from neurodevsim.simulator import *
import numpy as np
from sympy.solvers import solve
from sympy import Point3D, Plane, symbols
import math
from heapq import nlargest
import time
# mode 0: find target nearby
# mode 1: tangential migration to the target
# mode 1.5 --> 2: close enough to extend root_axon and start radial migration
# mode 2 --> 3: (after extended root axon) radially migrating
# mode 3 --> 4: leave BG proc guidance [expected to start experiencing interference by BG and PC somata]
# mode 4 --> 5: arrived at IGL_z
# mode -1: stuck
redirect = False # for using BG detection
verbose_cell = empty_ID#ID(3,588)
verbose = 1
# 1: dendritic selection
# 2: synapses
# 3: rare cases
# 4: morphology
# 5: Bergmann Glia
# 6: Failed Granule Cells
byFronts = False # False = retract by signal input
PCL_z = 4 # top of PCL in average (top line of PC soma), IGL_z in nds_analyze_cerebellum
# global variables for PCs
PC_start_growth = 65
# import starts from cycle 71
wholeCheck_cycle_1 = 90
wholeCheck_cycle_2 = wholeCheck_cycle_1 + 7
Whole_signal_1st = 500
Whole_signal_2nd = 1200
PC_root_radius = 0.05
PC_root_offsets_y = [-6.5, -3.5, -0.5, 3, 6]
PC_root_num = 5
PC_root_len = 7.5
PC_growth_step = 5.0
PC_taper = 1.0
PC_branch_taper = 1.0
degree = 65 # mean bifurcation angle 65 degree in vivo (Fujishima et al.,2012),
repel_fac = 0.6
repel_lim = 1.0
# global variables for BGs #
BG_offsets = [-20.5, -10.,-4.75,-0.5,4.75,10.,19.5]
num_roots = 7
BGproc_radi = 0.5
root_len = 4#
proc_len = 4
pia = 0 + 6 + 125 # PC soma position + PC soma radi + ML in P11 mice (Komuro and Rakic 1995)
# global variables for GCs #
axon_root_len = 2.0
axon_root_x_coord = 5.0
initial_pf_step = Point(0,2.,0)
pf_step = Point(0,4.,0)
radial_step = Point(0,0,-5)
ymax = 119.9
ymin = -19.9
IGL_z = -15
f_radi = 0.1 # sync with soma_radi
BG_GCoffset = (BGproc_radi + f_radi) * 1.1
close_but_closer = 0.3
ag_step = Point(0,0,-4)
syn_distance = 1.0
max_loop = 3
# Signal prams (from Synapses.ipynb example)
MAX_FR = 0.2
NEW_FR = 10.0
SIGNAL_DECAY = 20.
class PurkinjeCell(SynFront):
# status1(): False = first solve_collision_PC_den trial, Ture = second and the last trial
_fields_ = Front._fields_ + [('prev_branch', c_short),('signal', c_double),('stage', c_short)]
def manage_front(self,constellation):
if constellation.cycle == 1: # initially Purkinje cells are not active
self.disable(constellation,till_cycle_g=PC_start_growth) # re-activate at PC_start_growth
ID = self.get_id()
somaID = self.get_soma(constellation,returnID=True)
if self.swc_type == 1:
roots = self.get_children(constellation)
if constellation.cycle == PC_start_growth:
self.stage = 1
self.make_dendrite_roots(constellation,somaID)
elif constellation.cycle >= wholeCheck_cycle_1 and self.stage == 1:
self.select_winners(constellation,somaID)
elif constellation.cycle >= wholeCheck_cycle_2 and self.stage == 2:
self.select_winners(constellation,somaID)
elif self.stage == 3:
self.select_winners(constellation,somaID)
self.disable(constellation) # done
else:
return
elif (self.swc_type == 5) or (self.swc_type == 3):
if self.has_synapse(): # front has a synapse and integrates syn_input each cycle
self.signal += self.syn_input - (self.signal / SIGNAL_DECAY)
soma = constellation.front_by_id(somaID)
if (soma.is_status2()) and (not self.is_growing()):# 2nd retractions done and not grwoing tip
self.disable(constellation)
else:
self.clear_growing()
return
# long enough -> stop growth
if self.end.z >= 100: # ML thickness at P10 = ˜75µm (Fig1, Yamanaka, Yanagawa, Obata 2004)
if (verbose >= 4) or (verbose_cell == somaID):
print (somaID,ID," : _extend_basal_dendrite_, long enough, disable at",self.end.z)
self.disable(constellation)
elif self.num_children == 0:
self.extend_basal_dendrite(constellation,ID,somaID)
else:
self.disable(constellation)
return
else:
print ("Error in manage_front PurkinjeCell: unexpected swc_type =",self.swc_type)
# count synapses on all dendrite branches and pick winners, retract others
def select_winners(self,constellation,somaID):
nname = self.get_neuron_name(constellation)
# setups for signal detection
total_input = [0.] * self.num_children # store summed signal from each synapses in a dendrite
sum_tot = 0. # sum all dendrite totals to compute the mean
roots = self.get_children(constellation)
# compute total signal for each dendrite
nd = 0 # index of current dendrite
for root in roots:
syns = root.get_branch_synapses(constellation)
for syn in syns: # get signal and add to total
den_front = constellation.front_by_id(syn.post_syn)
total_input[nd] += den_front.signal
sum_tot += total_input[nd]
nd += 1
if self.stage == 1:
if sum_tot > Whole_signal_1st:
if (verbose >= 1) or (verbose_cell == somaID):
print(nname,"reached whole signal threshold =",Whole_signal_1st,"at",constellation.cycle)
self.stage = 2
mean_tot = sum_tot / self.num_children
if (verbose >= 1) or (verbose_cell == somaID):
neuron = self.get_neuron(constellation)
print (nname,"has",neuron.num_fronts,"fronts with",neuron.num_synapses,"synapses, mean summed input per dendrite: {:5.2f}".format(mean_tot))
# retract by by synaptic input
nd = 0
for root in roots:
root_name = root.get_branch_name()
if total_input[nd] < mean_tot:
if (verbose >= 1) or (verbose_cell == somaID):
print (root_name," summed input of {:5.2f}".format(total_input[nd]),"and is retracted")
self.retract_branch(constellation,root)
else:
if (verbose >= 1) or (verbose_cell == somaID):
print (root_name," summed input of {:5.2f}".format(total_input[nd]),"and stays")
nd += 1
elif self.stage == 2: # final selection
if sum_tot > Whole_signal_2nd:
if (verbose >= 1) or (verbose_cell == somaID):
print(nname,"reached whole signal threshold 2 =",Whole_signal_2nd,"at",constellation.cycle)
self.stage = 3
self.set_status2() # flag as done with second selection
nd = 0
for root in roots:
root_name = root.get_branch_name()
if total_input[nd] == max(total_input):
if (verbose >= 1) or (verbose_cell == somaID):
print (root_name,", 2nd selection, won with____",total_input[nd],"total signal input")
else:
if (verbose >= 1) or (verbose_cell == somaID):
print(root_name,"at 2nd selection: total signal input =",total_input[nd], ", retract")
self.retract_branch(constellation,root)
nd += 1
soma = constellation.front_by_id(somaID)
soma.set_status2() # flag as done with second selection
elif self.stage == 3: #count the final numbers of primary trees
self.stage == 4
if (verbose >= 1) or (verbose_cell == somaID):
print(nname,": final num survivors =",self.num_children)#
else:
print ("Error in select_winners PurkinjeCell: unexpected stage =",self.stage)
def make_dendrite_roots(self,constellation,somaID):
n_roots = 0
for i in range(0,PC_root_num):
x = np.random.uniform(-PC_root_len,PC_root_len)
y = PC_root_offsets_y[i] + np.random.uniform(-1,1) # adding jitter on the offsets
z = np.random.random()+ PC_root_len
x_points = np.arange(-PC_root_len,PC_root_len+0.5,0.5)
np.random.shuffle(x_points)
new_name = self.get_neuron_name(constellation) + "root" + str(i)
for x_point in x_points:
direction = Point(x_point,y,z)
norm_dir = direction.norm() # turn the direction to unit vector
new_pos = self.orig + norm_dir * PC_root_len
try:
new_front = self.add_child(constellation,new_pos,\
radius=PC_root_radius,\
branch_name=new_name,swc_type=5)
n_roots += 1
break # success
except (CollisionError, GridCompetitionError, InsideParentError, VolumeError):
continue # pick another point, no attempt to correct the error
# print error messages if less roots made
if n_roots == 0:
print (somaID,": _make_dendrite_root_ no valid root dendrite found")
elif n_roots < PC_root_num:
print (somaID,"_make_dendrite_root_ less roots",n_roots)
def extend_basal_dendrite(self,constellation,ID,somaID):
if (self.prev_branch == 0) and (np.random.random() < 0.08): # branch rate in vitro 0.26times/3hrs (Fujishima et al.,2012)
self.branching(constellation,ID,somaID)
return
#search front for adding repulsion force
other_dendrites = self.get_fronts(constellation,what='other',max_distance=10,swc_types=[3,5])
sorted_other_dendrites = sorted(other_dendrites, key=lambda e:abs(e[0].end.y-self.end.y)) # re-arrange order by distance in y-directions
# get list of fronts from same cell but different branches
samecell_dendrites = self.get_fronts(constellation,what='self',max_distance=10,swc_types=[3,5])
self_branch_name = self.get_branch_name() # ex. 'PC_10_root0_'
b = self_branch_name.find("root")
self_root_name = self_branch_name[:b+5]#self_branch_name[:5] # ex. 'root1'
del_candidates = [] # empty list to save items to be removed in the 2nd loop
for i in range(len(samecell_dendrites)):
den_front = samecell_dendrites[i][0] # extract front from tuple (front,distance) of index i
den_branch_name = den_front.get_branch_name()
b = den_branch_name.find("root")
den_root_name = den_branch_name[:b+5]
if den_root_name == self_root_name: # front on the same dendritic tree --> remove from the list
del_candidates.append(samecell_dendrites[i])
for del_item in del_candidates: # 2nd loop indexing del_candidates to remove item from the original list
samecell_dendrites.remove(del_item)
sorted_samecell_dendrites = sorted(samecell_dendrites, key=lambda e:abs(e[0].end.y-self.end.y)) # re-arrange order by distance in y-directions
if (other_dendrites) or (samecell_dendrites):
if (other_dendrites) and (samecell_dendrites): # if both detected choose closer one
other = sorted_other_dendrites[0]
samecell = sorted_samecell_dendrites[0]
if other[1] <= samecell[1]: # comparing distance
other_dendrite = other # assign other as other_dendrite
else:
other_dendrite = samecell # assign samacell as other_dendrite
elif other_dendrites:
# get first detected one only (not considering other dendritic structure still close to each other)
other_dendrite = sorted_other_dendrites[0]
if (verbose >= 4) or (verbose_cell == somaID):
print (ID,self.get_neuron_name(constellation),"extend_basal_dendrite, repulsion: list of other_dendrites_____self.orig =",self.orig,"self.end =",self.end)
