.4.0"
+version = "6.2.5"
 description = "pytest: simple powerful testing with Python"
 category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.6"
 
 [package.dependencies]
+atomicwrites = {version = ">=1.0", markers = "sys_platform == \"win32\""}
+attrs = ">=19.2.0"
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
-exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
 iniconfig = "*"
 packaging = "*"
 pluggy = ">=0.12,<2.0"
-tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
+py = ">=1.8.2"
+toml = "*"
 
 [package.extras]
-testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
+testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "requests", "xmlschema"]
 
 [[package]]
 name = "pytest-cov"
-version = "4.1.0"
+version = "3.0.0"
 description = "Pytest plugin for measuring coverage."
 category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.6"
 
 [package.dependencies]
 coverage = {version = ">=5.2.1", extras = ["toml"]}
@@ -456,16 +470,12 @@ pure-eval = "*"
 tests = ["pytest", "typeguard", "pygments", "littleutils", "cython"]
 
 [[package]]
-name = "syrupy"
+name = "toml"
-version = "4.0.8"
+version = "0.10.2"
-description = "Pytest Snapshot Test Utility"
+description = "Python Library for Tom's Obvious, Minimal Language"
 category = "dev"
 optional = false
-python-versions = ">=3.8.1,<4"
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
-
-[package.dependencies]
-colored = ">=1.3.92,<2.0.0"
-pytest = ">=7.0.0,<8.0.0"
 
 [[package]]
 name = "tomli"
@@ -504,20 +514,20 @@ python-versions = "*"
 
 [metadata]
 lock-version = "1.1"
-python-versions = ">=3.8.1,<3.10"
+python-versions = "^3.8,<3.10"
-content-hash = "b5275c33449e8f85acbf9c0f6dfe1ec4e7296adfa16360d782b33534e1223638"
+content-hash = "567ea207157ac7a29ce1939535942beb45f7f382aeee56e54e9eeac37a7a7b73"
 
 [metadata.files]
 appnope = []
 asttokens = []
+atomicwrites = []
+attrs = []
 backcall = []
 black = []
 click = []
 colorama = []
-colored = []
 coverage = []
 decorator = []
-exceptiongroup = []
 executing = []
 flake8 = []
 iniconfig = []
@@ -538,6 +548,7 @@ pluggy = []
 prompt-toolkit = []
 ptyprocess = []
 pure-eval = []
+py = []
 pycodestyle = []
 pyflakes = []
 pygments = []
@@ -547,7 +558,7 @@ pytest-cov = []
 scipy = []
 six = []
 stack-data = []
-syrupy = []
+toml = []
 tomli = []
 traitlets = []
 typing-extensions = []

pyproject.toml

@@ -1,24 +1,23 @@
 [tool.poetry]
 name = "pdme"
-version = "0.8.9"
+version = "0.8.8"
 description = "Python dipole model evaluator"
 authors = ["Deepak <dmallubhotla+github@gmail.com>"]
 license = "GPL-3.0-only"
 readme = "README.md"
 
 [tool.poetry.dependencies]
-python = ">=3.8.1,<3.10"
+python = "^3.8,<3.10"
 numpy = "^1.22.3"
 scipy = "~1.10"
 
 [tool.poetry.dev-dependencies]
 pytest = ">=6"
 flake8 = "^4.0.0"
-pytest-cov = "^4.1.0"
+pytest-cov = "^3.0.0"
 mypy = "^0.991"
 ipython = "^8.2.0"
 black = "^22.3.0"
-syrupy = "^4.0.8"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]

tests/model/__snapshots__/test_log_spaced_fixed_orientation_fixedxy_orientation_mcmc.ambr

