update: fix dependency (#65)

* update: fix dependency

* fix: update CI

* fix: CI check 3.9

* fix: painted it black

* fix: correct install in CI

* fix: update poetry lock

* fix: update code to new numpy version

---------

Co-authored-by: Sylvain Chevallier <[email protected]>

.github/workflows/test_lint.yml

@@ -13,31 +13,34 @@ jobs:
     strategy:
       fail-fast: true
       matrix:
-        python_version: [3.7, 3.8, 3.9]
+        python_version: [3.9]
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
+
       - name: "Setup Python"
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python_version }}
-      - uses: pre-commit/[email protected]
-      - name: "Install dependencies"
-        shell: bash
-        run: |
-          python -m pip install --upgrade pip poetry wheel flake8 coverage
-          poetry config virtualenvs.create false
-          poetry install
-      - name: "Check style"
-        shell: bash
-        run: |
-          flake8
+
+      - uses: pre-commit/[email protected]
+
+      - name: Install Poetry
+        uses: snok/install-poetry@v1
+        with:
+          virtualenvs-create: true
+          virtualenvs-in-project: true
+
+      - name: Install MDLA
+        run: poetry install --no-interaction --with dev
+
       - name: "Run tests"
         shell: bash
         run: |
-          pytest --cov=./ --cov-report=xml
+          poetry run pytest --cov=./ --cov-report=xml
+
       - name: "Coverage"
-        uses: codecov/codecov-action@v1
+        uses: codecov/codecov-action@v3
         with:
           files: ./coverage.xml
           flags: unittests

.pre-commit-config.yaml

@@ -10,21 +10,31 @@ repos:
       - id: mixed-line-ending
 
   - repo: https://github.com/psf/black
-    rev: 20.8b1
+    rev: 23.9.1
     hooks:
       - id: black
-        language_version: python
+        language_version: python3.9
 
-  - repo: https://github.com/pycqa/isort
-    rev: 5.7.0
+  - repo: https://github.com/PyCQA/isort
+    rev: 5.12.0
     hooks:
       - id: isort
 
-  - repo: https://gitlab.com/pycqa/flake8
-    rev: 3.9.0
+  - repo: https://github.com/PyCQA/flake8
+    rev: 6.1.0
     hooks:
       - id: flake8
-        additional_dependencies: [flake8-bugbear]
+        additional_dependencies:
+          [
+            "flake8-blind-except",
+            "flake8-docstrings",
+            "flake8-bugbear",
+            "flake8-comprehensions",
+            "flake8-docstrings",
+            "flake8-implicit-str-concat",
+            "pydocstyle>=5.0.0",
+          ]
+        exclude: ^docs/ | ^setup\.py$ |
 
   - repo: https://github.com/pre-commit/mirrors-prettier
     rev: v2.2.1

mdla/mdla.py

@@ -51,7 +51,7 @@ def _get_learning_rate(iteration, max_iteration, learning_rate):
         return 0.0
     last_iterations = np.floor(max_iteration * 2.0 / 3.0)
     if iteration >= last_iterations:
-        return last_iterations ** learning_rate
+        return last_iterations**learning_rate
     else:
         return (iteration + 1) ** learning_rate
 
@@ -107,7 +107,7 @@ def _multivariate_OMP(signal, dictionary, n_nonzero_coefs=None, verbose=False):
     if verbose >= 4:
         print("[M-OMP # 0 ] signal is")
         print(residual)
-    Ainv = np.zeros((n_kernels, n_kernels), np.float)
+    Ainv = np.zeros((n_kernels, n_kernels), float)
     Ainv[0, 0] = 1.0
 
     # First iteration
@@ -145,8 +145,8 @@ def _multivariate_OMP(signal, dictionary, n_nonzero_coefs=None, verbose=False):
         print("[M-OMP # 0 ] residual is now")
         print(residual)
 
-    signal_energy = (signal ** 2).sum(1).mean()
-    residual_energy = (residual ** 2).sum(1).mean()
+    signal_energy = (signal**2).sum(1).mean()
+    residual_energy = (residual**2).sum(1).mean()
 
     if verbose >= 3:
         print(
@@ -213,7 +213,7 @@ def _multivariate_OMP(signal, dictionary, n_nonzero_coefs=None, verbose=False):
         Ainv[0:atoms_in_estimate, atoms_in_estimate : atoms_in_estimate + 1] = -beta * b
         Ainv[atoms_in_estimate, atoms_in_estimate] = beta
         decomposition[atoms_in_estimate] = np.array(
-            [alpha, k_off, k_selected], dtype=np.float64
+            alpha.flatten().tolist() + [k_off, k_selected], dtype=np.float64
         )
         atoms_in_estimate += 1
         selected_list = np.vstack((selected_list, selected_atom.flatten()))
@@ -230,7 +230,7 @@ def _multivariate_OMP(signal, dictionary, n_nonzero_coefs=None, verbose=False):
         residual = signal - estimated_signal
 
         if verbose >= 3:
-            residual_energy = (residual ** 2).sum(1).mean()
+            residual_energy = (residual**2).sum(1).mean()
             print(
                 "[M-OMP #",
                 atoms_in_estimate - 1,
@@ -1335,7 +1335,6 @@ def __init__(
         random_state=None,
         callback=None,
     ):
-
         self._set_mdla_params(
             n_kernels, n_nonzero_coefs, kernel_init_len, n_jobs, learning_rate
         )
@@ -1504,7 +1503,6 @@ def __init__(
         learning_rate=None,
         callback=None,
     ):
-
         self._set_mdla_params(
             n_kernels, n_nonzero_coefs, kernel_init_len, n_jobs, learning_rate
         )