951 lines
31 KiB
Python
951 lines
31 KiB
Python
"""
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Text-based visual representations of graphs
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"""
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import sys
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import warnings
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from collections import defaultdict
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import networkx as nx
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from networkx.utils import open_file
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__all__ = ["forest_str", "generate_network_text", "write_network_text"]
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class BaseGlyphs:
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@classmethod
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def as_dict(cls):
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return {
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a: getattr(cls, a)
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for a in dir(cls)
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if not a.startswith("_") and a != "as_dict"
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}
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class AsciiBaseGlyphs(BaseGlyphs):
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empty: str = "+"
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newtree_last: str = "+-- "
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newtree_mid: str = "+-- "
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endof_forest: str = " "
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within_forest: str = ": "
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within_tree: str = "| "
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class AsciiDirectedGlyphs(AsciiBaseGlyphs):
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last: str = "L-> "
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mid: str = "|-> "
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backedge: str = "<-"
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vertical_edge: str = "!"
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class AsciiUndirectedGlyphs(AsciiBaseGlyphs):
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last: str = "L-- "
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mid: str = "|-- "
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backedge: str = "-"
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vertical_edge: str = "|"
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class UtfBaseGlyphs(BaseGlyphs):
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# Notes on available box and arrow characters
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# https://en.wikipedia.org/wiki/Box-drawing_character
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# https://stackoverflow.com/questions/2701192/triangle-arrow
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empty: str = "╙"
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newtree_last: str = "╙── "
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newtree_mid: str = "╟── "
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endof_forest: str = " "
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within_forest: str = "╎ "
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within_tree: str = "│ "
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class UtfDirectedGlyphs(UtfBaseGlyphs):
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last: str = "└─╼ "
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mid: str = "├─╼ "
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backedge: str = "╾"
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vertical_edge: str = "╽"
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class UtfUndirectedGlyphs(UtfBaseGlyphs):
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last: str = "└── "
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mid: str = "├── "
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backedge: str = "─"
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vertical_edge: str = "│"
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def generate_network_text(
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graph,
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with_labels=True,
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sources=None,
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max_depth=None,
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ascii_only=False,
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vertical_chains=False,
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):
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"""Generate lines in the "network text" format
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This works via a depth-first traversal of the graph and writing a line for
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each unique node encountered. Non-tree edges are written to the right of
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each node, and connection to a non-tree edge is indicated with an ellipsis.
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This representation works best when the input graph is a forest, but any
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graph can be represented.
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This notation is original to networkx, although it is simple enough that it
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may be known in existing literature. See #5602 for details. The procedure
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is summarized as follows:
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1. Given a set of source nodes (which can be specified, or automatically
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discovered via finding the (strongly) connected components and choosing one
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node with minimum degree from each), we traverse the graph in depth first
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order.
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2. Each reachable node will be printed exactly once on it's own line.
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3. Edges are indicated in one of four ways:
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a. a parent "L-style" connection on the upper left. This corresponds to
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a traversal in the directed DFS tree.
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b. a backref "<-style" connection shown directly on the right. For
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directed graphs, these are drawn for any incoming edges to a node that
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is not a parent edge. For undirected graphs, these are drawn for only
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the non-parent edges that have already been represented (The edges that
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have not been represented will be handled in the recursive case).
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c. a child "L-style" connection on the lower right. Drawing of the
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children are handled recursively.
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d. if ``vertical_chains`` is true, and a parent node only has one child
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a "vertical-style" edge is drawn between them.
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4. The children of each node (wrt the directed DFS tree) are drawn
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underneath and to the right of it. In the case that a child node has already
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been drawn the connection is replaced with an ellipsis ("...") to indicate
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that there is one or more connections represented elsewhere.
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5. If a maximum depth is specified, an edge to nodes past this maximum
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depth will be represented by an ellipsis.
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6. If a a node has a truthy "collapse" value, then we do not traverse past
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that node.
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Parameters
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----------
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graph : nx.DiGraph | nx.Graph
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Graph to represent
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with_labels : bool | str
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If True will use the "label" attribute of a node to display if it
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exists otherwise it will use the node value itself. If given as a
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string, then that attribute name will be used instead of "label".
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Defaults to True.
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sources : List
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Specifies which nodes to start traversal from. Note: nodes that are not
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reachable from one of these sources may not be shown. If unspecified,
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the minimal set of nodes needed to reach all others will be used.