@@ -1,55 +0,0 @@
-# serializer version: 1
-# name: test_log_spaced_fixedxy_orientation_mcmc_basic
-  list([
-    tuple(
-      array([3984.46179656]),
-      array([[ 9.55610128,  2.94634152,  0.        ,  9.21529051, -2.46576127,
-           2.42481096,  9.19034554]]),
-    ),
-    tuple(
-      array([8583.99087872]),
-      array([[ 9.99991539,  0.04113671,  0.        ,  8.71258954, -2.26599865,
-           2.60452102,  6.37042214]]),
-    ),
-    tuple(
-      array([6215.6376616]),
-      array([[ 9.81950685, -1.89137124,  0.        ,  8.90637055, -2.48043039,
-           2.28444435,  8.84239221]]),
-    ),
-    tuple(
-      array([424.73328466]),
-      array([[ 1.00028483,  9.94984574,  0.        ,  8.53064898, -2.59230757,
-           2.33774773,  8.6714416 ]]),
-    ),
-    tuple(
-      array([300.92203808]),
-      array([[ 1.4003442 ,  9.90146636,  0.        ,  8.05557992, -2.6753126 ,
-           2.65915755, 13.02021385]]),
-    ),
-    tuple(
-      array([2400.01072771]),
-      array([[ 9.97761813,  0.66868263,  0.        ,  8.69171028, -2.73145011,
-           2.90140456, 19.94999593]]),
-    ),
-    tuple(
-      array([5001.46205113]),
-      array([[ 9.93976109, -1.09596962,  0.        ,  8.95245025, -2.59409162,
-           2.90140456,  9.75535945]]),
-    ),
-    tuple(
-      array([195.21980745]),
-      array([[ 0.20690762,  9.99785923,  0.        ,  9.59636585, -2.83240984,
-           2.90140456, 16.14771567]]),
-    ),
-    tuple(
-      array([2698.2588445]),
-      array([[-9.68130127, -2.50447712,  0.        ,  8.94823619, -2.92889659,
-           2.77065328, 13.63173263]]),
-    ),
-    tuple(
-      array([1193.69854739]),
-      array([[-6.16597091, -7.87278875,  0.        ,  9.62210721, -2.75993924,
-           2.77065328,  5.64553534]]),
-    ),
-  ])
-# ---

tests/model/__snapshots__/test_log_spaced_fixed_orientation_free_orientation_mcmc.ambr

@@ -1,55 +0,0 @@
-# serializer version: 1
-# name: test_log_spaced_free_orientation_mcmc_basic
-  list([
-    tuple(
-      array([3167.67112687]),
-      array([[ 9.60483896, -1.41627817, -2.3960853 , -4.76615152, -1.80902942,
-           2.11809123, 16.17452242]]),
-    ),
-    tuple(
-      array([3167.67112687]),
-      array([[ 9.60483896, -1.41627817, -2.3960853 , -4.76615152, -1.80902942,
-           2.11809123, 16.17452242]]),
-    ),
-    tuple(
-      array([3167.67112687]),
-      array([[ 9.60483896, -1.41627817, -2.3960853 , -4.76615152, -1.80902942,
-           2.11809123, 16.17452242]]),
-    ),
-    tuple(
-      array([736.03065271]),
-      array([[ 4.1660069 , -8.11557337,  4.0965663 , -4.35968351, -1.97945216,
-           2.43615641, 12.92143144]]),
-    ),
-    tuple(
-      array([736.03065271]),
-      array([[ 4.1660069 , -8.11557337,  4.0965663 , -4.35968351, -1.97945216,
-           2.43615641, 12.92143144]]),
-    ),
-    tuple(
-      array([736.03065271]),
-      array([[ 4.1660069 , -8.11557337,  4.0965663 , -4.35968351, -1.97945216,
-           2.43615641, 12.92143144]]),
-    ),
-    tuple(
-      array([2248.07799863]),
-      array([[-1.71755535, -5.59925137,  8.10545419, -4.03306318, -1.81098441,
-           2.77407111, 32.28020575]]),
-    ),
-    tuple(
-      array([1663.31067274]),
-      array([[-5.16785855,  2.7558756 ,  8.10545419, -3.34620897, -1.74763642,
-           2.42770463, 52.98214008]]),
-    ),
-    tuple(
-      array([1329.27041439]),
-      array([[ -1.39600464,   9.69718343,  -2.00394725,  -2.59147366,
-           -1.91246681,   2.07361175, 123.01833742]]),
-    ),
-    tuple(
-      array([355.76955919]),
-      array([[  9.76047401,   0.84696075,  -2.00394725,  -3.04310053,
-           -1.99338573,   2.1185589 , 271.35743739]]),
-    ),
-  ])
-# ---

