Note
Click here to download the full example code
Test fastplotlib install
This notebook is intended to test your installation of fastplotlib and the associated libraries. If everything in this notebook runs properly, with no errors, then you're good to go!
Otherwise, come to the setup help session on Saturday afternoon.
import fastplotlib as fpl
import numpy as np
Test Figure and adding different types of Graphics
fig = fpl.Figure(shape=(2,2))
create some random image and line data
img = np.random.rand(512, 512)
# linspace, create 100 evenly spaced x values from -10 to 10
xs = np.linspace(-10, 10, 100)
# sine wave
ys = np.sin(xs)
sine = np.column_stack([xs, ys])
# cosine wave
ys = np.cos(xs) + 5
cosine = np.column_stack([xs, ys])
# sinc function
a = 0.5
ys = np.sinc(xs) * 3 + 8
sinc = np.column_stack([xs, ys])
# random scatter plot data
n_points = 1_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
fig[0,0].add_image(data=img, name="random-img")
fig[0,1].add_line_collection(data=[sine, cosine, sinc], colors=["r", "g", "b"])
fig[1,0].add_scatter(data=cloud, colors=colors)
fig.show()
The above figure should look like the following screenshot:
Test ImageWidget
iw_data = np.random.rand(30, 512, 512)
iw = fpl.ImageWidget(data=iw_data, cmap="viridis")
iw.show()
The above figure should look like the following screenshot:
Total running time of the script: ( 0 minutes 0.000 seconds)
Download Python source code: test_fastplotlib_installation.py
Download Jupyter notebook: test_fastplotlib_installation.ipynb