LinearRegionSelectors with LineCollection

Example showing how to use a LinearRegionSelector with a LineCollection

/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

# data to plot
xs = np.linspace(0, 10 * np.pi, 1_000)
sine = np.column_stack([xs, np.sin(xs)])
cosine = np.column_stack([xs, np.cos(xs)])

figure = fpl.Figure((5, 1), size=(700, 1000))

# preallocated size for zoomed data
zoomed_prealloc = 1_000

# sines and cosines
data = [sine, cosine, sine, cosine]

# make line stack
line_stack = figure[0, 0].add_line_stack(data, separation=2)

# make selector
selector = line_stack.add_linear_region_selector()

# preallocate array for storing zoomed in data
zoomed_init = np.column_stack([np.arange(zoomed_prealloc), np.zeros(zoomed_prealloc)])

# populate zoomed view subplots with graphics using preallocated buffer sizes
for i, subplot in enumerate(figure):
    if i == 0:
        # skip the first one
        continue
    # make line graphics for displaying zoomed data
    subplot.add_line(zoomed_init, name="zoomed")


def interpolate(subdata: np.ndarray, axis: int):
    """1D interpolation to display within the preallocated data array"""
    x = np.arange(0, zoomed_prealloc)
    xp = np.linspace(0, zoomed_prealloc, subdata.shape[0])

    # interpolate to preallocated size
    return np.interp(x, xp, fp=subdata[:, axis])  # use the y-values


@selector.add_event_handler("selection")
def update_zoomed_subplots(ev):
    """update the zoomed subplots"""
    zoomed_data = ev.get_selected_data()

    for i in range(len(zoomed_data)):
        # interpolate y-vals
        data = interpolate(zoomed_data[i], axis=1)
        figure[i + 1, 0]["zoomed"].data[:, 1] = data
        figure[i + 1, 0].auto_scale()


# set initial selection so zoomed plots update
selector.selection = (0, 4 * np.pi)

# hide toolbars to reduce clutter
for subplot in figure:
    subplot.toolbar = False

figure.show(maintain_aspect=False)


# 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()