tests/model/__snapshots__/test_log_spaced_fixed_orientation_mcmc.ambr

@@ -1,55 +0,0 @@
-# serializer version: 1
-# name: test_log_spaced_fixed_orientation_mcmc_basic
-  list([
-    tuple(
-      array([50.56831193]),
-      array([[ 0.        ,  0.        , 10.        , -2.3960853 ,  4.23246234,
-           2.26169242, 39.39900844]]),
-    ),
-    tuple(
-      array([50.56831193]),
-      array([[ 0.        ,  0.        , 10.        , -2.3960853 ,  4.23246234,
-           2.26169242, 39.39900844]]),
-    ),
-    tuple(
-      array([47.40865455]),
-      array([[ 0.        ,  0.        , 10.        , -2.03666518,  4.14084039,
-           2.21309317, 47.82371559]]),
-    ),
-    tuple(
-      array([47.40865455]),
-      array([[ 0.        ,  0.        , 10.        , -2.03666518,  4.14084039,
-           2.21309317, 47.82371559]]),
-    ),
-    tuple(
-      array([47.40865455]),
-      array([[ 0.        ,  0.        , 10.        , -2.03666518,  4.14084039,
-           2.21309317, 47.82371559]]),
-    ),
-    tuple(
-      array([47.40865455]),
-      array([[ 0.        ,  0.        , 10.        , -2.03666518,  4.14084039,
-           2.21309317, 47.82371559]]),
-    ),
-    tuple(
-      array([22.93279028]),
-      array([[ 0.        ,  0.        , 10.        , -1.63019717,  3.97041764,
-           2.53115835, 38.2051999 ]]),
-    ),
-    tuple(
-      array([28.81197733]),
-      array([[ 0.        ,  0.        , 10.        , -1.14570315,  4.07709911,
-           2.48697441, 49.58615195]]),
-    ),
-    tuple(
-      array([28.81197733]),
-      array([[ 0.        ,  0.        , 10.        , -1.14570315,  4.07709911,
-           2.48697441, 49.58615195]]),
-    ),
-    tuple(
-      array([40.97406005]),
-      array([[ 0.        ,  0.        , 10.        , -0.50178755,  3.83878089,
-           2.93560796, 82.07827571]]),
-    ),
-  ])
-# ---

tests/model/__snapshots__/test_log_spaced_random_count_multiple_dipole_fixed_orientation_fixed_magnitude_model.ambr

@@ -1,31 +0,0 @@
-# serializer version: 1
-# name: test_random_count_multiple_dipole_fixed_or_fixed_mag_model_get_n_dipoles
-  list([
-    list([
-      list([
-        10.0,
-        0.0,
-        6.123233995736766e-16,
-        -2.3960852996076447,
-        4.232462337639554,
-        2.2616924238635443,
-        39.399008444891905,
-      ]),
-    ]),
-  ])
-# ---
-# name: test_random_count_multiple_dipole_fixed_or_fixed_mag_model_get_n_dipoles.1
-  list([
-    list([
-      list([
-        10.0,
-        0.0,
-        6.123233995736766e-16,
-        -2.3960852996076447,
-        4.232462337639554,
-        2.2616924238635443,
-        39.399008444891905,
-      ]),
-    ]),
-  ])
-# ---

tests/model/test_log_spaced_fixed_orientation_fixedxy_orientation_mcmc.py

@@ -1,90 +0,0 @@
-from pdme.model import (
-	LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel,
-)
-import pdme.inputs
-import pdme.measurement.input_types
-import pdme.subspace_simulation
-import numpy
-
-SEED_TO_USE = 42
-
-
-def get_cost_function():
-	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(SEED_TO_USE)
-
-	freqs = [0.01, 0.1, 1, 10, 100]
-	dot_positions = [[-1.5, 0, 0], [-0.5, 0, 0], [0.5, 0, 0], [1.5, 0, 0]]
-	dot_inputs = pdme.inputs.inputs_with_frequency_range(dot_positions, freqs)
-	dot_input_array = pdme.measurement.input_types.dot_inputs_to_array(dot_inputs)
-
-	actual_dipoles = model.get_dipoles(0, numpy.random.default_rng(SEED_TO_USE))
-	actual_measurements = actual_dipoles.get_dot_measurements(dot_inputs)
-	actual_measurements_array = numpy.array([m.v for m in actual_measurements])
-
-	def cost_to_use(sample_dipoles: numpy.ndarray) -> numpy.ndarray:
-		return pdme.subspace_simulation.proportional_costs_vs_actual_measurement(
-			dot_input_array, actual_measurements_array, sample_dipoles
-		)
-
-	return cost_to_use
-
-
-def test_log_spaced_fixedxy_orientation_mcmc_basic(snapshot):
-
-	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)
-
-	seed = model.get_monte_carlo_dipole_inputs(1, -1)[0]
-
-	cost_function = get_cost_function()
-	stdev = pdme.subspace_simulation.DipoleStandardDeviation(2, 2, 1, 0.25, 0.5, 1)
-	stdevs = pdme.subspace_simulation.MCMCStandardDeviation([stdev])
-
-	chain = model.get_mcmc_chain(
-		seed, cost_function, 10, stdevs, rng_arg=numpy.random.default_rng(1515)
-	)
-
-	assert chain == snapshot

tests/model/test_log_spaced_fixed_orientation_free_orientation_mcmc.py

@@ -1,90 +0,0 @@
-from pdme.model import (
-	LogSpacedRandomCountMultipleDipoleFixedMagnitudeModel,
-)
-import pdme.inputs
-import pdme.measurement.input_types
-import pdme.subspace_simulation
-import numpy
-
-SEED_TO_USE = 42
-
-
-def get_cost_function():
-	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 = LogSpacedRandomCountMultipleDipoleFixedMagnitudeModel(
-		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(SEED_TO_USE)
-
-	freqs = [0.01, 0.1, 1, 10, 100]
-	dot_positions = [[-1.5, 0, 0], [-0.5, 0, 0], [0.5, 0, 0], [1.5, 0, 0]]
-	dot_inputs = pdme.inputs.inputs_with_frequency_range(dot_positions, freqs)
-	dot_input_array = pdme.measurement.input_types.dot_inputs_to_array(dot_inputs)
-
-	actual_dipoles = model.get_dipoles(0, numpy.random.default_rng(SEED_TO_USE))
-	actual_measurements = actual_dipoles.get_dot_measurements(dot_inputs)
-	actual_measurements_array = numpy.array([m.v for m in actual_measurements])
-
-	def cost_to_use(sample_dipoles: numpy.ndarray) -> numpy.ndarray:
-		return pdme.subspace_simulation.proportional_costs_vs_actual_measurement(
-			dot_input_array, actual_measurements_array, sample_dipoles
-		)
-
-	return cost_to_use
-
-
-def test_log_spaced_free_orientation_mcmc_basic(snapshot):
-
-	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 = LogSpacedRandomCountMultipleDipoleFixedMagnitudeModel(
-		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)
-
-	seed = model.get_monte_carlo_dipole_inputs(1, -1)[0]
-
-	cost_function = get_cost_function()
-	stdev = pdme.subspace_simulation.DipoleStandardDeviation(2, 2, 1, 0.25, 0.5, 1)
-	stdevs = pdme.subspace_simulation.MCMCStandardDeviation([stdev])
-
-	chain = model.get_mcmc_chain(
-		seed, cost_function, 10, stdevs, rng_arg=numpy.random.default_rng(1515)
-	)
-
-	assert chain == snapshot

