diff --git a/gempy/assets/kriging.py b/gempy/assets/kriging.py
index 44440ec45..062a3e3c1 100644
--- a/gempy/assets/kriging.py
+++ b/gempy/assets/kriging.py
@@ -14,6 +14,9 @@
 
 import numpy as np
 import pandas as pd
+from gempy.plot import visualization_2d, plot, helpers
+import matplotlib.cm as cm
+import matplotlib.pyplot as plt
 
 class kriging_model(object):
 
@@ -456,7 +459,7 @@ def create_gaussian_field(self):
 
         self.results_sim_df = pd.DataFrame(data=d)
 
-    def plot_results():
+    def plot_results_dep():
         # probably set of functions for visualization
         # some brainstorming:
         # 1) 3D and 2D options for domain with colormaps of property
@@ -465,3 +468,69 @@ def plot_results():
         # 4) options to plot variances
         # ...
         return None
+
+    def plot_results(self, geo_data, prop='val', direction='y', cell_number=0, contour=False,
+                     cmap='viridis', alpha=0, legend=False):
+        """
+        TODO WRITE DOCSTRING
+        Args:
+            geo_data:
+            prop:
+            direction:
+            cell_number:
+            contour:
+            cmap:
+            alpha:
+            legend:
+
+        Returns:
+
+        """
+        a = np.full_like(self.mask, np.nan, dtype=np.double)
+        est_vals = self.results_df['est_value'].values
+        est_var = self.results_df['est_variance'].values
+
+        if prop == 'val':
+            a[np.where(self.mask == True)] = est_vals
+        elif prop == 'var':
+            a[np.where(self.mask == True)] = est_var
+        elif prop == 'both':
+            a[np.where(self.mask == True)] = est_vals
+            b = np.full_like(self.mask, np.nan, dtype=np.double)
+            b[np.where(self.mask == True)] = est_var
+        else:
+            print('prop must be val var or both')
+
+        p = visualization_2d.PlotSolution(geo_data)
+        _a, _b, _c, extent_val, x, y = p._slice(direction, cell_number)[:-2]
+
+        cmap = cm.get_cmap(cmap)
+        cmap.set_bad(color='w', alpha=alpha)
+
+        if prop is not 'both':
+
+            plot.plot_section(geo_data, direction=direction, cell_number=cell_number)
+            if contour == True:
+                im = plt.contourf(a.reshape(self.sol.grid.regular_grid.resolution)[_a, _b, _c].T, cmap=cmap,
+                                  origin='lower',
+                                  extent=extent_val)
+            else:
+                im = plt.imshow(a.reshape(self.sol.grid.regular_grid.resolution)[_a, _b, _c].T, cmap=cmap,
+                                origin='lower',
+                                extent=extent_val)
+                if legend:
+                    helpers.add_colorbar(im, location='right')
+
+        else:
+            f, ax = plt.subplots(1, 2, sharex=True, sharey=True)
+            ax[0].title.set_text('Estimated value')
+            im1 = ax[0].imshow(a.reshape(self.sol.grid.regular_grid.resolution)[:, 2, :].T, cmap=cmap,
+                               origin='lower',
+                               extent=self.sol.grid.regular_grid.extent[[0, 1, 4, 5]])
+            helpers.add_colorbar(im1)
+            ax[1].title.set_text('Variance')
+            im2 = ax[1].imshow(b.reshape(self.sol.grid.regular_grid.resolution)[:, 2, :].T, cmap=cmap,
+                               origin='lower',
+                               extent=self.sol.grid.regular_grid.extent[[0, 1, 4, 5]])
+            helpers.add_colorbar(im2)
+            plt.tight_layout()
diff --git a/notebooks/kriging_examples/Plotting options.ipynb b/notebooks/kriging_examples/Plotting options.ipynb
index a57f68d1b..94a4fa80c 100644
--- a/notebooks/kriging_examples/Plotting options.ipynb	
+++ b/notebooks/kriging_examples/Plotting options.ipynb	
@@ -47,7 +47,7 @@
    ],
    "source": [
     "# set resolution, extent and input data\n",
-    "geo_data = gp.create_data([0,1000,0,50,0,1000],resolution=[20,2,30], \n",
+    "geo_data = gp.create_data([0,1000,0,50,0,1000],resolution=[20,5,30], \n",
     "                        path_o = os.pardir+\"/data/input_data/jan_models/model1_orientations.csv\",\n",
     "                        path_i = os.pardir+\"/data/input_data/jan_models/model1_surface_points.csv\") "
    ]
@@ -61,39 +61,39 @@
      "data": {
       "text/html": [
        "<style  type=\"text/css\" >\n",
-       "    #T_e7023cb8_d09b_11e9_ade1_e82a44a18926row0_col4 {\n",
+       "    #T_587290ac_d0b6_11e9_a320_e82a44a18926row0_col4 {\n",
        "            background-color:  #015482;\n",
-       "        }    #T_e7023cb8_d09b_11e9_ade1_e82a44a18926row1_col4 {\n",
+       "        }    #T_587290ac_d0b6_11e9_a320_e82a44a18926row1_col4 {\n",
        "            background-color:  #9f0052;\n",
-       "        }    #T_e7023cb8_d09b_11e9_ade1_e82a44a18926row2_col4 {\n",
