[WIP] debugging actors

Author: Leguark

gempy_viewer/API/_plot_3d_API.py

@@ -187,7 +187,7 @@ def plot_3d(
             scalar_data_type=ScalarDataType.SCALAR_FIELD,
             active_scalar_field=active_scalar_field,
             solution=solutions_raw_arrays,
-            cmap='viridis',
+            cmap='magma',
             **kwargs_plot_structured_grid
         )
 

gempy_viewer/modules/plot_3d/drawer_input_3d.py

@@ -22,26 +22,22 @@ def plot_data(gempy_vista: GemPyToVista,
 
     plot_surface_points(
         gempy_vista=gempy_vista,
-        surface_points=surface_points_copy,
-        elements_colors=model.structural_frame.elements_colors,
-        **kwargs
+        surface_points=surface_points_copy
     )
 
     plot_orientations(
         gempy_vista=gempy_vista,
         orientations=orientations_copy,
-        elements_colors=model.structural_frame.elements_colors_orientations,
+        surface_points=surface_points_copy,
         arrows_factor=arrows_factor
     )
 
 
 def plot_surface_points(
         gempy_vista: GemPyToVista,
         surface_points: SurfacePointsTable,
-        elements_colors: list[str],
         render_points_as_spheres=True,
-        point_size=10,
-        **kwargs
+        point_size=10
 ):
     # Selecting the surfaces to plot
     xyz = surface_points.xyz
@@ -54,22 +50,24 @@ def plot_surface_points(
     ids = surface_points.ids
     if ids.shape[0] == 0:
         return
-    poly['id'] = _vectorize_ids(ids)
+    vectorize_ids = _vectorize_ids(ids, ids)
+    poly['id'] = vectorize_ids
 
     gempy_vista.surface_points_mesh = poly
     gempy_vista.surface_points_actor = gempy_vista.p.add_mesh(
         mesh=poly,
         scalars='id',
         render_points_as_spheres=render_points_as_spheres,
         point_size=point_size,
-        show_scalar_bar=False
+        show_scalar_bar=False,
+        # clim=(0, ids.max())
     )
 
 
 def plot_orientations(
         gempy_vista: GemPyToVista,
         orientations: OrientationsTable,
-        elements_colors: list[str],
+        surface_points: SurfacePointsTable,
         arrows_factor: float,
 ):
     orientations_xyz = orientations.xyz
@@ -81,16 +79,11 @@ def plot_orientations(
     pv = require_pyvista()
     poly = pv.PolyData(orientations_xyz)
 
-    ids = orientations.ids
-
-    poly['id'] = _vectorize_ids(ids)
-    poly['vectors'] = orientations_grads
-
-    # TODO: I am still trying to figure out colors and ids in orientations and surface points
-    cmap = get_geo_model_cmap(
-        elements_colors=np.array(elements_colors),
-        reverse=False
+    poly['id'] = _vectorize_ids(
+        mapping_ids=surface_points.ids,
+        ids_to_map=orientations.ids
     )
+    poly['vectors'] = orientations_grads
 
     arrows = poly.glyph(
         orient='vectors',
@@ -100,17 +93,21 @@ def plot_orientations(
 
     gempy_vista.orientations_actor = gempy_vista.p.add_mesh(
         mesh=arrows,
-        cmap=cmap,
+        scalars='id',
         show_scalar_bar=False
     )
     gempy_vista.orientations_mesh = arrows
 
 
-def _vectorize_ids(ids):
-    unique_values, first_indices = np.unique(ids, return_index=True)  # Find the unique elements and their first indices
-    unique_values_order = unique_values[np.argsort(first_indices)]  # Sort the unique values by their first appearance in `a`
-    # Flip order to please pyvista vertical scalarbar
-    unique_values_order = unique_values_order[::-1]
-    mapping_dict = {value: i + 1 for i, value in enumerate(unique_values_order)}  # Use a dictionary to map the original numbers to new values
-    mapped_array = np.vectorize(mapping_dict.get)(ids)  # Map the original array to the new values
+def _vectorize_ids(mapping_ids, ids_to_map):
+    def _mapping_dict(ids):
+        unique_values, first_indices = np.unique(ids, return_index=True)  # Find the unique elements and their first indices
+        unique_values_order = unique_values[np.argsort(first_indices)]  # Sort the unique values by their first appearance in `a`
+        # Flip order to please pyvista vertical scalarbar
+        unique_values_order = unique_values_order[::-1]
+        mapping_dict = {value: i + 1 for i, value in enumerate(unique_values_order)}  # Use a dictionary to map the original numbers to new values
+        return mapping_dict
+
+    mapping_dict = _mapping_dict(mapping_ids)
+    mapped_array = np.vectorize(mapping_dict.get)(ids_to_map)  # Map the original array to the new values
     return mapped_array

gempy_viewer/modules/plot_3d/drawer_structured_grid_3d.py

@@ -68,14 +68,10 @@ def add_regular_grid_mesh(
         _clim = None
     gempy_vista.regular_grid_actor = gempy_vista.p.add_mesh(
         mesh=structured_grid,
-        # cmap=cmap,
         # ? scalars=main_scalar, if we prepare the structured grid do we need this arg?
         show_scalar_bar=False,
-        # scalar_bar_args=gempy_vista.scalar_bar_arguments,
         interpolate_before_map=True,
         opacity=opacity,
-        # flip_scalars=True,
-        # clim=(4,0),
         **kwargs
     )
 
