Infrastructure and dependencies update

.github/workflows/tests.yml

@@ -6,44 +6,56 @@ name: Tests
 on: [push, pull_request]
 
 jobs:
+  get_python_versions:
+    name: "Determine Python versions"
+    runs-on: ubuntu-latest
+    permissions: {}
+    outputs:
+      min-python: ${{ steps.nep29.outputs.min-python }}
+      max-python: "${{ steps.nep29.outputs.max-python }}"
+    steps:
+      - name: "calculate versions according to SPEC-0"
+        id: nep29
+        uses: mstimberg/github-calc-nep29@a73481e4e8488a5fa0b3be70a385cc5206a261ba # v0.7
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+          # Match SPEC-0
+          deprecate-python-after: 36
+          min-python-releases: 0
+
   build:
-
     runs-on: ubuntu-latest
+    needs: [get_python_versions]
+    name: "Python ${{ matrix.python-version }} (latest Brian: ${{ matrix.latest-brian }})"
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.8, 3.11]
-        latest-brian: [true, false]
+        python-version: ["${{ needs.get_python_versions.outputs.min-python }}", "${{ needs.get_python_versions.outputs.max-python }}"]
+        latest-brian: [false, true]
 
     steps:
     - name: Checkout Repository
-      uses: actions/checkout@v3
+      uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
       with:
         fetch-depth: 0
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@e797f83bcb11b83ae66e0230d6156d7c80228e7c # v6.0.0
       with:
         python-version: ${{ matrix.python-version }}
+    - name: Install uv
+      uses: astral-sh/setup-uv@v7
+      with:
+        enable-cache: true
     - name: Install brian2modelfitting
-      run: |
-        python -m pip install --upgrade pip wheel
-        python -m pip install flake8 pytest-coverage pytest-timeout coveralls
-        python -m pip install ".[all]"
+      run: uv sync -v --extra skopt --extra sbi --extra efel --extra test --dev  # Not testing efel for now, since incompatible with numpy 2
     - name: Update to latest Brian development version
-      run: python -m pip install -i https://test.pypi.org/simple/ --pre --upgrade Brian2
+      run: uv pip install -i https://test.pypi.org/simple/ --pre --upgrade Brian2
       if: ${{ matrix.latest-brian }}
-    - name: Lint with flake8
-      run: |
-        # stop the build if there are Python syntax errors or undefined names
-        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: Check for syntax errors and undefined names
+      run: uv run ruff check . --select=E9,F63,F7,F82
     - name: Test with pytest
       run: |
-        pytest --timeout=60 --cov=brian2modelfitting
+        uv run --no-sync --frozen pytest --timeout=240 --cov=brian2modelfitting --cov-report=lcov
     - name: Upload coverage to coveralls
-      env:
-        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-      if: ${{ matrix.python-version == '3.8' && !matrix.latest-brian }}
-      run: coveralls --service=github
-
+      uses: coverallsapp/github-action@648a8eb78e6d50909eff900e4ec85cab4524a45b  # v2.3.6
+      if: ${{ matrix.python-version == needs.get_python_versions.outputs.min-python && ! matrix.latest-brian}}

brian2modelfitting/inferencer.py

@@ -1,44 +1,49 @@
 """
 Module to perform simulation-based inference with the ``sbi`` library.
 """
+import warnings
 from numbers import Number
 from typing import Mapping
-import warnings
 
+import numpy as np
 from brian2.core.functions import Function
 from brian2.core.namespace import get_local_namespace
 from brian2.core.network import Network
 from brian2.devices.cpp_standalone.device import CPPStandaloneDevice
-from brian2.devices.device import get_device, device
+from brian2.devices.device import device, get_device
 from brian2.equations.equations import Equations
 from brian2.groups.neurongroup import NeuronGroup
 from brian2.input.timedarray import TimedArray
 from brian2.monitors.spikemonitor import SpikeMonitor
 from brian2.monitors.statemonitor import StateMonitor
-from brian2.units.fundamentalunits import (DIMENSIONLESS,
-                                           fail_for_dimension_mismatch,
-                                           get_dimensions,
-                                           Quantity)
+from brian2.units.fundamentalunits import (
+    DIMENSIONLESS,
+    Quantity,
+    fail_for_dimension_mismatch,
+    get_dimensions,
+)
 from brian2.utils.logger import get_logger
+
 from brian2modelfitting.fitter import get_spikes
-import numpy as np
+
 try:
     import sbi
     import torch
 except ImportError:
     sbi = None
     torch = None
 
