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Clean up governing_method and method in CandidateSpaces #73

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Jan 3, 2024
Merged

Clean up governing_method and method in CandidateSpaces #73

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ef50d0a
use governing_method as class attribute only, use method as instance …
dilpath Dec 17, 2023
37f9723
reorder
dilpath Dec 17, 2023
ad78660
remove governing_method
dilpath Dec 17, 2023
6d894b5
remove governing_method from ui
dilpath Dec 17, 2023
12079b2
typo
dilpath Dec 17, 2023
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82 changes: 39 additions & 43 deletions petab_select/candidate_space.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,10 +69,6 @@ class CandidateSpace(abc.ABC):
An example of a difference is in the bidirectional method, where ``governing_method``
stores the bidirectional method, whereas `method` may also store the forward or
backward methods.
retry_model_space_search_if_no_models:
Whether a search with a candidate space should be repeated upon failure.
Useful for the :class:`BidirectionalCandidateSpace`, which switches directions
upon failure.
summary_tsv:
A string or :class:`pathlib.Path`. A summary of the model selection progress
will be written to this file.
Expand All @@ -84,26 +80,22 @@ class CandidateSpace(abc.ABC):
# Models will fail `self.consider` if `len(self.models) >= limit`.
"""

governing_method: Method = None
method: Method = None
retry_model_space_search_if_no_models: bool = False

def __init__(
self,
method: Method,
# TODO add MODEL_TYPE = Union[str, Model], str for VIRTUAL_INITIAL_MODEL
predecessor_model: Optional[Model] = None,
exclusions: Optional[List[Any]] = None,
limit: TYPE_LIMIT = np.inf,
summary_tsv: TYPE_PATH = None,
previous_predecessor_model: Optional[Model] = None,
):
self.method = method

self.limit = LimitHandler(
current=self.n_accepted,
limit=limit,
)
# Each candidate class specifies this as a class attribute.
if self.governing_method is None:
self.governing_method = self.method
self.reset(predecessor_model=predecessor_model, exclusions=exclusions)

self.summary_tsv = summary_tsv
Expand Down Expand Up @@ -133,10 +125,7 @@ def write_summary_tsv(self, row):
def _setup_summary_tsv(self):
self.summary_tsv.resolve().parent.mkdir(parents=True, exist_ok=True)

if self.summary_tsv.exists():
with open(self.summary_tsv, "r", encoding="utf-8") as f:
last_row = f.readlines()[-1]
else:
if not self.summary_tsv.exists():
self.write_summary_tsv(
[
'method',
Expand Down Expand Up @@ -500,7 +489,6 @@ class ForwardCandidateSpace(CandidateSpace):
Defaults to no maximum (``None``).
"""

method = Method.FORWARD
direction = 1

def __init__(
Expand All @@ -516,7 +504,12 @@ def __init__(
self.max_steps = max_steps
if predecessor_model is None:
predecessor_model = VIRTUAL_INITIAL_MODEL
super().__init__(*args, predecessor_model=predecessor_model, **kwargs)
super().__init__(
method=Method.FORWARD if self.direction == 1 else Method.BACKWARD,
*args,
predecessor_model=predecessor_model,
**kwargs,
)

def is_plausible(self, model: Model) -> bool:
distances = self.distances_in_estimated_parameters(model)
Expand Down Expand Up @@ -565,7 +558,6 @@ def _consider_method(self, model) -> bool:
class BackwardCandidateSpace(ForwardCandidateSpace):
"""The backward method class."""

method = Method.BACKWARD
direction = -1


Expand Down Expand Up @@ -604,7 +596,6 @@ class FamosCandidateSpace(CandidateSpace):
be applied after one lateral move.
"""

method = Method.FAMOS
default_method_scheme = {
(Method.BACKWARD, Method.FORWARD): Method.LATERAL,
(Method.FORWARD, Method.BACKWARD): Method.LATERAL,
Expand Down Expand Up @@ -722,9 +713,12 @@ def __init__(
self.initial_method
]

super().__init__(*args, predecessor_model=predecessor_model, **kwargs)

self.governing_method = Method.FAMOS
super().__init__(
method=self.method,
*args,
predecessor_model=predecessor_model,
**kwargs,
)

self.n_reattempts = n_reattempts

Expand Down Expand Up @@ -1176,8 +1170,6 @@ def wrapper():
class LateralCandidateSpace(CandidateSpace):
"""Find models with the same number of estimated parameters."""

