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renovate/s
...
0992f0e746
| Author | SHA1 | Date | |
|---|---|---|---|
| 0992f0e746 |
4
.gitignore
vendored
4
.gitignore
vendored
@@ -114,10 +114,6 @@ ENV/
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env.bak/
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venv.bak/
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# direnv
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.envrc
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.direnv
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# Spyder project settings
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.spyderproject
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.spyproject
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98
CHANGELOG.md
98
CHANGELOG.md
@@ -2,104 +2,6 @@
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All notable changes to this project will be documented in this file. See [standard-version](https://github.com/conventional-changelog/standard-version) for commit guidelines.
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### [0.6.4](https://gitea.deepak.science:2222/physics/deepdog/compare/0.6.3...0.6.4) (2022-08-13)
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### Features
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* Prints model names while running ([7ea1d71](https://gitea.deepak.science:2222/physics/deepdog/commit/7ea1d715f67e81c9fa841c5a62f1cc700ff7363d))
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### [0.6.3](https://gitea.deepak.science:2222/physics/deepdog/compare/0.6.2...0.6.3) (2022-06-12)
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### Features
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* adds fast filter variant ([2c5c122](https://gitea.deepak.science:2222/physics/deepdog/commit/2c5c1228209e51d17253f07470e2f1e6dc6872d7))
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* adds tester for fast filter real spectrum ([0a1a277](https://gitea.deepak.science:2222/physics/deepdog/commit/0a1a27759b0d4ab01da214b76ab14bf2b1fe00e3))
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### [0.6.2](https://gitea.deepak.science:2222/physics/deepdog/compare/0.6.1...0.6.2) (2022-05-26)
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### Features
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* adds better import api for real data run ([d7e0f13](https://gitea.deepak.science:2222/physics/deepdog/commit/d7e0f13ca55197b24cb534c80f321ee76b9c4a40))
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### [0.6.1](https://gitea.deepak.science:2222/physics/deepdog/compare/0.6.0...0.6.1) (2022-05-22)
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### Features
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* adds new runner for real spectra ([bd56f24](https://gitea.deepak.science:2222/physics/deepdog/commit/bd56f247748babb2ee1f2a1182d25aa968bff5a5))
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## [0.6.0](https://gitea.deepak.science:2222/physics/deepdog/compare/0.5.0...0.6.0) (2022-05-22)
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||||
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### ⚠ BREAKING CHANGES
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* bayes run now handles multidipoles with changes to output file format etc.
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* logs multiple dipoles better maybe
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* switches over to pdme new stuff, uses models and scraps discretisations entirely
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* removes alt_bayes bayes distinction, which was superfluous when only alt worked
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### Features
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* adds pdme 0.7.0 for multiprocessing ([874d876](https://gitea.deepak.science:2222/physics/deepdog/commit/874d876c9d774433b034d47c4cc0cdac41e6f2c7))
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* bayes run now handles multidipoles with changes to output file format etc. ([5d0a7a4](https://gitea.deepak.science:2222/physics/deepdog/commit/5d0a7a4be09c58f8f8f859384f01d7912a98b8b9))
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* logs multiple dipoles better maybe ([ae8977b](https://gitea.deepak.science:2222/physics/deepdog/commit/ae8977bb1e4d6cd71e88ea0876da8f4318e030b6))
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* removes alt_bayes bayes distinction, which was superfluous when only alt worked ([101569d](https://gitea.deepak.science:2222/physics/deepdog/commit/101569d749e4f3f1842886aa2fd3321b8132278b))
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* switches over to pdme new stuff, uses models and scraps discretisations entirely ([6e29f7a](https://gitea.deepak.science:2222/physics/deepdog/commit/6e29f7a702b578c266a42bba23ac973d155ada10))
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* Uses multidipole for bayes run, with more verbose output ([df89776](https://gitea.deepak.science:2222/physics/deepdog/commit/df8977655de977fd3c4f7383dd9571e551eb1382))
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### Bug Fixes
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* another bug fix for csv generation ([b7da3d6](https://gitea.deepak.science:2222/physics/deepdog/commit/b7da3d61cc5c128cba1d2fcb3770b71b7f6fc4b8))
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* fixes crash when dipole count is smaller than expected max during file write ([b5e0ecb](https://gitea.deepak.science:2222/physics/deepdog/commit/b5e0ecb52886b32d9055302eacfabb69338026b4))
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* fixes format string in csv output for headers ([9afa209](https://gitea.deepak.science:2222/physics/deepdog/commit/9afa209864cdb9255988778e987fe05952848fd4))
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* fixes random issue ([eec926a](https://gitea.deepak.science:2222/physics/deepdog/commit/eec926aaac654f78942b4c6b612e4d1cdcbf81dc))
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* moves logging successes to after they've actually happened ([0caad05](https://gitea.deepak.science:2222/physics/deepdog/commit/0caad05e3cc6a9adba8bf937c3d2f944e1b096a3))
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* now doesn't double randomise frequency ([23b202b](https://gitea.deepak.science:2222/physics/deepdog/commit/23b202beb81cb89f7f20b691e83116fa53764902))
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* whoops deleted word multiprocessing ([31070b5](https://gitea.deepak.science:2222/physics/deepdog/commit/31070b5342c265d930b4c51402f42a3ee2415066))
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## [0.5.0](https://gitea.deepak.science:2222/physics/deepdog/compare/0.4.0...0.5.0) (2022-04-30)
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### ⚠ BREAKING CHANGES
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* simulpairs now uses different rng calculator
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### Features
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* adds simulpairs run ([e9277c3](https://gitea.deepak.science:2222/physics/deepdog/commit/e9277c3da777359feb352c0b19f3bb029248ba2f))
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* has better parallelisation ([edf0ba6](https://gitea.deepak.science:2222/physics/deepdog/commit/edf0ba6532c0588fce32341709cdb70e384b83f4))
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* simulpairs now uses different rng calculator ([50dbc48](https://gitea.deepak.science:2222/physics/deepdog/commit/50dbc4835e60bace9e9b4ba37415f073a3c9e479))
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### Bug Fixes
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* better parallelisation hopefully ([42829c0](https://gitea.deepak.science:2222/physics/deepdog/commit/42829c0327e080e18be2fb75e746f6ac0d7c2f6d))
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* Makes altbayessimulpairs available in package ([492a5e6](https://gitea.deepak.science:2222/physics/deepdog/commit/492a5e6681c85f95840e28cfd5d4ce4ca1d54eba))
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* stronger names ([0954429](https://gitea.deepak.science:2222/physics/deepdog/commit/0954429e2d015a105ff16dfbb9e7a352bf53e5e9))
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* Uses correct filename arg for passed in rng ([349341b](https://gitea.deepak.science:2222/physics/deepdog/commit/349341b405375a43b933f1fd7db4ee9fc501def3))
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* uses correct filename for pairs guy ([4c06b39](https://gitea.deepak.science:2222/physics/deepdog/commit/4c06b3912c811c93c310b1d9e4c153f2014c4f8b))
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## [0.4.0](https://gitea.deepak.science:2222/physics/deepdog/compare/0.3.5...0.4.0) (2022-04-10)
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### ⚠ BREAKING CHANGES
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* Adds pair calculations, with changing api format
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### Features
|
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* Adds dynamic cycle count increases to help reach minimum success count ([ec7b4ca](https://gitea.deepak.science:2222/physics/deepdog/commit/ec7b4cac393c15e94c513215c4f1ba32be2ae87a))
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* Adds pair calculations, with changing api format ([6463b13](https://gitea.deepak.science:2222/physics/deepdog/commit/6463b135ef2d212b565864b5ac1b655e014d2194))
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### Bug Fixes
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* uses bigfix from pdme for negatives ([c1c711f](https://gitea.deepak.science:2222/physics/deepdog/commit/c1c711f47b574d3a9b8a24dbcbdd7f50b9be8ea9))
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### [0.3.5](https://gitea.deepak.science:2222/physics/deepdog/compare/0.3.4...0.3.5) (2022-03-07)
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@@ -1,20 +1,15 @@
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import logging
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from deepdog.meta import __version__
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from deepdog.bayes_run import BayesRun
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from deepdog.bayes_run_simulpairs import BayesRunSimulPairs
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from deepdog.real_spectrum_run import RealSpectrumRun
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from deepdog.alt_bayes_run import AltBayesRun
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from deepdog.diagnostic import Diagnostic
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def get_version():
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return __version__
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__all__ = [
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"get_version",
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"BayesRun",
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"BayesRunSimulPairs",
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"RealSpectrumRun",
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]
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__all__ = ["get_version", "BayesRun", "AltBayesRun", "Diagnostic"]
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logging.getLogger(__name__).addHandler(logging.NullHandler())
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134
deepdog/alt_bayes_run.py
Normal file
134
deepdog/alt_bayes_run.py
Normal file
@@ -0,0 +1,134 @@
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import pdme.model
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import pdme.measurement.oscillating_dipole
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import pdme.util.fast_v_calc
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from typing import Sequence, Tuple, List
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import datetime
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import csv
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import multiprocessing
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import logging
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import numpy
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# TODO: remove hardcode
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CHUNKSIZE = 50
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# TODO: It's garbage to have this here duplicated from pdme.
