[MAINT] add tests (#17)

* set up test notebooks

* add tests and coverage

* change path

.flake8

@@ -1,15 +1,6 @@
 [flake8]
-; exclude =
-    ; .git,
-    ; __pycache__,
-    ; build,
-    ; dist,
-	; env,
-	; venv,
-	; doc/_build
 --select = A,B,C,D,E,F,W,C90,FS
-; docstring-convention = numpy
-max-line-length = 100
+max-line-length = 90
 # For PEP8 error codes see
 # http://pep8.readthedocs.org/en/latest/intro.html#error-codes
 ; per-file-ignores =

.github/workflows/run_examples.yml

@@ -22,7 +22,7 @@ jobs:
         strategy:
             fail-fast: false
             matrix:
-                example: [comparedesigns.py, comparison_neurodesign.py, JSS_example.py, optimisation.py]
+                example: [compare_designs.py, JSS_example.py, optimisation.py]
         steps:
         -   name: Checkout
             uses: actions/checkout@v4

.github/workflows/test_notebook.yml

@@ -0,0 +1,31 @@
+---
+name: test notebook
+
+on:
+    push:
+        branches:
+        -   master
+    pull_request:
+        branches:
+        -   '*'
+
+concurrency:
+    group: ${{ github.workflow }}-${{ github.ref }}
+    cancel-in-progress: true
+
+jobs:
+    test_notebook:
+        name: run notebooks
+        runs-on: ubuntu-latest
+        steps:
+        -   name: Checkout
+            uses: actions/checkout@v4
+        -   name: Setup python
+            uses: actions/setup-python@v5
+            with:
+                python-version: '3.12'
+                allow-prereleases: false
+        -   name: Install tox
+            run: python -m pip install --upgrade tox
+        -   name: Run tests
+            run: tox run -e test_notebook

.github/workflows/tests.yml

@@ -0,0 +1,41 @@
+---
+name: tests
+
+on:
+    push:
+        branches:
+        -   master
+    pull_request:
+        branches:
+        -   '*'
+
+concurrency:
+    group: ${{ github.workflow }}-${{ github.ref }}
+    cancel-in-progress: true
+
+jobs:
+    tests:
+        name: Test with ${{ matrix.py }} on ${{ matrix.os }}
+        runs-on: ${{ matrix.os }}
+        strategy:
+            fail-fast: false
+            matrix:
+                py: ['3.12', '3.11', '3.10', '3.9', '3.8']
+                os: [ubuntu-latest, macos-latest, windows-latest]
+        steps:
+        -   name: Checkout
+            uses: actions/checkout@v4
+        -   name: Setup python
+            uses: actions/setup-python@v5
+            with:
+                python-version: ${{ matrix.py }}
+                allow-prereleases: false
+        -   name: Install tox
+            run: python -m pip install --upgrade tox
+        -   name: Run tests
+            run: tox run -e tests
+        -   name: Upload coverage to CodeCov
+            uses: codecov/codecov-action@v4
+            with:
+                flags: ${{ matrix.os }}_${{ matrix.py }}
+            if: success()

.pre-commit-config.yaml

@@ -32,6 +32,7 @@ repos:
     rev: 24.1.1
     hooks:
     -   id: black
+        additional_dependencies: ['.[jupyter]']
         args: [--config, pyproject.toml]
 
 -   repo: https://github.com/adamchainz/blacken-docs
@@ -65,4 +66,4 @@ repos:
     hooks:
     -   id: flake8
         args: [--config, .flake8, --verbose, neurodesign, examples]
-        additional_dependencies: [flake8-docstrings, flake8-use-fstring]
+        additional_dependencies: [flake8-docstrings, flake8-use-fstring, flake8-nb]

examples/JSS_example.py

@@ -1,12 +1,14 @@
-import os
-import os.path as op
 from collections import Counter
+from pathlib import Path
 
 import matplotlib.pyplot as plt
 
 import neurodesign
 
-EXP = neurodesign.experiment(
+output_dir = Path(__file__).parent / "output"
+output_dir.mkdir(parents=True, exist_ok=True)
+
+exp = neurodesign.experiment(
     TR=1.2,
     n_trials=20,
     P=[0.3, 0.3, 0.4],
@@ -19,40 +21,44 @@
     ITImax=4,
 )
 
-DES1 = neurodesign.design(
-    order=[0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1], ITI=[2] * 20, experiment=EXP
+design_1 = neurodesign.design(
+    order=[0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1],
+    ITI=[2] * 20,
+    experiment=exp,
 )
 
-DES1.designmatrix()
-
-DES1.FCalc(weights=[0.25, 0.25, 0.25, 0.25])
+design_1.designmatrix()
 
+design_1.FCalc(weights=[0.25, 0.25, 0.25, 0.25])
 
-plt.plot(DES1.Xconv)
 
-out_dir = "output"
-if not op.isdir(out_dir):
-    os.makedirs(out_dir)
+plt.plot(design_1.Xconv)
 
