Docs script edit + better precision in verbose tracer + progress bar updates
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Copyright 2014 Modelling, Simulation and Design Lab (MSDL) at
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McGill University and the University of Antwerp (http://msdl.cs.mcgill.ca/)
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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Minimal Simulation Kernel
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=========================
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Due to the many features that PythonPDEVS supports, the code is quite big and many additional steps need to be taken during simulation.
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Certainly with Python, this causes problems due to the lack of compilation (and consequently optimization).
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For this reason, but also to show the minimal simulation algorithm of PythonPDEVS, a minimal simulation kernel is added.
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Such a minimal kernel, even without any special features, is useful for benchmarking different algorithms, without needing to worry about the supported features.
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It can also be useful for end-users, if the user is only interested in the state of the simulated model.
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Its use is identical to the normal simulation kernel, but the import is different.
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Instead of importing *Simulator* from the file *simulator.py*, it needs to be imported from *minimal.py*.
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So the only change is the import, which becomes something like::
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from pypdevs.minimal import Simulator
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All other code remains exactly the same.
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Unless configuration options (apart from *setTerminationTime*) are used, as these will no longer be possible.
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The only supported option is *setTerminationTime*, which works exactly the same as in the normal simulation kernel.
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While it is still possible to define transfer functions or define allocations in the model construction, these are ignored during simulation.
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The polymorphic scheduler is used automatically, so the performance will automatically be optimized to the different access patterns.
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There is thus no need to manually specify the scheduler.
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