def __init__(self, swc_file, random_seed=10):
nrn.load_neuron_modules(None, None)
self._hobj = h.Biophys1(swc_file)
self._morphology = Morphology(self._hobj)
self._morphology.set_seg_props()
self._morphology.calc_seg_coords()
self._prng = np.random.RandomState(random_seed)
self._secs = []
self._save_sections()
def make_morphologies(self):
"""Creating a Morphology object for each biophysical model"""
# TODO: Let Morphology take care of the cache
# TODO: Let other types have morphologies
# TODO: Get all available morphologies from TypesTable or group
for gid, cell in self._rank_node_gids.items():
if not isinstance(cell, BioCell):
continue
morphology_file = cell.morphology_file
if morphology_file in self._morphologies_cache:
# create a single morphology object for each model_group which share that morphology
morph = self._morphologies_cache[morphology_file]
# associate morphology with a cell
cell.set_morphology(morph)
self._morphology_lookup[morphology_file].append(cell.gid)
else:
hobj = cell.hobj # get hoc object (hobj) from the first cell with a new morphologys
morph = Morphology(hobj)
# associate morphology with a cell
cell.set_morphology(morph)
# create a single morphology object for each model_group which share that morphology
self._morphologies_cache[morphology_file] = morph
self._morphology_lookup[morphology_file] = [cell.gid]
self.io.barrier()
def make_morphologies(self):
"""Creating a Morphology object for each biophysical model"""
for node in self._local_nodes:
if node.cell_type == CellTypes.Biophysical:
node_type_id = node.node_type_id
morphology_file = node.morphology_file
if node_type_id in self.__morphologies_cache:
# create a single morphology object for each model_group which share that morphology
morph = self.__morphologies_cache[node_type_id]
# associate morphology with a cell
self._cells[node.node_id].set_morphology(morph)
else:
hobj = self._cells[
node.
node_id].hobj # get hoc object (hobj) from the first cell with a new morphologys
morph = Morphology(hobj)
# associate morphology with a cell
self._cells[node.node_id].set_morphology(morph)
# create a single morphology object for each model_group which share that morphology
self.__morphologies_cache[node_type_id] = morph
io.print2log0(" Created morphologies")
self._morphologies_built = True
class SWCReader(object):
def __init__(self, swc_file, random_seed=10):
nrn.load_neuron_modules(None, None)
self._hobj = h.Biophys1(swc_file)
self._morphology = Morphology(self._hobj)
self._morphology.set_seg_props()
self._morphology.calc_seg_coords()
self._prng = np.random.RandomState(random_seed)
self._secs = []
self._save_sections()
def _save_sections(self):
for sec in self._hobj.all:
for _ in sec:
self._secs.append(sec)
def find_sections(self, section_names, distance_range):
return self._morphology.find_sections(section_names, distance_range)
def choose_sections(self, section_names, distance_range, n_sections=1):
secs, probs = self.find_sections(section_names, distance_range)
secs_ix = self._prng.choice(secs, n_sections, p=probs)
return secs_ix, self._morphology.seg_prop['x'][secs_ix]
def get_coord(self,
sec_ids,
sec_xs,
soma_center=(0.0, 0.0, 0.0),
rotations=None):
adjusted = self._morphology.get_soma_pos() - np.array(soma_center)
absolute_coords = []
for sec_id, sec_x in zip(sec_ids, sec_xs):
sec = self._secs[sec_id]
n_coords = int(h.n3d(sec=sec))
coord_indx = int(sec_x * (n_coords - 1))
swc_coords = np.array([
h.x3d(coord_indx, sec=sec),
h.x3d(coord_indx, sec=sec),
h.x3d(coord_indx, sec=sec)
])
absolute_coords.append(swc_coords - adjusted)
if rotations is not None:
raise NotImplementedError
return absolute_coords
def get_dist(self, sec_ids):
return [
self._morphology.seg_prop['dist'][sec_id] for sec_id in sec_ids
]
def get_type(self, sec_ids):
return [
self._morphology.seg_prop['type'][sec_id] for sec_id in sec_ids
]
class SWCReader(object):
"""A class for pulling out section id, section locations, coordinates from a SWC file. Useful when building a
network that requires exact locations of pre- or post-synaptic locations. Requires NEURON.
Attributes
==========
swc_file - path to a SWC morphology file
fix_axon - If set to true, the axon will be removed and replaced with a 30 um stub, as defined for all Allen
Cell-Type models (default: True).
random_seed - integer value to seed the random genator, used by choose_sections method.
