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24
CHANGELOG.md
24
CHANGELOG.md
@@ -2,6 +2,30 @@
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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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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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## [0.4.0](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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### Features
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* makes chunksize configurable ([88d9613](https://gitea.deepak.science:2222/physics/deepdog/commit/88d961313c1db0d49fd96939aa725a8706fa0412))
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### [0.3.4](https://gitea.deepak.science:2222/physics/deepdog/compare/0.3.3...0.3.4) (2022-03-06)
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### [0.3.4](https://gitea.deepak.science:2222/physics/deepdog/compare/0.3.3...0.3.4) (2022-03-06)
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@@ -1,6 +1,9 @@
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import pdme.inputs
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import pdme.model
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import pdme.model
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import pdme.measurement.input_types
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import pdme.measurement.oscillating_dipole
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import pdme.measurement.oscillating_dipole
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import pdme.util.fast_v_calc
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import pdme.util.fast_v_calc
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import pdme.util.fast_nonlocal_spectrum
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from typing import Sequence, Tuple, List
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from typing import Sequence, Tuple, List
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import datetime
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import datetime
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import csv
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import csv
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@@ -10,7 +13,7 @@ import numpy
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# TODO: remove hardcode
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# TODO: remove hardcode
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CHUNKSIZE = 20
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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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# 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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DotInput = Tuple[numpy.typing.ArrayLike, float]
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@@ -26,6 +29,17 @@ def get_a_result(input) -> int:
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return numpy.count_nonzero(pdme.util.fast_v_calc.between(vals, lows, highs))
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return numpy.count_nonzero(pdme.util.fast_v_calc.between(vals, lows, highs))
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def get_a_result_using_pairs(input) -> int:
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discretisation, dot_inputs, pair_inputs, local_lows, local_highs, nonlocal_lows, nonlocal_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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local_vals = pdme.util.fast_v_calc.fast_vs_for_dipoles(dot_inputs, sample_dipoles)
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local_matches = pdme.util.fast_v_calc.between(local_vals, local_lows, local_highs)
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nonlocal_vals = pdme.util.fast_nonlocal_spectrum.fast_s_nonlocal(pair_inputs, sample_dipoles)
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nonlocal_matches = pdme.util.fast_v_calc.between(nonlocal_vals, nonlocal_lows, nonlocal_highs)
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combined_matches = numpy.logical_and(local_matches, nonlocal_matches)
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return numpy.count_nonzero(combined_matches)
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class AltBayesRun():
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class AltBayesRun():
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'''
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'''
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A single Bayes run for a given set of dots.
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A single Bayes run for a given set of dots.
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@@ -43,26 +57,46 @@ class AltBayesRun():
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run_count: int
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run_count: int
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The number of runs to do.
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The number of runs to do.
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'''
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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) -> None:
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def __init__(self, dot_positions: Sequence[numpy.typing.ArrayLike], frequency_range: Sequence[float], discretisations_with_names: Sequence[Tuple[str, pdme.model.Discretisation]], actual_model: pdme.model.Model, 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, use_pairs: bool = False) -> None:
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self.dot_inputs = dot_inputs
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self.dot_inputs = pdme.inputs.inputs_with_frequency_range(dot_positions, frequency_range)
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self.dot_inputs_array = pdme.measurement.oscillating_dipole.dot_inputs_to_array(dot_inputs)
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self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(self.dot_inputs)
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self.use_pairs = use_pairs
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self.dot_pair_inputs = pdme.inputs.input_pairs_with_frequency_range(dot_positions, frequency_range)
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self.dot_pair_inputs_array = pdme.measurement.input_types.dot_pair_inputs_to_array(self.dot_pair_inputs)
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self.discretisations = [disc for (_, disc) in discretisations_with_names]
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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.model_names = [name for (name, _) in discretisations_with_names]
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self.actual_model = actual_model
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self.actual_model = actual_model
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self.model_count = len(self.discretisations)
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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_count = monte_carlo_count
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self.monte_carlo_cycles = monte_carlo_cycles
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self.monte_carlo_cycles = monte_carlo_cycles
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self.target_success = target_success
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self.max_monte_carlo_cycles_steps = max_monte_carlo_cycles_steps
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self.run_count = run_count
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self.run_count = run_count
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self.low_error = low_error
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self.low_error = low_error
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self.high_error = high_error
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self.high_error = high_error
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if pairs_low_error is None:
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self.pairs_low_error = self.low_error
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else:
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self.pairs_low_error = pairs_low_error
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if pairs_high_error is None:
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self.pairs_high_error = self.high_error
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else:
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self.pairs_high_error = pairs_high_error
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self.csv_fields = ["dipole_moment", "dipole_location", "dipole_frequency"]
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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.compensate_zeros = True
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self.chunksize = chunksize
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for name in self.model_names:
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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.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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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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timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
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if self.use_pairs:
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self.filename = f"{timestamp}-{filename_slug}.altbayes.pairs.csv"
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else:
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self.filename = f"{timestamp}-{filename_slug}.altbayes.csv"
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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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self.max_frequency = max_frequency
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@@ -88,7 +122,13 @@ class AltBayesRun():
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actual_dipoles = self.actual_model.get_dipoles(frequency)
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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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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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lows, highs = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(dots)
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pair_lows, pair_highs = (None, None)
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if self.use_pairs:
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pair_measurements = actual_dipoles.get_percent_range_dot_pair_measurements(self.dot_pair_inputs, self.pairs_low_error, self.pairs_high_error)
