Implement Levenshtein distance, to be used to apply hunks
This commit is contained in:
parent
0a9c03d1e1
commit
50f54b1389
1 changed files with 180 additions and 0 deletions
180
patch2vimedit/hunk_changes.py
Normal file
180
patch2vimedit/hunk_changes.py
Normal file
|
|
@ -0,0 +1,180 @@
|
|||
""" Tools to make smart edition to apply a hunk """
|
||||
|
||||
from collections import OrderedDict
|
||||
|
||||
|
||||
class Levenshtein:
|
||||
cache = {}
|
||||
moves = {
|
||||
"D": (-1, 0),
|
||||
"S": (-1, -1),
|
||||
"I": (0, -1),
|
||||
}
|
||||
|
||||
def __init__(self, pre, post):
|
||||
self.pre = pre
|
||||
self.post = post
|
||||
self.work_matrix = None
|
||||
self.op_matrix = None
|
||||
|
||||
@classmethod
|
||||
def get_full_cache(cls):
|
||||
return cls.cache
|
||||
|
||||
def cache_key(self):
|
||||
if isinstance(self.pre, list):
|
||||
return (tuple(self.pre), tuple(self.post))
|
||||
return (self.pre, self.post)
|
||||
|
||||
def getcache(self):
|
||||
return self.get_full_cache().get(self.cache_key(), None)
|
||||
|
||||
@classmethod
|
||||
def clean_cache(cls):
|
||||
cls.cache = {}
|
||||
|
||||
def insert_cost(self, to_insert, pre_idx, post_idx):
|
||||
return 1
|
||||
|
||||
def del_cost(self, to_delete, pre_idx, post_idx):
|
||||
return 1
|
||||
|
||||
def subst_cost(self, subst_from, subst_to, pre_idx, post_idx):
|
||||
return int(subst_from != subst_to)
|
||||
|
||||
@staticmethod
|
||||
def _argmin(**kwargs):
|
||||
""" Returns the first encountered pair (k, v) with lowest v wrt. `<`. """
|
||||
if not kwargs:
|
||||
raise Exception("No arguments")
|
||||
argmin = next(iter(kwargs))
|
||||
valmin = kwargs[argmin]
|
||||
|
||||
for key in kwargs:
|
||||
val = kwargs[key]
|
||||
if val < valmin:
|
||||
argmin = key
|
||||
valmin = val
|
||||
return (argmin, valmin)
|
||||
|
||||
def compute(self):
|
||||
cached = self.getcache()
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
self.op_matrix = [[None] + ["I"] * len(self.post)] + [
|
||||
["D"] + [None] * (len(self.post)) for _ in range(len(self.pre))
|
||||
]
|
||||
self.work_matrix = [
|
||||
[0] * (len(self.post) + 1) for _ in range(len(self.pre) + 1)
|
||||
]
|
||||
|
||||
for post_idx in range(len(self.post)):
|
||||
self.work_matrix[0][post_idx + 1] = self.work_matrix[0][
|
||||
post_idx
|
||||
] + self.insert_cost(self.post[post_idx], 0, post_idx + 1)
|
||||
for pre_idx in range(len(self.pre)):
|
||||
self.work_matrix[pre_idx + 1][0] = self.work_matrix[pre_idx][
|
||||
0
|
||||
] + self.del_cost(self.pre[pre_idx], pre_idx + 1, 0)
|
||||
|
||||
for pre_idx in range(len(self.pre)):
|
||||
for post_idx in range(len(self.post)):
|
||||
c_insert_cost = self.insert_cost(
|
||||
self.post[post_idx], pre_idx + 1, post_idx + 1
|
||||
)
|
||||
c_del_cost = self.del_cost(self.pre[pre_idx], pre_idx + 1, post_idx + 1)
|
||||
c_subst_cost = self.subst_cost(
|
||||
