Fix warnings

Author: patnr

pipt/loop/assimilation.py

@@ -41,11 +41,6 @@ class Assimilate:
     def __init__(self, ensemble: Ensemble):
         """
         Initialize by passing the PIPT init. file up the hierarchy.
-
-        Parameters
-        ----------
-        init_file : str
-            PIPT init. filename
         """
         # Internalize ensemble and simulator class instances
         self.ensemble = ensemble
@@ -442,11 +437,6 @@ def calc_forecast(self):
                 > check_sim_end
                 > get_sim_results
 
-        Parameters
-        ----------
-        assim_step : int
-            Current assimilation step.
-
         Notes
         -----
         Parallel run in "ampersand" mode means that it will be started in the background and run independently of the

pipt/misc_tools/analysis_tools.py

@@ -1327,7 +1327,7 @@ def resample_state(aug_state, state, list_state, new_en_size):
 
     Parameters
     ----------
-    aug_upd_state : ndarray
+    aug_state : ndarray
         Augmented matrix of state variables
     state : dict
         Dict. af state variables

pipt/update_schemes/enkf.py

@@ -27,12 +27,6 @@ def __init__(self, keys_da, keys_fwd, sim):
         """
         The class is initialized by passing the PIPT init. file upwards in the hierarchy to be read and parsed in
         `pipt.input_output.pipt_init.ReadInitFile`.
-
-        Parameters
-        ----------
-        init_file : str
-            PIPT init. file containing info. to run the inversion algorithm
-
         """
         # Pass the init_file upwards in the hierarchy
         super().__init__(keys_da, keys_fwd, sim)

pipt/update_schemes/enrml.py

@@ -50,11 +50,6 @@ def __init__(self, keys_da, keys_fwd, sim):
         """
         The class is initialized by passing the PIPT init. file upwards in the hierarchy to be read and parsed in
         `pipt.input_output.pipt_init.ReadInitFile`.
-
-        Parameters
-        ----------
-        init_file : str
-            PIPT init. file containing info. to run the inversion algorithm
         """
         # Pass the init_file upwards in the hierarchy
         super().__init__(keys_da, keys_fwd, sim)
@@ -310,11 +305,6 @@ def __init__(self, keys_da, keys_fwd, sim):
         """
         The class is initialized by passing the PIPT init. file upwards in the hierarchy to be read and parsed in
         `pipt.input_output.pipt_init.ReadInitFile`.
-
-        Parameters
-        ----------
-        init_file : str
-            PIPT init. file containing info. to run the inversion algorithm
         """
         # Pass the init_file upwards in the hierarchy
         super().__init__(keys_da, keys_fwd, sim)
@@ -668,11 +658,6 @@ def __init__(self, keys_da):
         The class is initialized by passing the PIPT init. file upwards in the hierarchy to be read and parsed in
         `pipt.input_output.pipt_init.ReadInitFile`.
 
-        Parameters
-        ----------
-        init_file : str
-            PIPT init. file containing info. to run the inversion algorithm
-
         References
         ----------
         [1] Chen Y. & Oliver D.S. 2013, Levenberg-Marquardt Forms of the Iterative Ensemble Smoother for Efficient
@@ -685,7 +670,7 @@ def calc_analysis(self):
         """
         Calculate the update step in approximate LM-EnRML code.
 
-        Parameters
+        Attributes
         ----------
         iteration : int
             Iteration number
@@ -822,11 +807,6 @@ def __init__(self, keys_da):
         The class is initialized by passing the PIPT init. file upwards in the hierarchy to be read and parsed in
         `pipt.input_output.pipt_init.ReadInitFile`.
 
-        Parameters
-        ----------
-        init_file : str
-            PIPT init. file containing info. to run the inversion algorithm
-
         References
         ----------
         [1] Raanes, P. N., Stordal, A. S., & Evensen, G. (2019). Revising the stochastic iterative ensemble smoother.
@@ -1005,17 +985,6 @@ def check_convergence(self):
         Check if GN-EnRML have converged based on evaluation of change sizes of objective function, state and damping
         parameter. Very similar to original function, but exit if there is no reduction in obj. function.
 
-        Parameters
-        ----------
-        prev_data_misfit : float
-            Data misfit calculated from the previous update.
-
-        step : float
-            Step size.
-
-        lam : float
-            LM damping parameter.
-
         Returns
         -------
         conv : bool

pipt/update_schemes/es.py

@@ -25,11 +25,6 @@ def __init__(self, keys_da, keys_fwd, sim):
         """
         The class is initialized by passing the PIPT init. file upwards in the hierarchy to be read and parsed in
         `pipt.input_output.pipt_init.ReadInitFile`.
-
-        Parameters
-        ----------
-        init_file : str
-            PIPT init. file containing info. to run the inversion algorithm
         """
         # Pass init. file to Simultaneous parent class (Python searches parent classes from left to right).
         super().__init__(keys_da, keys_fwd, sim)

pipt/update_schemes/esmda.py

@@ -86,11 +86,6 @@ def calc_analysis(self):
         covariance matrix is inflated with an inflation parameter alpha. The update is done as an iterative smoother
         where all data is assimilated at once.
 
