Note
Go to the end to download the full example code.
Heatmap or large arrays#
Example showing how ImageGraphics can be useful for viewing large arrays, these can be in the order of 10^4 x 10^4. The performance and limitations will depend on your hardware.
# test_example = true
import fastplotlib as fpl
import numpy as np
figure = fpl.Figure(size=(700, 560))
xs = np.linspace(0, 2300, 2300, dtype=np.float16)
sine = np.sin(np.sqrt(xs))
data = np.vstack([sine * i for i in range(2_300)])
# plot the image data
img = figure[0, 0].add_image(data=data, name="heatmap")
del data
figure.show()
# NOTE: `if __name__ == "__main__"` is NOT how to use fastplotlib interactively
# please see our docs for using fastplotlib interactively in ipython and jupyter
if __name__ == "__main__":
print(__doc__)
fpl.loop.run()
Total running time of the script: (0 minutes 0.719 seconds)