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DotInput = Tuple[numpy.typing.ArrayLike, float]
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_logger = logging.getLogger(__name__)
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def get_a_result(input) -> int:
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discretisation, dot_inputs, lows, highs, monte_carlo_count, max_frequency = input
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sample_dipoles = discretisation.get_model().get_n_single_dipoles(monte_carlo_count, max_frequency)
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vals = pdme.util.fast_v_calc.fast_vs_for_dipoles(dot_inputs, sample_dipoles)
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return numpy.count_nonzero(pdme.util.fast_v_calc.between(vals, lows, highs))
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class AltBayesRun():
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'''
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A single Bayes run for a given set of dots.
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Parameters
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----------
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dot_inputs : Sequence[DotInput]
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The dot inputs for this bayes run.
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discretisations_with_names : Sequence[Tuple(str, pdme.model.Model)]
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The models to evaluate.
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actual_model_discretisation : pdme.model.Discretisation
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The discretisation for the model which is actually correct.
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filename_slug : str
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The filename slug to include.
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run_count: int
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The number of runs to do.
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'''
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def __init__(self, dot_inputs: Sequence[DotInput], discretisations_with_names: Sequence[Tuple[str, pdme.model.Discretisation]], actual_model: pdme.model.Model, filename_slug: str, run_count: int, low_error: float = 0.9, high_error: float = 1.1, monte_carlo_count: int = 10000, monte_carlo_cycles: int = 10, max_frequency: float = 20, end_threshold: float = None, chunksize: int = CHUNKSIZE) -> None:
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self.dot_inputs = dot_inputs
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self.dot_inputs_array = pdme.measurement.oscillating_dipole.dot_inputs_to_array(dot_inputs)
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self.discretisations = [disc for (_, disc) in discretisations_with_names]
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self.model_names = [name for (name, _) in discretisations_with_names]
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self.actual_model = actual_model
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self.model_count = len(self.discretisations)
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self.monte_carlo_count = monte_carlo_count
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self.monte_carlo_cycles = monte_carlo_cycles
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self.run_count = run_count
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self.low_error = low_error
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self.high_error = high_error
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self.csv_fields = ["dipole_moment", "dipole_location", "dipole_frequency"]
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self.compensate_zeros = True
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self.chunksize = chunksize
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for name in self.model_names:
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self.csv_fields.extend([f"{name}_success", f"{name}_count", f"{name}_prob"])
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self.probabilities = [1 / self.model_count] * self.model_count
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timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
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self.filename = f"{timestamp}-{filename_slug}.altbayes.csv"
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self.max_frequency = max_frequency
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if end_threshold is not None:
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if 0 < end_threshold < 1:
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self.end_threshold: float = end_threshold
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self.use_end_threshold = True
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_logger.info(f"Will abort early, at {self.end_threshold}.")
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else:
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raise ValueError(f"end_threshold should be between 0 and 1, but is actually {end_threshold}")
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def go(self) -> None:
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with open(self.filename, "a", newline="") as outfile:
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writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
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writer.writeheader()
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for run in range(1, self.run_count + 1):
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rng = numpy.random.default_rng()
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frequency = rng.uniform(1, self.max_frequency)
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# Generate the actual dipoles
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actual_dipoles = self.actual_model.get_dipoles(frequency)
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dots = actual_dipoles.get_percent_range_dot_measurements(self.dot_inputs, self.low_error, self.high_error)
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lows, highs = pdme.measurement.oscillating_dipole.dot_range_measurements_low_high_arrays(dots)
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_logger.info(f"Going to work on dipole at {actual_dipoles.dipoles}")
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results = []
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_logger.debug("Going to iterate over discretisations now")
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for disc_count, discretisation in enumerate(self.discretisations):
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_logger.debug(f"Doing discretisation #{disc_count}")
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with multiprocessing.Pool(multiprocessing.cpu_count() - 1 or 1) as pool:
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results.append(sum(
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pool.imap_unordered(get_a_result, [(discretisation, self.dot_inputs_array, lows, highs, self.monte_carlo_count, self.max_frequency)] * self.monte_carlo_cycles, self.chunksize)
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))
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_logger.debug("Done, constructing output now")
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row = {
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"dipole_moment": actual_dipoles.dipoles[0].p,
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"dipole_location": actual_dipoles.dipoles[0].s,
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"dipole_frequency": actual_dipoles.dipoles[0].w
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}
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successes: List[float] = []
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counts: List[int] = []
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for model_index, (name, result) in enumerate(zip(self.model_names, results)):
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row[f"{name}_success"] = result
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row[f"{name}_count"] = self.monte_carlo_count * self.monte_carlo_cycles
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successes.append(max(result, 0.5))
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counts.append(self.monte_carlo_count * self.monte_carlo_cycles)
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success_weight = sum([(succ / count) * prob for succ, count, prob in zip(successes, counts, self.probabilities)])
|
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new_probabilities = [(succ / count) * old_prob / success_weight for succ, count, old_prob in zip(successes, counts, self.probabilities)]
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self.probabilities = new_probabilities
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for name, probability in zip(self.model_names, self.probabilities):
|
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row[f"{name}_prob"] = probability
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_logger.info(row)
|
||||
|
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with open(self.filename, "a", newline="") as outfile:
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writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
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writer.writerow(row)
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|
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if self.use_end_threshold:
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max_prob = max(self.probabilities)
|
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if max_prob > self.end_threshold:
|
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_logger.info(f"Aborting early, because {max_prob} is greater than {self.end_threshold}")
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break
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||||
@@ -1,19 +1,17 @@
|
||||
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
|
||||
import datetime
|
||||
import itertools
|
||||
import csv
|
||||
import multiprocessing
|
||||
import logging
|
||||
import numpy
|
||||
import scipy.optimize
|
||||
import multiprocessing
|
||||
|
||||
|
||||
# TODO: remove hardcode
|
||||
CHUNKSIZE = 50
|
||||
COST_THRESHOLD = 1e-10
|
||||
|
||||
|
||||
# TODO: It's garbage to have this here duplicated from pdme.
|
||||
DotInput = Tuple[numpy.typing.ArrayLike, float]
|
||||
@@ -22,126 +20,43 @@ DotInput = Tuple[numpy.typing.ArrayLike, float]
|
||||
_logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def get_a_result(input) -> int:
|
||||
model, dot_inputs, lows, highs, monte_carlo_count, max_frequency, seed = input
|
||||
|
||||
rng = numpy.random.default_rng(seed)
|
||||
sample_dipoles = model.get_monte_carlo_dipole_inputs(
|
||||
monte_carlo_count, max_frequency, 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))
|
||||
def get_a_result(discretisation, dots, index) -> Tuple[Tuple[int, ...], scipy.optimize.OptimizeResult]:
|
||||
return (index, discretisation.solve_for_index(dots, index))
|
||||
|
||||
|
||||
def get_a_result_using_pairs(input) -> int:
|
||||
(
|
||||
model,
|
||||
dot_inputs,
|
||||
pair_inputs,
|
||||
local_lows,
|
||||
local_highs,
|
||||
nonlocal_lows,
|
||||
nonlocal_highs,
|
||||
monte_carlo_count,
|
||||
max_frequency,
|
||||
) = input
|
||||
sample_dipoles = model.get_n_single_dipoles(monte_carlo_count, max_frequency)
|
||||
local_vals = pdme.util.fast_v_calc.fast_vs_for_dipoles(dot_inputs, sample_dipoles)
|
||||
local_matches = pdme.util.fast_v_calc.between(local_vals, local_lows, local_highs)
|
||||
nonlocal_vals = pdme.util.fast_nonlocal_spectrum.fast_s_nonlocal(
|
||||
pair_inputs, sample_dipoles
|
||||
)
|
||||
nonlocal_matches = pdme.util.fast_v_calc.between(
|
||||
nonlocal_vals, nonlocal_lows, nonlocal_highs
|
||||
)
|
||||
combined_matches = numpy.logical_and(local_matches, nonlocal_matches)
|
||||
return numpy.count_nonzero(combined_matches)
|
||||
|
||||
|
||||
class BayesRun:
|
||||
"""
|
||||
class BayesRun():
|
||||
'''
|
||||
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)]
|
||||
discretisations_with_names : Sequence[Tuple(str, pdme.model.Model)]
|
||||
The models to evaluate.
