Some missions, for example New Horizons, store very long time intervals in a single data CDF. When downloading via cda_download(), we should have a time_clip option that trims the returned data down to the specific times requested by the user.
Example, again from Nick Gross on Helionauts:
import pyspedas
from pytplot import tplot
cdaweb_obj = pyspedas.CDAWeb()
mission_list = ['New Horizons']
#instrument_list = ['Plasma and Solar Wind']
instrument_list = ['Particles (space)']
dataset_list = cdaweb_obj.get_datasets(mission_list, instrument_list)
print(dataset_list)
dataset = 'NEW_HORIZONS_SWAP_VALIDSUM (2008-10-10 to 2023-07-31)'
start_time = '2009-10-10 00:00:00'
end_time = '2009-11-10 00:00:00'
# Get the URLs for the available data in this time range
urllist = cdaweb_obj.get_filenames([dataset],start_time, end_time)
cdaweb_obj.cda_download(urllist,"cdaweb/",prefix='nh_')
tplot('nh_n')
This actually plots data from 2008 through 2023! It's all in a single CDF.
Some missions, for example New Horizons, store very long time intervals in a single data CDF. When downloading via cda_download(), we should have a time_clip option that trims the returned data down to the specific times requested by the user.
Example, again from Nick Gross on Helionauts:
This actually plots data from 2008 through 2023! It's all in a single CDF.