Installation

The latest stable version of SimCADO can be installed from PyPI with

pip install simcado

If you have SimCADO already installed and you want to install the latest version, please type

pip install --upgrade simcado

Please do not forget to obtain the latest data file package as explained in the section below

The latest development version of SimCADO can be found on GitHub:

https://github.com/astronomyk/SimCADO

Python 3 vs Python 2

Note

SimCADO has been programmed in Python 3.

While most of the basic functionality for SimCADO will work with Python 2.7, we haven’t tested it properly. For example, the function simcado.install_noise_cube() only works in Python 3. This isn’t critical - it just means that if you want to have read noise variations in your images, you need to use Python 3. However it won’t crash SimCADO for single images.

Note

A side note: Astropy will stop supporting Python 2.7 in 2019 and the official End-of-Life for Python 2.7 is 2020, i.e. no more maintainance. We are running under the assumption that SimCADO will (hopefully) still be around after 2020, hence why we have concentrated our efforts on developing in Python 3.

Note

SimCADO will need to download several hundreds of MBs of instrument data into the install directory. Hence why we use the –user flag when installing via pip. If you want to keep SimCADO in your normal packages directory, then you will need to give python root access while updating SimCADO’s data files.

Dependencies

Required

Package	Version
numpy	>1.10.4
scipy	>0.17
astropy	>1.1.2
wget	>3.0
requests	>2.0
synphot	>0.1
pyyaml

Optional

Package	Version
matplotlib	>1.5.0
poppy	>0.4

All dependencies should be automatically installed when typing the pip command above. In case of any error message you can try to install them manually:

$ pip install numpy scipy astropy wget matplotlib poppy pyyaml synphot requests

We really recomend to install SimCADO in a python distribution like anaconda or miniconda as they allow to have full control over your python environment without interfering with your system instalation.

Getting up-to-date data for SimCADO

SimCADO is being developed along side MICADO. To keep the files that SimCADO uses as fresh as possible, you should run the following command, at the very least the first time you start SimCADO:

>>> import simcado
>>> simcado.get_extras()

This downloads the latest versions of all the files SimCADO uses behind the scenes, e.g. PSF files, transmission curves etc. If you haven’t used SimCADO for several months, chances are there are new data available. It is therefore advantageous to run this command periodically.

Adding variation to the Detector noise

Note

Currently only available for Python 3.

By default SimCADO only supplies a single H4RG noise frame. Hence if you plan on generating a series of images, all images will have the same detector noise pattern. Don’t worry, photon shot noise is still completely random, however if you stack 1000s of simulated images with the same detector noise frame, this pattern will show through. This problem can be avoided by running the following function the first time you run simcado:

We recommend running this command in a separate Python session as it can take up to 10 minutes depending on your computer.:

>>> simcado.install_noise_cube(n=25)

SimCADO contains the code to generate unique detector noise images (Rauscher 2015), however creating a 4k detector noise frame takes about 20 seconds. In order to avoid wasting time by generating noise for each frame every time SimCADO is run, .install_noise_cube(n) generates n noise frames and saves them in the SimCADO data directory. In future simulation one of these detector noise frames are picked at random whenever a <Detector>.read_out() is called.

Obviously a trade-off has to be made when running .install_noise_cube(n). The more noise frames available, the less systematic noise is visible in the read noise of stacked images. However, the more frames are generated, the longer it takes. A good solution is to open a separate window and have SimCADO generate frames in the background.