|
||||
|
||||
actual_model : pdme.model.DipoleModel
|
||||
The model which is actually correct.
|
||||
|
||||
actual_model_discretisation : pdme.model.Discretisation
|
||||
The discretisation for 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,
|
||||
run_count: int = 100,
|
||||
low_error: float = 0.9,
|
||||
high_error: float = 1.1,
|
||||
monte_carlo_count: int = 10000,
|
||||
monte_carlo_cycles: int = 10,
|
||||
target_success: int = 100,
|
||||
max_monte_carlo_cycles_steps: int = 10,
|
||||
max_frequency: float = 20,
|
||||
end_threshold: float = None,
|
||||
chunksize: int = CHUNKSIZE,
|
||||
) -> 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 = [model for (_, model) in models_with_names]
|
||||
self.model_names = [name for (name, _) in models_with_names]
|
||||
'''
|
||||
def __init__(self, dot_inputs: Sequence[DotInput], discretisations_with_names: Sequence[Tuple[str, pdme.model.Discretisation]], actual_model: pdme.model.Model, filename_slug: str, run_count: int, max_frequency: float = None, end_threshold: float = None) -> None:
|
||||
self.dot_inputs = dot_inputs
|
||||
self.discretisations = [disc for (_, disc) in discretisations_with_names]
|
||||
self.model_names = [name for (name, _) in discretisations_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.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.model_count = len(self.discretisations)
|
||||
self.run_count = run_count
|
||||
self.low_error = low_error
|
||||
self.high_error = high_error
|
||||
|
||||
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.csv_fields = ["dipole_moment", "dipole_location", "dipole_frequency"]
|
||||
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"])
|
||||
|
||||
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}.bayesrun.csv"
|
||||
self.filename = f"{timestamp}-{filename_slug}.csv"
|
||||
self.max_frequency = max_frequency
|
||||
|
||||
if end_threshold is not None:
|
||||
@@ -150,9 +65,7 @@ class BayesRun:
|
||||
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}"
|
||||
)
|
||||
raise ValueError(f"end_threshold should be between 0 and 1, but is actually {end_threshold}")
|
||||
|
||||
def go(self) -> None:
|
||||
with open(self.filename, "a", newline="") as outfile:
|
||||
@@ -160,122 +73,56 @@ class BayesRun:
|
||||
writer.writeheader()
|
||||
|
||||
for run in range(1, self.run_count + 1):
|
||||
frequency: float = run
|
||||
if self.max_frequency is not None and self.max_frequency > 1:
|
||||
rng = numpy.random.default_rng()
|
||||
frequency = rng.uniform(1, self.max_frequency)
|
||||
dipoles = self.actual_model.get_dipoles(frequency)
|
||||
|
||||
# Generate the actual dipoles
|
||||
actual_dipoles = self.actual_model.get_dipoles(self.max_frequency)
|
||||
|
||||
dots = actual_dipoles.get_percent_range_dot_measurements(
|
||||
self.dot_inputs, self.low_error, self.high_error
|
||||
)
|
||||
(
|
||||
lows,
|
||||
highs,
|
||||
) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
|
||||
dots
|
||||
)
|
||||
|
||||
_logger.info(f"Going to work on dipole at {actual_dipoles.dipoles}")
|
||||
|
||||
# define a new seed sequence for each run
|
||||
seed_sequence = numpy.random.SeedSequence(run)
|
||||
dots = dipoles.get_dot_measurements(self.dot_inputs)
|
||||
_logger.info(f"Going to work on dipole at {dipoles.dipoles}")
|
||||
|
||||
results = []
|
||||
_logger.debug("Going to iterate over models now")
|
||||
for model_count, model in enumerate(self.models):
|
||||
_logger.debug(f"Doing model #{model_count}")
|
||||
core_count = multiprocessing.cpu_count() - 1 or 1
|
||||
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)
|
||||
|
||||
current_success = sum(
|
||||
pool.imap_unordered(
|
||||
get_a_result,
|
||||
[
|
||||
(
|
||||
model,
|
||||
self.dot_inputs_array,
|
||||
lows,
|
||||
highs,
|
||||
self.monte_carlo_count,
|
||||
self.max_frequency,
|
||||
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("Going to iterate over discretisations now")
|
||||
for disc_count, discretisation in enumerate(self.discretisations):
|
||||
_logger.debug(f"Doing discretisation #{disc_count}")
|
||||
with multiprocessing.Pool(multiprocessing.cpu_count() - 1 or 1) as pool:
|
||||
results.append(pool.starmap(get_a_result, zip(itertools.repeat(discretisation), itertools.repeat(dots), discretisation.all_indices())))
|
||||
|
||||
_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,
|
||||
"dipole_moment": dipoles.dipoles[0].p,
|
||||
"dipole_location": dipoles.dipoles[0].s,
|
||||
"dipole_frequency": 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
|
||||
|
||||
successes: List[float] = []
|
||||
counts: List[int] = []
|
||||
for model_index, (name, (count, result)) in enumerate(
|
||||
zip(self.model_names, results)
|
||||
):
|
||||
for model_index, (name, result) in enumerate(zip(self.model_names, results)):
|
||||
count = 0
|
||||
success = 0
|
||||
for idx, val in result:
|
||||
count += 1
|
||||
if val.success and val.cost <= COST_THRESHOLD:
|
||||
success += 1
|
||||
|
||||
row[f"{name}_success"] = result
|
||||
row[f"{name}_success"] = success
|
||||
row[f"{name}_count"] = count
|
||||
successes.append(max(result, 0.5))
|
||||
successes.append(max(success, 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)
|
||||
]
|
||||
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 = 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}"
|
||||
)
|
||||
_logger.info(f"Aborting early, because {max_prob} is greater than {self.end_threshold}")
