feat: added ntgs converter

LoopDataConverter/converters/ntgs_converter.py

@@ -1,35 +1,69 @@
+# internal imports
 from .base_converter import BaseConverter
+from ..utils import (
+    convert_dipdir_terms,
+    convert_dip_terms,
+    convert_tightness_terms,
+    convert_displacement_terms,
+)
+
+# external imports
 import pandas
 import numpy
 
 
 class NTGSConverter(BaseConverter):
     def __init__(self, data: pandas.DataFrame):
-        self.data = data
+        self.raw_data = data.copy()
         self._type_label = "NTGSConverter"
+        self._data = None
 
     def type(self):
         return self._type_label
 
     def convert_fold_map(self):
-        pass
+        # convert dip direction terms to degrees
+        self.raw_data["AxialPlaneDipDir"] = self.raw_data["AxialPlaneDipDir"].apply(
+            lambda x: convert_dipdir_terms(x)
+        )
+        # convert dip terms to degrees
+        self.raw_data["AxialPlaneDip"] = self.raw_data["AxialPlaneDip"].apply(
+            lambda x: convert_dip_terms(x, type="fold")
+        )
+        # convert tightness terms to degrees
+        self.raw_data["InterlimbAngle"] = self.raw_data["InterlimbAngle"].apply(
+            lambda x: convert_tightness_terms(x)
+        )
 
     def convert_fault_map(self):
-        pass
-
-    def convert_geology_map(self):
-        pass
+        # convert dip direction terms to degrees
+        self.raw_data["DipDirection"] = self.raw_data["DipDirection"].apply(
+            lambda x: convert_dipdir_terms(x)
+        )
+        # convert dip terms to degrees
+        self.raw_data["Dip"] = self.raw_data["Dip"].apply(
+            lambda x: convert_dip_terms(x, type="fault")
+        )
+        self.raw_data["Displacement"] = self.raw_data["Displacement"].apply(
+            lambda x: convert_displacement_terms(x)
+        )
 
     def convert_structure_map(self):
         # discard any rows that has a dip value of -99 and does not have any esimated dip value
-        condition = (self.data["Dip"] != -99) & (self.data["DipEstimate"] != numpy.nan)
-        self.data = self.data[condition]
+        condition = (self.raw_data["Dip"] != -99) & (
+            self.raw_data["DipEstimate"] != numpy.nan
+        )
+        self.raw_data = self.raw_data[condition]
         # convert dip estimate to float (average of the range)
-        condition = self.data["Dip"] == -99
-        self.data.loc[condition, "DipEstimate"] = self.data.loc[
+        condition = self.raw_data["Dip"] == -99
+        self.raw_data.loc[condition, "DipEstimate"] = self.raw_data.loc[
             condition, "DipEstimate"
         ].apply(lambda x: sum(map(float, x.split("-"))) / 2)
-        self.data[condition, "Dip"] = self.data[condition, "DipEstimate"]
+        self.raw_data[condition, "Dip"] = self.raw_data[condition, "DipEstimate"]
 
     def convert(self):
-        pass
+        self.convert_fold_map()
+        self.convert_fault_map()
+        self.convert_structure_map()
+
+        self._data = self.raw_data.copy()