Image item with non linear axis normalization

[vallsv]

I have this request for Flint https://gitlab.esrf.fr/bliss/bliss/-/issues/3398

I could use a scatter but the rendering will probably not be very good.

Any idea if we could imagine such item in silx?

In the meantime i will probably try to create an item to see what i could do with the existing tools.

[vallsv]

For the record, here is the implementation i will use.

from silx.gui.plot.items.scatter import Scatter

class ImageWithNormalization(Scatter):
    def __init__(self):
        Scatter.__init__(self)
        self.setVisualization(self.Visualization.IRREGULAR_GRID)

    def setData(self, image, xAxis, yAxis, copy=True):
        x = numpy.asarray(xAxis)
        y = numpy.asarray(yAxis)
        value = numpy.asarray(image)
        assert x.ndim == 1
        assert y.ndim == 1
        assert value.ndim == 2
        assert (y.shape[0], x.shape[0]) == value.shape

        ax = numpy.broadcast_to(x, value.shape)
        ay = numpy.broadcast_to(y.reshape(-1, 1), value.shape)
        Scatter.setData(self, ax.flatten(), ay.flatten(), value.flatten())

        self.setVisualizationParameter(
            self.VisualizationParameter.GRID_SHAPE,
            image.shape,
        )
        self.setVisualizationParameter(
            self.VisualizationParameter.GRID_BOUNDS,
            ((x[0], y[0]), (x[-1], y[-1])),
        )
        self.setVisualizationParameter(
            self.VisualizationParameter.GRID_MAJOR_ORDER, "row"
        )

image = numpy.array([[1, 2, 3, 4], [3, 4, 5, 6]])
xAxis = numpy.array([1, 2.5, 3, 3.5])
yAxis = numpy.array([3, 4])
item = ImageWithNormalization(image, xAxis, yAxis)

[t20100]

Related to #4153