chore(deps): update dependency flake8 to v6

Reviewed-on: #32

CHANGELOG.md

@@ -2,6 +2,71 @@
 
 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.
 
+### [0.7.3](https://gitea.deepak.science:2222/physics/deepdog/compare/0.7.2...0.7.3) (2023-07-27)
+
+
+### Features
+
+* adds utility options and avoids memory leak ([598dad1](https://gitea.deepak.science:2222/physics/deepdog/commit/598dad1e6dc8fc0b7a5b4a90c8e17bf744e8d98c))
+
+### [0.7.2](https://gitea.deepak.science:2222/physics/deepdog/compare/0.7.1...0.7.2) (2023-07-24)
+
+
+### Features
+
+* clamps results now ([9bb8fc5](https://gitea.deepak.science:2222/physics/deepdog/commit/9bb8fc50fe1bd1a285a333c5a396bfb6ac3176cf))
+
+
+### Bug Fixes
+
+* fixes clamping format etc. ([a170a3c](https://gitea.deepak.science:2222/physics/deepdog/commit/a170a3ce01adcec356e5aaab9abcc0ec4accd64b))
+
+### [0.7.1](https://gitea.deepak.science:2222/physics/deepdog/compare/0.7.0...0.7.1) (2023-07-24)
+
+
+### Features
+
+* adds subset simulation stuff ([33cab9a](https://gitea.deepak.science:2222/physics/deepdog/commit/33cab9ab4179cec13ae9e591a8ffc32df4dda989))
+
+## [0.7.0](https://gitea.deepak.science:2222/physics/deepdog/compare/0.6.7...0.7.0) (2023-05-01)
+
+
+### ⚠ BREAKING CHANGES
+
+* removes fastfilter parameter because it should never be needed
+
+### Features
+
+* adds pair capability to real spectrum run hopefully ([a089951](https://gitea.deepak.science:2222/physics/deepdog/commit/a089951bbefcd8a0b2efeb49b7a8090412cbb23d))
+* removes fastfilter parameter because it should never be needed ([a015daf](https://gitea.deepak.science:2222/physics/deepdog/commit/a015daf5ff6fa5f6155c8d7e02981b588840a5b0))
+
+### [0.6.7](https://gitea.deepak.science:2222/physics/deepdog/compare/0.6.6...0.6.7) (2023-04-14)
+
+
+### Features
+
+* adds option to cap core count for real spectrum run ([bf15f4a](https://gitea.deepak.science:2222/physics/deepdog/commit/bf15f4a7b7f59504983624e7d512ed7474372032))
+* adds option to cap core count for temp aware run ([12903b2](https://gitea.deepak.science:2222/physics/deepdog/commit/12903b2540cefb040174d230bc0d04719a6dc1b7))
+
+
+### Bug Fixes
+
+* avoids redefinition of core count in loop ([1cf4454](https://gitea.deepak.science:2222/physics/deepdog/commit/1cf44541531541088198bd4599d467df3e1acbcf))
+
+### [0.6.6](https://gitea.deepak.science:2222/physics/deepdog/compare/0.6.5...0.6.6) (2023-04-09)
+
+
+### Bug Fixes
+
+* removes bad logging in multiprocessing function ([8fd1b75](https://gitea.deepak.science:2222/physics/deepdog/commit/8fd1b75e1378301210bfa8f14dd09174bbd21414))
+
+### [0.6.5](https://gitea.deepak.science:2222/physics/deepdog/compare/0.6.4...0.6.5) (2023-04-09)
+
+
+### Features
+
+* adds temp aware guy using new pdme temp-flexible feature for bundling temp models ([de1ec3e](https://gitea.deepak.science:2222/physics/deepdog/commit/de1ec3e70062d418e0d4c89716905cc9313d2e26))
+
 ### [0.6.4](https://gitea.deepak.science:2222/physics/deepdog/compare/0.6.3...0.6.4) (2022-08-13)
 
 

Jenkinsfile

@@ -4,7 +4,7 @@ pipeline {
 		label 'deepdog'  // all your pods will be named with this prefix, followed by a unique id
 		idleMinutes 5  // how long the pod will live after no jobs have run on it
 		yamlFile 'jenkins/ci-agent-pod.yaml'  // path to the pod definition relative to the root of our project
-		defaultContainer 'python'  // define a default container if more than a few stages use it, will default to jnlp container
+		defaultContainer 'poetry'  // define a default container if more than a few stages use it, will default to jnlp container
 	  }
 	}
 
@@ -12,36 +12,30 @@ pipeline {
 		parallelsAlwaysFailFast()
 	}
 
-	environment {
-		POETRY_HOME="/opt/poetry"
-		POETRY_VERSION="1.1.12"
-	}
-
 	stages {
 		stage('Build') {
 			steps {
 				echo 'Building...'
 				sh 'python --version'
-				sh 'curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python'
-				sh '${POETRY_HOME}/bin/poetry --version'
-				sh '${POETRY_HOME}/bin/poetry install'
+				sh 'poetry --version'
+				sh 'poetry install'
 			}
 		}
 		stage('Test') {
 			parallel{
 				stage('pytest') {
 					steps {
-						sh '${POETRY_HOME}/bin/poetry run pytest'
+						sh 'poetry run pytest'
 					}
 				}
 				stage('lint') {
 					steps {
-						sh '${POETRY_HOME}/bin/poetry run flake8 deepdog tests'
+						sh 'poetry run flake8 deepdog tests'
 					}
 				}
 				stage('mypy') {
 					steps {
-						sh '${POETRY_HOME}/bin/poetry run mypy deepdog'
+						sh 'poetry run mypy deepdog'
 					}
 				}
 			}
@@ -57,7 +51,7 @@ pipeline {
 			}
 			steps {
 				echo 'Deploying...'
-				sh '${POETRY_HOME}/bin/poetry publish -u ${PYPI_USR} -p ${PYPI_PSW} --build'
+				sh 'poetry publish -u ${PYPI_USR} -p ${PYPI_PSW} --build'
 			}
 		}
 

README.md

@@ -5,7 +5,7 @@
 [![Jenkins](https://img.shields.io/jenkins/build?jobUrl=https%3A%2F%2Fjenkins.deepak.science%2Fjob%2Fgitea-physics%2Fjob%2Fdeepdog%2Fjob%2Fmaster&style=flat-square)](https://jenkins.deepak.science/job/gitea-physics/job/deepdog/job/master/)
 ![Jenkins tests](https://img.shields.io/jenkins/tests?compact_message&jobUrl=https%3A%2F%2Fjenkins.deepak.science%2Fjob%2Fgitea-physics%2Fjob%2Fdeepdog%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%2Fdeepdog%2Fjob%2Fmaster%2F&style=flat-square)
-![Maintenance](https://img.shields.io/maintenance/yes/2022?style=flat-square)
+![Maintenance](https://img.shields.io/maintenance/yes/2023?style=flat-square)
 
 The DiPole DiaGnostic tool.
 

deepdog/__init__.py

@@ -3,6 +3,8 @@ from deepdog.meta import __version__
 from deepdog.bayes_run import BayesRun
 from deepdog.bayes_run_simulpairs import BayesRunSimulPairs
 from deepdog.real_spectrum_run import RealSpectrumRun
+from deepdog.temp_aware_real_spectrum_run import TempAwareRealSpectrumRun
+from deepdog.bayes_run_with_ss import BayesRunWithSubspaceSimulation
 
 
 def get_version():
@@ -14,6 +16,8 @@ __all__ = [
 	"BayesRun",
 	"BayesRunSimulPairs",
 	"RealSpectrumRun",
+	"TempAwareRealSpectrumRun",
+	"BayesRunWithSubspaceSimulation",
 ]
 
