Table of Contents
PSpipe
is a pipeline creator for the analysis of the high resolution maps of the large aperture
telescope of the Simons Observatory. It contains tools for estimating power spectra and a
multi-frequency likelihood interfaced with the cobaya
MCMC sampler.
The pipelines are mainly written in python and make use of three different codes
pspy
: python library for power spectrum estimation (https://github.com/simonsobs/pspy)namaster
: C library + python wrapper for power spectrum estimation (https://github.com/LSSTDESC/NaMaster)mflike
: mutlifrequency likelihood interfaced withcobaya
(https://github.com/simonsobs/LAT_MFLike)
The package is licensed under the BSD license.
- Python >= 3.5
- GSL: version 2 required
- FFTW: version 3 required
- cfitsio: at least version 3.0
- healpix: at least version 2.0
If the previous requirements are fulfilled, you can install the PSpipe
package with its
dependencies by doing
$ pip install --user git+https://simonsobs/PSpipe.git
If you plan to develop or want to use the different projects, it is better to checkout the latest version by doing
$ git clone https://github.com/simonsobs/PSpipe.git /where/to/clone
Then you can install the PSpipe
library and its dependencies via
$ pip install --user /where/to/clone
Instructions for installing pspy
at NERSC
are available at INSTALL_PSPY_NERSC.
Instructions for installing NaMaster
at NERSC
are available at INSTALL_NAMASTER_NERSC.
Given the number of requirements, you can use a docker
image already made with the needed
libraries and everything compiled. You should first install docker for your operating system.
We have written a simple bash script to install the PSpipe
docker and to clone the main PSpipe
libraries.
Just copy the script in a directory where you want to work with pspipe and run
$ ./run_docker.sh
This will open a new bash
terminal with a full installation of PSpipe
, pixell
,
NaMaster
, pspy
... For instance, you can start the ipython
interpreter and run the following
import
command
$ ipython
Python 3.6.9 (default, Nov 7 2019, 10:44:02)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.11.1 -- An enhanced Interactive Python. Type '?' for help.
In [1]: import pixell, pymaster, pspy
You can run the python scripts from the tutorials directory of PSpipe
.
When you are done with the image, just type exit
and you will go back to your local machine prompt.
It is also possible to start a jupyter
server from the PSpipe
image and run it into your web
browser. Inside the image terminal, you have to start the jupyter
server by typing
$ jupyter notebook --ip 0.0.0.0
Finally open the http
link (something like http://127.0.0.1:8888/?token...
) within your web
browser and you should be able to run one of the python
notebook.
Everything perfomed within the /home/pspipe/workspace
directory will be reflected into
the /where/to/work_with_pspipe
on your host machine. You can then share configuration files, source codes, data
files... between the running docker
container and your local machine. Nothing will be lost after
you exit from the docker
container.
Docker for Mac limits the resource available to 2Gb of RAM by default, This might cause the code to crash unexpectedly with a cryptic Killed
message. It can easily be modified, click on the docker logo (top right of your screen), go in Preferences/Resources and increase the RAM allocated to Docker.
You are not ready for it: youtube