Bug summary

When invoking a LinearSegmentedColormap  object as a function, the output can differ based on whether you pass an integer or a float.

For example, in the code snippet below, cmap(1) returns a completely different result than cmap(1.0). While this behavior might be expected given how the colormap is implemented, it feels unintuitive.

IMO the provided reprex demonstrates the issue clearly, but please let me know if more details are needed.

Code for reproduction

from matplotlib.colors import LinearSegmentedColormap

cmap = LinearSegmentedColormap.from_list(name="reprex", colors=["red", "blue"])
print("cmap(0):", cmap(0))
print("cmap(1):", cmap(1))
print("cmap(1.0):", cmap(1.0))

Actual outcome

cmap(0): (np.float64(1.0), np.float64(0.0), np.float64(0.0), np.float64(1.0)) (red)
cmap(1): (np.float64(0.996078431372549), np.float64(0.0), np.float64(0.00392156862745098), np.float64(1.0)) (red)
cmap(1.0): (np.float64(0.0), np.float64(0.0), np.float64(1.0), np.float64(1.0)) (blue)

Expected outcome

cmap(0): (np.float64(1.0), np.float64(0.0), np.float64(0.0), np.float64(1.0)) (red)
cmap(1): (np.float64(0.0), np.float64(0.0), np.float64(1.0), np.float64(1.0)) (blue)
cmap(1.0): (np.float64(0.0), np.float64(0.0), np.float64(1.0), np.float64(1.0)) (blue)

Additional information

No response

Operating system

MacOS Sonoma 14.6.1

Matplotlib Version

3.10.0

Matplotlib Backend

module://positron_ipykernel.matplotlib_backend

Python version

Python 3.13.1

Jupyter version

/

Installation

pip