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Add type hints to strings/min_cost_string_conversion.py (#2337)

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* done

* add types for local variables

* Revert "add types for local variables"

This reverts commit 971c15673b.

* rename variables

* Update strings/min_cost_string_conversion.py

Co-authored-by: Christian Clauss <cclauss@me.com>

* rename strings

* use flake8

* Update strings/min_cost_string_conversion.py

Co-authored-by: Christian Clauss <cclauss@me.com>
This commit is contained in:
Eugeniy Orlov 2020-10-01 04:04:31 +03:00 committed by GitHub
parent 2fa009aa53
commit 2388bf4e17
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1 changed files with 45 additions and 33 deletions
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78
strings/min_cost_string_conversion.py
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@ -1,55 +1,67 @@
from typing import List, Tuple
"""
Algorithm for calculating the most cost-efficient sequence for converting one string
into another.
The only allowed operations are
---Copy character with cost cC
---Replace character with cost cR
---Delete character with cost cD
---Insert character with cost cI
--- Cost to copy a character is copy_cost
--- Cost to replace a character is replace_cost
--- Cost to delete a character is delete_cost
--- Cost to insert a character is insert_cost
"""
def compute_transform_tables(X, Y, cC, cR, cD, cI):
X = list(X)
Y = list(Y)
m = len(X)
n = len(Y)
def compute_transform_tables(
source_string: str,
destination_string: str,
copy_cost: int,
replace_cost: int,
delete_cost: int,
insert_cost: int,
) -> Tuple[List[int], List[str]]:
source_seq = list(source_string)
destination_seq = list(destination_string)
len_source_seq = len(source_seq)
len_destination_seq = len(destination_seq)
costs = [[0 for _ in range(n + 1)] for _ in range(m + 1)]
ops = [[0 for _ in range(n + 1)] for _ in range(m + 1)]
costs = [
[0 for _ in range(len_destination_seq + 1)] for _ in range(len_source_seq + 1)
]
ops = [
[0 for _ in range(len_destination_seq + 1)] for _ in range(len_source_seq + 1)
]
for i in range(1, m + 1):
costs[i][0] = i * cD
ops[i][0] = "D%c" % X[i - 1]
for i in range(1, len_source_seq + 1):
costs[i][0] = i * delete_cost
ops[i][0] = "D%c" % source_seq[i - 1]
for i in range(1, n + 1):
costs[0][i] = i * cI
ops[0][i] = "I%c" % Y[i - 1]
for i in range(1, len_destination_seq + 1):
costs[0][i] = i * insert_cost
ops[0][i] = "I%c" % destination_seq[i - 1]
for i in range(1, m + 1):
for j in range(1, n + 1):
if X[i - 1] == Y[j - 1]:
costs[i][j] = costs[i - 1][j - 1] + cC
ops[i][j] = "C%c" % X[i - 1]
for i in range(1, len_source_seq + 1):
for j in range(1, len_destination_seq + 1):
if source_seq[i - 1] == destination_seq[j - 1]:
costs[i][j] = costs[i - 1][j - 1] + copy_cost
ops[i][j] = "C%c" % source_seq[i - 1]
else:
costs[i][j] = costs[i - 1][j - 1] + cR
ops[i][j] = "R%c" % X[i - 1] + str(Y[j - 1])
costs[i][j] = costs[i - 1][j - 1] + replace_cost
ops[i][j] = "R%c" % source_seq[i - 1] + str(destination_seq[j - 1])
if costs[i - 1][j] + cD < costs[i][j]:
costs[i][j] = costs[i - 1][j] + cD
ops[i][j] = "D%c" % X[i - 1]
if costs[i - 1][j] + delete_cost < costs[i][j]:
costs[i][j] = costs[i - 1][j] + delete_cost
ops[i][j] = "D%c" % source_seq[i - 1]
if costs[i][j - 1] + cI < costs[i][j]:
costs[i][j] = costs[i][j - 1] + cI
ops[i][j] = "I%c" % Y[j - 1]
if costs[i][j - 1] + insert_cost < costs[i][j]:
costs[i][j] = costs[i][j - 1] + insert_cost
ops[i][j] = "I%c" % destination_seq[j - 1]
return costs, ops
def assemble_transformation(ops, i, j):
def assemble_transformation(ops: List[str], i: int, j: int) -> List[str]:
if i == 0 and j == 0:
seq = []
return seq
return []
else:
if ops[i][j][0] == "C" or ops[i][j][0] == "R":
seq = assemble_transformation(ops, i - 1, j - 1)