for den in sorted_other_dendrites[0:min(3,len(sorted_other_dendrites))]:
den_front = den[0]
print ("_________________________",den_front.get_id(),den_front.get_neuron_name(constellation),"orig =",den_front.orig,"end =",den_front.end,", distance =",den[1])
elif samecell_dendrites:
other_dendrite = sorted_samecell_dendrites[0]
if (verbose >= 4) or (verbose_cell == somaID):
print (ID,self.get_neuron_name(constellation),self.get_branch_name(),"extend_basal_dendrite, repulsion: list of samecell_dendrites_____self.orig =",self.orig,"self.end =",self.end)
for den in sorted_samecell_dendrites[0:min(3,len(sorted_samecell_dendrites))]:
den_front = den[0]
print ("_________________________",den_front.get_id(),den_front.get_neuron_name(constellation),den_front.get_branch_name(),"orig =",den_front.orig,"end =",den_front.end,", distance =",den[1])
dir_to_repel = Point(self.end.x, other_dendrite[0].end.y, self.end.z) - self.end
y_distance = abs(other_dendrite[0].end.y - self.end.y)
# give repulson directly relative to distance
repel_vec = dir_to_repel.norm()*(repel_fac/y_distance)
if abs(repel_vec.y) >= repel_lim: # prevent from getting large repel value when other_dendrite is too close (e.g. y_distance < 0.1)
repel_vec = dir_to_repel.norm()
if (verbose >= 4) or (verbose_cell == somaID):
print (ID,"extend_basal_dendrite,added repel_vec, y_distance =",repel_vec,y_distance)
else: # no neighboring dendrite found
repel_vec = Point(0,0,0)
# continue growth
# search for PF around
if self.order >= 1:
#check if has synapse (come back from return on solve_collision_PC_den)
if self.has_synapse():# self already has_synapse (skip target detection)
synapse = self.get_synapse(constellation)
front_id = synapse.pre_syn
pre_syn_front = constellation.front_by_id(front_id)
else:
targets = self.get_fronts(constellation,what='name',name="granule",max_distance=5)
if not targets:
heading_dir = self.end - self.orig
extension = self.unit_heading_sample()
if heading_dir.z < 0: # growing downward
upwards = Point(0,0,0.6)
else:
upwards = Point(0,0,0.2)
new_pos = self.end + (extension + upwards) * (PC_growth_step/2) - repel_vec
if (verbose >= 4) or (verbose_cell == somaID):
print (ID," : _extend_basal_dendrite_, no target is detected, grow to heading + upwards, return confirm_extension,heading_dir/upwards =",heading_dir,upwards,"self.end & new_pos =",self.end,new_pos)
self.confirm_extension(constellation,new_pos,ID,somaID)
return
else: # detected targets
sorted_target = () # tuple
alt_target = None # store descending axon as an alternative target
for t in targets:
candidate = t[0] # extract only front from list of tuples (front,distance)
soma = self.get_soma(constellation)
if candidate.orig.z < soma.orig.z:
continue
if (candidate.swc_type == 1) or (candidate.swc_type == 12): # soma or filipod
continue
if candidate.has_synapse(): # candidate already has a synapse
continue
if candidate.swc_type == 2: # descending axon, only thin dendrites can make synapse with descending axon (Gundappa-Sulur, De Schutter et al. 1999)
continue
if candidate.orig.z < self.end.z: # GC front is at lower than self
continue
if ((candidate.swc_type == 100) or (candidate.swc_type == 101)) and (abs(candidate.orig.x - candidate.end.x) >= 1.0): # skip weird behaving PF
if (verbose >= 3) or (verbose_cell == somaID):
print (ID,"candidate =",candidate.get_id(),"is oriented in weird way, abs =",abs(candidate.orig.x - candidate.end.x),"at", candidate.end)
continue
sorted_target += t # t = (front,distance)
break
if len(sorted_target) == 0:
heading_dir = self.end - self.orig
extension = self.unit_heading_sample()
if heading_dir.z < 0: # growing downward
upwards = Point(0,0,0.6)
else:
upwards = Point(0,0,0.2)
new_pos = self.end + (extension+upwards) * (PC_growth_step/2) - repel_vec
self.confirm_extension(constellation,new_pos,ID,somaID)
return
else: # has sorted_target
pre_syn_front = sorted_target[0]
distance = sorted_target[1]
if distance <= syn_distance: # close enough for new synapse
self.add_synapse(constellation,pre_syn_front,1.0,presynaptic=False) # self is postsynaptic front
else: # grow towards the target (the shortest path)
close_dist, close_point = dist3D_point_to_cyl(self.end,pre_syn_front.orig,pre_syn_front.end,points=True)
orig_cpoint_dir = pre_syn_front.orig - close_point
orig_cpoint_len = orig_cpoint_dir.length()
sur_pos = orig_cpoint_len / pre_syn_front.length()
goal = pre_syn_front.surface_point_to(self.end,mid=False,offset=PC_root_radius+f_radi,pos=sur_pos)
direction = goal - self.end
n_direction = direction.norm()
distance = direction.length()
new_pos = self.end + n_direction * (distance - syn_distance*0.5)
y_dev = abs(self.end.y - new_pos.y)
y_dev2 = max(y_dev,1)
if y_dev > repel_lim:
upwards = Point(0,0,y_dev2)
ndir_up = n_direction+upwards
new_pos = self.end + ndir_up.norm() * (distance - syn_distance*0.5) - repel_vec
# check if new_pos deviate from heading direction
new_pos_dir = n_direction * (distance - syn_distance*0.5) # direction vector from [0,0,0]
ref_dir = Point(0,0,PC_growth_step)
heading = self.end - self.orig
heading_dir = heading.norm() * PC_growth_step
heading_angle = angle_two_dirs(ref_dir,heading_dir)
newpos_angle = angle_two_dirs(heading_dir,new_pos_dir)
if (self.prev_branch == 0) and (newpos_angle > heading_angle):
if (verbose >= 4) or (verbose_cell == somaID):
print (ID," : _extend_basal_dendrite_, target_detected and grow closer to the target =",pre_syn_front.get_id(),", but deviated from headng_dir, return directed_branching, headinf_angle =",heading_angle,", newpos_angle =",newpos_angle,"self.end =",self.end,",goal =",goal,"repel_vec =",repel_vec,"new_pos =",new_pos)
self.directed_branching(constellation,new_pos,ID,somaID)
return
else: # prev_branch > 1 or newpos_angle is not deviating from heading --> grow closer to the target
self.confirm_extension(constellation,new_pos,ID,somaID)
return
# added synapse with satisfactory target & grow perpendicular to that target
# set parpendicular growth (Nagata,Ono,Kawana et al., 2006) using plane equation
PF_vec = pre_syn_front.end - pre_syn_front.orig
count = 0
col_error = None
x,y,z = symbols('x y z')
eq = PF_vec.x * (x - self.end.x) + PF_vec.y * (y - self.end.y) + PF_vec.z * (z - self.end.z)
# check direction of heading and growing to target
heading_dir = self.end - self.orig
close_dist, close_point = dist3D_point_to_cyl(self.end,pre_syn_front.orig,pre_syn_front.end,points=True)
orig_cpoint_dir = pre_syn_front.orig - close_point
orig_cpoint_len = orig_cpoint_dir.length()
sur_pos = orig_cpoint_len / pre_syn_front.length()
goal = pre_syn_front.surface_point_to(self.end,mid=False,offset=PC_root_radius+f_radi,pos=sur_pos)
goal_dir = goal - self.end
if math.copysign(1,heading_dir.x) == math.copysign(1,goal_dir.x):
direction = goal_dir
else: # goal is opposite to heading direction, still growing to the goal though having verbose to alert
direction = goal_dir
if (verbose >= 4) or (verbose_cell == somaID):
print(ID,"extend_basal_dendrite: perpendicular growth, goal is opposite to heading_dir, self.end =",self.end,",goal =",goal,"repel_vec =",repel_vec)
n_direction = direction.norm() - repel_vec
x_value = self.end.x + n_direction.x * PC_growth_step
while count < 50:
z_value = np.random.uniform(self.end.z, self.end.z + PC_growth_step) # random float: self.end.z <= z < self.end.z + growth_step
eq2 = eq.subs(x, x_value).subs(z, z_value)
given_ys = solve(eq2) # return list of y values
if not given_ys: # PF_vec.y == 0 (rare case)
if (verbose >= 3) or (verbose_cell == somaID):
print (ID,"PC_extend_basal_dendrite, make synapse: no given_ys (rare case), assign self.end.y as given_y")
given_y = self.end.y
else:
given_y = float(given_ys[0]) # convert to float
new_pos = Point(x_value,given_y,z_value) - repel_vec
if abs(new_pos.y - self.end.y) > repel_lim: # growing to y_direction more than upper limit of repel
if (verbose >= 3) or (verbose_cell == somaID):
print(ID,"extend_basal_dendrite: trying to grow on y_direction, self.end =",self.end,",new_pos =",new_pos)
try:
new_front = self.add_child(constellation,new_pos,radius=PC_root_radius,swc_type=3)
if self.prev_branch > 0:
new_front.prev_branch = self.prev_branch - 1
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation)
return # success
except CollisionError as error:
count += 1
col_error = error
continue
except (GridCompetitionError, InsideParentError, VolumeError):
count += 1
continue
if col_error:
self.solve_collision_PC_den(constellation,new_pos,col_error,ID,somaID)
return
else:
if (verbose >= 3) or (verbose_cell == somaID):
print (ID,"PC_extend_basal_dendrite, make synapse: could not find valid point on the plane, and not collision error --> disabled (few loop cases can happen, e.g. 6 cells/3000cells)")
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation)
return
else: # not branched yet
extension = self.unit_heading_sample()
upwards = Point(0,0,0.3)
new_pos = self.end + (extension + upwards) * PC_growth_step/2 - repel_vec
if (verbose >= 4) or (verbose_cell == somaID):
print (ID,"extend_basal_dendrite: not branched yet, self.end & new_pos =",self.end,new_pos)
self.confirm_extension(constellation,new_pos,ID,somaID)
return
print ("EROOR! in extend_basal_dendrite: ending without return. ID =",ID,self.has_synapse(),self.order,col_error)
def confirm_extension(self,constellation,new_pos,ID,somaID):
new_pos_dir = new_pos - self.end # direction vector from [0,0,0]
if abs(new_pos.y - self.end.y) > repel_lim: # growing to y_direction more than upper limit of repel
if (verbose >= 3) or (verbose_cell == somaID):
print(ID,"confirm_extension: trying to grow on y_direction, self.end =",self.end,",new_pos =",new_pos)
ref_dir = Point(0,0,PC_growth_step)
heading = self.end - self.orig
heading_dir = heading.norm() * PC_growth_step
heading_angle = angle_two_dirs(ref_dir,heading_dir)
newpos_angle = angle_two_dirs(heading_dir,new_pos_dir)
if (self.prev_branch == 0) and (newpos_angle > heading_angle): # growing on the plane, but deviated from headng_dir
self.directed_branching(constellation,new_pos,ID,somaID)
