"""

Line Plot Data Slicing

======================

Example showing data slicing with cosine, sine, sinc lines.

"""

# test_example = true

# sphinx_gallery_pygfx_docs = 'screenshot'

import fastplotlib as fpl

import numpy as np

figure = fpl.Figure(size=(700, 560))

xs = np.linspace(-10, 10, 100)

# sine wave

ys = np.sin(xs)

sine = np.dstack([xs, ys])[0]

# cosine wave

ys = np.cos(xs) + 5

cosine = np.dstack([xs, ys])[0]

# sinc function

a = 0.5

ys = np.sinc(xs) * 3 + 8

sinc = np.dstack([xs, ys])[0]

sine_graphic = figure[0, 0].add_line(data=sine, thickness=5, colors="magenta")

# you can also use colormaps for lines!

cosine_graphic = figure[0, 0].add_line(data=cosine, thickness=12, cmap="autumn")

# or a list of colors for each datapoint

colors = ["r"] * 25 + ["purple"] * 25 + ["y"] * 25 + ["b"] * 25

sinc_graphic = figure[0, 0].add_line(data=sinc, thickness=5, colors=colors)

figure.show()

cosine_graphic.data[10:50:5, :2] = sine[10:50:5]

cosine_graphic.data[90:, 1] = 7

cosine_graphic.data[0] = np.array([[-10, 0, 0]])

# additional fancy indexing with boolean array

bool_key = [True, True, True, False, False] * 20

sinc_graphic.data[bool_key, 1] = 7 # y vals to 1

# 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()