Getting started with AMUSE¶

Introduction¶

At this point you should have built and tested AMUSE, as described in the previous sections, and are probably wondering “What can AMUSE do for me?”. This section will get you started with AMUSE.

AMUSE is based on python, so if you’re new to Python, you’ll find the official Python documentation a valuable resource. Like with Python, there are basically two ways to use AMUSE. Firstly, directly via the interactive (Python) command line:

> amuse.sh
Python 2.6.4 (r264:75706, Feb 17 2010, 12:05:36)
[GCC 4.4.3 20100127 (Red Hat 4.4.3-4)] on linux2
>>>
>>> quit()

Secondly, by writing (Python) scripts. Suppose you wrote the following script myscript.py, and saved it in the current working directory:

 1 2 3 4 5 6 7 8 9 10 11 12 from amuse.units.units import * from amuse.units import constants def convert_to_freq(wavelengths = [355.1, 468.6, 616.5, 748.1, 893.1] | nano(m)): """ This function converts wavelength to frequency, using the speed of light in vacuum. """ print "The speed of light in vacuum:", constants.c print "wavelength --> frequency" for wavelength in wavelengths: print wavelength, " --> ", (constants.c/wavelength).as_quantity_in(giga(Hz))

Then this script can be executed from the AMUSE interactive command line:

>>> import myscript
>>> help(myscript) # Tells you what myscript can do, ...
>>>    # ... for example that it has a function to convert wavelength to frequency.
>>> myscript.convert_to_freq()
The speed of light in vacuum: 299792458.0 m * s**-1
wavelength -->  frequency
355.1 nm   -->  844247.98085 GHz
468.6 nm   -->  639761.967563 GHz
616.5 nm   -->  486281.359286 GHz
748.1 nm   -->  400738.481486 GHz
893.1 nm   -->  335676.24902 GHz
>>> from amuse.units.units import *
>>> myscript.convert_to_freq([21.0, 18.0, 6.0] | cm)
The speed of light in vacuum: 299792458.0 m * s**-1
wavelength -->  frequency
21.0 cm   -->  1.42758313333 GHz
18.0 cm   -->  1.66551365556 GHz
6.0 cm   -->  4.99654096667 GHz
>>> quit()

You can also run scripts directly from the terminal prompt. Calling amuse.sh with a file name argument will make AMUSE execute the file. For this you need to add the following line to your script, telling the script which of its functions to call when executed:

if __name__ == '__main__':
convert_to_freq()

Your script can now be executed directly from the terminal prompt:

> amuse.sh myscript.py
The speed of light in vacuum: 299792458.0 m * s**-1
wavelength -->  frequency
355.1 nm   -->  844247.98085 GHz
468.6 nm   -->  639761.967563 GHz
616.5 nm   -->  486281.359286 GHz
748.1 nm   -->  400738.481486 GHz
893.1 nm   -->  335676.24902 GHz

Example interactive session¶

This is an example of an interactive session with AMUSE, showing how the interface to a typical (gravitational dynamics) legacy code works. Using the Barnes & Hut Tree code, the dynamics of the Sun-Earth system is solved. This two-body problem is chosen for simplicity, and is, of course, not exactly what a Tree code normally is used for. First we import the necessary AMUSE modules.

>>> from amuse.community.bhtree.interface import BHTree
>>> from amuse.datamodel import Particles
>>> from amuse.units import nbody_system
>>> from amuse.units import units

Gravitational dynamics legacy codes usually work with N-body units internally. We have to tell the code how to convert these to the natural units of the specific system, when creating an instance of the legacy code class.

>>> convert_nbody = nbody_system.nbody_to_si(1.0 | units.MSun, 149.5e6 | units.km)
>>> instance = BHTree(convert_nbody)

Now we can tell the instance to change one of its parameters, before it initializes itself:

>>> instance.parameters.epsilon_squared = 0.001 | units.AU**2

Then we create two particles, with properties set to those of the Sun and the Earth, and hand them over to the BHTree instance.

>>> stars = Particles(2)
>>> sun = stars[0]
>>> sun.mass = 1.0 | units.MSun
>>> sun.position = [0.0,0.0,0.0] | units.m
>>> sun.velocity = [0.0,0.0,0.0] | units.m / units.s
>>> sun.radius = 1.0 | units.RSun
>>> earth = stars[1]
>>> earth.mass = 5.9736e24 | units.kg
>>> earth.radius = 6371.0 | units.km
>>> earth.position = [1.0, 0.0, 0.0] | units.AU
>>> earth.velocity = [0.0, 29783, 0.0] | units.m / units.s

We need to setup a channel to copy values from the code to our model in python:

>>> channel = instance.particles.new_channel_to(stars)

Now the model can be evolved up to a specified end time. The current values of the particles are retieved from the legacy code by using copy from the channel.

>>> print earth.position[0]
149597870691.0 m
>>> print earth.position.as_quantity_in(units.AU)[0]
1.0 AU
>>> instance.evolve_model(1.0 | units.yr)
>>> print earth.position.as_quantity_in(units.AU)[0] # This is the outdated value! (should update_particles first)
1.0 AU
>>> channel.copy()
>>> print earth.position.as_quantity_in(units.AU)[0]
0.999843742682 AU
>>> instance.evolve_model(1.5 | units.yr)
>>> channel.copy()
>>> print earth.position.as_quantity_in(units.AU)[0]
-1.0024037469 AU

It’s always a good idea to clean up after you’re finished:

>>> instance.stop()

Example scripts¶

In the test/examples subdirectory several example scripts are included. They show how the different legacy codes can be used. One such example is test_HRdiagram_cluster.py. It has several optional arguments. The example script can be executed from the AMUSE command line as well as from the terminal prompt (in the latter case use -h to get a list of the available command line options):

>>> import test_HRdiagram_cluster
>>> test_HRdiagram_cluster.simulate_stellar_evolution()
The evolution of  1000  stars will be  simulated until t= 1000.0 Myr ...
Using SSE legacy code for stellar evolution.
Deriving a set of  1000  random masses following a Salpeter IMF between 0.1 and 125 MSun (alpha = -2.35).
Initializing the particles
Start evolving...
Evolved model successfully.
Plotting the data...
All done!
>>> from amuse.units.units import *
>>> test_HRdiagram_cluster.simulate_stellar_evolution(end_time=5000 | Myr)
The evolution of  1000  stars will be  simulated until t= 5000 Myr ...
...
> amuse.sh test_HRdiagram_cluster.py -h
Usage: test_HRdiagram_cluster.py [options]

This script will generate HR diagram for an
evolved cluster of stars with a Salpeter mass
distribution.

Options:
-h, --help            show this help message and exit
...
> amuse.sh test_HRdiagram_cluster.py
The evolution of  1000  stars will be  simulated until t= 1000.0 Myr ...
...

If instead of “Plotting the data…” the script printed “Unable to produce plot: couldn’t find matplotlib.”, this probably means you do not have Matplotlib installed. See the subsection on Matplotlib below.

Matplotlib¶

Matplotlib is a python plotting library which produces publication quality figures. Many of the AMUSE example scripts use this library to produce graphical output. If you would like to take advantage of this library, get it from https://matplotlib.org/ and install it in the Python site-packages directory. For your own work, it is of course also possible to print the required output to the terminal and use your favourite plotting tool to make the figures, or use gnuplot, as described in the next section.

Gnuplot¶

Another plotting utility that can be used from Python and AMUSE scripts is gnuplot. Gnuplot can be downloaded from http://www.gnuplot.info/. If you have gnuplot, you can install the gnuplot-py package to control gnuplot directly from your script.

To install gnuplot-py, open a shell and do:

easy_install gnuplot-py

Further documentation¶

I hope this got you started with AMUSE. To further explore the possibilities with AMUSE, take a look at the other example scripts, and the available: