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sims_maf_contrib

Many cutting-edge

Analyzing simulated ZTF surveys with LSST MAF

Installation

LSST MAF

here

Create a conda environment for maf, to isolate the dependencies:

    conda create --name maf python=2.7 python

Next, activate the new environment you created:

    source activate maf

Now add the LSST conda channel and install the relevant software:

Each time you want to run maf, you need to execute three commands:

    alias mafinit='source activate maf; source eups-setups.sh; setup sims_maf'

ZTF-specific tools

To analyze ztf_sim outputs, we'll use the ztf_maf package.

    git clone https://github.com/ZwickyTransientFacility/ztf_maf.git

You'll also need to download some ztf_sim simulations. Their location is TBD.

Running MAF analyses

Let's take a look at an example notebook with ztf_sim. Change directories to the ztf_maf/notebooks/ directory, then execute

    mafinit
    jupyter notebook

A directory will open in your web browser; click ZTF_MAF_intro.ipynb and start hitting Shift-Enter in the notebook that appears.

Learning more about MAF

High-level MAF resources are available here and here.

installation (see http://lsstsciencecollaborations.github.io/ObservingStrategy/):

conda is recommended

installing:

    conda config --add channels http://eupsforge.net/conda/dev 
    conda install lsst-sims-maf

each time you want to run it:

   source eups-setups.sh 
   setup sims_maf
   ipython notebook