[MRG] Add name parameter to tonic bias and add tonic biases to different sections

doc/whats_new.rst

@@ -41,6 +41,10 @@ API
 - Add :func:`~hnn_core.CellResponse.spike_times_by_type` to get cell spiking times
   organized by cell type, by `Mainak Jas`_ in :gh:`916`.
 
+- Add option to apply a tonic bias to any compartment of the cell, and option to 
+  add multiple biases per simulation and cell :func:`hnn_core.network.add_tonic_bias`, 
+  by `Katharina Duecker`_ in :gh:`922`.
+
 .. _0.4:
 
 0.4

hnn_core/cell.py

@@ -728,8 +728,9 @@ def _insert_dipole(self, sec_name_apical):
             dpp.ztan = seg_lens_z[-1]
         self.dipole = h.Vector().record(self.dpl_ref)
 
-    def create_tonic_bias(self, amplitude, t0, tstop, loc=0.5):
-        """Create tonic bias at the soma.
+    def create_tonic_bias(self, amplitude, t0, tstop, section='soma',
+                          loc=0.5):
+        """Create tonic bias at defined section.
 
         Parameters
         ----------
@@ -739,10 +740,13 @@ def create_tonic_bias(self, amplitude, t0, tstop, loc=0.5):
             The start time of tonic input (in ms).
         tstop : float
             The end time of tonic input (in ms).
+        section : str
+            Section tonic input is applied to.
         loc : float (0 to 1)
-            The location of the input in the soma section.
+            The location of the input in the section.
         """
-        stim = h.IClamp(self._nrn_sections['soma'](loc))
+
+        stim = h.IClamp(self._nrn_sections[section](loc))
         stim.delay = t0
         stim.dur = tstop - t0
         stim.amp = amplitude

hnn_core/network.py

@@ -1133,7 +1133,8 @@ def _instantiate_drives(self, tstop, n_trials=1):
                 self.external_drives[
                     drive['name']]['events'].append(event_times)
 
-    def add_tonic_bias(self, *, cell_type=None, amplitude, t0=0, tstop=None):
+    def add_tonic_bias(self, *, cell_type=None, section='soma',
+                       bias_name='tonic', amplitude, t0=0, tstop=None):
         """Attaches parameters of tonic bias input for given cell types
 
         Parameters
@@ -1142,6 +1143,11 @@ def add_tonic_bias(self, *, cell_type=None, amplitude, t0=0, tstop=None):
             The name of the cell type to add a tonic input. When supplied,
             a float value must be provided with the `amplitude` keyword.
             Valid inputs are those listed in  `net.cell_types`.
+        section : str
+            name of cell section the bias should be applied to.
+            See net.cell_types[cell_type].sections.keys()
+        bias_name : str
+            The name of the bias.
         amplitude: dict | float
             A dictionary of cell type keys (str) to amplitude values (float).
             Valid inputs for cell types are those listed in `net.cell_types`.
@@ -1169,6 +1175,7 @@ def add_tonic_bias(self, *, cell_type=None, amplitude, t0=0, tstop=None):
             _validate_type(amplitude, (float, int), 'amplitude')
 
             _add_cell_type_bias(network=self, cell_type=cell_type,
+                                section=section, bias_name=bias_name,
                                 amplitude=float(amplitude),
                                 t_0=t0, t_stop=tstop)
         else:
@@ -1180,6 +1187,7 @@ def add_tonic_bias(self, *, cell_type=None, amplitude, t0=0, tstop=None):
 
             for _cell_type, _amplitude in amplitude.items():
                 _add_cell_type_bias(network=self, cell_type=_cell_type,
+                                    section=section, bias_name=bias_name,
                                     amplitude=_amplitude,
                                     t_0=t0, t_stop=tstop)
 
@@ -1648,7 +1656,7 @@ def __repr__(self):
 
 
 def _add_cell_type_bias(network: Network, amplitude: Union[float, dict],
-                        cell_type=None,
+                        cell_type=None, section='soma', bias_name='tonic',
                         t_0=0, t_stop=None):
 
     if network is None:
@@ -1665,15 +1673,27 @@ def _add_cell_type_bias(network: Network, amplitude: Union[float, dict],
                              f'{list(network.cell_types.keys())}. '
                              f'Got {cell_type}')
 
