# note that the keywords are the same as in IDL mms_load_fgm(probe='4', data_rate='brst', trange=['2015-10-16/13:06', '2015-10-16/13:07'], time_clip=True) # find which variables were loaded from pytplot import tplot_names tplot_names() from pyspedas.mms import mms_load_edp # load some burst mode electric field data mms_load_edp(probe='4', data_rate='brst', trange=['2015-10-16/13:06', '2015-10-16/13:07'], time_clip=True) from pyspedas import tnames # the tnames function supports filtering with wild cards, e.g., # to find the E-field variables: dce_vars = tnames('*_edp_dce_*') # trange also accepts datetime objects # note: be aware of potential time zone issues from pyspedas.mms import mms_load_fpi from datetime import datetime from datetime import timezone as tz start_time = datetime(year=2015,
def test_load_brst_data(self): data = mms_load_edp(data_rate='brst', trange=['2015-10-16/13:06', '2015-10-16/13:10']) self.assertTrue(data_exists('mms1_edp_dce_gse_brst_l2'))
def test_load_spdf_data(self): data = mms_load_edp(trange=['2015-10-16', '2015-10-16/01:00'], spdf=True) self.assertTrue(data_exists('mms1_edp_dce_gse_fast_l2'))
def test_load_suffix(self): data = mms_load_edp(trange=['2015-10-16', '2015-10-16/01:00'], suffix='_test') self.assertTrue(data_exists('mms1_edp_dce_gse_fast_l2'))
def test_load_hfesp_data(self): data = mms_load_edp(trange=['2015-10-16', '2015-10-16/01:00'], datatype='hfesp', data_rate='srvy') self.assertTrue(data_exists('mms1_edp_hfesp_srvy_l2'))