def perform_download_coincidences(filename):
"""Load data from esd/api to h5 (filename)"""
filters = tables.Filters(complevel=1)
start = datetime.datetime(2016, 3, 10, 0, 0, 0)
end = datetime.datetime(2016, 3, 10, 0, 1, 0)
with tables.open_file(filename, 'w', filters=filters) as datafile:
esd.download_coincidences(datafile, stations=[501, 510], start=start, end=end, n=2, progress=False)
def perform_download_coincidences(filename):
"""Load data from esd/api to h5 (filename)"""
filters = tables.Filters(complevel=1)
start = datetime.datetime(2012, 1, 1, 0, 0, 0)
eind = datetime.datetime(2012, 1, 1, 0, 2, 0)
with tables.open_file(filename, 'w', filters=filters) as datafile:
esd.download_coincidences(datafile, cluster='Science Park',
start=start, end=eind, n=2, progress=False)
def perform_download_coincidences(filename):
"""Load data from esd/api to h5 (filename)"""
filters = tables.Filters(complevel=1)
start = datetime.datetime(2012, 1, 1, 0, 0, 0)
eind = datetime.datetime(2012, 1, 1, 0, 2, 0)
with tables.open_file(filename, 'w', filters=filters) as datafile:
esd.download_coincidences(datafile,
cluster='Science Park',
start=start,
end=eind,
n=2,
progress=False)
import datetime
import tables
from sapphire import esd
DATAFILE = 'data.h5'
STATIONS = [501, 503, 506]
START = datetime.datetime(2016, 1, 1)
END = datetime.datetime(2016, 1, 2)
if __name__ == '__main__':
if 'data' not in globals():
data = tables.open_file(DATAFILE, 'a')
if '/coincidences' not in data:
esd.download_coincidences(data, stations=STATIONS, start=START, end=END)
# In[43]:
# We have to open a datafile(but in our case we have to creat one):
data = tables.open_file('data_coincidences.h5', 'a')
# In[44]:
# Then downloading the coincidences.
# Here we specify the cluster 'Enschede' to select all stations in that cluster.
# We set n to 3, requiring that a coincidence has at least 3 events.
esd.download_coincidences(data, cluster='Enschede', start=start, end=end, n=3)
# In[45]:
# If you now look in the data file it will contain event tables for all stations with at least one event in a coincidence,and
# a coincidence table for the coincidence data.
# Just like when coincidences were searched manually:
print(data)