|
||||
break
|
||||
|
||||
@@ -1,382 +0,0 @@
|
||||
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
|
||||
import datetime
|
||||
import csv
|
||||
import multiprocessing
|
||||
import logging
|
||||
import numpy
|
||||
import numpy.random
|
||||
|
||||
|
||||
# TODO: remove hardcode
|
||||
CHUNKSIZE = 50
|
||||
|
||||
# TODO: It's garbage to have this here duplicated from pdme.
|
||||
DotInput = Tuple[numpy.typing.ArrayLike, float]
|
||||
|
||||
|
||||
_logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def get_a_simul_result_using_pairs(input) -> numpy.ndarray:
|
||||
(
|
||||
model,
|
||||
dot_inputs,
|
||||
pair_inputs,
|
||||
local_lows,
|
||||
local_highs,
|
||||
nonlocal_lows,
|
||||
nonlocal_highs,
|
||||
monte_carlo_count,
|
||||
monte_carlo_cycles,
|
||||
max_frequency,
|
||||
seed,
|
||||
) = input
|
||||
|
||||
rng = numpy.random.default_rng(seed)
|
||||
local_total = 0
|
||||
combined_total = 0
|
||||
|
||||
sample_dipoles = model.get_monte_carlo_dipole_inputs(
|
||||
monte_carlo_count, max_frequency, rng_to_use=rng
|
||||
)
|
||||
local_vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(dot_inputs, sample_dipoles)
|
||||
local_matches = pdme.util.fast_v_calc.between(local_vals, local_lows, local_highs)
|
||||
nonlocal_vals = pdme.util.fast_nonlocal_spectrum.fast_s_nonlocal_dipoleses(
|
||||
pair_inputs, sample_dipoles
|
||||
)
|
||||
nonlocal_matches = pdme.util.fast_v_calc.between(
|
||||
nonlocal_vals, nonlocal_lows, nonlocal_highs
|
||||
)
|
||||
combined_matches = numpy.logical_and(local_matches, nonlocal_matches)
|
||||
|
||||
local_total += numpy.count_nonzero(local_matches)
|
||||
combined_total += numpy.count_nonzero(combined_matches)
|
||||
return numpy.array([local_total, combined_total])
|
||||
|
||||
|
||||
class BayesRunSimulPairs:
|
||||
"""
|
||||
A dual pairs-nonpairs 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 modoel for 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,
|
||||
run_count: int = 100,
|
||||
low_error: float = 0.9,
|
||||
high_error: float = 1.1,
|
||||
pairs_high_error=None,
|
||||
pairs_low_error=None,
|
||||
monte_carlo_count: int = 10000,
|
||||
monte_carlo_cycles: int = 10,
|
||||
target_success: int = 100,
|
||||
max_monte_carlo_cycles_steps: int = 10,
|
||||
max_frequency: float = 20,
|
||||
end_threshold: float = None,
|
||||
chunksize: int = CHUNKSIZE,
|
||||
) -> 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.dot_pair_inputs = pdme.inputs.input_pairs_with_frequency_range(
|
||||
dot_positions, frequency_range
|
||||
)
|
||||
self.dot_pair_inputs_array = (
|
||||
pdme.measurement.input_types.dot_pair_inputs_to_array(self.dot_pair_inputs)
|
||||
)
|
||||
|
||||
self.models = [mod for (_, mod) 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.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.run_count = run_count
|
||||
self.low_error = low_error
|
||||
self.high_error = high_error
|
||||
if pairs_low_error is None:
|
||||
self.pairs_low_error = self.low_error
|
||||
else:
|
||||
self.pairs_low_error = pairs_low_error
|
||||
if pairs_high_error is None:
|
||||
self.pairs_high_error = self.high_error
|
||||
else:
|
||||
self.pairs_high_error = pairs_high_error
|
||||
|
||||
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}_success", f"{name}_count", f"{name}_prob"])
|
||||
|
||||
self.probabilities_no_pairs = [1 / self.model_count] * self.model_count
|
||||
self.probabilities_pairs = [1 / self.model_count] * self.model_count
|
||||
|
||||
timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
|
||||
self.filename_pairs = f"{timestamp}-{filename_slug}.simulpairs.yespairs.csv"
|
||||
self.filename_no_pairs = f"{timestamp}-{filename_slug}.simulpairs.noopairs.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}"
|
||||
)
|
||||
|
||||
def go(self) -> None:
|
||||
with open(self.filename_pairs, "a", newline="") as outfile:
|
||||
writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
|
||||
writer.writeheader()
|
||||
with open(self.filename_no_pairs, "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)
|
||||
|
||||
dots = actual_dipoles.get_percent_range_dot_measurements(
|
||||
self.dot_inputs, self.low_error, self.high_error
|
||||
)
|
||||
(
|
||||
lows,
|
||||
highs,
|
||||
) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
|
||||
dots
|
||||
)
|
||||
|
||||
pair_lows, pair_highs = (None, None)
|
||||
pair_measurements = actual_dipoles.get_percent_range_dot_pair_measurements(
|
||||
self.dot_pair_inputs, self.pairs_low_error, self.pairs_high_error
|
||||
)
|
||||
(
|
||||
pair_lows,
|
||||
pair_highs,
|
||||
) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
|
||||
pair_measurements
|
||||
)
|
||||
|
||||
_logger.info(f"Going to work on dipole at {actual_dipoles.dipoles}")
|
||||
|
||||
# define a new seed sequence for each run
|
||||
seed_sequence = numpy.random.SeedSequence(run)
|
||||
|
||||
results_pairs = []
|
||||
results_no_pairs = []
|
||||
_logger.debug("Going to iterate over models now")
|
||||
for model_count, model in enumerate(self.models):
|
||||
_logger.debug(f"Doing model #{model_count}")
|
||||
|
||||
core_count = multiprocessing.cpu_count() - 1 or 1
|
||||
with multiprocessing.Pool(core_count) as pool:
|
||||
cycle_count = 0
|
||||
cycle_success_pairs = 0
|
||||
cycle_success_no_pairs = 0
|
||||
cycles = 0
|
||||
while (cycles < self.max_monte_carlo_cycles_steps) and (
|
||||
min(cycle_success_pairs, cycle_success_no_pairs)
|
||||
<= self.target_success
|
||||
):
|
||||
_logger.debug(f"Starting cycle {cycles}")
|
||||
|
||||
cycles += 1
|
||||
current_success_pairs = 0
|
||||
current_success_no_pairs = 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)
|
||||
_logger.debug(f"Creating {self.monte_carlo_cycles} seeds")
|
||||
current_success_both = numpy.array(
|
||||
sum(
|
||||
pool.imap_unordered(
|
||||
get_a_simul_result_using_pairs,
|
||||
[
|
||||
(
|
||||
model,
|
||||
self.dot_inputs_array,
|
||||
self.dot_pair_inputs_array,
|
||||
lows,
|
||||
highs,
|
||||
pair_lows,
|
||||
pair_highs,
|
||||
self.monte_carlo_count,
|
||||
self.monte_carlo_cycles,
|
||||
self.max_frequency,
|
||||
seed,
|
||||
)
|
||||
for seed in seeds
|
||||
],
|
||||
self.chunksize,
|
||||
)
|
||||
)
|
||||
)
|
||||
current_success_no_pairs = current_success_both[0]
|
||||
current_success_pairs = current_success_both[1]
|
||||
|
||||
cycle_success_no_pairs += current_success_no_pairs
|
||||
cycle_success_pairs += current_success_pairs
|
||||
_logger.debug(
|
||||
f"(pair, no_pair) successes are {(cycle_success_pairs, cycle_success_no_pairs)}"
|
||||
)
|
||||
results_pairs.append((cycle_count, cycle_success_pairs))
|
||||
results_no_pairs.append((cycle_count, cycle_success_no_pairs))
|
||||
|
||||
_logger.debug("Done, constructing output now")
|
||||
row_pairs = {
|
||||
"dipole_moment_1": actual_dipoles.dipoles[0].p,
|
||||
"dipole_location_1": actual_dipoles.dipoles[0].s,
|
||||
"dipole_frequency_1": actual_dipoles.dipoles[0].w,
|
||||
}
|
||||
row_no_pairs = {
|
||||
"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_pairs[f"dipole_moment_{i+1}"] = current_dipoles.p
|
||||
row_pairs[f"dipole_location_{i+1}"] = current_dipoles.s
|
||||
row_pairs[f"dipole_frequency_{i+1}"] = current_dipoles.w
|
||||
row_no_pairs[f"dipole_moment_{i+1}"] = current_dipoles.p
|
||||
row_no_pairs[f"dipole_location_{i+1}"] = current_dipoles.s
|
||||
row_no_pairs[f"dipole_frequency_{i+1}"] = current_dipoles.w
|
||||
except IndexError:
|
||||
_logger.info(f"Not writing anymore, saw end after {i}")
|
||||
break
|
||||
|
||||
successes_pairs: List[float] = []
|
||||
successes_no_pairs: List[float] = []
|
||||
counts: List[int] = []
|
||||
for model_index, (
|
||||
name,
|
||||
(count_pair, result_pair),
|
||||
(count_no_pair, result_no_pair),
|
||||
) in enumerate(zip(self.model_names, results_pairs, results_no_pairs)):
|
||||
|
||||
row_pairs[f"{name}_success"] = result_pair
|
||||
row_pairs[f"{name}_count"] = count_pair
|
||||
successes_pairs.append(max(result_pair, 0.5))
|
||||
|
||||
row_no_pairs[f"{name}_success"] = result_no_pair
|
||||
row_no_pairs[f"{name}_count"] = count_no_pair
|
||||
successes_no_pairs.append(max(result_no_pair, 0.5))
|
||||
|
||||
counts.append(count_pair)
|
||||
|
||||
success_weight_pair = sum(
|
||||
[
|
||||
(succ / count) * prob
|
||||
for succ, count, prob in zip(
|
||||
successes_pairs, counts, self.probabilities_pairs
|
||||
)
|
||||
]
|
||||
)
|
||||
success_weight_no_pair = sum(
|
||||
[
|
||||
(succ / count) * prob
|
||||
for succ, count, prob in zip(
|
||||
successes_no_pairs, counts, self.probabilities_no_pairs
|
||||
)
|
||||
]
|
||||
)
|
||||
new_probabilities_pair = [
|
||||
(succ / count) * old_prob / success_weight_pair
|
||||
for succ, count, old_prob in zip(
|
||||
successes_pairs, counts, self.probabilities_pairs
|
||||
)
|
||||
]
|
||||
new_probabilities_no_pair = [
|
||||
(succ / count) * old_prob / success_weight_no_pair
|
||||
for succ, count, old_prob in zip(
|
||||
successes_no_pairs, counts, self.probabilities_no_pairs
|
||||
)
|
||||
]
|
||||
self.probabilities_pairs = new_probabilities_pair
|
||||
self.probabilities_no_pairs = new_probabilities_no_pair
|
||||
for name, probability_pair, probability_no_pair in zip(
|
||||
self.model_names, self.probabilities_pairs, self.probabilities_no_pairs
|
||||
):
|
||||
row_pairs[f"{name}_prob"] = probability_pair
|
||||
row_no_pairs[f"{name}_prob"] = probability_no_pair
|
||||
_logger.debug(row_pairs)
|
||||
_logger.debug(row_no_pairs)
|
||||
|
||||
with open(self.filename_pairs, "a", newline="") as outfile:
|
||||
writer = csv.DictWriter(
|
||||
outfile, fieldnames=self.csv_fields, dialect="unix"
|
||||
)
|
||||
writer.writerow(row_pairs)
|
||||
with open(self.filename_no_pairs, "a", newline="") as outfile:
|
||||
writer = csv.DictWriter(
|
||||
outfile, fieldnames=self.csv_fields, dialect="unix"
|
||||
)
|
||||
writer.writerow(row_no_pairs)
|
||||
|
||||
if self.use_end_threshold:
|
||||
max_prob = min(
|
||||
max(self.probabilities_pairs), max(self.probabilities_no_pairs)
|
||||
)
|
||||
if max_prob > self.end_threshold:
|
||||
_logger.info(
|
||||
f"Aborting early, because {max_prob} is greater than {self.end_threshold}"
|
||||
)
|
||||
break
|
||||
99
deepdog/diagnostic.py
Normal file
99
deepdog/diagnostic.py
Normal file
@@ -0,0 +1,99 @@
|
||||
from pdme.measurement import OscillatingDipole, OscillatingDipoleArrangement
|
||||
import pdme
|
||||
from deepdog.bayes_run import DotInput
|
||||
import datetime
|
||||
import numpy
|
||||
from dataclasses import dataclass
|
||||
import logging
|
||||
from typing import Sequence, Tuple
|
||||
import csv
|
||||
import itertools
|
||||
import multiprocessing
|
||||
|
||||
_logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def get_a_result(discretisation, dots, index):
|
||||
return (index, discretisation.solve_for_index(dots, index))
|
||||
|
||||
|
||||
@dataclass
|
||||
class SingleDipoleDiagnostic():
|
||||
model: str
|
||||
index: Tuple
|
||||
bounds: Tuple
|
||||
actual_dipole: OscillatingDipole
|
||||
result_dipole: OscillatingDipole
|
||||
success: bool
|
||||
|
||||
def __post_init__(self) -> None:
|
||||
self.p_actual_x = self.actual_dipole.p[0]
|
||||
self.p_actual_y = self.actual_dipole.p[1]
|
||||
self.p_actual_z = self.actual_dipole.p[2]
|
||||
self.s_actual_x = self.actual_dipole.s[0]
|
||||
self.s_actual_y = self.actual_dipole.s[1]
|
||||
self.s_actual_z = self.actual_dipole.s[2]
|
||||
self.p_result_x = self.result_dipole.p[0]
|
||||
self.p_result_y = self.result_dipole.p[1]
|
||||
self.p_result_z = self.result_dipole.p[2]
|
||||
self.s_result_x = self.result_dipole.s[0]
|
||||
self.s_result_y = self.result_dipole.s[1]
|
||||
self.s_result_z = self.result_dipole.s[2]
|
||||
self.w_actual = self.actual_dipole.w
|
||||
self.w_result = self.result_dipole.w
|
||||
|
||||
|
||||
class Diagnostic():
|
||||
'''
|
||||
Represents a diagnostic for a single dipole moment given a set of discretisations.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
dot_inputs : Sequence[DotInput]
|
||||
The dot inputs for this diagnostic.
|
||||
discretisations_with_names : Sequence[Tuple(str, pdme.model.Model)]
|
||||
The models to evaluate.
|
||||
actual_model_discretisation : pdme.model.Discretisation
|
||||
The discretisation for 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, actual_dipole_moment: numpy.ndarray, actual_dipole_position: numpy.ndarray, actual_dipole_frequency: float, dot_inputs: Sequence[DotInput], discretisations_with_names: Sequence[Tuple[str, pdme.model.Discretisation]], filename_slug: str) -> None:
|
||||
self.dipoles = OscillatingDipoleArrangement([OscillatingDipole(actual_dipole_moment, actual_dipole_position, actual_dipole_frequency)])
|
||||
self.dots = self.dipoles.get_dot_measurements(dot_inputs)
|
||||
|
||||
self.discretisations_with_names = discretisations_with_names
|
||||
self.model_count = len(self.discretisations_with_names)
|
||||
|
||||
self.csv_fields = ["model", "index", "bounds", "p_actual_x", "p_actual_y", "p_actual_z", "s_actual_x", "s_actual_y", "s_actual_z", "w_actual", "success", "p_result_x", "p_result_y", "p_result_z", "s_result_x", "s_result_y", "s_result_z", "w_result"]
|
||||
|
||||
timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
|
||||
self.filename = f"{timestamp}-{filename_slug}.diag.csv"
|
||||
|
||||
def go(self):
|
||||
with open(self.filename, "a", newline="") as outfile:
|
||||
# csv fields
|
||||
writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect='unix')
|
||||
writer.writeheader()
|
||||
|
||||
for (name, discretisation) in self.discretisations_with_names:
|
||||
_logger.info(f"Working on discretisation {name}")
|
||||
|
||||
results = []
|
||||
with multiprocessing.Pool(multiprocessing.cpu_count() - 1 or 1) as pool:
|
||||
results = pool.starmap(get_a_result, zip(itertools.repeat(discretisation), itertools.repeat(self.dots), discretisation.all_indices()))
|
||||
|
||||
with open(self.filename, "a", newline='') as outfile:
|
||||
writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect='unix', extrasaction="ignore")
|
||||
|
||||
for idx, result in results:
|
||||
|
||||
bounds = discretisation.bounds(idx)
|
||||
|
||||
actual_success = result.success and result.cost <= 1e-10
|
||||
diag_row = SingleDipoleDiagnostic(name, idx, bounds, self.dipoles.dipoles[0], discretisation.model.solution_as_dipoles(result.normalised_x)[0], actual_success)
|
||||
row = vars(diag_row)
|
||||
_logger.debug(f"Writing result {row}")
|
||||
writer.writerow(row)
|
||||
@@ -1,3 +1,3 @@
|
||||
from importlib.metadata import version
|
||||
|
||||
__version__ = version("deepdog")
|
||||
__version__ = version('deepdog')
|
||||
|
||||
@@ -1,222 +0,0 @@
|
||||
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
|
||||
import datetime
|
||||
import csv
|
||||
import multiprocessing
|
||||
import logging
|
||||
import numpy
|
||||
|
||||
|
||||
# TODO: remove hardcode
|
||||
CHUNKSIZE = 50
|
||||
|
||||
|
||||
_logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def get_a_result(input) -> int:
|
||||
model, dot_inputs, lows, 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))
|
||||
|
||||
|
||||
def get_a_result_fast_filter(input) -> int:
|
||||
model, dot_inputs, lows, 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
|
||||
)
|
||||
|
||||
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)]
|
||||
return len(current_sample)
|
||||
|
||||
|
||||
class RealSpectrumRun:
|
||||
"""
|
||||
A bayes run given some real data.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
measurements : Sequence[pdme.measurement.DotRangeMeasurement]
|
||||
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,
|
||||
measurements: 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,
|
||||
use_fast_filter: bool = True,
|
||||
) -> None:
|
||||
self.measurements = measurements
|
||||
self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements]
|
||||
|
||||
self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(
|
||||
self.dot_inputs
|
||||
)
|
||||
|
||||
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")
|
||||
self.use_fast_filter = use_fast_filter
|
||||
ff_string = "no_fast_filter"
|
||||
if self.use_fast_filter:
|
||||
ff_string = "fast_filter"
|
||||
self.filename = f"{timestamp}-{filename_slug}.realdata.{ff_string}.bayesrun.csv"
|
||||
self.initial_seed = initial_seed
|
||||
|
||||
def go(self) -> None:
|
||||
with open(self.filename, "a", newline="") as outfile:
|
||||
writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
|
||||
writer.writeheader()
|
||||
|
||||
(
|
||||
lows,
|
||||
highs,
|
||||
) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
|
||||
self.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")
|
||||
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
|
||||
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)
|
||||
|
||||
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,
|
||||
)
|
||||
)
|
||||
|
||||
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)
|
||||
5
do.sh
5
do.sh
@@ -16,11 +16,6 @@ test() {
|
||||
poetry run pytest
|
||||
}
|
||||
|
||||
fmt() {
|
||||
poetry run black .