+       "        }    #T_587290ac_d0b6_11e9_a320_e82a44a18926row2_col4 {\n",
        "            background-color:  #ffbe00;\n",
-       "        }</style><table id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >surface</th>        <th class=\"col_heading level0 col1\" >series</th>        <th class=\"col_heading level0 col2\" >order_surfaces</th>        <th class=\"col_heading level0 col3\" >isBasement</th>        <th class=\"col_heading level0 col4\" >color</th>        <th class=\"col_heading level0 col5\" >id</th>    </tr></thead><tbody>\n",
+       "        }</style><table id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >surface</th>        <th class=\"col_heading level0 col1\" >series</th>        <th class=\"col_heading level0 col2\" >order_surfaces</th>        <th class=\"col_heading level0 col3\" >isBasement</th>        <th class=\"col_heading level0 col4\" >color</th>        <th class=\"col_heading level0 col5\" >id</th>    </tr></thead><tbody>\n",
        "                <tr>\n",
-       "                        <th id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row0_col0\" class=\"data row0 col0\" >rock2</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row0_col1\" class=\"data row0 col1\" >Strat_Series</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row0_col2\" class=\"data row0 col2\" >1</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row0_col3\" class=\"data row0 col3\" >False</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row0_col4\" class=\"data row0 col4\" >#015482</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row0_col5\" class=\"data row0 col5\" >1</td>\n",
+       "                        <th id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row0_col0\" class=\"data row0 col0\" >rock2</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row0_col1\" class=\"data row0 col1\" >Strat_Series</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row0_col2\" class=\"data row0 col2\" >1</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row0_col3\" class=\"data row0 col3\" >False</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row0_col4\" class=\"data row0 col4\" >#015482</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row0_col5\" class=\"data row0 col5\" >1</td>\n",
        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row1_col0\" class=\"data row1 col0\" >rock1</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row1_col1\" class=\"data row1 col1\" >Strat_Series</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row1_col2\" class=\"data row1 col2\" >2</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row1_col3\" class=\"data row1 col3\" >False</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row1_col4\" class=\"data row1 col4\" >#9f0052</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row1_col5\" class=\"data row1 col5\" >2</td>\n",
+       "                        <th id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row1_col0\" class=\"data row1 col0\" >rock1</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row1_col1\" class=\"data row1 col1\" >Strat_Series</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row1_col2\" class=\"data row1 col2\" >2</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row1_col3\" class=\"data row1 col3\" >False</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row1_col4\" class=\"data row1 col4\" >#9f0052</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row1_col5\" class=\"data row1 col5\" >2</td>\n",
        "            </tr>\n",
        "            <tr>\n",
-       "                        <th id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row2_col0\" class=\"data row2 col0\" >basement</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row2_col1\" class=\"data row2 col1\" >Basement_Series</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row2_col2\" class=\"data row2 col2\" >1</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row2_col3\" class=\"data row2 col3\" >True</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row2_col4\" class=\"data row2 col4\" >#ffbe00</td>\n",
-       "                        <td id=\"T_e7023cb8_d09b_11e9_ade1_e82a44a18926row2_col5\" class=\"data row2 col5\" >3</td>\n",
+       "                        <th id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row2_col0\" class=\"data row2 col0\" >basement</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row2_col1\" class=\"data row2 col1\" >Basement_Series</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row2_col2\" class=\"data row2 col2\" >1</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row2_col3\" class=\"data row2 col3\" >True</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row2_col4\" class=\"data row2 col4\" >#ffbe00</td>\n",
