Merge branch 'fix_selftests' of github.com:GrainLearning/grainLearnin…

…g into fix_selftests

.github/workflows/build.yml

@@ -17,7 +17,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ['ubuntu-latest', 'macos-latest', 'windows-latest']
-        python-version: ['3.8', '3.9', '3.10']
+        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
 
     steps:
     - uses: actions/checkout@v3

grainlearning/dynamic_systems.py

@@ -179,7 +179,7 @@ def __init__(
         #### Uncertainty ####
 
         self.sigma_min =  1.0e-6
-        
+
         self.sigma_max = sigma_max
 
         self.sigma_tol = sigma_tol
@@ -383,7 +383,7 @@ class IODynamicSystem(DynamicSystem):
     :param inv_obs_weight: Inverse of the observation weight, defaults to None, optional
     :param param_data: Parameter data, defaults to None, optional
     :param sim_data: Simulation data, defaults to None, optional
-    :param sim_data_files: List pf simulation data files (num_samples), defaults to None, optional
+    :param sim_data_files: List of simulation data files (num_samples), defaults to None, optional
     """
 
     def __init__(
@@ -428,7 +428,7 @@ def __init__(
             param_names
         )
         # TODO: reuse initialization from base class
-        
+
         ##### Parameters #####
 
         self.num_params = len(param_names)

grainlearning/inference.py

@@ -66,8 +66,6 @@ def __init__(
 
         self.ess = None
 
-
-
     @classmethod
     def from_dict(cls: Type["SMC"], obj: dict):
         """Initialize the class using a dictionary style

grainlearning/sampling.py

@@ -91,8 +91,8 @@ class GaussianMixtureModel:
 
     def __init__(
         self,
-        max_num_components=0,
-        weight_concentration_prior: float = 0.2,
+        max_num_components = 0,
+        weight_concentration_prior: float = 0.0,
         covariance_type: str = "tied",
         n_init: int = 1,
         tol: float = 1.0e-5,
@@ -106,7 +106,7 @@ def __init__(
         """ Initialize the Gaussian Mixture Model class"""
         self.max_num_components = max_num_components
 
-        if weight_concentration_prior is None:
+        if not weight_concentration_prior:
             self.weight_concentration_prior = 1.0 / max_num_components
         else:
             self.weight_concentration_prior = weight_concentration_prior

pyproject.toml

@@ -12,13 +12,17 @@ license = "GPLv2"
 homepage = "https://grainlearning.readthedocs.io/"
 repository = "https://github.com/GrainLearning/grainLearning"
 keywords = ["Bayesian inference", "Uncertainty quantification", "Non-parametric Gaussian mixture", "DEM", "Constitutive modeling", "Granular materials"]
+packages = [
+    { include = "grainlearning"}
+]
 
 [tool.poetry.dependencies]
-python = ">=3.8,<3.11"
+python = ">=3.8,<3.12"
 numpy = "^1.23.2"
 scipy = "^1.9.1"
 scikit-learn = "^1.1.3"
 matplotlib = "^3.6.0"
+seaborn = '^0.12.2'
 
 Sphinx = {version = "^5.1.1", optional = true}
 sphinx-autodoc-typehints = {version = "^1.19.2", optional = true}
@@ -30,21 +34,16 @@ prospector = {version = "^1.7.6", optional = true, extras = ["with_pyroma"]}
 pyroma = {version = "^4.0", optional = true}
 h5py = {version ="^3.7.0", optional = true}
 wandb = {version ="^0.13.4", optional = true}
-tensorflow = {version ="2.10.0", optional = true}
+tensorflow = {version ="^2.10.0", optional = true}
 ipykernel = {version = "*", optional = true}
-seaborn = {version = '^0.12.2', optional = true}
 
 [tool.poetry.extras]
 docs = ["Sphinx", "sphinx-autodoc-typehints", "sphinx-mdinclude", "sphinx-rtd-theme"]
-dev = ["pytest", "pytest-cov", "prospector", "pyroma", "h5py"]
+dev = ["pytest", "pytest-cov", "prospector", "pyroma", "h5py", "tensorflow", "wandb"]
 rnn = ["wandb", "tensorflow"]
 tutorials = ["ipykernel"]
 visuals = ["seaborn"]
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
 build-backend = "poetry.core.masonry.api"
-
-packages = [
-    { include = "grainlearning"}
-]