def handle(self, *args, **options):
if len(args)==1 and "-h"==args[0]:
print "Usage: test_locations"
sys.exit(0)
tstart = time.time()
run = DimRun.objects.get(id = 1509)
number = len(run.dimexecution_set.all())
print "%s executions to go" % number
adapter = EMOD_Adapter("admin")
i = 0
for execution in run.dimexecution_set.all():
adapter.fetch_data(execution.id, channel_name="Daily EIR")
i += 1
print "%s / %s (%s)" % (i, number, time.time() - tstart)
tend = time.time()
print "timing: fetch_data from run 1509 took %f sec" % (tend-tstart)
def viewtastic_fetch_data(request):
"""
For a given execution dictionary, the fetch_data function returns a chart json for insertion into
a highcharts object.
This function also returns the channel id for asynchronous data flow and identification reasons.
:param request: needed for providing a validated username and providing the execution dictionary via the
packaged GET data.
:type request: ajax request object
:return: a dictionary containing the channel id and the associated chart for the selected channel
"""
temp_chart_json = {}
temp_chart_json.clear()
adapter = EMOD_Adapter(user_name=request.user.username) # get_appropriate_model_adapter(request)
dict_list = []
for key in request.POST:
dict_list.append(json.loads(key))
# if there weren't any sweeps done, then the execution id needs to be passed to the function.
the_params = None
try:
the_params = dict_list[0]['parameters']
# Turn the dict of lists into a list of dicts, ordered by the mod order from when the fetch_keys
# was called
the_param_list = []
for sweep_object in the_params:
the_params[sweep_object]['name'] = sweep_object
the_param_list.append(the_params[sweep_object])
final_param_list = []
for param in sorted(the_param_list, key=lambda sweep: sweep['mod_order']):
final_param_list.append({param['name']: param['values']})
except:
the_execid = dict_list[0]['execution']
try:
chart_type = dict_list[0]['chart_type']
except:
chart_type = 'time_series'
try:
the_aggregation = dict_list[0]['aggregation']
except:
the_aggregation = 'daily'
try:
the_run = int(dict_list[0]['run_id'])
the_channel = int(dict_list[0]['channel_id'])
except:
# Requesting Simulation data
sim_id = int(dict_list[0]['run_id'][1:]) # Remove first 's' character
the_channel = dict_list[0]['channel_id']
start_date = datetime.datetime(1995, 1, 1)
insetchartfile = SimulationOutputFile.objects.get(simulation=sim_id, name="InsetChart.json")
data = json.loads(insetchartfile.get_contents())["Channels"][the_channel]["Data"]
data = as_chart(data, start_date)
else:
# if the parameters aren't available then try getting the data via the execution id
if the_params is not None:
if the_aggregation == 'yearly_sum':
data = adapter.fetch_data(group_by=True,
exec_dict=final_param_list,
run_id=the_run,
channel_id=the_channel,
as_chart=True, as_highstock=True)
else:
data = adapter.fetch_data(exec_dict=final_param_list,
run_id=the_run,
channel_id=the_channel,
as_chart=True, as_highstock=True)
else:
if the_aggregation == 'yearly_sum':
data = adapter.fetch_data(group_by=True,
execution_id=the_execid,
run_id=the_run,
channel_id=the_channel,
as_chart=True, as_highstock=True)
else:
data = adapter.fetch_data(execution_id=the_execid,
run_id=the_run,
channel_id=the_channel,
as_chart=True, as_highstock=True)
temp_chart_json = json.loads(data)
temp_chart_json['chart']['height'] = 335 + (15 * len(temp_chart_json['series']))
temp_chart_json['chart']['width'] = 500
temp_chart_json['rangeSelector'] = {'enabled': False}
real_return_json = dict(channel_id=the_channel,
chart_JSON=temp_chart_json,
chart_type=chart_type,
aggregation=the_aggregation)
return HttpResponse(content=json.dumps(real_return_json), content_type="application/json")
