I'm pretty sure that the error is on your end because the parseTime API was
changed between sumo versions and this is the expected error when mixing
versions. Take a look at
https://sumo.dlr.de/docs/TraCI/Interfacing_TraCI_from_Python.html#determine_the_traci_library_being_loaded
and substitute 'sumolib' for 'traci' to figure out where the version mix
comes from.

Am Do., 27. Aug. 2020 um 17:48 Uhr schrieb Sumo User <
[email protected]>:

> I downloaded the files from:
> https://sumo.dlr.de/docs/Downloads.php#sumo_-_latest_development_version
>
> But get the original error:
> Traceback (most recent call last):
>   File "detector/edgeDataFromFlow.py", line 124, in <module>
>     main(get_options())
>   File "detector/edgeDataFromFlow.py", line 86, in main
>     beginM = int(sumolib.miscutils.parseTime(options.begin, 60) / 60)
> TypeError: parseTime() takes exactly 1 argument (2 given)
>
> Could this be a bug or do you think it is a problem on my end?
>
> On Wed, Aug 26, 2020 at 2:11 AM Jakob Erdmann <[email protected]>
> wrote:
>
>> Hello,
>> the error you encountered indicates that you are loading sumo tools from
>> different versions which are incompatible regarding their internal API
>> (parseTime). Make sure you update all of the sumo tool, the linked
>> debugging tip applies also to the other tools:
>> https://sumo.dlr.de/docs/TraCI/Interfacing_TraCI_from_Python.html#determine_the_traci_library_being_loaded
>>
>> Regarding your steps, there may be a misunderstanding.
>> In step 1, the route file generated by randomTrips is used as input for
>> routeSampler.py rather than as input to edgeDataFromFlow.
>>
>> Regarding the resulting flows, try running routeSampler with the option
>> --optimize full and post the log output.
>>
>> regards,
>> Jakob
>>
>>
>> Am Mi., 26. Aug. 2020 um 00:31 Uhr schrieb Sumo User <
>> [email protected]>:
>>
>>> I used the latest development version and got this error:
>>>
>>> Traceback (most recent call last):
>>>   File "detector/edgeDataFromFlow.py", line 124, in <module>
>>>     main(get_options())
>>>   File "detector/edgeDataFromFlow.py", line 86, in main
>>>     beginM = int(sumolib.miscutils.parseTime(options.begin, 60) / 60)
>>> TypeError: parseTime() takes exactly 1 argument (2 given)
>>>
>>> I opened the code and changed this:
>>>
>>>     beginM = int(sumolib.miscutils.parseTime(options.begin, 60) / 60)
>>>
>>>     intervalM = int(sumolib.miscutils.parseTime(options.interval, 60) /
>>> 60)
>>>
>>>     endM = min(int(sumolib.miscutils.parseTime(options.end, 60) / 60),
>>> tMax)
>>>
>>> to this:
>>>
>>>     beginM = int(sumolib.miscutils.parseTime(options.begin) / 60)
>>>
>>>     intervalM = int(sumolib.miscutils.parseTime(options.interval) / 60)
>>>
>>>     endM = min(int(sumolib.miscutils.parseTime(options.end) / 60), tMax)
>>>
>>> I changed the input interval and end times from minutes to seconds and
>>> it ran.  But the flow rate did not match my measured data well enough.  For
>>> example, some exit ramps had a flow of 0 for almost the entire simulation
>>> when they should have had cars constantly using them.  I'm not too
>>> experienced with Python, so I do not know if that edit I made is the reason
>>> for the error.
>>>
>>> I'm not sure where my error is, I wanted to make sure that the following
>>> steps made sense:
>>> 1) randomTrips.py to get the route file used in edgeDataFromFlow
>>> 2) edgeDataFromFlow.py to get the edgeData file
>>> 3) routeSampler.py for the route file used in the simulation
>>> 4) DFRouter for a validation file and detector file
>>> 5) SUMO
>>>
>>>
>>>
>>> On Tue, Aug 25, 2020 at 2:06 AM Jakob Erdmann <[email protected]>
>>> wrote:
>>>
>>>> Unfortunately, the 1.6.0 version of routeSampler did not yet handle
>>>> data intervals. This is fixed in the latest development version (
>>>> https://sumo.dlr.de/docs/Downloads.php#sumo_-_latest_development_version
>>>> ).
>>>> However, I would recommend setting the option "--interval 900" to
>>>> aggregate the interval data to larger time slices. (or larger depending on
>>>> the typical travel time of vehicles within your network).
>>>>
>>>> Am Mo., 24. Aug. 2020 um 18:34 Uhr schrieb Sumo User <
>>>> [email protected]>:
>>>>
>>>>> Thank you for your response Jakob.
>>>>>
>>>>> I am working on using routeSampler.py, but have run into a problem
>>>>> using edgeDataFromFlow.py.  My flow data that was previously used as a 
>>>>> flow
>>>>> input file to DFRouter is three hours of data in 5 minute intervals.  When
>>>>> I run edgeDataFromFlow, I get an end time of 3600 seconds, but for three
>>>>> hours I would expect 10800.  I looked in the Python file and did not see 
>>>>> an
>>>>> input for end time, so I was wondering how to change it.
>>>>>
>>>>> Thank you,
>>>>> Alex
>>>>>
>>>>> On Thu, Aug 20, 2020 at 2:08 PM Jakob Erdmann <[email protected]>
>>>>> wrote:
>>>>>
>>>>>> Unfortunately, DFRouter does not provide additional customization
>>>>>> features. Consider using routeSampler.py instead.
>>>>>> However, this will only give meaningful changes if the measurement
>>>>>> data does not constrain the possible route combinations too strongly.
>>>>>> You could also try to define a stronger variation in vehicle speeds
>>>>>> by using the speedDev attribute and set sumo option --random in addition 
>>>>>> to
>>>>>> dfrouter option --random.
>>>>>>
>>>>>> Am Do., 20. Aug. 2020 um 19:04 Uhr schrieb Sumo User <
>>>>>> [email protected]>:
>>>>>>
>>>>>>> Hello,
>>>>>>>
>>>>>>> I have a set of measured data from a highway on a specific
>>>>>>> afternoon.  When use DFROUTER to run a simulation, the validation file
>>>>>>> matches the measured data in flow and speed well.  But after running 
>>>>>>> many
>>>>>>> simulations (>500), I can see that all the validation files are 
>>>>>>> extremely
>>>>>>> similar to each other.  What I want is to use my measured data as a 
>>>>>>> base,
>>>>>>> but have more variation so the simulation does not provide extremely
>>>>>>> similar outputs each time.  I have set --random to true and
>>>>>>> --randomize-flows to true, but that does not provide the variation that 
>>>>>>> I
>>>>>>> seek. I want to know if it is possible to generate outputs that are 
>>>>>>> still
>>>>>>> close to my measured data, but vary between simulations.
>>>>>>>
>>>>>>> Any ideas are appreciated!!
>>>>>>> _______________________________________________
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>>>>>>>
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