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max_depth : int | None
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The maximum depth to traverse before stopping. Defaults to None.
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ascii_only : Boolean
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If True only ASCII characters are used to construct the visualization
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vertical_chains : Boolean
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If True, chains of nodes will be drawn vertically when possible.
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Yields
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------
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str : a line of generated text
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Examples
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--------
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>>> graph = nx.path_graph(10)
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>>> graph.add_node("A")
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>>> graph.add_node("B")
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>>> graph.add_node("C")
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>>> graph.add_node("D")
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>>> graph.add_edge(9, "A")
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>>> graph.add_edge(9, "B")
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>>> graph.add_edge(9, "C")
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>>> graph.add_edge("C", "D")
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>>> graph.add_edge("C", "E")
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>>> graph.add_edge("C", "F")
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>>> nx.write_network_text(graph)
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╙── 0
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└── 1
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└── 2
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└── 3
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└── 4
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└── 5
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└── 6
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└── 7
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└── 8
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└── 9
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├── A
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├── B
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└── C
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├── D
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├── E
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└── F
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>>> nx.write_network_text(graph, vertical_chains=True)
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╙── 0
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│
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1
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│
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2
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│
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3
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│
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4
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│
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5
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│
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6
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│
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7
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│
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8
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│
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9
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├── A
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├── B
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└── C
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├── D
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├── E
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└── F
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"""
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from typing import Any, NamedTuple
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class StackFrame(NamedTuple):
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parent: Any
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node: Any
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indents: list
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this_islast: bool
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this_vertical: bool
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collapse_attr = "collapse"
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is_directed = graph.is_directed()
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if is_directed:
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glyphs = AsciiDirectedGlyphs if ascii_only else UtfDirectedGlyphs
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succ = graph.succ
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pred = graph.pred
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else:
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glyphs = AsciiUndirectedGlyphs if ascii_only else UtfUndirectedGlyphs
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succ = graph.adj
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pred = graph.adj
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if isinstance(with_labels, str):
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label_attr = with_labels
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elif with_labels:
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label_attr = "label"
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else:
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label_attr = None
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if max_depth == 0:
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yield glyphs.empty + " ..."
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elif len(graph.nodes) == 0:
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yield glyphs.empty
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else:
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# If the nodes to traverse are unspecified, find the minimal set of
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# nodes that will reach the entire graph
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if sources is None:
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sources = _find_sources(graph)
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# Populate the stack with each:
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# 1. parent node in the DFS tree (or None for root nodes),
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# 2. the current node in the DFS tree
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# 2. a list of indentations indicating depth
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# 3. a flag indicating if the node is the final one to be written.
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# Reverse the stack so sources are popped in the correct order.
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last_idx = len(sources) - 1
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stack = [
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StackFrame(None, node, [], (idx == last_idx), False)
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for idx, node in enumerate(sources)
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][::-1]
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num_skipped_children = defaultdict(lambda: 0)
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seen_nodes = set()
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while stack:
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parent, node, indents, this_islast, this_vertical = stack.pop()
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if node is not Ellipsis:
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skip = node in seen_nodes
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if skip:
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# Mark that we skipped a parent's child
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num_skipped_children[parent] += 1
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if this_islast:
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# If we reached the last child of a parent, and we skipped
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# any of that parents children, then we should emit an
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# ellipsis at the end after this.
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if num_skipped_children[parent] and parent is not None:
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# Append the ellipsis to be emitted last
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next_islast = True
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try_frame = StackFrame(
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node, Ellipsis, indents, next_islast, False
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)
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stack.append(try_frame)
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# Redo this frame, but not as a last object
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next_islast = False
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try_frame = StackFrame(
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parent, node, indents, next_islast, this_vertical
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)
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stack.append(try_frame)
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continue
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if skip:
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continue
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seen_nodes.add(node)
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if not indents:
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# Top level items (i.e. trees in the forest) get different
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# glyphs to indicate they are not actually connected
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if this_islast:
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this_vertical = False
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this_prefix = indents + [glyphs.newtree_last]
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next_prefix = indents + [glyphs.endof_forest]
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else:
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this_prefix = indents + [glyphs.newtree_mid]
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next_prefix = indents + [glyphs.within_forest]
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else:
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# Non-top-level items
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if this_vertical:
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this_prefix = indents
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next_prefix = indents
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else:
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if this_islast:
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this_prefix = indents + [glyphs.last]
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next_prefix = indents + [glyphs.endof_forest]
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else:
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this_prefix = indents + [glyphs.mid]
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next_prefix = indents + [glyphs.within_tree]
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if node is Ellipsis:
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label = " ..."
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suffix = ""
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children = []
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else:
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if label_attr is not None:
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label = str(graph.nodes[node].get(label_attr, node))
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else:
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label = str(node)
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# Determine if we want to show the children of this node.
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if collapse_attr is not None:
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collapse = graph.nodes[node].get(collapse_attr, False)
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else:
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collapse = False
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# Determine:
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# (1) children to traverse into after showing this node.
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# (2) parents to immediately show to the right of this node.
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if is_directed:
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# In the directed case we must show every successor node
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# note: it may be skipped later, but we don't have that
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# information here.
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children = list(succ[node])
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# In the directed case we must show every predecessor
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# except for parent we directly traversed from.
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handled_parents = {parent}
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else:
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# Showing only the unseen children results in a more
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# concise representation for the undirected case.
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children = [
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child for child in succ[node] if child not in seen_nodes
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]
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# In the undirected case, parents are also children, so we
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# only need to immediately show the ones we can no longer
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# traverse
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handled_parents = {*children, parent}
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if max_depth is not None and len(indents) == max_depth - 1:
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# Use ellipsis to indicate we have reached maximum depth
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if children:
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children = [Ellipsis]
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handled_parents = {parent}
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if collapse:
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# Collapsing a node is the same as reaching maximum depth
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if children:
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children = [Ellipsis]
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handled_parents = {parent}
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# The other parents are other predecessors of this node that
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# are not handled elsewhere.
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other_parents = [p for p in pred[node] if p not in handled_parents]
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if other_parents:
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if label_attr is not None:
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other_parents_labels = ", ".join(
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[
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str(graph.nodes[p].get(label_attr, p))
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for p in other_parents
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]
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)
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else:
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other_parents_labels = ", ".join(
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[str(p) for p in other_parents]
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)
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suffix = " ".join(["", glyphs.backedge, other_parents_labels])
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else:
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suffix = ""
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# Emit the line for this node, this will be called for each node
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# exactly once.
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if this_vertical:
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yield "".join(this_prefix + [glyphs.vertical_edge])
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yield "".join(this_prefix + [label, suffix])
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if vertical_chains:
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if is_directed:
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num_children = len(set(children))
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else:
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num_children = len(set(children) - {parent})
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# The next node can be drawn vertically if it is the only
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# remaining child of this node.
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next_is_vertical = num_children == 1
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else:
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next_is_vertical = False
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# Push children on the stack in reverse order so they are popped in
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# the original order.
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for idx, child in enumerate(children[::-1]):
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next_islast = idx == 0
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try_frame = StackFrame(
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node, child, next_prefix, next_islast, next_is_vertical
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)
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stack.append(try_frame)
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@open_file(1, "w")
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def write_network_text(
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graph,
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path=None,
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with_labels=True,
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sources=None,
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max_depth=None,
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ascii_only=False,
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end="\n",
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vertical_chains=False,
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):
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"""Creates a nice text representation of a graph
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This works via a depth-first traversal of the graph and writing a line for
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each unique node encountered. Non-tree edges are written to the right of
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each node, and connection to a non-tree edge is indicated with an ellipsis.
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This representation works best when the input graph is a forest, but any
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graph can be represented.
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Parameters
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----------
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graph : nx.DiGraph | nx.Graph
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Graph to represent
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path : string or file or callable or None
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Filename or file handle for data output.
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if a function, then it will be called for each generated line.
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if None, this will default to "sys.stdout.write"
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with_labels : bool | str
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If True will use the "label" attribute of a node to display if it
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exists otherwise it will use the node value itself. If given as a
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string, then that attribute name will be used instead of "label".
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Defaults to True.
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sources : List
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Specifies which nodes to start traversal from. Note: nodes that are not
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reachable from one of these sources may not be shown. If unspecified,
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the minimal set of nodes needed to reach all others will be used.
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max_depth : int | None
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The maximum depth to traverse before stopping. Defaults to None.
