{{ message }}
-
Notifications
You must be signed in to change notification settings - Fork 5
Expand file tree
/
Copy pathcontrols.py
More file actions
257 lines (204 loc) · 9.65 KB
/
Copy pathcontrols.py
File metadata and controls
257 lines (204 loc) · 9.65 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
"""The Controls class for providing RAT algorithm settings."""
import contextlib
import os
import tempfile
import warnings
from pathlib import Path
import prettytable
from pydantic import (
BaseModel,
Field,
ValidationError,
ValidatorFunctionWrapHandler,
model_serializer,
model_validator,
)
from ratapi.utils.custom_errors import custom_pydantic_validation_error
from ratapi.utils.enums import BoundHandling, Display, Parallel, Procedures, Strategies
common_fields = [
"procedure",
"parallel",
"numSimulationPoints",
"resampleMinAngle",
"resampleNPoints",
"display",
]
update_fields = ["updateFreq", "updatePlotFreq"]
fields = {
"calculate": common_fields,
"simplex": [*common_fields, "xTolerance", "funcTolerance", "maxFuncEvals", "maxIterations", *update_fields],
"de": [
*common_fields,
"populationSize",
"fWeight",
"crossoverProbability",
"strategy",
"targetValue",
"numGenerations",
*update_fields,
],
"ns": [*common_fields, "nLive", "nMCMC", "propScale", "nsTolerance"],
"dream": [*common_fields, "nSamples", "nChains", "jumpProbability", "pUnitGamma", "boundHandling", "adaptPCR"],
}
class Controls(BaseModel, validate_assignment=True, extra="forbid", use_attribute_docstrings=True):
"""The full set of controls parameters for all five procedures that are required for the compiled RAT code."""
# All Procedures
procedure: Procedures = Procedures.Calculate
"""Which procedure RAT should execute. Can be 'calculate', 'simplex', 'de', 'ns', or 'dream'."""
parallel: Parallel = Parallel.Single
"""How the calculation should be parallelised. Can be 'single', 'contrasts' or 'points'."""
numSimulationPoints: int = Field(500, ge=2)
"""The number of points used for reflectivity simulations where no data is supplied."""
resampleMinAngle: float = Field(0.9, le=1, gt=0)
"""The upper threshold on the angle between three sampled points for resampling, in units of radians over pi."""
resampleNPoints: int = Field(50, gt=0)
"""The number of initial points to use for resampling."""
display: Display = Display.Iter
"""How much RAT should print to the terminal. Can be 'off', 'iter', 'notify', or 'final'."""
# Simplex
xTolerance: float = Field(1.0e-6, gt=0.0)
"""[SIMPLEX] The termination tolerance for step size."""
funcTolerance: float = Field(1.0e-6, gt=0.0)
"""[SIMPLEX] The termination tolerance for change in chi-squared."""
maxFuncEvals: int = Field(10000, gt=0)
"""[SIMPLEX] The maximum number of function evaluations before the algorithm terminates."""
maxIterations: int = Field(1000, gt=0)
"""[SIMPLEX] The maximum number of iterations before the algorithm terminates."""
# Simplex and DE
updateFreq: int = 1
"""[SIMPLEX, DE] Number of iterations between printing progress updates to the terminal."""
updatePlotFreq: int = 20
"""[SIMPLEX, DE] Number of iterations between updates to live plots."""
# DE
populationSize: int = Field(20, ge=1)
"""[DE] The number of candidate solutions that exist at any time."""
fWeight: float = Field(0.5, gt=0.0)
"""[DE] The step size for how different mutations are to their parents."""
crossoverProbability: float = Field(0.8, gt=0.0, lt=1.0)
"""[DE] The probability of exchange of parameters between individuals at any iteration."""
strategy: Strategies = Strategies.RandomWithPerVectorDither
"""[DE] The algorithm used to generate new candidates."""
targetValue: float = Field(1.0, ge=1.0)
"""[DE] The value of chi-squared at which the algorithm will terminate."""
numGenerations: int = Field(500, ge=1)
"""[DE] The maximum number of iterations before the algorithm terminates."""
# NS
nLive: int = Field(150, ge=1)
"""[NS] The number of points to sample."""
nMCMC: int = Field(0, ge=0)
"""[NS] If non-zero, an MCMC process with ``nMCMC`` chains will be used instead of MultiNest."""
propScale: float = Field(0.1, gt=0.0, lt=1.0)
"""[NS] A scaling factor for the ellipsoid generated by MultiNest."""
nsTolerance: float = Field(0.1, ge=0.0)
"""[NS] The tolerance threshold for when the algorithm should terminate."""
