Bump up to Series 1.1.5 update

.github/workflows/docs.yml

@@ -1,7 +1,7 @@
 # From https://github.com/eeholmes/readthedoc-test/blob/main/.github/workflows/docs_pages.yml
 name: docs
 
-# execute this workflow automatically when a we push to master
+# execute this workflow automatically when we push to master
 on:
  push:
  branches:
@@ -28,7 +28,7 @@ jobs:
  uses: actions/setup-python@v4
  with:
  python-version: 3.11
- cache: 'pip'
+ cache: "pip"
 
  - name: Install dependencies
  run: |

.github/workflows/publish.yml

@@ -7,10 +7,10 @@ jobs:
  runs-on: ubuntu-latest
  steps:
  - name: Checkout
- uses: actions/checkout@v3
+ uses: actions/checkout@v4
  with:
  fetch-depth: 0
- - run: python3 -m pip install --upgrade build && python3 -m build
+ - run: python3 -m pip install -U build && python3 -m build
  - name: Publish package
  uses: pypa/gh-action-pypi-publish@release/v1
  with:

.github/workflows/tests.yml

@@ -3,7 +3,7 @@ name: Tests
 on:
  pull_request:
  push:
- branches: 
+ branches:
  - master
  - Development
 
@@ -14,17 +14,18 @@ jobs:
  strategy:
  matrix:
  os: [ubuntu-latest, windows-latest]
- python-version: ['3.9']
+ python-version: ["3.10", "3.11"]
 
  steps:
- - uses: actions/checkout@v2
+ - uses: actions/checkout@v4
  - name: Set up Python ${{ matrix.python-version }}
- uses: actions/setup-python@v2
+ uses: actions/setup-python@v5
  with:
  python-version: ${{ matrix.python-version }}
  - name: Install dependencies
  run: |
- python -m pip install --upgrade pip
- pip install tox tox-gh-actions
+ python -m ensurepip
+ python -m pip install -U pip setuptools wheel
+ python -m pip install tox tox-gh-actions
  - name: Test with tox
  run: tox

INSTALL.rst

@@ -4,7 +4,7 @@ Full Installation Instructions
 Requirements
 ------------
 
-This package requires Python 3.9 or later.
+This package requires Python 3.10 or later.
 A simple installation is possible via `Miniconda <https://docs.conda.io/en/latest/miniconda.html>`_,
 e.g. (on Linux)
 

pyproject.toml

@@ -26,7 +26,7 @@ no_implicit_reexport = true
 
 [tool.black]
 line-length = 120
-target-version = ["py39", "py310"]
+target-version = ["py310", "py311"]
 
 [tool.isort]
 profile = "black"

requirements_dev.txt

@@ -1,5 +1,6 @@
 flake8>=6.1.0
 tox>=4.10.0
 pytest>=7.2.0
+pytest-xdist>=3.5.0
 pytest-cov>=4.1.0
 myp>=1.5.1

setup.cfg

@@ -30,7 +30,7 @@ keywords =
  model comparison
 
 [options]
-python_requires = >=3.9
+python_requires = >=3.10
 packages = find:
 install_requires =
  h5py >= 3.7
@@ -51,6 +51,7 @@ testing =
  flake8 >= 3.9
  tox >= 3.24
  pytest >= 6.0
+ pytest-xdist >= 2.4.0
  pytest-cov >= 2.10.0
  mypy >= 0.910
 docs =

tests/test_sensitivity.py

@@ -1,12 +1,11 @@
+from copy import deepcopy
 from functools import partial
 from unittest.mock import MagicMock, Mock
 
 import numpy as np
 import pytest
 import tensorflow as tf
 
-from copy import deepcopy
-
 from bayesflow import computational_utilities, sensitivity, simulation
 from tests.test_trainers import _create_training_setup, _prior, _simulator
 
@@ -26,7 +25,7 @@ def _trainer_amortizer_sample_mock(input_dict, n_samples):
 
 
 class TestMisspecificationExperiment:
- def setup(self):
+ def setup_method(self):
  self.trainer = _create_training_setup(mode="posterior")
 
  # Mock the approximate posterior sampling of the amortizer, return np.ones of shape (n_sim, n_samples)

tests/test_trainers.py

@@ -68,8 +68,9 @@ def _create_training_setup(mode):
  trainer = Trainer(generative_model=model, amortizer=amortizer)
  return trainer
 
+
 class TestTrainer:
- def setup(self):
+ def setup_method(self):
  trainer_posterior = _create_training_setup("posterior")
  trainer_likelihood = _create_training_setup("likelihood")
  trainer_joint = _create_training_setup("joint")
@@ -111,7 +112,6 @@ def test_train_online(self, mode, reuse_optimizer, validation_sims):
  assert type(h["train_losses"]) is DataFrame
  assert type(h["val_losses"]) is DataFrame
 
-
  @pytest.mark.parametrize("mode", ["posterior", "joint"])
  @pytest.mark.parametrize("reuse_optimizer", [True, False])
  @pytest.mark.parametrize("validation_sims", [20, None])
@@ -202,34 +202,3 @@ def test_train_rounds(self, mode, reuse_optimizer, validation_sims):
  assert type(h) is dict
  assert type(h["train_losses"]) is DataFrame
  assert type(h["val_losses"]) is DataFrame
-
- @pytest.mark.parametrize("reference_data", [None, "dict", "numpy"])
- @pytest.mark.parametrize("observed_data_type", ["dict", "numpy"])
- @pytest.mark.parametrize("bootstrap", [True, False])
- def mmd_hypothesis_test_no_reference(self, reference_data, observed_data_type, bootstrap):
- trainer = self.trainers["posterior"]
- _ = trainer.train_online(epochs=1, iterations_per_epoch=1, batch_size=4)
-
- num_reference_simulations = 10
- num_observed_simulations = 2
- num_null_samples = 5
-
- if reference_data is None:
- if reference_data == "dict":
- reference_data = trainer.configurator(trainer.generative_model(num_reference_simulations))
- elif reference_data == "numpy":
- reference_data = trainer.configurator(trainer.generative_model(num_reference_simulations))['summary_conditions']
-
- if observed_data_type == "dict":
- observed_data = trainer.configurator(trainer.generative_model(num_observed_simulations))
- elif observed_data_type == "numpy":
- observed_data = trainer.configurator(trainer.generative_model(num_observed_simulations))['summary_conditions']
-
- MMD_sampling_distribution, MMD_observed = trainer.mmd_hypothesis_test(observed_data=observed_data,
- reference_data=reference_data,
- num_reference_simulations=num_reference_simulations,
- num_null_samples=num_null_samples,
- bootstrap=bootstrap)
-
- assert MMD_sampling_distribution.shape[0] == num_reference_simulations
- assert np.all(MMD_sampling_distribution > 0)

tox.ini

@@ -5,25 +5,25 @@ envlist =
 
 [gh-actions]
 python =
- 3.9: base, flake8
+ 3.10: base, flake8
 
 [testenv]
 setenv =
  PYTHONPATH = {toxinidir}
 deps =
  -r{toxinidir}/requirements_dev.txt
 commands =
- pytest --basetemp={envtmpdir}
+ pytest -n auto --basetemp={envtmpdir}
 
 [testenv:flake8]
-basepython = python3.9
+basepython = python3.10
 deps = flake8
 commands = flake8 bayesflow tests
 
 [testenv:base]
 extras = test
 commands =
- pytest tests
+ pytest tests -n auto
 
 [testenv:docs]
 extras =