+       "                        <td id=\"T_587290ac_d0b6_11e9_a320_e82a44a18926row2_col5\" class=\"data row2 col5\" >3</td>\n",
        "            </tr>\n",
        "    </tbody></table>"
       ],
@@ -155,26 +155,86 @@
     "sol = gp.compute_model(geo_data)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "import gempy as gp\n",
+    "#importlib.reload(kriging)\n",
+    "from gempy.assets import kriging"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_data = np.array([[110,0,510,2],[910,0,510,1],[510,0,530,1],[310,0,410,5]])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Creating a kriging object with model solution and input domain (by id) and conditioning data\n",
+    "kriging_model = kriging.kriging_model(model=sol, domain=[1,3],data=test_data)\n",
+    "\n",
+    "kriging_model.krig_grid = np.round(kriging_model.krig_grid,0)\n",
+    "\n",
+    "# set some parameters, not final yet\n",
+    "kriging_model.range_ = 200\n",
+    "kriging_model.moving_neighbourhood  = 'all'\n",
+    "kriging_model.set_kriging_type('OK')\n",
+    "kriging_model.nugget = 2\n",
+    "kriging_model.sill = np.var(test_data[:,3])\n",
+    "\n",
+    "kriging_model.create_kriged_field()\n",
+    "#kriging_model.results_df.head()\n",
+    "kriging_model.plot_results(geo_data=geo_data, prop='val', contour=False, direction='y', cell_number=2, alpha=.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "<gempy.plot.visualization_2d.PlotData2D at 0x18440896518>"
+       "<Figure size 748.8x514.8 with 1 Axes>"
       ]
      },
-     "execution_count": 6,
      "metadata": {},
-     "output_type": "execute_result"
-    },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "kriging_model.plot_results(geo_data=geo_data, prop='val', contour=False, direction='y', cell_number=2, alpha=.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<Figure size 748.8x514.8 with 1 Axes>"
+       "<Figure size 748.8x514.8 with 4 Axes>"
       ]
      },
      "metadata": {},
@@ -182,158 +242,402 @@
     }
    ],
    "source": [
-    "# Plot cross section, which is basically the whole model in this example\n",
-    "gp.plot.plot_section(geo_data, cell_number=0)"
+    "# Creating a kriging object with model solution and input domain (by id) and conditioning data\n",
+    "kriging_model = kriging.kriging_model(model=sol, domain=[2],data=test_data)\n",
+    "\n",
+    "kriging_model.krig_grid = np.round(kriging_model.krig_grid,0)\n",
+    "\n",
+    "# set some parameters, not final yet\n",
+    "kriging_model.range_ = 200\n",
+    "kriging_model.moving_neighbourhood  = 'all'\n",
+    "kriging_model.set_kriging_type('OK')\n",
+    "kriging_model.nugget = 2\n",
+    "kriging_model.sill = np.var(test_data[:,3])\n",
+    "\n",
+    "kriging_model.create_kriged_field()\n",
+    "#kriging_model.results_df.head()\n",
+    "kriging_model.plot_results(geo_data=geo_data, prop='both', contour=False, direction='y', cell_number=2, alpha=0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 748.8x514.8 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Creating a kriging object with model solution and input domain (by id) and conditioning data\n",
+    "kriging_model = kriging.kriging_model(model=sol, domain=[2],data=test_data)\n",
+    "\n",
+    "kriging_model.krig_grid = np.round(kriging_model.krig_grid,0)\n",
+    "\n",
+    "# set some parameters, not final yet\n",
+    "kriging_model.range_ = 200\n",
+    "kriging_model.moving_neighbourhood  = 'all'\n",
+    "kriging_model.set_kriging_type('OK')\n",
+    "kriging_model.nugget = 2\n",
+    "kriging_model.sill = np.var(test_data[:,3])\n",
+    "\n",
+    "kriging_model.create_kriged_field()\n",
+    "#kriging_model.results_df.head()\n",
+    "kriging_model.plot_results(geo_data=geo_data, prop='var', contour=False, direction='y', cell_number=2, alpha=0,\n",
+    "                          legend=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 157,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import gempy as gp\n",
-    "#importlib.reload(kriging)\n",
-    "from gempy.assets import kriging"
+    "a=np.full_like(kriging_model.mask, np.nan, dtype=np.double)\n",
+    "b=np.full_like(kriging_model.mask, np.nan, dtype=np.double)\n",
+    "est_vals = kriging_model.results_df['est_value'].values\n",
+    "est_var = kriging_model.results_df['est_variance'].values\n",
+    "a[np.where(kriging_model.mask == True)] = est_vals\n",
+    "b[np.where(kriging_model.mask == True)] = est_var"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 138,
    "metadata": {},
    "outputs": [],
    "source": [
-    "test_data = np.array([[110,0,510,2],[910,0,510,1],[510,0,530,1],[310,0,410,5]])"
+    "from gempy.plot.helpers import add_colorbar"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Creating a kriging object with model solution and input domain (by id) and conditioning data\n",