|
||||
find . -type f -name "*.py" -exec sed -i -e 's/ /\t/g' {} \;
|
||||
}
|
||||
|
||||
release() {
|
||||
./scripts/release.sh
|
||||
}
|
||||
|
||||
95
flake.lock
generated
95
flake.lock
generated
@@ -1,95 +0,0 @@
|
||||
{
|
||||
"nodes": {
|
||||
"flake-utils": {
|
||||
"locked": {
|
||||
"lastModified": 1648297722,
|
||||
"narHash": "sha256-W+qlPsiZd8F3XkzXOzAoR+mpFqzm3ekQkJNa+PIh1BQ=",
|
||||
"owner": "numtide",
|
||||
"repo": "flake-utils",
|
||||
"rev": "0f8662f1319ad6abf89b3380dd2722369fc51ade",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
"owner": "numtide",
|
||||
"repo": "flake-utils",
|
||||
"rev": "0f8662f1319ad6abf89b3380dd2722369fc51ade",
|
||||
"type": "github"
|
||||
}
|
||||
},
|
||||
"flake-utils_2": {
|
||||
"locked": {
|
||||
"lastModified": 1653893745,
|
||||
"narHash": "sha256-0jntwV3Z8//YwuOjzhV2sgJJPt+HY6KhU7VZUL0fKZQ=",
|
||||
"owner": "numtide",
|
||||
"repo": "flake-utils",
|
||||
"rev": "1ed9fb1935d260de5fe1c2f7ee0ebaae17ed2fa1",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
"owner": "numtide",
|
||||
"repo": "flake-utils",
|
||||
"type": "github"
|
||||
}
|
||||
},
|
||||
"nixpkgs": {
|
||||
"locked": {
|
||||
"lastModified": 1655087213,
|
||||
"narHash": "sha256-4R5oQ+OwGAAcXWYrxC4gFMTUSstGxaN8kN7e8hkum/8=",
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "37b6b161e536fddca54424cf80662bce735bdd1e",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "37b6b161e536fddca54424cf80662bce735bdd1e",
|
||||
"type": "github"
|
||||
}
|
||||
},
|
||||
"nixpkgs_2": {
|
||||
"locked": {
|
||||
"lastModified": 1655046959,
|
||||
"narHash": "sha256-gxqHZKq1ReLDe6ZMJSbmSZlLY95DsVq5o6jQihhzvmw=",
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "07bf3d25ce1da3bee6703657e6a787a4c6cdcea9",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"type": "github"
|
||||
}
|
||||
},
|
||||
"poetry2nix": {
|
||||
"inputs": {
|
||||
"flake-utils": "flake-utils_2",
|
||||
"nixpkgs": "nixpkgs_2"
|
||||
},
|
||||
"locked": {
|
||||
"lastModified": 1654921554,
|
||||
"narHash": "sha256-hkfMdQAHSwLWlg0sBVvgrQdIiBP45U1/ktmFpY4g2Mo=",
|
||||
"owner": "nix-community",
|
||||
"repo": "poetry2nix",
|
||||
"rev": "7b71679fa7df00e1678fc3f1d1d4f5f372341b63",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
"owner": "nix-community",
|
||||
"repo": "poetry2nix",
|
||||
"rev": "7b71679fa7df00e1678fc3f1d1d4f5f372341b63",
|
||||
"type": "github"
|
||||
}
|
||||
},
|
||||
"root": {
|
||||
"inputs": {
|
||||
"flake-utils": "flake-utils",
|
||||
"nixpkgs": "nixpkgs",
|
||||
"poetry2nix": "poetry2nix"
|
||||
}
|
||||
}
|
||||
},
|
||||
"root": "root",
|
||||
"version": 7
|
||||
}
|
||||
63
flake.nix
63
flake.nix
@@ -1,63 +0,0 @@
|
||||
{
|
||||
description = "Application packaged using poetry2nix";
|
||||
|
||||
inputs.flake-utils.url = "github:numtide/flake-utils?rev=0f8662f1319ad6abf89b3380dd2722369fc51ade";
|
||||
inputs.nixpkgs.url = "github:NixOS/nixpkgs?rev=37b6b161e536fddca54424cf80662bce735bdd1e";
|
||||
inputs.poetry2nix.url = "github:nix-community/poetry2nix?rev=7b71679fa7df00e1678fc3f1d1d4f5f372341b63";
|
||||
|
||||
outputs = { self, nixpkgs, flake-utils, poetry2nix }:
|
||||
{
|
||||
# Nixpkgs overlay providing the application
|
||||
overlay = nixpkgs.lib.composeManyExtensions [
|
||||
poetry2nix.overlay
|
||||
(final: prev: {
|
||||
# The application
|
||||
deepdog = prev.poetry2nix.mkPoetryApplication {
|
||||
overrides = final.poetry2nix.overrides.withDefaults (self: super: {
|
||||
# …
|
||||
# workaround https://github.com/nix-community/poetry2nix/issues/568
|
||||
pdme = super.pdme.overridePythonAttrs (old: {
|
||||
buildInputs = old.buildInputs or [ ] ++ [ final.python39.pkgs.poetry-core ];
|
||||
});
|
||||
});
|
||||
projectDir = ./.;
|
||||
};
|
||||
deepdogEnv = prev.poetry2nix.mkPoetryEnv {
|
||||
overrides = final.poetry2nix.overrides.withDefaults (self: super: {
|
||||
# …
|
||||
# workaround https://github.com/nix-community/poetry2nix/issues/568
|
||||
pdme = super.pdme.overridePythonAttrs (old: {
|
||||
buildInputs = old.buildInputs or [ ] ++ [ final.python39.pkgs.poetry-core ];
|
||||
});
|
||||
});
|
||||
projectDir = ./.;
|
||||
};
|
||||
})
|
||||
];
|
||||
} // (flake-utils.lib.eachDefaultSystem (system:
|
||||
let
|
||||
pkgs = import nixpkgs {
|
||||
inherit system;
|
||||
overlays = [ self.overlay ];
|
||||
};
|
||||
in
|
||||
{
|
||||
apps = {
|
||||
deepdog = pkgs.deepdog;
|
||||
};
|
||||
|
||||
defaultApp = pkgs.deepdog;
|
||||
devShell = pkgs.mkShell {
|
||||
buildInputs = [
|
||||
pkgs.poetry
|
||||
pkgs.deepdogEnv
|
||||
pkgs.deepdog
|
||||
];
|
||||
shellHook = ''
|
||||
export DO_NIX_CUSTOM=1
|
||||
'';
|
||||
packages = [ pkgs.nodejs-16_x ];
|
||||
};
|
||||
|
||||
}));
|
||||
}
|
||||
683
poetry.lock
generated
683
poetry.lock
generated
@@ -20,51 +20,26 @@ 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"
|
||||
description = "The uncompromising code formatter."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6.2"
|
||||
|
||||
[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\""}
|
||||
typing-extensions = {version = ">=3.10.0.0", markers = "python_version < \"3.10\""}
|
||||
|
||||
[package.extras]
|
||||
colorama = ["colorama (>=0.4.3)"]
|
||||
d = ["aiohttp (>=3.7.4)"]
|
||||
jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
|
||||
uvloop = ["uvloop (>=0.15.2)"]
|
||||
|
||||
[[package]]
|
||||
name = "bleach"
|
||||
version = "5.0.0"
|
||||
version = "4.1.0"
|
||||
description = "An easy safelist-based HTML-sanitizing tool."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
packaging = "*"
|
||||
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)"]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2022.5.18.1"
|
||||
version = "2021.10.8"
|
||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "cffi"
|
||||
@@ -90,18 +65,18 @@ unicode_backport = ["unicodedata2"]
|
||||
|
||||
[[package]]
|
||||
name = "click"
|
||||
version = "8.1.3"
|
||||
version = "8.0.3"
|
||||
description = "Composable command line interface toolkit"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
colorama = {version = "*", markers = "platform_system == \"Windows\""}
|
||||
|
||||
[[package]]
|
||||
name = "click-log"
|
||||
version = "0.4.0"
|
||||
version = "0.3.2"
|
||||
description = "Logging integration for Click"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -120,21 +95,21 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
|
||||
[[package]]
|
||||
name = "coverage"
|
||||
version = "6.4.2"
|
||||
version = "6.3.2"
|
||||
description = "Code coverage measurement for Python"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.dependencies]
|
||||
tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.11.0a6\" and extra == \"toml\""}
|
||||
tomli = {version = "*", optional = true, markers = "extra == \"toml\""}
|
||||
|
||||
[package.extras]
|
||||
toml = ["tomli"]
|
||||
|
||||
[[package]]
|
||||
name = "cryptography"
|
||||
version = "37.0.2"
|
||||
version = "36.0.1"
|
||||
description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -149,7 +124,7 @@ docstest = ["pyenchant (>=1.6.11)", "twine (>=1.12.0)", "sphinxcontrib-spelling
|
||||
pep8test = ["black", "flake8", "flake8-import-order", "pep8-naming"]
|
||||
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-cov", "pytest-subtests", "pytest-xdist", "pretend", "iso8601", "pytz", "hypothesis (>=1.11.4,!=3.79.2)"]
|
||||
|
||||
[[package]]
|
||||
name = "docutils"
|
||||
@@ -196,7 +171,7 @@ smmap = ">=3.0.1,<6"
|
||||
|
||||
[[package]]
|
||||
name = "gitpython"
|
||||
version = "3.1.27"
|
||||
version = "3.1.26"
|
||||
description = "GitPython is a python library used to interact with Git repositories"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -215,7 +190,7 @@ python-versions = ">=3.5"
|
||||
|
||||
[[package]]
|
||||
name = "importlib-metadata"
|
||||
version = "4.11.4"
|
||||
version = "4.11.0"
|
||||
description = "Read metadata from Python packages"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -225,9 +200,9 @@ python-versions = ">=3.7"
|
||||
zipp = ">=0.5"
|
||||
|
||||
[package.extras]
|
||||
docs = ["sphinx", "jaraco.packaging (>=9)", "rst.linker (>=1.9)"]
|
||||
docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"]
|
||||
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)", "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", "importlib-resources (>=1.3)"]
|
||||
|
||||
[[package]]
|
||||
name = "iniconfig"
|
||||
@@ -239,7 +214,7 @@ python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "invoke"
|
||||
version = "1.7.1"
|
||||
version = "1.6.0"
|
||||
description = "Pythonic task execution"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -247,33 +222,33 @@ python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "jeepney"
|
||||
version = "0.8.0"
|
||||
version = "0.7.1"
|
||||
description = "Low-level, pure Python DBus protocol wrapper."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.extras]
|
||||
test = ["pytest", "pytest-trio", "pytest-asyncio (>=0.17)", "testpath", "trio", "async-timeout"]
|
||||
test = ["pytest", "pytest-trio", "pytest-asyncio", "testpath", "trio", "async-timeout"]
|
||||
trio = ["trio", "async-generator"]
|
||||
|
||||
[[package]]
|
||||
name = "keyring"
|
||||
version = "23.6.0"
|
||||
version = "23.5.0"
|
||||
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 = ">=3.6"
|
||||
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\""}
|
||||
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)"]
|
||||
docs = ["sphinx", "jaraco.packaging (>=8.2)", "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"]
|
||||
|
||||
[[package]]
|
||||
name = "mccabe"
|
||||
@@ -285,7 +260,7 @@ python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "mypy"
|
||||
version = "0.971"
|
||||
version = "0.940"
|
||||
description = "Optional static typing for Python"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -293,7 +268,7 @@ python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
mypy-extensions = ">=0.4.3"
|
||||
tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
|
||||
tomli = ">=1.1.0"
|
||||
typing-extensions = ">=3.10"
|
||||
|
||||
[package.extras]
|
||||
@@ -311,7 +286,7 @@ python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "numpy"
|
||||
version = "1.22.3"
|
||||
version = "1.22.1"
|
||||
description = "NumPy is the fundamental package for array computing with Python."