-        Parameters
-        ----------
-        assim_step : int
-            Current assimilation step
-
         Notes
         -----
         ES-MDA is an iterative ensemble smoother with a predefined number of iterations, where the updates is done with
@@ -343,11 +338,6 @@ def __init__(self, keys_da):
         The class is initialized by passing the PIPT init. file upwards in the hierarchy to be read and parsed in
         `pipt.input_output.pipt_init.ReadInitFile`.
 
-        Parameters
-        ----------
-        init_file : str
-            PIPT init. file containing info. to run the inversion algorithm
-
         References
         ----------
         [1] J. Rafiee & A. Reynolds, Inverse Problems 33 (11), 2017

popt/cost_functions/ren_npv.py

@@ -9,16 +9,16 @@ def ren_npv(pred_data, kwargs):
 
     Parameters
     ----------
-    pred_data_en : ndarray
+    pred_data : ndarray
         Ensemble of predicted data.
 
     **kwargs : dict
         Other arguments sent to the npv function
 
-        keys_opt : list
+        - keys_opt (list)
             Keys with economic data.
 
-        report : list
+        - report (list)
             Report dates.
 
     Returns

popt/loop/dist.py

@@ -315,8 +315,9 @@ def delA(theta):
 
     Parameters
     --------------------------------------------
-    a : float
-    b : float
+    theta : tuple
+        - a : float
+        - b : float
     
     Returns
     --------------------------------------------

popt/update_schemes/cma.py

@@ -107,23 +107,23 @@ def __call__(self, cov, step, X, J):
 
         Parameters
         --------------------------------------------------
-            cov : array_like, of shape (d, d)
-                Current covariance or correlation matrix.
-            
-            step : array_like, of shape (d,)
-                New step of control vector.
-                Used to update the evolution path.
+        cov : array_like, of shape (d, d)
+            Current covariance or correlation matrix.
+        
+        step : array_like, of shape (d,)
+            New step of control vector.
+            Used to update the evolution path.
 
-            X : array_like, of shape (n, d)
-                Control ensemble of size n.
-            
-            J : array_like, of shape (n,)
-                Objective ensemble of size n.
+        X : array_like, of shape (n, d)
+            Control ensemble of size n.
+        
+        J : array_like, of shape (n,)
+            Objective ensemble of size n.
         
         Returns
         --------------------------------------------------
-            out : array_like, of shape (d, d)
-                CMA updated covariance (correlation) matrix.
+        out : array_like, of shape (d, d)
+            CMA updated covariance (correlation) matrix.
         '''
         a_mu  = self.alpha_mu
         a_one = self.alpha_1 

simulator/eclipse.py

@@ -216,7 +216,7 @@ def setup_fwd_run(self, **kwargs):
         """
         Setup the simulator.
 
-        Parameters
+        Attributes
         ----------
         assimIndex : int
             Gives the index-type (e.g. step,time,etc.) and the index for the
@@ -360,7 +360,7 @@ def coarsen(self, folder, ensembleMember=None):
 
         Parameters
         ----------
-        Folder : str, optional
+        folder : str, optional
             Path to the ecl_100 run folder.
 
         ensembleMember : int, optional
@@ -796,22 +796,16 @@ def get_sim_results(self, whichResponse, ext_data_info=None, member=None):
 
         Parameters
         ----------
-        file_rsm : str
-            Summary file from ECL 100.
-
-        file_rst : str
-            Restart file from ECL 100.
-
         whichResponse : str
             Which of the responses is to be outputted (e.g., WBHP PRO-1, WOPR, PRESS, OILSAT, etc).
 
-        member : int, optional
-            Ensemble member that is finished.
-
         ext_data_info : tuple, optional
             Tuple containing the assimilation step information, including the place of assimilation (e.g., which TIME) and the
             index of this assimilation place.
 
+        member : int, optional
+            Ensemble member that is finished.
+
         Returns
         -------
         yFlow : array-like
@@ -1028,10 +1022,10 @@ def call_sim(self, path=None, wait_for_proc=False):
 
         Parameters
         ----------
-        Path : str
+        path : str
             Alternative folder for the ecl_100.data file.
 
-        Wait_for_proc : bool, optional
+        wait_for_proc : bool, optional
             Logical variable to wait for the simulator to finish. Default is False.
 
         Returns
@@ -1087,14 +1081,14 @@ def call_sim(self, path=None, wait_for_proc=False):
 
         Parameters
         ----------
-        Path : str
+        path : str
             Alternative folder for the ecl_100.data file.
 
-        Wait_for_proc : bool, optional
+        wait_for_proc : bool, optional
             Logical variable to wait for the simulator to finish. Default is False.
 
-        !!! note
-            For now, this option is only utilized in a single localization option.
+            !!! note
+                For now, this option is only utilized in a single localization option.
 
         Returns
         -------