-    "kriging_model = kriging.kriging_model(model=sol, domain=[1],data=test_data)\n",
+    "add_colorbar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 281,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_results(kriging_model, geo_data=None, prop='val', direction='y', cell_number=0, contour=True, alpha=0):   \n",
+    "    a=np.full_like(kriging_model.mask, np.nan, dtype=np.double)\n",
+    "    est_vals = kriging_model.results_df['est_value'].values\n",
+    "    est_var = kriging_model.results_df['est_variance'].values\n",
+    "    \n",
+    "    if prop == 'val':\n",
+    "        a[np.where(kriging_model.mask == True)] = est_vals\n",
+    "    elif prop == 'var':   \n",
+    "        a[np.where(kriging_model.mask == True)] = est_var\n",
+    "    elif prop == 'both':\n",
+    "        a[np.where(kriging_model.mask == True)] = est_vals\n",
+    "        b=np.full_like(kriging_model.mask, np.nan, dtype=np.double)\n",
+    "        b[np.where(kriging_model.mask == True)] = est_var\n",
+    "    else:\n",
+    "        print('prop must be val var or both')\n",
+    "    \n",
+    "    p =visualization_2d.PlotSolution(geo_data)\n",
+    "    _a, _b, _c, extent_val, x, y = p._slice(direction, cell_number)[:-2]   \n",
     "\n",
-    "kriging_model.krig_grid = np.round(kriging_model.krig_grid,0)\n",
+    "    \n",
+    "    cmap = matplotlib.cm.get_cmap('viridis')\n",
+    "    cmap.set_bad(color='w',alpha=alpha)\n",
+    "    \n",
+    "    if prop is not 'both':      \n",
+    "        if geo_data is not None:\n",
+    "            gp.plot.plot_section(geo_data, direction=direction, cell_number=cell_number)\n",
+    "        if contour == True:\n",
+    "            im = plt.contourf(a.reshape(kriging_model.sol.grid.regular_grid.resolution)[_a, _b, _c].T, cmap=cmap,origin='lower',\n",
+    "                      extent=extent_val)\n",
+    "        else: \n",
+    "            im = plt.imshow(a.reshape(kriging_model.sol.grid.regular_grid.resolution)[_a, _b, _c].T, cmap=cmap,origin='lower',\n",
+    "                  extent=extent_val)\n",
+    "        add_colorbar(im, location='right')\n",
+    "    else:\n",
+    "        f, ax = plt.subplots(1,2, sharex=True, sharey=True)\n",
+    "        ax[0].title.set_text('Estimated value')\n",
+    "        im1=ax[0].imshow(a.reshape(kriging_model.sol.grid.regular_grid.resolution)[:,2,:].T, cmap=cmap,origin='lower',\n",
+    "                      extent=kriging_model.sol.grid.regular_grid.extent[[0,1,4,5]])\n",
+    "        add_colorbar(im1)\n",
+    "        ax[1].title.set_text('Variance')\n",
     "\n",
-    "# set some parameters, not final yet\n",
-    "kriging_model.range_ = 200\n",
-    "kriging_model.moving_neighbourhood  = 'all'\n",
-    "kriging_model.set_kriging_type('OK')\n",
-    "kriging_model.nugget = 2\n",
-    "kriging_model.sill = np.var(test_data[:,3])\n",
+    "        im2=ax[1].imshow(b.reshape(kriging_model.sol.grid.regular_grid.resolution)[:,2,:].T, cmap=cmap,origin='lower',\n",
+    "                      extent=kriging_model.sol.grid.regular_grid.extent[[0,1,4,5]])\n",
+    "        add_colorbar(im2)\n",
+    "        plt.tight_layout()\n",
+    "    #add_colorbar(im, location='right')\n",
+    "    #plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 283,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 748.8x514.8 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_results(kriging_model, geo_data, prop = 'var', contour=False, alpha=.9, direction='y', cell_number=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 159,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from gempy.plot import visualization_2d\n",
+    "p =visualization_2d.PlotSolution(geo_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 193,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "direction='y'\n",
+    "cell_number=2\n",
+    "alpha=.5\n",
+    "contour=False"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 194,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 748.8x514.8 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "a=np.full_like(kriging_model.mask, np.nan, dtype=np.double)\n",
+    "b=np.full_like(kriging_model.mask, np.nan, dtype=np.double)\n",
+    "est_vals = kriging_model.results_df['est_value'].values\n",
+    "est_var = kriging_model.results_df['est_variance'].values\n",
+    "a[np.where(kriging_model.mask == True)] = est_vals\n",
+    "b[np.where(kriging_model.mask == True)] = est_var\n",
     "\n",
-    "kriging_model.create_kriged_field()\n",
-    "#kriging_model.results_df.head()"
+    "p =visualization_2d.PlotSolution(geo_data)\n",
+    "_a, _b, _c, extent_val, x, y = p._slice(direction, cell_number)[:-2]\n",
+    "\n",
