Refactor input and output units

scaling/froude.py

@@ -9,18 +9,18 @@ TIME_EXPONENT = 1 / 2
 MASS_EXPONENT = 3
 
 
-def _convert(x, length_scale_factor, from_unit, to_unit):
+def _convert(x, length_scale_factor, input_unit, target_unit):
 
     # Calculate unit conversion factor
-    from_unit = UREG(from_unit)
-    to_unit = UREG(to_unit)
-    unit_conversion_factor = from_unit.to(to_unit).magnitude
+    input_unit = UREG(input_unit)
+    target_unit = UREG(target_unit)
+    unit_conversion_factor = input_unit.to(target_unit).magnitude
 
     # Calculate Froude scaling factor
     froude_scale_factor = length_scale_factor**(
-        from_unit.dimensionality['[length]'] * LENGTH_EXPONENT +
-        from_unit.dimensionality['[time]'] * TIME_EXPONENT +
-        from_unit.dimensionality['[mass]'] * MASS_EXPONENT)
+        input_unit.dimensionality['[length]'] * LENGTH_EXPONENT +
+        input_unit.dimensionality['[time]'] * TIME_EXPONENT +
+        input_unit.dimensionality['[mass]'] * MASS_EXPONENT)
 
     # Scale values
     x_scaled = x * froude_scale_factor
@@ -37,14 +37,14 @@ def _convert(x, length_scale_factor, from_unit, to_unit):
     return x_scaled
 
 
-def proto_to_model(x_proto, length_scale, from_unit, to_unit):
+def proto_to_model(x_proto, length_scale, input_unit, target_unit):
     """Convert prototype value(s) to model value(s) in specified units.
 
     Args:
         x_proto:       prototype values (array_like, or pandas dataframe)
         length_scale:  ratio between prototype and model dimensions (float)
-        from_unit (str):  unit of input value(s)
-        to_unit (str):    unit of output value(s)
+        input_unit:    unit of input (string)
+        target_unit:   unit of output (string)
 
     Returns:
         input values in model scale
@@ -52,17 +52,17 @@ def proto_to_model(x_proto, length_scale, from_unit, to_unit):
 
     length_scale_factor = 1 / length_scale
 
-    return _convert(x_proto, length_scale_factor, from_unit, to_unit)
+    return _convert(x_proto, length_scale_factor, input_unit, target_unit)
 
 
-def model_to_proto(x_model, length_scale, from_unit, to_unit):
+def model_to_proto(x_model, length_scale, input_unit, target_unit):
     """Convert model value(s) to prototype value(s) in specified units.
 
     Args:
         x_model:       model values (array_like, or pandas dataframe)
         length_scale:  ratio between prototype and model dimensions (float)
-        from_unit (str):  unit of input value(s)
-        to_unit (str):    unit of output value(s)
+        input_unit:    unit of input (string)
+        target_unit:   unit of output (string)
 
     Returns:
         input values in prototype scale
@@ -70,14 +70,14 @@ def model_to_proto(x_model, length_scale, from_unit, to_unit):
 
     length_scale_factor = length_scale
 
-    return _convert(x_model, length_scale_factor, from_unit, to_unit)
+    return _convert(x_model, length_scale_factor, input_unit, target_unit)
 
 
 def dimensions(unit):
     """Get unit dimensions.
 
     Args:
-        unit (str):  unit name or symbol
+        unit:  unit name or symbol (string)
 
     Returns:
         string containing unit dimensions
@@ -101,7 +101,7 @@ def scaling_exponent(unit):
     """Convert prototype value(s) to model value(s) in specified units.
 
     Args:
-        unit (str):  unit of quantity to be scaled
+        unit:  unit of quantity to be scaled (string)
 
     Returns:
         scaling factor