Getting started¶
Installation¶
Starting from version 1.2 AI.CDAS officially supports only Python 3, so make sure that you have a working installation of it.
Assuming the above requirement is satisfied install the package with Python package manager:
$ pip install ai.cdas
Known issues¶
NASA CDAS REST API endpoint currently does not support IPv6 addressing. However, newer linux distros (for example, Ubuntu 16.04) are set up to prefer IPv6 addressing over IPv4 by default. This may result in unnecessary delays in communication with the server. If you experience the issue it might be that this is the case with your system. Here is how it can be cured in Ubuntu 16.04:
$ sudoedit /etc/gai.conf
# Uncomment the line
# precedence ::ffff:0:0/96 100
Now you machine will attempt IPv4 prior to IPv6. For other distros refer to respective docs.
Examples¶
Example 1: Retrieving observatory groups and associated instruments which measure plasma and solar wind:
from ai import cdas
import json # for pretty output
obsGroupsAndInstruments = cdas.get_observatory_groups_and_instruments(
'istp_public',
instrumentType='Plasma and Solar Wind'
)
print(json.dumps(obsGroupsAndInstruments, indent=4))
Example 2: Getting STEREO-A datasets using regular expressions for dataset id and label:
from ai import cdas
import json # for pretty output
datasets = cdas.get_datasets(
'istp_public',
idPattern='STA.*',
labelPattern='.*STEREO.*'
)
print(json.dumps(datasets, indent=4))
Example 3: Fetching a list of variables in one of STEREO datasets:
from ai import cdas
import json # for pretty output
variables = cdas.get_variables('istp_public', 'STA_L1_MAGB_RTN')
print(json.dumps(variables, indent=4))
Example 4: This snippet of code gets magnetic field data from STEREO-A spacecraft for one hour of 01.01.2010 and plots it (requires matplotlib):
from ai import cdas
from datetime import datetime
from matplotlib import pyplot as plt
data = cdas.get_data(
'sp_phys',
'STA_L1_MAG_RTN',
datetime(2010, 1, 1),
datetime(2010, 1, 1, 0, 59, 59),
['BFIELD']
)
plt.plot(data['EPOCH'], data['BTOTAL'])
plt.show()
Example 5: This snippet of code gets magnetic field data from STEREO-A spacecraft for one hour of 01.01.2010 and plots it (requires matplotlib). The data are downloaded in CDF format in this case. CDF format is binary and results in a much smaller filesize and hence faster downloads. In order for this to work you have to have NASA CDF library on your machine and spacepy installed afterwards:
from ai import cdas
from datetime import datetime
from matplotlib import pyplot as plt
data = cdas.get_data(
'sp_phys',
'STA_L1_MAG_RTN',
datetime(2010, 1, 1),
datetime(2010, 1, 1, 0, 59, 59),
['BFIELD'],
cdf=True # download data in CDF format
)
# Note that variables identifiers are different than in the previous
# example. It often the case with CDAS data. You should check the
# variables names by printing out `data` dictionary.
plt.plot(data['Epoch'], data['BFIELD'][:, 3])
plt.show()
Example 6: This snippet of code gets magnetic field data from STEREO-A spacecraft for 01.01.2010 and saves it to cache directory. The next time the same data is requested it is taken from cache without downloading:
import os
from ai import cdas
from datetime import datetime
# For the sake of example we are using your current working
# directory as a cache directory
cache_dir = os.getcwd()
cdas.set_cache(True, cache_dir)
# this data is downloaded from CDAS
data = cdas.get_data(
'sp_phys',
'STA_L1_MAG_RTN',
datetime(2010, 1, 1),
datetime(2010, 1, 1, 0, 59, 59),
['BFIELD']
)
# this data is taken from cache
data = cdas.get_data(
'sp_phys',
'STA_L1_MAG_RTN',
datetime(2010, 1, 1),
datetime(2010, 1, 1, 0, 59, 59),
['BFIELD']
)