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pair_lows, pair_highs = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(pair_measurements)
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_logger.info(f"Going to work on dipole at {actual_dipoles.dipoles}")
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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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results = []
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@@ -96,9 +136,25 @@ class AltBayesRun():
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for disc_count, discretisation in enumerate(self.discretisations):
|
for disc_count, discretisation in enumerate(self.discretisations):
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_logger.debug(f"Doing discretisation #{disc_count}")
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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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with multiprocessing.Pool(multiprocessing.cpu_count() - 1 or 1) as pool:
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results.append(sum(
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cycle_count = 0
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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, CHUNKSIZE)
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cycle_success = 0
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))
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cycles = 0
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while (cycles < self.max_monte_carlo_cycles_steps) and (cycle_success <= self.target_success):
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_logger.debug(f"Starting cycle {cycles}")
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cycles += 1
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current_success = 0
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cycle_count += self.monte_carlo_count * self.monte_carlo_cycles
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if self.use_pairs:
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current_success = sum(
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pool.imap_unordered(get_a_result_using_pairs, [(discretisation, self.dot_inputs_array, self.dot_pair_inputs_array, lows, highs, pair_lows, pair_highs, self.monte_carlo_count, self.max_frequency)] * self.monte_carlo_cycles, self.chunksize)
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)
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else:
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current_success = 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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cycle_success += current_success
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results.append((cycle_count, cycle_success))
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_logger.debug("Done, constructing output now")
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_logger.debug("Done, constructing output now")
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row = {
|
row = {
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@@ -108,12 +164,12 @@ class AltBayesRun():
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}
|
}
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successes: List[float] = []
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successes: List[float] = []
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counts: List[int] = []
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counts: List[int] = []
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for model_index, (name, result) in enumerate(zip(self.model_names, results)):
|
for model_index, (name, (count, result)) in enumerate(zip(self.model_names, results)):
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row[f"{name}_success"] = result
|
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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row[f"{name}_count"] = count
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successes.append(max(result, 0.5))
|
successes.append(max(result, 0.5))
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counts.append(self.monte_carlo_count * self.monte_carlo_cycles)
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counts.append(count)
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success_weight = sum([(succ / count) * prob for succ, count, prob in zip(successes, counts, self.probabilities)])
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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)]
|
new_probabilities = [(succ / count) * old_prob / success_weight for succ, count, old_prob in zip(successes, counts, self.probabilities)]
|
||||||
|
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110
poetry.lock
generated
110
poetry.lock
generated
@@ -260,7 +260,7 @@ python-versions = "*"
|
|||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "mypy"
|
name = "mypy"
|
||||||
version = "0.931"
|
version = "0.942"
|
||||||
description = "Optional static typing for Python"
|
description = "Optional static typing for Python"
|
||||||
category = "dev"
|
category = "dev"
|
||||||
optional = false
|
optional = false
|
||||||
@@ -274,6 +274,7 @@ typing-extensions = ">=3.10"
|
|||||||
[package.extras]
|
[package.extras]
|
||||||
dmypy = ["psutil (>=4.0)"]
|
dmypy = ["psutil (>=4.0)"]
|
||||||
python2 = ["typed-ast (>=1.4.0,<2)"]
|
python2 = ["typed-ast (>=1.4.0,<2)"]
|
||||||
|
reports = ["lxml"]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "mypy-extensions"
|
name = "mypy-extensions"