return
try:
new_front = self.add_child(constellation,new_pos,radius=PC_root_radius,swc_type=3)
if self.prev_branch > 0:
new_front.prev_branch = self.prev_branch - 1
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation) # stop growing
return # success
except VolumeError: # no attempt to correct error
if (verbose >= 3) or (verbose_cell == somaID):
print (self.get_branch_name(),ID,"confirm_extension new_pos is out of simulation")
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation) # stop growing
return
except InsideParentError: # no attempt to correct error
if (verbose >= 3) or (verbose_cell == somaID):
print (self.get_branch_name(),ID,"confirm_extension new_pos is inside parent")
return
except CollisionError as error: # attempt to find solution
self.solve_collision_PC_den(constellation,new_pos,error,ID,somaID)
return
except GridCompetitionError:
if (verbose >= 3) or (verbose_cell == somaID):
print (self.get_branch_name(),ID,"confirm_extension new_pos is raising a GridCompetitionError")
return
def branching(self,constellation,ID,somaID):
col_front = None
# sample first branch on heading direction
count = 0
new_name = self.get_branch_name() + "_0"
if abs(self.end.y - self.orig.y) > repel_lim: # stronger upward force applys if grwoing to y
upwards = Point(0,0,PC_growth_step)
else:
upwards = Point(0,0,0.05)
while count < 100:
extension = self.unit_heading_sample(width=1.0,max_angle=20)
headup = extension + upwards
first_pos = self.end + headup.norm() * (PC_growth_step)
success = False
try:
new_front1 = self.add_child(constellation,first_pos,radius=PC_root_radius,\
branch_name=new_name,swc_type=3)
success = True
break
except CollisionError as error:
col_front = error.collider
count += 1
continue
except (GridCompetitionError, InsideParentError, VolumeError):
count += 1
continue
if not success:
if (verbose >= 4) or (verbose_cell == somaID):
print (ID," : _branching_, could not find first point for branching return, self.end =",self.end)
if col_front:
print ("---> colliding with id =", col_front.get_id(),", swc =",col_front.swc_type)
return
# calculate degree deviation of 1st pos from z-plane
opp_direction = first_pos - Point(first_pos.x,first_pos.y,self.end.z)
opp = opp_direction.length()
hyp_direction = first_pos - self.end
hyp = hyp_direction.length()
dev_theta = np.arcsin(opp/hyp)
# sampling 2nd branch
count2 = 0
new_name = self.get_branch_name() + "_1"
while count2 < 100:
random_degree = np.random.normal(degree,20) # arbitrary
theta = random_degree * np.pi / 180
theta_options = [theta,-theta] # try both positive & negative directions of theta
np.random.shuffle(theta_options) # avoid keep having the same branch directions
for theta in theta_options:
new_pos = self.end + Point(np.sin(dev_theta+theta),0,\
np.cos(dev_theta+theta))*(PC_growth_step)
success = False
try:
new_front2 = self.add_child(constellation,new_pos,radius=PC_root_radius,\
branch_name=new_name,swc_type=3)
success = True
break
except CollisionError as error:
col_front = error.collider
continue
except (GridCompetitionError, InsideParentError, VolumeError):
continue
if success:
break
else:
count2 += 1
if not success:
if (verbose >= 4) or (verbose_cell == somaID):
print (somaID,ID," : _branching_, could not find 2nd point, extend 1st point only, self.end =",self.end, "front1.end =",new_front1.end)
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation)
return
else:
if (verbose >= 4) or (verbose_cell == somaID):
ydev1 = abs(self.end.y - new_front1.end.y)
ydev2 = abs(self.end.y - new_front2.end.y)
if (ydev1 >= repel_lim) or (ydev2 >= repel_lim):
print (ID,"PC_branching success, self, front1, front2 =", self.end, new_front1.end, new_front2.end)
# prevent newly branching front to branch again soon
new_front1.prev_branch = 2
new_front2.prev_branch = 2
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation)
return
def directed_branching(self,constellation,new_pos,ID,somaID):
# growing to y_direction more than upper limit of repel, give stronger upward force
if abs(self.end.y - self.orig.y) > repel_lim:
upwards = Point(0,0,PC_growth_step)
else:
upwards = Point(0,0,0.05)
count = 0
new_front1 = False
new_front2 = False
new_name = self.get_branch_name() + "_0"
while count < 100: # to deal with GridCompetitionError
heading_dir = self.unit_heading_sample(width=1.0,max_angle=20)
headup = heading_dir + upwards
heading_pos = self.end + headup.norm() * (PC_growth_step)
try:
new_front1 = self.add_child(constellation,heading_pos,radius=PC_root_radius,\
branch_name=new_name,swc_type=3)
success = True
break
except CollisionError as error:
col_front = error.collider
break # not remedied
except (InsideParentError, VolumeError):
break # not remedied
except GridCompetitionError:
count += 1
continue
count = 0
new_front2 = False
new_name = self.get_branch_name() + "_1"
while count < 100: # to deal with GridCompetitionError
try:
new_front2 = self.add_child(constellation,new_pos,radius=PC_root_radius,\
branch_name=new_name,swc_type=3)
success = True
break
except CollisionError as error:
col_front = error.collider
break # not remedied
except (InsideParentError, VolumeError):
break # not remedied
except GridCompetitionError:
count += 1
continue
if new_front1 and new_front2: # 2 positions may be valid
if (verbose >= 3) or (verbose_cell == somaID):
ydev1 = abs(self.end.y - new_front1.end.y)
ydev2 = abs(self.end.y - new_front2.end.y)
if (ydev1 >= repel_lim) or (ydev2 >= repel_lim):
print (ID,"PC_directed_branching return b, self, front1, front2 =", self.end, new_front1.end, new_front2.end)
# prevent newly branching front to branch again soon
new_front1.prev_branch = 2
new_front2.prev_branch = 2
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation)
return
elif not new_front1 and not new_front2: # both branch failed
new_pos = self.end + heading_dir.norm() * PC_growth_step
self.prev_branch = 2 # avoid loop between confirm_extension & directed_branching
if (verbose >= 4) or (verbose_cell == somaID):
print (ID," : _directed_branchinf_, did not get 2 valid points & extend to heading, self.end =",self.end,", new_pos =",new_pos," --> return confirm_extension")
self.confirm_extension(constellation,new_pos,ID,somaID)
return
else: #either position is invalid, only extend the success one
if (verbose >= 4) or (verbose_cell == somaID):
print (somaID,ID," : _directed_branching_, could not find either point extend single front only, self.end =",self.end)
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation)
return
def solve_collision_PC_den(self,constellation,new_pos,error,ID,somaID):
if error:
col_front = error.collider
else:
if (verbose >= 4) or (verbose_cell == somaID):
print (somaID,ID," : _solve_collision_PC_den_ no col_fronts were detected, disable & return")
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation)
return
points = self.solve_collision(constellation,new_pos,error)
if points:
soma = self.get_soma(constellation)
if points[-1].z >= (soma.orig.z): # <condition 1> check if the last point is higher than the bottom of PC soma
heading_dir = self.end - self.orig
new_dir = points[0] - self.end
if math.copysign(1,heading_dir.x) == math.copysign(1,new_dir.x): # <condition 2> check if the path to reach new_pos is not deviating from heading_dir
try:
new_fronts = self.add_branch(constellation,points,swc_type=3)
if self.prev_branch > 0:
for front in new_fronts:
front.prev_branch = max(0,self.prev_branch - 1)
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation) # success -> disable this filipod front
return
except (CollisionError,GridCompetitionError,InsideParentError,\
VolumeError):
if (verbose >= 3) or (verbose_cell == somaID): # appears around 4 in one simulation
print (somaID,ID," : _solve_collision, has points but they did not satisfy given conditions", col_front.get_neuron_name(constellation),col_front.swc_type,"(ID =", col_front.get_id(),"), self.end =",self.end,", paths = ",points[0],"new point =", points[-1])
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation)
return
# check whether this is first or second failure
if self.is_status1(): # second failure
if (verbose >= 4) or (verbose_cell == somaID):
print (ID,": _solve_collision_PC_den, could not find points by solve collision, colliding partner =", col_front.get_neuron_name(constellation),col_front.swc_type," --> disable")
if self.is_postsynaptic():
self.clear_growing()
else:
self.disable(constellation)
return
else:
self.set_status1() # flag as first failure
return
class BergmannGlia(Front):
_fields_ = Front._fields_ + [('occupancy', c_int)]
def manage_front(self,constellation):
if self.swc_type == 1:
self.Bergmann_soma(constellation)
else:
self.Bergmann_glia(constellation)
# make initial glia roots from soma
def Bergmann_soma(self,constellation):
n_roots = 0
for i in range(0, num_roots):
name = self.get_neuron_name(constellation)+'proc'+str(i)
count = 0
success = False
while count < 20:
# increase noise gradually
new_pos = self.orig + \
Point(BG_offsets[i],0.,root_len) + random_point(-count/20,count/20)
try:
new_front = self.add_child(constellation,new_pos,radius=BGproc_radi,\
branch_name=name,swc_type=99)
success = True
n_roots += 1
break # success
except (GridCompetitionError, InsideParentError, VolumeError,CollisionError) as error:
count += 1
continue # pick another point, no attempt to correct the error
if not success:
if (verbose >= 5) or (verbose_cell == self.get_id()):
print (self.get_id(),": could not find solution points for swc99 skip ",name)
if (verbose >= 5) or (verbose_cell == self.get_id()):
print (name," (",self.get_id(),") total process ____",n_roots)
self.disable(constellation)
# extend glia roots
def Bergmann_glia(self,constellation):
if self.end.z > pia: # BG process reached to the end
if (verbose >= 5) or (verbose_cell == self.get_soma(constellation,returnID=True)):
print (self.get_soma(constellation,returnID=True),self.get_id(),"location of Bergman glia tip", self.end)
self.disable(constellation) # stop growing
# swc == 99 or 7
else:
dir_to_pia = Point(0.,0.,1.)
