Add a library with supported shapes about nestml HOT 1 CLOSED

def apply_spikes(spike_buffer, state_variable=None, model=None, tau_syn=None,
                 normalization=None, shape=None):
    '''
    Apply the effect of the spikes on the state variables.
    
    Parameters
    ----------
    buffer : spike_buffer (real)
        Buffer storing the spikes that should be applied.
    state_variable : state variable, optional (default: None)
        State variable on which the spikes should be applied, e.g. `I_syn_ex`
        for a model with post-synaptic currents implementing excitatory
        synapses. If the state variable is computed through a differential
        equation, the user should pass the right time derivative on which
        the effect of the spikes is applied.
    model : str, optional (default: None)
        Name of the predefined model that should be used, among "alpha", "exp",
        and "delta".
    tau_syn : parameter (ms), optional (default: None)
        Synaptic time constant to be used by either the "exp" or "alpha"
        predefined model.
    normalization : float, optional, (default: None)
        Normalization constant to set the peak value of the current or
        conductance. E.g. for an implicitely defined alpha-shape current
        (declared through an ODE), the constant is ``1pA*e/tau_syn_ex``.
    shape : function, optional (default: None)
        Custom shape function which will be used to convolve the spike times.
    
    Notes
    -----
    The optional parameters can be combined in the following ways:
        * `model` alone for "delta"
        * `state_variable` + `model` + `tau_syn` (for "alpha" and "exp")
        * `state_variable` + `shape`
        * `state_variable` alone if no normalization factor is required
        (defaults to 1), e.g. for exponential synapses declared through an ODE.
        * a derivative of the `state_variable` + `normalization` (for synaptic
        state-variables declared through an ODE)
    '''