1 Unstar Star 0 Fork 0

AstroTJU / AstroCatRGPL-2.0

Create your Gitee Account
Explore and code with more than 5 million developers,Free private repositories !:)
Sign up
A Tool for Time Series Reconstruction of Large-Scale Astronomical Catalogs spread retract

Clone or download
Cancel
Notice: Creating folder will generate an empty file .keep, because not support in Git
Loading...
README.en.md

AstroCatR

Description

A Tool for Time Series Reconstruction of Large-Scale Astronomical Catalogues

This is the main source code of AstroCatR, which can reconstruct all celestial objects' time series data for astronomical catalogues.

AstroCatR is a command-line opensource program running on the Linux platform, which is implemented in C and Python. Its capabilities are based on specialized sky partitioning and MPI parallel programming.

Software Architecture

AstroCatR contains three parts, ETL (extract-transform-load) preprocessing, TS-matching calculation and time series data retrieval. You need to have original catalogs, and small data samples are provided in the Data directory. Then run program ETL preprocessing to generate sky zoning file. Next, run program TS-matching to mark celestial objects. Finally, run program Query to search the celestial objects from time series datasets which matched with the target.

CMP directory is the comparative experiments for in-memory reference table, which uses MySQL's memory table and PostgreSQL's unlogged table to store the reference table for matching calculation.

Prerequisites

This program has the following dependencies, which can be found in main directory.

  • mpich
  • Python
  • Gnuplot
  • Cfitsio

Cfitsio is used to parse catalogue FITS files information, MPI is used to accelerate TS-matching calculations and Python is used to manage user queries. Gnuplot creates scatter plots according to the time series data.

Installation steps of Cfitsio

  1. Decompress and extract the contents of the distribution file in a source directory. You can use the following commands:
tar zxvf cfitsio_latest.tar.gz

Generate the make file:

./configure --prefix=/usr

Note that I have included the option --prefix=/usr in order to control where the library will be installed. Otherwise, by default CFITSIO will be installed under the source directory, which normally is a bad idea because that directory will not be included in the default search path for auto-tools.

Compile the source files:

make
make install

The different versions of the CFITSIO library (libcfitsio.*) are installed under: /usr/lib. The auxiliary files longnam.h, fitsio.h, fitsio2.h, and drvrsmem.h are placed under: /usr/include.

Installation

1. Folder: ETL Preprocessing

Under the xingbiao folder, use the next command to compile

make

It will generate an executable file:xingbiao1, then the ETL preprocessing can be executed by running a shell script.

2. Folder: Matching Calculation

Use the next command to compile

make

It will generate an executable file:Matching

3. Folder:Query

It is written in Python, so it needs to install Python and the Python version must be greater than 2.7.

Operating guide

1. The ETL Preprocessing

Set up your own configuration file and create a new folder.

Setting Paths according to actual requirements and execute corresponding shell scripts.

time sh test.sh

To generate sky zoning files

2. TS-matching Calculation

Set the number of processes and level of partitions according to the actual situation, and achieve the desired performance based on partition function.

Use the next command to run mactching operation

mpirun -np $procs ./Matching $input $output $procs

3. Query

Set position parameters and use next command to query service

python Query.py $ra $dec $input $output

Use next command to produce scatter plots

time sh Draw.sh

Use the following command to realize the transfer of time series data

python TScat.py $input $output

Comments ( 0 )

Sign in for post a comment

1
https://gitee.com/AstroTJU/AstroCatR.git
git@gitee.com:AstroTJU/AstroCatR.git
AstroTJU
AstroCatR
AstroCatR
master

Search