new_pos = self.end + dir_to_pia * proc_len
count = 0
while count < 10:
try:
new_front = self.add_child(constellation,new_pos,swc_type=7)
self.disable(constellation) # stop growing
return # success
except (VolumeError, InsideParentError): # no attempt to correct error
self.disable(constellation) # stop growing
return
except CollisionError as error: # attempt to find solution
count += 1
continue
except GridCompetitionError:
count += 1
continue # try again
# did not return -> extension failure
if constellation.cycle - self.birth > 1 : # second cycle we tried
if (verbose >= 5) or (verbose_cell == self.get_soma(constellation,returnID=True)):
print (self.get_branch_name(),self.get_id()," (",self.get_soma(constellation,returnID=True),") : could not solve Bergman collision, stop at z =",self.end.z)
self.disable(constellation) # stop growing
class GranuleCell(SynFront):
_fields_ = Front._fields_ + [('mode',c_int),('target_ID',ID),\
('loop_lim',c_int),('root_pos',Point),\
('nograndchildD_loop',c_int)]
def manage_front(self,constellation):
# adjust close_enough by initiation timing
name = self.get_neuron_name(constellation)
if (name.startswith('granule_p12')) or (name.startswith('granule_p11')) \
or (name.startswith('granule_p10')):
close_enough = 0.2 + 0.45
elif (name.startswith('granule_p9')) or (name.startswith('granule_p8')) \
or (name.startswith('granule_p7')):
close_enough = 0.2 + 0.30
elif (name.startswith('granule_p6')) or (name.startswith('granule_p5')) \
or (name.startswith('granule_p4')):
close_enough = 0.2 + 0.15
else:
close_enough = 0.2
ID = self.get_id()
if self.swc_type == 1: # soma
self.gc_soma(constellation,close_enough,axon_root_len,ID)
return
else: # all other types of front
soma = self.get_soma(constellation)
somaID = soma.get_id()
# pass the conditions stored in soma to front
self.mode = soma.mode
self.target_ID = soma.target_ID
if self.mode == -1:
self.disable(constellation)
return
if self.swc_type == 12: # filipod
if self.mode == 1:
self.extend_filipod(constellation,close_enough,ID,somaID)
return
elif (self.mode == 2) or (self.mode == 3):
target_front = constellation.front_by_id(self.target_ID)
goal = target_front.surface_point_to(self.end)
direction_xy = Point(goal.x,goal.y,self.end.z) - self.end
distance = direction_xy.length()
if distance <= close_enough:
self.radial_filipod(constellation,close_enough,ID,somaID)
return
else:
self.extend_filipod(constellation,close_enough,ID,somaID)
return
elif self.mode == 4:
self.after_guidance(constellation,ID,somaID,close_enough)
return
elif (self.mode == 5) or (self.mode == -1):
self.disable(constellation)
return
else:
print ("ERROR! in manage_front: swc = 12, unexpected mode = ", self.mode)
elif self.swc_type == 2 and self.is_status1(): # vertical axon
self.axon_branch(constellation,ID,somaID,close_enough)
return
elif (self.swc_type == 100) or (self.swc_type == 101): # parallel fibers
self.simple_PF_extension(constellation,ID,somaID,close_enough)
return
else:
print ("ERROR! in manage_front, unexpected swc_type, somaID =",somaID,"swc_type = ",self.swc_type,",selfID =",ID,",status_1 =",self.is_status1(),"--> disabled")
self.disable(constellation)
return
def gc_soma(self,constellation,close_enough,axon_root_len,ID):
# Get child info
children = self.get_children(constellation)
filipod = None
axon = None
for child in children:
if child.swc_type == 12:
if filipod:
print ("ERROR! in gc_soma: more than 2 filipod children",ID,len(children),"in mode =", self.mode)
filipod = child
elif child.swc_type == 2:
if axon:
print ("ERROR! in gc_soma: more than 2 axon children",ID,len(children))
axon = child
else:
print ("ERROR! in gc_soma: unexpected swc_type = ",child.swc_type,ID)
# failed GC, retract self after retracting all children for whom could not even reach PCL
if (self.mode == -1) and (self.orig.z > PCL_z):
if filipod:
self.retract_branch(constellation,filipod)
return
elif axon:
self.retract_branch(constellation,axon)
return
else: # only soma left
self.retract(constellation)
return
# make root axon if appropriate
if (self.mode == 2) and (not axon) and (self.orig.z > PCL_z):
target_front = constellation.front_by_id(self.target_ID)
target_point = Point(target_front.end.x, target_front.end.y,\
self.orig.z)
goal = target_front.surface_point_to(self.orig)
soma_direction_xy = Point(goal.x,goal.y,self.orig.z) - self.orig
soma_distance = soma_direction_xy.length()
# make the initial axon
if soma_distance <= close_enough:
# decide the x direction away from target BG proc
if target_point.x - self.orig.x < 0:
root_x = self.orig.x + axon_root_x_coord
else:
root_x = self.orig.x - axon_root_x_coord
direction = Point(root_x, self.orig.y, \
self.orig.z + 2.0) - self.orig
new_pos = self.orig + direction.norm()*axon_root_len
if self.rootaxon_initiation(constellation,target_point,\
new_pos,direction,False,ID,ID):
self.mode = 3
# set initial firing rate
neuron = self.get_neuron(constellation)
rate = np.random.random() * MAX_FR
neuron.set_firing_rate(constellation,rate)
return
else: # try once more with noise added
if self.rootaxon_initiation(constellation,\
target_point,new_pos,direction,True,ID,ID):
self.mode = 3
# set initial firing rate
neuron = self.get_neuron(constellation)
rate = np.random.random() * MAX_FR
neuron.set_firing_rate(constellation,rate)
return
# Migrate if possible
if filipod: # if mode < 4 a filipod grandchild is needed
if (self.mode == 5) or (filipod.num_children == 1) or (self.mode == -1): # migrate
count = 0 # loop for GridCompetitionError
while count < 50:
if axon: # filipod + trailing axon mode
try:
coordinate = self.migrate_soma(constellation,None,\
filipod=True,trailing_axon=True)
return # filipod + axon success -> self.has_moved() = True
except (GridCompetitionError):
count += 1
continue # try again
except (CollisionError,ActiveChildError):
# filipod + axon failed
if not self.has_moved(): # second failed attempt: delete filipod
self.retract_branch(constellation,filipod)
return
else:
count += 1
continue
else: # only filipod
try:
coordinate = self.migrate_soma(constellation,None,\
filipod=True)
# filipod success -> self.has_moved() = True
return
except (GridCompetitionError):
count += 1
continue # try again
except (CollisionError,ActiveChildError):
# filipod failed
if not self.has_moved(): # second failed attempt: delete filipod
self.retract_branch(constellation,filipod)
return
else:
count += 1
continue
# end of while loop
if not self.has_moved():# second failed attempt: delete filipod
self.retract_branch(constellation,filipod)
return
elif (self.mode < 5) and (filipod.num_children == 0): # no grand_child
if (self.mode == 2) and (self.orig.z <= IGL_z): # reached IGL_z without extending axon
if (verbose >= 6) or (verbose_cell == ID):
print (ID," : gc_soma, reached IGL_z without axon, have 1 filipod --> mode -1")
self.mode = -1
return
self.nograndchildD_loop += 1 # avoid endless no migration
if self.nograndchildD_loop > 6: # no grandchild for a while and stuck
if ((verbose >= 6) and (self.orig.z > PCL_z)) or (verbose_cell == ID):
print (ID," : gc_soma, nograndchildD_loop reached its limit in mode = ", self.mode, self.nograndchildD_loop,"stop migration at",self.orig,self.get_neuron_name(constellation))
print (" its filipod",filipod)
self.mode = -1 # migrate to a filipos then stop migrating next cycle
return
return
else:
print ("ERROR! undefined condition in gc_soma with filipod, ID =",ID,", filipod.num_children =",filipod.num_children,", mode =",self.mode)
else: # no filipod -> try to make one
if (self.mode == 5) or (self.mode == -1): # reached IGL or stuck below PCL
self.disable(constellation) # stop migrating
return
elif self.mode == 0:
self.radial_target(constellation,close_enough,ID)
return
else: # no filipod in mode 1,1.5,2,3 --> extend new filipod
if self.mode == 1:
self.extend_filipod(constellation,close_enough,ID,ID)
return
elif (self.mode == 3) or (self.mode == 2):
self.radial_filipod(constellation,close_enough,ID,ID)
return
elif self.mode == 4:
self.after_guidance(constellation,ID,ID,close_enough)
return
else:
print ("ERROR! in gc_soma: unexpected mode = ",self.mode,"(",ID,")")
print("ERROR in gc_soma: reached bottom without returns", ID)
def radial_target(self,constellation,close_enough,somaID):
if (self.swc_type == 1) and (self.mode == 0):
guidance = self.get_fronts(constellation,what='name',\
name="bergmann",max_distance=15,swc_types=[7]) #GC soma in the bottom of EGL can travel 90µm (Komuro et al., 2001)
# max_distance=20: 40 to 110 guidance found
# max_distance=15: 10 to 120 guidance found
# max_distance=10: 0 to 4 guidance found
num_list = 1 # just get one target BG process
guidance_len = len(guidance)
guidance_list = []
name_list = []
#print (somaID," : _radial_target_, guidance_len =",guidance_len)
else:
print ("ERROR! in radial_target: unexpected swc and mode, swc =", self.swc_type," mode =",self.mode,"(",somaID,")")
num = 0
i = 0
while (num < num_list) and (i < guidance_len):
BG = guidance[i][0]
process = BG.get_branch_name()
BGid = BG.get_id()
if process in name_list:
i +=1
continue
name_list.append(process)
BGroot = BG
# memorize occupancy at BG root front
while BGroot.swc_type != 99:
BGroot = BGroot.get_parent(constellation)
i +=1
if BGroot.occupancy > 15:
if (verbose >= 5) or (verbose_cell == somaID):
print (somaID," : _radial_target_ while loop detected",BGroot.get_branch_name(),"is occupied and skipped ")
i +=1
continue
if (BG.orig.z <= self.orig.z):
guidance_list.append(BGid)
num +=1
#for safety, if not find enough
if num < num_list:
num_list = num
#for safety, if no process found
if num == 0:
print ("ERROR! in radial_target",somaID,"could not find open BG process ")
self.mode = -1 # self is soma
self.disable(constellation)
return
# got target
self.target_ID = guidance_list[0] # self is soma
self.mode = 1 # self is soma
BGroot.occupancy += 1 # may not be accurate due to competition
# below arise LockError
"""
if constellation.lock(BGroot):
BGroot.occupancy += 1
result = constellation.unlock(BGroot)
"""
self.extend_filipod(constellation,close_enough,ID,somaID)
return
def extend_filipod(self,constellation,close_enough,ID,somaID):
target_front = constellation.front_by_id(self.target_ID)
if self.swc_type == 1:
z = self.orig.z
self_pos = self.orig
else:
z = self.end.z
self_pos = self.end
goal = target_front.surface_point_to(self_pos)
direction_xy = Point(goal.x,goal.y,self_pos.z) - self_pos
distance = direction_xy.length()
if distance <= close_enough: # close enough
if (self.mode == 0) or (self.mode == 1):
self.mode = 2
if self.swc_type == 12:
soma = self.get_soma(constellation)
soma.mode = self.mode # avoiding LockError
"""
if constellation.lock(soma): # lock the soma before changing its attribute
soma.mode = self.mode
result = constellation.unlock(soma) # unlock the soma again
"""
self.radial_filipod(constellation,close_enough,ID,somaID)
return
# mode 1.5 or 2 can come to this condition again
elif distance <= close_but_closer: # close but grow closer
dir_to_guidance = direction_xy.norm() * (distance*0.2)
# mode 1.5 or 2 also come to this
else:# far, grow closer with stronger weights
dir_to_guidance = direction_xy.norm() * (distance*0.4)# less than 0.3 then new_pos is inside sphere when distance 0.3 < d <= 0.33
new_pos = self_pos + dir_to_guidance
# check if the filipod is longer than radius of soma
if (self.swc_type == 1):
filipod_direction = new_pos - self_pos
filipod_len = filipod_direction.length()
if filipod_len <= 0.1: # filipod is too short --> adjust length
shortage = 0.1 - filipod_len
new_pos += direction_xy.norm()*(shortage+0.001)
try:
new_front = self.add_child(constellation,new_pos,radius=f_radi,\
swc_type=12,branch_name="filipod")
if self.swc_type == 12: # filipod should stop growth
self.disable(constellation)
elif self.mode < 1:
self.mode = 1 # self is soma
#else:
# swc=1 & mode=1
return
except CollisionError as error: # attempt to correct error
if (self.swc_type == 1):
self.check_validity_soma(constellation,new_pos,close_enough,\
error,ID,somaID)
return
elif (self.swc_type == 12):
self.check_validity_filipod(constellation,new_pos,\
close_enough,error,ID,somaID,False)
return
else:
print ("ERROR in extend_filipod unexpected swc and mode, swc =", self.swc_type, " in mode =",self.mode,", somaID =",somaID)
except (GridCompetitionError, InsideParentError, VolumeError):
return # no attempt to correct error
def radial_filipod(self,constellation,close_enough,ID,somaID):
if self.swc_type == 1:
self_pos = self.orig
else: # swc == 12
self_pos = self.end
if self_pos.z < PCL_z: # dont have to be close to BG proc anymore (can ignore appropriate point sorting in CV_filipod)
self.mode = 4
if self.swc_type == 12:
soma = self.get_soma(constellation)
soma.mode = self.mode # avoiding LockError
"""
if constellation.lock(soma): # lock the soma before changing its attribute
soma.mode = self.mode
result = constellation.unlock(soma) # unlock the soma again
"""
self.after_guidance(constellation,ID,somaID,close_enough)
return
else:
new_pos = self_pos + radial_step
try:
new_front = self.add_child(constellation,new_pos,radius=f_radi,\
swc_type=12,branch_name="filipod")
if self.swc_type == 12: # extension success & filipod should stop growth (have active new front)
self.disable(constellation)
return
except CollisionError as error: # attempt to correct error
if (self.swc_type == 1):
self.check_validity_soma(constellation,new_pos,\
close_enough,error,ID,somaID)
return
elif (self.swc_type == 12):
self.check_validity_filipod(constellation,new_pos,\
close_enough,error,ID,somaID,False)
return
else:
print ("ERROR in radial_filipod unexpected swc and mode, swc =", self.swc_type, " in mode =",self.mode,", somaID =",somaID)
except (GridCompetitionError, InsideParentError, VolumeError):
return # no attempt to correct error
def after_guidance(self,constellation,ID,somaID,close_enough):
if self.end.z >= IGL_z:
new_pos = self.end + ag_step
try:
new_front = self.add_child(constellation,new_pos,radius=f_radi,\
swc_type=12,branch_name="filipod")
if self.swc_type == 12: # success & filipod should stop growth
self.disable(constellation)
return
except CollisionError as error: # attempt to correct error
if (self.swc_type == 1):
self.check_validity_soma(constellation,new_pos,\
close_enough,error,ID,somaID)
return
elif (self.swc_type == 12):
self.check_validity_filipod(constellation,new_pos,\
close_enough,error,ID,somaID,False)
return
else:
print ("ERROR in after_guidance unexpected swc and mode, swc =", self.swc_type, " in mode =",self.mode,", somaID =",somaID)
except (GridCompetitionError, InsideParentError, VolumeError):
# no attempt to correct error
return
else: # filipod arrived at IGL and Terminate
self.mode = 5
if self.swc_type == 12:
soma = self.get_soma(constellation)
soma.mode = self.mode # avoiding LockError
"""
if constellation.lock(soma): # lock the soma before changing its attribute
soma.mode = self.mode
result = constellation.unlock(soma) # unlock the soma again
"""
# set new firing rate
neuron = self.get_neuron(constellation)
rate = np.random.random() * NEW_FR
neuron.set_firing_rate(constellation,rate)
self.disable(constellation)
return
def axon_branch(self,constellation,ID,somaID,close_enough):
children = self.get_children(constellation)
for npf in range(2):
if npf == 0:
for child in children:
if child.swc_type == 100: # already made this front
continue
new_pos = self.end - initial_pf_step
swc_type = 100
else:
for child in children:
if child.swc_type == 101: # already made this front
self.disable(constellation) # axon should stop growth
return
new_pos = self.end + initial_pf_step
swc_type = 101
name = 'pf_root' + str(swc_type) + \
self.get_neuron_name(constellation)
count = 0
col_error = None
while count < 10:
try:
new_front = self.add_child(constellation,new_pos,radius=f_radi,\
swc_type=swc_type,branch_name=name)
break
except (VolumeError, InsideParentError):
break
except GridCompetitionError:
count += 1
continue # while loop
except CollisionError as error: # attempt to correct error
col_error = error
break
if not col_error: # made one branch or unsolvable error
continue # for npf loop
# CollisionError occurred
CK = False
Skip = False
col_front = col_error.collider
col_front_name = col_front.get_neuron_name(constellation)
z_offset = 0.1
if col_front_name.startswith('bergmann'):
up = 0
if col_front.swc_type == 1: #rare case
up = 3. + 0.5 # BGsoma radi + extra
center = Point(col_front.orig.x, col_front.orig.y, \
self.end.z + z_offset + up)
circle_radius = BG_GCoffset
center2 = center
circle_radius2 = circle_radius + close_enough + 0.2
#horizontally oriented fronts
elif (col_front.swc_type == 1 and self.mode <= 1) or (col_front.swc_type == 12 and self.mode <= 1) or (col_front.swc_type == 100) or (col_front.swc_type == 101):
center = col_front.orig#
circle_radius = col_front.radius + self.radius + 0.05
center2 = center
circle_radius2 = circle_radius + 0.25
#vertically oriented fronts + PC dendrites
elif (col_front.swc_type == 1 and self.mode > 1) or (col_front.swc_type == 12 and self.mode > 1) or (col_front.swc_type == 2) or (col_front.swc_type == 5) or (col_front.swc_type == 3):
center = Point(col_front.orig.x, col_front.orig.y, self.end.z + z_offset)
circle_radius = (col_front.radius + self.radius) * 1.1
center2 = center
circle_radius2 = circle_radius + 0.25
else:
print ("ERROR! in axon_branch : unexpected swc of col_front =",col_front.swc_type,"(",col_front_name,")")
n = (2*np.pi*circle_radius)/0.2
num_points = int(round(n))
n2 = (2*np.pi*circle_radius2)/0.2
num_points2 = int(round(n2))
target_front = constellation.front_by_id(self.target_ID)
target_point = Point(target_front.end.x,\
target_front.end.y,self.orig.z)
x_dis = target_point.x - self.orig.x
soma = self.get_soma(constellation)
for further in range(2):
if further == 0:
n = (2*np.pi*circle_radius)/0.2
num_points = int(round(n))
else:
center = center2
circle_radius = circle_radius2
n2 = (2*np.pi*circle_radius)/0.2
num_points = int(round(n2))
point_list = [] # to use append
num = 0
num_point_memory = num_points
point_counts = 0
while num < num_point_memory:
nums = num_points*1.5
num_samples = int(round(nums))
points = col_front.alternate_locations(center,circle_radius,num_samples)
for p in points:
if p == self.end:
continue
if (swc_type == 100) and (p.y >= self.end.y):
continue
if (swc_type == 100) and (col_front.swc_type == 7) and (p.y >= col_front.orig.y):
continue
if (swc_type == 101) and (p.y <= self.end.y):
continue
# checking if the pos is far away enough from BG proc
if (x_dis < 0) and (p.x < self.end.x):
continue
if (x_dis >= 0) and (p.x > self.end.x):
continue
if p in point_list:
continue
if num >= num_point_memory:
break
point_list.append(p)
num +=1
point_counts +=1
if point_counts > 3: # less points given
num_point_memory = num
#for safety
if num == 0:
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID," : _axon_branch_ swc =",swc_type," no good point found, interfered by swc/ID =",col_front.swc_type,"/",col_front.get_soma(constellation,returnID=True))
if further == 0:
continue # go on to the next futher = 1 for-loop