|
||||||
@@ -304,7 +305,7 @@ pyparsing = ">=2.0.2,<3.0.5 || >3.0.5"
|
|||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "pdme"
|
name = "pdme"
|
||||||
version = "0.5.4"
|
version = "0.6.1"
|
||||||
description = "Python dipole model evaluator"
|
description = "Python dipole model evaluator"
|
||||||
category = "main"
|
category = "main"
|
||||||
optional = false
|
optional = false
|
||||||
@@ -312,7 +313,7 @@ python-versions = ">=3.8,<3.10"
|
|||||||
|
|
||||||
[package.dependencies]
|
[package.dependencies]
|
||||||
numpy = ">=1.21.1,<2.0.0"
|
numpy = ">=1.21.1,<2.0.0"
|
||||||
scipy = ">=1.5,<1.6"
|
scipy = ">=1.8,<1.9"
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "pkginfo"
|
name = "pkginfo"
|
||||||
@@ -532,14 +533,14 @@ idna2008 = ["idna"]
|
|||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "scipy"
|
name = "scipy"
|
||||||
version = "1.5.4"
|
version = "1.8.0"
|
||||||
description = "SciPy: Scientific Library for Python"
|
description = "SciPy: Scientific Library for Python"
|
||||||
category = "main"
|
category = "main"
|
||||||
optional = false
|
optional = false
|
||||||
python-versions = ">=3.6"
|
python-versions = ">=3.8,<3.11"
|
||||||
|
|
||||||
[package.dependencies]
|
[package.dependencies]
|
||||||
numpy = ">=1.14.5"
|
numpy = ">=1.17.3,<1.25.0"
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "secretstorage"
|
name = "secretstorage"
|
||||||
@@ -697,7 +698,7 @@ testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-
|
|||||||
[metadata]
|
[metadata]
|
||||||
lock-version = "1.1"
|
lock-version = "1.1"
|
||||||
python-versions = "^3.8,<3.10"
|
python-versions = "^3.8,<3.10"
|
||||||
content-hash = "ba794e6f69d42e44e2b1abc40731fd78d2f417cdc9be12d6e752dbcfa95adaad"
|
content-hash = "2911e2f292dbc9f6a87bfbb0b534695e2f0ae1e1a260aecca10955e685d6f846"
|
||||||
|
|
||||||
[metadata.files]
|
[metadata.files]
|
||||||
atomicwrites = [
|
atomicwrites = [
|
||||||
@@ -898,26 +899,29 @@ mccabe = [
|
|||||||
{file = "mccabe-0.6.1.tar.gz", hash = "sha256:dd8d182285a0fe56bace7f45b5e7d1a6ebcbf524e8f3bd87eb0f125271b8831f"},
|
{file = "mccabe-0.6.1.tar.gz", hash = "sha256:dd8d182285a0fe56bace7f45b5e7d1a6ebcbf524e8f3bd87eb0f125271b8831f"},
|
||||||
]
|
]
|
||||||
mypy = [
|
mypy = [
|
||||||
{file = "mypy-0.931-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:3c5b42d0815e15518b1f0990cff7a705805961613e701db60387e6fb663fe78a"},
|
{file = "mypy-0.942-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5bf44840fb43ac4074636fd47ee476d73f0039f4f54e86d7265077dc199be24d"},
|
||||||
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{file = "scipy-1.5.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3d5db5d815370c28d938cf9b0809dade4acf7aba57eaf7ef733bfedc9b2474c4"},
|
{file = "scipy-1.8.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e6f0cd9c0bd374ef834ee1e0f0999678d49dcc400ea6209113d81528958f97c7"},
|
||||||
{file = "scipy-1.5.4-cp39-cp39-manylinux1_i686.whl", hash = "sha256:6b0ceb23560f46dd236a8ad4378fc40bad1783e997604ba845e131d6c680963e"},
|
{file = "scipy-1.8.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f3720d0124aced49f6f2198a6900304411dbbeed12f56951d7c66ebef05e3df6"},
|
||||||
{file = "scipy-1.5.4-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:ed572470af2438b526ea574ff8f05e7f39b44ac37f712105e57fc4d53a6fb660"},
|
{file = "scipy-1.8.0-cp39-cp39-win32.whl", hash = "sha256:3d573228c10a3a8c32b9037be982e6440e411b443a6267b067cac72f690b8d56"},
|
||||||
{file = "scipy-1.5.4-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:8c8d6ca19c8497344b810b0b0344f8375af5f6bb9c98bd42e33f747417ab3f57"},
|
{file = "scipy-1.8.0-cp39-cp39-win_amd64.whl", hash = "sha256:bb7088e89cd751acf66195d2f00cf009a1ea113f3019664032d9075b1e727b6c"},
|
||||||
{file = "scipy-1.5.4-cp39-cp39-win32.whl", hash = "sha256:d84cadd7d7998433334c99fa55bcba0d8b4aeff0edb123b2a1dfcface538e474"},
|
{file = "scipy-1.8.0.tar.gz", hash = "sha256:31d4f2d6b724bc9a98e527b5849b8a7e589bf1ea630c33aa563eda912c9ff0bd"},
|
||||||
{file = "scipy-1.5.4-cp39-cp39-win_amd64.whl", hash = "sha256:cc1f78ebc982cd0602c9a7615d878396bec94908db67d4ecddca864d049112f2"},
|
|
||||||
{file = "scipy-1.5.4.tar.gz", hash = "sha256:4a453d5e5689de62e5d38edf40af3f17560bfd63c9c5bd228c18c1f99afa155b"},
|
|
||||||
]
|
]
|
||||||
secretstorage = [
|
secretstorage = [
|
||||||
{file = "SecretStorage-3.3.1-py3-none-any.whl", hash = "sha256:422d82c36172d88d6a0ed5afdec956514b189ddbfb72fefab0c8a1cee4eaf71f"},
|
{file = "SecretStorage-3.3.1-py3-none-any.whl", hash = "sha256:422d82c36172d88d6a0ed5afdec956514b189ddbfb72fefab0c8a1cee4eaf71f"},
|
||||||
|
|||||||
@@ -1,18 +1,18 @@
|
|||||||
[tool.poetry]
|
[tool.poetry]
|
||||||
name = "deepdog"
|
name = "deepdog"
|
||||||
version = "0.3.4"
|
version = "0.4.0"
|
||||||
description = ""
|
description = ""
|
||||||
authors = ["Deepak Mallubhotla <dmallubhotla+github@gmail.com>"]
|
authors = ["Deepak Mallubhotla <dmallubhotla+github@gmail.com>"]
|
||||||
|
|
||||||
[tool.poetry.dependencies]
|
[tool.poetry.dependencies]
|
||||||
python = "^3.8,<3.10"
|
python = "^3.8,<3.10"
|
||||||
pdme = "^0.5.4"
|
pdme = "^0.6.1"
|
||||||
|
|
||||||
[tool.poetry.dev-dependencies]
|
[tool.poetry.dev-dependencies]
|
||||||
pytest = ">=6"
|
pytest = ">=6"
|
||||||
flake8 = "^4.0.1"
|
flake8 = "^4.0.1"
|
||||||
pytest-cov = "^3.0.0"
|
pytest-cov = "^3.0.0"
|
||||||
mypy = "^0.931"
|
mypy = "^0.942"
|
||||||
python-semantic-release = "^7.24.0"
|
python-semantic-release = "^7.24.0"
|
||||||
|
|
||||||
[build-system]
|
[build-system]
|
||||||
|
|||||||
Reference in New Issue
Block a user