def get_layers():
data = get.get_collection()
layers = {'layers': list()}
for row in data['pinpoints']:
layers['layers'].append(row['layer'])
layers['layers'] = set(layers['layers'])
return prepare.data_to_json(layers)
def get_layer_by_time(layer_name, datestart, timestart, datestop, timestop):
start = datestart + " " + timestart
stop = datestop + " " + timestop
json_data = get.get_layer_by_timestamp(str(layer_name), str(start),
str(stop))
geojson = {'type': 'FeatureCollection', 'features': list()}
for point in json_data['pinpoints']:
geojson['features'].append(prepare.json_to_geojson(point))
return prepare.data_to_json(geojson)
def anomaly():
data = request.get_json()['input']
output = ml.anomaly_detection(data).tolist()
return prepare.data_to_json({'output': output})
def forecasting():
data = request.get_json()['input']
output = ml.forecast(data, int(0.1 * len(data)))
return prepare.data_to_json({'output': output})
def get_layer_by_location(layer_name, latmin, latmax, longmin, longmax):
return prepare.data_to_json(
get.get_layer_by_location(str(layer_name),
float(latmin), float(latmax), float(longmin),
float(longmax)))
def get_layer(layer_name):
return prepare.data_to_json(get.get_layer(str(layer_name)))
def get_collections():
return prepare.data_to_json(get.get_collection())