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fix problem by clearing variable pools?

refactoring
Sebastian Junges 4 years ago
parent
commit
d8fd39cdc5
  1. 5
      examples/pomdp/01-pomdps.py

5
examples/pomdp/01-pomdps.py

@ -26,6 +26,8 @@ def example_parametric_models_01():
else: else:
import pycarl.gmp.formula import pycarl.gmp.formula
# Prevent curious side effects from earlier runs (for tests only)
pycarl.clear_pools()
### ###
# How to apply an unknown FSC to obtain a pMC from a POMDP # How to apply an unknown FSC to obtain a pMC from a POMDP
path = stormpy.examples.files.prism_pomdp_maze path = stormpy.examples.files.prism_pomdp_maze
@ -68,9 +70,6 @@ def example_parametric_models_01():
# apply the memory onto the POMDP to get the cartesian product # apply the memory onto the POMDP to get the cartesian product
pomdp = stormpy.pomdp.unfold_memory(pomdp, memory) pomdp = stormpy.pomdp.unfold_memory(pomdp, memory)
# apply the unknown FSC to obtain a pmc from the POMDP # apply the unknown FSC to obtain a pmc from the POMDP
if False:
# Currently, this command is known to cause problems in combination with running some other tests.
# While we are investigating, we do not run the code
pmc = stormpy.pomdp.apply_unknown_fsc(pomdp, stormpy.pomdp.PomdpFscApplicationMode.simple_linear) pmc = stormpy.pomdp.apply_unknown_fsc(pomdp, stormpy.pomdp.PomdpFscApplicationMode.simple_linear)
export_pmc = False # Set to True to export the pMC as drn. export_pmc = False # Set to True to export the pMC as drn.

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