def station_output_auto():
"""
Obtain predicted average daily rides at the best possible location.
Add the new station to the station database. Regenerate the predicted
average daily rides matrix.
"""
# get the user id number
uid = userisactive_output()
# google geo code API plugin to translate between address and lat/long
googlegeo = makegeo()
# get the user's directory
growdir = getgrowdir(uid)
# run the model on the best possible location
prediction = gridpredict.autoinput(growdir)
# get the list of stations, daily rides, and ranking of the new station
stationslistdict, riderate, ranking = makeoutput(prediction, googlegeo)
return render_template("output.html", riderate=riderate, ranking=ranking,
stations=stationslistdict)
def station_output_auto():
"""
Obtain predicted average daily rides at the best possible location.
Add the new station to the station database. Regenerate the predicted
average daily rides matrix.
"""
# get the user id number
uid = userisactive_output()
# google geo code API plugin to translate between address and lat/long
googlegeo = makegeo()
# get the user's directory
growdir = getgrowdir(uid)
# run the model on the best possible location
prediction = gridpredict.autoinput(growdir)
# get the list of stations, daily rides, and ranking of the new station
stationslistdict, riderate, ranking = makeoutput(prediction, googlegeo)
return render_template("output.html",
riderate=riderate,
ranking=ranking,
stations=stationslistdict)
import gridpredict basedir = '../Data/Boston/' growdir = '../Data/Boston/growing/' gridpredict.resetiteration(basedir, growdir) test1 = gridpredict.autoinput(growdir) print(test1) import pdb; pdb.set_trace() test1 = gridpredict.autoinput(growdir) print(test1) import pdb; pdb.set_trace() test1 = gridpredict.autoinput(growdir) print(test1) test1 = gridpredict.autoinput(growdir) print(test1) test1 = gridpredict.autoinput(growdir) print(test1) test1 = gridpredict.autoinput(growdir) print(test1) test1 = gridpredict.autoinput(growdir) print(test1) # open street map for river outline # data thief
import gridpredict basedir = '../Data/Boston/' growdir = '../Data/Boston/growing/' gridpredict.resetiteration(basedir, growdir) test1 = gridpredict.autoinput(growdir) print(test1) import pdb pdb.set_trace() test1 = gridpredict.autoinput(growdir) print(test1) import pdb pdb.set_trace() test1 = gridpredict.autoinput(growdir) print(test1) test1 = gridpredict.autoinput(growdir) print(test1) test1 = gridpredict.autoinput(growdir) print(test1) test1 = gridpredict.autoinput(growdir) print(test1) test1 = gridpredict.autoinput(growdir) print(test1) # open street map for river outline # data thief
