Bump versions

.github/workflows/ci.yml

@@ -16,12 +16,12 @@ on:
 # A workflow run is made up of one or more jobs that can run sequentially or in parallel
 jobs:
   build-py:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-latest
 
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.7, 3.8, 3.9, '3.10']
+        python-version: [3.8, 3.9, '3.10', 3.11]
 
     env:
       UCI_DB: "https://archive.ics.uci.edu/ml/machine-learning-databases"
@@ -70,12 +70,12 @@ jobs:
         run: pytest tests --cov=aif360 --cov-report=term-missing
 
   build-r:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-latest
 
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.7, 3.8, 3.9, '3.10']
+        python-version: [3.8, 3.9, '3.10', 3.11]
 
     steps:
       - name: Check out repo

README.md

@@ -76,9 +76,9 @@ Supported Python Configurations:
 
 | OS      | Python version |
 | ------- | -------------- |
-| macOS   | 3.7 – 3.10     |
-| Ubuntu  | 3.7 – 3.10     |
-| Windows | 3.7 – 3.10     |
+| macOS   | 3.8 – 3.11     |
+| Ubuntu  | 3.8 – 3.11     |
+| Windows | 3.8 – 3.11     |
 
 ### (Optional) Create a virtual environment
 
@@ -95,10 +95,10 @@ is sufficient (see [the difference between Anaconda and
 Miniconda](https://conda.io/docs/user-guide/install/download.html#anaconda-or-miniconda)
 if you are curious) if you do not already have conda installed.
 
-Then, to create a new Python 3.7 environment, run:
+Then, to create a new Python 3.11 environment, run:
 
 ```bash
-conda create --name aif360 python=3.7
+conda create --name aif360 python=3.11
 conda activate aif360
 ```
 
@@ -110,9 +110,6 @@ The shell should now look like `(aif360) $`. To deactivate the environment, run:
 
 The prompt will return to `$ `.
 
-Note: Older versions of conda may use `source activate aif360` and `source
-deactivate` (`activate aif360` and `deactivate` on Windows).
-
 ### Install with `pip`
 
 To install the latest stable version from PyPI, run:

aif360/aif360-r/R/utils.R

@@ -20,7 +20,7 @@
 #'   only occur within RStudio).
 #'
 #' @param conda_python_version the python version installed in the created conda
-#'   environment. Python 3.6 is installed by default.
+#'   environment. Python 3.11 is installed by default.
 #'
 #' @param ... other arguments passed to [reticulate::conda_install()] or
 #'   [reticulate::virtualenv_install()].
@@ -33,13 +33,13 @@ install_aif360 <- function(method = c("auto", "virtualenv", "conda"),
                                envname = NULL,
                                extra_packages = NULL,
                                restart_session = TRUE,
-                               conda_python_version = "3.7",
+                               conda_python_version = "3.11",
                                ...) {
 
   method <- match.arg(method)
 
   reticulate::py_install(
-    packages       = c("aif360", "numba", "BlackBoxAuditing", "tensorflow>=1.13.1,<2", "pandas", 
+    packages       = c("aif360", "numba", "BlackBoxAuditing", "tensorflow>=1.13.1,<2", "pandas",
                        "fairlearn==0.4.6", "protobuf==3.20.1"),
     envname        = envname,
     method         = method,

aif360/algorithms/postprocessing/eq_odds_postprocessing.py

@@ -143,29 +143,29 @@ def fit(self, dataset_true, dataset_pred):
 
         sm_tn = np.logical_and(sflip,
             y_true[cond_vec_priv] == dataset_true.unfavorable_label,
-            dtype=np.float64)
+            ).astype(np.float64)
         sm_fn = np.logical_and(sflip,
             y_true[cond_vec_priv] == dataset_true.favorable_label,
-            dtype=np.float64)
+            ).astype(np.float64)
         sm_fp = np.logical_and(sconst,
             y_true[cond_vec_priv] == dataset_true.unfavorable_label,
-            dtype=np.float64)
+            ).astype(np.float64)
         sm_tp = np.logical_and(sconst,
             y_true[cond_vec_priv] == dataset_true.favorable_label,
-            dtype=np.float64)
+            ).astype(np.float64)
 
         om_tn = np.logical_and(oflip,
             y_true[cond_vec_unpriv] == dataset_true.unfavorable_label,
-            dtype=np.float64)
+            ).astype(np.float64)
         om_fn = np.logical_and(oflip,
             y_true[cond_vec_unpriv] == dataset_true.favorable_label,
-            dtype=np.float64)
+            ).astype(np.float64)
         om_fp = np.logical_and(oconst,
             y_true[cond_vec_unpriv] == dataset_true.unfavorable_label,
-            dtype=np.float64)
+            ).astype(np.float64)
         om_tp = np.logical_and(oconst,
             y_true[cond_vec_unpriv] == dataset_true.favorable_label,
-            dtype=np.float64)
+            ).astype(np.float64)
 
         # A_eq - 2-D array which, when matrix-multiplied by x,
         # gives the values of the equality constraints at x

setup.py

@@ -39,7 +39,7 @@
       long_description_content_type='text/markdown',
       license='Apache License 2.0',
       packages=[pkg for pkg in find_packages() if pkg.startswith('aif360')],
-      python_requires='>=3.7',
+      python_requires='>=3.8',
       install_requires=[
           'numpy>=1.16',
           'scipy>=1.2.0',

tests/sklearn/test_datasets.py

@@ -233,7 +233,7 @@ def test_cache_meps(panel):
     meps_raw = fetch_meps(panel, cache=False, accept_terms=True)[0]
     fetch_meps(panel, cache=True, accept_terms=True)
     meps_cached = fetch_meps(panel, cache=True)[0]
-    assert_frame_equal(meps_raw, meps_cached, check_dtype=False)
+    assert_frame_equal(meps_raw, meps_cached, check_dtype=False, check_categorical=False)
     assert_array_equal(meps_raw.to_numpy(), meps_cached.to_numpy())
 
 @pytest.mark.parametrize(