graph_tool.dynamics.ContinuousStateBase#

class graph_tool.dynamics.ContinuousStateBase(g, make_state, params, t0=0, s=None, stype='double')[source]#

Bases: object

Base state for continuous-time dynamics. This class it not meant to be instantiated directly.

Methods

copy()

Copy state.

get_diff(dt)

Returns the current time derivative for all the nodes.

get_state()

Returns the internal VertexPropertyMap with the current state.

solve(t, *args, **kwargs)

Integrate the system up to time t.

solve_euler(t[, dt])

Integrate the system up o time t using a simple Euler's method with step size dt.
copy()[source]#

Copy state.

get_diff(dt)[source]#

Returns the current time derivative for all the nodes. The parameter dt is the time interval in consideration, which is used only if the ODE has a stochastic component.

If enabled during compilation, this algorithm runs in parallel.

get_state()[source]#

Returns the internal VertexPropertyMap with the current state.

solve(t, *args, **kwargs)[source]#

Integrate the system up to time t. The remaining parameters are passed to scipy.integrate.solve_ivp(). This solver is not suitable for stochastic ODEs.

solve_euler(t, dt=0.001)[source]#

Integrate the system up o time t using a simple Euler’s method with step size dt. This solver is suitable for stochastic ODEs.