Fix interpolation for u0 (#3)

* ensure u0 is linearly interpolated

* fix pandas future deprecation

* bump version

---------

Co-authored-by: Julien Hericher <[email protected]>

Author: Julien76

CHANGES.md

@@ -1,5 +1,12 @@
 # Changes
 
+## Version 0.1.6:
+
+**date: 2024-09-26**
+
+- missing data interpolation: ensure that u0 is always linearly interpolated
+- fix interpolation warning from pandas future deprecation
+
 ## Version 0.1.5:
 
 **date: 2024-09-24**

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "ngi-calculations"
-version = "0.1.5"
+version = "0.1.6"
 description = "CPT correlations including commonly used empirical correlations"
 authors = [
     "Julien Hericher <[email protected]>", 

src/ngi_calculations/cpt_correlations/methods/cpt_process/calculations.py

@@ -170,7 +170,12 @@ def _integrate_lab_profile(self):
         _df.set_index(depth, drop=False, inplace=True)
 
         # Interpolate the missing values.
-        _df = interpolate_missing_values(_df, key_col=depth, col_list=lab_cols, mode=self.options.interpolation_mode)
+        _df = interpolate_missing_values(
+            _df, key_col=depth, col_list=[c for c in lab_cols if c != "u0"], mode=self.options.interpolation_mode
+        )
+
+        # Handle u0 differently as it should always be interpolated linearly
+        _df = interpolate_missing_values(_df, key_col=depth, col_list=["u0"], mode=self.options.interpolation_mode)
 
         # # Prevent values for certain lab profiles to go below zero
         # _df[GEO.u0.key] = _df[GEO.u0.key].clip(lower=0.0)

src/ngi_calculations/cpt_correlations/utils/interpolation.py

@@ -18,7 +18,7 @@ def interpolate_missing_values__padding_method(df: pd.DataFrame, inplace: bool =
     _cols = set_replace_columns(_df, col_list)
 
     for col in _cols:
-        _df[col] = _df[col].interpolate(method="pad")
+        _df[col] = _df[col].ffill()
 
     return _df