IMAGINE observational datasets repository

Still under construction

This package allows one to import a number of observational datasets in a format compatible with IMAGINE.

Usage

One can the available datasets using the package's show_available function.

import imagine_datasets as img_data

# Shows a list of available packages
img_data.show_available()

This will print the details of all the available datasets to screen. For example, the part of this output corresponding to the Oppermann2012 Faraday depth map is:

-------------------imagine_datasets.HEALPix.fd.Oppermann2012--------------------
Class: imagine_datasets.HEALPix.fd.Oppermann2012
Observable: fd
Type: HEALPix
Bibliographic ref:  Oppermann et al. (2012) A&A, 542, A93
URL:  https://ui.adsabs.harvard.edu/abs/2012A&A...542A..93O/abstract

A dataset can be used in an IMAGINE inference pipeline by simply instantiating its corresponding class and including it in a Measurements object, for example,

import imagine as img
import imagine_datasets as img_data
dset = img_data.HEALPix.fd.Oppermann2012(Nside=64)

Once loaded, the dataset contents can be used as a regular IMAGINE dataset:

measurements = img.observables.Measurements(dset)

Additionally, the datasets in this repository come with handy attributes which point to the original publications

citation = dset.ref
citation_url = dset.ref_url

Datasets in this repository also support caching. Usually, a dataset is downloaded when it is requested (i.e. instantiated) for the first time. If a cache directory is set, the data is saved to disk and, thus, will not need to be downloaded again.

One can choose cache directory setting the module variable imagine_datasets.cache_dir or using the environment variable IMAGINE_DATASETS_CACHE_PATH, for example including the following line in your .bashrc file:

export IMAGINE_DATASETS_CACHE_DIR=foo/bar/DatasetCacheDir