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Merged
connorferster merged 2 commits into from
Oct 10, 2025
Merged

Fixes/adding robustness to singularities to polygon #11

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08579c9
test: add failing test
connorferster Oct 10, 2025
e6ddef8
fix: removed popping from x_acc and implemented filtering instead
connorferster Oct 10, 2025
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15 changes: 10 additions & 5 deletions src/load_distribution/load_distribution.py
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Original file line number Diff line number Diff line change
Expand Up @@ -215,31 +215,36 @@ def singularities_to_polygon(los: list[Singularity], xy: bool = False) -> Polygo
# required shape, even if that means the exact x value is omitted (because we are
# keeping the value immediately to the left and immediately to the right instead).
x_acc = sorted(list(set(x_acc)))

x_ord_count = Counter([round(x, 6) for x in x_acc])
to_filter = []
for key, count in x_ord_count.items():
if count == 3:
to_filter.append(key)

filtered_indexes = []
if to_filter:
rounded_x_acc = [round(x, 6) for x in x_acc]
for filter_val in to_filter:
index = rounded_x_acc.index(filter_val)
x_acc.pop(index)
filtered_indexes.append(index + 1)

filtered_x = []
for idx, x_val in enumerate(x_acc):
if idx not in filtered_indexes:
filtered_x.append(x_val)

# Now, for every x value, compute the corresponding y value
y_acc = [sum([sing(x) for sing in sorted_sings]) for x in x_acc[:-1]]
y_acc = [sum([sing(x) for sing in sorted_sings]) for x in filtered_x[:-1]]
# Always ends on 0.0
y_acc.append(0.0)
if xy:
return x_acc, y_acc
else:
precision = n if n else 2
xy_acc = zip(
[round(x, precision) for x in x_acc], [round(y, precision) for y in y_acc]
[round(x, precision) for x in filtered_x],
[round(y, precision) for y in y_acc],
)

return Polygon(xy_acc)


Expand Down
319 changes: 319 additions & 0 deletions tests/test_data.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,319 @@
from load_distribution import Singularity
import numpy as np

# An output from papermodels that caused an error in the singularities_to_polygon function due to lots of list popping

big_list_o_singularities = [
Singularity(
x0=6.628,
x1=7.859,
m=np.float64(0.0),
y0=np.float64(-111.0726290117895),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=0.413,
m=np.float64(0.0),
y0=np.float64(1684.3833962328304),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=6.628,
x1=7.859,
m=np.float64(0.0),
y0=np.float64(-111.0726290117895),
precision=6,
eps=1e-12,
),
Singularity(
x0=7.57,
x1=7.859,
m=np.float64(0.0),
y0=np.float64(1274.5157420687394),
precision=6,
eps=1e-12,
),
Singularity(
x0=6.628,
x1=7.859,
m=np.float64(0.0),
y0=np.float64(-111.0726290117895),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=0.413,
m=np.float64(0.0),
y0=np.float64(1684.3833962328304),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=6.628,
x1=7.859,
m=np.float64(0.0),
y0=np.float64(-111.0726290117895),
precision=6,
eps=1e-12,
),
Singularity(
x0=7.57,
x1=7.859,
m=np.float64(0.0),
y0=np.float64(1274.5157420687394),
precision=6,
eps=1e-12,
),
Singularity(
x0=6.628,
x1=7.859,
m=np.float64(0.0),
y0=np.float64(-111.0726290117895),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=0.413,
m=np.float64(0.0),
y0=np.float64(1684.3833962328304),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=3.172,
x1=6.876,
m=np.float64(0.0),
y0=np.float64(-110.42669320082763),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=0.001,
x1=3.504,
m=np.float64(0.0),
y0=np.float64(-110.44792139070424),
precision=6,
eps=1e-12,
),
Singularity(
x0=6.628,
x1=7.859,
m=np.float64(0.0),
y0=np.float64(-111.0726290117895),
precision=6,
eps=1e-12,
),
Singularity(
x0=7.57,
x1=7.859,
m=np.float64(0.0),
y0=np.float64(1274.5157420687394),
precision=6,
eps=1e-12,
),
]
9 changes: 9 additions & 0 deletions tests/test_load_distribution.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import load_distribution as ld
import test_data as data
from shapely import Polygon, GeometryCollection

import pytest
Expand Down Expand Up @@ -236,6 +237,14 @@ def test_singularities_to_polygon():
== "POLYGON ((0 0, 0.034368 0, 0.051573 0.5, 0.051573 0.5, 11.705 0.5, 11.705 0, 0 0))"
)

# This test fails due to popping multiple items from a list where the indexes have changed
# because of the popping

assert (
(ld.singularities_to_polygon(data.big_list_o_singularities).wkt)
== "POLYGON ((0 0, 0.001 0, 0.001 3396.431373, 0.413 3396.431373, 0.413 -1656.718815, 3.172 -1656.718815, 3.172 -2981.839131, 3.504 -2981.839131, 3.504 -1325.120316, 6.628 -1325.120316, 6.628 -1991.55609, 6.876 -1991.55609, 6.876 -666.435774, 7.57 -666.435774, 7.57 3157.111452, 7.859 3157.111452, 7.859 0, 0 0))"
)


def test_overlap_region_to_singularity():
assert ld.overlap_region_to_singularity(
Expand Down