Using the Manual Plotting Interface

Sometimes you need a lot of flexibility in creating plots. While the PlotWindow provides an easy to use object that can create nice looking, publication quality plots with a minimum of effort, there are often times when its ease of use conflicts with your need to change the font only on the x-axis, or whatever your need/desire/annoying coauthor requires. To that end, yt provides a number of ways of getting the raw data that goes into a plot to you in the form of a one or two dimensional dataset that you can plot using any plotting method you like. matplotlib or another python library are easiest, but these methods allow you to take your data and plot it in gnuplot, or any unnamed commercial plotting packages.

Note that the hierarchy object associated with your snapshot file contains a list of plots you’ve made in pf.h.plots.

Slice, Projections, and other Images: The Fixed Resolution Buffer

For slices and projects, yt provides a manual plotting interface based on the FixedResolutionBuffer (hereafter referred to as FRB) object. Despite its somewhat unwieldy name, at its heart, an FRB is a very simple object: it’s essentially a window into your data: you give it a center and a width or a left and right edge, and an image resolution, and the FRB returns a fully pixelized image. The simplest way to generate an FRB is to use the .to_frb(width, resolution, center=None) method of any data two-dimensional data object:

import pylab as P
from yt.mods import *
pf = load("IsolatedGalaxy/galaxy0030/galaxy0030")

c = pf.h.find_max('Density')[1]
proj = pf.h.proj(0, 'Density')

width = 10/pf['kpc'] # we want a 1.5 mpc view
res = [1000, 1000] # create an image with 1000x1000 pixels
frb = proj.to_frb(width, res, center=c)

P.imshow(frb['Density'])
P.savefig('my_perfect_figure.png')

The FRB is a very small object that can be deleted and recreated quickly (in fact, this is how the reason GUI works when you pan and scan). Furthermore, you can add new fields in the same “window”, and each of them can be plotted with their own zlimit. This is quite useful for creating a mosaic of the same region in space with Density, Temperature, and x-velocity, for example. Each of these quantities requires a substantially different set of limits.

A more complex example, showing a few yt helper functions that can make setting up multiple axes with colorbars easier than it would be using only matplotlib can be found in the cookbook.

Line Plots

This is perhaps the simplest thing to do. yt provides a number of one dimensional objects, and these return a 1-D numpy array of their contents with direct dictionary access. As a simple example, take a AMROrthoRayBase object, which can be created from a hierarchy by calling pf.h.ortho_ray(axis, center).

from yt.mods import *
import pylab as P
pf = load("IsolatedGalaxy/galaxy0030/galaxy0030")
c = pf.h.find_max("Density")[1]
ax = 0 # take a line cut along the x axis
ray = pf.h.ortho_ray(ax, (c[1], c[2])) # cutting through the y0,z0 such that we hit the max density

P.subplot(211)
P.semilogy(ray['x'], ray['Density'])
P.ylabel('Density')
P.subplot(212)
P.semilogy(ray['x'], ray['Temperature'])
P.xlabel('x')
P.ylabel('Temperature')

P.savefig("den_temp_xsweep.png")

Of course, you’ll likely want to do something more sophisticated than using the matplotlib defaults, but this gives the general idea.