 

deepdog/bayes_run_with_ss.py

@@ -0,0 +1,238 @@
+import deepdog.subset_simulation
+import pdme.inputs
+import pdme.model
+import pdme.measurement.input_types
+import pdme.measurement.oscillating_dipole
+import pdme.util.fast_v_calc
+import pdme.util.fast_nonlocal_spectrum
+from typing import Sequence, Tuple, List, Optional
+import datetime
+import csv
+import logging
+import numpy
+import numpy.typing
+
+
+# TODO: remove hardcode
+CHUNKSIZE = 50
+
+# TODO: It's garbage to have this here duplicated from pdme.
+DotInput = Tuple[numpy.typing.ArrayLike, float]
+
+
+CLAMPING_FACTOR = 10
+
+_logger = logging.getLogger(__name__)
+
+
+class BayesRunWithSubspaceSimulation:
+	"""
+	A single Bayes run for a given set of dots.
+
+	Parameters
+	----------
+	dot_inputs : Sequence[DotInput]
+	The dot inputs for this bayes run.
+
+	models_with_names : Sequence[Tuple(str, pdme.model.DipoleModel)]
+	The models to evaluate.
+
+	actual_model : pdme.model.DipoleModel
+	The model which is actually correct.
+
+	filename_slug : str
+	The filename slug to include.
+
+	run_count: int
+	The number of runs to do.
+	"""
+
+	def __init__(
+		self,
+		dot_positions: Sequence[numpy.typing.ArrayLike],
+		frequency_range: Sequence[float],
+		models_with_names: Sequence[Tuple[str, pdme.model.DipoleModel]],
+		actual_model: pdme.model.DipoleModel,
+		filename_slug: str,
+		max_frequency: float = 20,
+		end_threshold: float = None,
+		run_count=100,
+		chunksize: int = CHUNKSIZE,
+		ss_n_c: int = 500,
+		ss_n_s: int = 100,
+		ss_m_max: int = 15,
+		ss_target_cost: Optional[float] = None,
+		ss_level_0_seed: int = 200,
+		ss_mcmc_seed: int = 20,
+		ss_use_adaptive_steps=True,
+		ss_default_phi_step=0.01,
+		ss_default_theta_step=0.01,
+		ss_default_r_step=0.01,
+		ss_default_w_log_step=0.01,
+		ss_default_upper_w_log_step=4,
+		ss_dump_last_generation=False,
+	) -> None:
+		self.dot_inputs = pdme.inputs.inputs_with_frequency_range(
+			dot_positions, frequency_range
+		)
+		self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(
+			self.dot_inputs
+		)
+
+		self.models_with_names = models_with_names
+		self.models = [model for (_, model) in models_with_names]
+		self.model_names = [name for (name, _) in models_with_names]
+		self.actual_model = actual_model
+
+		self.n: int
+		try:
+			self.n = self.actual_model.n  # type: ignore
+		except AttributeError:
+			self.n = 1
+
+		self.model_count = len(self.models)
+
+		self.csv_fields = []
+		for i in range(self.n):
+			self.csv_fields.extend(
+				[
+					f"dipole_moment_{i+1}",
+					f"dipole_location_{i+1}",
+					f"dipole_frequency_{i+1}",
+				]
+			)
+		self.compensate_zeros = True
+		self.chunksize = chunksize
+		for name in self.model_names:
+			self.csv_fields.extend([f"{name}_likelihood", f"{name}_prob"])
+
+		self.probabilities = [1 / self.model_count] * self.model_count
+
+		timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
+		self.filename = f"{timestamp}-{filename_slug}.bayesrunwithss.csv"
+		self.max_frequency = max_frequency
+
+		if end_threshold is not None:
+			if 0 < end_threshold < 1:
+				self.end_threshold: float = end_threshold
+				self.use_end_threshold = True
+				_logger.info(f"Will abort early, at {self.end_threshold}.")
+			else:
+				raise ValueError(
+					f"end_threshold should be between 0 and 1, but is actually {end_threshold}"
+				)
+
+		self.ss_n_c = ss_n_c
+		self.ss_n_s = ss_n_s
+		self.ss_m_max = ss_m_max
+		self.ss_target_cost = ss_target_cost
+		self.ss_level_0_seed = ss_level_0_seed
+		self.ss_mcmc_seed = ss_mcmc_seed
+		self.ss_use_adaptive_steps = ss_use_adaptive_steps
+		self.ss_default_phi_step = ss_default_phi_step
+		self.ss_default_theta_step = ss_default_theta_step
+		self.ss_default_r_step = ss_default_r_step
+		self.ss_default_w_log_step = ss_default_w_log_step
+		self.ss_default_upper_w_log_step = ss_default_upper_w_log_step
+		self.ss_dump_last_generation = ss_dump_last_generation
+
+		self.run_count = run_count
+
+	def go(self) -> None:
+		with open(self.filename, "a", newline="") as outfile:
+			writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
+			writer.writeheader()
+
+		for run in range(1, self.run_count + 1):
+
+			# Generate the actual dipoles
+			actual_dipoles = self.actual_model.get_dipoles(self.max_frequency)
+
+			measurements = actual_dipoles.get_dot_measurements(self.dot_inputs)
+
+			_logger.info(f"Going to work on dipole at {actual_dipoles.dipoles}")
+
+			# define a new seed sequence for each run
+
+			results = []
+			_logger.debug("Going to iterate over models now")
+			for model_count, model in enumerate(self.models_with_names):
+				_logger.debug(f"Doing model #{model_count}, {model[0]}")
+				subset_run = deepdog.subset_simulation.SubsetSimulation(
+					model,
+					self.dot_inputs,
+					measurements,
+					self.ss_n_c,
+					self.ss_n_s,
+					self.ss_m_max,
+					self.ss_target_cost,
+					self.ss_level_0_seed,
+					self.ss_mcmc_seed,
+					self.ss_use_adaptive_steps,
+					self.ss_default_phi_step,
+					self.ss_default_theta_step,
+					self.ss_default_r_step,
+					self.ss_default_w_log_step,
+					self.ss_default_upper_w_log_step,
+					keep_probs_list=False,
+					dump_last_generation_to_file=self.ss_dump_last_generation,
+				)
+				results.append(subset_run.execute())
+
+			_logger.debug("Done, constructing output now")
+			row = {
+				"dipole_moment_1": actual_dipoles.dipoles[0].p,
+				"dipole_location_1": actual_dipoles.dipoles[0].s,
+				"dipole_frequency_1": actual_dipoles.dipoles[0].w,
+			}
+			for i in range(1, self.n):
+				try:
+					current_dipoles = actual_dipoles.dipoles[i]
+					row[f"dipole_moment_{i+1}"] = current_dipoles.p
+					row[f"dipole_location_{i+1}"] = current_dipoles.s
+					row[f"dipole_frequency_{i+1}"] = current_dipoles.w
+				except IndexError:
+					_logger.info(f"Not writing anymore, saw end after {i}")
+					break
+
+			likelihoods: List[float] = []
+
+			for (name, result) in zip(self.model_names, results):
+				if result.over_target_likelihood is None:
+					clamped_likelihood = result.probs_list[-1][0] / CLAMPING_FACTOR
+					_logger.warning(
+						f"got a none result, clamping to {clamped_likelihood}"
+					)
+				else:
+					clamped_likelihood = result.over_target_likelihood
+				likelihoods.append(clamped_likelihood)
+				row[f"{name}_likelihood"] = clamped_likelihood
+
+			success_weight = sum(
+				[
+					likelihood * prob
+					for likelihood, prob in zip(likelihoods, self.probabilities)
+				]
+			)
+			new_probabilities = [
+				likelihood * old_prob / success_weight
+				for likelihood, old_prob in zip(likelihoods, self.probabilities)
+			]
+			self.probabilities = new_probabilities
+			for name, probability in zip(self.model_names, self.probabilities):
+				row[f"{name}_prob"] = probability
+			_logger.info(row)
+
+			with open(self.filename, "a", newline="") as outfile:
+				writer = csv.DictWriter(
+					outfile, fieldnames=self.csv_fields, dialect="unix"
+				)
+				writer.writerow(row)
+
+			if self.use_end_threshold:
+				max_prob = max(self.probabilities)
+				if max_prob > self.end_threshold:
+					_logger.info(
+						f"Aborting early, because {max_prob} is greater than {self.end_threshold}"
+					)
+					break

deepdog/real_spectrum_run.py

@@ -5,7 +5,7 @@ import pdme.measurement.input_types
 import pdme.measurement.oscillating_dipole
 import pdme.util.fast_v_calc
 import pdme.util.fast_nonlocal_spectrum
-from typing import Sequence, Tuple, List, Dict, Union
+from typing import Sequence, Tuple, List, Dict, Union, Optional
 import datetime
 import csv
 import multiprocessing
@@ -20,16 +20,50 @@ CHUNKSIZE = 50
 _logger = logging.getLogger(__name__)
 
