def send_extract(self, query):
f = StringIO()
query = urllib.unquote(query)
content = Vlist()
for (i,sub) in enumerate(query.split(',')):
r = sub.split('-')
if len(r)==1:
if sub.strip()[0].lower()=='t':
sub=sub.strip()[1:]
content.append(Path(test_data.extract(int(sub)), 'T%s<br>'%sub))
else:
content.append(Path(train_data.extract(int(sub)), '%s<br>'%sub))
elif len(r)==2:
test = False
if r[0].strip()[0].lower()=='t':
test = True
r[0]=r[0].strip()[1:]
if r[1].strip()[0].lower()=='t':
r[1]=r[1].strip()[1:]
for i in xrange(int(r[0]), int(r[1])+1):
if test:
content.append(Path(test_data.extract(i), 'T%d<br>'%i))
else:
content.append(Path(train_data.extract(i), '%d<br>'%i))
elif len(r)>2:
self.send_error(404, 'File not found')
return None
content.write(f)
length = f.tell()
f.seek(0)
self.send_response(200)
encoding = sys.getfilesystemencoding()
self.send_header("Content-type", "text/html; charset=%s" % encoding)
self.send_header("Content-Length", str(length))
self.end_headers()
return f
#!/usr/bin/env python
from data.hdf5 import taxi_it
from visualizer import Vlist, Point
if __name__ == '__main__':
points = Vlist(heatmap=True)
for line in taxi_it('test'):
for (lat, lon) in zip(line['latitude'], line['longitude']):
points.append(Point(lat, lon))
points.save('test positions')
def send_extract(self, query):
f = StringIO()
query = urllib.unquote(query)
content = Vlist()
for (i, sub) in enumerate(query.split(',')):
r = sub.split('-')
if len(r) == 1:
if sub.strip()[0].lower() == 't':
sub = sub.strip()[1:]
content.append(
Path(test_data.extract(int(sub)), 'T%s<br>' % sub))
else:
content.append(
Path(train_data.extract(int(sub)), '%s<br>' % sub))
elif len(r) == 2:
test = False
if r[0].strip()[0].lower() == 't':
test = True
r[0] = r[0].strip()[1:]
if r[1].strip()[0].lower() == 't':
r[1] = r[1].strip()[1:]
for i in xrange(int(r[0]), int(r[1]) + 1):
if test:
content.append(
Path(test_data.extract(i), 'T%d<br>' % i))
else:
content.append(
Path(train_data.extract(i), '%d<br>' % i))
elif len(r) > 2:
self.send_error(404, 'File not found')
return None
content.write(f)
length = f.tell()
f.seek(0)
self.send_response(200)
encoding = sys.getfilesystemencoding()
self.send_header("Content-type", "text/html; charset=%s" % encoding)
self.send_header("Content-Length", str(length))
self.end_headers()
return f
#!/usr/bin/env python
from data.hdf5 import taxi_it
from visualizer import Vlist, Point
if __name__ == '__main__':
it = taxi_it('stands')
next(it)
points = Vlist()
for (i, line) in enumerate(it):
points.append(
Point(line['stands_latitude'], line['stands_longitude'],
'Stand (%d): %s' % (i + 1, line['stands_name'])))
points.save('stands')
#!/usr/bin/env python
from data.hdf5 import taxi_it
from visualizer import Vlist, Point
if __name__ == '__main__':
points = Vlist(heatmap=True)
for line in taxi_it('test'):
for (lat, lon) in zip(line['latitude'], line['longitude']):
points.append(Point(lat, lon))
points.save('test positions')
#!/usr/bin/env python
from data.hdf5 import taxi_it
from visualizer import Vlist, Point
if __name__ == '__main__':
it = taxi_it('stands')
next(it) # Ignore the "no stand" entry
points = Vlist()
for (i, line) in enumerate(it):
points.append(Point(line['stands_latitude'], line['stands_longitude'], 'Stand (%d): %s' % (i+1, line['stands_name'])))
points.save('stands')
#!/usr/bin/env python
from data.hdf5 import taxi_it
from visualizer import Vlist, Point
_sample_size = 5000
if __name__ == '__main__':
points = Vlist(cluster=True)
for line in taxi_it('train'):
if len(line['latitude']) > 0:
points.append(Point(line['latitude'][-1], line['longitude'][-1]))
if len(points) >= _sample_size:
break
points.save('destinations (cluster)')
points.cluster = False
points.heatmap = True
points.save('destinations (heatmap)')
#!/usr/bin/env python
from data.hdf5 import taxi_it
from visualizer import Vlist, Point
_sample_size = 5000
if __name__ == '__main__':
points = Vlist(cluster=True)
for line in taxi_it('train'):
if len(line['latitude'])>0:
points.append(Point(line['latitude'][-1], line['longitude'][-1]))
if len(points) >= _sample_size:
break
points.save('destinations (cluster)')
points.cluster = False
points.heatmap = True
points.save('destinations (heatmap)')