I am hoping that someone might help me understand how the axes’ tick values are defined when using an image glyph. All of the examples in the gallery show the x and y axes ranging from 0 -> 10, and I have been hard-pressed to get them to show anything else.
As in my other recent post, I am working on various ways to create audio spectrograms. So if using an image, the idea would be that the color of each pixel represents a value at a particular timestamp and frequency. However for the life of me, I can’t seem to define the figure and/or figure.image() x/y properties to create axes which reflect this.
In my use case, I would eventually like to have x labels in some sort of datetime format, and y labels in Hz. However, to define a simpler problem, taking the image example from the gallery what would need to be modified to get the axes for the same image (as well as the x,y coordinates of the pixels when using tooltips) to read -5 -> 5. Or 2->17, or anything else?
Here’s some things I have tried so far, including changing x,y anchors in figure.image, x/y_range props etc. I hope the solution here ends up being as simple as my last question. Many thanks.
import numpy as np from bokeh.plotting import figure, output_file, show N = 500 # original example # x = np.linspace(0, 10, N) v # y = np.linspace(0, 10, N) # modified example x = np.linspace(-5, 5, N) y = np.linspace(-5, 5, N) xx, yy = np.meshgrid(x, y) d = np.sin(xx)*np.cos(yy) # breakout the ranges directly x_range = (min(x), max(x)) y_range = (min(y), max(y)) # original example # p = figure(tooltips=[("x", "$x"), ("y", "$y"), ("value", "@image")]) # p.x_range.range_padding = p.y_range.range_padding = 0 # modified example p = figure(tooltips=[("x", "$x"), ("y", "$y"), ("value", "@image")], x_range=x_range, y_range=y_range) # modified # p.x_range.range_padding = p.y_range.range_padding = 0 # must give a vector of image data for image parameter # original example # p.image(image=[d], x=0, y=0, dw=10, dh=10, palette="Spectral11", level="image") # modified example p.image(image=[d], x=int(x_range), y=int(y_range), dw=10, dh=10, palette="Spectral11", level="image") p.grid.grid_line_width = 0.5 output_file("image.html", title="image_axis.py example") show(p)