helper.py 文件源码

def get_final_error(ret_nodes, nodes, assumedNodesPresent, trueNodesPresent):
    '''
    Computes final displacement error
    Parameters
    ==========

    ret_nodes : A tensor of shape pred_length x numNodes x 2
    Contains the predicted positions for the nodes

    nodes : A tensor of shape pred_length x numNodes x 2
    Contains the true positions for the nodes

    nodesPresent : A list of lists, of size pred_length
    Each list contains the nodeIDs of the nodes present at that time-step

    Returns
    =======

    Error : Mean final euclidean distance between predicted trajectory and the true trajectory
    '''
    pred_length = ret_nodes.size()[0]
    error = 0
    counter = 0

    # Last time-step
    tstep = pred_length - 1
    for nodeID in assumedNodesPresent:

        if nodeID not in trueNodesPresent[tstep]:
            continue

        pred_pos = ret_nodes[tstep, nodeID, :]
        true_pos = nodes[tstep, nodeID, :]

        error += torch.norm(pred_pos - true_pos, p=2)
        counter += 1

    if counter != 0:
        error = error / counter

    return error