From 35c831fa3496d255e3383dab92205fd08cd2851d Mon Sep 17 00:00:00 2001
From: Jan Fousek <jan.fousek@univ-amu.fr>
Date: Mon, 7 Jun 2021 15:46:05 +0200
Subject: [PATCH] cleaned up utils
---
utils.py | 195 ++++++++-----------------------------------------------
1 file changed, 28 insertions(+), 167 deletions(-)
mode change 100755 => 100644 utils.py
diff --git a/utils.py b/utils.py
old mode 100755
new mode 100644
index 8d47949..fc04b05
--- a/utils.py
+++ b/utils.py
@@ -1,168 +1,29 @@
-# -*- coding: utf-8 -*-
-#
-#
-# TheVirtualBrain-Scientific Package. This package holds all simulators, and
-# analysers necessary to run brain-simulations. You can use it stand alone or
-# in conjunction with TheVirtualBrain-Framework Package. See content of the
-# documentation-folder for more details. See also http://www.thevirtualbrain.org
-#
-# (c) 2012-2017, Baycrest Centre for Geriatric Care ("Baycrest") and others
-#
-# This program is free software: you can redistribute it and/or modify it under the
-# terms of the GNU General Public License as published by the Free Software Foundation,
-# either version 3 of the License, or (at your option) any later version.
-# This program is distributed in the hope that it will be useful, but WITHOUT ANY
-# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
-# PARTICULAR PURPOSE. See the GNU General Public License for more details.
-# You should have received a copy of the GNU General Public License along with this
-# program. If not, see <http://www.gnu.org/licenses/>.
-#
-#
-# CITATION:
-# When using The Virtual Brain for scientific publications, please cite it as follows:
-#
-# Paula Sanz Leon, Stuart A. Knock, M. Marmaduke Woodman, Lia Domide,
-# Jochen Mersmann, Anthony R. McIntosh, Viktor Jirsa (2013)
-# The Virtual Brain: a simulator of primate brain network dynamics.
-# Frontiers in Neuroinformatics (7:10. doi: 10.3389/fninf.2013.00010)
-#
-#
-
-from pylab import *
from tvb.simulator.lab import *
-import threading
-import numpy
-import time
-import sys
-from matplotlib.tri import Triangulation
-from matplotlib import pyplot as plt
-
-class SimThread(threading.Thread):
-
- def set_sim(self, sim, **kwds):
- self.sim = sim
- self.kwds = kwds
- self.t = -1.0
-
- def run(self):
- "Convenience method to call the simulator with **kwds and collect output data."
- tic = time.time()
- ts, xs = [], []
-
- for _ in self.sim.monitors:
- ts.append([])
- xs.append([])
-
- for data in self.sim(**self.kwds):
- for tl, xl, t_x in zip(ts, xs, data):
- if t_x is not None:
- t, x = t_x
- if t > self.t:
- self.t = t
- tl.append(t)
- xl.append(x)
-
- for i in range(len(ts)):
- ts[i] = numpy.array(ts[i])
- xs[i] = numpy.array(xs[i])
-
- self.results = list(zip(ts, xs))
- self.wall_time = time.time() - tic
-
-def formattime(eta):
- m = 60
- h = m*60
- d = 24*h
- msg = ''
- if eta > d:
- msg += '%d day(s), %d hour(s)' % (eta/d, ((eta/h) % 24))
- elif eta > h:
- msg += '%d hour(s), %d minute(s)' % (eta/h, ((eta/m) % 60))
- else:
- msg += '%d minute(s), %d seconds(s)' % (eta/m, eta%m)
- return msg
-
-def pbpct(p=1e2, eta=None, walltime=None):
- i = int(p/2)
- msg = '\r[%s%s] %d %%' % ('.'*i, ' '*(50 - i), p)
- if eta:
- msg += ', ETA: ' + formattime(eta)
- elif walltime:
- msg += ' Wall Time: ' + formattime(walltime)
- sys.stdout.write(msg)
- sys.stdout.flush()
-