-from .base import (handle_input_args,
-                   handle_output_args,
-                   handle_param_init,
-                   input_equations,
-                   output_equations,
-                   output_dims)
-from .simulator import RuntimeSimulator, CPPStandaloneSimulator
+from .base import (
+    handle_input_args,
+    handle_output_args,
+    handle_param_init,
+    input_equations,
+    output_dims,
+    output_equations,
+)
+from .simulator import CPPStandaloneSimulator, RuntimeSimulator
 from .utils import tqdm
 
-
 logger = get_logger(__name__)
 
 
@@ -606,9 +611,7 @@ def init_inference(self, inference_method, density_estimator_model, prior,
             Instantiated inference object.
         """
         import sbi.inference
-        from sbi.utils.get_nn_models import (posterior_nn,
-                                             likelihood_nn,
-                                             classifier_nn)
+        from sbi.neural_nets import classifier_nn, likelihood_nn, posterior_nn
         try:
             inference_method = str.upper(inference_method)
             inference_method_fun = getattr(sbi.inference, inference_method)
@@ -960,8 +963,15 @@ def load_posterior(self, f):
             Loaded neural posterior with defined method family, density
             estimator state dictionary, the prior over parameters and
             the output shape of the simulator.
-        """
-        p = torch.load(f)
+
+        Notes
+        -----
+        Only use this function to load files from trusted sources. It will
+        call `torch.load` with ``weights_only=False``, potentially resulting
+        in arbitrary code execution. See
+        https://pytorch.org/docs/stable/generated/torch.load.html
+        """        
+        p = torch.load(f, weights_only=False)
         self.posterior = p
         return p
 

brian2modelfitting/tests/test_inferencer.py

@@ -319,7 +319,6 @@ def test_infer_step(setup_full):
                                       n_samples=10,
                                       inference=inference)
     assert isinstance(posterior, DirectPosterior)
-    assert_equal(np.array(posterior._x_shape), np.array([1, 5]))
 
 
 def test_infer_step_errors(setup_full):

brian2modelfitting/tests/test_metric.py

@@ -218,6 +218,7 @@ def test_get_errors_gamma():
 
 @pytest.mark.parametrize("parallel_processes", [0, 2, -1, -2])  # only testing that it works at all
 def test_calc_EFL(parallel_processes):
+    pytest.importorskip("efel")
     # "voltage traces" that are constant at -70*mV, -60mV, -50mV, -40mV for
     # 50ms each.
     dt = 1*ms
@@ -239,6 +240,7 @@ def test_calc_EFL(parallel_processes):
 
 
 def test_get_features_feature_metric():
+    pytest.importorskip("efel")
     # "voltage traces" that are constant at -70*mV, -60mV, -50mV, -40mV for
     # 50ms each.
     voltage_target = np.ones((2, 200)) * np.repeat([-70, -60, -50, -40], 50) * mV
@@ -276,6 +278,7 @@ def test_get_features_feature_metric():
 
 
 def test_get_errors_feature_metric():
+    pytest.importorskip("efel")
     # Fake results
     features = [{'feature1': np.array([0, 0.5]),
                 'feature2': np.array([1, 2])},

brian2modelfitting/tests/test_modelfitting_tracefitter.py

@@ -1,23 +1,46 @@
 '''
 Test the modelfitting module
 '''
-import pytest
+import brian2.numpy_ as np  # for unit-awareness
 import pandas as pd
+import pytest
 import scipy.optimize
-
-from numpy.testing import assert_equal, assert_almost_equal
-from brian2 import (zeros, Equations, NeuronGroup, StateMonitor, TimedArray,
-                    nS, mV, volt, ms, pA, pF, Quantity, set_device, get_device,
-                    Network, have_same_dimensions, DimensionMismatchError)
-from brian2.equations.equations import DIFFERENTIAL_EQUATION, SUBEXPRESSION
-import brian2.numpy_ as np  # for unit-awareness
-from brian2modelfitting import (NevergradOptimizer, TraceFitter, MSEMetric,
-                                OnlineTraceFitter, Simulator, Metric,
-                                Optimizer, GammaFactor, FeatureMetric)
+from brian2 import (
+    DimensionMismatchError,
+    Equations,
+    Network,
+    NeuronGroup,
+    Quantity,
+    StateMonitor,
+    TimedArray,
+    get_device,
+    have_same_dimensions,
+    ms,
+    mV,
+    nS,
+    pA,
+    pF,
+    set_device,
+    volt,
+    zeros,
+)
 from brian2.devices.device import reinit_devices, reset_device
+from brian2.equations.equations import DIFFERENTIAL_EQUATION, SUBEXPRESSION
+from numpy.testing import assert_almost_equal, assert_equal
+
+from brian2modelfitting import (
+    FeatureMetric,
+    GammaFactor,
+    Metric,
+    MSEMetric,
+    NevergradOptimizer,
+    OnlineTraceFitter,
+    Optimizer,
+    Simulator,
+    TraceFitter,
+)
 from brian2modelfitting.fitter import get_param_dic
 
