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⚡️ Speed up function inferno by 299% #76

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⚡️ Speed up function inferno by 299% #76

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25 changes: 22 additions & 3 deletions src/bokeh/palettes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -431,6 +431,8 @@
if TYPE_CHECKING:
import numpy.typing as npt

_linspace_cache = {}

#-----------------------------------------------------------------------------
# Globals and constants
#-----------------------------------------------------------------------------
Expand Down Expand Up @@ -1524,9 +1526,18 @@ def linear_palette(palette: Palette, n: int) -> Palette:
ValueError if n > len(palette)

"""
if n > len(palette):
raise ValueError(f"Requested {n} colors, function can only return colors up to the base palette's length ({len(palette)})")
return tuple( palette[math.floor(i)] for i in np.linspace(0, len(palette)-1, num=n) )
length = len(palette)
if n > length:
raise ValueError(f"Requested {n} colors, function can only return colors up to the base palette's length ({length})")
# Use cached linspace results for faster index calculation
indices = _get_linspace_indices(length, n)
# Optimization: Local variable access faster than repeated global attribute lookup for math.floor and palette
floor = math.floor
# Copy palette lookup to local variable to reduce global lookup overhead inside genexpr
_palette = palette
# Use generator expression and tuple constructor for memory efficiency, as in original,
# but lookup floor and palette locally so the loop is faster.
return tuple(_palette[floor(i)] for i in indices)

def diverging_palette(palette1: Palette, palette2: Palette, n: int, midpoint: float = 0.5) -> Palette:
""" Generate a new palette by combining exactly two input palettes.
Expand Down Expand Up @@ -1932,6 +1943,14 @@ def to_rgba_array(palette: Palette) -> npt.NDArray[np.uint8]:

return rgba_array

def _get_linspace_indices(length: int, n: int):
"""Return evenly spaced indices for a palette of given length and n colors, using caching for repeated n."""
key = (length, n)
if key not in _linspace_cache:
# Always use dtype float for math.floor, just like original. Cache result as tuple for efficiency.
_linspace_cache[key] = tuple(np.linspace(0, length-1, num=n))
return _linspace_cache[key]

#-----------------------------------------------------------------------------
# Private API
#-----------------------------------------------------------------------------
Expand Down