method = Method.LATERAL

def __init__(
self,
*args,
Expand All @@ -1191,6 +1183,7 @@ def __init__(
Maximal allowed number of swap moves. If 0 then there is no maximum.
"""
super().__init__(
method=Method.LATERAL,
*args,
predecessor_model=predecessor_model,
**kwargs,
Expand Down Expand Up @@ -1233,8 +1226,6 @@ def _consider_method(self, model):
class BruteForceCandidateSpace(CandidateSpace):
"""The brute-force method class."""

method = Method.BRUTE_FORCE

def __init__(self, *args, **kwargs):
# if args or kwargs:
# # FIXME remove?
Expand All @@ -1243,38 +1234,43 @@ def __init__(self, *args, **kwargs):
# 'Arguments were provided but will be ignored, because of the '
# 'brute force candidate space.'
# )
super().__init__(*args, **kwargs)
super().__init__(
method=Method.BRUTE_FORCE,
*args,
**kwargs,
)

def _consider_method(self, model):
return True


candidate_space_classes = [
ForwardCandidateSpace,
BackwardCandidateSpace,
LateralCandidateSpace,
BruteForceCandidateSpace,
FamosCandidateSpace,
]
candidate_space_classes = {
Method.FORWARD: ForwardCandidateSpace,
Method.BACKWARD: BackwardCandidateSpace,
Method.LATERAL: LateralCandidateSpace,
Method.BRUTE_FORCE: BruteForceCandidateSpace,
Method.FAMOS: FamosCandidateSpace,
}


def method_to_candidate_space_class(method: Method) -> Type[CandidateSpace]:
"""Instantiate a candidate space given its method name.
"""Get a candidate space class, given its method name.

Args:
method:
The name of the method corresponding to one of the implemented candidate
spaces.
The name of the method corresponding to one of the implemented
candidate spaces.

Returns:
The candidate space.
"""
for candidate_space_class in candidate_space_classes:
if candidate_space_class.method == method:
return candidate_space_class
raise NotImplementedError(
f'The provided method name {method} does not correspond to an implemented candidate space.'
)
candidate_space_class = candidate_space_classes.get(method, None)
if candidate_space_class is None:
raise NotImplementedError(
f'The provided method `{method}` does not correspond to an '
'implemented candidate space.'
)
return candidate_space_class


'''
Expand Down
8 changes: 4 additions & 4 deletions petab_select/ui.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@
import numpy as np
import petab

from .candidate_space import CandidateSpace
from .candidate_space import CandidateSpace, FamosCandidateSpace
from .constants import INITIAL_MODEL_METHODS, TYPE_PATH, Criterion, Method
from .model import Model, default_compare
from .problem import Problem
Expand Down Expand Up @@ -137,7 +137,7 @@ def candidates(
# Else, in case we jumped to most distant in this iteration, go into
# calibration with only the model we've jumped to.
if (
candidate_space.governing_method == Method.FAMOS
isinstance(candidate_space, FamosCandidateSpace)
and candidate_space.jumped_to_most_distant
):
return candidate_space
Expand Down Expand Up @@ -179,7 +179,7 @@ def candidates(
# if the candidate space is able to switch methods.
# N.B.: candidate spaces that switch methods must raise `StopIteration`
# when they stop switching.
if candidate_space.governing_method == Method.FAMOS:
if isinstance(candidate_space, FamosCandidateSpace):
try:
candidate_space.update_after_calibration(
calibrated_models=calibrated_models,
Expand Down Expand Up @@ -310,7 +310,7 @@ def write_summary_tsv(
# FIXME remove once MostDistantCandidateSpace exists...
method = candidate_space.method
if (
candidate_space.governing_method == Method.FAMOS
isinstance(candidate_space, FamosCandidateSpace)
and isinstance(candidate_space.predecessor_model, Model)
and candidate_space.predecessor_model.predecessor_model_hash is None
):
Expand Down