-
 E = 40*mV
 input_traces = zeros((10, 5))*volt
 for i in range(5):
@@ -339,6 +362,8 @@ def test_tracefitter_fit_default_metric(setup):
 
 
 from nevergrad.optimization import registry as nevergrad_registry
+
+
 @pytest.mark.parametrize('method', sorted(nevergrad_registry.keys()))
 def test_fitter_fit_methods(method):
     dt = 0.01 * ms
@@ -347,15 +372,20 @@ def test_fitter_fit_methods(method):
         g : siemens (constant)
         E : volt (constant)
         ''')
+    # Fix for optimizers that don't support parallelization (DS)
+    # or have small fixed budgets (NGOptSingle)
+    n_samples = 30
+    if any(name in method for name in ['DS', 'NGOptSingle']):
+        n_samples = 1
     tf = TraceFitter(dt=dt,
                      model=model,
                      input_var='v',
                      output_var='I',
                      input=input_traces,
                      output=output_traces,
-                     n_samples=30)
+                     n_samples=n_samples)
     # Skip a few methods that seem to hang due to multi-threading deadlocks (?) or simply take very long
-    skip = ['BO', 'ParaPortfolio', 'BAR', 'MultiBFGS', 'MultiCobyla', 'MultiSQP', 'NgIohRW', 'F3SQPCMA']
+    skip = ['MultiDS', 'BO', 'ParaPortfolio', 'BAR', 'MultiBFGS', 'MultiCobyla', 'MultiSQP', 'NgIohRW', 'F3SQPCMA']
     if any(s in method for s in skip):
         pytest.skip(f'Skipping method {method}')
 
@@ -702,6 +732,7 @@ def test_fitter_refine_reuse_tsteps_multiobjective(setup_constant_multiobjective
 
 
 def test_fitter_refine_errors(setup):
+    pytest.importorskip("efel")
     dt, tf = setup
     with pytest.raises(TypeError):
         # Missing start parameter
@@ -1136,7 +1167,7 @@ def test_multiobjective_basic(setup_multiobjective):
 
 def test_multiobjective_no_units(setup_multiobjective_no_units):
     dt, tf = setup_multiobjective_no_units
-    result, error = tf.fit(n_rounds=20,
+    result, error = tf.fit(n_rounds=30,
                        metric={'var1': MSEMetric(t_start=50*ms),
                                'var2': MSEMetric(t_start=50*ms, normalization=0.001)},
                        optimizer=n_opt,

pyproject.toml

@@ -6,9 +6,9 @@ authors = [
     {name = 'Marcel Stimberg'},
     {name ='Romain Brette'}
 ]
-requires-python = '>=3.8'
+requires-python = '>=3.12'
 dependencies = [
-    'numpy>=1.21',
+    'numpy>=2.0,<2.4',  # Nevergrad depends on library incompatible with 2.4
     'brian2>=2.2',
     'nevergrad>=0.4',
     'scikit-learn>=0.22',
@@ -30,16 +30,16 @@ classifiers = [
 ]
 
 [project.optional-dependencies]
-test = ['pytest']
+test = ['pytest', 'pytest-coverage', 'pytest-timeout']
 docs = ['sphinx>=1.8']
 algos = [  # additional optimizers for nevergrad
-         'cma>=3.0', 'fcmaes', 'loguru',  # loguru seems to be an undeclared dependency of fcmaes
+         'cma>=3.0',
          'nlopt',
          'poap',
          'ConfigSpace']
 skopt = ['scikit-optimize']
 efel = ['efel']
-sbi = ['sbi>=0.16.0']
+sbi = ['sbi>=0.23.0']
 all = ['brian2modelfitting[test]',
        'brian2modelfitting[docs]',
        'brian2modelfitting[algos]',
@@ -48,6 +48,12 @@ all = ['brian2modelfitting[test]',
        'brian2modelfitting[sbi]'
 ]
 
+[dependency-groups]
+dev = ['ruff']
+
+[tool.uv]
+override-dependencies = ["torch"]  # Remove sbi's upper dependency
+
 [project.urls]
 Documentation ='https://brian2modelfitting.readthedocs.io/'
 Source = 'https://github.com/brian-team/brian2modelfitting'