Imports¶

In [1]:

import pyaurorax
import os
import pprint
import pandas as pd

Get all data sources¶

In [2]:

# get data sources
sources = pyaurorax.sources.list(order="program")

# show as a pandas dataframe
sources_dict = [source.__dict__ for source in sources]
df = pd.DataFrame(sources_dict, 
                  columns=[
                      "identifier", 
                      "program", 
                      "platform", 
                      "instrument_type", 
                      "source_type", 
                      "display_name"
                  ])
df.sort_values(["program", "platform"])

Out[2]:

	identifier	program	platform	instrument_type	source_type	display_name
0	38	arase	arase	footprint	heo	Arase
1	175	auroramax	yellowknife	DSLR	ground	AuroraMAX
2	39	cluster	cluster1	footprint	heo	Cluster-1
4	265	dmsp	dmsp06	footprint	leo	DMSP-06
7	286	dmsp	dmsp07	footprint	leo	DMSP-07
...	...	...	...	...	...	...
104	101	trex	lucky lake	RGB ASI	ground	TREx RGB LUCK
105	102	trex	pinawa	RGB ASI	ground	TREx RGB PINA
100	94	trex	rabbit lake	near-infrared ASI	ground	TREx NIR RABB
103	97	trex	rabbit lake	spectrograph	ground	TREx Spectrograph RABB
107	104	trex	rabbit lake	RGB ASI	ground	TREx RGB RABB

108 rows × 6 columns

Get all THEMIS ASI data sources¶

In [3]:

# get data sources
sources = pyaurorax.sources.list(program="themis-asi")

# show as a pandas dataframe
sources_dict = [source.__dict__ for source in sources]
df = pd.DataFrame(sources_dict, 
                  columns=[
                      "identifier", 
                      "program", 
                      "platform", 
                      "instrument_type", 
                      "source_type", 
                      "display_name"
                  ])
df.sort_values(["program", "platform"])

Out[3]:

	identifier	program	platform	instrument_type	source_type	display_name
0	44	themis-asi	athabasca	panchromatic ASI	ground	THEMIS-ASI ATHA
18	62	themis-asi	chibougamau	panchromatic ASI	ground	THEMIS-ASI CHBG
12	56	themis-asi	ekati	panchromatic ASI	ground	THEMIS-ASI EKAT
1	45	themis-asi	fort simpson	panchromatic ASI	ground	THEMIS-ASI FSIM
11	55	themis-asi	fort smith	panchromatic ASI	ground	THEMIS-ASI FSMI
13	57	themis-asi	fort yukon	panchromatic ASI	ground	THEMIS-ASI FYKN
19	64	themis-asi	gakona	panchromatic ASI	ground	THEMIS-ASI GAKO
2	46	themis-asi	gillam	panchromatic ASI	ground	THEMIS-ASI GILL
21	66	themis-asi	goose bay	panchromatic ASI	ground	THEMIS-ASI GBAY
3	47	themis-asi	inuvik	panchromatic ASI	ground	THEMIS-ASI INUV
4	48	themis-asi	kapuskasing	panchromatic ASI	ground	THEMIS-ASI KAPU
20	65	themis-asi	kiana	panchromatic ASI	ground	THEMIS-ASI KIAN
5	49	themis-asi	kuujjuaq	panchromatic ASI	ground	THEMIS-ASI KUUJ
14	58	themis-asi	mcgrath	panchromatic ASI	ground	THEMIS-ASI MCGR
22	71	themis-asi	narsarsuaq	panchromatic ASI	ground	THEMIS-ASI NRSQ
6	50	themis-asi	pinawa	panchromatic ASI	ground	THEMIS-ASI PINA
15	59	themis-asi	prince george	panchromatic ASI	ground	THEMIS-ASI PGEO
7	51	themis-asi	rankin inlet	panchromatic ASI	ground	THEMIS-ASI RANK
8	52	themis-asi	sanikiluaq	panchromatic ASI	ground	THEMIS-ASI SNKQ
16	60	themis-asi	snap lake	panchromatic ASI	ground	THEMIS-ASI SNAP
9	53	themis-asi	taloyoak	panchromatic ASI	ground	THEMIS-ASI TALO
10	54	themis-asi	the pas	panchromatic ASI	ground	THEMIS-ASI TPAS
17	61	themis-asi	whitehorse	panchromatic ASI	ground	THEMIS-ASI WHIT
23	73	themis-asi	yellowknife	panchromatic ASI	ground	THEMIS-ASI YKNF