"""
def __init__(self, swc_file, random_seed=10, fix_axon=True):
nrn.load_neuron_modules(None, None)
self._swc_file = swc_file
self._hobj = h.Biophys1(swc_file)
if fix_axon:
self._fix_axon()
self._morphology = Morphology(self._hobj)
self._morphology.set_seg_props()
self._morphology.calc_seg_coords()
self._prng = np.random.RandomState(random_seed)
self._secs = []
self._save_sections()
def _save_sections(self):
for sec in self._hobj.all:
for _ in sec:
self._secs.append(sec)
def _fix_axon(self):
"""Removes and refixes axon"""
axon_diams = [self._hobj.axon[0].diam, self._hobj.axon[0].diam]
for sec in self._hobj.all:
section_name = sec.name().split(".")[1][:4]
if section_name == 'axon':
axon_diams[1] = sec.diam
for sec in self._hobj.axon:
h.delete_section(sec=sec)
h.execute('create axon[2]', self._hobj)
for index, sec in enumerate(self._hobj.axon):
sec.L = 30
sec.diam = 1
self._hobj.axonal.append(sec=sec)
self._hobj.all.append(sec=sec) # need to remove this comment
self._hobj.axon[0].connect(self._hobj.soma[0], 1.0, 0)
self._hobj.axon[1].connect(self._hobj.axon[0], 1.0, 0)
h.define_shape()
def get_coord(self,
sec_ids,
sec_xs,
soma_center=(0.0, 0.0, 0.0),
rotation_matrix=None):
"""Takes in a list of section_ids and section_x values and returns a list of coordinates, assuming the soma
is at the center of the system.
:param sec_ids: [float]: list of N section_ids
:param sec_xs: [float]: list of N cooresponding section_x's
:param soma_center: location of soma in respect to the coordinate system. (default (0, 0, 0)).
:param rotation_matrix: List of rotations (not yet implemented)
:return: [(float, float, float)]: for seach sec_ids/sec_xs returna the x,y,z coordinates as a tuple
"""
adjusted = self._morphology.get_soma_pos() - np.array(soma_center)
absolute_coords = []
for sec_id, sec_x in zip(sec_ids, sec_xs):
sec = self._secs[sec_id]
n_coords = int(h.n3d(sec=sec))
coord_indx = int(sec_x * (n_coords - 1))
swc_coords = np.array([
h.x3d(coord_indx, sec=sec),
h.y3d(coord_indx, sec=sec),
h.x3d(coord_indx, sec=sec)
])
adjusted_coords = swc_coords - adjusted
if rotation_matrix is not None:
adjusted_coords = np.dot(rotation_matrix, adjusted_coords)
absolute_coords.append(adjusted_coords)
return absolute_coords
def get_dist(self, sec_ids):
"""Returns arc-length distance from soma for a list of section_ids"""
return [
self._morphology.seg_prop['dist'][sec_id] for sec_id in sec_ids
]
class SWCReader(object):
def __init__(self, swc_file, random_seed=10, fix_axon=True):
nrn.load_neuron_modules(None, None)
self._swc_file = swc_file
self._hobj = h.Biophys1(swc_file)
if fix_axon:
self._fix_axon()
self._morphology = Morphology(self._hobj)
self._morphology.set_seg_props()
self._morphology.calc_seg_coords()
self._prng = np.random.RandomState(random_seed)
self._secs = []
self._save_sections()
def _save_sections(self):
for sec in self._hobj.all:
for _ in sec:
self._secs.append(sec)
def _fix_axon(self):
"""Removes and refixes axon"""
axon_diams = [self._hobj.axon[0].diam, self._hobj.axon[0].diam]
for sec in self._hobj.all:
section_name = sec.name().split(".")[1][:4]
if section_name == 'axon':
axon_diams[1] = sec.diam
for sec in self._hobj.axon:
h.delete_section(sec=sec)
h.execute('create axon[2]', self._hobj)
for index, sec in enumerate(self._hobj.axon):
sec.L = 30
sec.diam = 1
self._hobj.axonal.append(sec=sec)
self._hobj.all.append(sec=sec) # need to remove this comment
self._hobj.axon[0].connect(self._hobj.soma[0], 1.0, 0)
self._hobj.axon[1].connect(self._hobj.axon[0], 1.0, 0)
h.define_shape()
def find_sections(self, section_names, distance_range):
return self._morphology.find_sections(section_names, distance_range)
def choose_sections(self, section_names, distance_range, n_sections=1):
secs, probs = self.find_sections(section_names, distance_range)
secs_ix = self._prng.choice(secs, n_sections, p=probs)
return secs_ix, self._morphology.seg_prop['x'][secs_ix]
def get_coord(self,
sec_ids,
sec_xs,
soma_center=(0.0, 0.0, 0.0),
rotations=None):
adjusted = self._morphology.get_soma_pos() - np.array(soma_center)
absolute_coords = []
for sec_id, sec_x in zip(sec_ids, sec_xs):
sec = self._secs[sec_id]
n_coords = int(h.n3d(sec=sec))
coord_indx = int(sec_x * (n_coords - 1))
swc_coords = np.array([
h.x3d(coord_indx, sec=sec),
h.y3d(coord_indx, sec=sec),
h.x3d(coord_indx, sec=sec)
])
absolute_coords.append(swc_coords - adjusted)
if rotations is not None:
raise NotImplementedError
return absolute_coords
def get_dist(self, sec_ids):
return [
self._morphology.seg_prop['dist'][sec_id] for sec_id in sec_ids
]
def get_type(self, sec_ids):
return [
self._morphology.seg_prop['type'][sec_id] for sec_id in sec_ids
]
class SWCReader(object):
"""A class for pulling out section id, section locations, coordinates from a SWC file. Useful when building a
network that requires exact locations of pre- or post-synaptic locations. Requires NEURON.