# Dream
nSamples: int = Field(20000, ge=0)
"""[DREAM] The total number of function evaluations (number of algorithm generations times number of chains)."""
nChains: int = Field(10, gt=1)
"""[DREAM] The number of Markov chains to use in the algorithm."""
jumpProbability: float = Field(0.5, gt=0.0, lt=1.0)
"""[DREAM] The probability range for the size of jumps in sampling. Larger values mean more variable jumps."""
pUnitGamma: float = Field(0.2, gt=0.0, lt=1.0)
"""[DREAM] The probability that the scaling-down factor of jumps will be ignored and a larger jump will be taken."""
boundHandling: BoundHandling = BoundHandling.Reflect
"""[DREAM] How steps past the space boundaries should be handled. Can be 'off', 'reflect', 'bound', or 'fold'."""
adaptPCR: bool = True
"""[DREAM] Whether the crossover probability for differential evolution should be adapted during the run."""
# Private field for IPC file
_IPCFilePath: str = ""
@model_validator(mode="wrap")
def warn_setting_incorrect_properties(self, handler: ValidatorFunctionWrapHandler) -> "Controls":
"""Raise a warning if the user sets fields that apply to other procedures."""
model_input = self
try:
input_dict = model_input.__dict__
except AttributeError:
input_dict = model_input
validated_self = None
try:
validated_self = handler(self)
except ValidationError as exc:
procedure = input_dict.get("procedure", Procedures.Calculate)
custom_error_msgs = {
"extra_forbidden": f'Extra inputs are not permitted. The fields for the "{procedure}"'
f" controls procedure are:\n "
f"{', '.join(fields.get('procedure', []))}\n",
}
custom_error_list = custom_pydantic_validation_error(exc.errors(include_url=False), custom_error_msgs)
raise ValidationError.from_exception_data(exc.title, custom_error_list, hide_input=True) from None
if isinstance(model_input, validated_self.__class__):
# This is for changing fields in a defined model
changed_fields = [key for key in input_dict if input_dict[key] != validated_self.__dict__[key]]
elif isinstance(model_input, dict):
# This is for a newly-defined model
changed_fields = input_dict.keys()
else:
raise ValueError('The input to the "Controls" model is invalid.')
new_procedure = validated_self.procedure
allowed_fields = fields[new_procedure]
for field in changed_fields:
if field not in allowed_fields:
incorrect_procedures = [key for (key, value) in fields.items() if field in value]
warnings.warn(
f'\nThe current controls procedure is "{new_procedure}", but the property'
f' "{field}" applies instead to the {", ".join(incorrect_procedures)} procedure.\n\n'
f' The fields for the "{new_procedure}" controls procedure are:\n'
f" {', '.join(fields[new_procedure])}\n",
stacklevel=2,
)
return validated_self
@model_serializer
def serialize(self):
"""Filter fields so only those applying to the chosen procedure are serialized."""
return {model_field: getattr(self, model_field) for model_field in fields[self.procedure]}
def __repr__(self) -> str:
fields_repr = ", ".join(repr(v) if a is None else f"{a}={v!r}" for a, v in self.model_dump().items())
return f"{self.__repr_name__()}({fields_repr})"
def __str__(self) -> str:
table = prettytable.PrettyTable()
table.field_names = ["Property", "Value"]
table.add_rows([[k, v] for k, v in self.model_dump().items()])
return table.get_string()
def initialise_IPC(self):
"""Set up the inter-process communication file."""
IPC_obj, self._IPCFilePath = tempfile.mkstemp()
os.write(IPC_obj, b"0")
os.close(IPC_obj)
return None
def sendStopEvent(self):
"""Send the stop event via the inter-process communication file.
Warnings
--------
UserWarning
Raised if we try to delete an IPC file that was not initialised.
"""
if os.path.isfile(self._IPCFilePath):
with open(self._IPCFilePath, "wb") as f:
f.write(b"1")
else:
warnings.warn("An IPC file was not initialised.", UserWarning, stacklevel=2)
return None
def delete_IPC(self):
"""Delete the inter-process communication file."""
with contextlib.suppress(FileNotFoundError):
os.remove(self._IPCFilePath)
return None
def save(self, filepath: str | Path = "./controls.json"):
"""Save a controls object to a JSON file.
Parameters
----------
filepath : str or Path
The path to where the controls file will be written.
"""
filepath = Path(filepath).with_suffix(".json")
filepath.write_text(self.model_dump_json())
@classmethod
def load(cls, path: str | Path) -> "Controls":
"""Load a controls object from file.
Parameters
----------
path : str or Path
The path to the controls object file.
"""
file = Path(path)
return cls.model_validate_json(file.read_text())
You can’t perform that action at this time.