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())