self.pre[pre_idx], self.post[post_idx], pre_idx + 1, post_idx + 1
|
||||
)
|
||||
|
||||
opmin, costmin = self._argmin(
|
||||
**OrderedDict(
|
||||
[
|
||||
("D", self.work_matrix[pre_idx][post_idx + 1] + c_del_cost),
|
||||
(
|
||||
"I",
|
||||
self.work_matrix[pre_idx + 1][post_idx] + c_insert_cost,
|
||||
),
|
||||
("S", self.work_matrix[pre_idx][post_idx] + c_subst_cost),
|
||||
]
|
||||
)
|
||||
)
|
||||
|
||||
self.work_matrix[pre_idx + 1][post_idx + 1] = costmin
|
||||
self.op_matrix[pre_idx + 1][post_idx + 1] = opmin
|
||||
self.cur_mode = opmin
|
||||
|
||||
ops = []
|
||||
pre_pos = len(self.pre)
|
||||
post_pos = len(self.post)
|
||||
while pre_pos > 0 or post_pos > 0:
|
||||
cur_op = self.op_matrix[pre_pos][post_pos]
|
||||
cost_pre = pre_pos
|
||||
cost_post = post_pos
|
||||
row_m, col_m = self.moves[cur_op]
|
||||
pre_pos += row_m
|
||||
post_pos += col_m
|
||||
if cur_op == "S":
|
||||
pre_val = self.pre[pre_pos]
|
||||
post_val = self.post[post_pos]
|
||||
ops.append(
|
||||
(
|
||||
cur_op,
|
||||
(pre_val, post_val),
|
||||
self.subst_cost(pre_val, post_val, cost_pre, cost_post),
|
||||
)
|
||||
)
|
||||
if cur_op == "I":
|
||||
post_val = self.post[post_pos]
|
||||
ops.append(
|
||||
(cur_op, post_val, self.insert_cost(post_val, cost_pre, cost_post))
|
||||
)
|
||||
if cur_op == "D":
|
||||
pre_val = self.pre[pre_pos]
|
||||
ops.append(
|
||||
(cur_op, pre_val, self.del_cost(pre_val, cost_pre, cost_post))
|
||||
)
|
||||
|
||||
cached_result = {
|
||||
"count": self.work_matrix[-1][-1],
|
||||
"ops": ops[::-1],
|
||||
}
|
||||
|
||||
self.get_full_cache()[self.cache_key()] = cached_result
|
||||
|
||||
return cached_result
|
||||
|
||||
|
||||
class InlineLevenshtein(Levenshtein):
|
||||
""" Levenshtein distance for edition of a single line """
|
||||
|
||||
def insert_cost(self, to_insert, pre_idx, post_idx):
|
||||
return 1
|
||||
|
||||
def del_cost(self, to_delete, pre_idx, post_idx):
|
||||
return 1 # 'x'
|
||||
|
||||
def subst_cost(self, subst_from, subst_to, pre_idx, post_idx):
|
||||
if subst_from == subst_to:
|
||||
return 0
|
||||
return 1
|
||||
|
||||
|
||||
class HunkLevenshtein(Levenshtein):
|
||||
""" Levenshtein distance for hunk edition, ie. should we delete a whole line,
|
||||
insert a whole line or substitute one line with another """
|
||||
|
||||
def insert_cost(self, to_insert, pre_idx, post_idx):
|
||||
indent = 0
|
||||
while indent < len(to_insert) and to_insert[indent] == " ":
|
||||
indent += 1
|
||||
indent_cost = 3 if indent else 0
|
||||
return indent_cost + len(to_insert.strip()) + 1
|
||||
|
||||
def del_cost(self, to_delete, pre_idx, post_idx):
|
||||
return 2
|
||||
|
||||
def subst_cost(self, subst_from, subst_to, pre_idx, post_idx):
|
||||
res = InlineLevenshtein(subst_from, subst_to).compute()
|
||||
return res["count"]
|
||||
Loading…
Add table
Reference in a new issue