Notebook

In [1]:

import pyaurorax
import datetime
import pprint

aurorax = pyaurorax.PyAuroraX()

Data Availability¶

PyAuroraX can be used to retrieve availability information about the data existing in the AuroraX data platform. The two categories - ephemeris and data_products - each have functions to retrieve availability information about them.

You can also view this information in a web interface, on the AuroraX data availability webpage.

Using the aurorax.search.availability.ephemeris() function, we can retrieve data availability information about ephemeris records in the AuroraX data platform. This function retrieves the information from the AuroraX API, which receives updates about this data ~10 minutes after changes are applied (ie. new data is uploaded).

The equivalent function for data products is aurorax.search.availability.data_products().

In [2]:

# set parameters
start_date = datetime.datetime(2019, 1, 1)
end_date = datetime.date(2019, 1, 10)
program = "swarm"
platform = "swarma"
instrument_type = "footprint"

In [3]:

# get availability
availability = aurorax.search.availability.ephemeris(start_date,
                                                     end_date,
                                                     program=program,
                                                     platform=platform,
                                                     instrument_type=instrument_type,
                                                     format=pyaurorax.search.FORMAT_BASIC_INFO)
print(availability)

[AvailabilityResult(data_source=DataSource(identifier=3, program='swarm', platform='swarma', instrument_type='footprint', source_type='leo', display_name='Swarm A', metadata=None, owner=None, maintainers=None, ephemeris_metadata_schema=None, data_product_metadata_schema=None, stats=None, format='basic_info'), available_data_products=None, available_ephemeris={'2019-01-01': 1440, '2019-01-02': 1440, '2019-01-03': 1440, '2019-01-04': 1440, '2019-01-05': 1440, '2019-01-06': 1440, '2019-01-07': 1440, '2019-01-08': 1440, '2019-01-09': 1440, '2019-01-10': 1440})]

In [4]:

pprint.pprint(availability[0].__dict__)

{'available_data_products': None,
 'available_ephemeris': {'2019-01-01': 1440,
                         '2019-01-02': 1440,
                         '2019-01-03': 1440,
                         '2019-01-04': 1440,
                         '2019-01-05': 1440,
                         '2019-01-06': 1440,
                         '2019-01-07': 1440,
                         '2019-01-08': 1440,
                         '2019-01-09': 1440,
                         '2019-01-10': 1440},
 'data_source': DataSource(identifier=3, program='swarm', platform='swarma', instrument_type='footprint', source_type='leo', display_name='Swarm A', metadata=None, owner=None, maintainers=None, ephemeris_metadata_schema=None, data_product_metadata_schema=None, stats=None, format='basic_info')}