Note
Go to the end to download the full example code.
Scatter Plot#
Example showing scatter plot.
/home/runner/work/fastplotlib/fastplotlib/fastplotlib/graphics/_features/_base.py:18: UserWarning: casting float64 array to float32
warn(f"casting {array.dtype} array to float32")
# test_example = false
import fastplotlib as fpl
import numpy as np
figure = fpl.Figure(size=(700, 560))
# create a random distribution of 10,000 xyz coordinates
n_points = 5_000
# dimensions always have to be [n_points, xyz]
dims = (n_points, 3)
clouds_offset = 15
# create some random clouds
normal = np.random.normal(size=dims, scale=5)
# stack the data into a single array
cloud = np.vstack(
[
normal - clouds_offset,
normal,
normal + clouds_offset,
]
)
# color each of them separately
colors = ["yellow"] * n_points + ["cyan"] * n_points + ["magenta"] * n_points
# use an alpha value since this will be a lot of points
figure[0,0].add_scatter(data=cloud, sizes=3, colors=colors, alpha=0.6)
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.run()
Total running time of the script: (0 minutes 0.946 seconds)