WIP

src/xtgeo/well/_welldata.py

@@ -20,9 +20,12 @@
 similarly of a column is removed, the corresponding entries in wlogtypes and wlogrecords
 will be deleted.
 """
+from __future__ import annotations
+
 import math
 from dataclasses import dataclass, field
 from enum import Enum, EnumMeta, unique
+from typing import Any, Optional
 
 import numpy as np
 import pandas as pd
@@ -31,8 +34,6 @@
 from xtgeo import XTGeoCLibError  # type: ignore[attr-defined]
 from xtgeo.cxtgeo import _cxtgeo
 
-from . import _well_aux
-
 
 class _LogTypeMeta(EnumMeta):
     """For enabling 'in' method, cf https://stackoverflow.com/questions/43634618"""
@@ -69,20 +70,20 @@ class _WellData:
 
     The wlogstypes is on form {"PHIT": CONT, "FACIES": DISC, ...}
 
-    The wlogrecords is somewhat heterogenous, on form:
+    The wlogrecords is somewhat heterogeneous, on form:
     {"PHIT": ("unit", "scale"), "FACIES": {0:BG, 2: "SST", 4: "CALC"}}
     Hence the CONT logs hold a tuple or list with 2 str members, or None, while DISC
     log holds a dict where the key is an int and the value is a string.
 
     Note::
 
-    Callers shall not use properties, but methods, e.g.::
+        Callers shall not use properties, but methods, e.g.::
 
-        instance.well = some_new_dataframe   # not
+            instance.well = some_new_dataframe   # not
 
-    but::
+        but
 
-        instance.set_dataframe(some_new_dataframe)
+            instance.set_dataframe(some_new_dataframe)
     """
 
     data: pd.DataFrame
@@ -112,7 +113,12 @@ def _infer_log_dtypes(self):
         datatypes = {}
         for name, dtype in dlist.items():
             if name in self.wlogtypes:
-                datatypes[name] = self.wlogtypes[name]  # keep as is
+                datatypes[name] = self.wlogtypes[name]
+                if "DISC" in datatypes[name]:
+                    datatypes[name] = _LogType.DISC.value
+                else:
+                    datatypes[name] = _LogType.CONT.value
+
                 continue
 
             if name in (self.xname, self.yname, self.zname):
@@ -205,6 +211,7 @@ def ensure_consistency(self):
 
         * When adding one or columns to the dataframe
         * When removing one or more columns from the dataframe
+        * ...
         """
 
         if list(self.data.columns[:3]) != [self.xname, self.yname, self.zname]:
@@ -213,6 +220,7 @@ def ensure_consistency(self):
                 f"and '{self.zname}', got {list(self.data.columns[:3])}"
             )
 
+        # order matters:
         self._ensure_consistency_wlogtypes()
         self._ensure_consistency_wlogrecords()
         self._ensure_consistency_df_dtypes()
@@ -232,7 +240,7 @@ def set_wlogtype(self, name: str, wtype: str) -> None:
             apply_wtype = "DISC"
 
         if name not in self.wlogtypes:
-            raise ValueError(f"No such well log name present: {name}")
+            raise ValueError(f"No such log name present: {name}")
 
         if apply_wtype in _LogType:
             self.wlogtypes[name] = _LogType(apply_wtype)
@@ -247,7 +255,7 @@ def set_wlogrecord(self, name: str, record: dict) -> None:
         """Set a wlogrecord for a named log."""
 
         if name not in self.wlogtypes:
-            raise ValueError(f"No such well log name present: {name}")
+            raise ValueError(f"No such logname: {name}")
 
         if self.wlogtypes[name] == _LogType.CONT.value and isinstance(
             record, (list, tuple)
@@ -265,11 +273,13 @@ def set_wlogrecord(self, name: str, record: dict) -> None:
             record, dict
         ):
             raise ValueError(
-                "Cannot set a log record for a discrete log: input record is "
-                "not a dictionary"
+                "Input is not a dictionary. Cannot set a log record for a discrete log"
             )
         else:
-            raise ValueError("Something went wrong when setting logrecord.")
+            raise ValueError(
+                "Something went wrong when setting logrecord: "
+                f"({self.wlogtypes[name]} {type(record)})."
+            )
 
         self.ensure_consistency()
 
@@ -401,9 +411,9 @@ def geometrics(self):
             )
 
         # extract numpies from XYZ trajetory logs
-        ptr_xv = _well_aux.get_carray(self, "X_UTME")
-        ptr_yv = _well_aux.get_carray(self, "Y_UTMN")
-        ptr_zv = _well_aux.get_carray(self, "Z_TVDSS")
+        ptr_xv = self._get_carray(self.xname)
+        ptr_yv = self._get_carray(self.yname)
+        ptr_zv = self._get_carray(self.zname)
 
         # get number of rows in pandas
         nlen = len(self.data.index)
@@ -447,7 +457,7 @@ def _convert_np_carr_int(self, np_array):
 
         The numpy is always a double (float64), so need to convert first
         """
-        carr = _cxtgeo.new_intarray(self.nrow)
+        carr = _cxtgeo.new_intarray(len(self.data.index))
 
         np_array = np_array.astype(np.int32)
 
@@ -457,7 +467,7 @@ def _convert_np_carr_int(self, np_array):
 
     def _convert_np_carr_double(self, np_array):
         """Convert numpy 1D array to C array, assuming double type."""
-        carr = _cxtgeo.new_doublearray(self.nrow)
+        carr = _cxtgeo.new_doublearray(len(self.data.index))
 
         _cxtgeo.swig_numpy_to_carr_1d(np_array, carr)
 
@@ -466,8 +476,26 @@ def _convert_np_carr_double(self, np_array):
     def _convert_carr_double_np(self, carray, nlen=None):
         """Convert a C array to numpy, assuming double type."""
         if nlen is None:
-            nlen = len(self._wdata.data.index)
+            nlen = len(self.data.index)
 
         nparray = _cxtgeo.swig_carr_to_numpy_1d(nlen, carray)
 
         return nparray
+
+    def _get_carray(self, lname: str) -> Optional[Any]:
+        """Returns the C array pointer (via SWIG) for a given log.
+
+        Type conversion is double if float64, int32 if DISC log.
+        Returns None if log does not exist.
+        """
+        if lname in self.data:
+            np_array = self.data[lname].values
+        else:
+            return None
+
+        if "DISC" in self.wlogtypes[lname]:
+            carr = self._convert_np_carr_int(np_array)
+        else:
+            carr = self._convert_np_carr_double(np_array)
+
+        return carr

src/xtgeo/well/well1.py

@@ -4,7 +4,6 @@
 from __future__ import annotations
 
 import io
-import math
 from copy import deepcopy
 from pathlib import Path
 from typing import Dict, List, Optional, Union