checked testpypi

pyproject.toml

@@ -10,12 +10,15 @@ authors = [
 description = "A python package for inducing membership functions from labeled data"
 keywords = ["fuzzy set", "fuzzy membership", "machine learning"]
 readme = "README.md"
-requires-python = ">=3.6"
+requires-python = ">=3.8"
 dependencies = [
+  "gurobipy",
   "json_fix",
-  "numpy",
+  "numpy<2.0",
+  "tqdm",
   "scipy",
-  "scikit-learn"
+  "scikit-learn",
+  "tensorflow==2.17"
 ]
 license = {text = "Apache-2.0"}
 classifiers = [
@@ -26,10 +29,6 @@ classifiers = [
 
 dynamic = ['version']
 
-[project.optional-dependencies]
-gurobi = ["gurobipy"]
-tensorflow = ["tensorflow"]
-
 [project.urls]
 Homepage = "https://github.com/dariomalchiodi/mulearn"
 Documentation = "https://mulearn-mr.readthedocs.io/"

src/mulearn/__init__.py

@@ -1,4 +1,4 @@
-__version__ = '0.3.2'
+__version__ = '0.3.9'
 
 
 import copy

src/mulearn/optimization.py

@@ -8,10 +8,6 @@
 Note that at least one of these libraries is needed in order to solve the
 optimization problems involved in the fuzzy inference process.
 
-The module also checks the availability of tqdm, which is used in order to
-graphically depict the progress of some learning processes using a progress
-bar. However, this package is not strictly needed: if it is not installed,
-the above mentioned progress bars will not be displayed.
 """
 
 import numpy as np
@@ -37,7 +33,6 @@
     import os
 
     os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
-    logging.getLogger('tensorflow').setLevel(logging.FATAL)
     import tensorflow as tf
 
     tensorflow_ok = True