+    "\n",
+    "if geo_data is not None:\n",
+    "    gp.plot.plot_section(geo_data, direction=direction, cell_number=cell_number)\n",
+    "cmap = matplotlib.cm.get_cmap('viridis')\n",
+    "cmap.set_bad(color='w',alpha=alpha)\n",
+    "if contour == True:\n",
+    "    im = plt.contourf(a.reshape(kriging_model.sol.grid.regular_grid.resolution)[_a, _b, _c].T, cmap=cmap,origin='lower',\n",
+    "              extent=extent_val)\n",
+    "else: \n",
+    "    im = plt.imshow(a.reshape(kriging_model.sol.grid.regular_grid.resolution)[_a, _b, _c].T, cmap=cmap,origin='lower',\n",
+    "          extent=extent_val)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 253,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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88onj/RcvXtTkyZPVunVrBQQEqHPnzlqxYoXTZ5w+fVoTJ05UaGiomjRpoj59+mj37t1Ofe655x6tW7dOo0ePVlBQkP7yl7/olVdekd1u1/jx49W8eXOFhYVp9uzZTtfGXevYb775psaPH68WLVooKChII0aM0MmTJyVJ48aN04YNG/Tdd9/pnnvu0T//+c/rXk/CHQAAcKn33ntPR44c0Zw5czR8+HBt2rRJEyZMkCTNmjVLS5cuVZ8+fbR8+XJNnTpVp0+f1ogRI3ThwgVJ0ksvvaSPPvpI48aN04oVK3Tfffdp1qxZ2rhxoyQpOztb/fr1044dO/Tss89qwYIFqly5svr166fPP//cqZaZM2fKx8dHixcvVtu2bbVw4UL17NlTlSpV0vz589W2bVstX75cW7du/cNjz5kzR5IUFxen5557TomJiZoxY4Yk6emnn1a7du10xx13aN26dWrTps11ryfX3AEAAJfy9fXV3/72N1WsWFGSVK5cOU2ZMkWHDh3Sjz/+qGeffVZ9+/Z19K9QoYKeeeYZffPNN2rSpIk+/fRThYWF6f7775cktWzZUrfccot8fHwkSZs2bdKBAwe0fv16NW7cWJLUunVr9ezZU/PmzVN8fLxj7EaNGun555+XJP35z3/WP//5T91+++168cUXJUlhYWHavHmz9u7dq06dOv2hsf/85z8rNjbWMU5qaqq2b98uSapVq5Z8fX3l6emppk2b3tB6Eu4AAIBLRUREOIKdJN13332aPHmyUlNTNW/ePEnSqVOndOTIEaWnpysxMVGSlJubK+mXMPfmm28qIyNDERERioiI0LBhwxzj/ec//5Gfn58aNGigvLw8R3vbtm316quvKicnR56enpKkJk2aOI77+PjIw8NDgYGBjjY3NzdVrlxZ586d+8NjN2vWzGne1apVc+w+FiXCHQAAcKkqVao4vfb19ZUk/fjjj0pNTdWUKVOUmpqqSpUq6a677lL16tUl/e+ZcM8//7yqVaumt99+W1OnTtXUqVMVFBSkyZMn689//rPOnDmjjIwMNWrU6LKff/r0afn5+UmSvLy8Ch2vVKnSFWv/I2P/OsBKkru7uy5dunTFsa8X4Q4AALjU2bNnnV4X3GRQsWJFDRo0SA0aNNB7772nunXryt3dXTt37tSWLVsc/T09PTV06FANHTpU33//vRITE7V48WI999xzeuedd2Sz2VSvXj3NnDnzsp9fcPr2ehTn2NeLGyoAAIBL/ec//1F+fr7j9ebNmyVJQUFBOnPmjPr166e77rpL7u6/xJaPPvpI0i87dzk5OercubNWrlwpSapevbr69u2rBx54QCdOnJAktWjRQt9//72qVq2qxo0bO/7861//0qpVq1S+fPnrrr0ox/bw8LjuOn6NnTsAAOBSGRkZGjlypPr06aP9+/crLi5OjzzyiPz9/eXt7a3FixfLzc1N7u7u2rp1qzZs2CBJOn/+vDw9PdW4cWO98sorKl++vO655x6lpaVp48aN6tSpkyTpkUce0erVq9W/f39FR0fLz89PO3bsUHx8vIYPHy43N7frrr0ox7bZbPr555+1c+dONWjQQFWrVr2umgh3AADApfr06aOzZ8/q6aefVsWKFfXkk09qxIgRKl++vBYvXqxZs2bpr3/9q7y8vNSgQQOtXr1aTz31lHbv3q2IiAhNmTJFPj4+WrlypX766Sfdfvvt6tmzp2JiYiT9ch3dmjVr9PLLL2vGjBnKysrSn/70J73wwgt64oknbqj2ohy7d+/e2rFjh4YNG6aYmBgNGjToumpys4riN9RCkhQcHKwzWRd1JKC3q0sBALhQ3S/WSZIO7f+i+D/sJv/dsih67NwBAHAzI1DhN7ihAgAAwCCEOwAAAIMQ7gAAAAxCuAMAADAI4Q4AAMAgN0W4W7t2rbp06aKmTZuqa9euevvtt52OJyUlqUePHgoMDFS7du0cT6n+tdTUVEVGRiooKEjh4eGaO3eu4xcOAwAAmKLUh7t169Zp8uTJatOmjRYvXqxWrVrpueeec/xqkpSUFA0ZMkR169bVwoUL1bVrV82aNUsrVqxwjJGenq5+/fqpQoUKiouL04ABAxQfH6/Y2FhXTQsAAKBYlPrn3G3cuFEtW7bU2LFjJUmtWrXSF198ob///e/q0qWLFixYoIYNG2r27NmSpNatWysvL09Lly5VZGSkPD09tWzZMtlsNi1evFienp6KiIhQxYoVNW3aNMevCgEAADBBqd+5y87OlpeXl1PbbbfdpjNnzig7O1vJycnq2LGj0/FOnTrp3LlzSklJkSTt2rVLbdu2laenp6NP586dlZ+fr6SkpOKfBAAAQAkp9eHuySef1L///W9t3rxZdrtdH3zwgXbs2KFu3brp+PHjys3Nlb+/v9N7ateuLUlKS0vThQsXdOLEiUJ9fH195e3trbS0tBKbCwAAQHEr9adlH3jgAf33v/91/PJfSerevbsGDRqkPXv2SJK8vb2d3lOw02e325WZmXnZPgX97Hb7NdcSHBx81eOZmZmSe/lrHg8AAKColfpwN3ToUO3Zs0fjx49Xw4YNtW/fPi1evFje3t66//77JUlubm6Xfa+7u7ssy7piH8uy5O5e6jcvAQAArlmpDncpKSlKSkpSbGysHnnkEUlSSEiIbr31Vr344ovq2bOnJBXafSt4bbPZHDt2l9uhO3/+vGw22zXXk5ycfNXjwcHBOpN18ZrHAwAAKGqletvq+++/lyQ1a9bMqb3g9Oj+/fvl4eGhY8eOOR0veO3v7y8vLy/5+fkpPT3dqc/Jkydlt9sLXYsHAABwMyvV4a4geH322WdO7Xv37pUk1a1bV8HBwdq6davj9KskbdmyRTabTQEBAZKksLAwJSYmKicnx6mPh4eHQkJCinsaAAAAJaZUn5Zt1KiR2rdvr5deeklZWVlq0KCBvvjiCy1atEitW7dWYGCghg4dqv79+2vkyJHq3r279uzZoxUrVmjUqFGqVKmSJGnQoEF67733NHjwYEVFReno0aOaO3euevXqperVq7t4lgAAAEXHzfr1llcplJOTo1deeUVvv/22Tp48qRo1aujBBx/U4MGDHc+t27ZtmxYsWKC0tDT5+fmpb9++GjBggNM4ycnJmjVrlvbv3y8fHx89/PDDeuaZZ1S+fNHd3Vpwzd2RgN5FNiYA4OZT94t1kqRD+79wcSUoi0p9uLuZEO4AABLhDq5Vqq+5AwAAwB9DuAMAADAI4Q4AAMAghDsAAACDEO4AAAAMQrgDAAAwCOEOAADAIIQ7AAAAgxDuAAAADEK4AwAAMAjhDgAAwCCEOwAAAIMQ7gAAAAxCuAMAADAI4Q4AAMAghDsAAACDEO4AAAAMQrgDAAAwCOEOAADAIIQ7AAAAgxDuAAAADEK4AwAAMAjhDgAAwCCEOwAAAIMQ7gAAAAxCuAMAADAI4Q4AAMAghDsAAACDEO4AAAAMQrgDAAAwCOEOAADAIIQ7AAAAgxDuAAAADEK4AwAAMAjhDgAAwCCEOwAAAIMQ7gAAAAxCuAMAADAI4Q4AAMAghDsAAACDEO4AAAAMQrgDAAAwCOEOAADAIIQ7AAAAgxDuAAAADEK4AwAAMAjhDgAAwCCEOwAAAIMQ7gAAAAxCuAMAADAI4Q4AAMAghDsAAACDEO4AAAAMQrgDAAAwCOEOAADAIIQ7AAAAgxDuAAAADEK4AwAAMAjhDgAAwCCEOwAAAIMQ7gAAAAxCuAMAADAI4Q4AAMAghDsAAACDEO4AAAAMclOEu88++0x9+vRRYGCgwsPDNXXqVGVlZTmOJyUlqUePHgoMDFS7du20cuXKQmOkpqYqMjJSQUFBCg8P19y5c5Wbm1uS0wAAACh2pT7c7d27V/3799cdd9yhJUuWaNiwYXr77bc1ceJESVJKSoqGDBmiunXrauHCheratatmzZqlFStWOMZIT09Xv379VKFCBcXFxWnAgAGKj49XbGysq6YFAABQLMq5uoDfM2fOHDVt2lTz58+Xm5ubWrVqpUuXLik+Pl4XLlzQggUL1LBhQ82ePVuS1Lp1a+Xl5Wnp0qWKjIyUp6enli1bJpvNpsWLF8vT01MRERGqWLGipk2bpujoaPn5+bl4lgAAAEWjVO/cnTp1SsnJyerTp4/c3Nwc7X379tX27dvl7u6u5ORkdezY0el9nTp10rlz55SSkiJJ2rVrl9q2bStPT09Hn86dOys/P19JSUklMxkAAIASUKp37g4ePCjLslS5cmXFxMRox44d8vDw0IMPPqjx48fr22+/VW5urvz9/Z3eV7t2bUlSWlqaAgMDdeLEiUJ9fH195e3trbS0tGuuJzg4+KrHMzMzJffy1zweAABAUSvV4e7UqVOSpHHjxqlDhw5asmSJDhw4oLi4OGVnZ6t3796SJG9vb6f3eXl5SZLsdvsvgesyfQr62e324pwCAABAiSrV4a7gbtZmzZpp0qRJkqTQ0FBZlqWZM2eqV69ekuR0yvbX3N3dZVnWFftYliV392s/M52cnHzV48HBwco5k6WVG/Ze85gAAPPMrZfv6hJQhpXqa+4KduBat27t1B4eHi7LspSamipJhXbfCl7bbDbHjt3ldujOnz8vm81W5HUDAAC4SqkOd3Xq1JEk5eTkOLUX7OjVrFlTHh4eOnbsmNPxgtf+/v7y8vKSn5+f0tPTnfqcPHlSdru90LV4AAAAN7NSHe7q1aunGjVq6P3333dqT0xMVLly5RQUFKTg4GBt3brVcfpVkrZs2SKbzaaAgABJUlhYmBITE51C4pYtW+Th4aGQkJCSmQwAAEAJKNXhzs3NTaNHj1ZycrJGjx6tjz/+WMuWLdOSJUsUGRkpX19fDR06VCkpKRo5cqR27typuLg4rVixQtHR0apUqZIkadCgQfrpp580ePBgJSYmOh5g3KtXL1WvXt3FswQAACg6btavt7xKqe3bt2vRokU6dOiQbr/9dvXu3VvR0dGOmyG2bdumBQsWKC0tTX5+furbt68GDBjgNEZycrJmzZql/fv3y8fHRw8//LCeeeYZlS9fdI8uKbih4tnDDYtsTADAzWduva8kSZ8f2u/iSlAW3RTh7mZBuAMASIQ7uFapPi0LAACAP4ZwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEGuGu4SEhKUkpJyzYMdOHBAr7zyyg0XBQAAgOtz1XA3btw4PfHEE5oxY4ZycnJ+d7ADBw5o0aJFRVYcAAAA/pjfPS1rs9n02muv6dFHH9U333xTEjUBAADgOv1uuBs3bpz69++vgwcPqmfPnlq1alVJ1AUAAIDr8Lvhrly5cho7dqxWrFihW2+9VS+99JIGDRqkn376qSTqAwAAwB9wzXfLtmrVSu+++646duyopKQkdevWTf/617+KszYAAAD8QX/oUSiVK1fW/PnzFRsbq5ycHA0fPlwvvviiLl68WFz1AQAA4A+4rufcde/eXQkJCQoKCtJbb72l7t2768svvyzq2gAAAPAHXfdDjGvWrKk1a9YoJiZGx48f12OPPaZNmzYVZW0AAAD4g64a7qpXr65bbrnlisfd3Nw0ZMgQvfnmm6pZs6Z27dpV5AUCAADg2pW72sEPP/zwmgYJCAhQQkKClixZoh9++KFICgMAAMAfd9Vw90dUqFBBMTExRTUcAAAArsN1X3MHAACA0odwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGOSmC3fDhw9Xhw4dnNqSkpLUo0cPBQYGql27dlq5cmWh96WmpioyMlIT74+5AAAYpUlEQVRBQUEKDw/X3LlzlZubW1JlAwAAlIibKtxt2rRJ27Ztc2pLSUnRkCFDVLduXS1cuFBdu3bVrFmztGLFCkef9PR09evXTxUqVFBcXJwGDBig+Ph4xcbGlvQUAAAAilU5VxdwrX744QdNnz5d1apVc2pfsGCBGjZsqNmzZ0uSWrdurby8PC1dulSRkZHy9PTUsmXLZLPZtHjxYnl6eioiIkIVK1bUtGnTFB0dLT8/P1dMCQAAoMjdNDt3EydOVFhYmEJDQx1t2dnZSk5OVseOHZ36durUSefOnVNKSookadeuXWrbtq08PT0dfTp37qz8/HwlJSWVzAQAAABKwE0R7tavX68vv/xSL7zwglP78ePHlZubK39/f6f22rVrS5LS0tJ04cIFnThxolAfX19feXt7Ky0trXiLBwAAKEGl/rTsd999p9jYWMXGxsrX19fpWGZmpiTJ29vbqd3Ly0uSZLfbr9inoJ/dbr/mWoKDg696PDMzUxVujrwMAAAMVarDnWVZmjBhgiIiItSpU6fLHpckNze3y77f3d39qn0sy5K7e9GGMU/vXPX78J9FOiYA4Obyysh6ri4BZVipDndr1qzRgQMH9M477ygvL0/S/wJdXl6ebDabJBXafSt4bbPZHDt2l9uhO3/+vGOMa5GcnHzV48HBwVLemWseDwAAoKiV6nC3ZcsWnT59WuHh4YWONWrUSJMnT5aHh4eOHTvmdKzgtb+/v7y8vOTn56f09HSnPidPnpTdbi90LR4AAMDNrFSHuylTpigrK8upbdGiRdq/f79eeeUV1axZU5s3b9bWrVsVFRXlOPW6ZcsW2Ww2BQQESJLCwsKUmJioMWPGOO6Y3bJlizw8PBQSElKykwIAAChGpTrc1a1bt1DbbbfdJk9PTzVu3FiSNHToUPXv318jR45U9+7dtWfPHq1YsUKjRo1SpUqVJEmDBg3Se++9p8GDBysqKkpHjx7V3Llz1atXL1WvXr1E5wQAAFCcbvpbO0NDQ7Vw4UIdPnxYw4YN0zvvvKMxY8boqaeecvSpV6+eVq5cqfPnz+uvf/2r4uPj1b9/fz3//PMurBwAAKDouVkFdyjghhXcUJE877CrSwEAuFDw/90tm7z3kIsrQVl00+/cAQAA4H8IdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBSn24u3TpktauXauuXbsqKChI7du3V2xsrOx2u6NPamqqIiMjFRQUpPDwcM2dO1e5ublO4xw9elRDhgxRcHCwWrZsqUmTJjmNAQAAYIJyri7g9yxfvlxxcXEaOHCgQkNDlZaWpgULFujQoUNasWKF0tPT1a9fPwUFBSkuLk6HDx/WvHnzZLfb9eKLL0qSzp49q6ioKN1xxx2aOXOmTp48qdmzZysjI0Ovvvqqi2cIAABQdEp1uLMsS8uXL1fv3r01atQoSVKrVq3k4+OjkSNHav/+/Vq9erVsNpsWL14sT09PRUREqGLFipo2bZqio6Pl5+enNWvW6Ny5c0pISJCPj48kyc/PT4MHD9a+ffsUGBjoymkCAAAUmVJ9WjYrK0sPPfSQHnzwQaf2unXrSpKOHTumXbt2qW3btvL09HQc79y5s/Lz85WUlCRJ2rVrl1q0aOEIdpIUHh4uLy8v7dy5swRmAgAAUDJK9c6dt7e3Jk6cWKh9+/btkqR69erpxIkT8vf3dzru6+srb29vpaWlSZKOHDmihx56yKmPh4eHatas6egDAABgglId7i5n3759WrZsmdq3b69bb71V0i8h8Le8vLwcN0xkZmb+bp9rERwcfNXjmZmZslW65uEAAACKXKk+Lftbu3fv1qBBg1SzZk1NmzZNlmVJktzc3Ar1tSxL7u7/m9619AEAALjZ3TQ7d++//77GjRunOnXqaPny5fLx8VFWVpYkXXb37fz587LZbJJ+2dm7XJ+srCzVqFHjmmtITk6+6vHg4GAp78w1jwcAAFDUboptq/j4eD377LNq2rSp1qxZo6pVq0r65bSqn5+f0tPTnfqfPHlSdrvdcS2ev79/oT75+fn69ttvC12vBwAAcDMr9eFu/fr1mjFjhrp06aLly5c7duMKhIWFKTExUTk5OY62LVu2yMPDQyEhIY4+n3zyic6c+d+uWlJSks6fP69WrVqVzEQAAABKQKk+LXvy5ElNnz5dNWrUUN++ffXVV185Ha9Vq5YGDRqk9957T4MHD1ZUVJSOHj2quXPnqlevXqpevbok6fHHH9fq1avVr18/DRs2TGfOnNHs2bPVunVrNWvWzBVTAwAAKBZuVsFdCaVQQkKCxo4de8Xjs2bNUrdu3ZScnKxZs2Zp//798vHx0cMPP6xnnnlG5cuXd/Q9ePCgXnrpJe3Zs0deXl5q3769xowZc9m7aK9XwTV3yfMOF9mYAICbT/DIepKk5L2HXFwJyqJSHe5uNoQ7AIBEuINrlfpr7gAAAHDtCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQcpUuHv33Xf1wAMPqEmTJurSpYsSEhJcXRIAAECRKjPhbvPmzRo9erTCwsK0aNEihYSEaOzYsfrggw9cXRoAAECRKefqAkrK3Llz1aVLF02YMEGSdO+99+rs2bOaP3++Onfu7OLqAAAAikaZ2Lk7fvy4jh07po4dOzq1d+rUSUeOHNHx48ddVBkAAEDRKhPh7siRI5Ikf39/p/batWtLktLS0kq8JgAAgOJQJk7LZmZmSpK8vb2d2r28vCRJdrv9msYJDg6+hs9xV/DIen+8SACAMTIvuMvNzdVVoKwqE+HOsixJkttv/qUVtLu7F+UGpptU7rYiHM98BeHbZrO5uJKbB2t2fVi368O6XY9M/d9/MUCJKxPhruAb0m936LKyspyO/57k5OSrHi/Y2fu9fnDGuv1xrNn1Yd2uD+v2x/3emR6gOJWJa+4KrrU7duyYU3t6errTcQAAgJtdmQh3tWvXVs2aNQs9027r1q2qU6eOqlev7qLKAAAAilaZOC0rScOGDdP48eNVuXJltWnTRh9++KE2b96sefPmubo0AACAIlNmwt0jjzyinJwcrVy5UuvXr9ef/vQnzZw5U/fff7+rSwMAACgyZSbcSdJjjz2mxx57zNVlAAAAFJsycc0dAABAWUG4AwAAMIibZfGYRQAAAFOwcwcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwV0TeffddPfDAA2rSpIm6dOmihIQEV5fkMpcuXdLatWvVtWtXBQUFqX379oqNjZXdbnf0SU1NVWRkpIKCghQeHq65c+cqNzfXaZyjR49qyJAhCg4OVsuWLTVp0iSnMUw3fPhwdejQwaktKSlJPXr0UGBgoNq1a6eVK1cWet+1rK1pPvvsM/Xp00eBgYEKDw/X1KlTlZWV5TjOul3e2rVr1aVLFzVt2lRdu3bV22+/7XScdfuf/fv3q1GjRsrIyHBqL6o1Kuvf71C0PCZPnjzZ1UXc7DZv3qxRo0apa9euGjp0qLKzsxUXF6e7775bd911l6vLK3F/+9vfNGvWLD3yyCOKjo5WnTp19PrrryslJUXdunVTenq6+vTpo5o1a2rs2LGqU6eOlixZolOnTikiIkKSdPbsWfXu3Vtubm4aP368mjZtqtdff12pqanq2rWri2dY/DZt2qRXX31VlStX1pNPPilJSklJ0cCBAxUSEqKYmBjZbDYtWLBAlSpVUrNmzSTpmtbWNHv37lVUVJQCAgI0btw41a9fX6+99poOHTqkzp07s25XsG7dOk2aNEndu3fX008/rUuXLmn27Nm66667dPfdd7Nuv3LkyBENGjRImZmZ6t+/v7y9vSUV3b/Jsv79DsXAwg1r3769FRMT49Q2YsQIq3Pnzi6qyHUuXbpktWjRwpo8ebJT+3vvvWfVr1/f+uqrr6wJEyZYERERVnZ2tuP4mjVrrAYNGlgZGRmWZVnWokWLrKZNm1qnTp1y9NmxY4dVv359a+/evSUzGRfJyMiwWrRoYbVu3dpq3769oz0qKsp69NFHnfrOmjXLCg4Odqzltaytafr27Wv17dvXunTpkqNt9erV1n333WedP3+edbuC3r17W5GRkU5tjz/+uPXEE09YlsXXm2VZVm5urrV69WorKCjICgkJserXr2+dOHHCcbyo1qgsf79D8eC07A06fvy4jh07po4dOzq1d+rUSUeOHNHx48ddVJlrZGVl6aGHHtKDDz7o1F63bl1J0rFjx7Rr1y61bdtWnp6ejuOdO3dWfn6+kpKSJEm7du1SixYt5OPj4+gTHh4uLy8v7dy5swRm4joTJ05UWFiYQkNDHW3Z2dlKTk6+7NfZuXPnlJKSIknXtLYmOXXqlJKTk9WnTx+5ubk52vv27avt27fL3d2ddbuC7OxseXl5ObXddtttOnPmDF9v/2f37t2aM2eOBgwYoNGjRzsdK8o1Ksvf71A8CHc36MiRI5Ikf39/p/batWtLktLS0kq8Jlfy9vbWxIkT1bx5c6f27du3S5Lq1aunEydOFFovX19feXt7O9bryJEjhfp4eHioZs2aRq/p+vXr9eWXX+qFF15waj9+/Lhyc3Ov+nV24cKFa1pbkxw8eFCWZaly5cqKiYlR06ZN1bx5c02aNEkXL15k3a7iySef1L///W9t3rxZdrtdH3zwgXbs2KFu3bqxbv+nXr162r59u4YPHy4PDw+nY0W5RmX1+x2KTzlXF3Czy8zMlCTHNRgFCn4i5oJYad++fVq2bJnat2+vW2+9VVLh9ZJ+WbOC9crMzPzdPqb57rvvFBsbq9jYWPn6+jodu5avsyv1Kehn4rqdOnVKkjRu3Dh16NBBS5Ys0YEDBxQXF6fs7Gz17t1bEut2OQ888ID++9//KiYmxtHWvXt3DRo0SHv27JHEulWpUuWKx4ry32RZ/H6H4kW4u0GWZUmS0ymhX7e7u5ftzdHdu3dryJAhqlmzpqZNm6acnBxJhddL+mXNfr1e19LHFJZlacKECYqIiFCnTp0ue1y6/JpIv3ydXa2PqetWcMdhs2bNNGnSJElSaGioLMvSzJkz1atXL0ms2+UMHTpUe/bs0fjx49WwYUPt27dPixcvlre3t+6//35JrNvVFPW/ybK6jigefNXcIJvNJqnwDl3BYxgKjpdF77//vvr3768777xTr732mnx8fBw/nV7up9Hz58871svb2/uyfbKysi77E+7Nbs2aNTpw4IAmTJigvLw85eXlOf5jyMvLu+LXWcFrm812zWtrkoJdktatWzu1h4eHy7IspaamSmLdfislJUVJSUmaOHGi+vXrp5CQED311FMaN26cVq1apVtuuUUS63Y1Rflvsqx9v0PxI9zdoILrJI4dO+bUnp6e7nS8rImPj9ezzz6rpk2bas2aNapataqkX/4z9vPzc6xPgZMnT8putzvWy9/fv1Cf/Px8ffvtt0au6ZYtW3T69GmFh4erUaNGatSokRISEnTs2DE1atRIycnJ8vDwKPR1VvDa39//mtfWJHXq1JEkx45wgYIdvZo1a7Jul/H9999LkuNxHQWCg4Ml/fJMN9bt6mrVqlVka1TWvt+h+BHublDt2rVVs2ZNffDBB07tW7duVZ06dVS9enUXVeY669ev14wZM9SlSxctX7680E/wYWFhSkxMdPoPecuWLfLw8FBISIijzyeffKIzZ844+iQlJen8+fNq1apVyUykBE2ZMkUbNmxw+tO2bVtVq1ZNGzZsUOfOnRUcHKytW7c6dvSkX9bNZrMpICBA0rWtrUnq1aunGjVq6P3333dqT0xMVLly5RQUFMS6XUZBYPjss8+c2vfu3Svpl7vbWberq1ChQpGtUVn7fofix0OMi4DNZtOSJUt0+vRpubm5KT4+Xhs3btSkSZN09913u7q8EnXy5EkNGjRIfn5+GjVqlE6ePKmMjAzHH09PTzVs2FArV65UcnKyKleurB07dmj27Nl69NFHHQ/svOuuu/Tmm29q+/btuv3225WSkqLJkyerZcuWio6OdvEsi56Pj4/8/Pyc/iQlJenHH3/U6NGjValSJVWrVk1Lly7V4cOHValSJSUkJOhvf/ubnnnmGbVs2VLSL/9p/97amsTNzU133HGH4uPjdfToUXl7e2vz5s1atGiRIiMj1aFDB9btMqpWraqvv/5af//731WxYkVlZ2dry5YtevnllxUaGqqnnnqKdfuN/fv361//+pfTQ4yLao3K2vc7lICSe6Se2dauXWt16NDBCggIsLp06WJt3LjR1SW5xMaNG6369etf8U9CQoJlWZb12WefWY8++qgVEBBg3XvvvdbLL79s5eTkOI114MABKyoqymrSpIkVGhpqvfDCC1ZmZqYrpuUSY8eOdXqIsWVZ1tatW60HH3zQatSokdWuXTtrxYoVhd53LWtrmm3btlkPP/ywFRAQYEVERFiLFy+28vPzHcdZt8Kys7Otl19+2YqIiLACAgKsTp06WQsXLnR62C7r9j//+Mc/Cj3E2LKKbo3K+vc7FC03y/rVfjIAAABualxzBwAAYBDCHQAAgEEIdwAAAAYh3AEAABiEcAcAAGAQwh0AAIBBCHcArtupU6f0l7/8RSEhIfr5558v2ycmJsbxi+kBAMWPcAfguvn6+mrixIk6e/as/t//+3+FjickJGjz5s166qmnFBgY6IIKAaDs4SHGAG7Y0KFD9eGHH2rhwoXq2LGjJOm7777TQw89pFq1aumtt95S+fLlXVwlAJQNhDsAN+zHH3/UAw88oAoVKuj999+XzWZTZGSk9u3bp3/+859l7ncsA4ArcVoWwA2rWrWqxo4dq59++klz5szR2rVr9dlnnykmJoZgBwAljJ07AEVm4MCB+vjjj1WxYkU1bNhQq1atkrs7P0MCQEki3AEoMsePH1eHDh1kWZYSEhLUoEEDV5cEAGUOP1IDKDLvvvuuCn5eXL16tYurAYCyiZ07AEXi66+/Vs+ePRUSEqLc3Fx9+umnWrlypcLCwlxdGgCUKYQ7ADcsJydHPXr00PHjx7Vp0ybl5eXp4Ycf1h133KF33nlHXl5eri4RAMoMTssCuGELFizQwYMHFRMTo9q1a6tevXoaOnSovvvuO82ZM8fV5QFAmcLOHYAbkpKSor59+6pp06Zas2aN4+7Y3Nxc9ejRQwcPHtQbb7yhkJAQF1cKAGUD4Q7Adbtw4YK6deumjIwMbdq0Sf7+/k7HU1NT1bt3b9WoUUNvv/22KlWq5KJKAaDs4LQsgOs2a9Yspaena8SIEYWCnSQ1btxYUVFROnbsmObNm+eCCgGg7GHnDgAAwCDs3AEAABiEcAcAAGAQwh0AAIBBCHcAAAAGIdwBAAAYhHAHAABgEMIdAACAQQh3AAAABiHcAQAAGIRwBwAAYJD/D7GaFMxPuPb9AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "array([[110,   0, 510,   2],\n",
-       "       [910,   0, 510,   1],\n",
-       "       [510,   0, 530,   1],\n",
-       "       [310,   0, 410,   5]])"
+       "<Figure size 748.8x514.8 with 1 Axes>"
       ]
      },
-     "execution_count": 10,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "kriging_model.data"
