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Refactoring v0.15.1

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See CHANGELOG.md for a full list of changes

* Removed nxsim
* Refactored `agents.NetworkAgent` and `agents.BaseAgent`
* Refactored exporters
* Added stats to history
This commit is contained in:
J. Fernando Sánchez
2020-10-19 13:14:48 +02:00
parent 3b2c6a3db5
commit 05f7f49233
29 changed files with 4847 additions and 572 deletions
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4
docs/conf.py
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@@ -31,7 +31,7 @@
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = []
extensions = ['IPython.sphinxext.ipython_console_highlighting']
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
@@ -69,7 +69,7 @@ language = None
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
# This patterns also effect to html_static_path and html_extra_path
exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store', '**.ipynb_checkpoints']
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'sphinx'

21
docs/configuration.rst
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@@ -218,3 +218,24 @@ These agents are programmed in much the same way as network agents, the only dif
You may use environment agents to model events that a normal agent cannot control, such as natural disasters or chance.
They are also useful to add behavior that has little to do with the network and the interactions within that network.
Templating
==========
Sometimes, it is useful to parameterize a simulation and run it over a range of values in order to compare each run and measure the effect of those parameters in the simulation.
For instance, you may want to run a simulation with different agent distributions.
This can be done in Soil using **templates**.
A template is a configuration where some of the values are specified with a variable.
e.g., ``weight: "{{ var1 }}"`` instead of ``weight: 1``.
There are two types of variables, depending on how their values are decided:
* Fixed. A list of values is provided, and a new simulation is run for each possible value. If more than a variable is given, a new simulation will be run per combination of values.
* Bounded/Sampled. The bounds of the variable are provided, along with a sampler method, which will be used to compute all the configuration combinations.
When fixed and bounded variables are mixed, Soil generates a new configuration per combination of fixed values and bounded values.
Here is an example with a single fixed variable and two bounded variable:
.. literalinclude:: ../examples/template.yml
:language: yaml