Attributes
==========
swc_file - path to a SWC morphology file
fix_axon - If set to true, the axon will be removed and replaced with a 30 um stub, as defined for all Allen
Cell-Type models (default: True).
random_seed - integer value to seed the random genator, used by choose_sections method.
"""
def __init__(self, swc_file, random_seed=10, fix_axon=True):
nrn.load_neuron_modules(None, None)
self._swc_file = swc_file
self._hobj = h.Biophys1(swc_file)
if fix_axon:
self._fix_axon()
self._morphology = Morphology(self._hobj)
self._morphology.set_seg_props()
self._morphology.calc_seg_coords()
self._prng = np.random.RandomState(random_seed)
self._secs = []
self._save_sections()
def _save_sections(self):
for sec in self._hobj.all:
for _ in sec:
self._secs.append(sec)
def _fix_axon(self):
"""Removes and refixes axon"""
axon_diams = [self._hobj.axon[0].diam, self._hobj.axon[0].diam]
for sec in self._hobj.all:
section_name = sec.name().split(".")[1][:4]
if section_name == 'axon':
axon_diams[1] = sec.diam
for sec in self._hobj.axon:
h.delete_section(sec=sec)
h.execute('create axon[2]', self._hobj)
for index, sec in enumerate(self._hobj.axon):
sec.L = 30
sec.diam = 1
self._hobj.axonal.append(sec=sec)
self._hobj.all.append(sec=sec) # need to remove this comment
self._hobj.axon[0].connect(self._hobj.soma[0], 1.0, 0)
self._hobj.axon[1].connect(self._hobj.axon[0], 1.0, 0)
h.define_shape()
def find_sections(self, section_names, distance_range):
"""Retrieves a list of sections ids and section x's given a section name/type (eg axon, soma, apic, dend) and
the distance from the soma.
:param section_names: 'soma', 'dend', 'apic', 'axon'
:param distance_range: [float, float]: distance range of sections from the soma, in um.
:return: [float], [float]: A list of all section_ids and a list of all segment_x values (as defined by NEURON)
that meet the given critera.
"""
return self._morphology.find_sections(section_names, distance_range)
def choose_sections(self, section_names, distance_range, n_sections=1):
"""Similar to find_sections, but will only N=n_section number of sections_ids/x values randomly selected (may
return less if there aren't as many sections
:param section_names: 'soma', 'dend', 'apic', 'axon'
:param distance_range: [float, float]: distance range of sections from the soma, in um.
:param n_sections: int: maximum number of sections to select
:return: [float], [float]: A list of all section_ids and a list of all segment_x values (as defined by NEURON)
that meet the given critera.
"""
secs, probs = self.find_sections(section_names, distance_range)
secs_ix = self._prng.choice(secs, n_sections, p=probs)
return secs_ix, self._morphology.seg_prop['x'][secs_ix]
def get_coord(self, sec_ids, sec_xs, soma_center=(0.0, 0.0, 0.0), rotations=None):
"""Takes in a list of section_ids and section_x values and returns a list of coordinates, assuming the soma
is at the center of the system.
:param sec_ids: [float]: list of N section_ids
:param sec_xs: [float]: list of N cooresponding section_x's
:param soma_center: location of soma in respect to the coordinate system. (default (0, 0, 0)).
:param rotations: List of rotations (not yet implemented)
:return: [(float, float, float)]: for seach sec_ids/sec_xs returna the x,y,z coordinates as a tuple
"""
adjusted = self._morphology.get_soma_pos() - np.array(soma_center)
absolute_coords = []
for sec_id, sec_x in zip(sec_ids, sec_xs):
sec = self._secs[sec_id]
n_coords = int(h.n3d(sec=sec))
coord_indx = int(sec_x*(n_coords - 1))
swc_coords = np.array([h.x3d(coord_indx, sec=sec), h.y3d(coord_indx, sec=sec), h.x3d(coord_indx, sec=sec)])
absolute_coords.append(swc_coords - adjusted)
if rotations is not None:
raise NotImplementedError
return absolute_coords
def get_dist(self, sec_ids):
"""Returns arc-length distance from soma for a list of section_ids"""
return [self._morphology.seg_prop['dist'][sec_id] for sec_id in sec_ids]
def get_type(self, sec_ids):
"""For each section_id returns the type (1: soma, 2: axon, 3: dend, 4: apic"""
return [self._morphology.seg_prop['type'][sec_id] for sec_id in sec_ids]