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -328,48 +303,28 @@ 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"
|
||||
version = "0.5.4"
|
||||
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"
|
||||
numpy = ">=1.21.1,<2.0.0"
|
||||
scipy = ">=1.5,<1.6"
|
||||
|
||||
[[package]]
|
||||
name = "pkginfo"
|
||||
version = "1.8.3"
|
||||
version = "1.8.2"
|
||||
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.*"
|
||||
python-versions = "*"
|
||||
|
||||
[package.extras]
|
||||
testing = ["nose", "coverage"]
|
||||
|
||||
[[package]]
|
||||
name = "platformdirs"
|
||||
version = "2.5.2"
|
||||
description = "A small Python module 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)"]
|
||||
testing = ["coverage", "nose"]
|
||||
|
||||
[[package]]
|
||||
name = "pluggy"
|
||||
@@ -417,30 +372,30 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
|
||||
|
||||
[[package]]
|
||||
name = "pygments"
|
||||
version = "2.12.0"
|
||||
version = "2.11.2"
|
||||
description = "Pygments is a syntax highlighting package written in Python."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.5"
|
||||
|
||||
[[package]]
|
||||
name = "pyparsing"
|
||||
version = "3.0.7"
|
||||
description = "Python parsing module"
|
||||
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"]
|
||||
diagrams = ["jinja2", "railroad-diagrams"]
|
||||
|
||||
[[package]]
|
||||
name = "pytest"
|
||||
version = "7.1.2"
|
||||
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\""}
|
||||
@@ -450,10 +405,10 @@ iniconfig = "*"
|
||||
packaging = "*"
|
||||
pluggy = ">=0.12,<2.0"
|
||||
py = ">=1.8.2"
|
||||
tomli = ">=1.0.0"
|
||||
toml = "*"
|
||||
|
||||
[package.extras]
|
||||
testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"]
|
||||
testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "requests", "xmlschema"]
|
||||
|
||||
[[package]]
|
||||
name = "pytest-cov"
|
||||
@@ -472,23 +427,23 @@ testing = ["fields", "hunter", "process-tests", "six", "pytest-xdist", "virtuale
|
||||
|
||||
[[package]]
|
||||
name = "python-gitlab"
|
||||
version = "3.5.0"
|
||||
version = "2.10.1"
|
||||
description = "Interact with GitLab API"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7.0"
|
||||
python-versions = ">=3.6.0"
|
||||
|
||||
[package.dependencies]
|
||||
requests = ">=2.25.0"
|
||||
requests-toolbelt = ">=0.9.1"
|
||||
|
||||
[package.extras]
|
||||
autocompletion = ["argcomplete (>=1.10.0,<3)"]
|
||||
autocompletion = ["argcomplete (>=1.10.0,<2)"]
|
||||
yaml = ["PyYaml (>=5.2)"]
|
||||
|
||||
[[package]]
|
||||
name = "python-semantic-release"
|
||||
version = "7.29.1"
|
||||
version = "7.24.0"
|
||||
description = "Automatic Semantic Versioning for Python projects"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -500,15 +455,15 @@ click-log = ">=0.3,<1"
|
||||
dotty-dict = ">=1.3.0,<2"
|
||||
gitpython = ">=3.0.8,<4"
|
||||
invoke = ">=1.4.1,<2"
|
||||
python-gitlab = ">=2,<4"
|
||||
python-gitlab = ">=1.10,<3"
|
||||
requests = ">=2.25,<3"
|
||||
semver = ">=2.10,<3"
|
||||
tomlkit = ">=0.10.0,<0.11.0"
|
||||
tomlkit = "0.7.0"
|
||||
twine = ">=3,<4"
|
||||
|
||||
[package.extras]
|
||||
dev = ["tox", "isort", "black"]
|
||||
docs = ["Sphinx (==1.3.6)", "Jinja2 (==3.0.3)"]
|
||||
docs = ["Sphinx (==1.3.6)"]
|
||||
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)"]
|
||||
|
||||
@@ -522,11 +477,11 @@ python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "readme-renderer"
|
||||
version = "35.0"
|
||||
version = "32.0"
|
||||
description = "readme_renderer is a library for rendering \"readme\" descriptions for Warehouse"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
bleach = ">=2.1.0"
|
||||
@@ -534,24 +489,24 @@ docutils = ">=0.13.1"
|
||||
Pygments = ">=2.5.1"
|
||||
|
||||
[package.extras]
|
||||
md = ["cmarkgfm (>=0.8.0)"]
|
||||
md = ["cmarkgfm (>=0.5.0,<0.7.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.28.0"
|
||||
version = "2.27.1"
|
||||
description = "Python HTTP for Humans."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7, <4"
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
|
||||
|
||||
[package.dependencies]
|
||||
certifi = ">=2017.4.17"
|
||||
charset-normalizer = ">=2.0.0,<2.1.0"
|
||||
idna = ">=2.5,<4"
|
||||
charset-normalizer = {version = ">=2.0.0,<2.1.0", markers = "python_version >= \"3\""}
|
||||
idna = {version = ">=2.5,<4", markers = "python_version >= \"3\""}
|
||||
urllib3 = ">=1.21.1,<1.27"
|
||||
|
||||
[package.extras]
|
||||
socks = ["PySocks (>=1.5.6,!=1.5.7)"]
|
||||
socks = ["PySocks (>=1.5.6,!=1.5.7)", "win-inet-pton"]
|
||||
use_chardet_on_py3 = ["chardet (>=3.0.2,<5)"]
|
||||
|
||||
[[package]]
|
||||
@@ -578,18 +533,18 @@ idna2008 = ["idna"]
|
||||
|
||||
[[package]]
|
||||
name = "scipy"
|
||||
version = "1.8.0"
|
||||
version = "1.5.4"
|
||||
description = "SciPy: Scientific Library for Python"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.8,<3.11"
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
numpy = ">=1.17.3,<1.25.0"
|
||||
numpy = ">=1.14.5"
|
||||
|
||||
[[package]]
|
||||
name = "secretstorage"
|
||||
version = "3.3.2"
|
||||
version = "3.3.1"
|
||||
description = "Python bindings to FreeDesktop.org Secret Service API"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -639,9 +594,17 @@ category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[[package]]
|
||||
name = "toml"
|
||||
version = "0.10.2"
|
||||
description = "Python Library for Tom's Obvious, Minimal Language"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
|
||||
|
||||
[[package]]
|
||||
name = "tomli"
|
||||
version = "2.0.1"
|
||||
version = "2.0.0"
|
||||
description = "A lil' TOML parser"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -649,15 +612,15 @@ python-versions = ">=3.7"
|
||||
|
||||
[[package]]
|
||||
name = "tomlkit"
|
||||
version = "0.10.2"
|
||||
version = "0.7.0"
|
||||
description = "Style preserving TOML library"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6,<4.0"
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
|
||||
[[package]]
|
||||
name = "tqdm"
|
||||
version = "4.64.0"
|
||||
version = "4.62.3"
|
||||
description = "Fast, Extensible Progress Meter"
|
||||
category = "dev"