tests/model/test_log_spaced_fixed_orientation_mcmc.py

@@ -1,98 +0,0 @@
-from pdme.model import (
-	LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel,
-)
-import pdme.inputs
-import pdme.measurement.input_types
-import pdme.subspace_simulation
-import numpy
-
-SEED_TO_USE = 42
-
-
-def get_cost_function():
-	x_min = -10
-	x_max = 10
-	y_min = -5
-	y_max = 5
-	z_min = 2
-	z_max = 3
-	p_fixed = 10
-	theta = 0
-	phi = 0
-	max_frequency = 5
-
-	model = LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel(
-		x_min,
-		x_max,
-		y_min,
-		y_max,
-		z_min,
-		z_max,
-		0,
-		max_frequency,
-		p_fixed,
-		theta,
-		phi,
-		1,
-		0.5,
-	)
-	model.rng = numpy.random.default_rng(SEED_TO_USE)
-
-	freqs = [0.01, 0.1, 1, 10, 100]
-	dot_positions = [[-1.5, 0, 0], [-0.5, 0, 0], [0.5, 0, 0], [1.5, 0, 0]]
-	dot_inputs = pdme.inputs.inputs_with_frequency_range(dot_positions, freqs)
-	dot_input_array = pdme.measurement.input_types.dot_inputs_to_array(dot_inputs)
-
-	actual_dipoles = model.get_dipoles(0, numpy.random.default_rng(SEED_TO_USE))
-	actual_measurements = actual_dipoles.get_dot_measurements(dot_inputs)
-	actual_measurements_array = numpy.array([m.v for m in actual_measurements])
-
-	def cost_to_use(sample_dipoles: numpy.ndarray) -> numpy.ndarray:
-		return pdme.subspace_simulation.proportional_costs_vs_actual_measurement(
-			dot_input_array, actual_measurements_array, sample_dipoles
-		)
-
-	return cost_to_use
-
-
-def test_log_spaced_fixed_orientation_mcmc_basic(snapshot):
-
-	x_min = -10
-	x_max = 10
-	y_min = -5
-	y_max = 5
-	z_min = 2
-	z_max = 3
-	p_fixed = 10
-	theta = 0
-	phi = 0
-	max_frequency = 5
-
-	model = LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel(
-		x_min,
-		x_max,
-		y_min,
-		y_max,
-		z_min,
-		z_max,
-		0,
-		max_frequency,
-		p_fixed,
-		theta,
-		phi,
-		1,
-		0.5,
-	)
-	model.rng = numpy.random.default_rng(1234)
-
-	seed = model.get_monte_carlo_dipole_inputs(1, -1)[0]
-
-	cost_function = get_cost_function()
-	stdev = pdme.subspace_simulation.DipoleStandardDeviation(2, 2, 1, 0.25, 0.5, 1)
-	stdevs = pdme.subspace_simulation.MCMCStandardDeviation([stdev])
-
-	chain = model.get_mcmc_chain(
-		seed, cost_function, 10, stdevs, rng_arg=numpy.random.default_rng(1515)
-	)
-
-	assert chain == snapshot

tests/model/test_log_spaced_random_count_multiple_dipole_fixed_orientation_fixed_magnitude_model.py

@@ -115,7 +115,7 @@ def test_random_count_multiple_dipole_fixed_mag_model_get_dipoles_invariant():
 			)
 
 
-def test_random_count_multiple_dipole_fixed_or_fixed_mag_model_get_n_dipoles(snapshot):
+def test_random_count_multiple_dipole_fixed_or_fixed_mag_model_get_n_dipoles():
 	# TODO: this test is a bit garbage just calls things without testing.
 	x_min = -10
 	x_max = 10
@@ -145,9 +145,7 @@ def test_random_count_multiple_dipole_fixed_or_fixed_mag_model_get_n_dipoles(sna
 	)
 	model.rng = numpy.random.default_rng(1234)
 
-	actual_inputs = model.get_monte_carlo_dipole_inputs(1, max_frequency)
+	model.get_monte_carlo_dipole_inputs(1, max_frequency)
-	assert actual_inputs.tolist() == snapshot
+	model.get_monte_carlo_dipole_inputs(
-	actual_monte_carlo_inputs = model.get_monte_carlo_dipole_inputs(
 		1, max_frequency, numpy.random.default_rng(1234)
 	)
-	assert actual_monte_carlo_inputs.tolist() == snapshot

tests/subspace_simulation/__snapshots__/test_costs.ambr

@@ -1,4 +0,0 @@
-# serializer version: 1
-# name: test_proportional_costs
-  7000.0
-# ---

tests/subspace_simulation/__snapshots__/test_sort_dipoles.ambr

@@ -1,32 +0,0 @@
-# serializer version: 1
-# name: test_sort_dipoles_by_freq
-  list([
-    list([
-      100.0,
-      200.0,
-      300.0,
-      400.0,
-      500.0,
-      600.0,
-      0.07,
-    ]),
-    list([
-      1.0,
-      2.0,
-      3.0,
-      4.0,
-      5.0,
-      6.0,
-      7.0,
-    ]),
-    list([
-      10.0,
-      200.0,
-      30.0,
-      41.0,
-      315.0,
-      0.31,
-      100.0,
-    ]),
-  ])
-# ---

