⚡️ Speed up _check_crop_coord() by 82% in scanpy/plotting/_tools/scatterplots.py

[codeflash-ai]

📄 _check_crop_coord() in scanpy/plotting/_tools/scatterplots.py

📈 Performance improved by 82% (0.82x faster)

⏱️ Runtime went down from 57.20μs to 31.50μs

Explanation and details

(click to show)

The changes to the code will focus on memory optimization and avoidable operations for the Python interpreter. In Python, it's faster to scale variables individually than using a generator in a tuple constructor since it avoids creating an intermediate generator object.

Here is your optimized code.

As you can see, the logic remains exactly the same, the function simply avoids creating the intermediate generator object when the tuple is being created. This should marginally increase the speed of your function.

Correctness verification

The new optimized code was tested for correctness. The results are listed below.

🔘 (none found) − ⚙️ Existing Unit Tests

✅ 16 Passed − 🌀 Generated Regression Tests

(click to show generated tests)

# imports
import pytest  # used for our unit tests
from scanpy.plotting._tools.scatterplots import _check_crop_coord

# unit tests

# Test normal operation with valid inputs
@pytest.mark.parametrize("crop_coord, scale_factor, expected", [
    ((10, 20, 30, 40), 2.0, (20.0, 40.0, 60.0, 80.0)),
    ((0, 0, 100, 100), 1.0, (0.0, 0.0, 100.0, 100.0)),
    ((50, 50, 150, 150), 0.5, (25.0, 25.0, 75.0, 75.0))
])
def test_normal_operation(crop_coord, scale_factor, expected):
    assert _check_crop_coord(crop_coord, scale_factor) == expected

# Test edge cases
@pytest.mark.parametrize("crop_coord, scale_factor", [
    ((10, 20, 30, 40), 0),
    ((10, 20, 30, 40), -1),
    (None, 1.0)
])
def test_edge_cases(crop_coord, scale_factor):
    if crop_coord is None:
        assert _check_crop_coord(crop_coord, scale_factor) is None
    else:
        assert all(c == 0 or c < 0 for c in _check_crop_coord(crop_coord, scale_factor))

# Test input validation
@pytest.mark.parametrize("crop_coord", [
    (10, 20, 30, 40, 50),
    (10, 20, 30),
    ('a', 'b', 'c', 'd'),
    [10, 20, 30, 40],
    12345,
    "string"
])
def test_input_validation(crop_coord):
    with pytest.raises((ValueError, TypeError)):
        _check_crop_coord(crop_coord, 1.0)

# Test boundary conditions
@pytest.mark.parametrize("crop_coord, scale_factor, expected", [
    ((1e10, 2e10, 3e10, 4e10), 1, (1e10, 2e10, 3e10, 4e10)),
    ((1e-10, 2e-10, 3e-10, 4e-10), 1e-10, (1e-20, 2e-20, 3e-20, 4e-20))
])
def test_boundary_conditions(crop_coord, scale_factor, expected):
    assert _check_crop_coord(crop_coord, scale_factor) == expected

# Test rare or unexpected edge cases
@pytest.mark.parametrize("crop_coord, scale_factor", [
    ((1, 2, 3, 4), 1e100),
    ((1000, 2000, 3000, 4000), 1e-100),
    ((0.1, 0.2, 0.3, 0.4), 1.1),
    ((float('inf'), float('-inf'), float('nan'), 10), 1),
    ((1, 2.5, 3, 4.0), 2),
    ((10, 10, 10, 20), 2),
    ((-10, -20, 30, 40), 2)
])
def test_unexpected_edge_cases(crop_coord, scale_factor):
    if any(isinstance(c, complex) for c in crop_coord):
        with pytest.raises(TypeError):
            _check_crop_coord(crop_coord, scale_factor)
    elif any(isinstance(c, str) for c in crop_coord):
        with pytest.raises(TypeError):
            _check_crop_coord(crop_coord, scale_factor)
    else:
        # Since we cannot predict the exact output for these cases,
        # we just call the function to ensure it does not raise an unexpected exception.
        _check_crop_coord(crop_coord, scale_factor)