cigvis.colormap module#

Tools for colormap#

Including:

custom colormap: petrel
cmap to vispy and plotly

cigvis.colormap.arrs_to_image(arr, cmap, clim, as_uint8=False, nancolor=None)#

cigvis.colormap.cmap_to_mpl(cmap)#: convert vispy’s Colormap or str to matplotlib’s cmap

cigvis.colormap.cmap_to_plotly(cmap)#

convert matplotlib’s cmap into plotly’s style

Parameters#

cmapcmap in matplotlib: matplotlib’s cmap

Returns#

plotly_cmapList: colormap used in plotly

cigvis.colormap.cmap_to_vispy(cmap)#

convert matplotlib’s cmap into vispy’s style

Parameters#

cmapcmap in matplotlib: matplotlib’s cmap

Returns#

vispy_cmapvispy.color.Colormap: colormap used in vispy

cigvis.colormap.custom_disc_cmap(values: List, colors: List)#

Custom a discrete colormap from values and colors. Like this:

>>> values: [v1, v2, v3, v4, v5]
>>> colors: [c1, c2, c3, c4, c5]
>>> bound: [v1, (v1+v2)/2, (v2+v3)/2, (v3+v4)/2, (v4+v5)/2, v5]
        = [b1, b2, b3, b4, b5, b6]
>>> [b1, b2]: c1, [b2, b3]: c2, [b3, b4]: c3, [b4, b5]: c4, [b5, b6]: c5 

Parameters#

valuesList: values list, N elements
colorsList: the correspanding colors of values, N elements, each elements can be str, tuple, such as ‘red’, ‘#7F0000’, (0, 0.5, 0)

Returns#

cmapmatplotlib.colors.LinearSegmentedColormap: colormap

Examples#

>>> values = [0, 2, 7, 8]
>>> colors = ['green', '#7f6580', 'blue', (0, 0.8, 0.2)]
>>> cmap = custom_disc_cmap(values, colors)

cigvis.colormap.discrete_cmap(cmap, clim, values)#

cigvis.colormap.distinct_colors(n: int, seed: int = 0)#

Generate distinct RGBA colors for sparse line-style colormaps.

Parameters#

nint: Number of colors.
seedint: Random seed used to make the colors reproducible.

cigvis.colormap.fast_set_cmap(cmap, alpha, excpt)#: fast set cmap by name, alpha and excpt, excpt could be one of [None, ‘min’, ‘max’, ‘ramp’]

cigvis.colormap.get_cmap_from_str(cmap: str)#

return a Colormap from a cmap string

Parameters#

cmapstr: colormap name string

cigvis.colormap.get_colors_from_cmap(cmap, clim: List, values: List)#

get colors from a cmap when special vmin, vmax and values

Parameters#

cmapstr or matplotlib.color.Colormap: input cmap
climList: [vmin, vmax] to Normalize
valuesList: list of values

Returns#

cList: colors at norm(values) locations

cigvis.colormap.get_custom_cmap(cmap: str) → LinearSegmentedColormap#: Get a cmap from a name used in Opendtect software. The supported cmap can be see by get_opendtect_cmap_list()

cigvis.colormap.line_cmap(cmap=None, n_lines: int = 20, samples: int = 256, seed: int = 0)#

Convert a colormap into sparse opaque lines on a transparent background.

This is useful for overlaying RGT/label-like line responses as masks. It mirrors helpers such as set_alpha: pass a colormap object/name and get a modified matplotlib ListedColormap back.

Parameters#

cmapstr or Colormap or int or None: Source colormap. If None, use reproducible distinct random colors. If an integer is passed, it is interpreted as n_lines so calls such as line_cmap(28, 256) mean n_lines=28, samples=256.
n_linesint: Number of opaque color samples.
samplesint: Total number of samples in the returned colormap.
seedint: Random seed used when cmap is None.

cigvis.colormap.list_custom_cmap() → List#: avaliable cmap list

cigvis.colormap.plot_all_custom_cmap(norm: List = None, save: str = None, dpi=300)#: plot all custom cmaps with a norm

cigvis.colormap.plot_cmap(cmap, norm: List = None, save: str = None)#

plot a cmap with a norm

Parameters#

cmapstr or Colormap: colormap
normList: [vmin, vmax], set value range
savestr: name to save

cigvis.colormap.ramp(cmap, blow=0, up=1, alpha_min=0, alpha_max=1)#

Creates a modified colormap from an existing colormap, with adjustable transparency (alpha) levels.

Parameters: - cmap: The original colormap to be modified. - blow (float, optional): The lower bound of the colormap normalization range. Defaults to 0. - up (float, optional): The upper bound of the colormap normalization range. Defaults to 1. - alpha_min (float, optional): The minimum alpha (transparency) value to apply. Defaults to 0. - alpha_max (float, optional): The maximum alpha (transparency) value to apply. Defaults to 1.

Returns: - A new colormap with alpha adjusted from alpha_min to alpha_max within the specified range [blow, up].

cigvis.colormap.reversed(cmap)#

cigvis.colormap.set_alpha(cmap, alpha: float)#

Set the alpha blending value, between 0 (transparent) and 1 (opaque) for a cmap. This function is mainly used in vispy which doesn’t contain a parameter like alpha in matplotlib to set opacity

Parameters#

cmapstr or vispyColormap or mplColormap: the input cmap
alphafloat: opacity

Returns#

cmap : str or vispyColormap or mplColormap

cigvis.colormap.set_alpha_except_bottom(cmap, alpha, clim, segm)#: Set the alpha blending value, between 0 (transparent) and 1 (opaque) for a cmap. And set alphas in range [clim[0], segm] to 0

cigvis.colormap.set_alpha_except_max(cmap, alpha: float)#: Set the alpha blending value, between 0 (transparent) and 1 (opaque) for a cmap and set the alpha of the max value as 0. This means mask the max value when used for a discrete show.

cigvis.colormap.set_alpha_except_min(cmap, alpha: float)#: Set the alpha blending value, between 0 (transparent) and 1 (opaque) for a cmap and set the alpha of the min value as 0. This means mask the min value when used for a discrete show.

cigvis.colormap.set_alpha_except_ranges(cmap, alpha, clim, r)#

Set the alpha blending value, between 0 (transparent) and 1 (opaque) for a cmap. And set the alpha of the range as 0 when clim is applied. This means mask the range of values when used for a discrete show.

Parameters#

rList: ranges, like [0, 2] or [[1, 2], [5, 8], …]

cigvis.colormap.set_alpha_except_top(cmap, alpha, clim, segm)#: Set the alpha blending value, between 0 (transparent) and 1 (opaque) for a cmap. And set alphas in range [segm, clim[1]] to 0

cigvis.colormap.set_alpha_except_values(cmap, alpha: float, clim: List, values: List)#

Set the alpha blending value, between 0 (transparent) and 1 (opaque) for a cmap. And set the alpha of the select values as 0 when clim is applied. This means mask the values when used for a discrete show.

Parameters#

cmapstr or vispyColormap or mplColormap: the input cmap
alphafloat: opacity
climList: [vmin, vmax] for mpl.colors.Normalize
valuesList: the select values to except (or mask)

Returns#

cmap : str or vispyColormap or mplColormap

cigvis.colormap.set_down_as(cmap, color)#

cigvis.colormap.set_up_as(cmap, color)#