[CLN] A bit of cleaning before I figure out what to do next

Author: Leguark

docs/dev_logs/2025_May.md

@@ -10,7 +10,12 @@
 - [ ] Create a robust api to make sure we do not mess up assigning priors to gempy parameters
 - [ ] do we need to use index_put or just normal indexing?
 --- Vector examples
-- [ ] Bring the Vector example here...
+- [ ] Bring the Vector examples here...
+  - Stonepark
+    - Gravity
+    - Multidimensional likelihood
+  - spremberg
+    - Categories
 - [ ] Using categories as likelihood function (maybe I need to check out with Sam)
 --- MinEye
 - [ ] Revive magnetics
@@ -20,7 +25,7 @@
 - [x] Compressing code
 - [x] GemPy posterior visualization
 - [x] Add proper thickness likelihood
-- [ ] Segmentation function 
+- [x] Segmentation function 
 - [ ] Speed: Blocked by having a model that is not too big.
   - [ ] Time test for torch CPU
   - [ ] Time test for keops CPU

gempy_probability/modules/model_definition/model_examples.py

@@ -9,7 +9,7 @@
 import torch
 
 
-def model(geo_model: gempy.core.data.GeoModel, normal, y_obs_list):
+def two_wells_prob_model_I(geo_model: gempy.core.data.GeoModel, normal, y_obs_list):
     """
     This Pyro model represents the probabilistic aspects of the geological model.
     It defines a prior distribution for the top layer's location and 

tests/test_prob_model/test_prob_I.py

@@ -47,10 +47,10 @@ def test_basic_gempy_I() -> None:
         scale=torch.tensor(0.1, dtype=torch.float64)
     )
 
-    from gempy_probability.modules.model_definition.model_examples import model
+    from gempy_probability.modules.model_definition.model_examples import two_wells_prob_model_I
     _prob_run(
         geo_model=geo_model,
-        prob_model=model,
+        prob_model=two_wells_prob_model_I,
         normal=normal,
         y_obs_list=torch.tensor([200, 210, 190])
     )