Merge ebd261e into 9cbe65f

.travis.yml

@@ -1,8 +1,5 @@
 language: python
 python:
-  - "2.7"
-  - "3.4"
-  - "3.5"
   - "3.6"
   - "3.7"
   - "3.8"

LFPy/__init__.py

@@ -41,7 +41,7 @@
   * run_simulations - Functions to run NEURON simulations
 """
 
-__version__ = "2.0.7"
+from .version import version as __version__
 
 from .pointprocess import Synapse, PointProcess, StimIntElectrode
 from .recextelectrode import RecExtElectrode, RecMEAElectrode

LFPy/alias_method.py

@@ -1,6 +1,5 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
-from __future__ import division
 import numpy as np
 
 

LFPy/alias_method.pyx

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 # cython: language_level=2
 
-from __future__ import division
+
 import numpy as np
 cimport numpy as np
 cimport cython

LFPy/cell.py

@@ -12,7 +12,7 @@
 GNU General Public License for more details.
 """
 
-from __future__ import division
+
 import os
 import neuron
 import numpy as np
@@ -463,8 +463,6 @@ def _create_sectionlists_from_morphology_value(self):
                 self.somalist.append(sec=sec)
                 self.nsomasec += 1
 
-
-
     def _get_idx(self, seclist):
         """Return boolean vector which indexes where segments in seclist
         matches segments in neuron.h.allsec(), rewritten from
@@ -543,6 +541,7 @@ def _set_extracellular(self):
 
         for sec in self.allseclist:
             sec.insert('extracellular')
+        self.extracellular = True
 
     def set_synapse(self, idx, syntype,
                     record_current=False,
@@ -888,8 +887,8 @@ def get_rand_idx_area_and_distribution_norm(self, section='allsec', nidx=1,
         >>> cell = LFPy.Cell(morphology=join('cells', 'cells', 'j4a.hoc'))
         >>> cell.set_rotation(x=4.99, y=-4.33, z=3.14)
         >>> idx = cell.get_rand_idx_area_and_distribution_norm(nidx=10000,
-                                                           fun=ss.norm,
-                                                           funargs=dict(loc=0, scale=200))
+                                                               fun=ss.norm,
+                                                               funargs=dict(loc=0, scale=200))
         >>> bins = np.arange(-30, 120)*10
         >>> plt.hist(cell.zmid[idx], bins=bins, alpha=0.5)
         >>> plt.show()
@@ -924,6 +923,90 @@ def get_rand_idx_area_and_distribution_norm(self, section='allsec', nidx=1,
             p /= p.sum()
             return alias_method(poss_idx, p, nidx)
 
+    def enable_extracellular_stimulation(self, electrode, t_ext=None, n=1, model='inf'):
+        r"""
+        Enable extracellular stimulation with 'extracellular' mechanism.
+        Extracellular potentials are computed from the electrode currents
+        using the pointsource approximation.
+        If 'model' is 'inf' (default), potentials are computed as
+        (:math:`r_i` is the position of a comparment i,
+        :math:`r_e` is the position of an elextrode e, :math:`\sigma` is the
+        conductivity of the medium):
+
+        .. math::
+            V_e(r_i) = \sum_n \frac{I_n}{4 \pi \sigma |r_i - r_n|}
+
+        If model is 'semi', the method of images is used:
+
+        .. math::
+            V_e(r_i) = \sum_n \frac{I_n}{2 \pi \sigma |r_i - r_n|}
+
+
+        Parameters
+        ----------
+        electrode: RecExtElectrode
+            Electrode object with stimulating currents
+        t_ext: np.ndarray or list
+            Time im ms corrisponding to step changes in the provided currents.
+            If None, currents are assumed to have
+            the same time steps as NEURON simulation.
+        n: int
+            Points per electrode to compute spatial averaging
+        model: str
+            'inf' or 'semi'. If 'inf' the medium is assumed to be infinite and
+            homogeneous. If 'semi', the method of
+            images is used.
+
+        Returns
+        -------
+        v_ext: np.ndarray
+            Computed extracellular potentials at cell mid points
+
+        """
+        # access electrode object and append mapping
+        if electrode is not None:
+            # put electrode argument in list if needed
+            if type(electrode) == list:
+                electrodes = electrode
+            else:
+                electrodes = [electrode]
+        else:
+            print("'electrode' is None")
+            return
+
+        assert model in ['inf', 'semi'], "'model' can be 'inf' or 'semi'"
+
+        # extracellular stimulation
+        if np.any([np.any(el.probe.currents != 0) for el in electrodes]):
+            cell_mid_points = np.array([self.xmid, self.ymid, self.zmid]).T
+            n_tsteps = int(self.tstop / self.dt + 1)
+            t_cell = np.arange(n_tsteps) * self.dt
+
+            if t_ext is None:
+                print("Assuming t_ext is the same as simulation time")
+                t_ext = t_cell
+                for electrode in electrodes:
+                    assert electrode.probe.currents.shape[1] == len(t_cell), \
+                        "Discrepancy between t_ext and cell simulation time steps. Provide the 't_ext' argument"
+            else:
+                assert len(t_ext) < len(t_cell), "Stimulation time steps are greater than cell simulation steps"
+
+            v_ext = np.zeros((self.totnsegs, len(t_ext)))
+            for electrode in electrodes:
+                if np.any(np.any(electrode.probe.currents != 0)):
+                    electrode.probe.points_per_electrode = int(n)
+                    electrode.probe.model = model
+                    ve = electrode.probe.compute_field(cell_mid_points)
+                    if len(electrode.probe.currents.shape) == 1:
+                        ve = ve[:, np.newaxis]
+                    v_ext += ve
+
+            self._set_extracellular()
+            self.insert_v_ext(v_ext, np.array(t_ext))
+        else:
+            v_ext = None
+
+        return v_ext
 
