Description:
intersectioncalc 0.10
Finds rectangle intersections
pip install intersectioncalc
Tested against Windows 10 / Python 3.10 / Anaconda - should work on MacOS / Linux
Finds rectangle intersections in a DataFrame and populates a new column with results.
The function utilizes NumExpr for calculations, which can significantly improve
performance when dealing with large datasets of rectangles
Args:
df (pd.DataFrame): Input DataFrame containing rectangle coordinates.
columns (tuple or list, optional): Names of columns containing rectangle coordinates
(start_x, start_y, end_x, end_y). Defaults to ("start_x", "start_y", "end_x", "end_y").
new_column (str, int, float, optional): Name of the new column to store intersection results.
Defaults to "aa_intersecting".
dtype (np.float32 | np.float64 | np.int32 | np.int64, optional): Data type for calculations. Defaults to np.int32.
convert_to_tuples (bool, optional): If True, converts intersection results to tuples.
Defaults to False.
Returns:
pd.DataFrame: Input DataFrame with the new_column populated with intersection results.
from intersectioncalc import find_rectangle_intersections
import time
import pandas as pd
import numpy as np
min_x = 1
max_x = 100
min_y = 1
max_y = 100
size = 50000
min_width = 1
max_width = 1000
min_height = 1
max_height = 1000
df = pd.DataFrame(
[
(startx := np.random.randint(min_x, max_x, size=size)),
(starty := np.random.randint(min_y, max_y, size=size)),
startx + np.random.randint(min_width, max_width, size=size),
starty + np.random.randint(min_height, max_height, size=size),
]
).T.rename(columns={0: "start_x", 1: "start_y", 2: "end_x", 3: "end_y"})
start = time.perf_counter()
df = find_rectangle_intersections(
df,
columns=("start_x", "start_y", "end_x", "end_y"),
new_column="aa_intersecting",
dtype=np.int32,
convert_to_tuples=False,
)
print(time.perf_counter() - start)
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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