Intialize Sample

Created: 2013-01-04 20:37:02      Last updated: 2013-01-05 16:17:55

This workflow saves a tabular *.pckl Python pickle dataset in the local file system, containing values calculated on physical parameters associated to potential companions of a sample of target galaxies. These original physical parameters are extracted from a postgreSQL database, containing information of all galaxies covered by the SDSS spectroscopic survey. The workflow first access the external database located in the AMIGA server and selects the target galaxies from the sample (those having spectroscopic redshift between 0.03 and 0.1). It then creates a tabular gridded datacube with values associated to potential neighbours. These values are calculates for each point of a 3D space defined by the axes: magnitude in r band, photometric redshift and sigma level of detection. The input default values to build the parameterised datacube are:

- 14.5<mr><22.5><z><0.11><sigma><3.2>

Auxiliary function libraries and scripts are also copied in local file system, and the PYTHONPATH environmental variable is set to a value provided by the user as the Working Path of the digital experiment. Other user provided input values are the database connection settings: hostname, login and password.

Execution environment

The first requirement to run the workflows provided by both ROs is Taverna Workbench2 2.4 or higher. AstroTaverna (Taverna plugin) is also needed in order to get functionalities related with Virtual Observatory web services queries and management of standard VOTable data formats. In general, the execution environment is a Linux distribution including Python4 2.x and a bash shell, with psycopg and numpy Python packages. Access to a PostgreSQL database storing the physical parameters provided by SDSS is also needed; a dump file of database may be downloaded from the AMIGA web server and in order to be deployed and accessible from a local execution environment.

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