tests/subspace_simulation/__snapshots__/test_stdevs.ambr

@@ -1,22 +0,0 @@
-# serializer version: 1
-# name: test_return_four
-  DipoleStandardDeviation(p_phi_step=1, p_theta_step=2, rx_step=3, ry_step=4, rz_step=5, w_log_step=6)
-# ---
-# name: test_return_four.1
-  DipoleStandardDeviation(p_phi_step=10, p_theta_step=20, rx_step=30, ry_step=40, rz_step=50, w_log_step=60)
-# ---
-# name: test_return_four.2
-  DipoleStandardDeviation(p_phi_step=0.1, p_theta_step=0.2, rx_step=0.3, ry_step=0.4, rz_step=0.5, w_log_step=0.6)
-# ---
-# name: test_return_four.3
-  DipoleStandardDeviation(p_phi_step=1, p_theta_step=2, rx_step=3, ry_step=4, rz_step=5, w_log_step=6)
-# ---
-# name: test_return_four.4
-  DipoleStandardDeviation(p_phi_step=10, p_theta_step=20, rx_step=30, ry_step=40, rz_step=50, w_log_step=60)
-# ---
-# name: test_return_four.5
-  DipoleStandardDeviation(p_phi_step=0.1, p_theta_step=0.2, rx_step=0.3, ry_step=0.4, rz_step=0.5, w_log_step=0.6)
-# ---
-# name: test_return_one
-  DipoleStandardDeviation(p_phi_step=1, p_theta_step=2, rx_step=3, ry_step=4, rz_step=5, w_log_step=6)
-# ---

tests/subspace_simulation/test_costs.py

@@ -1,10 +0,0 @@
-import pdme.subspace_simulation
-import numpy
-
-
-def test_proportional_costs(snapshot):
-	a = numpy.array([2, 4, 5, 6, 7, 8, 10])
-	b = numpy.array([51, 13, 1, 31, 0.001, 3, 1])
-
-	actual_result = pdme.subspace_simulation.proportional_cost(a, b).tolist()
-	assert actual_result == snapshot

tests/subspace_simulation/test_sort_dipoles.py

@@ -1,15 +0,0 @@
-import numpy
-import pdme.subspace_simulation
-
-
-def test_sort_dipoles_by_freq(snapshot):
-	orig = numpy.array(
-		[
-			[1, 2, 3, 4, 5, 6, 7],
-			[100, 200, 300, 400, 500, 600, 0.07],
-			[10, 200, 30, 41, 315, 0.31, 100],
-		]
-	)
-
-	actual_sorted = pdme.subspace_simulation.sort_array_of_dipoles_by_frequency(orig)
-	assert actual_sorted.tolist() == snapshot

tests/subspace_simulation/test_stdevs.py

@@ -1,38 +0,0 @@
-import pytest
-import pdme.subspace_simulation
-
-
-def test_empty():
-	with pytest.raises(ValueError):
-		pdme.subspace_simulation.MCMCStandardDeviation([])
-
-
-def test_return_one(snapshot):
-	stdev = pdme.subspace_simulation.DipoleStandardDeviation(
-		1,
-		2,
-		3,
-		4,
-		5,
-		6,
-	)
-	stdevs = pdme.subspace_simulation.MCMCStandardDeviation([stdev])
-
-	assert stdevs[3] == snapshot
-	assert stdevs[3] == stdev
-
-
-def test_return_four(snapshot):
-	stdev_list = [
-		pdme.subspace_simulation.DipoleStandardDeviation(1, 2, 3, 4, 5, 6),
-		pdme.subspace_simulation.DipoleStandardDeviation(10, 20, 30, 40, 50, 60),
-		pdme.subspace_simulation.DipoleStandardDeviation(0.1, 0.2, 0.3, 0.4, 0.5, 0.6),
-	]
-	stdevs = pdme.subspace_simulation.MCMCStandardDeviation(stdev_list)
-
-	assert stdevs[0] == snapshot
-	assert stdevs[1] == snapshot
-	assert stdevs[2] == snapshot
-	assert stdevs[3] == snapshot
-	assert stdevs[4] == snapshot
-	assert stdevs[5] == snapshot