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GeezerVison is showing github.com — PlotPy/plotpy/lutrange.py at master · PlotPyStack/PlotPy

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# -*- coding: utf-8 -*-
#
# Licensed under the terms of the BSD 3-Clause
# (see plotpy/LICENSE for details)
"""
LUT range
---------
The :mod:`plotpy.lutrange` module provides functions to compute and manipulate
the LUT range of plot items.
.. autofunction:: hist_range_threshold
.. autofunction:: lut_range_threshold
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
if TYPE_CHECKING:
from plotpy.items import BaseImageItem, Histogram2DItem
from plotpy.items.histogram import HistDataSource
def hist_range_threshold(
hist: np.ndarray, bin_edges: np.ndarray, percent: float
) -> tuple[float, float]:
"""Return the range obtained by removing `percent` of the histogram mass.
Outliers are eliminated symmetrically (`percent / 2` on each side),
e.g. for contrast adjustment.
Notes:
- If the histogram comes from an image with integer values (e.g. 0-255),
the first bin is assumed to correspond to value 0 and will be ignored.
- For floating-point images, all bins are considered.
Args:
hist: The histogram (length N)
bin_edges: The bin edges (length N+1)
percent: Percent of histogram mass to eliminate (between 0 and 100)
Returns:
A tuple containing the minimum and maximum values of the range
remaining after removing `percent` of the histogram mass.
"""
if not (0 <= percent <= 100):
raise ValueError("percent must be in [0, 100]")
hist_len = len(hist)
i_offset = 0
# 1. Remove the first bin (typically corresponding to 0), only for integer images
if np.issubdtype(bin_edges.dtype, np.integer):
hist = hist[1:]
i_offset = 1
# 3. Threshold: keep `percent`% of the mass → remove (1 - percent)% symmetrically
threshold = 0.5 * percent / 100 * hist.sum()
# 4. Find index where left cumulative sum exceeds threshold
i_bin_min = max(np.cumsum(hist).searchsorted(threshold) - i_offset, 0)
# 5. Find index where right cumulative sum exceeds threshold
i_bin_max = hist_len - np.searchsorted(np.cumsum(np.flipud(hist)), threshold)
# 6. Return bounds as [bin_edges[i_min], bin_edges[i_max + 1]]
vmin, vmax = bin_edges[i_bin_min], bin_edges[i_bin_max]
return vmin, vmax
def lut_range_threshold(
item: BaseImageItem | Histogram2DItem | HistDataSource, bins: int, percent: float
) -> tuple[float, float]:
"""Return the lut range corresponding to the given percent of the histogram
Args:
item (BaseImageItem | Histogram2DItem | HistDataSource): The plot item
bins (int): The number of bins
percent (float): The percent of the histogram
Returns:
tuple[float, float]: The lut range
"""
hist, bin_edges = item.get_histogram(bins)
return hist_range_threshold(hist, bin_edges, percent)
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