Source code for napari.utils.colormaps.colormap

from enum import Enum
from typing import Optional

import numpy as np
from pydantic import PrivateAttr, validator

from ..events import EventedModel
from ..events.custom_types import Array
from .colorbars import make_colorbar
from .standardize_color import transform_color


class ColormapInterpolationMode(str, Enum):
    """INTERPOLATION: Interpolation mode for colormaps.

    Selects an interpolation mode for the colormap.
            * linear: colors are defined by linear interpolation between
              colors of neighboring controls points.
            * zero: colors are defined by the value of the color in the
              bin between by neighboring controls points.
    """

    LINEAR = 'linear'
    ZERO = 'zero'


[docs]class Colormap(EventedModel): """Colormap that relates intensity values to colors. Attributes ---------- colors : array, shape (N, 4) Data used in the colormap. name : str Name of the colormap. display_name : str Display name of the colormap. controls : array, shape (N,) or (N+1,) Control points of the colormap. interpolation : str Colormap interpolation mode, either 'linear' or 'zero'. If 'linear', ncontrols = ncolors (one color per control point). If 'zero', ncontrols = ncolors+1 (one color per bin). """ # fields colors: Array[float, (-1, 4)] name: str = 'custom' _display_name: Optional[str] = PrivateAttr(None) interpolation: ColormapInterpolationMode = ColormapInterpolationMode.LINEAR controls: Array[float, (-1,)] = None def __init__(self, colors, display_name: Optional[str] = None, **data): if display_name is None: display_name = data.get('name', 'custom') super().__init__(colors=colors, **data) self._display_name = display_name # validators @validator('colors', pre=True) def _ensure_color_array(cls, v): return transform_color(v) # controls validator must be called even if None for correct initialization @validator('controls', pre=True, always=True) def _check_controls(cls, v, values): if v is None or len(v) == 0: n_controls = len(values['colors']) + int( values['interpolation'] == ColormapInterpolationMode.ZERO ) return np.linspace(0, 1, n_controls) return v def __iter__(self): yield from (self.colors, self.controls, self.interpolation) def map(self, values): values = np.atleast_1d(values) if self.interpolation == ColormapInterpolationMode.LINEAR: # One color per control point cols = [ np.interp(values, self.controls, self.colors[:, i]) for i in range(4) ] cols = np.stack(cols, axis=1) elif self.interpolation == ColormapInterpolationMode.ZERO: # One color per bin indices = np.clip( np.searchsorted(self.controls, values) - 1, 0, len(self.colors) ) cols = self.colors[indices.astype(np.int32)] else: raise ValueError('Unrecognized Colormap Interpolation Mode') return cols @property def colorbar(self): return make_colorbar(self)