Plotting 2-D arrays or functions of 2 variables

In this chapter we will address methods for plotting a scalar function of two variables. Here are some examples:

• A photographic image, represented as a 2-D array of colors; the grid is regular, with each element of the array corresponding to a square pixel.
• Earth surface elevation and ocean bottom topography, represented as a 2-D array of heights; the grid is rectangular in latitude and longitude, but the latitude increment may not be uniform--often it will decrease toward the poles.
• A mathematical function of two variables, such as a bivariate Gaussian probability density.

Note: in this chapter we will assume the data to be plotted are on a grid. If you have scalar data of two variables, but the data are not on a grid - for example, sea level at island stations - then you will need to use an interpolation or other gridding routine before you can use any of the plotting methods we will discuss here.

As a 2-D plotting library, matplotlib offers two basic styles of plot for scalar functions of two variables: an image style and a contour style. The image style renders the data as either a continuously-varying field of color or a set of contiguous colored quadrilaterals. Hence, the image style is a direct representation of the data array. The contour style is less direct; isolines of the data are calculated and then either plotted as lines or used to delimit colored regions.