Get all RGB instrument types¶

In [4]:

# get data sources
sources = pyaurorax.sources.list(instrument_type="RGB ASI")

# show as a pandas dataframe
sources_dict = [source.__dict__ for source in sources]
df = pd.DataFrame(sources_dict, 
                  columns=[
                      "identifier", 
                      "program", 
                      "platform", 
                      "instrument_type", 
                      "source_type", 
                      "display_name"
                  ])
df.sort_values(["program", "platform"])

Out[4]:

	identifier	program	platform	instrument_type	source_type	display_name
0	85	rainbow	athabasca	RGB ASI	ground	Rainbow ATHA
1	86	rainbow	fort simpson	RGB ASI	ground	Rainbow FSIM
3	88	rainbow	fort smith	RGB ASI	ground	Rainbow FSMI
2	87	rainbow	gillam	RGB ASI	ground	Rainbow GILL
7	98	rainbow	pinawa	RGB ASI	ground	Rainbow PINA
4	89	rainbow	rabbit lake	RGB ASI	ground	Rainbow RABB
8	99	rainbow	resolute bay	RGB ASI	ground	Rainbow RESU
5	90	rainbow	saskatoon	RGB ASI	ground	Rainbow SASK
9	100	rainbow	yellowknife	RGB ASI	ground	Rainbow YKNF
6	96	trex	fort smith	RGB ASI	ground	TREx RGB FSMI
12	103	trex	gillam	RGB ASI	ground	TREx RGB GILL
10	101	trex	lucky lake	RGB ASI	ground	TREx RGB LUCK
11	102	trex	pinawa	RGB ASI	ground	TREx RGB PINA
13	104	trex	rabbit lake	RGB ASI	ground	TREx RGB RABB

Get all Swarm data sources¶

In [5]:

# get data sources
sources = pyaurorax.sources.list(program="swarm")

# show as a pandas dataframe
sources_dict = [source.__dict__ for source in sources]
df = pd.DataFrame(sources_dict, 
                  columns=[
                      "identifier", 
                      "program", 
                      "platform", 
                      "instrument_type", 
                      "source_type", 
                      "display_name"
                  ])
df.sort_values(["program", "platform", "instrument_type"])

Out[5]:

	identifier	program	platform	instrument_type	source_type	display_name
0	3	swarm	swarma	footprint	leo	Swarm A
1	29	swarm	swarmb	footprint	leo	Swarm B
2	30	swarm	swarmc	footprint	leo	Swarm C

Get all low-earth orbit data sources (LEO)¶

In [6]:

# source type options are "leo", "heo", "ground", "lunar", or "event_list"
sources = pyaurorax.sources.list(source_type=pyaurorax.SOURCE_TYPE_LEO)

# show as a pandas dataframe
sources_dict = [source.__dict__ for source in sources]
df = pd.DataFrame(sources_dict, 
                  columns=[
                      "identifier", 
                      "program", 
                      "platform", 
                      "instrument_type", 
                      "source_type", 
                      "display_name"
                  ])
df.sort_values(["program", "platform"])

Out[6]:

	identifier	program	platform	instrument_type	source_type	display_name
8	265	dmsp	dmsp06	footprint	leo	DMSP-06
11	286	dmsp	dmsp07	footprint	leo	DMSP-07
6	255	dmsp	dmsp08	footprint	leo	DMSP-08
7	264	dmsp	dmsp09	footprint	leo	DMSP-09
12	287	dmsp	dmsp10	footprint	leo	DMSP-10
13	288	dmsp	dmsp11	footprint	leo	DMSP-11
9	284	dmsp	dmsp12	footprint	leo	DMSP-12
10	285	dmsp	dmsp13	footprint	leo	DMSP-13
14	289	dmsp	dmsp14	footprint	leo	DMSP-14
15	290	dmsp	dmsp15	footprint	leo	DMSP-15
16	291	dmsp	dmsp16	footprint	leo	DMSP-16
17	292	dmsp	dmsp17	footprint	leo	DMSP-17
4	63	dmsp	dmsp18	footprint	leo	DMSP-18
18	293	dmsp	dmsp19	footprint	leo	DMSP-19
3	32	epop	epop	footprint	leo	ePOP
19	326	noaa	noaa10	footprint	leo	NOAA-10
20	327	noaa	noaa12	footprint	leo	NOAA-12
21	328	noaa	noaa14	footprint	leo	NOAA-14
22	329	noaa	noaa15	footprint	leo	NOAA-15
23	330	noaa	noaa16	footprint	leo	NOAA-16
24	331	noaa	noaa17	footprint	leo	NOAA-17
25	332	noaa	noaa18	footprint	leo	NOAA-18
26	333	noaa	noaa19	footprint	leo	NOAA-19
27	334	noaa	noaa20	footprint	leo	NOAA-20
5	106	sampex	sampex	footprint	leo	SAMPEX
0	3	swarm	swarma	footprint	leo	Swarm A
1	29	swarm	swarmb	footprint	leo	Swarm B
2	30	swarm	swarmc	footprint	leo	Swarm C

