diff --git a/epde/globals.py b/epde/globals.py
index 24adf7f..825ae9e 100644
--- a/epde/globals.py
+++ b/epde/globals.py
@@ -86,11 +86,12 @@ class VerboseManager:
     show_iter_idx : bool
     iter_fitness : bool
     iter_stats : bool
+    show_ann_loss : bool    
     show_warnings : bool
     
 def init_verbose(plot_DE_solutions : bool = False, show_iter_idx : bool = True, 
                  show_iter_fitness : bool = False, show_iter_stats : bool = False, 
-                 show_warnings : bool = False):
+                 show_ann_loss : bool = False, show_warnings : bool = False):
     """
     Method for initialized of manager for output in text form
 
@@ -110,4 +111,4 @@ def init_verbose(plot_DE_solutions : bool = False, show_iter_idx : bool = True,
     if not show_warnings:
         warnings.filterwarnings("ignore")
     verbose = VerboseManager(plot_DE_solutions, show_iter_idx, show_iter_fitness, 
-                             show_iter_stats, show_warnings)
+                             show_iter_stats, show_ann_loss, show_warnings)
diff --git a/epde/optimizers/moeadd/moeadd.py b/epde/optimizers/moeadd/moeadd.py
index 34db2ac..22fcc5a 100644
--- a/epde/optimizers/moeadd/moeadd.py
+++ b/epde/optimizers/moeadd/moeadd.py
@@ -6,8 +6,13 @@
 
 import numpy as np
 import warnings
+from itertools import chain
 
 from typing import Union
+
+def flatten_chain(matrix):
+    return list(chain.from_iterable(matrix))
+
 # from copy import deepcopy
 # from functools import reduce
 
@@ -154,7 +159,8 @@ def delete_point(self, point):
         self.population = population_cleared
 
     def get_stats(self):
-        return np.array([[element.obj_fun for element in level] for level in self.levels])
+        return np.array(flatten_chain([[element.obj_fun for element in level] 
+                                       for level in self.levels]))
 
     def fit_convex_hull(self):
         """
@@ -448,4 +454,4 @@ def plot_pareto(self, dimensions:list, **visualizer_kwargs):
         assert len(dimensions) == 2, 'Current approach supports only two dimensional plots'
         visualizer = ParetoVisualizer(self.pareto_levels)
         visualizer.plot_pareto(dimensions = dimensions, **visualizer_kwargs)
-        
\ No newline at end of file
+        
diff --git a/epde/preprocessing/smoothers.py b/epde/preprocessing/smoothers.py
index 88a7a30..927ef10 100644
--- a/epde/preprocessing/smoothers.py
+++ b/epde/preprocessing/smoothers.py
@@ -14,6 +14,7 @@
 import torch
 device = torch.device('cpu')
 
+import epde.globals as global_var
 
 class AbstractSmoother(ABC):
     def __init__(self, *args, **kwargs):
@@ -89,7 +90,8 @@ def __call__(self, data, grid, epochs_max=1e3, loss_mean=1000, batch_frac=0.5,
             if loss_mean < min_loss:
                 best_model = model
                 min_loss = loss_mean
-            print('Surface training t={}, loss={}'.format(t, loss_mean))
+            if global_var.verbose.show_ann_loss:
+                print('Surface training t={}, loss={}'.format(t, loss_mean))
             t += 1
 
         data_approx = best_model(grid_flattened).detach().numpy().reshape(original_shape)
diff --git a/epde/supplementary.py b/epde/supplementary.py
index 7cb0b4a..1570336 100644
--- a/epde/supplementary.py
+++ b/epde/supplementary.py
@@ -13,6 +13,7 @@
 device = torch.device('cpu')
 
 import matplotlib.pyplot as plt
+import epde.globals as global_var
 
 def exp_form(a, sign_num: int = 4):
     if np.isclose(a, 0):
@@ -95,7 +96,8 @@ def train_ann(grids: list, data: np.ndarray, epochs_max: int = 500):
             best_model = model
             min_loss = loss_mean
         losses.append(loss_mean)
-        print('Surface training t={}, loss={}'.format(t, loss_mean))
+        if global_var.verbose.show_ann_loss:
+            print('Surface training t={}, loss={}'.format(t, loss_mean))
         t += 1
     print_loss = True
     if print_loss:
diff --git a/setup.py b/setup.py
index f76cb16..28b5f54 100644
--- a/setup.py
+++ b/setup.py
@@ -11,10 +11,11 @@
 from pathlib import Path
 import pathlib
 
-here = pathlib.Path(__file__).parent.resolve()
+HERE = pathlib.Path(__file__).parent.resolve()
+README = Path(HERE, 'README.rst').read_text(encoding='utf-8')
+SHORT_DESCRIPTION = 'Data-driven dynamical system and differential equations discovery framework'
 
 # Get the long description from the README file
-long_description = (here / 'README.rst').read_text(encoding='utf-8')
 
 
 def read(*names, **kwargs):
@@ -35,8 +36,10 @@ def get_requirements():
 
 setup(
       name = 'epde',
-      version = '1.2.9',
-      description = 'EPDE package',
+      version = '1.2.14',
+      description = SHORT_DESCRIPTION,
+      long_description="PLACEHOLDER",
+#      long_description_content_type='text/x-rst',
       author = 'Mikhail Maslyaev',
       author_email = 'miklemas@list.ru',
       classifiers = [      
@@ -45,7 +48,7 @@ def get_requirements():
               'License :: OSI Approved :: MIT License',
               'Operating System :: OS Independent',
       ],
-      packages = find_packages(include = ['epde', 'epde.cache', 'epde.interface', 'epde.moeadd', 
+      packages = find_packages(include = ['epde', 'epde.cache', 'epde.interface', 
                                           'epde.optimizers', 'epde.optimizers.moeadd', 
                                           'epde.optimizers.single_criterion', 'epde.operators.common',
                                           'epde.operators', 'epde.operators.utils',
@@ -54,5 +57,5 @@ def get_requirements():
                                           'epde.operators.singleobjective', 'epde.preprocessing', 
                                           'epde.parametric', 'epde.structure', 'epde.solver']),
       include_package_data = True,                               
-      python_requires =' >=3.8'
+      python_requires =' >=3.8',
       )