Use step_begin, step_end when exporting to hoc if present

bluepyopt/ephys/create_hoc.py

@@ -108,6 +108,9 @@ def range_exprs_to_hoc(range_params):
         value = re.sub(r'\&', '&&', value)
         value = re.sub('{distance}', FLOAT_FORMAT, value)
         value = re.sub('{value}', format_float(param.value), value)
+        if hasattr(param.value_scaler, "step_begin"):
+            value = re.sub('{step_begin}', format_float(param.value_scaler.step_begin), value)
+            value = re.sub('{step_end}', format_float(param.value_scaler.step_end), value)
         ret.append(Range(param.location, param.name, value))
     return ret
 

bluepyopt/ephys/parameterscalers/parameterscalers.py

@@ -162,7 +162,7 @@ def inst_distribution(self):
         return string.Formatter().vformat(self.distribution, (), dist_dict)
 
     def scale_dict(self, values, distance):
-        """Create scale disctionary"""
+        """Create scale dictionary"""
         scale_dict = {}
         if isinstance(values, dict):
             for k, v in values.items():
@@ -204,7 +204,6 @@ def scale(self, values, segment, sim=None):
 
         # Find something to generalise this
         import math  # pylint:disable=W0611 #NOQA
-        import numpy
 
         # This eval is unsafe (but is it ever dangerous ?)
         # pylint: disable=W0123
@@ -290,7 +289,7 @@ def __init__(
             distribution (str): distribution of parameter dependent on distance
                 from soma. string can contain `distance` and/or `value` as
                 placeholders for the distance to the soma and parameter value
-                respectivily
+                respectivily. It can also contain step_begin and step_end.
             dist_param_names (list): list of names of parameters that
                 parametrise the distribution. These names will become
                 attributes of this object.