def _filter_res(filename):
"""
Reads files containing results of either algorithm1 or algorithm2,
and finds the results that are significant according to the
following criteria:
* waiting:
- Interval is contained in the non-negative part of the real axis.
- Interval is wider than 90 seconds.
- More than 50 points are in the solution region defined as
{(x,y): s<=x<=e, x-s <= y <= x-s+120}.
* blocking:
- Interval is contained in the non-negative part of the real axis.
- Interval is wider than 120 seconds.
- More than 50 points are in the solution region defined as A U B, where
A = {(x,y): s<=x<=e, x-s <= y <= x-s+120}.
B = {(x,y): e<=x<=e+120, max(0, x-e-120) <= y <= min(x-e, e-s)}
"""
algtype = filename[18:-4]
results = csv.reader(open(filename), delimiter=',')
firstrow = True
outfile = open(filename[:-4] + '_sig.csv', 'w')
reswriter = csv.writer(outfile, delimiter=',')
for row in results:
if firstrow:
firstrow = False
reswriter.writerow(row)
else:
if int(float(row[5])) > 0:
if int(float(row[6])) > int(float(row[5])):
if algtype == 'waiting':
data = get_matching_delay(row[1], row[0],
row[3], row[2])
#Check if solution region has more than 50 points
if delaycounter(data[0], data[1], row[5:], 120) > 50:
if int(float(row[6])) - int(float(row[5])) > 90:
#save
reswriter.writerow(row)
else:
#blocking
data = get_matching_delay(row[1], row[0],
row[3], row[2])
#Check if solution region has more than 50 points
if delaycounter(data[0], data[1], row[5:], 120) > 50:
if int(float(row[6])) - int(float(row[5])) > 120:
#save
reswriter.writerow(row)
outfile.close()
from plot_trains import scatter_trains
from get_matching_delay import get_matching_delay
from train_algos import algorithm1_mod, algorithm1
from delaycounter import delaycounter
from new_alg1mod import algorithm1_mod2
delayer, victim = get_matching_delay('1619','45961', False, True)
import csv
algres = (90, -842, -72)
print delaycounter(delayer, victim, (algres[1], algres[2]),
algtype = 'blocking')
scatter_trains(delayer, victim, algres, waiting = False, show = True)
