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feat: Adds monte carlo cycles to trade off space and cpu

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This commit is contained in:
Deepak Mallubhotla 2022-03-06 17:18:24 -06:00
parent e00dc95f02
commit e6d8d33c27
Signed by: deepak
GPG Key ID: BEBAEBF28083E022
1 changed files with 14 additions and 4 deletions
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18
deepdog/alt_bayes_run.py
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@ -4,6 +4,7 @@ import pdme.util.fast_v_calc
from typing import Sequence, Tuple, List
import datetime
import csv
import multiprocessing
import logging
import numpy
@ -19,6 +20,13 @@ DotInput = Tuple[numpy.typing.ArrayLike, float]
_logger = logging.getLogger(__name__)
def get_a_result(input) -> int:
discretisation, dot_inputs, lows, highs, monte_carlo_count, max_frequency = input
sample_dipoles = discretisation.get_model().get_n_single_dipoles(monte_carlo_count, max_frequency)
vals = pdme.util.fast_v_calc.fast_vs_for_dipoles(dot_inputs, sample_dipoles)
return numpy.count_nonzero(pdme.util.fast_v_calc.between(vals, lows, highs))
class AltBayesRun():
'''
A single Bayes run for a given set of dots.
@ -36,7 +44,7 @@ class AltBayesRun():
run_count: int
The number of runs to do.
'''
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, max_frequency: float = 20, end_threshold: float = None) -> None:
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:
self.dot_inputs = dot_inputs
self.dot_inputs_array = pdme.measurement.oscillating_dipole.dot_inputs_to_array(dot_inputs)
self.discretisations = [disc for (_, disc) in discretisations_with_names]
@ -44,6 +52,7 @@ class AltBayesRun():
self.actual_model = actual_model
self.model_count = len(self.discretisations)
self.monte_carlo_count = monte_carlo_count
self.monte_carlo_cycles = monte_carlo_cycles
self.run_count = run_count
self.low_error = low_error
self.high_error = high_error
@ -87,9 +96,10 @@ class AltBayesRun():
_logger.debug("Going to iterate over discretisations now")
for disc_count, discretisation in enumerate(self.discretisations):
_logger.debug(f"Doing discretisation #{disc_count}")
sample_dipoles = discretisation.get_model().get_n_single_dipoles(self.monte_carlo_count, self.max_frequency)
vals = pdme.util.fast_v_calc.fast_vs_for_dipoles(self.dot_inputs_array, sample_dipoles)
results.append(numpy.count_nonzero(pdme.util.fast_v_calc.between(vals, lows, highs)))
with multiprocessing.Pool(multiprocessing.cpu_count() - 1 or 1) as pool:
results.append(sum(
pool.imap_unordered(get_a_result, [(discretisation, self.dot_inputs_array, lows, highs, self.monte_carlo_count, self.max_frequency)] * self.monte_carlo_cycles)
))
_logger.debug("Done, constructing output now")
row = {