Linear Selectors Image

Example showing how to use a LinearSelector to selector rows or columns of an image. The subplot on the right displays the data for the selector row and column.

# test_example = false

import fastplotlib as fpl
from imageio import v3 as iio

image_data = iio.imread("imageio:coins.png")

figure = fpl.Figure(
    (1, 3),
    size=(700, 300),
    names=[["image", "selected row data", "selected column data"]]
)

# create an image
image = figure[0, 0].add_image(image_data)

# add a row selector
image_row_selector = image.add_linear_selector(axis="y")

# add column selector
image_col_selector = image.add_linear_selector()

# make a line to indicate row data
line_image_row = figure[0, 1].add_line(image.data[0])

# make a line to indicate column data
line_image_col = figure[0, 2].add_line(image.data[:, 0])


# callbacks to change the line data in subplot [0, 1]
# to display selected row and selected column data
def image_row_selector_changed(ev):
    ix = ev.get_selected_index()
    new_data = image.data[ix]
    # set y values of line with the row data
    line_image_row.data[:, 1] = new_data


def image_col_selector_changed(ev):
    ix = ev.get_selected_index()
    new_data = image.data[:, ix]
    # set y values of line with the column data
    line_image_col.data[:, 1] = new_data


# add event handlers, you can also use a decorator
image_row_selector.add_event_handler(image_row_selector_changed, "selection")
image_col_selector.add_event_handler(image_col_selector_changed, "selection")

# programmatically set the selection or drag it with your mouse pointer
image_row_selector.selection = 200
image_col_selector.selection = 180

figure.show()

for subplot in figure:
    subplot.camera.zoom = 0.5


# 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()