 
-def get_a_result(input) -> int:
-	model, dot_inputs, lows, highs, monte_carlo_count, seed = input
+def get_a_result_fast_filter_pairs(input) -> int:
+	(
+		model,
+		dot_inputs,
+		lows,
+		highs,
+		pair_inputs,
+		pair_lows,
+		pair_highs,
+		monte_carlo_count,
+		seed,
+	) = input
 
 	rng = numpy.random.default_rng(seed)
 	# TODO: A long term refactor is to pull the frequency stuff out from here. The None stands for max_frequency, which is unneeded in the actually useful models.
 	sample_dipoles = model.get_monte_carlo_dipole_inputs(
 		monte_carlo_count, None, rng_to_use=rng
 	)
-	vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(dot_inputs, sample_dipoles)
-	return numpy.count_nonzero(pdme.util.fast_v_calc.between(vals, lows, highs))
+
+	current_sample = sample_dipoles
+	for di, low, high in zip(dot_inputs, lows, highs):
+
+		if len(current_sample) < 1:
+			break
+		vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(
+			numpy.array([di]), current_sample
+		)
+
+		current_sample = current_sample[numpy.all((vals > low) & (vals < high), axis=1)]
+
+	for pi, plow, phigh in zip(pair_inputs, pair_lows, pair_highs):
+		if len(current_sample) < 1:
+			break
+		vals = pdme.util.fast_nonlocal_spectrum.fast_s_nonlocal_dipoleses(
+			numpy.array([pi]), current_sample
+		)
+
+		current_sample = current_sample[
+			numpy.all(
+				((vals > plow) & (vals < phigh)) | ((vals < plow) & (vals > phigh)),
+				axis=1,
+			)
+		]
+	return len(current_sample)
 
 
 def get_a_result_fast_filter(input) -> int:
@@ -87,7 +121,10 @@ class RealSpectrumRun:
 		max_monte_carlo_cycles_steps: int = 10,
 		chunksize: int = CHUNKSIZE,
 		initial_seed: int = 12345,
-		use_fast_filter: bool = True,
+		cap_core_count: int = 0,
+		pair_measurements: Optional[
+			Sequence[pdme.measurement.DotPairRangeMeasurement]
+		] = None,
 	) -> None:
 		self.measurements = measurements
 		self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements]
@@ -96,6 +133,21 @@ class RealSpectrumRun:
 			self.dot_inputs
 		)
 
+		if pair_measurements is not None:
+			self.pair_measurements = pair_measurements
+			self.use_pair_measurements = True
+			self.dot_pair_inputs = [
+				(measure.r1, measure.r2, measure.f)
+				for measure in self.pair_measurements
+			]
+			self.dot_pair_inputs_array = (
+				pdme.measurement.input_types.dot_pair_inputs_to_array(
+					self.dot_pair_inputs
+				)
+			)
+		else:
+			self.use_pair_measurements = False
+
 		self.models = [model for (_, model) in models_with_names]
 		self.model_names = [name for (name, _) in models_with_names]
 		self.model_count = len(self.models)
@@ -116,13 +168,14 @@ class RealSpectrumRun:
 		self.probabilities = [1 / self.model_count] * self.model_count
 
 		timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
-		self.use_fast_filter = use_fast_filter
-		ff_string = "no_fast_filter"
-		if self.use_fast_filter:
-			ff_string = "fast_filter"
+
+		ff_string = "fast_filter"
+
 		self.filename = f"{timestamp}-{filename_slug}.realdata.{ff_string}.bayesrun.csv"
 		self.initial_seed = initial_seed
 
+		self.cap_core_count = cap_core_count
+
 	def go(self) -> None:
 		with open(self.filename, "a", newline="") as outfile:
 			writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
@@ -135,16 +188,29 @@ class RealSpectrumRun:
 			self.measurements
 		)
 
+		pair_lows = None
+		pair_highs = None
+		if self.use_pair_measurements:
+			(
+				pair_lows,
+				pair_highs,
+			) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
+				self.pair_measurements
+			)
+
 		# define a new seed sequence for each run
 		seed_sequence = numpy.random.SeedSequence(self.initial_seed)
 
 		results = []
 		_logger.debug("Going to iterate over models now")
+		core_count = multiprocessing.cpu_count() - 1 or 1
+		if (self.cap_core_count >= 1) and (self.cap_core_count < core_count):
+			core_count = self.cap_core_count
+		_logger.info(f"Using {core_count} cores")
 		for model_count, (model, model_name) in enumerate(
 			zip(self.models, self.model_names)
 		):
 			_logger.debug(f"Doing model #{model_count}: {model_name}")
-			core_count = multiprocessing.cpu_count() - 1 or 1
 			with multiprocessing.Pool(core_count) as pool:
 				cycle_count = 0
 				cycle_success = 0
@@ -162,27 +228,46 @@ class RealSpectrumRun:
 					# that way we get more stuff.
 					seeds = seed_sequence.spawn(self.monte_carlo_cycles)
 
-					if self.use_fast_filter:
-						result_func = get_a_result_fast_filter
-					else:
-						result_func = get_a_result
-					current_success = sum(
-						pool.imap_unordered(
-							result_func,
-							[
-								(
-									model,
-									self.dot_inputs_array,
-									lows,
-									highs,
-									self.monte_carlo_count,
-									seed,
-								)
-								for seed in seeds
-							],
-							self.chunksize,
+					if self.use_pair_measurements:
+						current_success = sum(
+							pool.imap_unordered(
+								get_a_result_fast_filter_pairs,
+								[
+									(
+										model,
+										self.dot_inputs_array,
+										lows,
+										highs,
+										self.dot_pair_inputs_array,
+										pair_lows,
+										pair_highs,
+										self.monte_carlo_count,
+										seed,
+									)
+									for seed in seeds
+								],
+								self.chunksize,
+							)
+						)
+					else:
+
+						current_success = sum(
+							pool.imap_unordered(
+								get_a_result_fast_filter,
+								[
+									(
+										model,
+										self.dot_inputs_array,
+										lows,
+										highs,
+										self.monte_carlo_count,
+										seed,
+									)
+									for seed in seeds
+								],
+								self.chunksize,
+							)
 						)
-					)
 
 					cycle_success += current_success
 					_logger.debug(f"current running successes: {cycle_success}")

deepdog/subset_simulation/__init__.py

@@ -0,0 +1,3 @@
+from deepdog.subset_simulation.subset_simulation_impl import SubsetSimulation
+
+__all__ = ["SubsetSimulation"]

