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Lets-Plot for Python

v4.3.2

lets_plot.geom_imshow#

lets_plot.geom_imshow(image_data, cmap=None, *, norm=None, alpha=None, vmin=None, vmax=None, extent=None, compression=None, show_legend=True, color_by='paint_c')#

Display image specified by ndarray with shape.

  • (M, N) - grey-scale image

  • (M, N, 3) - color RGB image

  • (M, N, 4) - color RGB image with alpha channel

This geom is not as flexible as geom_raster() or geom_tile() but vastly superior in the terms of rendering efficiency.

Parameters:
image_datandarray

Specify image type, size and pixel values. Supported array shapes are:

  • (M, N): an image with scalar data. The values are mapped to colors (greys by default) using normalization. See parameters norm, cmap, vmin, vmax.

  • (M, N, 3): an image with RGB values (0-1 float or 0-255 int).

  • (M, N, 4): an image with RGBA values (0-1 float or 0-255 int).

The first two dimensions (M, N) define the rows and columns of the image. Out-of-range values are clipped.

cmapstr, optional

Name of colormap. For example “viridis”, “magma”, “plasma”, “inferno”, or any other colormap which is supported by the Palettable package (jiffyclub/palettable) This parameter is ignored for RGB(A) images.

normbool, default=True

True - luminance values in grey-scale image will be scaled to [0-255] range using a linear scaler. False - disables scaling of luminance values in grey-scale image. This parameter is ignored for RGB(A) images.

alpha: float, optional

The alpha blending value, between 0 (transparent) and 1 (opaque).

vmin, vmaxnumber, optional

Define the data range used for luminance normalization in grey-scale images. This parameter is ignored for RGB(A) images or if parameter norm=False.

extentlist of 4 numbers: [left, right, bottom, top], optional

Define image’s bounding box in terms of the “data coordinates”.

  • left, right: coordinates of pixels’ outer edge along the x-axis for pixels in the 1-st and the last column.

  • bottom, top: coordinates of pixels’ outer edge along the y-axis for pixels in the 1-st and the last row.

The default is: [-0.5, ncol-0.5, -0.5, nrow-0.5]

compressionint, optional

The compression level to be used by the zlib module. Values from 0 (no compression) to 9 (highest). Value None means that the zlib module uses the default level of compression (which is generally acceptable).

show_legendbool, default=True

Greyscale images only. False - do not show legend for this layer.

color_by{‘fill’, ‘color’, ‘paint_a’, ‘paint_b’, ‘paint_c’}, default=’paint_c’

Define the color aesthetic used by the legend shown for a greyscale image.

Returns:
LayerSpec

Geom object specification.

Notes

This geom doesn’t understand any aesthetics. It doesn’t support color scales either.

Examples

1import numpy as np
2from lets_plot import *
3LetsPlot.setup_html()
4np.random.seed(42)
5image = np.random.randint(256, size=(64, 64, 4))
6ggplot() + geom_imshow(image)


1import numpy as np
2from lets_plot import *
3LetsPlot.setup_html()
4n = 64
5image = 256 * np.linspace(np.linspace(0, .5, n), \
6                          np.linspace(.5, .5, n), n)
7ggplot() + geom_imshow(image, norm=False)


1import numpy as np
2from lets_plot import *
3LetsPlot.setup_html()
4np.random.seed(42)
5image = np.random.normal(size=(64, 64))
6ggplot() + geom_imshow(image, vmin=-1, vmax=1)
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