FA-70716 / GIS polygon topology / Open access
WKT polygon and multipolygon ring structure: keyword case folding · case 01
Lower-case WKT from some databases is rejected.
ROOT CAUSE
Keywords are compared case-sensitively.
VERIFIED REPAIR
At the keyword case folding step restore `words = up.replace('(', ' ( ').split()`, leaving the rest of the model unchanged.
Unsuccessful approach: Only the geometry keyword is upper-cased; a lower-case EMPTY marker is still not recognised.
Case contract
Input: a WKT string. The keyword (case-insensitive) must be POLYGON or MULTIPOLYGON, else None; "<keyword> EMPTY" returns []. Otherwise parse the parenthesised body into polygons -> rings -> positions, keeping only x and y of every position (Z/M ordinates are dropped). Every ring must have at least 4 positions and be closed in x/y, else None. Return a list of polygons (a POLYGON gives a one-element list).
Why this case matters
WKT is the lingua franca between databases and GIS tools; losing a dimension or nesting level corrupts rings.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(x):
s = x.strip()
up = s.upper()
words = s.replace('(', ' ( ').split()
if not words or words[0] not in ('POLYGON', 'MULTIPOLYGON'):
return None
if len(words) == 2 and words[1] == 'EMPTY':
return []
if '(' not in s:
return None
body = s[s.index('('):]
stack = [[]]
cur = ''
for ch in body:
if ch == '(':
stack.append([])
elif ch in '),':
if cur.strip():
nums = [float(t) for t in cur.split()]
stack[-1].append(nums[:2])
cur = ''
if ch == ')':
done = stack.pop()
stack[-1].append(done)
else:
cur += ch
tree = stack[0][0]
polys = [tree] if words[0] == 'POLYGON' else tree
for poly in polys:
for ring in poly:
if len(ring) < 4 or ring[0] != ring[-1]:
return None
return polys
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('control #0', 'POLYGON ((0 0, 4 0, 4 4, 0 4, 0 0))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]]), ('control #1', 'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0), (2 2, 2 4, 4 4, 2 2))', [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]]), ('regression #2', 'POLYGON Z ((0 0 5, 4 0 5, 4 4 6, 0 0 5))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('regression #3', 'POLYGON ZM ((0 0 5 1, 4 0 5 2, 4 4 6 3, 0 0 5 1))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('regression #4', 'POLYGON M ((0 0 7, 4 0 8, 4 4 9, 0 0 7))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('boundary #5', 'POLYGON EMPTY', []), ('boundary #6', 'polygon empty', []), ('regression #7', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)), ((5 5, 6 5, 6 6, 5 5), (5.2 5.1, 5.8 5.8, 5.8 5.1, 5.2 5.1)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]])], [('regression #3', 'POLYGON ZM ((0 0 5 1, 4 0 5 2, 4 4 6 3, 0 0 5 1))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('regression #4', 'POLYGON M ((0 0 7, 4 0 8, 4 4 9, 0 0 7))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('boundary #5', 'POLYGON EMPTY', []), ('boundary #6', 'polygon empty', []), ('regression #7', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)), ((5 5, 6 5, 6 6, 5 5), (5.2 5.1, 5.8 5.8, 5.8 5.1, 5.2 5.1)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]]), ('regression #8', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]]]), ('regression #9', 'multipolygon (((-1.5 -2, 3e2 0, 0 1e1, -1.5 -2)))', [[[[-1.5, -2.0], [300.0, 0.0], [0.0, 10.0], [-1.5, -2.0]]]]), ('boundary #10', 'POLYGON ((0 0, 4 0, 4 4, 0 1))', None)], [('boundary #6', 'polygon empty', []), ('regression #7', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)), ((5 5, 6 5, 6 6, 5 5), (5.2 5.1, 5.8 5.8, 5.8 5.1, 5.2 5.1)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]]), ('regression #8', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]]]), ('regression #9', 'multipolygon (((-1.5 -2, 3e2 0, 0 1e1, -1.5 -2)))', [[[[-1.5, -2.0], [300.0, 0.0], [0.0, 10.0], [-1.5, -2.0]]]]), ('boundary #10', 'POLYGON ((0 0, 4 0, 4 4, 0 1))', None), ('boundary #11', 'POLYGON ((0 0, 4 0, 0 0))', None), ('control #12', 'Polygon((1 1,5 1,5 5,1 1))', [[[[1.0, 1.0], [5.0, 1.0], [5.0, 5.0], [1.0, 1.0]]]]), ('boundary #13', 'LINESTRING (0 0, 1 1)', None)], [('boundary #6', 'polygon empty', []), ('boundary #10', 'POLYGON ((0 0, 4 0, 4 4, 0 1))', None), ('boundary #11', 'POLYGON ((0 0, 4 0, 0 0))', None), ('control #12', 'Polygon((1 1,5 1,5 5,1 1))', [[[[1.0, 1.0], [5.0, 1.0], [5.0, 5.0], [1.0, 1.0]]]]), ('boundary #13', 'LINESTRING (0 0, 1 1)', None), ('boundary #14', 'MULTIPOLYGON EMPTY', []), ('control #15', ' POLYGON ((0 0, -3 0, -3 -3, 0 0)) ', [[[[0.0, 0.0], [-3.0, 0.0], [-3.0, -3.0], [0.0, 0.0]]]]), ('regression #16', 'MULTIPOLYGON Z (((0 0 1, 2 0 1, 2 2 1, 0 0 1)), ((9 9 0, 8 9 0, 8 8 0, 9 9 0)))', [[[[0.0, 0.0], [2.0, 0.0], [2.0, 2.0], [0.0, 0.0]]], [[[9.0, 9.0], [8.0, 9.0], [8.0, 8.0], [9.0, 9.0]]]])], [('control #0', 'POLYGON ((0 0, 4 0, 4 4, 0 4, 0 0))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]]), ('control #1', 'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0), (2 2, 2 4, 4 4, 2 2))', [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]]), ('boundary #6', 'polygon empty', []), ('regression #9', 'multipolygon (((-1.5 -2, 3e2 0, 0 1e1, -1.5 -2)))', [[[[-1.5, -2.0], [300.0, 0.0], [0.0, 10.0], [-1.5, -2.0]]]]), ('boundary #14', 'MULTIPOLYGON EMPTY', []), ('control #15', ' POLYGON ((0 0, -3 0, -3 -3, 0 0)) ', [[[[0.0, 0.0], [-3.0, 0.0], [-3.0, -3.0], [0.0, 0.0]]]]), ('regression #16', 'MULTIPOLYGON Z (((0 0 1, 2 0 1, 2 2 1, 0 0 1)), ((9 9 0, 8 9 0, 8 8 0, 9 9 0)))', [[[[0.0, 0.0], [2.0, 0.0], [2.0, 2.0], [0.0, 0.0]]], [[[9.0, 9.0], [8.0, 9.0], [8.0, 8.0], [9.0, 9.0]]]]), ('boundary #17', 'POLYGON ((0 0 1, 4 0 1, 4 4 1, 0 0 2))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]])]]
for label, args, expected in fixtures[N-1]:
check(label, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| control #0 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]] | Passed |
| control #1 | [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]] | [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]] | Passed |
| regression #2 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | Passed |
| regression #3 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | Passed |
| regression #4 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | Passed |
| boundary #5 | [] | [] | Passed |
| boundary #6 | None | [] | Failed |
| regression #7 | [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]] | [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]] | Passed |
SHA-256 / 4fbf1f0fd1494d072021f3557fa8245e0246aa47d6ae3932d7f9c90a5dea14ed
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(x):
s = x.strip()
up = s.upper()
words = s.replace('(', ' ( ').split()
words[:1] = [w.upper() for w in words[:1]]
if not words or words[0] not in ('POLYGON', 'MULTIPOLYGON'):
return None
if len(words) == 2 and words[1] == 'EMPTY':
return []
if '(' not in s:
return None
body = s[s.index('('):]
stack = [[]]
cur = ''
for ch in body:
if ch == '(':
stack.append([])
elif ch in '),':
if cur.strip():
nums = [float(t) for t in cur.split()]
stack[-1].append(nums[:2])
cur = ''
if ch == ')':
done = stack.pop()
stack[-1].append(done)
else:
cur += ch
tree = stack[0][0]
polys = [tree] if words[0] == 'POLYGON' else tree
for poly in polys:
for ring in poly:
if len(ring) < 4 or ring[0] != ring[-1]:
return None
return polys
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('control #0', 'POLYGON ((0 0, 4 0, 4 4, 0 4, 0 0))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]]), ('control #1', 'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0), (2 2, 2 4, 4 4, 2 2))', [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]]), ('regression #2', 'POLYGON Z ((0 0 5, 4 0 5, 4 4 6, 0 0 5))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('regression #3', 'POLYGON ZM ((0 0 5 1, 4 0 5 2, 4 4 6 3, 0 0 5 1))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('regression #4', 'POLYGON M ((0 0 7, 4 0 8, 4 4 9, 0 0 7))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('boundary #5', 'POLYGON EMPTY', []), ('boundary #6', 'polygon empty', []), ('regression #7', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)), ((5 5, 6 5, 6 6, 5 5), (5.2 5.1, 5.8 5.8, 5.8 5.1, 5.2 5.1)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]])], [('regression #3', 'POLYGON ZM ((0 0 5 1, 4 0 5 2, 4 4 6 3, 0 0 5 1))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('regression #4', 'POLYGON M ((0 0 7, 4 0 8, 4 4 9, 0 0 7))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('boundary #5', 'POLYGON EMPTY', []), ('boundary #6', 'polygon empty', []), ('regression #7', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)), ((5 5, 6 5, 6 6, 5 5), (5.2 5.1, 5.8 5.8, 5.8 5.1, 5.2 5.1)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]]), ('regression #8', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]]]), ('regression #9', 'multipolygon (((-1.5 -2, 3e2 0, 0 1e1, -1.5 -2)))', [[[[-1.5, -2.0], [300.0, 0.0], [0.0, 10.0], [-1.5, -2.0]]]]), ('boundary #10', 'POLYGON ((0 0, 4 0, 4 4, 0 1))', None)], [('boundary #6', 'polygon empty', []), ('regression #7', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)), ((5 5, 6 5, 6 6, 5 5), (5.2 5.1, 5.8 5.8, 5.8 5.1, 5.2 5.1)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]]), ('regression #8', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]]]), ('regression #9', 'multipolygon (((-1.5 -2, 3e2 0, 0 1e1, -1.5 -2)))', [[[[-1.5, -2.0], [300.0, 0.0], [0.0, 10.0], [-1.5, -2.0]]]]), ('boundary #10', 'POLYGON ((0 0, 4 0, 4 4, 0 1))', None), ('boundary #11', 'POLYGON ((0 0, 4 0, 0 0))', None), ('control #12', 'Polygon((1 1,5 1,5 5,1 1))', [[[[1.0, 1.0], [5.0, 1.0], [5.0, 5.0], [1.0, 1.0]]]]), ('boundary #13', 'LINESTRING (0 0, 1 1)', None)], [('boundary #6', 'polygon empty', []), ('boundary #10', 'POLYGON ((0 0, 4 0, 4 4, 0 1))', None), ('boundary #11', 'POLYGON ((0 0, 4 0, 0 0))', None), ('control #12', 'Polygon((1 1,5 1,5 5,1 1))', [[[[1.0, 1.0], [5.0, 1.0], [5.0, 5.0], [1.0, 1.0]]]]), ('boundary #13', 'LINESTRING (0 0, 1 1)', None), ('boundary #14', 'MULTIPOLYGON EMPTY', []), ('control #15', ' POLYGON ((0 0, -3 0, -3 -3, 0 0)) ', [[[[0.0, 0.0], [-3.0, 0.0], [-3.0, -3.0], [0.0, 0.0]]]]), ('regression #16', 'MULTIPOLYGON Z (((0 0 1, 2 0 1, 2 2 1, 0 0 1)), ((9 9 0, 8 9 0, 8 8 0, 9 9 0)))', [[[[0.0, 0.0], [2.0, 0.0], [2.0, 2.0], [0.0, 0.0]]], [[[9.0, 9.0], [8.0, 9.0], [8.0, 8.0], [9.0, 9.0]]]])], [('control #0', 'POLYGON ((0 0, 4 0, 4 4, 0 4, 0 0))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]]), ('control #1', 'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0), (2 2, 2 4, 4 4, 2 2))', [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]]), ('boundary #6', 'polygon empty', []), ('regression #9', 'multipolygon (((-1.5 -2, 3e2 0, 0 1e1, -1.5 -2)))', [[[[-1.5, -2.0], [300.0, 0.0], [0.0, 10.0], [-1.5, -2.0]]]]), ('boundary #14', 'MULTIPOLYGON EMPTY', []), ('control #15', ' POLYGON ((0 0, -3 0, -3 -3, 0 0)) ', [[[[0.0, 0.0], [-3.0, 0.0], [-3.0, -3.0], [0.0, 0.0]]]]), ('regression #16', 'MULTIPOLYGON Z (((0 0 1, 2 0 1, 2 2 1, 0 0 1)), ((9 9 0, 8 9 0, 8 8 0, 9 9 0)))', [[[[0.0, 0.0], [2.0, 0.0], [2.0, 2.0], [0.0, 0.0]]], [[[9.0, 9.0], [8.0, 9.0], [8.0, 8.0], [9.0, 9.0]]]]), ('boundary #17', 'POLYGON ((0 0 1, 4 0 1, 4 4 1, 0 0 2))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]])]]
for label, args, expected in fixtures[N-1]:
check(label, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| control #0 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]] | Passed |
| control #1 | [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]] | [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]] | Passed |
| regression #2 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | Passed |
| regression #3 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | Passed |
| regression #4 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | Passed |
| boundary #5 | [] | [] | Passed |
| boundary #6 | None | [] | Failed |
| regression #7 | [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]] | [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]] | Passed |
SHA-256 / ae9eb68227865214ee9b7a4126a94b24c2f1ac1dd00afff29f734ec422cc3f47
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(x):
s = x.strip()
up = s.upper()
words = up.replace('(', ' ( ').split()
if not words or words[0] not in ('POLYGON', 'MULTIPOLYGON'):
return None
if len(words) == 2 and words[1] == 'EMPTY':
return []
if '(' not in s:
return None
body = s[s.index('('):]
stack = [[]]
cur = ''
for ch in body:
if ch == '(':
stack.append([])
elif ch in '),':
if cur.strip():
nums = [float(t) for t in cur.split()]
stack[-1].append(nums[:2])
cur = ''
if ch == ')':
done = stack.pop()
stack[-1].append(done)
else:
cur += ch
tree = stack[0][0]
polys = [tree] if words[0] == 'POLYGON' else tree
for poly in polys:
for ring in poly:
if len(ring) < 4 or ring[0] != ring[-1]:
return None
return polys
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('control #0', 'POLYGON ((0 0, 4 0, 4 4, 0 4, 0 0))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]]), ('control #1', 'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0), (2 2, 2 4, 4 4, 2 2))', [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]]), ('regression #2', 'POLYGON Z ((0 0 5, 4 0 5, 4 4 6, 0 0 5))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('regression #3', 'POLYGON ZM ((0 0 5 1, 4 0 5 2, 4 4 6 3, 0 0 5 1))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('regression #4', 'POLYGON M ((0 0 7, 4 0 8, 4 4 9, 0 0 7))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('boundary #5', 'POLYGON EMPTY', []), ('boundary #6', 'polygon empty', []), ('regression #7', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)), ((5 5, 6 5, 6 6, 5 5), (5.2 5.1, 5.8 5.8, 5.8 5.1, 5.2 5.1)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]])], [('regression #3', 'POLYGON ZM ((0 0 5 1, 4 0 5 2, 4 4 6 3, 0 0 5 1))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('regression #4', 'POLYGON M ((0 0 7, 4 0 8, 4 4 9, 0 0 7))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]]), ('boundary #5', 'POLYGON EMPTY', []), ('boundary #6', 'polygon empty', []), ('regression #7', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)), ((5 5, 6 5, 6 6, 5 5), (5.2 5.1, 5.8 5.8, 5.8 5.1, 5.2 5.1)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]]), ('regression #8', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]]]), ('regression #9', 'multipolygon (((-1.5 -2, 3e2 0, 0 1e1, -1.5 -2)))', [[[[-1.5, -2.0], [300.0, 0.0], [0.0, 10.0], [-1.5, -2.0]]]]), ('boundary #10', 'POLYGON ((0 0, 4 0, 4 4, 0 1))', None)], [('boundary #6', 'polygon empty', []), ('regression #7', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)), ((5 5, 6 5, 6 6, 5 5), (5.2 5.1, 5.8 5.8, 5.8 5.1, 5.2 5.1)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]]), ('regression #8', 'MULTIPOLYGON (((0 0, 1 0, 1 1, 0 0)))', [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]]]), ('regression #9', 'multipolygon (((-1.5 -2, 3e2 0, 0 1e1, -1.5 -2)))', [[[[-1.5, -2.0], [300.0, 0.0], [0.0, 10.0], [-1.5, -2.0]]]]), ('boundary #10', 'POLYGON ((0 0, 4 0, 4 4, 0 1))', None), ('boundary #11', 'POLYGON ((0 0, 4 0, 0 0))', None), ('control #12', 'Polygon((1 1,5 1,5 5,1 1))', [[[[1.0, 1.0], [5.0, 1.0], [5.0, 5.0], [1.0, 1.0]]]]), ('boundary #13', 'LINESTRING (0 0, 1 1)', None)], [('boundary #6', 'polygon empty', []), ('boundary #10', 'POLYGON ((0 0, 4 0, 4 4, 0 1))', None), ('boundary #11', 'POLYGON ((0 0, 4 0, 0 0))', None), ('control #12', 'Polygon((1 1,5 1,5 5,1 1))', [[[[1.0, 1.0], [5.0, 1.0], [5.0, 5.0], [1.0, 1.0]]]]), ('boundary #13', 'LINESTRING (0 0, 1 1)', None), ('boundary #14', 'MULTIPOLYGON EMPTY', []), ('control #15', ' POLYGON ((0 0, -3 0, -3 -3, 0 0)) ', [[[[0.0, 0.0], [-3.0, 0.0], [-3.0, -3.0], [0.0, 0.0]]]]), ('regression #16', 'MULTIPOLYGON Z (((0 0 1, 2 0 1, 2 2 1, 0 0 1)), ((9 9 0, 8 9 0, 8 8 0, 9 9 0)))', [[[[0.0, 0.0], [2.0, 0.0], [2.0, 2.0], [0.0, 0.0]]], [[[9.0, 9.0], [8.0, 9.0], [8.0, 8.0], [9.0, 9.0]]]])], [('control #0', 'POLYGON ((0 0, 4 0, 4 4, 0 4, 0 0))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]]), ('control #1', 'POLYGON ((0 0, 10 0, 10 10, 0 10, 0 0), (2 2, 2 4, 4 4, 2 2))', [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]]), ('boundary #6', 'polygon empty', []), ('regression #9', 'multipolygon (((-1.5 -2, 3e2 0, 0 1e1, -1.5 -2)))', [[[[-1.5, -2.0], [300.0, 0.0], [0.0, 10.0], [-1.5, -2.0]]]]), ('boundary #14', 'MULTIPOLYGON EMPTY', []), ('control #15', ' POLYGON ((0 0, -3 0, -3 -3, 0 0)) ', [[[[0.0, 0.0], [-3.0, 0.0], [-3.0, -3.0], [0.0, 0.0]]]]), ('regression #16', 'MULTIPOLYGON Z (((0 0 1, 2 0 1, 2 2 1, 0 0 1)), ((9 9 0, 8 9 0, 8 8 0, 9 9 0)))', [[[[0.0, 0.0], [2.0, 0.0], [2.0, 2.0], [0.0, 0.0]]], [[[9.0, 9.0], [8.0, 9.0], [8.0, 8.0], [9.0, 9.0]]]]), ('boundary #17', 'POLYGON ((0 0 1, 4 0 1, 4 4 1, 0 0 2))', [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]])]]
for label, args, expected in fixtures[N-1]:
check(label, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| control #0 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 4.0], [0.0, 0.0]]]] | Passed |
| control #1 | [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]] | [[[[0.0, 0.0], [10.0, 0.0], [10.0, 10.0], [0.0, 10.0], [0.0, 0.0]], [[2.0, 2.0], [2.0, 4.0], [4.0, 4.0], [2.0, 2.0]]]] | Passed |
| regression #2 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | Passed |
| regression #3 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | Passed |
| regression #4 | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | [[[[0.0, 0.0], [4.0, 0.0], [4.0, 4.0], [0.0, 0.0]]]] | Passed |
| boundary #5 | [] | [] | Passed |
| boundary #6 | [] | [] | Passed |
| regression #7 | [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]] | [[[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]], [[[5.0, 5.0], [6.0, 5.0], [6.0, 6.0], [5.0, 5.0]], [[5.2, 5.1], [5.8, 5.8], [5.8, 5.1], [5.2, 5.1]]]] | Passed |
SHA-256 / ab178526a29e27f5ebc61439dd66c6903fc5eb9bde7abac5392cca56c2a0a09e
Verification & scope
Stipulated deterministic toy contract on a bounded input domain; results are rounded as stated and no conformance with any published standard or library is claimed. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.
Observations recorded using Python 3.12.14 at 2026-09-29T14:48:23.195390+00:00.
Case digest / 4dc392042d907804a8658f7a1583e1b5b2fc076b0d33f183682b822ead456cbe