Source code for tvb.simulator.models.linear
# -*- 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
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"""
Generic linear model.
"""
import numpy
from .base import Model
from tvb.basic.neotraits.api import NArray, Final, List, Range
[docs]
class Linear(Model):
gamma = NArray(
label=r":math:`\gamma`",
default=numpy.array([-10.0]),
domain=Range(lo=-100.0, hi=0.0, step=1.0),
doc="The damping coefficient specifies how quickly the node's activity relaxes, must be larger"
" than the node's in-degree in order to remain stable.")
state_variable_range = Final(
label="State Variable ranges [lo, hi]",
default={"x": numpy.array([-1, 1])},
doc="Range used for state variable initialization and visualization.")
variables_of_interest = List(
of=str,
label="Variables watched by Monitors",
choices=("x",),
default=("x",), )
coupling_terms = Final(
label="Coupling terms",
# how to unpack coupling array
default=["c"]
)
state_variable_dfuns = Final(
label="Drift functions",
default={
"x": "gamma * x + c",
}
)
parameter_names = List(
of=str,
label="List of parameters for this model",
default=tuple('gamma'.split()))
state_variables = ('x',)
_nvar = 1
cvar = numpy.array([0], dtype=numpy.int32)
[docs]
def dfun(self, state, coupling, local_coupling=0.0):
"""
.. math::
x = a{\gamma} + b
"""
x, = state
c, = coupling
dx = self.gamma * x + c + local_coupling * x
return numpy.array([dx])