|
||||
optional = false
|
||||
@@ -669,7 +632,6 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
|
||||
[package.extras]
|
||||
dev = ["py-make (>=0.1.0)", "twine", "wheel"]
|
||||
notebook = ["ipywidgets (>=6)"]
|
||||
slack = ["slack-sdk"]
|
||||
telegram = ["requests"]
|
||||
|
||||
[[package]]
|
||||
@@ -694,22 +656,22 @@ urllib3 = ">=1.26.0"
|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.2.0"
|
||||
description = "Backported and Experimental Type Hints for Python 3.7+"
|
||||
version = "4.0.1"
|
||||
description = "Backported and Experimental Type Hints for Python 3.6+"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[[package]]
|
||||
name = "urllib3"
|
||||
version = "1.26.9"
|
||||
version = "1.26.8"
|
||||
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"
|
||||
|
||||
[package.extras]
|
||||
brotli = ["brotlicffi (>=0.8.0)", "brotli (>=1.0.9)", "brotlipy (>=0.6.0)"]
|
||||
brotli = ["brotlipy (>=0.6.0)"]
|
||||
secure = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "certifi", "ipaddress"]
|
||||
socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
|
||||
|
||||
@@ -723,81 +685,428 @@ python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.8.0"
|
||||
version = "3.7.0"
|
||||
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", "jaraco.packaging (>=8.2)", "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"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "1.1"
|
||||
python-versions = "^3.8,<3.10"
|
||||
content-hash = "1e52cabf54af905e05d979683b28779e59690cf38ad4f805dbbf455b19d0a337"
|
||||
content-hash = "ac69ab9be2cde12f64be445f46af378b6943d3c19cbf9fd3e1b6b81371c7a5a6"
|
||||
|
||||
[metadata.files]
|
||||
atomicwrites = []
|
||||
attrs = []
|
||||
black = []
|
||||
bleach = []
|
||||
certifi = []
|
||||
cffi = []
|
||||
charset-normalizer = []
|
||||
click = []
|
||||
click-log = []
|
||||
colorama = []
|
||||
coverage = []
|
||||
cryptography = []
|
||||
docutils = []
|
||||
dotty-dict = []
|
||||
flake8 = []
|
||||
gitdb = []
|
||||
gitpython = []
|
||||
idna = []
|
||||
importlib-metadata = []
|
||||
iniconfig = []
|
||||
invoke = []
|
||||
jeepney = []
|
||||
keyring = []
|
||||
mccabe = []
|
||||
mypy = []
|
||||
mypy-extensions = []
|
||||
numpy = []
|
||||
packaging = []
|
||||
pathspec = []
|
||||
pdme = []
|
||||
pkginfo = []
|
||||
platformdirs = []
|
||||
pluggy = []
|
||||
py = []
|
||||
pycodestyle = []
|
||||
pycparser = []
|
||||
pyflakes = []
|
||||
pygments = []
|
||||
pyparsing = []
|
||||
pytest = []
|
||||
pytest-cov = []
|
||||
python-gitlab = []
|
||||
python-semantic-release = []
|
||||
pywin32-ctypes = []
|
||||
readme-renderer = []
|
||||
requests = []
|
||||
requests-toolbelt = []
|
||||
rfc3986 = []
|
||||
scipy = []
|
||||
secretstorage = []
|
||||
semver = []
|
||||
setuptools-scm = []
|
||||
six = []
|
||||
smmap = []
|
||||
tomli = []
|
||||
tomlkit = []
|
||||
tqdm = []
|
||||
twine = []
|
||||
typing-extensions = []
|
||||
urllib3 = []
|
||||
webencodings = []
|
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{file = "smmap-5.0.0.tar.gz", hash = "sha256:c840e62059cd3be204b0c9c9f74be2c09d5648eddd4580d9314c3ecde0b30936"},
|
||||
]
|
||||
toml = [
|
||||
{file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
|
||||
{file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
|
||||
]
|
||||
tomli = [
|
||||
{file = "tomli-2.0.0-py3-none-any.whl", hash = "sha256:b5bde28da1fed24b9bd1d4d2b8cba62300bfb4ec9a6187a957e8ddb9434c5224"},
|
||||
{file = "tomli-2.0.0.tar.gz", hash = "sha256:c292c34f58502a1eb2bbb9f5bbc9a5ebc37bee10ffb8c2d6bbdfa8eb13cc14e1"},
|
||||
]
|
||||
tomlkit = [
|
||||
{file = "tomlkit-0.7.0-py2.py3-none-any.whl", hash = "sha256:6babbd33b17d5c9691896b0e68159215a9387ebfa938aa3ac42f4a4beeb2b831"},
|
||||
{file = "tomlkit-0.7.0.tar.gz", hash = "sha256:ac57f29693fab3e309ea789252fcce3061e19110085aa31af5446ca749325618"},
|
||||
]
|
||||
tqdm = [
|
||||
{file = "tqdm-4.62.3-py2.py3-none-any.whl", hash = "sha256:8dd278a422499cd6b727e6ae4061c40b48fce8b76d1ccbf5d34fca9b7f925b0c"},
|
||||
{file = "tqdm-4.62.3.tar.gz", hash = "sha256:d359de7217506c9851b7869f3708d8ee53ed70a1b8edbba4dbcb47442592920d"},
|
||||
]
|
||||
twine = [
|
||||
{file = "twine-3.8.0-py3-none-any.whl", hash = "sha256:d0550fca9dc19f3d5e8eadfce0c227294df0a2a951251a4385797c8a6198b7c8"},
|
||||
{file = "twine-3.8.0.tar.gz", hash = "sha256:8efa52658e0ae770686a13b675569328f1fba9837e5de1867bfe5f46a9aefe19"},
|
||||
]
|
||||
typing-extensions = [
|
||||
{file = "typing_extensions-4.0.1-py3-none-any.whl", hash = "sha256:7f001e5ac290a0c0401508864c7ec868be4e701886d5b573a9528ed3973d9d3b"},
|
||||
{file = "typing_extensions-4.0.1.tar.gz", hash = "sha256:4ca091dea149f945ec56afb48dae714f21e8692ef22a395223bcd328961b6a0e"},
|
||||
]
|
||||
urllib3 = [
|
||||
{file = "urllib3-1.26.8-py2.py3-none-any.whl", hash = "sha256:000ca7f471a233c2251c6c7023ee85305721bfdf18621ebff4fd17a8653427ed"},
|
||||
{file = "urllib3-1.26.8.tar.gz", hash = "sha256:0e7c33d9a63e7ddfcb86780aac87befc2fbddf46c58dbb487e0855f7ceec283c"},
|
||||
]
|
||||
webencodings = [
|
||||
{file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
|
||||
{file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
|
||||
]
|
||||
zipp = [
|
||||
{file = "zipp-3.7.0-py3-none-any.whl", hash = "sha256:b47250dd24f92b7dd6a0a8fc5244da14608f3ca90a5efcd37a3b1642fac9a375"},
|
||||
{file = "zipp-3.7.0.tar.gz", hash = "sha256:9f50f446828eb9d45b267433fd3e9da8d801f614129124863f9c51ebceafb87d"},
|
||||
]
|
||||
|
||||
@@ -1,22 +1,19 @@
|
||||
[tool.poetry]
|
||||
name = "deepdog"
|
||||
version = "0.6.4"
|
||||
version = "0.3.5"
|
||||
description = ""
|
||||
authors = ["Deepak Mallubhotla <dmallubhotla+github@gmail.com>"]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8,<3.10"
|
||||
pdme = "^0.8.6"
|
||||
numpy = "1.22.3"
|
||||
scipy = "1.10.1"
|
||||
pdme = "^0.5.4"
|
||||
|
||||
[tool.poetry.dev-dependencies]
|
||||
pytest = ">=6"
|
||||
flake8 = "^4.0.1"
|
||||
pytest-cov = "^3.0.0"
|
||||
mypy = "^0.971"
|
||||
mypy = "^0.940"
|
||||
python-semantic-release = "^7.24.0"
|
||||
black = "^22.3.0"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core>=1.0.0"]
|
||||
|
||||
Reference in New Issue
Block a user