-        if 'tonic' not in network.external_biases:
-            network.external_biases['tonic'] = dict()
+        if bias_name not in network.external_biases:
+            network.external_biases[bias_name] = dict()
 
-        if cell_type in network.external_biases['tonic']:
-            raise ValueError(f'Tonic bias already defined for {cell_type}')
+        if cell_type in network.external_biases[bias_name]:
+            raise ValueError(f'Bias named {bias_name} already defined '
+                             f'for {cell_type}')
 
         cell_type_bias = {
             'amplitude': amplitude,
             't0': t_0,
-            'tstop': t_stop
+            'tstop': t_stop,
+            'section': section
         }
-        network.external_biases['tonic'][cell_type] = cell_type_bias
+
+        sections = list(network.cell_types[cell_type].sections.keys())
+
+        # error when section is defined that doesn't exist.
+        if section not in sections:
+            raise ValueError(f"section must be one of {sections}. "
+                             f"Got {section}.")
+        else:
+            cell_type_bias['section'] = section
+
+        network.external_biases[bias_name][cell_type] = cell_type_bias

hnn_core/network_builder.py

@@ -441,10 +441,10 @@ def _create_cells_and_drives(self, threshold, record_vsec=False,
                 else:
                     cell.build()
                 # add tonic biases
-                if ('tonic' in self.net.external_biases and
-                        src_type in self.net.external_biases['tonic']):
-                    cell.create_tonic_bias(**self.net.external_biases
-                                           ['tonic'][src_type])
+                for bias in self.net.external_biases:
+                    if src_type in self.net.external_biases[bias]:
+                        cell.create_tonic_bias(**self.net.external_biases
+                                               [bias][src_type])
                 cell.record(record_vsec, record_isec, record_ca)
 
                 # this call could belong in init of a _Cell (with threshold)?

hnn_core/tests/assets/jones2009_3x3_drives.json

@@ -2128,22 +2128,26 @@
             "L2_pyramidal": {
                 "amplitude": 1.0,
                 "t0": 0,
-                "tstop": null
+                "tstop": null,
+                "section": "soma"
             },
             "L5_pyramidal": {
                 "amplitude": 0.0,
                 "t0": 0,
-                "tstop": null
+                "tstop": null,
+                "section": "soma"
             },
             "L2_basket": {
                 "amplitude": 0.0,
                 "t0": 0,
-                "tstop": null
+                "tstop": null,
+                "section": "soma"
             },
             "L5_basket": {
                 "amplitude": 0.0,
                 "t0": 0,
-                "tstop": null
+                "tstop": null,
+                "section": "soma"
             }
         }
     },

hnn_core/tests/test_network.py

@@ -855,9 +855,22 @@ def test_tonic_biases():
     assert 'tonic' in net.external_biases
     assert 'L5_pyramidal' not in net.external_biases['tonic']
     assert net.external_biases['tonic']['L2_pyramidal']['t0'] == 0
-    with pytest.raises(ValueError, match=r'Tonic bias already defined for.*$'):
+    with pytest.raises(ValueError, match=r'Bias named tonic already defined '
+                       r'for.*$'):
         net.add_tonic_bias(amplitude=tonic_bias_2)
 
+    net = jones_2009_model()
+    net.add_tonic_bias(amplitude=tonic_bias_2, bias_name='tonic_2', t0=100)
+    assert 'tonic_2' in net.external_biases
+    assert net.external_biases['tonic_2']['L2_pyramidal']['t0'] == 100
+
+    # non-existent section
+    net.external_biases = dict()
+
+    with pytest.raises(ValueError, match=(r'section must be one of .*'
+                                          ' Got apical_4.')):
+        net.add_tonic_bias(amplitude={'L2_pyramidal': .5}, section='apical_4')
+
 
 def test_network_mesh():
     """Test mesh for defining cell positions biases."""