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minor change in docs
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@ -3,6 +3,11 @@ All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [0.14.7]
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### Changed
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* Minor change to traceback handling in async simulations
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### Fixed
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* Incomplete example in the docs (example.yml) caused an exception
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## [0.14.6]
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## [0.14.6]
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### Fixed
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### Fixed
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* Bug with newer versions of networkx (0.24) where the Graph.node attribute has been removed. We have updated our calls, but the code in nxsim is not under our control, so we have pinned the networkx version until that issue is solved.
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* Bug with newer versions of networkx (0.24) where the Graph.node attribute has been removed. We have updated our calls, but the code in nxsim is not under our control, so we have pinned the networkx version until that issue is solved.
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@ -8,32 +8,8 @@ The advantage of a configuration file is that it is a clean declarative descript
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Simulation configuration files can be formatted in ``json`` or ``yaml`` and they define all the parameters of a simulation.
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Simulation configuration files can be formatted in ``json`` or ``yaml`` and they define all the parameters of a simulation.
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Here's an example (``example.yml``).
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Here's an example (``example.yml``).
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.. code:: yaml
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.. literalinclude:: example.yml
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:language: yaml
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---
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name: MyExampleSimulation
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max_time: 50
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num_trials: 3
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interval: 2
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network_params:
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generator: barabasi_albert_graph
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n: 100
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m: 2
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network_agents:
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- agent_type: SISaModel
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weight: 1
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state:
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id: content
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- agent_type: SISaModel
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weight: 1
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state:
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id: discontent
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- agent_type: SISaModel
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weight: 8
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state:
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id: neutral
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environment_params:
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prob_infect: 0.075
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This example configuration will run three trials (``num_trials``) of a simulation containing a randomly generated network (``network_params``).
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This example configuration will run three trials (``num_trials``) of a simulation containing a randomly generated network (``network_params``).
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35
docs/example.yml
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35
docs/example.yml
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@ -0,0 +1,35 @@
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---
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name: MyExampleSimulation
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max_time: 50
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num_trials: 3
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interval: 2
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network_params:
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generator: barabasi_albert_graph
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n: 100
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m: 2
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network_agents:
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- agent_type: SISaModel
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weight: 1
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state:
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id: content
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- agent_type: SISaModel
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weight: 1
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state:
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id: discontent
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- agent_type: SISaModel
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weight: 8
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state:
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id: neutral
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environment_params:
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prob_infect: 0.075
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neutral_discontent_spon_prob: 0.1
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neutral_discontent_infected_prob: 0.3
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neutral_content_spon_prob: 0.3
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neutral_content_infected_prob: 0.4
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discontent_neutral: 0.5
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discontent_content: 0.5
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variance_d_c: 0.2
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content_discontent: 0.2
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variance_c_d: 0.2
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content_neutral: 0.2
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standard_variance: 1
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@ -1 +1 @@
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0.14.6
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0.14.7
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@ -216,9 +216,10 @@ class Simulation(NetworkSimulation):
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try:
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try:
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return self.run_trial(*args, **kwargs)
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return self.run_trial(*args, **kwargs)
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except Exception as ex:
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except Exception as ex:
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c = ex.__cause__
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if ex.__cause__ is not None:
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c.message = ''.join(traceback.format_exception(type(c), c, c.__traceback__)[:])
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ex = ex.__cause__
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return c
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ex.message = ''.join(traceback.format_exception(type(ex), ex, ex.__traceback__)[:])
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return ex
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def to_dict(self):
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def to_dict(self):
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return self.__getstate__()
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return self.__getstate__()
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