streams = opts.streams
else:
data = input
# Only consider these locations
if opts.areas != "all":
print "Matching areas", opts.areas
data = data[match_areas(data, opts.areas)]
matched = opts.areas
elif opts.tracts != "all":
print "Matching tracts", opts.tracts
data = data[match_tracts(data, opts.tracts)]
matched = opts.tracts
with mytimer:
R, Sopt, Dopt, iters = search(data, np.array(streams))
Xn = np.sum(match_streams(data,Dopt) * match_tracts(data,Sopt))
Yn = np.sum(match_streams(data,[opts.predict]) * match_tracts(data,Sopt))
print "\n\n-------------------- In area", matched, "with streams", streams
print "Correlation = %.05f"%R
print "for predicting", opts.predict, "with these leading indicators:", ', '.join(Dopt)
print "# of events in X:", Xn
print "# of events in Y:", Yn
f = open(opts.output,"w")
out = csv.writer(f)
out.writerow("predict streams region R Dopt Sopt Xn Yn elapsed".split())
out.writerow([opts.predict, streams, matched, R, Dopt, Sopt, Xn, Yn, mytimer.elapsed])
print "search complete, output written to %s"%(opts.output)
print "precalculating centers of all tracts (this may take a little while)"
with mytimer:
tract_centers = calculate_tract_centers(input)
print "completed in %d seconds"%mytimer.elapsed
f = open(opts.output,"w")
out = csv.writer(f)
out.writerow("predict tract R R_a R_b Dopt Sopt Xn Yn elapsed".split())
n_tracts = len(np.unique(input['tract'])) * 1.0
for i, tract in enumerate(np.unique(input['tract'])):
data = input[match_tracts(input, nearby_tracts(tract_centers[tract],input,RADIUS))]
with mytimer:
R_a, Sopt, Dopt, iters = search(data, np.array(streams), daterange=TIME_PERIOD_A)
X = match_streams(data,Dopt) * match_tracts(data,Sopt)
Y = match_streams(data,[opts.predict]) * match_tracts(data,Sopt)
Xn = np.sum(X)
Yn = np.sum(Y)
X_ts = time_series(data[X], daterange=TIME_PERIOD_B)
Y_ts = time_series(data[Y],lag=Y_LAG, daterange=TIME_PERIOD_B)
R_b = X_ts.corr(Y_ts)
X_ts = time_series(data[X], daterange=daterange)
Y_ts = time_series(data[Y],lag=Y_LAG, daterange=daterange)
R = X_ts.corr(Y_ts)
print "\n\n-------------------- TRACT", tract
print "Correlation = %.05f (%.05f for first half of year, %.05f for second half of year)"%(R,R_a,R_b)
print "for predicting", opts.predict, "with these leading indicators:", ', '.join(Dopt)