Different results when performing one to many vs many to many matrix

[rarearth]

Describe the bug
I have a data frames of origins and destinations and when I compute the travel times from every origin to every destination I noticed that some of the travel times seemed incredible unrealistic. For example it would say going 3 block by walking + transit would take upwards of 30 minutes.

I then decided to take the specific origin point I was concerned with and do a one to many travel time matrix calculation and I found the results to be much more reasonable, i.e. ~~5 minutes or so.

I also noticed that when I rerun the travel time matrix for the many to many, I get different results every time.

my input shapes are

origins_gdf.shape, destinations_gdf.shape
>>> ((1004, 3), (506, 19))

To Reproduce

transport_network = TransportNetwork(
    "../data/Chicago.osm.pbf",
    [
        "../data/GTFS.zip"
    ]
)

travel_time_matrix_computer = TravelTimeMatrixComputer(
    transport_network,
    origins=origins_gdf,
    destinations=destinations_gdf,
    transport_modes=[TransitMode.TRANSIT, LegMode.WALK],
    breakdown=True
)
travel_time_matrix = travel_time_matrix_computer.compute_travel_times()

# vs
travel_time_matrix_computer = TravelTimeMatrixComputer(
    transport_network,
    origins=origins_gdf[origins_gdf.id == 227],
    destinations=destinations_gdf,
    transport_modes=[TransitMode.TRANSIT, LegMode.WALK],
    breakdown=True
)
travel_time_matrix = travel_time_matrix_computer.compute_travel_times()

I can provide the gdf shape files and the transport network if need be

Expected behavior
I would expect the

Environment:
Apple M1 Max
Ventura 13.4 (22F66)

java zulu-11.jdk

platform: osx-arm64

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additional context
I get hundreds of this warning when ever I run the calculation

self._regional_task.fromLat = origin.y
/opt/homebrew/Caskroom/miniconda/base/envs/rarearth/lib/python3.10/site-packages/r5py/r5/regional_task.py:395: FutureWarning: Calling float on a single element Series is deprecated and will raise a TypeError in the future. Use float(ser.iloc[0]) instead

[christophfink]

Hi!
Thanks for the bug report. There have been extensive changes to the code base of R5py over the last months. Could you try whether the issue persists on the current development version? You can install the latest git main branch using pip:

pip install git+https://github.com/r5py/r5py.git

[christophfink]

@rarearth have you had the chance to test the development branch?