else:
break
else:
for new_pos in point_list:
try:
new_front = self.add_child(constellation,new_pos,\
radius=f_radi,swc_type=swc_type,branch_name=name)
CK = True
break
except (CollisionError, GridCompetitionError, InsideParentError, VolumeError): # no attempt to correct error
continue
if CK == True:
break # for-further-loop
#couldnt find alternative points
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID," : _axon_branch_ swc =",swc_type," is skipped, interfered by swc/ID =",col_front.swc_type,"/",col_front.get_soma(constellation,returnID=True))
continue # for-further-loop
if self.swc_type == 2: # axon should stop growth
self.disable(constellation)
return
else:
print ("ERROR! in axon_branch, unexpected swc_type =",self.swc_type,ID)
return
def simple_PF_extension(self,constellation,ID,somaID,close_enough):
if self.swc_type == 100:
new_pos = self.end - pf_step
if self.swc_type == 101:
new_pos = self.end + pf_step
try:
new_front = self.add_child(constellation,new_pos)
self.disable(constellation)
return
except CollisionError as error: # attempt to correct error
self.check_validity_PF(constellation,new_pos,close_enough,\
error,ID,somaID)
return
except (VolumeError):
self.disable(constellation) # stop growing
return
except (GridCompetitionError, InsideParentError):
return # no attempt to correct error
def check_validity_filipod(self,constellation,new_pos,close_enough,\
error,ID,somaID,short):
col_front = error.collider
target_front = constellation.front_by_id(self.target_ID)
if short: # 2nd call, assign shorter new_pos
if self.mode == 4:
shorter_new_pos = self.end + (ag_step/3)
new_pos = shorter_new_pos
else:
shorter_new_pos = self.end + (radial_step/3)
new_pos = shorter_new_pos
try:
new_front = self.add_child(constellation,new_pos,\
radius=f_radi,swc_type=12,branch_name="filipod")
# filipod should stop growth
self.disable(constellation)
return # success
except CollisionError: # no attempt to correct error
pass # go to the next code
except (GridCompetitionError, InsideParentError, VolumeError):
pass # no attempt to correct error
points = self.solve_collision(constellation,new_pos,error)
if points: # a list of points
if (self.mode == 2) or (self.mode == 3) or (self.mode == 4):
failed = False
if points[-1].z > self.end.z:
failed = True
if failed:
# repeated failures (have points but not appropriate)
if (constellation.cycle - self.birth) > 2:
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID,": _check_validity_filipod in mode = ",self.mode,", have points but not appropriate, disable at", self.end," interfered by swc/name=",col_front.swc_type,"/",col_front.get_soma(constellation,returnID=True),"located at", col_front.orig)
self.disable(constellation) # stop growth
# try one more time next cycle
if not short:
self.check_validity_filipod(constellation,\
new_pos,close_enough,error,ID,\
somaID,True)
return
try:
new_fronts = self.add_branch(constellation,points,\
swc_type=12)
# filipod should stop growth
self.disable(constellation)
# success --> assign mode to new branch
except (CollisionError, GridCompetitionError,\
InsideParentError, VolumeError):
# new code: retract front that keeps colliding
if (constellation.cycle - self.birth) > 4:
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID,": _check_validity_filipod_extension in mode = ",self.mode,", have points but could not add branch, disabled at", self.end," interfered by swc/name=",col_front.swc_type,"/",col_front.get_soma(constellation,returnID=True),"located at", col_front.orig)
self.disable(constellation) # stop growth
return
else: #mode 1,5
try:
new_fronts = self.add_branch(constellation,points,\
swc_type=12)
# filipod should stop growth
self.disable(constellation)
# add_branch success --> assign mode to new fronts
except (CollisionError, GridCompetitionError,\
InsideParentError, VolumeError):
# new code: retract front that keeps colliding
if (constellation.cycle - self.birth) > 4:
self.disable(constellation) # stop growth
return
for f in new_fronts:
f.mode = self.mode
return
else: # no point was given from solve_collision
if (constellation.cycle - self.birth) > 2: # repeated failures
if self.mode == 3:
ref_front = target_front
center = Point(target_front.orig.x,target_front.orig.y,self.end.z) + radial_step
circle_radius = BGproc_radi + f_radi + close_enough
center2 = Point(target_front.orig.x,target_front.orig.y,self.end.z) + (radial_step/3)
circle_radius2 = BGproc_radi + f_radi + close_enough + 0.1
self.check_validity_2(constellation,new_pos,ID,somaID,col_front,ref_front,center,circle_radius,center2,circle_radius2)
return
if ((verbose >= 6) or (verbose_cell == somaID)):
print (somaID,ID,": _check_validity_filipod in mode = ",self.mode,", no points given, disabled at", self.end," interfered by swc/name=",col_front.swc_type,"/",col_front.get_soma(constellation,returnID=True),"located at", col_front.orig)
self.disable(constellation)
return
else:# try one more time next cycle
if (not short) and ( (self.mode == 2) or \
(self.mode == 3) or (self.mode == 4)):
self.check_validity_filipod(constellation,\
new_pos,close_enough,error,\
ID,somaID,True)
return
print ("ERROR in check_validity_filipod: reached to the bottom without return")
def check_validity_soma(self,constellation,new_pos,close_enough,\
error,ID,somaID,short=False):
col_front = error.collider
target_front = constellation.front_by_id(self.target_ID)
if self.loop_lim >= max_loop:
if ((verbose >= 6) and (self.orig.z > PCL_z)) or (verbose_cell == somaID):
print (somaID,ID,": _check_validity_soma in mode = ",self.mode," reached loop limit, disable at", self.orig,"(col_front soma:",col_front.get_soma(constellation,returnID=True),")")
print (" interfered by swc/name=",col_front.swc_type,"/",col_front.get_id(),"located at", col_front.orig)
self.mode = -1
return
if short: # 2nd call, assign shorter new_pos
if (self.mode == 2) or (self.mode == 3):
shorter_new_pos = self.orig + (radial_step/3)
new_pos = shorter_new_pos
if self.mode == 4:
shorter_new_pos = self.end + (ag_step/3)
new_pos = shorter_new_pos
try:
new_front = self.add_child(constellation,new_pos,\
radius=f_radi,swc_type=12,branch_name="filipod")
return # success
except CollisionError: # no attempt to correct error
pass # go to the next code
except (GridCompetitionError, InsideParentError, VolumeError): # no attempt to correct error
pass
points = self.solve_collision(constellation,new_pos,error)
if points: # a list of points
if (self.mode == 2) or (self.mode == 3) or (self.mode == 4):
failed = False
if points[-1].z > self.end.z:
failed = True
if failed:
if not short:
# call again with shorter_new_pos
self.check_validity_soma(constellation,new_pos,\
close_enough,error,ID,somaID,short=True)
else:
self.loop_lim += 1
return
try:
new_fronts = self.add_branch(constellation,points,swc_type=12)
# add_branch success --> assign mode to new fronts
except (CollisionError, GridCompetitionError,\
InsideParentError, VolumeError):
self.loop_lim += 1
return
else: # mode 1,5
try:
new_fronts = self.add_branch(constellation,points,swc_type=12)
# add_branch success --> assign mode to new fronts
except (CollisionError, GridCompetitionError,\
InsideParentError, VolumeError):
self.loop_lim += 1
return
for f in new_fronts:
f.mode = self.mode
return
else: # no point was given from solve_collision
if (not short) and ((self.mode == 2) or \
(self.mode == 3) or (self.mode == 4)):
self.check_validity_soma(constellation,new_pos,\
close_enough,error,ID,somaID,short=True)
else:
self.loop_lim += 1
return
# return success (boolean), random is a booolean: add noise to new_pos
def rootaxon_initiation(self,constellation,target_point,\
new_pos,direction,random,ID,somaID):
if random: # decide the x direction away from target BG proc, give random direction
y_rand = (1.0 - 0.3) * np.random.rand() + 0.3 # 0.3 < y_rand < 1.0
x_rand = np.random.rand()
z_rand = (1.0 - 0.3) * np.random.rand() + 0.3
if target_point.x - self.orig.x < 0:
new_pos = new_pos + Point(x_rand,y_rand,z_rand)
else:
new_pos = new_pos + Point(-x_rand,y_rand,z_rand)
try:
new_front = self.add_child(constellation,new_pos,radius=f_radi,\
swc_type=2,branch_name="rootaxon")
new_front.set_status1() # flag status1 = True
self.root_pos = new_pos
# called by soma: do not disable
return True # success
except (CollisionError, GridCompetitionError, InsideParentError, VolumeError) as error: # no attempt to correct error
return False
def check_validity_PF(self,constellation,new_pos,close_enough,error,ID,somaID):
col_front = error.collider
col_front_name = col_front.get_neuron_name(constellation)
target_front = constellation.front_by_id(self.target_ID)
target_point = Point(target_front.end.x, target_front.end.y, self.orig.z)
x_dis = target_point.x - self.orig.x
soma = self.get_soma(constellation)
# not far enough from BG proc area
if ((x_dis < 0) and (self.end.x < soma.root_pos.x)) or ((x_dis > 0) and (self.end.x > soma.root_pos.x )):
if self.swc_type == 100:
if x_dis < 0:
center = Point(soma.root_pos.x + 0.2, self.end.y - 1.0, self.end.z)
else:
center = Point(soma.root_pos.x - 0.2, self.end.y - 1.0, self.end.z)
else: #self.swc_type == 101
if x_dis < 0:
center = Point(soma.root_pos.x + 0.2, self.end.y + 1.0, self.end.z)
else:
center = Point(soma.root_pos.x - 0.2, self.end.y + 1.0, self.end.z)
circle_radius = 0.2
center2 = center
circle_radius2 = circle_radius + 0.2
elif col_front_name.startswith('bergmann') or col_front_name.startswith('pc'):
z_offset = 0.1
if self.swc_type == 100:
pf_dir = 1.0
else:
pf_dir = -1.0
center = Point(self.end.x, self.end.y + pf_dir, self.end.z)
circle_radius = (col_front.radius + self.radius) * 1.1
center2 = center
circle_radius2 = circle_radius + self.radius#1.0
elif (col_front.swc_type == 2) or (col_front.swc_type == 12) or (col_front.swc_type == 1):
# assuming collision with vertically oriented granule cell front
center = Point(self.end.x, col_front.orig.y, self.end.z)
circle_radius = (col_front.radius + self.radius)*1.1
center2 = center
circle_radius2 = circle_radius + self.radius#0.2
elif (col_front.swc_type == 100) or (col_front.swc_type == 101):
if self.swc_type == 100:
if col_front.swc_type == 100:
if col_front.end.y < self.end.y:
center = col_front.end
else:
center = Point(col_front.end.x, self.end.y, col_front.end.z)
else:
y_distance = self.end.y - col_front.end.y
if y_distance <= 0.1:
center = col_front.orig
else:
center = col_front.end
else:
if col_front.swc_type == 101:
if col_front.end.y > self.end.y:
center = col_front.end
else:
y = self.end.y - col_front.end.y
center = Point(col_front.end.x, col_front.end.y + y, col_front.end.z)
else:
y_distance = col_front.end.y - self.end.y
if y_distance <= 0.1:
center = col_front.orig
else:
center = col_front.end
circle_radius = (col_front.radius + self.radius)*1.1
center2 = center
circle_radius2 = circle_radius + self.radius
else:
print ("ERROR in check_validity_PF: interfered by unexpected swc object, col_swc=", col_front.swc_type)
self.check_validity_2(constellation,new_pos,ID,somaID,col_front,col_front,center,circle_radius,center2,circle_radius2) # 2nd col_front is the same value as ref_front
return
# only for PFs and filipod in mode3
def check_validity_2(self,constellation,new_pos,ID,somaID,\
col_front,ref_front,center,circle_radius,center2,circle_radius2):
for further in range(2):
if further == 0:
n = (2*np.pi*circle_radius)/0.2
num_points = int(round(n))
else:
center = center2
circle_radius = circle_radius2
n2 = (2*np.pi*circle_radius)/0.2
num_points = int(round(n2))
if (self.swc_type != 100) and (self.swc_type != 101) and ((self.swc_type != 12)and(self.mode != 3)):
print ("ERROR in After_check_validity2_, unexpected mode or swc_type: mode=",self.mode,",swc=",self.swc_type)
return
count = 0
list_made = False
while True: # endless loop
count += 1
if count > 50:#200:
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID,"__check_validity_2_: killing the while loop,swc/end =",self.swc_type,self.end,", col_front_ID/swc/orig =",col_front,col_front.swc_type,col_front.orig)
self.disable(constellation)
return
try:
new_front = self.add_child(constellation,new_pos)
self.disable(constellation)
return # done
except CollisionError as error: # attempt to correct error
if list_made: # made a point_list
if point_list: # entries remaining
new_pos = point_list.pop(0)
continue # while True
else: # emptied the list
if further == 0:
break # go on to the next further loop
else: # failed
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID,": _check_validity2_ swc & mode = ",self.swc_type,self.mode,", could not find points, TRMINATE at", self.end," interfered by swc/ID = ",col_front.swc_type," / ",col_front.get_soma(constellation,returnID=True),"located at", col_front.orig ,"radius 1 =", circle_radius,", radius 2 =", circle_radius2,"(selfID =",self.get_id(),")")
self.disable(constellation)
return
else: # no list made yet
pass # drop down to make a new point_list
except (GridCompetitionError, InsideParentError,VolumeError):
pass # no attempt to correct error
#make point_list
point_list = []
num = 0
num_point_memory = num_points
point_counts = 0
ncount = 0
while num < num_point_memory:
ncount += 1
if ncount % 100 == 0:
print ("while num loop",ncount)
nums = num_points*1.5
num_samples = int(round(nums))
points = ref_front.alternate_locations(center,circle_radius,num_samples)
sorted_points = sorted(points, key=lambda e:(e-self.end).length())
if (self.swc_type == 100) or (self.swc_type == 101):
if len(sorted_points) > 0:
del sorted_points[0]
if len(sorted_points) == 0: #no alternative points found
if further == 0:
break # go on to the next further = 1 loop
else:
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID," : __check_validity_2_, no alternative points found ,self.swc/mode/pos = ",self.swc_type,"/",self.mode,"/",self.end,", interfered by swc/pos/ID = ",col_front.swc_type,"/",col_front.orig,"/",col_front.get_soma(constellation,returnID=True)," // radius 1/radius 2 =",circle_radius,"/",circle_radius2,"(selfID =",self.get_id(),")")
self.disable(constellation)
return
if (self.swc_type == 100) or (self.swc_type == 101):
target_front = constellation.front_by_id(self.target_ID)
target_point = Point(target_front.end.x, target_front.end.y, self.orig.z)
x_dis = target_point.x - self.orig.x
soma = self.get_soma(constellation)
for p in sorted_points:
if p == self.end:
continue
if (self.swc_type == 100) and (p.y >= self.end.y):
continue
if (self.swc_type == 100) and (col_front.swc_type == 7) and (p.y >= col_front.orig.y):
continue
if (self.swc_type == 101) and (p.y <= self.end.y):
continue
if (self.swc_type == 101) and (col_front.swc_type == 7) and (p.y <= col_front.orig.y):
continue
if ((self.swc_type == 100) or (self.swc_type == 101)) and (x_dis < 0) and (p.x < soma.root_pos.x):
continue
if ((self.swc_type == 100) or (self.swc_type == 101)) and (x_dis >= 0) and (p.x > soma.root_pos.x):
continue
if p in point_list:
continue
point_list.append(p)
num +=1
point_counts +=1
if point_counts > 3: # less points given for the point list
num_point_memory = num
#for safety
if num == 0:
if further == 0:
break # go on to the next further = 1 loop
else:
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID," : _check_validity2_ loop2, self swc/mode/self = ",self.swc_type,self.mode,self.end,", 0 alternative_points found")
print(" interfered by swc/ID =",col_front.swc_type,"/", col_front.get_soma(constellation,returnID=True))
self.disable(constellation)
return
list_made = True
print("ERROR! in check_validity_2: reached the bottom without returns")
class InvadingPF(SynFront):
def manage_front(self,constellation):
ID = self.get_id()
somaID = self.get_soma(constellation,returnID=True)
if self.swc_type == 1:
# set initial firing rate
neuron = self.get_neuron(constellation)
rate = np.random.random() * NEW_FR
neuron.set_firing_rate(constellation,rate)
if self.orig.y >= 155: # = y_epos_min in admin
new_pos = self.end - pf_step
swc = 100
elif self.orig.y <= 0: # = y_eneg_max in admin
new_pos = self.end + pf_step
swc = 101
else:
print ("ERROR in InvadingPF:",self.get_id(),"initiated in a wrong place",self.orig)
self.disable(constellation)
return
try:
new_front = self.add_child(constellation,new_pos,radius=f_radi,swc_type=swc)
self.disable(constellation)
return
except VolumeError:
# this error is expected: reached volume border -> stop growth
self.disable(constellation)
return # done for this cycle
except (CollisionError, GridCompetitionError, InsideParentError):
self.disable(constellation)
return # done for this cycle
elif (self.swc_type == 100) or (self.swc_type == 101):
if self.swc_type == 100:
new_pos = self.end - pf_step
if self.swc_type == 101:
new_pos = self.end + pf_step
try:
new_front = self.add_child(constellation,new_pos)
self.disable(constellation)
return
except CollisionError as error: # attempt to correct error
self.check_validity_InvadingPF(constellation,new_pos,error,ID,somaID)
return
except (VolumeError):
self.disable(constellation) # stop growing
return
except (GridCompetitionError, InsideParentError):
# no attempt to correct error
self.disable(constellation)
return
print(ID,"ERROR! in InvadingPF manage_front: at the bottom without returns")
def check_validity_InvadingPF(self,constellation,new_pos,error,ID,somaID):
col_front = error.collider
col_front_name = col_front.get_neuron_name(constellation)
if col_front_name.startswith('bergmann') or col_front_name.startswith('pc'):
z_offset = 0.1
if self.swc_type == 100:
pf_dir = 1.0
else:
pf_dir = -1.0
center = Point(self.end.x, self.end.y + pf_dir, self.end.z)
circle_radius = (col_front.radius + self.radius) * 1.1
center2 = center
circle_radius2 = circle_radius + self.radius#1.0
elif (col_front.swc_type == 2) or (col_front.swc_type == 12) or (col_front.swc_type == 1):
# assuming collision with vertically oriented granule cell front
center = Point(self.end.x, col_front.orig.y, self.end.z)
circle_radius = (col_front.radius + self.radius)*1.1
center2 = center
circle_radius2 = circle_radius + self.radius
elif (col_front.swc_type == 100) or (col_front.swc_type == 101):
if self.swc_type == 100:
if col_front.swc_type == 100:
if col_front.end.y < self.end.y:
center = col_front.end
else:
center = Point(col_front.end.x, self.end.y, col_front.end.z)
else:
y_distance = self.end.y - col_front.end.y
if y_distance <= 0.1:
center = col_front.orig
else:
center = col_front.end
else:
if col_front.swc_type == 101:
if col_front.end.y > self.end.y:
center = col_front.end
else:
y = self.end.y - col_front.end.y
center = Point(col_front.end.x, col_front.end.y + y, col_front.end.z)
else:
y_distance = col_front.end.y - self.end.y
if y_distance <= 0.1:
center = col_front.orig
else:
center = col_front.end
circle_radius = (col_front.radius + self.radius)*1.1
center2 = center
circle_radius2 = circle_radius + self.radius
else:
print ("ERROR in check_validity_InvadingPF: interfered by unexpected swc object, col_swc=", col_front.swc_type)
self.check_validity_IP2(constellation,new_pos,ID,somaID,col_front,center,circle_radius,center2,circle_radius2)
return