-plt.savefig(op.join(out_dir, "example_figure_1.pdf"), format="pdf")
+plt.savefig(output_dir / "example_figure_1.pdf", format="pdf")
 
-DES2 = neurodesign.design(
-    order=[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1], ITI=[2] * 20, experiment=EXP
+design_2 = neurodesign.design(
+    order=[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1],
+    ITI=[2] * 20,
+    experiment=exp,
 )
-DES2.designmatrix()
-DES2.FCalc(weights=[0.25, 0.25, 0.25, 0.25])
-print("Ff of Design 1: " + str(DES1.Ff))
-print("Ff of Design 2: " + str(DES2.Ff))
-print("Fd of Design 1: " + str(DES1.Fd))
-print("Fd of Design 2: " + str(DES2.Fd))
+design_2.designmatrix()
+design_2.FCalc(weights=[0.25, 0.25, 0.25, 0.25])
+print(f"Ff of Design 1: {str(design_1.Ff)}")
+print(f"Ff of Design 2: {str(design_2.Ff)}")
+print(f"Fd of Design 1: {str(design_1.Fd)}")
+print(f"Fd of Design 2: {str(design_2.Fd)}")
 
-DES3, DES4 = DES1.crossover(DES2, seed=2000)
-print(DES3.order)
-print(DES4.order)
+design_3, design_4 = design_1.crossover(design_2, seed=2000)
+print(design_3.order)
+print(design_4.order)
 
 
 order = neurodesign.generate.order(
-    nstim=4, ntrials=100, probabilities=[0.25, 0.25, 0.25, 0.25], ordertype="random", seed=1234
+    nstim=4,
+    ntrials=100,
+    probabilities=[0.25, 0.25, 0.25, 0.25],
+    ordertype="random",
+    seed=1234,
 )
 print(order[:10])
 Counter(order)
@@ -70,6 +76,11 @@
 )
 
 POP = neurodesign.optimisation(
-    experiment=EXP, weights=[0, 0.5, 0.25, 0.25], preruncycles=10, cycles=100, folder="./", seed=100
+    experiment=exp,
+    weights=[0, 0.5, 0.25, 0.25],
+    preruncycles=10,
+    cycles=100,
+    folder="./",
+    seed=100,
 )
 POP.optimise()

examples/compare_designs.py

@@ -0,0 +1,87 @@
+import neurodesign
+from neurodesign import generate
+
+# define experimental setup
+
+exp = neurodesign.experiment(
+    TR=2,
+    n_trials=20,
+    P=[0.3, 0.3, 0.4],
+    C=[[1, -1, 0], [0, 1, -1]],
+    n_stimuli=3,
+    rho=0.3,
+    stim_duration=1,
+    t_pre=0.5,
+    t_post=2,
+    ITImodel="exponential",
+    ITImin=2,
+    ITImax=4,
+    ITImean=2.1,
+)
+
+# define first design with a fixed ITI
+
+design_1 = neurodesign.design(
+    order=[0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1],
+    ITI=[2] * 20,
+    experiment=exp,
+)
+
+# expand to design matrix
+
+design_1.designmatrix()
+design_1.FCalc(weights=[0, 0.5, 0.25, 0.25])
+design_1.FdCalc()
+design_1.FcCalc()
+design_1.FfCalc()
+design_1.FeCalc()
+
+# define second design
+
+design_2 = neurodesign.design(
+    order=[0, 0, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2, 0, 1],
+    ITI=generate.iti(20, "exponential", min=1, mean=2, max=4, seed=1234)[0],
+    experiment=exp,
+)
+
+design_2.designmatrix()
+design_2.FeCalc()
+design_2.FdCalc()
+design_2.FcCalc()
+design_2.FfCalc()
+
+# crossover to obtain design 3 and 4
+
+design_3, design_4 = design_1.crossover(design_2, seed=2000)
+design_3.order
+design_4.order
+design_3.designmatrix()
+design_3.FeCalc()
+design_3.FdCalc()
+design_3.FcCalc()
+design_3.FfCalc()
+design_4.designmatrix()
+design_4.FeCalc()
+design_4.FdCalc()
+design_4.FcCalc()
+design_4.FfCalc()
+
+# mutate design
+DES5 = design_1.mutation(0.3, seed=2000)
+DES5.designmatrix()
+DES5.FeCalc()
+DES5.FdCalc()
+DES5.FcCalc()
+DES5.FfCalc()
+
+# compare detection power
+result = (
+    f" RESULTS \n ======= \n"
+    f"DESIGN 1: Fd = {design_1.Fd} \n"
+    f"DESIGN 2: Fd = {design_2.Fd} \n"
+    f"DESIGN 3: Fd = {design_3.Fd} \n"
+    f"DESIGN 4: Fd = {design_4.Fd} \n"
+    f"DESIGN 5: Fd = {DES5.Fd} \n"
+)
+
+print(result)