deepdog/deepdog/diagnostic.py

98 lines
3.6 KiB
Python

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]
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", "actual_dipole_freq", "success", "p_result_x", "p_result_y", "p_result_z", "s_result_x", "s_result_y", "s_result_z"]
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')
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), actual_success)
row = vars(diag_row)
_logger.debug(f"Writing result {row}")
writer.writerow(row)