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Generalize calculate_isochrone to calculate_isoline

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This commit is contained in:
Rafa de la Torre 2016-07-06 18:43:09 +02:00
parent 54221fa671
commit 523eda2cc7
1 changed files with 34 additions and 13 deletions
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47
server/lib/python/cartodb_services/cartodb_services/mapzen/isolines.py
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@ -27,25 +27,46 @@ class MapzenIsolines:
Returns:
Array of {lon: x, lat: y} as a representation of the isoline
"""
def calculate_isochrone(self, origin, transport_mode, isorange):
def calculate_isochrone(self, origin, transport_mode, time_range):
if transport_mode == 'walk':
max_speed = 3.3333333 # In m/s, assuming 12km/h walking speed
costing_model = 'pedestrian'
elif transport_mode == 'car':
max_speed = 41.67 # In m/s, assuming 140km/h max speed
costing_model = 'auto'
else:
raise NotImplementedError('car and walk are the only supported modes for the moment')
upper_rmax = max_speed * time_range # an upper bound for the radius
return self.calculate_isoline(origin, costing_model, time_range, upper_rmax, 'time')
"""Get an isoline using mapzen API.
The implementation tries to sick close to the SQL API:
cdb_isochrone(source geometry, mode text, range integer[], [options text[]]) -> SETOF isoline
But this calculates just one isoline.
Args:
origin dict containing {lat: y, lon: x}
costing_model string "auto" or "pedestrian"
isorange int Range of the isoline in seconds
upper_rmax float An upper bound for the binary search
cost_variable string Variable to optimize "time" or "distance"
Returns:
Array of {lon: x, lat: y} as a representation of the isoline
"""
def calculate_isoline(self, origin, costing_model, isorange, upper_rmax, cost_variable):
# NOTE: not for production
#logging.basicConfig(level=logging.DEBUG, filename='/tmp/isolines.log')
#logging.basicConfig(level=logging.DEBUG)
logging.debug('origin = %s' % origin)
logging.debug('transport_mode = %s' % transport_mode)
logging.debug('costing_model = %s' % costing_model)
logging.debug('isorange = %d' % isorange)
if transport_mode == 'walk':
upper_rmax = 3.3333333 * isorange # an upper bound for the radius, assuming 12km/h walking speed
costing_model = 'pedestrian'
elif transport_mode == 'car':
upper_rmax = 41.67 * isorange # assuming 140km/h max speed
costing_model = 'auto'
else:
raise NotImplementedError('car and walk are the only supported modes for the moment')
# Formally, a solution is an array of {angle, radius, lat, lon, cost} with cardinality NUMBER_OF_ANGLES
# we're looking for a solution in which abs(cost - isorange) / isorange <= TOLERANCE
@ -62,7 +83,7 @@ class MapzenIsolines:
# Just assume isorange and stop the calculations there
response = self._matrix_client.one_to_many([origin] + location_estimates, costing_model)
costs = [(c['time'] or isorange) for c in response['one_to_many'][0][1:]]
costs = [(c[cost_variable] or isorange) for c in response['one_to_many'][0][1:]]
logging.debug('i = %d, costs = %s' % (i, costs))