Thanks again Jakob for the answers
1) Ok. Eventually I just had a precision issue. I solved it by setting
save-state.precision to the integer number of digits I need.

Stefano

On Tue, Mar 14, 2023 at 2:45 AM Jakob Erdmann <[email protected]> wrote:

> 1) the state holds the position at the beginning of a time step whereas
> all other outputs hold the position at the end of a time step (so including
> vehicle movements for that step).
> 2) loading state clears all subscriptions so you need to renew them
> afterwards (since the state could hold anything or nothing subscriptions
> are at risk of becoming invalid anyway)
> 3). Thanks, it's 'traci.load' and the documentation has been fixed.
>
> Am Mo., 13. März 2023 um 17:12 Uhr schrieb Stefano Bonasera <
> [email protected]>:
>
>> Hi Jakob,
>>
>> Thanks for the prompt response, it was really helpful.
>> I find two issues with the save/load approach, plus another issue with
>> the documentation that I hope you can help me with:
>> 1) referring again to the previous env1 and env2 example: when env2 loads
>> the state saved from env1, vehicle information is a bit off. For example,
>> when getting position information from one of the vehicles, the state prior
>> to been saved reports a position of (101.5000452506627, 95.2), but if I
>> verify the position after having loaded that specific state file I get a
>> position of (101.49894165466144, 95.2) for the same vehicle - similarly
>> happens for other quantities. Do you have any hints on the reason of this
>> error?
>> 2) After env2 loads the state, I try to step within the simulation of
>> env2. However, after the simulation step, the _subscriptionMapping gets
>> empty at field 235, since the read int of the result (after sending the cmd
>> of CMD_SIMSTEP) is always 0. Do you know what is it causing this problem?
>> 3 - documentation) It seems the docu page of save and load (
>> https://sumo.dlr.de/docs/Simulation/SaveAndLoad.html) reports two load
>> options, but there is no def load under tools/traci/_simulation.py
>>
>> Thank you,
>> Stefano
>>
>> On Fri, Mar 10, 2023 at 10:04 AM Jakob Erdmann <[email protected]>
>> wrote:
>>
>>> Please see https://sumo.dlr.de/docs/Simulation/SaveAndLoad.htm
>>>
>>> Am Do., 9. März 2023 um 17:14 Uhr schrieb Stefano Bonasera <
>>> [email protected]>:
>>>
>>>> Hello,
>>>>
>>>> SUMO version: 1.16
>>>>
>>>> I am struggling with the following issue, working on python:
>>>> I start with two base environments (env1 and env2), randomly
>>>> initialized, leveraging flow to spawn actors, and with identical road
>>>> networks. The two envs will have at some point two different configurations
>>>> of existing actors/env_states - e.g., env1 has 4 actors with specific x_i,
>>>> y_i locations, velocity (lon and lat), angles, controllers, while env2 has
>>>> 2 actors with different features.
>>>>
>>>> At some point in my algo, I want env2 configuration to be identical to
>>>> env1's one via copying the current configuration/env_state of env1 into
>>>> env2: following the previous example, the final result would be for env2 to
>>>> have a configuration with 4 actors, each with features (x_i, y_i locations,
>>>> velocity (lon and lat), angles, controllers, ...) identical to what env1
>>>> has at that time.
>>>>
>>>> I have tried several approaches to manually removing/adding and moving
>>>> actors - all unsuccessful since I can change only a limited amount of
>>>> features of each actor (for example I cannot set the controllers, or the
>>>> lateral velocity), resulting in two different envs. Are you aware of any
>>>> solution for replicating env1 configuration/env_state into env2?
>>>>
>>>> Thank you so much for taking the time to read my email and for the help
>>>> in advance.
>>>>
>>>> --
>>>> Kind regards,
>>>> Stefano.
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>>
>>
>> --
>> Kind regards,
>> Stefano.
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-- 
Kind regards,
Stefano.
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