fredshone

What are your thoughts about the difference between the "planned" and "experienced" plans? Our current working assumption is that times and durations can be different due to the difference between...

I've not been able to reproduce the above using toy data, but in the process have got a little more familiar with the fact that we have been using planned...

I think we used `` then tuned pt costs to get calibration (essentially after we tuned walk, bike, car...) - but perhaps we were lucky. Not sure if the theorists...

First thought is that the additional activities are pt interactions. The `read_matsim` function has a `simplify_pt_trips` arg ([here](https://github.com/arup-group/pam/blob/23d2dcbea012d2e2b6a852b190c3994e0f5dabae/pam/read.py#L581)). The default is false...

Negative durations are a bummer. If it's not too inconvenient it would be great to get a xml sample of the negative duration plans so we can write some tests.

that loss of activities will be pam cropping stuff after 24 hours...

i am thinking to remove this restriction (or make it more optional) in future. Maybe pam can just generalise to activity plans of any duration, then we apply cropping more...

suggest: - slimming down existing with more minimal examples - removing duplicates/bad ones - better naming and order

> 1. If we have a population of 100 people distributed across 40 households, would we generally set up a model such that `sum(hh.freq for hh in population.households.values()) = 40`...

Seems `.size` should be reserved for "unweighted" counts and either `.freq` or `.weight` for "weighted"? So propose that: - population.size be changed to be count of hhs (rather than weighted)...