deepdog/subset_simulation/subset_simulation_impl.py

@@ -0,0 +1,337 @@
+import logging
+import numpy
+import pdme.measurement
+import pdme.measurement.input_types
+import pdme.subspace_simulation
+from typing import Sequence, Tuple, Optional
+
+from dataclasses import dataclass
+
+_logger = logging.getLogger(__name__)
+
+
+@dataclass
+class SubsetSimulationResult:
+	probs_list: Sequence[Tuple]
+	over_target_cost: Optional[float]
+	over_target_likelihood: Optional[float]
+	under_target_cost: Optional[float]
+	under_target_likelihood: Optional[float]
+	lowest_likelihood: Optional[float]
+
+
+class SubsetSimulation:
+	def __init__(
+		self,
+		model_name_pair,
+		dot_inputs,
+		actual_measurements: Sequence[pdme.measurement.DotMeasurement],
+		n_c: int,
+		n_s: int,
+		m_max: int,
+		target_cost: Optional[float] = None,
+		level_0_seed: int = 200,
+		mcmc_seed: int = 20,
+		use_adaptive_steps=True,
+		default_phi_step=0.01,
+		default_theta_step=0.01,
+		default_r_step=0.01,
+		default_w_log_step=0.01,
+		default_upper_w_log_step=4,
+		keep_probs_list=True,
+		dump_last_generation_to_file=False,
+	):
+		name, model = model_name_pair
+		self.model_name = name
+		self.model = model
+		_logger.info(f"got model {self.model_name}")
+
+		self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(
+			dot_inputs
+		)
+		# _logger.debug(f"actual measurements: {actual_measurements}")
+		self.actual_measurement_array = numpy.array([m.v for m in actual_measurements])
+
+		def cost_function_to_use(dipoles_to_test):
+			return pdme.subspace_simulation.proportional_costs_vs_actual_measurement(
+				self.dot_inputs_array, self.actual_measurement_array, dipoles_to_test
+			)
+
+		self.cost_function_to_use = cost_function_to_use
+
+		self.n_c = n_c
+		self.n_s = n_s
+		self.m_max = m_max
+
+		self.level_0_seed = level_0_seed
+		self.mcmc_seed = mcmc_seed
+
+		self.use_adaptive_steps = use_adaptive_steps
+		self.default_phi_step = default_phi_step
+		self.default_theta_step = default_theta_step
+		self.default_r_step = default_r_step
+		self.default_w_log_step = default_w_log_step
+		self.default_upper_w_log_step = default_upper_w_log_step
+
+		_logger.info("using params:")
+		_logger.info(f"\tn_c: {self.n_c}")
+		_logger.info(f"\tn_s: {self.n_s}")
+		_logger.info(f"\tm: {self.m_max}")
+		_logger.info("let's do level 0...")
+
+		self.target_cost = target_cost
+		_logger.info(f"will stop at target cost {target_cost}")
+
+		self.keep_probs_list = keep_probs_list
+		self.dump_last_generations = dump_last_generation_to_file
+
+	def execute(self) -> SubsetSimulationResult:
+
+		probs_list = []
+
+		sample_dipoles = self.model.get_monte_carlo_dipole_inputs(
+			self.n_c * self.n_s,
+			-1,
+			rng_to_use=numpy.random.default_rng(self.level_0_seed),
+		)
+		# _logger.debug(sample_dipoles)
+		# _logger.debug(sample_dipoles.shape)
+		costs = self.cost_function_to_use(sample_dipoles)
+
+		_logger.debug(f"costs: {costs}")
+		sorted_indexes = costs.argsort()[::-1]
+
+		_logger.debug(costs[sorted_indexes])
+		_logger.debug(sample_dipoles[sorted_indexes])
+
+		sorted_costs = costs[sorted_indexes]
+		sorted_dipoles = sample_dipoles[sorted_indexes]
+
+		threshold_cost = sorted_costs[-self.n_c]
+
+		all_dipoles = numpy.array(
+			[
+				pdme.subspace_simulation.sort_array_of_dipoles_by_frequency(samp)
+				for samp in sorted_dipoles
+			]
+		)
+		all_chains = list(zip(sorted_costs, all_dipoles))
+
+		mcmc_rng = numpy.random.default_rng(self.mcmc_seed)
+
+		for i in range(self.m_max):
+			next_seeds = all_chains[-self.n_c:]
+
+			if self.dump_last_generations:
+				_logger.info("writing out csv file")
+				next_dipoles_seed_dipoles = numpy.array([n[1] for n in next_seeds])
+				for n in range(self.model.n):
+					_logger.info(f"{next_dipoles_seed_dipoles[:, n].shape}")
+					numpy.savetxt(
+						f"generation_{self.n_c}_{self.n_s}_{i}_dipole_{n}.csv",
+						next_dipoles_seed_dipoles[:, n],
+						delimiter=",",
+					)
+
+			if self.keep_probs_list:
+				for cost_index, cost_chain in enumerate(all_chains[: -self.n_c]):
+					probs_list.append(
+						(
+							((self.n_c * self.n_s - cost_index) / (self.n_c * self.n_s))
+							/ (self.n_s ** (i)),
+							cost_chain[0],
+							i + 1,
+						)
+					)
+
+			next_seeds_as_array = numpy.array([s for _, s in next_seeds])
+
+			stdevs = self.get_stdevs_from_arrays(next_seeds_as_array)
+			_logger.info(f"got stdevs: {stdevs.stdevs}")
+
+			all_chains = []
+			for c, s in next_seeds:
+				# chain = mcmc(s, threshold_cost, n_s, model, dot_inputs_array, actual_measurement_array, mcmc_rng, curr_cost=c, stdevs=stdevs)
+				# until new version gotta do
+				chain = self.model.get_mcmc_chain(
+					s,
+					self.cost_function_to_use,
+					self.n_s,
+					threshold_cost,
+					stdevs,
+					initial_cost=c,
+					rng_arg=mcmc_rng,
+				)
+				for cost, chained in chain:
+					try:
+						filtered_cost = cost[0]
+					except IndexError:
+						filtered_cost = cost
+					all_chains.append((filtered_cost, chained))
+
+			# _logger.debug(all_chains)
+
+			all_chains.sort(key=lambda c: c[0], reverse=True)
+
+			threshold_cost = all_chains[-self.n_c][0]
+			_logger.info(
+				f"current threshold cost: {threshold_cost}, at P = (1 / {self.n_s})^{i + 1}"
+			)
+			if (self.target_cost is not None) and (threshold_cost < self.target_cost):
+				_logger.info(
+					f"got a threshold cost {threshold_cost}, less than {self.target_cost}. will leave early"
+				)
+
+				cost_list = [c[0] for c in all_chains]
+				over_index = reverse_bisect_right(cost_list, self.target_cost)
+
+				shorter_probs_list = []
+				for cost_index, cost_chain in enumerate(all_chains):
+					if self.keep_probs_list:
+						probs_list.append(
+							(
+								(
+									(self.n_c * self.n_s - cost_index)
+									/ (self.n_c * self.n_s)
+								)
+								/ (self.n_s ** (i)),
+								cost_chain[0],
+								i + 1,
+							)
+						)
+					shorter_probs_list.append(
+						(
+							cost_chain[0],
+							((self.n_c * self.n_s - cost_index) / (self.n_c * self.n_s))
+							/ (self.n_s ** (i)),
+						)
+					)
+				# _logger.info(shorter_probs_list)
+				result = SubsetSimulationResult(
+					probs_list=probs_list,
+					over_target_cost=shorter_probs_list[over_index - 1][0],
+					over_target_likelihood=shorter_probs_list[over_index - 1][1],
+					under_target_cost=shorter_probs_list[over_index][0],
+					under_target_likelihood=shorter_probs_list[over_index][1],
+					lowest_likelihood=shorter_probs_list[-1][1],
+				)
+				return result
+
+			# _logger.debug([c[0] for c in all_chains[-n_c:]])
+			_logger.info(f"doing level {i + 1}")
+
+		if self.keep_probs_list:
+			for cost_index, cost_chain in enumerate(all_chains):
+				probs_list.append(
+					(
+						((self.n_c * self.n_s - cost_index) / (self.n_c * self.n_s))
+						/ (self.n_s ** (self.m_max)),
+						cost_chain[0],
+						self.m_max + 1,
+					)
+				)
+		threshold_cost = all_chains[-self.n_c][0]
+		_logger.info(
+			f"final threshold cost: {threshold_cost}, at P = (1 / {self.n_s})^{self.m_max + 1}"
+		)
+		for a in all_chains[-10:]:
+			_logger.info(a)
+		# for prob, prob_cost in probs_list:
+		# 	_logger.info(f"\t{prob}: {prob_cost}")
+		probs_list.sort(key=lambda c: c[0], reverse=True)
+
+		min_likelihood = ((1) / (self.n_c * self.n_s)) / (self.n_s ** (self.m_max + 1))
+
+		result = SubsetSimulationResult(
+			probs_list=probs_list,
+			over_target_cost=None,
+			over_target_likelihood=None,
+			under_target_cost=None,
+			under_target_likelihood=None,
+			lowest_likelihood=min_likelihood,
+		)
+		return result
+
+	def get_stdevs_from_arrays(
+		self, array
+	) -> pdme.subspace_simulation.MCMCStandardDeviation:
+		# stdevs = get_stdevs_from_arrays(next_seeds_as_array, model)
+		if self.use_adaptive_steps:
+
+			stdev_array = []
+			count = array.shape[1]
+			for dipole_index in range(count):
+				selected = array[:, dipole_index]
+				pxs = selected[:, 0]
+				pys = selected[:, 1]
+				pzs = selected[:, 2]
+				thetas = numpy.arccos(pzs / self.model.pfixed)
+				phis = numpy.arctan2(pys, pxs)
+
+				rstdevs = numpy.maximum(
+					numpy.std(selected, axis=0)[3:6],
+					self.default_r_step / (self.n_s * 10),
+				)
+				frequency_stdevs = numpy.minimum(
+					numpy.maximum(
+						numpy.std(numpy.log(selected[:, -1])),
+						self.default_w_log_step / (self.n_s * 10),
+					),
+					self.default_upper_w_log_step,
+				)
+				stdev_array.append(
+					pdme.subspace_simulation.DipoleStandardDeviation(
+						p_theta_step=max(
+							numpy.std(thetas), self.default_theta_step / (self.n_s * 10)
+						),
+						p_phi_step=max(
+							numpy.std(phis), self.default_phi_step / (self.n_s * 10)
+						),
+						rx_step=rstdevs[0],
+						ry_step=rstdevs[1],
+						rz_step=rstdevs[2],
+						w_log_step=frequency_stdevs,
+					)
+				)
+		else:
+			default_stdev = pdme.subspace_simulation.DipoleStandardDeviation(
+				self.default_phi_step,
+				self.default_theta_step,
+				self.default_r_step,
+				self.default_r_step,
+				self.default_r_step,
+				self.default_w_log_step,
+			)
+			stdev_array = [default_stdev]
+		stdevs = pdme.subspace_simulation.MCMCStandardDeviation(stdev_array)
+		return stdevs
+
+
+def reverse_bisect_right(a, x, lo=0, hi=None):
+	"""Return the index where to insert item x in list a, assuming a is sorted in descending order.
+
+	The return value i is such that all e in a[:i] have e >= x, and all e in
+	a[i:] have e < x.  So if x already appears in the list, a.insert(x) will
+	insert just after the rightmost x already there.
+
+	Optional args lo (default 0) and hi (default len(a)) bound the
+	slice of a to be searched.
+
+	Essentially, the function returns number of elements in a which are >= than x.
+	>>> a = [8, 6, 5, 4, 2]
+	>>> reverse_bisect_right(a, 5)
+	3
+	>>> a[:reverse_bisect_right(a, 5)]
+	[8, 6, 5]
+	"""
+	if lo < 0:
+		raise ValueError("lo must be non-negative")
+	if hi is None:
+		hi = len(a)
+	while lo < hi:
+		mid = (lo + hi) // 2
+		if x > a[mid]:
+			hi = mid
+		else:
+			lo = mid + 1
+	return lo

deepdog/temp_aware_real_spectrum_run.py

@@ -0,0 +1,231 @@
+import pdme.inputs
+import pdme.model
+import pdme.measurement
+import pdme.measurement.input_types
+import pdme.measurement.oscillating_dipole
+import pdme.util.fast_v_calc
+import pdme.util.fast_nonlocal_spectrum
+from typing import Sequence, Tuple, List, Dict, Union, Mapping
+import datetime
+import csv
+import multiprocessing
+import logging
+import numpy
+
+
+# TODO: remove hardcode
+CHUNKSIZE = 50
+
+
+_logger = logging.getLogger(__name__)
+
+
+def get_a_result_fast_filter(input) -> int:
+	# 								(
+	# 	model,
+	# 	self.dot_inputs_array_dict,
+	# 	low_high_dict,
+	# 	self.monte_carlo_count,
+	# 	seed,
+	# )
+	model, dot_inputs_dict, low_high_dict, monte_carlo_count, seed = input
+
+	rng = numpy.random.default_rng(seed)
+	# TODO: A long term refactor is to pull the frequency stuff out from here. The None stands for max_frequency, which is unneeded in the actually useful models.
+	sample_dipoles = model.get_monte_carlo_dipole_inputs(
+		monte_carlo_count, None, rng_to_use=rng
+	)
+
+	current_sample = sample_dipoles
+	for temp in dot_inputs_dict.keys():
+		dot_inputs = dot_inputs_dict[temp]
+		lows, highs = low_high_dict[temp]
+		for di, low, high in zip(dot_inputs, lows, highs):
+
+			if len(current_sample) < 1:
+				break
+			vals = pdme.util.fast_v_calc.fast_vs_for_asymmetric_dipoleses(
+				numpy.array([di]), current_sample, temp
+			)
+
+			current_sample = current_sample[
+				numpy.all((vals > low) & (vals < high), axis=1)
+			]
+	return len(current_sample)
+
+
+class TempAwareRealSpectrumRun:
+	"""
+	A bayes run given some real data, with potentially variable temperature.
+
+	Parameters
+	----------
+	measurements_dict : Dict[float, Sequence[pdme.measurement.DotRangeMeasurement]]
+	The dot inputs for this bayes run, in a dictionary indexed by temperatures
+
+	models_with_names : models_with_names: Sequence[Tuple[str, pdme.model.DipoleModel]],
+
+	The models to evaluate.
+
+	actual_model : pdme.model.DipoleModel
+	The model which is actually correct.
+
+	filename_slug : str
+	The filename slug to include.
+
+	run_count: int
+	The number of runs to do.
+	"""
+
+	def __init__(
+		self,
+		measurements_dict: Mapping[
+			float, Sequence[pdme.measurement.DotRangeMeasurement]
+		],
+		models_with_names: Sequence[Tuple[str, pdme.model.DipoleModel]],
+		filename_slug: str,
+		monte_carlo_count: int = 10000,
+		monte_carlo_cycles: int = 10,
+		target_success: int = 100,
+		max_monte_carlo_cycles_steps: int = 10,
+		chunksize: int = CHUNKSIZE,
+		initial_seed: int = 12345,
+		cap_core_count: int = 0,
+	) -> None:
+		self.measurements_dict = measurements_dict
+		self.dot_inputs_dict = {
+			k: [(measure.r, measure.f) for measure in measurements]
+			for k, measurements in measurements_dict.items()
+		}
+
+		self.dot_inputs_array_dict = {
+			k: pdme.measurement.input_types.dot_inputs_to_array(dot_inputs)
+			for k, dot_inputs in self.dot_inputs_dict.items()
+		}
+
+		self.models = [model for (_, model) in models_with_names]
+		self.model_names = [name for (name, _) in models_with_names]
+		self.model_count = len(self.models)
+
+		self.monte_carlo_count = monte_carlo_count
+		self.monte_carlo_cycles = monte_carlo_cycles
+		self.target_success = target_success
+		self.max_monte_carlo_cycles_steps = max_monte_carlo_cycles_steps
+
+		self.csv_fields = []
+
+		self.compensate_zeros = True
+		self.chunksize = chunksize
+		for name in self.model_names:
+			self.csv_fields.extend([f"{name}_success", f"{name}_count", f"{name}_prob"])
+
+		# for now initialise priors as uniform.
+		self.probabilities = [1 / self.model_count] * self.model_count
+
+		timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
+		ff_string = "fast_filter"
+		self.filename = f"{timestamp}-{filename_slug}.realdata.{ff_string}.bayesrun.csv"
+		self.initial_seed = initial_seed
+
+		self.cap_core_count = cap_core_count
+
+	def go(self) -> None:
+		with open(self.filename, "a", newline="") as outfile:
+			writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
+			writer.writeheader()
+
+		low_high_dict = {}
+		for temp, measurements in self.measurements_dict.items():
+			(
+				lows,
+				highs,
+			) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
+				measurements
+			)
+			low_high_dict[temp] = (lows, highs)
+
+		# define a new seed sequence for each run
+		seed_sequence = numpy.random.SeedSequence(self.initial_seed)
+
+		results = []
+		_logger.debug("Going to iterate over models now")
+		core_count = multiprocessing.cpu_count() - 1 or 1
+		if (self.cap_core_count >= 1) and (self.cap_core_count < core_count):
+			core_count = self.cap_core_count
+		_logger.info(f"Using {core_count} cores")
+		for model_count, (model, model_name) in enumerate(
+			zip(self.models, self.model_names)
+		):
+			_logger.debug(f"Doing model #{model_count}: {model_name}")
+			with multiprocessing.Pool(core_count) as pool:
+				cycle_count = 0
+				cycle_success = 0
+				cycles = 0
+				while (cycles < self.max_monte_carlo_cycles_steps) and (
+					cycle_success <= self.target_success
+				):
+					_logger.debug(f"Starting cycle {cycles}")
+					cycles += 1
+					current_success = 0
+					cycle_count += self.monte_carlo_count * self.monte_carlo_cycles
+
+					# generate a seed from the sequence for each core.
+					# note this needs to be inside the loop for monte carlo cycle steps!
+					# that way we get more stuff.
+					seeds = seed_sequence.spawn(self.monte_carlo_cycles)
+
+					result_func = get_a_result_fast_filter
+
+					current_success = sum(
+						pool.imap_unordered(
+							result_func,
+							[
+								(
+									model,
+									self.dot_inputs_array_dict,
+									low_high_dict,
+									self.monte_carlo_count,
+									seed,
+								)
+								for seed in seeds
+							],
+							self.chunksize,
+						)
+					)
+
+					cycle_success += current_success
+					_logger.debug(f"current running successes: {cycle_success}")
+				results.append((cycle_count, cycle_success))
+
+		_logger.debug("Done, constructing output now")
+		row: Dict[str, Union[int, float, str]] = {}
+
+		successes: List[float] = []
+		counts: List[int] = []
+		for model_index, (name, (count, result)) in enumerate(
+			zip(self.model_names, results)
+		):
+
+			row[f"{name}_success"] = result
+			row[f"{name}_count"] = count
+			successes.append(max(result, 0.5))
+			counts.append(count)
+
+		success_weight = sum(
+			[
+				(succ / count) * prob
+				for succ, count, prob in zip(successes, counts, self.probabilities)
+			]
+		)
+		new_probabilities = [
+			(succ / count) * old_prob / success_weight
+			for succ, count, old_prob in zip(successes, counts, self.probabilities)
+		]
+		self.probabilities = new_probabilities
+		for name, probability in zip(self.model_names, self.probabilities):
+			row[f"{name}_prob"] = probability
+		_logger.info(row)
+
+		with open(self.filename, "a", newline="") as outfile:
+			writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
+			writer.writerow(row)

jenkins/ci-agent-pod.yaml

@@ -1,9 +1,11 @@
 apiVersion: v1
 kind: Pod
 spec:
+  imagePullSecrets:
+    - name: regcreds
   containers:  # list of containers that you want present for your build, you can define a default container in the Jenkinsfile
-    - name: python
-      image: python:3.8
+    - name: poetry
+      image: ghcr.io/dmallubhotla/poetry-image:1
       command: ["tail", "-f", "/dev/null"]  # this or any command that is bascially a noop is required, this is so that you don't overwrite the entrypoint of the base container
       imagePullPolicy: Always # use cache or pull image for agent
       resources:  # limits the resources your build contaienr

poetry.lock

@@ -1,39 +1,17 @@
-[[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 = "black"
-version = "22.3.0"
+version = "22.12.0"
 description = "The uncompromising code formatter."
 category = "dev"
 optional = false
-python-versions = ">=3.6.2"
+python-versions = ">=3.7"
 
 [package.dependencies]
 click = ">=8.0.0"
 mypy-extensions = ">=0.4.3"
 pathspec = ">=0.9.0"
 platformdirs = ">=2"
-tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
+tomli = {version = ">=1.1.0", markers = "python_full_version < \"3.11.0a7\""}
 typing-extensions = {version = ">=3.10.0.0", markers = "python_version < \"3.10\""}
 
 [package.extras]
@@ -44,7 +22,7 @@ uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "bleach"
-version = "5.0.0"
+version = "6.0.0"
 description = "An easy safelist-based HTML-sanitizing tool."
 category = "dev"
 optional = false
@@ -55,12 +33,11 @@ six = ">=1.9.0"
 webencodings = "*"
 
 [package.extras]
-css = ["tinycss2 (>=1.1.0)"]
-dev = ["pip-tools (==6.5.1)", "pytest (==7.1.1)", "flake8 (==4.0.1)", "tox (==3.24.5)", "sphinx (==4.3.2)", "twine (==4.0.0)", "wheel (==0.37.1)", "hashin (==0.17.0)", "black (==22.3.0)", "mypy (==0.942)"]
+css = ["tinycss2 (>=1.1.0,<1.2)"]
 
 [[package]]
 name = "certifi"
-version = "2022.5.18.1"
+version = "2022.12.7"
 description = "Python package for providing Mozilla's CA Bundle."
 category = "dev"
 optional = false
@@ -68,7 +45,7 @@ python-versions = ">=3.6"
 
 [[package]]
 name = "cffi"
-version = "1.15.0"
+version = "1.15.1"
 description = "Foreign Function Interface for Python calling C code."
 category = "dev"
 optional = false
@@ -79,14 +56,11 @@ pycparser = "*"
 
 [[package]]
 name = "charset-normalizer"
-version = "2.0.12"
+version = "3.1.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 category = "dev"
 optional = false
-python-versions = ">=3.5.0"
-
-[package.extras]
-unicode_backport = ["unicodedata2"]
+python-versions = ">=3.7.0"
 
 [[package]]
 name = "click"
@@ -112,15 +86,15 @@ click = "*"
 
 [[package]]
 name = "colorama"
-version = "0.4.4"
+version = "0.4.6"
 description = "Cross-platform colored terminal text."
 category = "dev"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 
 [[package]]
 name = "coverage"
-version = "6.4.2"
+version = "7.2.7"
 description = "Code coverage measurement for Python"
 category = "dev"
 optional = false
@@ -134,7 +108,7 @@ toml = ["tomli"]
 
 [[package]]
 name = "cryptography"
-version = "37.0.2"
+version = "40.0.1"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 category = "dev"
 optional = false
@@ -144,31 +118,41 @@ python-versions = ">=3.6"
 cffi = ">=1.12"
 
 [package.extras]
-docs = ["sphinx (>=1.6.5,!=1.8.0,!=3.1.0,!=3.1.1)", "sphinx-rtd-theme"]
+docs = ["sphinx (>=5.3.0)", "sphinx-rtd-theme (>=1.1.1)"]
 docstest = ["pyenchant (>=1.6.11)", "twine (>=1.12.0)", "sphinxcontrib-spelling (>=4.0.1)"]
-pep8test = ["black", "flake8", "flake8-import-order", "pep8-naming"]
-sdist = ["setuptools_rust (>=0.11.4)"]
+pep8test = ["black", "ruff", "mypy", "check-manifest"]
+sdist = ["setuptools-rust (>=0.11.4)"]
 ssh = ["bcrypt (>=3.1.5)"]
-test = ["pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-subtests", "pytest-xdist", "pretend", "iso8601", "pytz", "hypothesis (>=1.11.4,!=3.79.2)"]
+test = ["pytest (>=6.2.0)", "pytest-shard (>=0.1.2)", "pytest-benchmark", "pytest-cov", "pytest-subtests", "pytest-xdist", "pretend", "iso8601"]
+test-randomorder = ["pytest-randomly"]
+tox = ["tox"]
 
 [[package]]
 name = "docutils"
-version = "0.18.1"
+version = "0.19"
 description = "Docutils -- Python Documentation Utilities"
 category = "dev"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+python-versions = ">=3.7"
 
 [[package]]
 name = "dotty-dict"
-version = "1.3.0"
+version = "1.3.1"
 description = "Dictionary wrapper for quick access to deeply nested keys."
 category = "dev"
 optional = false
-python-versions = "*"
+python-versions = ">=3.5,<4.0"
 
-[package.dependencies]
-setuptools_scm = "*"
+[[package]]
+name = "exceptiongroup"
+version = "1.1.1"
+description = "Backport of PEP 654 (exception groups)"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+
+[package.extras]
+test = ["pytest (>=6)"]
 
 [[package]]
 name = "flake8"
@@ -185,19 +169,19 @@ pyflakes = ">=2.4.0,<2.5.0"
 
 [[package]]
 name = "gitdb"
-version = "4.0.9"
+version = "4.0.10"
 description = "Git Object Database"
 category = "dev"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 
 [package.dependencies]
 smmap = ">=3.0.1,<6"
 
 [[package]]
 name = "gitpython"
-version = "3.1.27"
-description = "GitPython is a python library used to interact with Git repositories"
+version = "3.1.31"
+description = "GitPython is a Python library used to interact with Git repositories"
 category = "dev"
 optional = false
 python-versions = ">=3.7"
@@ -207,7 +191,7 @@ gitdb = ">=4.0.1,<5"
 
 [[package]]
 name = "idna"
-version = "3.3"
+version = "3.4"
 description = "Internationalized Domain Names in Applications (IDNA)"
 category = "dev"
 optional = false
@@ -215,7 +199,7 @@ python-versions = ">=3.5"
 
 [[package]]
 name = "importlib-metadata"
-version = "4.11.4"
+version = "6.2.1"
 description = "Read metadata from Python packages"
 category = "dev"
 optional = false
@@ -225,26 +209,56 @@ python-versions = ">=3.7"
 zipp = ">=0.5"
 
 [package.extras]
-docs = ["sphinx", "jaraco.packaging (>=9)", "rst.linker (>=1.9)"]
+docs = ["sphinx (>=3.5)", "jaraco.packaging (>=9)", "rst.linker (>=1.9)", "furo", "sphinx-lint", "jaraco.tidelift (>=1.4)"]
 perf = ["ipython"]
-testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pyfakefs", "flufl.flake8", "pytest-perf (>=0.9.2)", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)", "importlib-resources (>=1.3)"]
+testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "flake8 (<5)", "pytest-cov", "pytest-enabler (>=1.3)", "packaging", "pyfakefs", "flufl.flake8", "pytest-perf (>=0.9.2)", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)", "pytest-flake8", "importlib-resources (>=1.3)"]
+
+[[package]]
+name = "importlib-resources"
+version = "5.12.0"
+description = "Read resources from Python packages"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
+
+[package.extras]
+docs = ["sphinx (>=3.5)", "jaraco.packaging (>=9)", "rst.linker (>=1.9)", "furo", "sphinx-lint", "jaraco.tidelift (>=1.4)"]
+testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "flake8 (<5)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)", "pytest-flake8"]
 
 [[package]]
 name = "iniconfig"
-version = "1.1.1"
-description = "iniconfig: brain-dead simple config-ini parsing"
+version = "2.0.0"
+description = "brain-dead simple config-ini parsing"
 category = "dev"
 optional = false
-python-versions = "*"
+python-versions = ">=3.7"
 
 [[package]]
 name = "invoke"
-version = "1.7.1"
+version = "1.7.3"
 description = "Pythonic task execution"
 category = "dev"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "jaraco.classes"
+version = "3.2.3"
+description = "Utility functions for Python class constructs"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+more-itertools = "*"
+
+[package.extras]
+docs = ["sphinx (>=3.5)", "jaraco.packaging (>=9)", "rst.linker (>=1.9)", "jaraco.tidelift (>=1.4)"]
+testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "flake8 (<5)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)"]
+
 [[package]]
 name = "jeepney"
 version = "0.8.0"
@@ -259,21 +273,24 @@ trio = ["trio", "async-generator"]
 
 [[package]]
 name = "keyring"
-version = "23.6.0"
+version = "23.13.1"
 description = "Store and access your passwords safely."
 category = "dev"
 optional = false
 python-versions = ">=3.7"
 
 [package.dependencies]
-importlib-metadata = {version = ">=3.6", markers = "python_version < \"3.10\""}
+importlib-metadata = {version = ">=4.11.4", markers = "python_version < \"3.12\""}
+importlib-resources = {version = "*", markers = "python_version < \"3.9\""}
+"jaraco.classes" = "*"
 jeepney = {version = ">=0.4.2", markers = "sys_platform == \"linux\""}
-pywin32-ctypes = {version = "<0.1.0 || >0.1.0,<0.1.1 || >0.1.1", markers = "sys_platform == \"win32\""}
+pywin32-ctypes = {version = ">=0.2.0", markers = "sys_platform == \"win32\""}
 SecretStorage = {version = ">=3.2", markers = "sys_platform == \"linux\""}
 
 [package.extras]
-docs = ["sphinx", "jaraco.packaging (>=9)", "rst.linker (>=1.9)", "jaraco.tidelift (>=1.4)"]
-testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)"]
+completion = ["shtab"]
+docs = ["sphinx (>=3.5)", "jaraco.packaging (>=9)", "rst.linker (>=1.9)", "furo", "jaraco.tidelift (>=1.4)"]
+testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "flake8 (<5)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)", "pytest-flake8"]
 
 [[package]]
 name = "mccabe"
@@ -283,6 +300,14 @@ category = "dev"
 optional = false
 python-versions = "*"
 
+[[package]]
+name = "more-itertools"
+version = "9.1.0"
+description = "More routines for operating on iterables, beyond itertools"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+
 [[package]]
 name = "mypy"
 version = "0.971"
@@ -303,11 +328,11 @@ reports = ["lxml"]
 
 [[package]]
 name = "mypy-extensions"
-version = "0.4.3"
-description = "Experimental type system extensions for programs checked with the mypy typechecker."
+version = "1.0.0"
+description = "Type system extensions for programs checked with the mypy type checker."
 category = "dev"
 optional = false
-python-versions = "*"
+python-versions = ">=3.5"
 
 [[package]]
 name = "numpy"
@@ -319,57 +344,54 @@ python-versions = ">=3.8"
 
 [[package]]
 name = "packaging"
-version = "21.3"
+version = "23.0"
 description = "Core utilities for Python packages"
 category = "dev"
 optional = false
+python-versions = ">=3.7"
+
+[[package]]
+name = "pathspec"
+version = "0.11.1"
+description = "Utility library for gitignore style pattern matching of file paths."
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+
+[[package]]
+name = "pdme"
+version = "0.9.1"
+description = "Python dipole model evaluator"
+category = "main"
+optional = false
+python-versions = ">=3.8.1,<3.10"
+
+[package.dependencies]
+numpy = ">=1.22.3,<2.0.0"
+scipy = ">=1.10,<1.11"
+
+[[package]]
+name = "pkginfo"
+version = "1.9.6"
+description = "Query metadata from sdists / bdists / installed packages."
+category = "dev"
+optional = false
 python-versions = ">=3.6"
 
-[package.dependencies]
-pyparsing = ">=2.0.2,<3.0.5 || >3.0.5"
-
-[[package]]
-name = "pathspec"
-version = "0.9.0"
-description = "Utility library for gitignore style pattern matching of file paths."
-category = "dev"
-optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
-
-[[package]]
-name = "pdme"
-version = "0.8.6"
-description = "Python dipole model evaluator"
-category = "main"
-optional = false
-python-versions = ">=3.8,<3.10"
-
-[package.dependencies]
-numpy = ">=1.22.3,<2.0.0"
-scipy = ">=1.8,<1.9"
-
-[[package]]
-name = "pkginfo"
-version = "1.8.3"
-description = "Query metadatdata from sdists / bdists / installed packages."
-category = "dev"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
-
 [package.extras]
-testing = ["nose", "coverage"]
+testing = ["pytest", "pytest-cov"]
 
 [[package]]
 name = "platformdirs"
-version = "2.5.2"
-description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
+version = "3.2.0"
+description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
 category = "dev"
 optional = false
 python-versions = ">=3.7"
 
 [package.extras]
-docs = ["furo (>=2021.7.5b38)", "proselint (>=0.10.2)", "sphinx-autodoc-typehints (>=1.12)", "sphinx (>=4)"]
-test = ["appdirs (==1.4.4)", "pytest-cov (>=2.7)", "pytest-mock (>=3.6)", "pytest (>=6)"]
+docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx-autodoc-typehints (>=1.22,!=1.23.4)", "sphinx (>=6.1.3)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest-cov (>=4)", "pytest-mock (>=3.10)", "pytest (>=7.2.2)"]
 
 [[package]]
 name = "pluggy"
@@ -383,14 +405,6 @@ python-versions = ">=3.6"
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
-[[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"
@@ -417,51 +431,41 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 
 [[package]]
 name = "pygments"
-version = "2.12.0"
+version = "2.14.0"
 description = "Pygments is a syntax highlighting package written in Python."
 category = "dev"
 optional = false
 python-versions = ">=3.6"
 
-[[package]]
-name = "pyparsing"
-version = "3.0.9"
-description = "pyparsing module - Classes and methods to define and execute parsing grammars"
-category = "dev"
-optional = false
-python-versions = ">=3.6.8"
-
 [package.extras]
-diagrams = ["railroad-diagrams", "jinja2"]
+plugins = ["importlib-metadata"]
 
 [[package]]
 name = "pytest"
-version = "7.1.2"
+version = "7.3.0"
 description = "pytest: simple powerful testing with Python"
 category = "dev"
 optional = false
 python-versions = ">=3.7"
 
 [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"
-py = ">=1.8.2"
-tomli = ">=1.0.0"
+tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
-testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"]
+testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"]
 
 [[package]]
 name = "pytest-cov"
-version = "3.0.0"
+version = "4.1.0"
 description = "Pytest plugin for measuring coverage."
 category = "dev"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 
 [package.dependencies]
 coverage = {version = ">=5.2.1", extras = ["toml"]}
@@ -472,7 +476,7 @@ testing = ["fields", "hunter", "process-tests", "six", "pytest-xdist", "virtuale
 
 [[package]]
 name = "python-gitlab"
-version = "3.5.0"
+version = "3.13.0"
 description = "Interact with GitLab API"
 category = "dev"
 optional = false
@@ -480,7 +484,7 @@ python-versions = ">=3.7.0"
 
 [package.dependencies]
 requests = ">=2.25.0"
-requests-toolbelt = ">=0.9.1"
+requests-toolbelt = ">=0.10.1"
 
 [package.extras]
 autocompletion = ["argcomplete (>=1.10.0,<3)"]
@@ -488,7 +492,7 @@ yaml = ["PyYaml (>=5.2)"]
 
 [[package]]
 name = "python-semantic-release"
-version = "7.29.1"
+version = "7.33.2"
 description = "Automatic Semantic Versioning for Python projects"
 category = "dev"
 optional = false
@@ -500,17 +504,18 @@ click-log = ">=0.3,<1"
 dotty-dict = ">=1.3.0,<2"
 gitpython = ">=3.0.8,<4"
 invoke = ">=1.4.1,<2"
+packaging = "*"
 python-gitlab = ">=2,<4"
 requests = ">=2.25,<3"
 semver = ">=2.10,<3"
-tomlkit = ">=0.10.0,<0.11.0"
+tomlkit = ">=0.10,<1.0"
 twine = ">=3,<4"
 
