def get_avalanche_index(from_date, to_date, region_ids=None, observer_ids=None):
'''
:param from_date:
:param to_date:
:param region_ids:
:param observer_ids:
:return:
'''
# get all data
avalanche_activities = go.get_avalanche_activity(from_date, to_date, region_ids=region_ids, observer_ids=observer_ids)
avalanche_activities_2 = go.get_avalanche_activity_2(from_date, to_date, region_ids=region_ids, observer_ids=observer_ids)
avalanches = go.get_avalanche(from_date, to_date, region_ids=region_ids, observer_ids=observer_ids)
danger_signs = go.get_danger_sign(from_date, to_date, region_ids=region_ids, observer_ids=observer_ids)
# get index definition
index_definition = rf.read_configuration_file('{0}aval_dl_order_of_size_and_num.csv'.format(env.input_folder), AvalancheIndex)
avalanche_indexes = []
for aa in avalanche_activities:
ai = AvalancheIndex()
ai.set_num_and_size_and_index(aa.EstimatedNumName, aa.DestructiveSizeName, index_definition)
ai.set_date_region_observation(aa.DtAvalancheTime, aa.ForecastRegionName, aa)
avalanche_indexes.append(ai)
for aa in avalanche_activities_2:
ai = AvalancheIndex()
ai.set_num_and_size_and_index(aa.EstimatedNumName, aa.DestructiveSizeName, index_definition)
# Activity date is the avarage of DtStart and DtEnd
activity_date = aa.DtStart+(aa.DtEnd-aa.DtStart)/2
ai.set_date_region_observation(activity_date.date(), aa.ForecastRegionName, aa)
avalanche_indexes.append(ai)
for aa in avalanches:
ai = AvalancheIndex()
# Make sure size is not None
ai.set_num_and_size_and_index("Ett (1)", aa.DestructiveSizeName, index_definition)
ai.set_date_region_observation(aa.DtAvalancheTime, aa.ForecastRegionName, aa)
avalanche_indexes.append(ai)
for ds in danger_signs:
ai = AvalancheIndex()
if 'Ferske skred' in ds.DangerSignName:
ai.set_avalanches_as_dangersign()
elif 'Ingen faretegn observert' in ds.DangerSignName:
ai.set_no_avalanche_activity()
else:
continue
ai.set_date_region_observation(ds.DtObsTime, ds.ForecastRegionName, ds)
avalanche_indexes.append(ai)
return avalanche_indexes
def pickle_M3(data_set, config_file_name, pickle_m3_file_name):
"""Makes a list of elements matching the m3 matrix. Uses a configuration file as for the matrix elements and
runs through all warnings adding occurances and danger level used at each combination of the matrix.
:param data_set:
:param pickle_m3_file_name:
:return:
"""
config_file_name = '{0}{1}'.format(env.input_folder, config_file_name)
m3_elements = rf.read_configuration_file(config_file_name, M3Element)
# read out the data_set and add to M3Elements
for i in range(0, len(data_set['level']['values']), 1):
size = data_set['size']['values'][i]
if size is None:
size = '0 - Ikke gitt'
print 'runmatrix.py -> picke_M3 -> Warning: Encountered occurrence where avalanche size is None. Set to 0 - Ikke gitt.'
trigger = data_set['trigger']['values'][i]
probability = data_set['probability']['values'][i]
distribution = data_set['distribution']['values'][i]
for e in m3_elements:
m3_size = e.avalanche_size
m3_trigger = e.trigger
m3_probability = e.probability
m3_distribution = e.distribution
if size in m3_size and trigger in m3_trigger and probability in m3_probability and distribution in m3_distribution:
level = data_set['level']['values'][i]
e.add_danger_level(level)
# count all levels added (for debug only) for control and make some stats
count = 0
for e in m3_elements:
count += len(e.danger_level_list)
e.set_level_average()
e.set_level_standard_dev()
mp.pickle_anything(m3_elements, pickle_m3_file_name)
def step_2_find_most_valued(date_region):
# most valued obs could change name to observation with highest index
index = rf.read_configuration_file('{0}aval_dl_order_of_size_and_num.csv'.format(env.input_folder), IndexOfSizeAndNumber)
for d in date_region:
for aa in d.avalanche_activity:
max_index = 0
for i in index:
if i.estimated_num in aa.EstimatedNumName and i.destructive_size in aa.DestructiveSizeName:
max_index = i.index
if d.highest_value < max_index:
d.highest_value = max_index
d.most_valued_observation = aa
for a in d.avalanche:
max_index = 0
for i in index:
if i.estimated_num in 'Ett (1)' and i.destructive_size in a.DestructiveSizeName:
max_index = i.index
if d.highest_value < max_index:
d.highest_value = max_index
d.most_valued_observation = a
for ds in d.danger_sign:
if 'Ferske skred' in ds.DangerSignName:
if d.highest_value < 2:
d.highest_value = 2
d.most_valued_observation = ds
if 'Ingen faretegn observert' in ds.DangerSignName:
if d.highest_value < 1:
d.highest_value = 1
d.most_valued_observation = ds
return date_region
from_date = dt.date(2014, 11, 30)
to_date = dt.date(2015, 6, 1)
#to_date = dt.date.today()
### get and make the data set
# date_region, forecasted_dangers = step_1_make_data_set(region_id, from_date, to_date)
# mp.pickle_anything([date_region, forecasted_dangers], '{0}runforavalancheactivity_step_1.pickle'.format(env.local_storage))
#
# ## Find the observaton of highest value pr region pr date
# date_region, forecasted_dangers = mp.unpickle_anything('{0}runforavalancheactivity_step_1.pickle'.format(env.local_storage))
# date_region = step_2_find_most_valued(date_region)
# mp.pickle_anything([date_region, forecasted_dangers], '{0}runforavalancheactivity_step_2.pickle'.format(env.local_storage))
# #
## ready to add to count elements
date_region, forecasted_dangers = mp.unpickle_anything('{0}runforavalancheactivity_step_2.pickle'.format(env.local_storage))
elements = rf.read_configuration_file('{0}aval_dl_configuration.csv'.format(env.input_folder), ActivityAndDanger)
elements = step_3_count_occurances(date_region, elements)
mp.pickle_anything([date_region, forecasted_dangers, elements], '{0}runforavalancheactivity_step_3.pickle'.format(env.local_storage))
### ready to plot?
date_region, forecasted_dangers, elements = mp.unpickle_anything('{0}runforavalancheactivity_step_3.pickle'.format(env.local_storage))
step_4_plot(date_region, forecasted_dangers, elements, '{0}Avalanches and dangers {1} to {2}'.format(env.plot_folder, from_date, to_date))
total_a = 0
total_aa = 0
total_ds = 0
for d in date_region:
total_a += len(d.avalanche)
total_aa += len(d.avalanche_activity)
total_ds += len(d.danger_sign)
