HierarchicalGraphMachine 隐藏嵌套状态答案

【问题标题】：HierarchicalGraphMachine hiding nested statesHierarchicalGraphMachine 隐藏嵌套状态
【发布时间】：2021-05-20 01:59:30
【问题描述】：

我一直在尝试使用 HierarchicalGraphMachine 类来帮助在我编辑机器结构时对其进行可视化。

from transitions.extensions import HierarchicalGraphMachine as Machine

count_states = ['1', '2', '3', 'done']
count_trans = [
    ['increase', '1', '2'],
    ['increase', '2', '3'],
    ['decrease', '3', '2'],
    ['decrease', '2', '1'],
    ['done', '3', 'done'],
    ['reset', '*', '1']
]
counter = Machine(states=count_states, transitions=count_trans, initial='1')

states = ['waiting', 'collecting', {'name': 'counting', 'children': counter, 'initial': '1'}]

transitions = [
    ['collect', '*', 'collecting'],
    ['wait', '*', 'waiting'],
    ['count', 'collecting', 'counting']
]

collector = Machine(states=states, transitions=transitions, initial='waiting')
collector.get_graph(show_roi=False).draw('count1.png', prog='dot')

这会生成预期的图形，完整地显示父状态和嵌套状态（我尚未获得上传图形的授权）。有没有办法在不扩展嵌套状态的情况下生成完整的父状态机图形？例如将嵌套状态减少到一个空框。

我试过“show_roi=True”，但这只会显示当前的转换事件，并删除所有其他状态。

【问题讨论】：

标签： pytransitions

【解决方案1】：

根据您是使用pygraphviz（0.8.8 及之前的默认版本）还是graphviz 后端，get_graph 可能会返回pygraphiv.AGraph 对象或自定义transitions.Graph。 AGraph 更容易操作，而第二个基本上是点中的纯图形符号。但是，您可以根据需要对两者进行操作。例如，您可以过滤 AGraph 中的边和节点并重建它的“平面”版本：

# your code here ...

collector.collect()

graph = collector.get_graph()

# iterate over all edges; We know that parent and child states are connected
# with an underscore. We just collect the root element of each source
# and target element of each edge. Furthermore, we collect the edge color,
# and the label which is stored either in 'label', 'taillabel' or 'headlabel' 
new_edges = [(edge[0].split('_')[0],
              edge[1].split('_')[0],
              edge.attr['color'],
              edge.attr['label']
              or edge.attr['taillabel']
              or edge.attr['headlabel']) for edge in graph.edges()]

# States with children are noted as subgraphs. We collect their name and their
# current color.
new_nodes = [(sgraph.graph_attr['label'], sgraph.graph_attr['color'])
             for sgraph in graph.subgraphs()]
# We add all states that have no children and also do not contain an
# underscore in their name. An underscore would suggest that this node/state
# is a child/substate.
new_nodes += [(node.name, node.attr['color'])
              for node in graph.nodes() if '_' not in node.name]

# remove everything from the graph obeject
graph.clear()

# and add nodes and edges again
for name, color in new_nodes:
    graph.add_node(name, color=color)

for start, target, color, label in new_edges:
    if label:
        graph.add_edge(start, target, color=color, label=label)

graph.draw('agraph.png', prog='dot')

结果如下图：

您会看到，我还收集了边缘和节点颜色以可视化最后的过渡，但 graph.clear() 删除了所有“默认”样式属性。它们也可以被复制和恢复，或者我们只能删除节点、边和子图。这取决于你愿意与 (py)graphviz 混淆多少。

【讨论】：