def check_validity_IP2(self,constellation,new_pos,ID,somaID,\
col_front,center,circle_radius,center2,circle_radius2):
for further in range(2):
if further == 0:
n = (2*np.pi*circle_radius)/0.2
num_points = int(round(n))
else:
center = center2
circle_radius = circle_radius2
n2 = (2*np.pi*circle_radius)/0.2
num_points = int(round(n2))
if (self.swc_type != 100) and (self.swc_type != 101):
print ("ERROR in After_check_validityIP2_, unexpected mode or swc_type: swc=",self.swc_type)
return
count = 0
list_made = False
while True: # endless loop
count += 1
if count > 50:#200:
if (verbose >= 6) or (verbose_cell == somaID):
print ("__check_validity_IP2_: killing the while loop,swc/end =",self.swc_type,self.end,", col_front_ID/swc/orig =",col_front,col_front.swc_type,col_front.orig)
self.disable(constellation)
return
try:
new_front = self.add_child(constellation,new_pos)
self.disable(constellation)
return # done
except CollisionError as error: # attempt to correct error
if list_made: # made a point_list
if point_list: # entries remaining
new_pos = point_list.pop(0)
continue # while True
else: # emptied the list
if further == 0:
break # force next of for further loop
else: # failed
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID,": _check_validityIP2_ swc = ",self.swc_type,", could not find points, TRMINATE at", self.end," interfered by swc/ID = ",col_front.swc_type," / ",col_front.get_soma(constellation,returnID=True),"located at", col_front.orig ,"radius 1 =", circle_radius,", radius 2 =", circle_radius2,"(selfID =",self.get_id(),")")
self.disable(constellation)
return
else: # no list made yet
pass
except (GridCompetitionError, InsideParentError,VolumeError):
pass # no attempt to correct error
# Error condition -> make point_list
point_list = []
num = 0
num_point_memory = num_points
point_counts = 0
ncount = 0
while num < num_point_memory:
ncount += 1
if ncount % 100 == 0:
print ("while num loop",ncount)
nums = num_points*1.5
num_samples = int(round(nums))
points = col_front.alternate_locations(center,circle_radius,num_samples)
sorted_points = sorted(points, key=lambda e:(e-self.end).length())
if (self.swc_type == 100) or (self.swc_type == 101):
if len(sorted_points) > 0:
del sorted_points[0]
if len(sorted_points) == 0:
if further == 0:
break # go on to the next further = 1 loop
else:
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID," : __check_validity_IP2_, no alternative points found ,self.swc/pos = ",self.swc_type,"/",self.end,", interfered by swc/pos/ID = ",col_front.swc_type,"/",col_front.orig,"/",col_front.get_soma(constellation,returnID=True)," --> return t // radius 1/radius 2 =",circle_radius,"/",circle_radius2)
self.disable(constellation)
return
for p in sorted_points:
if p == self.end:
continue
if (self.swc_type == 100) and (p.y >= self.end.y):
continue
if (self.swc_type == 100) and (col_front.swc_type == 7) and (p.y >= col_front.orig.y):
continue
if (self.swc_type == 101) and (p.y <= self.end.y):
continue
if (self.swc_type == 101) and (col_front.swc_type == 7) and (p.y <= col_front.orig.y):
continue
if p in point_list:
continue
point_list.append(p)
num +=1
point_counts +=1
if point_counts > 3:# less points given for the point list
num_point_memory = num
#for safety
if num == 0:
if further == 0:
break # go on to the next further = 1 loop
else:
if (verbose >= 6) or (verbose_cell == somaID):
print (somaID,ID," : _check_validityIP2_ loop2, self swc/self = ",self.swc_type,self.end,", 0 alternative_points found --> return t")
print(" interfered by swc/ID =",col_front.swc_type,"/", col_front.get_soma(constellation,returnID=True))
#
self.disable(constellation)
return
list_made = True
print(ID,"ERROR! in InvadingPF check_validity_IP2: reached at the bottom without return")
if __name__ == '__main__':
start = time.time()
s = int(sys.argv[1])
iname = "db_files_inDeigo/Note45D_part1_c64_seed" + str(s) + ".db"
#iname = "db_files/Note45_part1_S1test_c16_seed1_115mins.db"
fname = "db_files_inDeigo/Note46D_S3_500n1200_" + str(s) + ".db"
#fname = "db_files/Note46_part2_S2_1test_" + str(s) + ".db"
sim_volume = [[-20., -160., -20.], [180.0,300.0,140.0]]
neuron_types = [PurkinjeCell,BergmannGlia,GranuleCell,InvadingPF]
#15
#127
#63
admin = Admin_agent(63,fname,sim_volume,neuron_types,verbose=1,max_neurons=14000,\
max_fronts=2000000,max_arcs=100,max_active=240000,max_substrate=1280,\
max_synapse=120000,grid_step=10.,grid_extra=200)
# import previous simulation: this should be first call after creating Admin_agent
admin.import_simulation(iname)
# save neuron data for analysis
admin.attrib_to_db(PurkinjeCell,'signal',"real",last_only=False)
admin.attrib_to_db(GranuleCell,'firing_rate',"real",object=Neuron,last_only=False)
admin.attrib_to_db(InvadingPF,'firing_rate',"real",object=Neuron,last_only=False)
ML_base = 15# PC pos + PC radi, sync with ML_base in global variable list
# ML thickness = 121µm in P15 (Faust,2003)
x_min = -15#-20 + 20
x_max = 140#175#75#80#180 - 20
y_min = 0#-15#-5#-20 + 15
y_max = 40#75#25#160 - 15
x_min2 = -5
x_max2 = 155#160
y_min2 = 40
y_max2 = 90
x_min3 = 5
x_max3 = 175
y_min3 = 90
y_max3 = 145
x_e_max = 160
x_e_min = -5
y_epos_min = 155
y_epos_max = 290
y_eneg_min = -150
y_eneg_max = 0
soma_radi = 0.1 # sync with f_radi
try:
admin.simulation_loop(5)
except Exception as error:
print ("Failed:",error,s)
admin.destruction()
print ("\nTeam Havana____________________________________________________")
admin.add_neurons(GranuleCell,"granule_p8",84,\
[[x_min,y_min,ML_base+70],[x_max,y_max,ML_base+80]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p8",84,\
[[x_min2,y_min2,ML_base+70],[x_max2,y_max2,ML_base+80]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p8",84,\
[[x_min3,y_min3,ML_base+70],[x_max3,y_max3,ML_base+80]],soma_radi,migrating=True)
admin.add_neurons(InvadingPF,"granule_p8_exp",429,\
[[x_e_min,y_epos_min,ML_base],[x_e_max,y_epos_max,ML_base+80]],soma_radi)
admin.add_neurons(InvadingPF,"granule_p8_exn",429,\
[[x_e_min,y_eneg_min,ML_base],[x_e_max,y_eneg_max,ML_base+80]],soma_radi)
try:
admin.simulation_loop(10)
except Exception as error:
print ("Failed:",error,s)
admin.destruction()
print ("\nTeam India____________________________________________________")
admin.add_neurons(GranuleCell,"granule_p9",84,\
[[x_min,y_min,ML_base+80],[x_max,y_max,ML_base+90]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p9",84,\
[[x_min2,y_min2,ML_base+80],[x_max2,y_max2,ML_base+90]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p9",84,\
[[x_min3,y_min3,ML_base+80],[x_max3,y_max3,ML_base+90]],soma_radi,migrating=True)
admin.add_neurons(InvadingPF,"granule_p9_exp",429,\
[[x_e_min,y_epos_min,ML_base],[x_e_max,y_epos_max,ML_base+90]],soma_radi)
admin.add_neurons(InvadingPF,"granule_p9_exn",429,\
[[x_e_min,y_eneg_min,ML_base],[x_e_max,y_eneg_max,ML_base+90]],soma_radi)
try:
admin.simulation_loop(10)
except Exception as error:
print ("Failed:",error,s)
admin.destruction()
print ("\nTeam Juliett____________________________________________________")
admin.add_neurons(GranuleCell,"granule_p10",84,\
[[x_min,y_min,ML_base+90],[x_max,y_max,ML_base+100]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p10",84,\
[[x_min2,y_min2,ML_base+90],[x_max2,y_max2,ML_base+100]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p10",84,\
[[x_min3,y_min3,ML_base+90],[x_max3,y_max3,ML_base+100]],soma_radi,migrating=True)
admin.add_neurons(InvadingPF,"granule_p10_exp",429,\
[[x_e_min,y_epos_min,ML_base],[x_e_max,y_epos_max,ML_base+100]],soma_radi)
admin.add_neurons(InvadingPF,"granule_p10_exn",429,\
[[x_e_min,y_eneg_min,ML_base],[x_e_max,y_eneg_max,ML_base+100]],soma_radi)
try:
admin.simulation_loop(10)
except Exception as error:
print ("Failed:",error,s)
admin.destruction()
print ("\nTeam King____________________________________________________")
admin.add_neurons(GranuleCell,"granule_p11",84,\
[[x_min,y_min,ML_base+100],[x_max,y_max,ML_base+110]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p11",84,\
[[x_min2,y_min2,ML_base+100],[x_max2,y_max2,ML_base+110]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p11",84,\
[[x_min3,y_min3,ML_base+100],[x_max3,y_max3,ML_base+110]],soma_radi,migrating=True)
admin.add_neurons(InvadingPF,"granule_p11_exp",429,\
[[x_e_min,y_epos_min,ML_base],[x_e_max,y_epos_max,ML_base+110]],soma_radi)
admin.add_neurons(InvadingPF,"granule_p11_exn",429,\
[[x_e_min,y_eneg_min,ML_base],[x_e_max,y_eneg_max,ML_base+110]],soma_radi)
try:
admin.simulation_loop(10)
except Exception as error:
print ("Failed:",error,s)
admin.destruction()
print ("\nTeam LUIS____________________________________________________")
admin.add_neurons(GranuleCell,"granule_p12",84,\
[[x_min,y_min,ML_base+110],[x_max,y_max,ML_base+120]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p12",84,\
[[x_min2,y_min2,ML_base+110],[x_max2,y_max2,ML_base+120]],soma_radi,migrating=True)
admin.add_neurons(GranuleCell,"granule_p12",84,\
[[x_min3,y_min3,ML_base+110],[x_max3,y_max3,ML_base+120]],soma_radi,migrating=True) # z_pos should sync with stop growth condition on extend_basal_dendrite
admin.add_neurons(InvadingPF,"granule_p12_exp",429,\
[[x_e_min,y_epos_min,ML_base],[x_e_max,y_epos_max,ML_base+120]],soma_radi)
admin.add_neurons(InvadingPF,"granule_p12_exn",429,\
[[x_e_min,y_eneg_min,ML_base],[x_e_max,y_eneg_max,ML_base+120]],soma_radi)
try:
admin.simulation_loop(105)
except Exception as error:
print ("Failed:",error,s)
admin.destruction()
# clean up
print ("Cerebellum simulation:",s,time.time()-start,"seconds")
admin.destruction()