mirror of https://github.com/gsi-upm/soil
WIP soil
* Pandas integration * Improved environment * Logging and data dumps * Tests * Added Finite State Machine models * Rewritten ipython notebook and documentationTFG-David
J. Fernando Sánchez
7 years ago
parent
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__pycache__/
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.idea/
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.ipynb_checkpoints/
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*.png
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*.gexf
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.*
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results
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soil_output
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docs/_build*
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build/*
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dist/*
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include requirements.txt
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include test-requirements.txt
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include README.rst
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graft soil
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# [Soil](https://github.com/gsi-upm/soil)
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The purpose of Soil (SOcial network sImuLator) is provding an Agent-based Social Simulator written in Python for Social Networks.
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In order to see quickly how to use Soil, you can follow the following [tutorial](https://github.com/gsi-upm/soil/blob/master/soil_tutorial.ipynb).
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Soil is an extensible and user-friendly Agent-based Social Simulator for Social Networks.
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Learn how to run your own simulations with our [documentation](http://soilsim.readthedocs.io).
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Follow our [tutorial](notebooks/soil_tutorial.ipynb) to develop your own agent models.
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@Copyright GSI - Universidad Politécnica de Madrid 2017
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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: d241ad8149638a17f61def88be87f400
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tags: 645f666f9bcd5a90fca523b33c5a78b7
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@ -1,25 +0,0 @@
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.. Soil documentation master file, created by
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sphinx-quickstart on Tue Apr 25 12:48:56 2017.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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Welcome to Soil's documentation!
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================================
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Soil is an Agent-based Social Simulator in Python for modelling and simulation of Social Networks.
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.. toctree::
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:maxdepth: 2
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:caption: Learn more about soil:
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installation
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usage
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models
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.. Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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Installation
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------------
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The latest version can be installed through GitLab.
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.. code:: bash
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git clone https://lab.cluster.gsi.dit.upm.es/soil/soil.git
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Developing new models
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---------------------
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This document describes how to develop a new analysis model.
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What is a model?
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================
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A model defines the behaviour of the agents with a view to assessing their effects on the system as a whole.
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In practice, a model consists of at least two parts:
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* Python module: the actual code that describes the behaviour.
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* Setting up the variables in the Settings JSON file.
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This separation allows us to run the simulation with different agents.
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Models Code
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===========
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All the models are imported to the main file. The initialization look like this:
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.. code:: python
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import settings
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networkStatus = {} # Dict that will contain the status of every agent in the network
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sentimentCorrelationNodeArray = []
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for x in range(0, settings.network_params["number_of_nodes"]):
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sentimentCorrelationNodeArray.append({'id': x})
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# Initialize agent states. Let's assume everyone is normal.
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init_states = [{'id': 0, } for _ in range(settings.network_params["number_of_nodes"])]
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# add keys as as necessary, but "id" must always refer to that state category
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A new model have to inherit the BaseBehaviour class which is in the same module.
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There are two basics methods:
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* __init__
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* step: used to define the behaviour over time.
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Variable Initialization
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=======================
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The different parameters of the model have to be initialize in the Simulation Settings JSON file which will be
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passed as a parameter to the simulation.
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.. code:: json
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{
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"agent": ["SISaModel","ControlModelM2"],
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"neutral_discontent_spon_prob": 0.04,
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"neutral_discontent_infected_prob": 0.04,
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"neutral_content_spon_prob": 0.18,
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"neutral_content_infected_prob": 0.02,
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"discontent_neutral": 0.13,
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"discontent_content": 0.07,
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"variance_d_c": 0.02,
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"content_discontent": 0.009,
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"variance_c_d": 0.003,
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"content_neutral": 0.088,
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"standard_variance": 0.055,
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"prob_neutral_making_denier": 0.035,
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"prob_infect": 0.075,
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"prob_cured_healing_infected": 0.035,
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"prob_cured_vaccinate_neutral": 0.035,
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"prob_vaccinated_healing_infected": 0.035,
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"prob_vaccinated_vaccinate_neutral": 0.035,
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"prob_generate_anti_rumor": 0.035
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}
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In this file you will also define the models you are going to simulate. You can simulate as many models as you want.
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The simulation returns one result for each model, executing each model separately. For the usage, see :doc:`usage`.
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Example Model
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=============
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In this section, we will implement a Sentiment Correlation Model.
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The class would look like this:
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.. code:: python
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from ..BaseBehaviour import *
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from .. import sentimentCorrelationNodeArray
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class SentimentCorrelationModel(BaseBehaviour):
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def __init__(self, environment=None, agent_id=0, state=()):
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super().__init__(environment=environment, agent_id=agent_id, state=state)
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self.outside_effects_prob = environment.environment_params['outside_effects_prob']
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self.anger_prob = environment.environment_params['anger_prob']
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self.joy_prob = environment.environment_params['joy_prob']
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self.sadness_prob = environment.environment_params['sadness_prob']
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self.disgust_prob = environment.environment_params['disgust_prob']
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self.time_awareness = []
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for i in range(4): # In this model we have 4 sentiments
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self.time_awareness.append(0) # 0-> Anger, 1-> joy, 2->sadness, 3 -> disgust
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sentimentCorrelationNodeArray[self.id][self.env.now] = 0
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def step(self, now):
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self.behaviour() # Method which define the behaviour
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super().step(now)
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The variables will be modified by the user, so you have to include them in the Simulation Settings JSON file.
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Usage
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-----
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First of all, you need to install the package. See :doc:`installation` for installation instructions.
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Simulation Settings
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===================
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Once installed, before running a simulation, you need to configure it.
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* In the Settings JSON file you will find the configuration of the network.
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.. code:: python
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{
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"network_type": 1,
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"number_of_nodes": 1000,
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"max_time": 50,
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"num_trials": 1,
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"timeout": 2
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}
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* In the Settings JSON file, you will also find the configuration of the models.
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Network Types
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=============
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There are three types of network implemented, but you could add more.
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.. code:: python
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if settings.network_type == 0:
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G = nx.complete_graph(settings.number_of_nodes)
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if settings.network_type == 1:
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G = nx.barabasi_albert_graph(settings.number_of_nodes, 10)
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if settings.network_type == 2:
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G = nx.margulis_gabber_galil_graph(settings.number_of_nodes, None)
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# More types of networks can be added here
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Models Settings
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===============
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After having configured the simulation, the next step is setting up the variables of the models.
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For this, you will need to modify the Settings JSON file again.
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.. code:: json
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{
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"agent": ["SISaModel","ControlModelM2"],
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"neutral_discontent_spon_prob": 0.04,
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"neutral_discontent_infected_prob": 0.04,
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"neutral_content_spon_prob": 0.18,
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"neutral_content_infected_prob": 0.02,
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"discontent_neutral": 0.13,
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"discontent_content": 0.07,
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"variance_d_c": 0.02,
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"content_discontent": 0.009,
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"variance_c_d": 0.003,
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"content_neutral": 0.088,
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"standard_variance": 0.055,
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"prob_neutral_making_denier": 0.035,
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"prob_infect": 0.075,
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"prob_cured_healing_infected": 0.035,
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"prob_cured_vaccinate_neutral": 0.035,
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"prob_vaccinated_healing_infected": 0.035,
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"prob_vaccinated_vaccinate_neutral": 0.035,
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"prob_generate_anti_rumor": 0.035
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}
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|
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In this file you will define the different models you are going to simulate. You can simulate as many models
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as you want. Each model will be simulated separately.
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|
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After setting up the models, you have to initialize the parameters of each one. You will find the parameters needed
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in the documentation of each model.
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Parameter validation will fail if a required parameter without a default has not been provided.
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Running the Simulation
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======================
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After setting all the configuration, you will be able to run the simulation. All you need to do is execute:
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.. code:: bash
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python3 soil.py
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The simulation will return a dynamic graph .gexf file which could be visualized with
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`Gephi <https://gephi.org/users/download/>`__.
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It will also return one .png picture for each model simulated.
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@import url("basic.css");
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||||
div.admonition tt.xref, div.admonition code.xref, div.admonition a tt {
|
||||
background-color: ;
|
||||
border-bottom: 1px solid #fafafa;
|
||||
}
|
||||
|
||||
dd div.admonition {
|
||||
margin-left: -60px;
|
||||
padding-left: 60px;
|
||||
}
|
||||
|
||||
div.admonition p.admonition-title {
|
||||
font-family: 'Garamond', 'Georgia', serif;
|
||||
font-weight: normal;
|
||||
font-size: 24px;
|
||||
margin: 0 0 10px 0;
|
||||
padding: 0;
|
||||
line-height: 1;
|
||||
}
|
||||
|
||||
div.admonition p.last {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
div.highlight {
|
||||
background-color: #fff;
|
||||
}
|
||||
|
||||
dt:target, .highlight {
|
||||
background: #FAF3E8;
|
||||
}
|
||||
|
||||
div.warning {
|
||||
background-color: #FCC;
|
||||
border: 1px solid #FAA;
|
||||
}
|
||||
|
||||
div.danger {
|
||||
background-color: #FCC;
|
||||
border: 1px solid #FAA;
|
||||
-moz-box-shadow: 2px 2px 4px #D52C2C;
|
||||
-webkit-box-shadow: 2px 2px 4px #D52C2C;
|
||||
box-shadow: 2px 2px 4px #D52C2C;
|
||||
}
|
||||
|
||||
div.error {
|
||||
background-color: #FCC;
|
||||
border: 1px solid #FAA;
|
||||
-moz-box-shadow: 2px 2px 4px #D52C2C;
|
||||
-webkit-box-shadow: 2px 2px 4px #D52C2C;
|
||||
box-shadow: 2px 2px 4px #D52C2C;
|
||||
}
|
||||
|
||||
div.caution {
|
||||
background-color: #FCC;
|
||||
border: 1px solid #FAA;
|
||||
}
|
||||
|
||||
div.attention {
|
||||
background-color: #FCC;
|
||||
border: 1px solid #FAA;
|
||||
}
|
||||
|
||||
div.important {
|
||||
background-color: #EEE;
|
||||
border: 1px solid #CCC;
|
||||
}
|
||||
|
||||
div.note {
|
||||
background-color: #EEE;
|
||||
border: 1px solid #CCC;
|
||||
}
|
||||
|
||||
div.tip {
|
||||
background-color: #EEE;
|
||||
border: 1px solid #CCC;
|
||||
}
|
||||
|
||||
div.hint {
|
||||
background-color: #EEE;
|
||||
border: 1px solid #CCC;
|
||||
}
|
||||
|
||||
div.seealso {
|
||||
background-color: #EEE;
|
||||
border: 1px solid #CCC;
|
||||
}
|
||||
|
||||
div.topic {
|
||||
background-color: #EEE;
|
||||
}
|
||||
|
||||
p.admonition-title {
|
||||
display: inline;
|
||||
}
|
||||
|
||||
p.admonition-title:after {
|
||||
content: ":";
|
||||
}
|
||||
|
||||
pre, tt, code {
|
||||
font-family: 'Consolas', 'Menlo', 'Deja Vu Sans Mono', 'Bitstream Vera Sans Mono', monospace;
|
||||
font-size: 0.9em;
|
||||
}
|
||||
|
||||
.hll {
|
||||
background-color: #FFC;
|
||||
margin: 0 -12px;
|
||||
padding: 0 12px;
|
||||
display: block;
|
||||
}
|
||||
|
||||
img.screenshot {
|
||||
}
|
||||
|
||||
tt.descname, tt.descclassname, code.descname, code.descclassname {
|
||||
font-size: 0.95em;
|
||||
}
|
||||
|
||||
tt.descname, code.descname {
|
||||
padding-right: 0.08em;
|
||||
}
|
||||
|
||||
img.screenshot {
|
||||
-moz-box-shadow: 2px 2px 4px #EEE;
|
||||
-webkit-box-shadow: 2px 2px 4px #EEE;
|
||||
box-shadow: 2px 2px 4px #EEE;
|
||||
}
|
||||
|
||||
table.docutils {
|
||||
border: 1px solid #888;
|
||||
-moz-box-shadow: 2px 2px 4px #EEE;
|
||||
-webkit-box-shadow: 2px 2px 4px #EEE;
|
||||
box-shadow: 2px 2px 4px #EEE;
|
||||
}
|
||||
|
||||
table.docutils td, table.docutils th {
|
||||
border: 1px solid #888;
|
||||
padding: 0.25em 0.7em;
|
||||
}
|
||||
|
||||
table.field-list, table.footnote {
|
||||
border: none;
|
||||
-moz-box-shadow: none;
|
||||
-webkit-box-shadow: none;
|
||||
box-shadow: none;
|
||||
}
|
||||
|
||||
table.footnote {
|
||||
margin: 15px 0;
|
||||
width: 100%;
|
||||
border: 1px solid #EEE;
|
||||
background: #FDFDFD;
|
||||
font-size: 0.9em;
|
||||
}
|
||||
|
||||
table.footnote + table.footnote {
|
||||
margin-top: -15px;
|
||||
border-top: none;
|
||||
}
|
||||
|
||||
table.field-list th {
|
||||
padding: 0 0.8em 0 0;
|
||||
}
|
||||
|
||||
table.field-list td {
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
table.field-list p {
|
||||
margin-bottom: 0.8em;
|
||||
}
|
||||
|
||||
table.footnote td.label {
|
||||
width: .1px;
|
||||
padding: 0.3em 0 0.3em 0.5em;
|
||||
}
|
||||
|
||||
table.footnote td {
|
||||
padding: 0.3em 0.5em;
|
||||
}
|
||||
|
||||
dl {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
dl dd {
|
||||
margin-left: 30px;
|
||||
}
|
||||
|
||||
blockquote {
|
||||
margin: 0 0 0 30px;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
ul, ol {
|
||||
/* Matches the 30px from the narrow-screen "li > ul" selector below */
|
||||
margin: 10px 0 10px 30px;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
pre {
|
||||
background: #EEE;
|
||||
padding: 7px 30px;
|
||||
margin: 15px 0px;
|
||||
line-height: 1.3em;
|
||||
}
|
||||
|
||||
div.viewcode-block:target {
|
||||
background: #ffd;
|
||||
}
|
||||
|
||||
dl pre, blockquote pre, li pre {
|
||||
margin-left: 0;
|
||||
padding-left: 30px;
|
||||
}
|
||||
|
||||
dl dl pre {
|
||||
margin-left: -90px;
|
||||
padding-left: 90px;
|
||||
}
|
||||
|
||||
tt, code {
|
||||
background-color: #ecf0f3;
|
||||
color: #222;
|
||||
/* padding: 1px 2px; */
|
||||
}
|
||||
|
||||
tt.xref, code.xref, a tt {
|
||||
background-color: #FBFBFB;
|
||||
border-bottom: 1px solid #fff;
|
||||
}
|
||||
|
||||
a.reference {
|
||||
text-decoration: none;
|
||||
border-bottom: 1px dotted #004B6B;
|
||||
}
|
||||
|
||||
/* Don't put an underline on images */
|
||||
a.image-reference, a.image-reference:hover {
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
a.reference:hover {
|
||||
border-bottom: 1px solid #6D4100;
|
||||
}
|
||||
|
||||
a.footnote-reference {
|
||||
text-decoration: none;
|
||||
font-size: 0.7em;
|
||||
vertical-align: top;
|
||||
border-bottom: 1px dotted #004B6B;
|
||||
}
|
||||
|
||||
a.footnote-reference:hover {
|
||||
border-bottom: 1px solid #6D4100;
|
||||
}
|
||||
|
||||
a:hover tt, a:hover code {
|
||||
background: #EEE;
|
||||
}
|
||||
|
||||
|
||||
@media screen and (max-width: 870px) {
|
||||
|
||||
div.sphinxsidebar {
|
||||
display: none;
|
||||
}
|
||||
|
||||
div.document {
|
||||
width: 100%;
|
||||
|
||||
}
|
||||
|
||||
div.documentwrapper {
|
||||
margin-left: 0;
|
||||
margin-top: 0;
|
||||
margin-right: 0;
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
div.bodywrapper {
|
||||
margin-top: 0;
|
||||
margin-right: 0;
|
||||
margin-bottom: 0;
|
||||
margin-left: 0;
|
||||
}
|
||||
|
||||
ul {
|
||||
margin-left: 0;
|
||||
}
|
||||
|
||||
li > ul {
|
||||
/* Matches the 30px from the "ul, ol" selector above */
|
||||
margin-left: 30px;
|
||||
}
|
||||
|
||||
.document {
|
||||
width: auto;
|
||||
}
|
||||
|
||||
.footer {
|
||||
width: auto;
|
||||
}
|
||||
|
||||
.bodywrapper {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.footer {
|
||||
width: auto;
|
||||
}
|
||||
|
||||
.github {
|
||||
display: none;
|
||||
}
|
||||
|
||||
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
||||
@media screen and (max-width: 875px) {
|
||||
|
||||
body {
|
||||
margin: 0;
|
||||
padding: 20px 30px;
|
||||
}
|
||||
|
||||
div.documentwrapper {
|
||||
float: none;
|
||||
background: #fff;
|
||||
}
|
||||
|
||||
div.sphinxsidebar {
|
||||
display: block;
|
||||
float: none;
|
||||
width: 102.5%;
|
||||
margin: 50px -30px -20px -30px;
|
||||
padding: 10px 20px;
|
||||
background: #333;
|
||||
color: #FFF;
|
||||
}
|
||||
|
||||
div.sphinxsidebar h3, div.sphinxsidebar h4, div.sphinxsidebar p,
|
||||
div.sphinxsidebar h3 a {
|
||||
color: #fff;
|
||||
}
|
||||
|
||||
div.sphinxsidebar a {
|
||||
color: #AAA;
|
||||
}
|
||||
|
||||
div.sphinxsidebar p.logo {
|
||||
display: none;
|
||||
}
|
||||
|
||||
div.document {
|
||||
width: 100%;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
div.footer {
|
||||
display: none;
|
||||
}
|
||||
|
||||
div.bodywrapper {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
div.body {
|
||||
min-height: 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
.rtd_doc_footer {
|
||||
display: none;
|
||||
}
|
||||
|
||||
.document {
|
||||
width: auto;
|
||||
}
|
||||
|
||||
.footer {
|
||||
width: auto;
|
||||
}
|
||||
|
||||
.footer {
|
||||
width: auto;
|
||||
}
|
||||
|
||||
.github {
|
||||
display: none;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/* misc. */
|
||||
|
||||
.revsys-inline {
|
||||
display: none!important;
|
||||
}
|
||||
|
||||
/* Make nested-list/multi-paragraph items look better in Releases changelog
|
||||
* pages. Without this, docutils' magical list fuckery causes inconsistent
|
||||
* formatting between different release sub-lists.
|
||||
*/
|
||||
div#changelog > div.section > ul > li > p:only-child {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
/* Hide fugly table cell borders in ..bibliography:: directive output */
|
||||
table.docutils.citation, table.docutils.citation td, table.docutils.citation th {
|
||||
border: none;
|
||||
/* Below needed in some edge cases; if not applied, bottom shadows appear */
|
||||
-moz-box-shadow: none;
|
||||
-webkit-box-shadow: none;
|
||||
box-shadow: none;
|
||||
}
|
||||
@ -1,632 +0,0 @@
|
||||
/*
|
||||
* basic.css
|
||||
* ~~~~~~~~~
|
||||
*
|
||||
* Sphinx stylesheet -- basic theme.
|
||||
*
|
||||
* :copyright: Copyright 2007-2016 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
/* -- main layout ----------------------------------------------------------- */
|
||||
|
||||
div.clearer {
|
||||
clear: both;
|
||||
}
|
||||
|
||||
/* -- relbar ---------------------------------------------------------------- */
|
||||
|
||||
div.related {
|
||||
width: 100%;
|
||||
font-size: 90%;
|
||||
}
|
||||
|
||||
div.related h3 {
|
||||
display: none;
|
||||
}
|
||||
|
||||
div.related ul {
|
||||
margin: 0;
|
||||
padding: 0 0 0 10px;
|
||||
list-style: none;
|
||||
}
|
||||
|
||||
div.related li {
|
||||
display: inline;
|
||||
}
|
||||
|
||||
div.related li.right {
|
||||
float: right;
|
||||
margin-right: 5px;
|
||||
}
|
||||
|
||||
/* -- sidebar --------------------------------------------------------------- */
|
||||
|
||||
div.sphinxsidebarwrapper {
|
||||
padding: 10px 5px 0 10px;
|
||||
}
|
||||
|
||||
div.sphinxsidebar {
|
||||
float: left;
|
||||
width: 230px;
|
||||
margin-left: -100%;
|
||||
font-size: 90%;
|
||||
word-wrap: break-word;
|
||||
overflow-wrap : break-word;
|
||||
}
|
||||
|
||||
div.sphinxsidebar ul {
|
||||
list-style: none;
|
||||
}
|
||||
|
||||
div.sphinxsidebar ul ul,
|
||||
div.sphinxsidebar ul.want-points {
|
||||
margin-left: 20px;
|
||||
list-style: square;
|
||||
}
|
||||
|
||||
div.sphinxsidebar ul ul {
|
||||
margin-top: 0;
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
div.sphinxsidebar form {
|
||||
margin-top: 10px;
|
||||
}
|
||||
|
||||
div.sphinxsidebar input {
|
||||
border: 1px solid #98dbcc;
|
||||
font-family: sans-serif;
|
||||
font-size: 1em;
|
||||
}
|
||||
|
||||
div.sphinxsidebar #searchbox input[type="text"] {
|
||||
width: 170px;
|
||||
}
|
||||
|
||||
img {
|
||||
border: 0;
|
||||
max-width: 100%;
|
||||
}
|
||||
|
||||
/* -- search page ----------------------------------------------------------- */
|
||||
|
||||
ul.search {
|
||||
margin: 10px 0 0 20px;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
ul.search li {
|
||||
padding: 5px 0 5px 20px;
|
||||
background-image: url(file.png);
|
||||
background-repeat: no-repeat;
|
||||
background-position: 0 7px;
|
||||
}
|
||||
|
||||
ul.search li a {
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
ul.search li div.context {
|
||||
color: #888;
|
||||
margin: 2px 0 0 30px;
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
ul.keywordmatches li.goodmatch a {
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
/* -- index page ------------------------------------------------------------ */
|
||||
|
||||
table.contentstable {
|
||||
width: 90%;
|
||||
margin-left: auto;
|
||||
margin-right: auto;
|
||||
}
|
||||
|
||||
table.contentstable p.biglink {
|
||||
line-height: 150%;
|
||||
}
|
||||
|
||||
a.biglink {
|
||||
font-size: 1.3em;
|
||||
}
|
||||
|
||||
span.linkdescr {
|
||||
font-style: italic;
|
||||
padding-top: 5px;
|
||||
font-size: 90%;
|
||||
}
|
||||
|
||||
/* -- general index --------------------------------------------------------- */
|
||||
|
||||
table.indextable {
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
table.indextable td {
|
||||
text-align: left;
|
||||
vertical-align: top;
|
||||
}
|
||||
|
||||
table.indextable ul {
|
||||
margin-top: 0;
|
||||
margin-bottom: 0;
|
||||
list-style-type: none;
|
||||
}
|
||||
|
||||
table.indextable > tbody > tr > td > ul {
|
||||
padding-left: 0em;
|
||||
}
|
||||
|
||||
table.indextable tr.pcap {
|
||||
height: 10px;
|
||||
}
|
||||
|
||||
table.indextable tr.cap {
|
||||
margin-top: 10px;
|
||||
background-color: #f2f2f2;
|
||||
}
|
||||
|
||||
img.toggler {
|
||||
margin-right: 3px;
|
||||
margin-top: 3px;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
div.modindex-jumpbox {
|
||||
border-top: 1px solid #ddd;
|
||||
border-bottom: 1px solid #ddd;
|
||||
margin: 1em 0 1em 0;
|
||||
padding: 0.4em;
|
||||
}
|
||||
|
||||
div.genindex-jumpbox {
|
||||
border-top: 1px solid #ddd;
|
||||
border-bottom: 1px solid #ddd;
|
||||
margin: 1em 0 1em 0;
|
||||
padding: 0.4em;
|
||||
}
|
||||
|
||||
/* -- domain module index --------------------------------------------------- */
|
||||
|
||||
table.modindextable td {
|
||||
padding: 2px;
|
||||
border-collapse: collapse;
|
||||
}
|
||||
|
||||
/* -- general body styles --------------------------------------------------- */
|
||||
|
||||
div.body p, div.body dd, div.body li, div.body blockquote {
|
||||
-moz-hyphens: auto;
|
||||
-ms-hyphens: auto;
|
||||
-webkit-hyphens: auto;
|
||||
hyphens: auto;
|
||||
}
|
||||
|
||||
a.headerlink {
|
||||
visibility: hidden;
|
||||
}
|
||||
|
||||
h1:hover > a.headerlink,
|
||||
h2:hover > a.headerlink,
|
||||
h3:hover > a.headerlink,
|
||||
h4:hover > a.headerlink,
|
||||
h5:hover > a.headerlink,
|
||||
h6:hover > a.headerlink,
|
||||
dt:hover > a.headerlink,
|
||||
caption:hover > a.headerlink,
|
||||
p.caption:hover > a.headerlink,
|
||||
div.code-block-caption:hover > a.headerlink {
|
||||
visibility: visible;
|
||||
}
|
||||
|
||||
div.body p.caption {
|
||||
text-align: inherit;
|
||||
}
|
||||
|
||||
div.body td {
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
.first {
|
||||
margin-top: 0 !important;
|
||||
}
|
||||
|
||||
p.rubric {
|
||||
margin-top: 30px;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
img.align-left, .figure.align-left, object.align-left {
|
||||
clear: left;
|
||||
float: left;
|
||||
margin-right: 1em;
|
||||
}
|
||||
|
||||
img.align-right, .figure.align-right, object.align-right {
|
||||
clear: right;
|
||||
float: right;
|
||||
margin-left: 1em;
|
||||
}
|
||||
|
||||
img.align-center, .figure.align-center, object.align-center {
|
||||
display: block;
|
||||
margin-left: auto;
|
||||
margin-right: auto;
|
||||
}
|
||||
|
||||
.align-left {
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
.align-center {
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
.align-right {
|
||||
text-align: right;
|
||||
}
|
||||
|
||||
/* -- sidebars -------------------------------------------------------------- */
|
||||
|
||||
div.sidebar {
|
||||
margin: 0 0 0.5em 1em;
|
||||
border: 1px solid #ddb;
|
||||
padding: 7px 7px 0 7px;
|
||||
background-color: #ffe;
|
||||
width: 40%;
|
||||
float: right;
|
||||
}
|
||||
|
||||
p.sidebar-title {
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
/* -- topics ---------------------------------------------------------------- */
|
||||
|
||||
div.topic {
|
||||
border: 1px solid #ccc;
|
||||
padding: 7px 7px 0 7px;
|
||||
margin: 10px 0 10px 0;
|
||||
}
|
||||
|
||||
p.topic-title {
|
||||
font-size: 1.1em;
|
||||
font-weight: bold;
|
||||
margin-top: 10px;
|
||||
}
|
||||
|
||||
/* -- admonitions ----------------------------------------------------------- */
|
||||
|
||||
div.admonition {
|
||||
margin-top: 10px;
|
||||
margin-bottom: 10px;
|
||||
padding: 7px;
|
||||
}
|
||||
|
||||
div.admonition dt {
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
div.admonition dl {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
p.admonition-title {
|
||||
margin: 0px 10px 5px 0px;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
div.body p.centered {
|
||||
text-align: center;
|
||||
margin-top: 25px;
|
||||
}
|
||||
|
||||
/* -- tables ---------------------------------------------------------------- */
|
||||
|
||||
table.docutils {
|
||||
border: 0;
|
||||
border-collapse: collapse;
|
||||
}
|
||||
|
||||
table caption span.caption-number {
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
table caption span.caption-text {
|
||||
}
|
||||
|
||||
table.docutils td, table.docutils th {
|
||||
padding: 1px 8px 1px 5px;
|
||||
border-top: 0;
|
||||
border-left: 0;
|
||||
border-right: 0;
|
||||
border-bottom: 1px solid #aaa;
|
||||
}
|
||||
|
||||
table.footnote td, table.footnote th {
|
||||
border: 0 !important;
|
||||
}
|
||||
|
||||
th {
|
||||
text-align: left;
|
||||
padding-right: 5px;
|
||||
}
|
||||
|
||||
table.citation {
|
||||
border-left: solid 1px gray;
|
||||
margin-left: 1px;
|
||||
}
|
||||
|
||||
table.citation td {
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
/* -- figures --------------------------------------------------------------- */
|
||||
|
||||
div.figure {
|
||||
margin: 0.5em;
|
||||
padding: 0.5em;
|
||||
}
|
||||
|
||||
div.figure p.caption {
|
||||
padding: 0.3em;
|
||||
}
|
||||
|
||||
div.figure p.caption span.caption-number {
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
div.figure p.caption span.caption-text {
|
||||
}
|
||||
|
||||
/* -- field list styles ----------------------------------------------------- */
|
||||
|
||||
table.field-list td, table.field-list th {
|
||||
border: 0 !important;
|
||||
}
|
||||
|
||||
.field-list ul {
|
||||
margin: 0;
|
||||
padding-left: 1em;
|
||||
}
|
||||
|
||||
.field-list p {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
/* -- other body styles ----------------------------------------------------- */
|
||||
|
||||
ol.arabic {
|
||||
list-style: decimal;
|
||||
}
|
||||
|
||||
ol.loweralpha {
|
||||
list-style: lower-alpha;
|
||||
}
|
||||
|
||||
ol.upperalpha {
|
||||
list-style: upper-alpha;
|
||||
}
|
||||
|
||||
ol.lowerroman {
|
||||
list-style: lower-roman;
|
||||
}
|
||||
|
||||
ol.upperroman {
|
||||
list-style: upper-roman;
|
||||
}
|
||||
|
||||
dl {
|
||||
margin-bottom: 15px;
|
||||
}
|
||||
|
||||
dd p {
|
||||
margin-top: 0px;
|
||||
}
|
||||
|
||||
dd ul, dd table {
|
||||
margin-bottom: 10px;
|
||||
}
|
||||
|
||||
dd {
|
||||
margin-top: 3px;
|
||||
margin-bottom: 10px;
|
||||
margin-left: 30px;
|
||||
}
|
||||
|
||||
dt:target, .highlighted {
|
||||
background-color: #fbe54e;
|
||||
}
|
||||
|
||||
dl.glossary dt {
|
||||
font-weight: bold;
|
||||
font-size: 1.1em;
|
||||
}
|
||||
|
||||
.optional {
|
||||
font-size: 1.3em;
|
||||
}
|
||||
|
||||
.sig-paren {
|
||||
font-size: larger;
|
||||
}
|
||||
|
||||
.versionmodified {
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
.system-message {
|
||||
background-color: #fda;
|
||||
padding: 5px;
|
||||
border: 3px solid red;
|
||||
}
|
||||
|
||||
.footnote:target {
|
||||
background-color: #ffa;
|
||||
}
|
||||
|
||||
.line-block {
|
||||
display: block;
|
||||
margin-top: 1em;
|
||||
margin-bottom: 1em;
|
||||
}
|
||||
|
||||
.line-block .line-block {
|
||||
margin-top: 0;
|
||||
margin-bottom: 0;
|
||||
margin-left: 1.5em;
|
||||
}
|
||||
|
||||
.guilabel, .menuselection {
|
||||
font-family: sans-serif;
|
||||
}
|
||||
|
||||
.accelerator {
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
.classifier {
|
||||
font-style: oblique;
|
||||
}
|
||||
|
||||
abbr, acronym {
|
||||
border-bottom: dotted 1px;
|
||||
cursor: help;
|
||||
}
|
||||
|
||||
/* -- code displays --------------------------------------------------------- */
|
||||
|
||||
pre {
|
||||
overflow: auto;
|
||||
overflow-y: hidden; /* fixes display issues on Chrome browsers */
|
||||
}
|
||||
|
||||
span.pre {
|
||||
-moz-hyphens: none;
|
||||
-ms-hyphens: none;
|
||||
-webkit-hyphens: none;
|
||||
hyphens: none;
|
||||
}
|
||||
|
||||
td.linenos pre {
|
||||
padding: 5px 0px;
|
||||
border: 0;
|
||||
background-color: transparent;
|
||||
color: #aaa;
|
||||
}
|
||||
|
||||
table.highlighttable {
|
||||
margin-left: 0.5em;
|
||||
}
|
||||
|
||||
table.highlighttable td {
|
||||
padding: 0 0.5em 0 0.5em;
|
||||
}
|
||||
|
||||
div.code-block-caption {
|
||||
padding: 2px 5px;
|
||||
font-size: small;
|
||||
}
|
||||
|
||||
div.code-block-caption code {
|
||||
background-color: transparent;
|
||||
}
|
||||
|
||||
div.code-block-caption + div > div.highlight > pre {
|
||||
margin-top: 0;
|
||||
}
|
||||
|
||||
div.code-block-caption span.caption-number {
|
||||
padding: 0.1em 0.3em;
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
div.code-block-caption span.caption-text {
|
||||
}
|
||||
|
||||
div.literal-block-wrapper {
|
||||
padding: 1em 1em 0;
|
||||
}
|
||||
|
||||
div.literal-block-wrapper div.highlight {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
code.descname {
|
||||
background-color: transparent;
|
||||
font-weight: bold;
|
||||
font-size: 1.2em;
|
||||
}
|
||||
|
||||
code.descclassname {
|
||||
background-color: transparent;
|
||||
}
|
||||
|
||||
code.xref, a code {
|
||||
background-color: transparent;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
h1 code, h2 code, h3 code, h4 code, h5 code, h6 code {
|
||||
background-color: transparent;
|
||||
}
|
||||
|
||||
.viewcode-link {
|
||||
float: right;
|
||||
}
|
||||
|
||||
.viewcode-back {
|
||||
float: right;
|
||||
font-family: sans-serif;
|
||||
}
|
||||
|
||||
div.viewcode-block:target {
|
||||
margin: -1px -10px;
|
||||
padding: 0 10px;
|
||||
}
|
||||
|
||||
/* -- math display ---------------------------------------------------------- */
|
||||
|
||||
img.math {
|
||||
vertical-align: middle;
|
||||
}
|
||||
|
||||
div.body div.math p {
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
span.eqno {
|
||||
float: right;
|
||||
}
|
||||
|
||||
span.eqno a.headerlink {
|
||||
position: relative;
|
||||
left: 0px;
|
||||
z-index: 1;
|
||||
}
|
||||
|
||||
div.math:hover a.headerlink {
|
||||
visibility: visible;
|
||||
}
|
||||
|
||||
/* -- printout stylesheet --------------------------------------------------- */
|
||||
|
||||
@media print {
|
||||
div.document,
|
||||
div.documentwrapper,
|
||||
div.bodywrapper {
|
||||
margin: 0 !important;
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
div.sphinxsidebar,
|
||||
div.related,
|
||||
div.footer,
|
||||
#top-link {
|
||||
display: none;
|
||||
}
|
||||
}
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 756 B |
Binary file not shown.
|
Before Width: | Height: | Size: 829 B |
Binary file not shown.
|
Before Width: | Height: | Size: 641 B |
@ -1 +0,0 @@
|
||||
/* This file intentionally left blank. */
|
||||
@ -1,287 +0,0 @@
|
||||
/*
|
||||
* doctools.js
|
||||
* ~~~~~~~~~~~
|
||||
*
|
||||
* Sphinx JavaScript utilities for all documentation.
|
||||
*
|
||||
* :copyright: Copyright 2007-2016 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
/**
|
||||
* select a different prefix for underscore
|
||||
*/
|
||||
$u = _.noConflict();
|
||||
|
||||
/**
|
||||
* make the code below compatible with browsers without
|
||||
* an installed firebug like debugger
|
||||
if (!window.console || !console.firebug) {
|
||||
var names = ["log", "debug", "info", "warn", "error", "assert", "dir",
|
||||
"dirxml", "group", "groupEnd", "time", "timeEnd", "count", "trace",
|
||||
"profile", "profileEnd"];
|
||||
window.console = {};
|
||||
for (var i = 0; i < names.length; ++i)
|
||||
window.console[names[i]] = function() {};
|
||||
}
|
||||
*/
|
||||
|
||||
/**
|
||||
* small helper function to urldecode strings
|
||||
*/
|
||||
jQuery.urldecode = function(x) {
|
||||
return decodeURIComponent(x).replace(/\+/g, ' ');
|
||||
};
|
||||
|
||||
/**
|
||||
* small helper function to urlencode strings
|
||||
*/
|
||||
jQuery.urlencode = encodeURIComponent;
|
||||
|
||||
/**
|
||||
* This function returns the parsed url parameters of the
|
||||
* current request. Multiple values per key are supported,
|
||||
* it will always return arrays of strings for the value parts.
