82 lines
1.7 KiB
Python
82 lines
1.7 KiB
Python
import numpy as np
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from swc import read_swc, write_swc
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from neuron import h
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ptntls = np.loadtxt("neuron_ISO.fld")
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neuron = read_swc("input.swc")
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coords = neuron['coords'] * 1e-6
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ptntl_coords = ptntls[:, :3]
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from scipy.spatial import cKDTree
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ptntl_tree = cKDTree(ptntl_coords)
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# query nearest neighbor for each SWC node
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ptntl_idx = ptntl_tree.query(coords, k=1)[1]
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ptntls_ordered = ptntls[ptntl_idx] * 1e3
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flags = [not np.isnan(p[3]) for p in ptntls_ordered]
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non_nan = {
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'id' : neuron['id'][flags],
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'type' : neuron['type'][flags],
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'coords' : neuron['coords'][flags],
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'radius' : neuron['radius'][flags],
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'parent' : neuron['parent'][flags]
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}
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write_swc("pruned.swc", non_nan)
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ptntls_reduce = ptntls_ordered[flags]
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# load preamble
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h.load_file("import3d.hoc")
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imp = h.Import3d_SWC_read()
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imp.input("pruned.swc")
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gui = h.Import3d_GUI(imp)
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gui.instantiate(None)
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h.load_file("parameters.hoc")
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h.load_file("interpxyz.hoc")
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h.load_file("setup.hoc")
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# insert xtra at each section
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for sec in h.allsec():
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sec.insert("xtra")
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h.load_file("setpointers.hoc")
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h('setpointers()')
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segs = []
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seg_xyz = []
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for sec in h.allsec():
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for seg in sec:
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segs.append(seg)
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seg_xyz.append([seg.xtra.x, seg.xtra.y, seg.xtra.z])
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seg_xyz = np.array(seg_xyz)
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# KD-Tree again to match closest segments
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tree = cKDTree(non_nan['coords'])
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_, node_idx = tree.query(seg_xyz)
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i = 0
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for seg, idx in zip(segs, node_idx):
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print(i)
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i += 1
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seg.xtra.es = ptntls_reduce[idx][3]
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h.load_file("nrngui.hoc")
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h.load_file("stdlib.hoc")
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h.load_file("stim.hoc")
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h.load_file("exportLocs_seg.hoc")
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h.load_file("exportLocs_seg.hoc")
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h.load_file("TMS_sim_simple.hoc")
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h.load_file("detectFire.hoc")
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h.load_file("run.hoc")
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