+    "pls=p.plot_block_section(geo_data.solutions, direction=direction, cell_number=cell_number)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 251,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\elisa\\Anaconda3\\envs\\gempy_n\\lib\\site-packages\\matplotlib\\figure.py:98: MatplotlibDeprecationWarning: \n",
+      "Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
+      "  \"Adding an axes using the same arguments as a previous axes \"\n"
+     ]
+    }
+   ],
+   "source": [
+    "fig = pls\n",
+    "ax1 = pls.add_subplot(111)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 271,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "(480, 5)"
+       "<Figure size 748.8x514.8 with 4 Axes>"
       ]
      },
-     "execution_count": 11,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "add_colorbar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "kriging_model.results_df.shape"
+    "x = kriging_model.results_df['X'].values\n",
+    "y = kriging_model.results_df['Z'].values\n",
+    "prop = kriging_model.results_df['est_value'].values\n",
+    "var = kriging_model.results_df['est_variance'].values"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "(480, 3)"
+       "<Figure size 748.8x514.8 with 1 Axes>"
       ]
      },
-     "execution_count": 12,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "kriging_model.krig_grid.shape"
+    "from gempy.plot import visualization_2d\n",
+    "p = visualization_2d.PlotSolution(geo_data)\n",
+    "plot = plot_block_section(p, block=geo_data.solutions.lith_block, cell_number=0, direction='y')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(480,)"
+       "<matplotlib.colorbar.Colorbar at 0x1d1162d2f28>"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 60,
      "metadata": {},
      "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 748.8x514.8 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "kriging_model.krig_lith.shape"
+    "fig1, ax1 = plt.gcf(), plot.gca()\n",
+    "ax1.axis('equal')\n",
+    "\n",
+    "tcf = ax1.tricontourf(x, y, prop, 20, cmap='viridis')\n",
+    "tcf_lines = ax1.tricontour(x, y, prop, 20, linewidths=0.5, colors='k')\n",
+    "fig1.colorbar(tcf)\n",
+    "#plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "(480,)"
+       "<Figure size 748.8x514.8 with 1 Axes>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 61,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "geo_data.solutions.lith_block[kriging_model.mask].shape"
+    "plot"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -348,17 +652,9 @@
     }
    ],
    "source": [
-    "\n",
-    "x = kriging_model.results_df['X'].values\n",
-    "y = kriging_model.results_df['Z'].values\n",
-    "prop = kriging_model.results_df['est_value'].values\n",
-    "var = kriging_model.results_df['est_variance'].values\n",
-    "\n",
-    "\n",
     "fig1, ax1 = plt.subplots()\n",
     "ax1.axis('equal')\n",
     "\n",
-    "\n",
     "tcf = ax1.tricontourf(x, y, prop, 20, cmap='viridis')\n",
     "tcf_lines = ax1.tricontour(x, y, prop, 20, linewidths=0.5, colors='k')\n",
     "fig1.colorbar(tcf)\n",
@@ -367,27 +663,69 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = kriging_model.results_df['X'].values\n",
+    "y = kriging_model.results_df['Z'].values\n",
+    "prop = kriging_model.results_df['est_value'].values\n",
+    "var = kriging_model.results_df['est_variance'].values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(480,)"
+       "((240,), (240,), (240,), (240,))"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 74,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "prop.shape"
+    "var.shape, prop.shape, x.shape, y.shape"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_x = kriging_model.data[:,0]\n",
+    "data_y = kriging_model.data[:,1]\n",
+    "data_z = kriging_model.data[:,2]\n",
+    "data_val = kriging_model.data[:,3]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 748.8x514.8 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -467,44 +805,38 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "array([3.        , 3.        , 3.        , ..., 2.16095494, 2.16436534,\n",
-       "       2.16747924])"
+       "<Figure size 748.8x514.8 with 1 Axes>"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "source": [
-    "block"
-   ]
+   "source": []
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 748.8x514.8 with 1 Axes>"
-      ]
-     },
-     "execution_count": 37,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 748.8x514.8 with 1 Axes>"
       ]
@@ -513,9 +845,7 @@
      "output_type": "display_data"
     }
    ],
-   "source": [
-    "plot_block_section(plot, block=geo_data.solutions.lith_block, cell_number=0, direction='y')"
-   ]
+   "source": []
   },
   {
    "cell_type": "code",