pltimshow

plt.imshow is a function in matplotlib.pyplot that renders image data on the active axes. It takes array-like data and displays it as a grid of colored pixels, returning an AxesImage object that can be further manipulated or updated. It is commonly used to visualize images, heatmaps, or the results of simulations.

Data compatibility: a 2D array is treated as a grayscale image, while a 3D array with shape (M,N,3) or (M,N,4) is interpreted as RGB or RGBA data. When displaying a 2D array without color channels, you can specify a colormap with cmap (for example, cmap='gray').

Key parameters include: cmap selects the color map; vmin and vmax set the data value range for color mapping; norm can apply a more complex normalization (for example, LogNorm). The interpolation option controls how pixels are resampled when scaling (defaults to nearest); origin places the [0,0] data index at the top ('upper') or bottom ('lower') of the axes; extent can map array indices to specific data coordinates; aspect controls the axes aspect ratio (e.g., 'auto', 'equal').

Other options like alpha control transparency; you can supply data normalization via norm and specify whether the image should be displayed in grayscale or color.

After calling imshow, you can add a colorbar with plt.colorbar() to display the scale, and you may adjust axis limits or call plt.axis('image') to ensure equal data-to-pixel proportions.

Note that imshow draws on the current axes and does not automatically save or display the figure; in scripts, call plt.show() to render.