 [package.extras]
 dev = ["tox", "isort", "black"]
 docs = ["Sphinx (==1.3.6)", "Jinja2 (==3.0.3)"]
 mypy = ["mypy", "types-requests"]
-test = ["coverage (>=5,<6)", "pytest (>=5,<6)", "pytest-xdist (>=1,<2)", "pytest-mock (>=2,<3)", "responses (==0.13.3)", "mock (==1.3.0)"]
+test = ["coverage (>=5,<6)", "pytest (>=7,<8)", "pytest-xdist (>=1,<2)", "pytest-mock (>=2,<3)", "responses (==0.13.3)", "mock (==1.3.0)"]
 
 [[package]]
 name = "pywin32-ctypes"
@@ -522,7 +527,7 @@ python-versions = "*"
 
 [[package]]
 name = "readme-renderer"
-version = "35.0"
+version = "37.3"
 description = "readme_renderer is a library for rendering \"readme\" descriptions for Warehouse"
 category = "dev"
 optional = false
@@ -538,7 +543,7 @@ md = ["cmarkgfm (>=0.8.0)"]
 
 [[package]]
 name = "requests"
-version = "2.28.0"
+version = "2.28.2"
 description = "Python HTTP for Humans."
 category = "dev"
 optional = false
@@ -546,21 +551,21 @@ python-versions = ">=3.7, <4"
 
 [package.dependencies]
 certifi = ">=2017.4.17"
-charset-normalizer = ">=2.0.0,<2.1.0"
+charset-normalizer = ">=2,<4"
 idna = ">=2.5,<4"
 urllib3 = ">=1.21.1,<1.27"
 
 [package.extras]
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
-use_chardet_on_py3 = ["chardet (>=3.0.2,<5)"]
+use_chardet_on_py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
 name = "requests-toolbelt"
-version = "0.9.1"
+version = "0.10.1"
 description = "A utility belt for advanced users of python-requests"
 category = "dev"
 optional = false
-python-versions = "*"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 
 [package.dependencies]
 requests = ">=2.0.1,<3.0.0"
@@ -578,18 +583,23 @@ idna2008 = ["idna"]
 
 [[package]]
 name = "scipy"
-version = "1.8.0"
-description = "SciPy: Scientific Library for Python"
+version = "1.10.0"
+description = "Fundamental algorithms for scientific computing in Python"
 category = "main"
 optional = false
-python-versions = ">=3.8,<3.11"
+python-versions = "<3.12,>=3.8"
 
 [package.dependencies]
-numpy = ">=1.17.3,<1.25.0"
+numpy = ">=1.19.5,<1.27.0"
+
+[package.extras]
+test = ["pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "asv", "mpmath", "gmpy2", "threadpoolctl", "scikit-umfpack", "pooch"]
+doc = ["sphinx (!=4.1.0)", "pydata-sphinx-theme (==0.9.0)", "sphinx-design (>=0.2.0)", "matplotlib (>2)", "numpydoc"]
+dev = ["mypy", "typing-extensions", "pycodestyle", "flake8", "rich-click", "click", "doit (>=0.36.0)", "pydevtool"]
 
 [[package]]
 name = "secretstorage"
-version = "3.3.2"
+version = "3.3.3"
 description = "Python bindings to FreeDesktop.org Secret Service API"
 category = "dev"
 optional = false
@@ -607,22 +617,6 @@ category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 
-[[package]]
-name = "setuptools-scm"
-version = "6.4.2"
-description = "the blessed package to manage your versions by scm tags"
-category = "dev"
-optional = false
-python-versions = ">=3.6"
-
-[package.dependencies]
-packaging = ">=20.0"
-tomli = ">=1.0.0"
-
-[package.extras]
-test = ["pytest (>=6.2)", "virtualenv (>20)"]
-toml = ["setuptools (>=42)"]
-
 [[package]]
 name = "six"
 version = "1.16.0"
@@ -649,19 +643,19 @@ python-versions = ">=3.7"
 
 [[package]]
 name = "tomlkit"
-version = "0.10.2"
+version = "0.11.7"
 description = "Style preserving TOML library"
 category = "dev"
 optional = false
-python-versions = ">=3.6,<4.0"
+python-versions = ">=3.7"
 
 [[package]]
 name = "tqdm"
-version = "4.64.0"
+version = "4.65.0"
 description = "Fast, Extensible Progress Meter"
 category = "dev"
 optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
+python-versions = ">=3.7"
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
@@ -694,7 +688,7 @@ urllib3 = ">=1.26.0"
 
 [[package]]
 name = "typing-extensions"
-version = "4.2.0"
+version = "4.5.0"
 description = "Backported and Experimental Type Hints for Python 3.7+"
 category = "dev"
 optional = false
@@ -702,15 +696,15 @@ python-versions = ">=3.7"
 
 [[package]]
 name = "urllib3"
-version = "1.26.9"
+version = "1.26.15"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 category = "dev"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 
 [package.extras]
 brotli = ["brotlicffi (>=0.8.0)", "brotli (>=1.0.9)", "brotlipy (>=0.6.0)"]
-secure = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "certifi", "ipaddress"]
+secure = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "certifi", "urllib3-secure-extra", "ipaddress"]
 socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
@@ -723,24 +717,22 @@ python-versions = "*"
 
 [[package]]
 name = "zipp"
-version = "3.8.0"
+version = "3.15.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 category = "dev"
 optional = false
 python-versions = ">=3.7"
 
 [package.extras]
-docs = ["sphinx", "jaraco.packaging (>=9)", "rst.linker (>=1.9)"]
-testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "jaraco.itertools", "func-timeout", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)"]
+docs = ["sphinx (>=3.5)", "jaraco.packaging (>=9)", "rst.linker (>=1.9)", "furo", "sphinx-lint", "jaraco.tidelift (>=1.4)"]
+testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "flake8 (<5)", "pytest-cov", "pytest-enabler (>=1.3)", "jaraco.itertools", "jaraco.functools", "more-itertools", "big-o", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)", "pytest-flake8"]
 
 [metadata]
 lock-version = "1.1"
-python-versions = "^3.8,<3.10"
-content-hash = "1e52cabf54af905e05d979683b28779e59690cf38ad4f805dbbf455b19d0a337"
+python-versions = ">=3.8.1,<3.10"
+content-hash = "111972d04616ce3ddfc9039a0b38c7eb7c4a41f10390139b27e958aedac7e979"
 
 [metadata.files]
-atomicwrites = []
-attrs = []
 black = []
 bleach = []
 certifi = []
@@ -753,16 +745,20 @@ coverage = []
 cryptography = []
 docutils = []
 dotty-dict = []
+exceptiongroup = []
 flake8 = []
 gitdb = []
 gitpython = []
 idna = []
 importlib-metadata = []
+importlib-resources = []
 iniconfig = []
 invoke = []
+"jaraco.classes" = []
 jeepney = []
 keyring = []
 mccabe = []
+more-itertools = []
 mypy = []
 mypy-extensions = []
 numpy = []
@@ -772,12 +768,10 @@ pdme = []
 pkginfo = []
 platformdirs = []
 pluggy = []
-py = []
 pycodestyle = []
 pycparser = []
 pyflakes = []
 pygments = []
-pyparsing = []
 pytest = []
 pytest-cov = []
 python-gitlab = []
@@ -790,7 +784,6 @@ rfc3986 = []
 scipy = []
 secretstorage = []
 semver = []
-setuptools-scm = []
 six = []
 smmap = []
 tomli = []

pyproject.toml

@@ -1,19 +1,19 @@
 [tool.poetry]
 name = "deepdog"
-version = "0.6.4"
+version = "0.7.3"
 description = ""
 authors = ["Deepak Mallubhotla <dmallubhotla+github@gmail.com>"]
 
 [tool.poetry.dependencies]
-python = "^3.8,<3.10"
-pdme = "^0.8.6"
+python = ">=3.8.1,<3.10"
+pdme = "^0.9.1"
 numpy = "1.22.3"
-scipy = "1.8.0"
+scipy = "1.10"
 
 [tool.poetry.dev-dependencies]
 pytest = ">=6"
-flake8 = "^4.0.1"
-pytest-cov = "^3.0.0"
+flake8 = "^6.0.0"
+pytest-cov = "^4.1.0"
 mypy = "^0.971"
 python-semantic-release = "^7.24.0"
 black = "^22.3.0"