diff --git a/grainlearning/dynamic_systems.py b/grainlearning/dynamic_systems.py
index c5ad339..0e9e3e8 100644
--- a/grainlearning/dynamic_systems.py
+++ b/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)
diff --git a/grainlearning/inference.py b/grainlearning/inference.py
index 69a0a90..ab2b0c2 100644
--- a/grainlearning/inference.py
+++ b/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
diff --git a/grainlearning/sampling.py b/grainlearning/sampling.py
index 09d2d0b..0c05edd 100644
--- a/grainlearning/sampling.py
+++ b/grainlearning/sampling.py
@@ -91,14 +91,14 @@ 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,
         max_iter: int = 100,
         random_state: int = None,
-        init_params: str = "kmeans",
+        init_params: str = "k-means++",
         warm_start: bool = False,
         expand_factor: int = 10,
         slice_sampling: bool = False,
@@ -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