I am trying to use the aggregate function in pandana with impedance as time.
Firstly, I passed time in seconds to the weights in network. The performance was too slow for 120seconds.
Later I converted seconds to minutes and passed to weights which increased the performance a bit, but how do I increase the performance such that it responds quickly as it responds to when the impedance is in distance?
Also, I have a query. While passing time to the aggregate function. Should we pass in seconds or minutes?
I assume, as I pass time in seconds to network the seconds has to pass to aggregate and minutes if the time is in minutes. Am I correct?
code
code when the time is in minutes it returned the results in 6min.
```%%time
network.set(nodes,
name = 'etc')
accessibility = network1.aggregate(30,
type = 'count', imp_name='travel_time_seconds',
name = 'etc')
code when the time is in seconds it kept running and kernel was dead after a while.
%%time
network.set(nodes,
name = 'etc')
accessibility = network.aggregate(900,
type = 'count', imp_name='travel_time_seconds',
name = 'etc')
#pandana
Description of the issue
I am trying to use the aggregate function in pandana with impedance as time. Firstly, I passed time in seconds to the weights in network. The performance was too slow for 120seconds. Later I converted seconds to minutes and passed to weights which increased the performance a bit, but how do I increase the performance such that it responds quickly as it responds to when the impedance is in distance?
Also, I have a query. While passing time to the aggregate function. Should we pass in seconds or minutes? I assume, as I pass time in seconds to network the seconds has to pass to aggregate and minutes if the time is in minutes. Am I correct?
code