lsst-uk / lsst-ir-fusion

Development of code to exploit LSST and VISTA imaging
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LSST IR fusion

This repository defines the database structure for the upcoming combined Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) and Visible and Infrared Survey Telescope for Astronomy (VISTA) near infrared data product. This will provide pixel matched images and multiband catalogues. A preliminary data release will be produced using the Hyper SuprimeCam imaging and catalogues as a precursor to the LSST ten year survey due to start in 2023. The raw data is not stored in Git but there are various notebooks, code, and data descriptions here which, together with the raw data, define the data release. The full data product is currently under development and not publicly available.

Installation

The code is this repository makes use of the LSST stack and the bespoke obs_vista package which tells the LSST stack how to interact with VISTA data. The installation of both of these is described in the obs_vista package:

https://github.com/lsst-uk/obs_vista

That should then permit running the notebooks in the database here.

Data structure

Each folder contained here will have a corresponding data folder not stored on GitHub. Each stage of the processing is divided in to a seperate Data Management Unit (DMU) folder:

DMU Contents
DMU0 Images and catalogues which are inputs to data products produced here.
DMU1 Summaries and stats for raw data in DMU0
DMU2 Constructing photometric and astrometric reference catalogues
DMU3 SExtractor baseline catalogues
DMU4 LSST pipeline runs and Butler repositories
DMU5 Production of final catalogues and diagnostics
DMU6 Photometric redhshifts
DMU7 Spectral Energy Distribution (SED) modelling

Tiling, warping and pixel spaces

The basic tiles are set by the HSC public imaging product which should be similar to the final LSST version. This tiling of the sky into 'tracts' and 'patches' is described in the HSC release pages.

Basic procedure

To start running the pipeline we recommend you begin with the small area test described in ./dmu4/dmu4_Example. After installation of the LSST stack and obs_vista (instructions with the obs_vista package) and cloning this repository you need to do the following for a standard run:

1. Put raw data in DMU0

As a minimum you will need the VISTA imaging of interest, the HSC public processed data of interest, the public PanSTARRS photometric and astrometric catalogues used to calibrate HSC, the 2MASS point source catalogue.

2. Create data summaries in DMU1

We run some simple data trawls in DMU1 in order to find overlapping areas for the VISTA images with the relevant SkyMap patches for a given HSC survey. You need to create a list of VISTA images, their corresponding HSC patches, PanSTARRS 'shards' to make the PanSTARRS-2MASS reference catalogue.

3. Create the reference catalogues in DMU2

We merge the PanSTARRS and 2MASS catalogues using a positional cross match and write it to a format which can be ingested by the LSST stack

4. Run the photometry pipeline to create the final Butler repository in DMU4

This stage consists of many steps which are documented in DMU4. In the final DMU4 folder there are numerous repositories for various different data sets and fields. These repositories should follow the structure of the public HSC/LSST data releases as far as possible. This should allow them to incorporated with other data sets created with the LSST stack using the same procedure.

5. Produce the large area catalogues by merging the bands and patches into a single catalogues in DMU5

For many purposes we would like to have a single catalogue. We merge bands and patches together and conduct all field diagnostics in DMU5.

Test data set

We have made a test data set available here. Copy these files in to this repository and you should have the basic files required to run the test script in dmu4/dmu4_Example.

Running using BPS

To run at scale jobs must be run using the batch processing system. To do this using Slurm the gen3_workflow code must be installed.


License

Copyright 2019 University of Southampton

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.