Determine the identifier for a data source¶

In [7]:

data_sources = pyaurorax.sources.list(program="swarm",
                                      platform="swarma",
                                      instrument_type="footprint")
identifier = data_sources[0].identifier
print("Identifier: %d" % (identifier))

Identifier: 3

Get data source using identifier¶

In [8]:

# get data source
data_source = pyaurorax.sources.get_using_identifier(3)
pprint.pprint(data_source)

DataSource(identifier=3, program='swarm', platform='swarma', instrument_type='footprint', source_type='leo', display_name='Swarm A', metadata={}, owner='dchaddoc@ucalgary.ca', maintainers=[], ephemeris_metadata_schema=[{'field_name': 'nbt...}], data_product_metadata_schema=[])

Get data source information with different levels of information¶

You can retrieve different amounts of information about data sources. The default is pyaurorax.FORMAT_BASIC_INFO which provides some basic information, there are also format types for smaller or larger amounts of information.

In [9]:

# as little information as possible
data_sources = pyaurorax.sources.list(program="swarm",
                                      platform="swarma",
                                      instrument_type="footprint",
                                      format=pyaurorax.FORMAT_IDENTIFIER_ONLY)
print(data_sources[0])

DataSource(identifier=3)

In [11]:

# default information
data_source = pyaurorax.sources.get_using_identifier(3, format=pyaurorax.FORMAT_BASIC_INFO)
print(data_source)

DataSource(identifier=3, program='swarm', platform='swarma', instrument_type='footprint', source_type='leo', display_name='Swarm A')

In [12]:

# basic info, but with metadata
data_source = pyaurorax.sources.get_using_identifier(3, format=pyaurorax.FORMAT_BASIC_INFO_WITH_METADATA)
print(data_source)

DataSource(identifier=3, program='swarm', platform='swarma', instrument_type='footprint', source_type='leo', display_name='Swarm A', metadata={})

In [13]:

# all information
data_source = pyaurorax.sources.get_using_identifier(3, format=pyaurorax.FORMAT_FULL_RECORD)
print(data_source)

DataSource(identifier=3, program='swarm', platform='swarma', instrument_type='footprint', source_type='leo', display_name='Swarm A', metadata={}, owner='dchaddoc@ucalgary.ca', maintainers=[], ephemeris_metadata_schema=[{'field_name': 'nbt...}], data_product_metadata_schema=[])

Get statistics for a data source¶

In [14]:

# set parameters and get identifier
program = "themis"
platform = "themise"
instrument_type = "footprint"
data_sources = pyaurorax.sources.list(program=program,
                                      platform=platform,
                                      instrument_type=instrument_type)
print(data_sources[0])

DataSource(identifier=37, program='themis', platform='themise', instrument_type='footprint', source_type='heo', display_name='THEMIS-E', metadata={}, owner='dchaddoc@ucalgary.ca', maintainers=[], ephemeris_metadata_schema=[{'field_name': 'nbt...}], data_product_metadata_schema=[])

In [15]:

# get stats
stats = pyaurorax.sources.get_stats(identifier, format=pyaurorax.FORMAT_IDENTIFIER_ONLY)
print(stats)
print()
pprint.pprint(stats.__dict__)

DataSourceStatistics(data_source=DataSource(identifier=3), earliest_ephemeris_loaded=datetime.datetime(2013, 11, 26, 0, 0), latest_ephemeris_loaded=datetime.datetime(2021, 12, 10, 23, 59), ephemeris_count=4229280, earliest_data_product_loaded=None, latest_data_product_loaded=None, data_product_count=0)

{'data_product_count': 0,
 'data_source': DataSource(identifier=3),
 'earliest_data_product_loaded': None,
 'earliest_ephemeris_loaded': datetime.datetime(2013, 11, 26, 0, 0),
 'ephemeris_count': 4229280,
 'latest_data_product_loaded': None,
 'latest_ephemeris_loaded': datetime.datetime(2021, 12, 10, 23, 59)}

In [ ]: