Change the colormap type of a plot through server callback

[jonathansailing]

I have a object oriented code, with an image. Sometimes the user want’s a log. colormap, sometimes a linear one. Therefore I want to offer a dropdown where the user can select what colorbar to use. However the following minimal example doesn’t change the colormap, but gives me a AttributeError: 'method' object has no attribute 'color_mapper'

from bokeh.plotting import figure, curdoc
from bokeh.models import LinearColorMapper, LogColorMapper, Select
from bokeh.layouts import column
import numpy as np

class Test:
    def __init__(self):
        image = np.arange(0, 100, 1).reshape(10, 10)
        self.figure = figure()
        self.lin_cmap = LinearColorMapper(palette="Turbo256", low=0, high=100)
        self.log_cmap = LogColorMapper(palette="Turbo256", low=1, high=100)
        self.figure.image([image], x=0, y=0, dh=1, dw=1, color_mapper=self.log_cmap)
        self.select = Select(title="colormap", value="linear", options=["linear", "log"])
        self.select.on_change("value", self.change_cmap)

    def change_cmap(self, attr, old, new):
        if new == "log":
            self.figure.image.color_mapper = self.log_cmap
        else:
            self.figure.image.color_mapper = self.lin_cmap

    def plot(self):
        curdoc().add_root(column(self.figure, self.select))

I have also tried other things, like creating self.cmap and assigning that to either the linear or log cmap, but in that case nothing happens.

[Bryan]

It will be much simpler and more reliable to create two versions of the plot up front in a layout, and then toggle their visibility appropriately. Alternatively you could also try adding two versions of the glyphs up front to a single plot, and toggle the glyphs’ visibility.

[jonathansailing]

Thanks for your help! Changing the glyph works good and seems more efficient, than replacing the complete glyph.
In case anybody ever googels the same problem, here is a working solution incl. ColorBar.

class Test:
    def __init__(self):
        image = np.arange(0, 10000, 1).reshape(100, 100)
        self.figure = figure()
        self.lin_cmap = LinearColorMapper(palette="Turbo256", low=0, high=np.max(image))
        self.log_cmap = LogColorMapper(palette="Turbo256", low=0.1, high=np.max(image))
        self.lin_image = self.figure.image([image], x=0, y=0, dh=1, dw=1, color_mapper=self.lin_cmap)
        self.log_image = self.figure.image([image], x=0, y=0, dh=1, dw=1, color_mapper=self.log_cmap, visible=False)
        self.lin_bar = ColorBar(color_mapper=self.lin_cmap)
        self.log_bar = ColorBar(color_mapper=self.log_cmap, visible=False)
        self.figure.add_layout(self.log_bar, "below")
        self.figure.add_layout(self.lin_bar, "below")
        self.select = Select(title="colormap", value="linear", options=["linear", "log"])
        self.select.on_change("value", self.change_cmap)

    def change_cmap(self, attr, old, new):
        if new == "log":
            self.log_image.visible = True
            self.lin_image.visible = False
            self.lin_bar.visible = False
            self.log_bar.visible = True
        else:
            self.log_image.visible = False
            self.lin_image.visible = True
            self.lin_bar.visible = True
            self.log_bar.visible = False

    def plot(self):
        curdoc().add_root(column(self.figure, self.select))


test = Test()
test.plot()