-def run_sim_with_progress_bar(sim, simulation_length, polltime=1):
- tic = time.time()
- ar = SimThread()
- ar.set_sim(sim, simulation_length=simulation_length)
- ar.start()
- while True:
- prog = ar.t
- pct = prog*1e2/simulation_length
- toc = time.time() - tic
- if pct > 0.0:
- time_per_centile = toc / pct
- centiles_left = 100 - pct
- pbpct(pct, centiles_left * time_per_centile)
- else:
- pbpct(0.0)
- time.sleep(polltime)
- if hasattr(ar, 'wall_time'):
- pbpct(100.0, walltime=ar.wall_time)
- break
- return ar.results
-
-cortex = cortex.Cortex().from_file()
-
-def multiview(data, suptitle='', figsize=(15, 10), **kwds):
-
- cs = cortex
- vtx = cs.vertices
- tri = cs.triangles
- rm = cs.region_mapping
- x, y, z = vtx.T
- lh_tri = tri[(rm[tri] < 38).any(axis=1)]
- lh_vtx = vtx[rm < 38]
- lh_x, lh_y, lh_z = lh_vtx.T
- lh_tx, lh_ty, lh_tz = lh_vtx[lh_tri].mean(axis=1).T
- rh_tri = tri[(rm[tri] >= 38).any(axis=1)]
- rh_vtx = vtx[rm < 38]
- rh_x, rh_y, rh_z = rh_vtx.T
- rh_tx, rh_ty, rh_tz = vtx[rh_tri].mean(axis=1).T
- tx, ty, tz = vtx[tri].mean(axis=1).T
-
- views = {
- 'lh-lateral': Triangulation(-x, z, lh_tri[argsort(lh_ty)[::-1]]),
- 'lh-medial': Triangulation(x, z, lh_tri[argsort(lh_ty)]),
- 'rh-medial': Triangulation(-x, z, rh_tri[argsort(rh_ty)[::-1]]),
- 'rh-lateral': Triangulation(x, z, rh_tri[argsort(rh_ty)]),
- 'both-superior': Triangulation(y, x, tri[argsort(tz)]),
- }
-
- def plotview(i, j, k, viewkey, z=None, zlim=None, zthresh=None, suptitle='', shaded=True, cmap=plt.cm.coolwarm, viewlabel=False):
- v = views[viewkey]
- ax = subplot(i, j, k)
- if z is None:
- z = rand(v.x.shape[0])
- if not viewlabel:
- axis('off')
- kwargs = {'shading': 'gouraud'} if shaded else {'edgecolors': 'k', 'linewidth': 0.1}
- if zthresh:
- z = z.copy() * (abs(z) > zthresh)
- tc = ax.tripcolor(v, z, cmap=cmap, **kwargs)
- if zlim:
- tc.set_clim(vmin=-zlim, vmax=zlim)
- ax.set_aspect('equal')
- if suptitle:
- ax.set_title(suptitle, fontsize=24)
- if viewlabel:
- xlabel(viewkey)
-
- figure(figsize=figsize)
- plotview(2, 3, 1, 'lh-lateral', data, **kwds)
- plotview(2, 3, 4, 'lh-medial', data, **kwds)
- plotview(2, 3, 3, 'rh-lateral', data, **kwds)
- plotview(2, 3, 6, 'rh-medial', data, **kwds)
- plotview(1, 3, 2, 'both-superior', data, suptitle=suptitle, **kwds)
- subplots_adjust(left=0.0, right=1.0, bottom=0.0, top=1.0, wspace=0, hspace=0)
+import numpy as np
+import matplotlib.pylab as plt
+
+
+def plot_connectivity(conn):
+ # Visualization
+ fig = plt.figure(figsize=(15, 7))
+ fig.suptitle('TVB SC', fontsize=20)
+
+ # Weights
+ plt.subplot(121)
+ plt.imshow(conn.weights, interpolation='nearest', aspect='equal', cmap='jet')
+ plt.xticks(range(0, conn.number_of_regions), conn.region_labels, fontsize=7, rotation=90)
+ plt.yticks(range(0, conn.number_of_regions), conn.region_labels, fontsize=7)
+ cb = plt.colorbar(shrink=0.2)
+ cb.set_label('Weights', fontsize=14)
+
+ # Tracts lengths
+ plt.subplot(122)
+ plt.imshow(conn.tract_lengths, interpolation='nearest', aspect='equal', cmap='jet')
+ plt.xticks(range(0, conn.number_of_regions), conn.region_labels, fontsize=7, rotation=90)
+ plt.yticks(range(0, conn.number_of_regions), conn.region_labels, fontsize=7)
+ cb = plt.colorbar(shrink=0.2)
+ cb.set_label('Tract lenghts', fontsize=14)
+
+ fig.tight_layout()
+
+ plt.show()
--
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