Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

add finished property to manual generators #409

Closed
wants to merge 1 commit into from
Closed

add finished property to manual generators #409

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 9 additions & 4 deletions aepsych/generators/manual_generator.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,15 +6,16 @@
# LICENSE file in the root directory of this source tree.

import warnings
from typing import Optional, Union, Dict
from typing import Dict, Optional, Union

import numpy as np
import torch
from torch.quasirandom import SobolEngine

from aepsych.config import Config
from aepsych.generators.base import AEPsychGenerator
from aepsych.models.base import AEPsychMixin
from aepsych.utils import _process_bounds
from torch.quasirandom import SobolEngine


class ManualGenerator(AEPsychGenerator):
Expand Down Expand Up @@ -95,6 +96,10 @@ def get_config_options(cls, config: Config, name: Optional[str] = None) -> Dict:

return options

@property
def finished(self):
return self._idx >= len(self.points)


class SampleAroundPointsGenerator(ManualGenerator):
"""Generator that samples in a window around reference points in a predefined list."""
Expand Down Expand Up @@ -131,9 +136,9 @@ def __init__(
grid = self.engine.draw(samples_per_point)
grid = p_lb + (p_ub - p_lb) * grid
generated.append(grid)
generated = torch.Tensor(np.vstack(generated)) #type: ignore
generated = torch.Tensor(np.vstack(generated)) # type: ignore

super().__init__(lb, ub, generated, dim, shuffle, seed) #type: ignore
super().__init__(lb, ub, generated, dim, shuffle, seed) # type: ignore

@classmethod
def get_config_options(cls, config: Config, name: Optional[str] = None) -> Dict:
Expand Down
6 changes: 6 additions & 0 deletions tests/generators/test_manual_generator.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@

import numpy as np
import numpy.testing as npt

from aepsych.config import Config
from aepsych.generators import ManualGenerator, SampleAroundPointsGenerator

Expand Down Expand Up @@ -50,6 +51,7 @@ def test_manual_generator(self):
gen = ManualGenerator.from_config(config)
npt.assert_equal(gen.lb.numpy(), np.array([0, 0]))
npt.assert_equal(gen.ub.numpy(), np.array([1, 1]))
self.assertFalse(gen.finished)

p1 = list(gen.gen()[0])
p2 = list(gen.gen()[0])
Expand All @@ -60,6 +62,7 @@ def test_manual_generator(self):
self.assertEqual(sorted([p1, p2, p3, p4]), points)
self.assertEqual(gen.max_asks, len(points))
self.assertEqual(gen.seed, 123)
self.assertTrue(gen.finished)


class TestSampleAroundPointsGenerator(unittest.TestCase):
Expand All @@ -86,13 +89,16 @@ def test_sample_around_points_generator(self):
npt.assert_equal(gen.ub.numpy(), np.array([1, 1]))
self.assertEqual(gen.max_asks, len(points * samples_per_point))
self.assertEqual(gen.seed, 123)
self.assertFalse(gen.finished)

points = gen.gen(gen.max_asks)
for i in range(len(window)):
npt.assert_array_less(points[:, i], points[:, i] + window[i])
npt.assert_array_less(np.array([0] * len(points)), points[:, i])
npt.assert_array_less(points[:, i], np.array([1] * len(points)))

self.assertTrue(gen.finished)


if __name__ == "__main__":
unittest.main()
Loading