Added hoc modifier to models

bluepyopt/deapext/algorithms.py

@@ -24,6 +24,8 @@
 
 import random
 import logging
+import os
+import shutil
 
 import deap.algorithms
 import deap.tools
@@ -94,6 +96,9 @@ def eaAlphaMuPlusLambdaCheckpoint(
         continue_cp(bool): whether to continue
     """
 
+    if cp_filename:
+        cp_filename_tmp = str(cp_filename) + '.tmp'
+
     if continue_cp:
         # A file name has been given, then load the data from the file
         cp = pickle.load(open(cp_filename, "rb"))
@@ -149,8 +154,10 @@ def eaAlphaMuPlusLambdaCheckpoint(
                       history=history,
                       logbook=logbook,
                       rndstate=random.getstate())
-            pickle.dump(cp, open(cp_filename, "wb"))
-            logger.debug('Wrote checkpoint to %s', cp_filename)
+            pickle.dump(cp, open(cp_filename_tmp, "wb"))
+            if os.path.isfile(cp_filename_tmp):
+                shutil.copy(cp_filename_tmp, cp_filename)
+                logger.debug('Wrote checkpoint to %s', cp_filename)
 
         gen += 1
         stopping_params["gen"] = gen

bluepyopt/deapext/optimisationsCMA.py

@@ -24,6 +24,8 @@
 import pickle
 import random
 import functools
+import os
+import shutil
 
 import deap.tools
 
@@ -223,7 +225,9 @@ def run(self,
         """
 
         stats = self.get_stats()
-
+        if cp_filename:
+            cp_filename_tmp = str(cp_filename) + '.tmp'
+
         if continue_cp:
 
             # A file name has been given, then load the data from the file
@@ -308,8 +312,10 @@ def run(self,
                           rndstate=random.getstate(),
                           np_rndstate=numpy.random.get_state(),
                           CMA_es=CMA_es)
-                pickle.dump(cp, open(cp_filename, "wb"))
-                logger.debug('Wrote checkpoint to %s', cp_filename)
+                pickle.dump(cp, open(cp_filename_tmp, "wb"))
+                if os.path.isfile(cp_filename_tmp):
+                    shutil.copy(cp_filename_tmp, cp_filename)
+                    logger.debug('Wrote checkpoint to %s', cp_filename)
 
                 CMA_es.map_function = temp_mf
 

bluepyopt/ephys/models.py

@@ -1,7 +1,7 @@
 """Cell template class"""
 
 """
-Copyright (c) 2016, EPFL/Blue Brain Project
+Copyright (c) 2016-2020, EPFL/Blue Brain Project
 
  This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
 
@@ -65,12 +65,15 @@ class CellModel(Model):
     """Cell model class"""
 
     def __init__(
-            self,
-            name,
-            morph=None,
-            mechs=None,
-            params=None,
-            gid=0):
+        self,
+        name,
+        morph=None,
+        mechs=None,
+        params=None,
+        gid=0,
+        seclist_names=None,
+        secarray_names=None
+    ):
         """Constructor
 
         Args:
@@ -83,8 +86,14 @@ def __init__(
                 Mechanisms associated with the cell
             params (list of Parameters):
                 Parameters of the cell model
+            seclist_names (list of strings):
+                Names of the lists of sections
+            secarray_names (list of strings):
+                Names of the sections
         """
+
         super(CellModel, self).__init__(name)
+
         self.check_name()
         self.morphology = morph
         self.mechanisms = mechs
@@ -98,10 +107,20 @@ def __init__(
 
         self.param_values = None
         self.gid = gid
-        self.seclist_names = \
-            ['all', 'somatic', 'basal', 'apical', 'axonal', 'myelinated']
-        self.secarray_names = \
-            ['soma', 'dend', 'apic', 'axon', 'myelin']
+
+        if seclist_names is None:
+            self.seclist_names = [
+                'all', 'somatic', 'basal', 'apical', 'axonal', 'myelinated'
+            ]
+        else:
+            self.seclist_names = seclist_names
+
+        if secarray_names is None:
+            self.secarray_names = [
+                'soma', 'dend', 'apic', 'axon', 'myelin'
+            ]
+        else:
+            self.secarray_names = secarray_names
 
     def check_name(self):
         """Check if name complies with requirements"""
@@ -282,6 +301,22 @@ def create_hoc(self, param_values,
         else:
             replace_axon = None
 
