update class docstrings

bw_timex/dynamic_biosphere_builder.py

@@ -11,8 +11,7 @@
 
 class DynamicBiosphereBuilder:
     """
-    Class for building a dynamic biosphere matrix with dimensions
-    (biosphere flow at a specific point in time) x (processes)
+    Class for building a dynamic biosphere matrix with dimensions (biosphere flow at a specific point in time) x (processes)
     """
 
     def __init__(

bw_timex/matrix_modifier.py

@@ -9,10 +9,12 @@
 
 class MatrixModifier:
     """
-    This class is responsible for modifying the original LCA matrices to contain the time-explicit processes and to relink them to the time-explicit background databases.
-
-    It does this by creating datapackages that add or change matrix entries in technosphere and biosphere matrices, based on a timeline dataframe (created from TimelineBuilder.build_timeline()).
+    Class for adding and re-linking time-explicit processes in the LCA matrices.
 
+    This is done by creating datapackages that add or change matrix entries in the technosphere and
+    biosphere matrices, based on a process timeline (from TimelineBuilder.build_timeline()).
+    "Temporal markets" are created for processes that are linked to background databases, temporally
+    distributing the amounts to time-explicit background databases.
     """
 
     def __init__(

bw_timex/timeline_builder.py

@@ -18,10 +18,11 @@
 
 class TimelineBuilder:
     """
-    This class is responsible for building a timeline of processes based on the temporal relationship of the priority-first graph traversal.
+    Class for building a process timeline based on the temporal distributions of their exchanges.
 
-    First, the `EdgeExtractor` is called and it extracts a timeline of exchanges (edge_timeline) with temporal information.
-    Identical edges within temporal grouping (e.g. year, month, day, hour) are then grouped together and the amount of exchanges is summed up.
+    First, the `EdgeExtractor` does a priority-first graph traversal and extracts a timeline of
+    exchanges (edge_timeline) with temporal information. Identical edges within temporal grouping
+    (e.g. year, month, day, hour) are then grouped and the amount of exchanges is summed up.
     """
 
     def __init__(