Graph Recurser¶
Classes:
|
Turns out its a aa a lll a grappp hhh maaaaeeeennnnnn |
Functions:
|
take the words of Recurser to those of Graph_Recurser |
-
class
recurse_words.recursers.graph.
Graph_Recurser
(corpus, subtractions: bool = True, replacements: bool = True, *args, **kwargs)¶ Bases:
recurse_words.recursers.recurse_words.Recurser
Turns out its a aa a lll a grappp hhh maaaaeeeennnnnn
This class will eventually replace
Recurser
as there’s no reason to have both I just didn’t want to screw that one up is all.- Parameters
corpus ()
subtractions ()
replacements ()
*args ()
**kwargs ()
Methods:
__init__
(corpus[, subtractions, replacements])- Parameters
corpus ()
recurse_word
(word[, min_test_word, …])Recurse a single word – see
recurse_all_words()
for argsrecurse_all_words
([min_include_word, …])Populate
word_trees
by searching recursively through words for recurse wordsmake_graph
([root_word, graph_attr, depth, …])Attributes:
word_trees except for just a list of the edges after they have been made unique by calling set()
-
__init__
(corpus, subtractions: bool = True, replacements: bool = True, *args, **kwargs)¶ - Parameters
corpus ()
subtractions ()
replacements ()
*args ()
**kwargs ()
-
property
word_edges
¶ word_trees except for just a list of the edges after they have been made unique by calling set()
- Returns
[(from_word, transformation, to_word),…]
-
recurse_word
(word: str, min_test_word: int = 2, min_clipped_word: int = 3) → Dict[str, Tuple[Tuple[str, str, str]]]¶ Recurse a single word – see
recurse_all_words()
for argsNote
this could be made about a zillion times faster by vectorizing with pandas…
-
recurse_all_words
(min_include_word: int = 9, min_test_word: int = 2, min_clipped_word: int = 3, max_depth: int = 0, n_procs: int = 12, batch_size: int = 100)¶ Populate
word_trees
by searching recursively through words for recurse words- Parameters
min_include_word (int) – Minimum length of original words to test
min_test_word (int) – Minimum size of subwords to test splicing subwords with
min_clipped_word (int) – Minimum size of the resulting spliced/clipped word to be considered for additional recursive subwords
max_depth (int) – Maximum recursion depth to allow, if 0, infinite
n_procs (int) – Number of processors to spawn in the multiprocessing pool
-
make_graph
(root_word: Optional[str] = None, graph_attr: dict = {}, depth: int = 0, node_attr: dict = {}, edge_attr: dict = {}, translate=True) → pygraphviz.agraph.AGraph¶
-
recurse_words.recursers.graph.
_unstack_words
(words: Dict[int, list]) → Tuple[Tuple[str], Dict[str, int]]¶ take the words of Recurser to those of Graph_Recurser
- Parameters
words ()
- Returns
replacements for words and _words