# In an attempt to better predict the number of "tree debris" 311 calls in
# Chicago, this experiment incorporates data from local weather stations.
from datetime import datetime
from menorah import Menorah
sources = [
["chicago-311", "Tree Debris", "aggregate=1 day"],
["chicago-beach-weather", "Foster Weather Station", "humidity"],
["chicago-beach-weather", "Foster Weather Station", "interval_rain"],
["chicago-beach-water-quality", "Osterman Beach", "wave_height"],
]
menorah = Menorah(
sources,
"work/example5-multifield-aggregated",
since=datetime(2015, 5, 20)
)
menorah.swarm(swarmParams={"swarmSize":"large"})
menorah.runModel(plot=True)
# Gets aggregated data for Portland OR 911 calls and attempts to predict the # number of calls every 15 minutes. from datetime import datetime from menorah import Menorah sources = [ ["portland-911", "portland-911", "aggregate=15 minutes"], ] menorah = Menorah(sources, "work/example3-aggregated", since=datetime(2015, 7, 10)) menorah.swarm() menorah.runModel(plot=True)
# Tree Debris vs weather. sources = [ ["chicago-311", "Tree Debris", "aggregate=1 day"], ["chicago-beach-weather", "Foster Weather Station", "humidity"], ["chicago-beach-weather", "Foster Weather Station", "interval_rain"], ["chicago-beach-weather", "Foster Weather Station", "barometric_pressure"], ["chicago-beach-weather", "Foster Weather Station", "wind_speed"], ["chicago-beach-weather", "Foster Weather Station", "maximum_wind_speed"], ["chicago-beach-weather", "Foster Weather Station", "air_temperature"], ["chicago-beach-water-quality", "Osterman Beach", "wave_height"], ] menorah = Menorah( sources, "work/debris", since=datetime(2015, 5, 20) ) menorah.swarm() menorah.runModel() # Graffiti Removal vs weather. sources = [ ["chicago-311", "Graffiti Removal", "aggregate=1 day"], ["chicago-beach-weather", "Foster Weather Station", "humidity"], ["chicago-beach-weather", "Foster Weather Station", "interval_rain"], ["chicago-beach-weather", "Foster Weather Station", "barometric_pressure"], ["chicago-beach-weather", "Foster Weather Station", "wind_speed"], ["chicago-beach-weather", "Foster Weather Station", "maximum_wind_speed"],
# This example shows how to stream River View data into a NuPIC swarm in an # attempt to prediction energy consumption in Texas. Once the swarm is complete, # the resulting model parameters are used for running the data once again # through a newly created NuPIC model. from menorah import Menorah dataIds = [ # http://data.numenta.org/ercot-demand/system_wide_demand/data.html ["ercot-demand", "system_wide_demand", "Demand"], ] menorah = Menorah(dataIds, "work/example1-one-field") # menorah.swarm() menorah.runModel(plot=True) # Find your predictions in "work/example1-one-field/predictions.csv"
# Just an example of how to fetch River View data into a CSV so you can process # it yourself. from menorah import Menorah sources = [ ["mn-traffic-sensors", "T4013", "speed"], ["mn-traffic-sensors", "1036", "speed"], ["mn-traffic-sensors", "1187", "speed"], ] menorah = Menorah(sources, "work/example4-data-only") menorah.populateCsv() # Find CSV at "work/example4-data-only/data.csv".
