odeint

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odeint#

class brainpy.odeint(f=None, method=None, var_type=None, dt=None, name=None, show_code=False, state_delays=None, neutral_delays=None, **kwargs)[source]#

Numerical integration for ODEs.

Examples

>>> import brainpy as bp
>>> import matplotlib.pyplot as plt
>>>
>>> a=0.7;  b=0.8;  tau=12.5;  Vth=1.9
>>> V = 0;  w = 0  # initial values
>>>
>>> @bp.odeint(method='rk4', dt=0.04)
>>> def integral(V, w, t, Iext):
>>>   dw = (V + a - b * w) / tau
>>>   dV = V - V * V * V / 3 - w + Iext
>>>   return dV, dw
>>>
>>> hist_V = []
>>> for t in bp.math.arange(0, 100, integral.dt):
>>>     V, w = integral(V, w, t, 0.5)
>>>     hist_V.append(V)
>>> plt.plot(bp.math.arange(0, 100, integral.dt), hist_V)
>>> plt.show()

(Source code, png, hires.png, pdf)

../../_images/brainpy-odeint-1.png
Parameters:

  • f (callable, function) – The derivative function.

  • method (str) – The shortcut name of the numerical integrator.

  • var_type (str) – The type of the variable defined in the equation.

  • dt (float) – The numerical integration precision.

  • name (str) – The integrator node.

  • state_delays (Dict[str, AbstractDelay]) – The state delay variable.

  • show_code (bool) – Show the formated code.

  • adaptive (bool) – The use adaptive mode.

  • tol (float) – The tolerence to adapt new step size.

Returns:

integral – The numerical solver of f.

Return type:

ODEIntegrator

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