14. Color-filled Plotting#

We are not relegated to only plotting contours of values, we can color-fill a variable for our plots. There are a couple of different options we have including color-filled contour, image plots, and raster plots. The choice will depend on what you are looking to plot and the aesthetic of the output image. We’ll demonstrated color-filled plots using FilledContourPlot() and RasterPlot() here and you can look to examples on the web for others as desired.

14.1. Color-filled Plotting#

Plotting filled contours with FilledContourPlot() works very similarly to ContourPlot(), except that contours are filled using a colormap between contour values. All attributes for ContourPlot() work for FilledContourPlot() plots, except for linestyle, linecolor, and linewidth. Additionally, there are the following attributes that work for the various color-filling plot types:

Specific Color-fill Attributes#

  • colormap

  • colorbar

    • This attribute can be set to ‘vertical’ or ‘horizontal’, which is the location the colorbar will be plotted on the panel.

  • image_range

    • A set of values indicating the minimum and maximum for the data being plotted. This attribute should be set as (min_value, max_value), where min_value and max_value are numeric values.

Raster plot style use RasterPlot() for coloring in a cell with a given color for a value, creating a rasterized image (think color-filled pixels the size of a grid cell). This is a good alternative to color-filled contouring, especially as the size of the grid gets smaller.

Example of RasterPlot() use here.

One can also plot an image (e.g., satellite imagery), which uses the ImagePlot() class. This plot style is also a type of rasterized image. This will be used for plotting satellite imagery, which will be demonstrated later but could be used for gridded output from a model as well.

Armed with this palette, we can now use scripting and create very nice images using a suite of model output!