Ci update

.github/workflows/ci-build.yml

@@ -16,21 +16,12 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, macos-latest]
-        python-version: [3.8]
+        python-version: ["3.10"]
 
     steps:
       - name: Checkout
         uses: actions/checkout@v2
 
-      - name: Report WPS Errors
-        uses: wemake-services/wemake-python-styleguide@0.14.1
-        continue-on-error: true
-        with:
-          reporter: 'github-pr-review'
-          path: './modopt'
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-
       - name: Set up Conda with Python ${{ matrix.python-version }}
         uses: conda-incubator/setup-miniconda@v2
         with:
@@ -98,7 +89,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, macos-latest]
-        python-version: [3.6, 3.7, 3.9]
+        python-version: ["3.7", "3.8", "3.9"]
 
     steps:
       - name: Checkout

README.md

@@ -37,11 +37,11 @@ All packages required by ModOpt should be installed automatically. Optional pack
 In order to run the code in this repository the following packages must be
 installed:
 
-* [Python](https://www.python.org/) [> 3.6]
+* [Python](https://www.python.org/) [> 3.7]
 * [importlib_metadata](https://importlib-metadata.readthedocs.io/en/latest/) [==3.7.0]
 * [Numpy](http://www.numpy.org/) [==1.19.5]
 * [Scipy](http://www.scipy.org/) [==1.5.4]
-* [tqdm]([https://progressbar-2.readthedocs.io/](https://tqdm.github.io/) [>=4.64.0]
+* [tqdm](https://tqdm.github.io/) [>=4.64.0]
 
 ### Optional Packages
 

develop.txt

@@ -1,10 +1,8 @@
 coverage>=5.5
-flake8>=4
-nose>=1.3.7
 pytest>=6.2.2
 pytest-cov>=2.11.1
-pytest-pep8>=1.0.6
 pytest-emoji>=0.2.0
-pytest-flake8>=1.0.7
-wemake-python-styleguide>=0.15.2
 pytest-pydocstyle>=2.2.0
+black
+isort
+pytest-black

modopt/signal/filter.py

@@ -73,8 +73,8 @@ def mex_hat(data_point, sigma):
     Examples
     --------
     >>> from modopt.signal.filter import mex_hat
-    >>> mex_hat(2, 1)
-    -0.3521390522571337
+    >>> round(mex_hat(2, 1), 15)
+    -0.352139052257134
 
     """
     data_point = check_float(data_point)
@@ -108,8 +108,8 @@ def mex_hat_dir(data_gauss, data_mex, sigma):
     Examples
     --------
     >>> from modopt.signal.filter import mex_hat_dir
-    >>> mex_hat_dir(1, 2, 1)
-    0.17606952612856686
+    >>> round(mex_hat_dir(1, 2, 1), 16)
+    0.1760695261285668
 
     """
     data_gauss = check_float(data_gauss)

modopt/signal/positivity.py

@@ -48,7 +48,7 @@ def pos_recursive(input_data):
 
     """
     if input_data.dtype == 'O':
-        res = np.array([pos_recursive(elem) for elem in input_data])
+        res = np.array([pos_recursive(elem) for elem in input_data], dtype="object")
 
     else:
         res = pos_thresh(input_data)

modopt/signal/svd.py

@@ -57,7 +57,7 @@ def find_n_pc(u_vec, factor=0.5):
         )
 
     # Get the shape of the array
-    array_shape = np.repeat(np.int(np.sqrt(u_vec.shape[0])), 2)
+    array_shape = np.repeat(int(np.sqrt(u_vec.shape[0])), 2)
 
     # Find the auto correlation of the left singular vector.
     u_auto = [
@@ -299,7 +299,7 @@ def svd_thresh_coef(input_data, operator, threshold, thresh_type='hard'):
     a_matrix = np.dot(s_values, v_vec)
 
     # Get the shape of the array
-    array_shape = np.repeat(np.int(np.sqrt(u_vec.shape[0])), 2)
+    array_shape = np.repeat(int(np.sqrt(u_vec.shape[0])), 2)
 
     # Compute threshold matrix.
     ti = np.array([

setup.cfg

@@ -84,7 +84,6 @@ testpaths =
 addopts =
   --verbose
   --emoji
-  --flake8
   --cov=modopt
   --cov-report=term
   --cov-report=xml

setup.py

@@ -20,7 +20,7 @@
 license = 'MIT'
 
 # Set the package classifiers
-python_versions_supported = ['3.6', '3.7', '3.8', '3.9']
+python_versions_supported = ['3.7', '3.8', '3.9', '3.10', '3.11']
 os_platforms_supported = ['Unix', 'MacOS']
 
 lc_str = 'License :: OSI Approved :: {0} License'