@@ -104,8 +100,9 @@ def set_scalar_data(
     # Substitute the madness of the previous if with match
     match scalar_data_type:
         case ScalarDataType.LITHOLOGY | ScalarDataType.ALL:
-            max_lith = data.n_surfaces # (for basement)
-            structured_grid.cell_data['id'] = max_lith - (data.lith_block - 1)
+            max_lith = data.n_surfaces + 1 # (for basement)
+            block_ = max_lith - (data.lith_block - 1)
+            structured_grid.cell_data['id'] = block_
         case ScalarDataType.SCALAR_FIELD | ScalarDataType.ALL:
             scalar_field_ = 'sf_'
             for e in range(data.scalar_field_matrix.shape[0]):

gempy_viewer/modules/plot_3d/plot_3d_utils.py

@@ -26,6 +26,17 @@ def select_surfaces_data(data_df: pd.DataFrame, surfaces: Union[str, list[str]]
 
 def set_scalar_bar(gempy_vista: GemPyToVista, elements_names: list[str],
                    surfaces_ids: np.ndarray, custom_colors: list = None):
+    """
+   
+    LookupTable (0x7f3d1dc62e00)
+      Table Range:                (0.0, 2.0)
+      N Values:                   256
+      Above Range Color:          None
+      Below Range Color:          None
+      NAN Color:                  Color(name='darkgray', hex='#a9a9a9ff', opacity=255)
+      Log Scale:                  False
+      Color Map:                  "viridis"
+    """ 
     import pyvista as pv
 
     # Get mapper actor 
@@ -60,7 +71,7 @@ def set_scalar_bar(gempy_vista: GemPyToVista, elements_names: list[str],
 
         custom_cmap = ListedColormap(custom_colors)
         # Apply the custom colormap to the lookup table
-        lut.apply_cmap(cmap=custom_cmap, n_values=n_colors)
+        lut.apply_cmap(cmap=custom_cmap, n_values=n_colors, flip=True)
 
     else:
         # Apply a default colormap if no custom colors are provided
@@ -69,7 +80,7 @@ def set_scalar_bar(gempy_vista: GemPyToVista, elements_names: list[str],
     # Configure scalar bar arguments
     sargs = gempy_vista.scalar_bar_arguments
     min_id, max_id = surfaces_ids.min(), surfaces_ids.max()
-    mapper_actor.mapper.scalar_range = (min_id-.4 , max_id + .5)
+    mapper_actor.mapper.scalar_range = (min_id - .4, max_id + .5)
     sargs["mapper"] = mapper_actor.mapper
     sargs["n_labels"] = 0
 

tests/test_plotting/test_plot_3d.py

@@ -9,6 +9,7 @@
 
 np.random.seed(1234)
 
+
 class TestPlot3dInputData:
     def test_plot_3d_input_data(self, one_fault_model_no_interp):
         gpv.plot_3d(one_fault_model_no_interp, image=True)
@@ -18,19 +19,56 @@ class TestPlot3DSolutions:
     def test_plot_3d_solutions_default(self, one_fault_model_topo_solution):
         print(one_fault_model_topo_solution.structural_frame)
         gpv.plot_3d(one_fault_model_topo_solution, image=True)
-    
+
     def test_plot_3d_solutions(self, one_fault_model_topo_solution):
+        print(one_fault_model_topo_solution.structural_frame)
+        gpv.plot_3d(
+            model=one_fault_model_topo_solution,
+            show_topography=True,
+            show_scalar=False,
+            show_lith=True,
+            show_data=True,
+            show_boundaries=True,
+            image=True
+        )
+
+    def test_plot_3d_solutions_volume_and_input(self, one_fault_model_topo_solution):
+        print(one_fault_model_topo_solution.structural_frame)
+        gpv.plot_3d(
+            model=one_fault_model_topo_solution,
+            show_topography=False,
+            show_scalar=False,
+            show_lith=True,
+            show_data=True,
+            show_boundaries=True,
+            image=True,
+            kwargs_plot_structured_grid = {'opacity': 0.5}
+        )
+
+    def test_plot_3d_solutions_only_volume(self, one_fault_model_topo_solution):
         print(one_fault_model_topo_solution.structural_frame)
         gpv.plot_3d(
             model=one_fault_model_topo_solution,
             show_topography=False,
             show_scalar=False,
             show_lith=True,
             show_data=False,
+            show_boundaries=False,
+            image=True
+        )
+
+    def test_plot_3d_solutions_only_input(self, one_fault_model_topo_solution):
+        print(one_fault_model_topo_solution.structural_frame)
+        gpv.plot_3d(
+            model=one_fault_model_topo_solution,
+            show_topography=False,
+            show_scalar=False,
+            show_lith=False,
+            show_data=True,
             show_boundaries=True,
             image=True
         )
-    
+
     def test_plot_3d_scalar_field(self, one_fault_model_topo_solution):
         gpv.plot_3d(
             model=one_fault_model_topo_solution,
@@ -39,15 +77,15 @@ def test_plot_3d_scalar_field(self, one_fault_model_topo_solution):
             show_lith=False,
             image=True
         )
-    
+
     def test_plot_3d_solutions_topography(self, one_fault_model_topo_solution):
         gpv.plot_3d(
             model=one_fault_model_topo_solution,
             show_topography=True,
             topography_scalar_type=TopographyDataType.TOPOGRAPHY,
             image=True
         )
-    
+
     def test_plot_3d_solutions_topography_geological_map(self, one_fault_model_topo_solution):
         gpv.plot_3d(
             model=one_fault_model_topo_solution,
@@ -83,6 +121,5 @@ def one_fault_model_topo_solution_octrees(self) -> GeoModel:
         gp.compute_model(one_fault_model)
         return one_fault_model
 
-
     def test_plot_3d_solutions_default(self, one_fault_model_topo_solution_octrees):
         gpv.plot_3d(one_fault_model_topo_solution_octrees, image=True)