place_fields.py 文件源码

def get_heatmaps(neuron_list, spikes, pos, num_bins=100):
    """ Gets the 2D heatmaps for firing of a given set of neurons.

    Parameters
    ----------
    neuron_list : list of ints
        These will be the indices into the full list of neuron spike times
    spikes : list
        Containing nept.SpikeTrain for each neuron.
    pos : nept.Position
        Must be 2D.
    num_bins : int
        This will specify how the 2D space is broken up, the greater the number
        the more specific the heatmap will be. The default is set at 100.

    Returns
    -------
    heatmaps : dict of lists
        Where the key is the neuron number and the value is the heatmap for
        that individual neuron.
    """
    if not pos.dimensions == 2:
        raise ValueError("pos must be two-dimensional")

    xedges = np.linspace(np.min(pos.x)-2, np.max(pos.x)+2, num_bins+1)
    yedges = np.linspace(np.min(pos.y)-2, np.max(pos.y)+2, num_bins+1)

    heatmaps = dict()
    count = 1
    for neuron in neuron_list:
        field_x = []
        field_y = []
        for spike in spikes[neuron].time:
            spike_idx = find_nearest_idx(pos.time, spike)
            field_x.append(pos.x[spike_idx])
            field_y.append(pos.y[spike_idx])
            heatmap, out_xedges, out_yedges = np.histogram2d(field_x, field_y, bins=[xedges, yedges])
        heatmaps[neuron] = heatmap.T
        print(str(neuron) + ' of ' + str(len(neuron_list)))
        count += 1
    return heatmaps