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ascii_only : Boolean
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If True only ASCII characters are used to construct the visualization
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end : string
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The line ending character
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vertical_chains : Boolean
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If True, chains of nodes will be drawn vertically when possible.
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Examples
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--------
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>>> graph = nx.balanced_tree(r=2, h=2, create_using=nx.DiGraph)
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>>> nx.write_network_text(graph)
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╙── 0
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├─╼ 1
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│ ├─╼ 3
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│ └─╼ 4
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└─╼ 2
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├─╼ 5
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└─╼ 6
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>>> # A near tree with one non-tree edge
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>>> graph.add_edge(5, 1)
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>>> nx.write_network_text(graph)
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╙── 0
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├─╼ 1 ╾ 5
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│ ├─╼ 3
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│ └─╼ 4
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└─╼ 2
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├─╼ 5
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│ └─╼ ...
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└─╼ 6
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>>> graph = nx.cycle_graph(5)
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>>> nx.write_network_text(graph)
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╙── 0
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├── 1
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│ └── 2
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│ └── 3
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│ └── 4 ─ 0
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└── ...
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>>> graph = nx.cycle_graph(5, nx.DiGraph)
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>>> nx.write_network_text(graph, vertical_chains=True)
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╙── 0 ╾ 4
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╽
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1
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╽
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2
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╽
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3
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╽
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4
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└─╼ ...
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>>> nx.write_network_text(graph, vertical_chains=True, ascii_only=True)
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+-- 0 <- 4
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!
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1
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!
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2
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!
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3
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!
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4
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L-> ...
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>>> graph = nx.generators.barbell_graph(4, 2)
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>>> nx.write_network_text(graph, vertical_chains=False)
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╙── 4
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├── 5
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│ └── 6
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│ ├── 7
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│ │ ├── 8 ─ 6
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│ │ │ └── 9 ─ 6, 7
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│ │ └── ...
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│ └── ...
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└── 3
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├── 0
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│ ├── 1 ─ 3
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│ │ └── 2 ─ 0, 3
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│ └── ...
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└── ...
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>>> nx.write_network_text(graph, vertical_chains=True)
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╙── 4
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├── 5
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│ │
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│ 6
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│ ├── 7
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│ │ ├── 8 ─ 6
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│ │ │ │
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│ │ │ 9 ─ 6, 7
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│ │ └── ...
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│ └── ...
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|
└── 3
|
|
├── 0
|
|
│ ├── 1 ─ 3
|
|
│ │ │
|
|
│ │ 2 ─ 0, 3
|
|
│ └── ...
|
|
└── ...
|
|
|
|
>>> graph = nx.complete_graph(5, create_using=nx.Graph)
|
|
>>> nx.write_network_text(graph)
|
|
╙── 0
|
|
├── 1
|
|
│ ├── 2 ─ 0
|
|
│ │ ├── 3 ─ 0, 1
|
|
│ │ │ └── 4 ─ 0, 1, 2
|
|
│ │ └── ...
|
|
│ └── ...
|
|
└── ...
|
|
|
|
>>> graph = nx.complete_graph(3, create_using=nx.DiGraph)
|
|
>>> nx.write_network_text(graph)
|
|
╙── 0 ╾ 1, 2
|
|
├─╼ 1 ╾ 2
|
|
│ ├─╼ 2 ╾ 0
|
|
│ │ └─╼ ...
|
|
│ └─╼ ...
|
|
└─╼ ...
|
|
"""
|
|
if path is None:
|
|
# The path is unspecified, write to stdout
|
|
_write = sys.stdout.write
|
|
elif hasattr(path, "write"):
|
|
# The path is already an open file
|
|
_write = path.write
|
|
elif callable(path):
|
|
# The path is a custom callable
|
|
_write = path
|
|
else:
|
|
raise TypeError(type(path))
|
|
|
|
for line in generate_network_text(
|
|
graph,
|
|
with_labels=with_labels,
|
|
sources=sources,
|
|
max_depth=max_depth,
|
|
ascii_only=ascii_only,
|
|
vertical_chains=vertical_chains,
|
|
):
|
|
_write(line + end)
|
|
|
|
|
|
def _find_sources(graph):
|
|
"""
|
|
Determine a minimal set of nodes such that the entire graph is reachable
|
|
"""
|
|
# For each connected part of the graph, choose at least
|
|
# one node as a starting point, preferably without a parent
|
|
if graph.is_directed():
|
|
# Choose one node from each SCC with minimum in_degree
|
|
sccs = list(nx.strongly_connected_components(graph))
|
|
# condensing the SCCs forms a dag, the nodes in this graph with
|
|
# 0 in-degree correspond to the SCCs from which the minimum set
|
|
# of nodes from which all other nodes can be reached.
|
|
scc_graph = nx.condensation(graph, sccs)
|
|
supernode_to_nodes = {sn: [] for sn in scc_graph.nodes()}
|
|
# Note: the order of mapping differs between pypy and cpython
|
|
# so we have to loop over graph nodes for consistency
|
|
mapping = scc_graph.graph["mapping"]
|
|
for n in graph.nodes:
|
|
sn = mapping[n]
|
|
supernode_to_nodes[sn].append(n)
|
|
sources = []
|
|
for sn in scc_graph.nodes():
|
|
if scc_graph.in_degree[sn] == 0:
|
|
scc = supernode_to_nodes[sn]
|
|
node = min(scc, key=lambda n: graph.in_degree[n])
|
|
sources.append(node)
|
|
else:
|
|
# For undirected graph, the entire graph will be reachable as
|
|
# long as we consider one node from every connected component
|
|
sources = [
|
|
min(cc, key=lambda n: graph.degree[n])
|
|
for cc in nx.connected_components(graph)
|
|
]
|
|
sources = sorted(sources, key=lambda n: graph.degree[n])
|
|
return sources
|
|
|
|
|
|
def forest_str(graph, with_labels=True, sources=None, write=None, ascii_only=False):
|
|
"""Creates a nice utf8 representation of a forest
|
|
|
|
This function has been superseded by
|
|
:func:`nx.readwrite.text.generate_network_text`, which should be used
|
|
instead.
|
|
|
|
Parameters
|
|
----------
|
|
graph : nx.DiGraph | nx.Graph
|
|
Graph to represent (must be a tree, forest, or the empty graph)
|
|
|
|
with_labels : bool
|
|
If True will use the "label" attribute of a node to display if it
|
|
exists otherwise it will use the node value itself. Defaults to True.
|
|
|
|
sources : List
|
|
Mainly relevant for undirected forests, specifies which nodes to list
|
|
first. If unspecified the root nodes of each tree will be used for
|
|
directed forests; for undirected forests this defaults to the nodes
|
|
with the smallest degree.
|
|
|
|
write : callable
|
|
Function to use to write to, if None new lines are appended to
|
|
a list and returned. If set to the `print` function, lines will
|
|
be written to stdout as they are generated. If specified,
|
|
this function will return None. Defaults to None.
|
|
|
|
ascii_only : Boolean
|
|
If True only ASCII characters are used to construct the visualization
|
|
|
|
Returns
|
|
-------
|
|
str | None :
|
|
utf8 representation of the tree / forest
|
|
|
|
Examples
|
|
--------
|
|
>>> graph = nx.balanced_tree(r=2, h=3, create_using=nx.DiGraph)
|
|
>>> print(nx.forest_str(graph))
|
|
╙── 0
|
|
├─╼ 1
|
|
│ ├─╼ 3
|
|
│ │ ├─╼ 7
|
|
│ │ └─╼ 8
|
|
│ └─╼ 4
|
|
│ ├─╼ 9
|
|
│ └─╼ 10
|
|
└─╼ 2
|
|
├─╼ 5
|
|
│ ├─╼ 11
|
|
│ └─╼ 12
|
|
└─╼ 6
|
|
├─╼ 13
|
|
└─╼ 14
|
|
|
|
|
|
>>> graph = nx.balanced_tree(r=1, h=2, create_using=nx.Graph)
|
|
>>> print(nx.forest_str(graph))
|
|
╙── 0
|
|
└── 1
|
|
└── 2
|
|
|
|
>>> print(nx.forest_str(graph, ascii_only=True))
|
|
+-- 0
|
|
L-- 1
|
|
L-- 2
|
|
"""
|
|
msg = (
|
|
"\nforest_str is deprecated as of version 3.1 and will be removed "
|
|
"in version 3.3. Use generate_network_text or write_network_text "
|
|
"instead.\n"
|
|
)
|
|
warnings.warn(msg, DeprecationWarning)
|
|
|
|
if len(graph.nodes) > 0:
|
|
if not nx.is_forest(graph):
|
|
raise nx.NetworkXNotImplemented("input must be a forest or the empty graph")
|
|
|
|
printbuf = []
|
|
if write is None:
|
|
_write = printbuf.append
|
|
else:
|
|
_write = write
|
|
|
|
write_network_text(
|
|
graph,
|
|
_write,
|
|
with_labels=with_labels,
|
|
sources=sources,
|
|
ascii_only=ascii_only,
|
|
end="",
|
|
)
|
|
|
|
if write is None:
|
|
# Only return a string if the custom write function was not specified
|
|
return "\n".join(printbuf)
|
|
|
|
|
|
def _parse_network_text(lines):
|
|
"""Reconstructs a graph from a network text representation.
|
|
|
|
This is mainly used for testing. Network text is for display, not
|
|
serialization, as such this cannot parse all network text representations
|
|
because node labels can be ambiguous with the glyphs and indentation used
|
|
to represent edge structure. Additionally, there is no way to determine if
|
|
disconnected graphs were originally directed or undirected.
|
|
|
|
Parameters
|
|
----------
|
|
lines : list or iterator of strings
|
|
Input data in network text format
|
|
|
|
Returns
|
|
-------
|
|
G: NetworkX graph
|
|
The graph corresponding to the lines in network text format.
|
|
"""
|
|
from itertools import chain
|
|
from typing import Any, NamedTuple, Union
|
|
|
|
class ParseStackFrame(NamedTuple):
|
|
node: Any
|
|
indent: int
|
|
has_vertical_child: int | None
|
|
|
|
initial_line_iter = iter(lines)
|
|
|
|
is_ascii = None
|
|
is_directed = None
|
|
|
|
##############
|
|
# Initial Pass
|
|
##############
|
|
|
|
# Do an initial pass over the lines to determine what type of graph it is.
|
|
# Remember what these lines were, so we can reiterate over them in the
|
|
# parsing pass.
|
|
initial_lines = []
|
|
try:
|
|
first_line = next(initial_line_iter)
|
|
except StopIteration:
|
|
...
|
|
else:
|
|
initial_lines.append(first_line)
|
|
# The first character indicates if it is an ASCII or UTF graph
|
|
first_char = first_line[0]
|
|
if first_char in {
|
|
UtfBaseGlyphs.empty,
|
|
UtfBaseGlyphs.newtree_mid[0],
|
|
UtfBaseGlyphs.newtree_last[0],
|
|
}:
|
|
is_ascii = False
|
|
elif first_char in {
|
|
AsciiBaseGlyphs.empty,
|
|
AsciiBaseGlyphs.newtree_mid[0],
|
|
AsciiBaseGlyphs.newtree_last[0],
|
|
}:
|
|
is_ascii = True
|
|
else:
|
|
raise AssertionError(f"Unexpected first character: {first_char}")
|
|
|
|
if is_ascii:
|
|
directed_glyphs = AsciiDirectedGlyphs.as_dict()
|
|
undirected_glyphs = AsciiUndirectedGlyphs.as_dict()
|
|
else:
|
|
directed_glyphs = UtfDirectedGlyphs.as_dict()
|
|
undirected_glyphs = UtfUndirectedGlyphs.as_dict()
|
|
|
|
# For both directed / undirected glyphs, determine which glyphs never
|
|
# appear as substrings in the other undirected / directed glyphs. Glyphs
|
|
# with this property unambiguously indicates if a graph is directed /
|
|
# undirected.
|
|
directed_items = set(directed_glyphs.values())
|
|
undirected_items = set(undirected_glyphs.values())
|
|
unambiguous_directed_items = []
|
|
for item in directed_items:
|
|
other_items = undirected_items
|
|
other_supersets = [other for other in other_items if item in other]
|
|
if not other_supersets:
|
|
unambiguous_directed_items.append(item)
|
|
unambiguous_undirected_items = []
|
|
for item in undirected_items:
|
|
other_items = directed_items
|
|
other_supersets = [other for other in other_items if item in other]
|
|
if not other_supersets:
|
|
unambiguous_undirected_items.append(item)
|
|
|
|
for line in initial_line_iter:
|
|
initial_lines.append(line)
|
|
if any(item in line for item in unambiguous_undirected_items):
|
|
is_directed = False
|
|
break
|
|
elif any(item in line for item in unambiguous_directed_items):
|
|
is_directed = True
|
|
break
|
|
|
|
if is_directed is None:
|
|
# Not enough information to determine, choose undirected by default
|
|
is_directed = False
|
|
|
|
glyphs = directed_glyphs if is_directed else undirected_glyphs
|
|
|
|
# the backedge symbol by itself can be ambiguous, but with spaces around it
|
|
# becomes unambiguous.
|
|
backedge_symbol = " " + glyphs["backedge"] + " "
|
|
|
|
# Reconstruct an iterator over all of the lines.
|
|
parsing_line_iter = chain(initial_lines, initial_line_iter)
|
|
|
|
##############
|
|
# Parsing Pass
|
|
##############
|
|
|
|
edges = []
|
|
nodes = []
|
|
is_empty = None
|
|
|
|
noparent = object() # sentinel value
|
|
|
|
# keep a stack of previous nodes that could be parents of subsequent nodes
|
|
stack = [ParseStackFrame(noparent, -1, None)]
|
|
|
|
for line in parsing_line_iter:
|
|
if line == glyphs["empty"]:
|
|
# If the line is the empty glyph, we are done.
|
|
# There shouldn't be anything else after this.
|
|
is_empty = True
|
|
continue
|
|
|
|
if backedge_symbol in line:
|
|
# This line has one or more backedges, separate those out
|
|
node_part, backedge_part = line.split(backedge_symbol)
|
|
backedge_nodes = [u.strip() for u in backedge_part.split(", ")]
|
|
# Now the node can be parsed
|
|
node_part = node_part.rstrip()
|
|
prefix, node = node_part.rsplit(" ", 1)
|
|
node = node.strip()
|
|
# Add the backedges to the edge list
|
|
edges.extend([(u, node) for u in backedge_nodes])
|
|
else:
|
|
# No backedge, the tail of this line is the node
|
|
prefix, node = line.rsplit(" ", 1)
|
|
node = node.strip()
|
|
|
|
prev = stack.pop()
|
|
|
|
if node in glyphs["vertical_edge"]:
|
|
# Previous node is still the previous node, but we know it will
|
|
# have exactly one child, which will need to have its nesting level
|
|
# adjusted.
|
|
modified_prev = ParseStackFrame(
|
|
prev.node,
|
|
prev.indent,
|
|
True,
|
|
)
|
|
stack.append(modified_prev)
|
|
continue
|
|
|
|
# The length of the string before the node characters give us a hint
|
|
# about our nesting level. The only case where this doesn't work is
|
|
# when there are vertical chains, which is handled explicitly.
|
|
indent = len(prefix)
|
|
curr = ParseStackFrame(node, indent, None)
|
|
|
|
if prev.has_vertical_child:
|
|
# In this case we know prev must be the parent of our current line,
|
|
# so we don't have to search the stack. (which is good because the
|
|
# indentation check wouldn't work in this case).
|
|
...
|
|
else:
|
|
# If the previous node nesting-level is greater than the current
|
|
# nodes nesting-level than the previous node was the end of a path,
|
|
# and is not our parent. We can safely pop nodes off the stack
|
|
# until we find one with a comparable nesting-level, which is our
|
|
# parent.
|
|
while curr.indent <= prev.indent:
|
|
prev = stack.pop()
|
|
|
|
if node == "...":
|
|
# The current previous node is no longer a valid parent,
|
|
# keep it popped from the stack.
|
|
stack.append(prev)
|
|
else:
|
|
# The previous and current nodes may still be parents, so add them
|
|
# back onto the stack.
|
|
stack.append(prev)
|
|
stack.append(curr)
|
|
|
|
# Add the node and the edge to its parent to the node / edge lists.
|
|
nodes.append(curr.node)
|
|
if prev.node is not noparent:
|
|
edges.append((prev.node, curr.node))
|
|
|
|
if is_empty:
|
|
# Sanity check
|
|
assert len(nodes) == 0
|
|
|
|
# Reconstruct the graph
|
|
cls = nx.DiGraph if is_directed else nx.Graph
|
|
new = cls()
|
|
new.add_nodes_from(nodes)
|
|
new.add_edges_from(edges)
|
|
return new
|