Source code for netpyne.plotting.plotShape

Module for generating a shape plot (3D network layout)


from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
from __future__ import absolute_import

from builtins import open
from builtins import next
from builtins import range
from builtins import str

except NameError:
    basestring = str
from builtins import zip

from builtins import round
from future import standard_library

from netpyne import __gui__

if __gui__:
    import matplotlib.pyplot as plt
import numpy as np
from numbers import Number
from math import ceil
from ..analysis.utils import colorList, exception, _roundFigures, getCellsInclude, getCellsIncludeTags
from ..analysis.utils import _saveFigData, _showFigure
from .plotter import MetaFigure

[docs] @exception def plotShape( axis=None, includePre=['all'], includePost=['all'], showSyns=False, showElectrodes=False, synStyle='.', synSize=3, synColor='red', dist=0.6, elev=90, azim=-90, cvar=None, cvals=None, clim=None, iv=False, ivprops=None, includeAxon=True, bkgColor=None, aspect='auto', axisLabels=False, kind='shape', returnPlotter=False, dpi=300, **kwargs ): """ Function to plot morphology of network> """ from .. import sim from neuron import h print('Plotting 3D cell shape ...') cellsPreGids = [c.gid for c in sim.getCellsList(includePre)] if includePre else [] cellsPost = sim.getCellsList(includePost) if not hasattr(, 'compartCells'): = [c for c in cellsPost if type(c) is sim.CompartCell] try: # in case some cells had stylized morphologies without 3d pts except: pass saveFig = False if 'saveFig' in kwargs: saveFig = kwargs['saveFig'] fontSize = None if 'fontSize' in kwargs: fontSize = kwargs['fontSize'] if not iv: # plot using Python instead of interviews from mpl_toolkits.mplot3d import Axes3D from import ( morphology as morph, ) # code adapted from # create secList from include secs = None # Set cvals and secs if not cvals and cvar: cvals = [] secs = [] # weighNorm if cvar == 'weightNorm': for cellPost in cellsPost: cellSecs = ( list(cellPost.secs.values()) if includeAxon else [s for s in list(cellPost.secs.values()) if 'axon' not in s['hObj'].hname()] ) for sec in cellSecs: if 'weightNorm' in sec: secs.append(sec['hObj']) cvals.extend(sec['weightNorm']) cvals = np.array(cvals) cvals = cvals / min(cvals) # numSyns elif cvar == 'numSyns': for cellPost in cellsPost: cellSecs = ( cellPost.secs if includeAxon else {k: s for k, s in cellPost.secs.items() if 'axon' not in s['hObj'].hname()} ) for secLabel, sec in cellSecs.items(): nseg = sec['hObj'].nseg nsyns = [0] * nseg secs.append(sec['hObj']) conns = [ conn for conn in cellPost.conns if conn['sec'] == secLabel and conn['preGid'] in cellsPreGids ] for conn in conns: nsyns[int(ceil(conn['loc'] * nseg)) - 1] += 1 cvals.extend(nsyns) cvals = np.array(cvals) # voltage elif cvar == 'voltage': for cellPost in cellsPost: cellSecs = ( cellPost.secs if includeAxon else {k: s for k, s in cellPost.secs.items() if 'axon' not in s['hObj'].hname()} ) for secLabel, sec in cellSecs.items(): for seg in sec['hObj']: cvals.append(seg.v) cvals = np.array(cvals) if not isinstance(cellsPost[0].secs, dict): print('Error: Cell sections not available') return -1 if not secs: secs = [s['hObj'] for cellPost in cellsPost for s in list(cellPost.secs.values())] if not includeAxon: secs = [sec for sec in secs if 'axon' not in sec.hname()] # Plot shapeplot cbLabels = { 'numSyns': 'Number of synapses per segment', 'weightNorm': 'Weight scaling', 'voltage': 'Voltage (mV)', } # plt.rcParams.update({'font.size': fontSize}) if axis is None: metaFig = MetaFigure(kind=kind, subplots=None, **kwargs) fig = metaFig.fig shapeax = fig.add_subplot(111, projection='3d') = shapeax else: shapeax = axis fig = axis.figure metafig = fig.metafig numRows = np.shape([0] numCols = np.shape([1] axisLoc = np.where( == shapeax)[0][0] + 1 plt.delaxes(shapeax) figIndex = int(str(numRows) + str(numCols) + str(axisLoc)) shapeax = fig.add_subplot(figIndex, projection='3d') shapeax.elev = elev # 90 shapeax.azim = azim # -90 shapeax.dist = dist * shapeax.dist plt.axis(aspect) cmap = # #YlOrBr_r morph.shapeplot(h, shapeax, sections=secs, cvals=cvals, cmap=cmap, clim=clim) # fix so that axes can be scaled ax = plt.gca() def set_axes_equal(ax): """Set 3D plot axes to equal scale. Make axes of 3D plot have equal scale so that spheres appear as spheres and cubes as cubes. Required since `ax.axis('equal')` and `ax.set_aspect('equal')` don't work on 3D. """ limits = np.array( [ ax.get_xlim3d(), ax.get_ylim3d(), ax.get_zlim3d(), ] ) origin = np.mean(limits, axis=1) radius = 0.5 * np.max(np.abs(limits[:, 1] - limits[:, 0])) _set_axes_radius(ax, origin, radius) def _set_axes_radius(ax, origin, radius): x, y, z = origin ax.set_xlim3d([x - radius, x + radius]) ax.set_ylim3d([y - radius, y + radius]) ax.set_zlim3d([z - radius, z + radius]) ax.set_box_aspect([1, 1, 1]) # IMPORTANT - this is the new, key line set_axes_equal(ax) fig.subplots_adjust(left=0, right=1, bottom=0, top=1) if cvals is not None and len(cvals) > 0: vmin = np.min(cvals) vmax = np.max(cvals) if clim is not None: vmin = np.min(clim) vmax = np.max(clim) sm =, norm=plt.Normalize(vmin=vmin, vmax=vmax)) sm._A = [] # fake up the array of the scalar mappable cb = plt.colorbar(sm, fraction=0.15, shrink=0.5, pad=0.05, aspect=20) if cvar: cb.set_label(cbLabels[cvar], rotation=90, fontsize=fontSize) if saveFig == 'movie':'Time = ' + str(round(h.t, 1)), fontsize=fontSize) if bkgColor: shapeax.w_xaxis.set_pane_color(bkgColor) shapeax.w_yaxis.set_pane_color(bkgColor) shapeax.w_zaxis.set_pane_color(bkgColor) # shapeax.grid(False) # Synapses if showSyns: for cellPost in cellsPost: for sec in list(cellPost.secs.values()): for synMech in sec['synMechs']: morph.mark_locations( h, sec['hObj'], synMech['loc'], markspec=synStyle, color=synColor, markersize=synSize ) # Electrodes if showElectrodes: ax = plt.gca() colorOffset = 0 if 'avg' in showElectrodes: showElectrodes.remove('avg') colorOffset = 1 coords =[np.array(showElectrodes).astype(int), :] ax.scatter( coords[:, 0], coords[:, 1], coords[:, 2], s=150, c=colorList[colorOffset : len(coords) + colorOffset], marker='v', depthshade=False, edgecolors='k', linewidth=2, ) for i in range(coords.shape[0]): ax.text(coords[i, 0], coords[i, 1], coords[i, 2], ' ' + str(showElectrodes[i]), fontweight='bold') cb.set_label('Segment total transfer resistance to electrodes (kiloohm)', rotation=90, fontsize=fontSize) if axisLabels: shapeax.set_xlabel('x (um)') shapeax.set_ylabel('y (um)') shapeax.set_zlabel('z (um)') else: shapeax.set_xticklabels([]) shapeax.set_yticklabels([]) shapeax.set_zticklabels([]) if axis is None: metaFig.finishFig(**kwargs) else: if saveFig: if isinstance(saveFig, basestring): if saveFig == 'movie': filename = sim.cfg.filename + '_shape_movie_' + str(round(h.t, 1)) + '.png' else: filename = saveFig else: filename = sim.cfg.filename + '_shape.png' plt.savefig(filename, dpi=dpi) # show fig # if showFig: _showFigure() else: # Plot using Interviews # colors: 0 white, 1 black, 2 red, 3 blue, 4 green, 5 orange, 6 brown, 7 violet, 8 yellow, 9 gray from neuron import gui fig = h.Shape() secList = h.SectionList() if not ivprops: ivprops = {'colorSecs': 1, 'colorSyns': 2, 'style': 'O', 'siz': 5} for cell in [c for c in cellsPost]: for sec in list(cell.secs.values()): if 'axon' in sec['hObj'].hname() and not includeAxon: continue sec['hObj'].push() secList.append() h.pop_section() if showSyns: for synMech in sec['synMechs']: if synMech['hObj']: # find pre pop using conn[preGid] # create dict with color for each pre pop; check if exists; increase color counter # colorsPre[prePop] = colorCounter # find synMech using conn['loc'], conn['sec'] and conn['synMech'] fig.point_mark(synMech['hObj'], ivprops['colorSyns'], ivprops['style'], ivprops['siz']) fig.observe(secList) fig.color_list(secList, ivprops['colorSecs']) fig.flush() # show real diam # save figure if saveFig: if isinstance(saveFig, basestring): filename = saveFig else: filename = sim.cfg.filename + '_' + '' fig.printfile(filename) if not iv: if axis is None: if returnPlotter: return metaFig else: return fig, {} else: return fig, {} else: return fig, {}