Trajectory Collections

TrajaCollection

When handling multiple trajectories, Traja allows plotting and analysis simultaneously.

Initialize a TrajaCollection() with a dictionary or DataFrame and id_col.

Initializing with Dictionary

The keys of the dictionary can be used to identify types of objects in the scene, eg, “bus”, “car”, “person”:

dfs = {"car0":df0, "car1":df1, "bus0: df2, "person0": df3}

Or, arbitrary numbers can be used to initialize

class traja.frame.TrajaCollection(trjs: Union[TrajaDataFrame, DataFrame, dict], id_col: Optional[str] = None, **kwargs)

Collection of trajectories.

Initializing with a DataFrame

A dataframe containing an id column can be passed directly to TrajaCollection(), as long as the id_col is specified:

trjs = TrajaCollection(df, id_col="id")

Grouped Operations

Operations can be applied to each trajectory with apply_all().

TrajaCollection.apply_all(method, **kwargs)

Applies method to all trajectories

Parameters

method –

Returns

dataframe or series

>>> trjs = {ind: traja.generate(seed=ind) for ind in range(3)} 
>>> coll = traja.TrajaCollection(trjs) 
>>> angles = coll.apply_all(traja.calc_angle) 

Plottting Multiple Trajectories

Plotting multiple trajectories can be achieved with plot().

TrajaCollection.plot(colors=None, **kwargs)

Plot collection of trajectories with colors assigned to each id.

>>> trjs = {ind: traja.generate(seed=ind) for ind in range(3)} 
>>> coll = traja.TrajaCollection(trjs) 
>>> coll.plot() 

Colors can be specified for ids by supplying colors with a lookup dictionary:

or with a substring lookup:

colors = [“car”:”red”,

“bus”:”orange”, “12”:”red”, “13”:”orange”, “14”:”orange”]