+        if (
+            self.morphology.morph_modifiers is not None
+            and self.morphology.morph_modifiers_hoc is None
+        ):
+            logger.warning('You have provided custom morphology modifiers, \
+                            but no corresponding hoc files.')
+        elif (
+            self.morphology.morph_modifiers is not None
+            and self.morphology.morph_modifiers_hoc is not None
+        ):
+            if replace_axon is None:
+                replace_axon = ''
+            for morph_modifier_hoc in self.morphology.morph_modifiers_hoc:
+                replace_axon += '\n'
+                replace_axon += morph_modifier_hoc
+
         ret = create_hoc.create_hoc(mechs=self.mechanisms,
                                     parameters=self.params.values(),
                                     morphology=morphology,
@@ -637,6 +672,7 @@ def instantiate(self, sim=None):
         self.LFPyCell = LFPy.Cell(morphology=sim.neuron.h.allsec(), 
                                   dt=self.dt,
                                   v_init=self.v_init,
+                                  pt3d=True,
                                   delete_sections=False,
                                   nsegs_method=None)
 

bluepyopt/ephys/morphologies.py

@@ -139,7 +139,14 @@ def instantiate(self, sim=None, icell=None):
         if self.morph_modifiers is not None:
             for morph_modifier in self.morph_modifiers:
                 morph_modifier(sim=sim, icell=icell)
-
+
+        if self.morph_modifiers_hoc is not None:
+            hoc_modifiers = ''
+            for morph_modifier_hoc in self.morph_modifiers_hoc:
+                hoc_modifiers += morph_modifier_hoc
+                hoc_modifiers += '\n'
+            sim.neuron.h(hoc_modifiers)
+
     def destroy(self, sim=None):
         """Destroy morphology instantiation"""
         pass

bluepyopt/ephys/parameters.py

@@ -217,6 +217,7 @@ def instantiate(self, sim=None, icell=None):
         for location in self.locations:
             iseclist = location.instantiate(sim=sim, icell=icell)
             for section in iseclist:
+                print(section, self.param_name)
                 setattr(section, self.param_name,
                         self.value_scale_func(self.value, section, sim=sim))
             logger.debug(

bluepyopt/ephys/parameterscalers.py

@@ -1,7 +1,7 @@
 """Parameter scaler classes"""
 
 """
-Copyright (c) 2016, EPFL/Blue Brain Project
+Copyright (c) 2016-2020, EPFL/Blue Brain Project
 
  This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
 
@@ -96,7 +96,8 @@ def __init__(
             name=None,
             distribution=None,
             comment='',
-            dist_param_names=None):
+            dist_param_names=None,
+            soma_ref_location=0.5):
         """Constructor
 
         Args:
@@ -110,12 +111,19 @@ def __init__(
                 object.
                 The distribution string should contain these names, and they
                 will be replaced by values of the corresponding attributes
+            soma_ref_location (float): location along the soma used as origin
+                from which to compute the distances. Expressed as a fraction
+                (between 0.0 and 1.0).
         """
 
         super(NrnSegmentSomaDistanceScaler, self).__init__(name, comment)
         self.distribution = distribution
 
         self.dist_param_names = dist_param_names
+        self.soma_ref_location = soma_ref_location
+
+        if not(0. <= self.soma_ref_location <= 1.):
+            raise ValueError('soma_ref_location must be between 0 and 1.')
 
         if self.dist_param_names is not None:
             for dist_param_name in self.dist_param_names:
@@ -160,7 +168,7 @@ def scale(self, value, segment, sim=None):
         soma = segment.sec.cell().soma[0]
 
         # Initialise origin
-        sim.neuron.h.distance(0, 0.5, sec=soma)
+        sim.neuron.h.distance(0, self.soma_ref_location, sec=soma)
 
         distance = sim.neuron.h.distance(1, segment.x, sec=segment.sec)