     def simulate(self, electrode=None, rec_imem=False, rec_vmem=False,
                  rec_ipas=False, rec_icap=False,
@@ -1995,7 +2078,7 @@ def insert_v_ext(self, v_ext, t_ext):
         v_ext : ndarray
             Numpy array of size cell.totnsegs x t_ext.size, unit mV
         t_ext : ndarray
-            Time vector of v_ext
+            Time vector of v_ext in ms
         Examples
         --------
         >>> import LFPy

LFPy/eegmegcalc.py

@@ -12,7 +12,7 @@
 GNU General Public License for more details.
 """
 
-from __future__ import division
+
 from scipy.special import eval_legendre, lpmv, legendre
 import numpy as np
 from warnings import warn
@@ -1244,16 +1244,16 @@ class MEG(object):
     under the assumption of negligible magnetic induction effects (Nunez and
     Srinivasan, Oxford University Press, 2006):
 
-    .. math:: \mathbf{H} = \\frac{\\mathbf{p} \\times \\mathbf{R}}{4 \pi R^3}
+    .. math:: \\mathbf{H} = \\frac{\\mathbf{p} \\times \\mathbf{R}}{4 \\pi R^3}
 
-    where :math:`\mathbf{p}` is the current dipole moment, :math:`\mathbf{R}`
+    where :math:`\mathbf{p}` is the current dipole moment, :math:`\\mathbf{R}`
     the vector between dipole source location and measurement location, and
-    :math:`R=|\mathbf{R}|`
+    :math:`R=|\\mathbf{R}|`
 
-    Note that the magnetic field :math:`\mathbf{H}` is related to the magnetic
-    field :math:`\mathbf{B}` as :math:`\mu_0 \mathbf{H} = \mathbf{B}-\mathbf{M}`
-    where :math:`\mu_0` is the permeability of free space (very close to
-    permebility of biological tissues). :math:`\mathbf{M}` denotes material
+    Note that the magnetic field :math:`\\mathbf{H}` is related to the magnetic
+    field :math:`\\mathbf{B}` as :math:`\\mu_0 \\mathbf{H} = \\mathbf{B}-\\mathbf{M}`
+    where :math:`\\mu_0` is the permeability of free space (very close to
+    permebility of biological tissues). :math:`\\mathbf{M}` denotes material
     magnetization (also ignored)
 
 
@@ -1264,7 +1264,7 @@ class MEG(object):
         devices where magnetic field of current dipole moments is calculated.
         In unit of (µm)
     mu : float
-        Permeability. Default is permeability of vacuum (mu_0 = 4*pi*1E-7 T*m/A)
+        Permeability. Default is permeability of vacuum (:math:`\\mu_0 = 4*\\pi*10^{-7}` T*m/A)
 
 
     Examples

LFPy/inputgenerators.py

@@ -13,7 +13,7 @@
 
 """
 
-from __future__ import division
+
 import numpy as np
 import scipy.stats
 import warnings

LFPy/lfpcalc.py

@@ -14,7 +14,7 @@
 
 """
 
-from __future__ import division
+
 import numpy as np
 
 

LFPy/network.py

@@ -15,7 +15,7 @@
 GNU General Public License for more details.
 
 """
-from __future__ import division
+
 import numpy as np
 import os
 import scipy.stats as stats
@@ -113,9 +113,9 @@ class NetworkCell
     >>> import LFPy
     >>> cellParameters = {
     >>>     'morphology' : '<path to morphology.hoc>',
-    >>>     'templatefile' :  '<path to template_file.hoc>'
-    >>>     'templatename' :  'templatename'
-    >>>     'templateargs' :  None
+    >>>     'templatefile' :  '<path to template_file.hoc>',
+    >>>     'templatename' :  'templatename',
+    >>>     'templateargs' :  None,
     >>>     'v_init' : -65,
     >>>     'cm' : 1.0,
     >>>     'Ra' : 150,
@@ -853,6 +853,8 @@ def connect(self, pre, post, connectivity,
 
         return COMM.bcast([conncount, syncount])
 
+    def enable_extracellular_stimulation(self, electrode, t_ext=None, n=1, seed=None):
+        raise NotImplementedError()
 
     def simulate(self, electrode=None, rec_imem=False, rec_vmem=False,
                  rec_ipas=False, rec_icap=False,

LFPy/pointprocess.py

@@ -14,7 +14,7 @@
 
 """
 
-from __future__ import division
+
 import numpy as np
 import neuron