|
||||
*/
|
||||
jQuery.getQueryParameters = function(s) {
|
||||
if (typeof s == 'undefined')
|
||||
s = document.location.search;
|
||||
var parts = s.substr(s.indexOf('?') + 1).split('&');
|
||||
var result = {};
|
||||
for (var i = 0; i < parts.length; i++) {
|
||||
var tmp = parts[i].split('=', 2);
|
||||
var key = jQuery.urldecode(tmp[0]);
|
||||
var value = jQuery.urldecode(tmp[1]);
|
||||
if (key in result)
|
||||
result[key].push(value);
|
||||
else
|
||||
result[key] = [value];
|
||||
}
|
||||
return result;
|
||||
};
|
||||
|
||||
/**
|
||||
* highlight a given string on a jquery object by wrapping it in
|
||||
* span elements with the given class name.
|
||||
*/
|
||||
jQuery.fn.highlightText = function(text, className) {
|
||||
function highlight(node) {
|
||||
if (node.nodeType == 3) {
|
||||
var val = node.nodeValue;
|
||||
var pos = val.toLowerCase().indexOf(text);
|
||||
if (pos >= 0 && !jQuery(node.parentNode).hasClass(className)) {
|
||||
var span = document.createElement("span");
|
||||
span.className = className;
|
||||
span.appendChild(document.createTextNode(val.substr(pos, text.length)));
|
||||
node.parentNode.insertBefore(span, node.parentNode.insertBefore(
|
||||
document.createTextNode(val.substr(pos + text.length)),
|
||||
node.nextSibling));
|
||||
node.nodeValue = val.substr(0, pos);
|
||||
}
|
||||
}
|
||||
else if (!jQuery(node).is("button, select, textarea")) {
|
||||
jQuery.each(node.childNodes, function() {
|
||||
highlight(this);
|
||||
});
|
||||
}
|
||||
}
|
||||
return this.each(function() {
|
||||
highlight(this);
|
||||
});
|
||||
};
|
||||
|
||||
/*
|
||||
* backward compatibility for jQuery.browser
|
||||
* This will be supported until firefox bug is fixed.
|
||||
*/
|
||||
if (!jQuery.browser) {
|
||||
jQuery.uaMatch = function(ua) {
|
||||
ua = ua.toLowerCase();
|
||||
|
||||
var match = /(chrome)[ \/]([\w.]+)/.exec(ua) ||
|
||||
/(webkit)[ \/]([\w.]+)/.exec(ua) ||
|
||||
/(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) ||
|
||||
/(msie) ([\w.]+)/.exec(ua) ||
|
||||
ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) ||
|
||||
[];
|
||||
|
||||
return {
|
||||
browser: match[ 1 ] || "",
|
||||
version: match[ 2 ] || "0"
|
||||
};
|
||||
};
|
||||
jQuery.browser = {};
|
||||
jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Small JavaScript module for the documentation.
|
||||
*/
|
||||
var Documentation = {
|
||||
|
||||
init : function() {
|
||||
this.fixFirefoxAnchorBug();
|
||||
this.highlightSearchWords();
|
||||
this.initIndexTable();
|
||||
|
||||
},
|
||||
|
||||
/**
|
||||
* i18n support
|
||||
*/
|
||||
TRANSLATIONS : {},
|
||||
PLURAL_EXPR : function(n) { return n == 1 ? 0 : 1; },
|
||||
LOCALE : 'unknown',
|
||||
|
||||
// gettext and ngettext don't access this so that the functions
|
||||
// can safely bound to a different name (_ = Documentation.gettext)
|
||||
gettext : function(string) {
|
||||
var translated = Documentation.TRANSLATIONS[string];
|
||||
if (typeof translated == 'undefined')
|
||||
return string;
|
||||
return (typeof translated == 'string') ? translated : translated[0];
|
||||
},
|
||||
|
||||
ngettext : function(singular, plural, n) {
|
||||
var translated = Documentation.TRANSLATIONS[singular];
|
||||
if (typeof translated == 'undefined')
|
||||
return (n == 1) ? singular : plural;
|
||||
return translated[Documentation.PLURALEXPR(n)];
|
||||
},
|
||||
|
||||
addTranslations : function(catalog) {
|
||||
for (var key in catalog.messages)
|
||||
this.TRANSLATIONS[key] = catalog.messages[key];
|
||||
this.PLURAL_EXPR = new Function('n', 'return +(' + catalog.plural_expr + ')');
|
||||
this.LOCALE = catalog.locale;
|
||||
},
|
||||
|
||||
/**
|
||||
* add context elements like header anchor links
|
||||
*/
|
||||
addContextElements : function() {
|
||||
$('div[id] > :header:first').each(function() {
|
||||
$('<a class="headerlink">\u00B6</a>').
|
||||
attr('href', '#' + this.id).
|
||||
attr('title', _('Permalink to this headline')).
|
||||
appendTo(this);
|
||||
});
|
||||
$('dt[id]').each(function() {
|
||||
$('<a class="headerlink">\u00B6</a>').
|
||||
attr('href', '#' + this.id).
|
||||
attr('title', _('Permalink to this definition')).
|
||||
appendTo(this);
|
||||
});
|
||||
},
|
||||
|
||||
/**
|
||||
* workaround a firefox stupidity
|
||||
* see: https://bugzilla.mozilla.org/show_bug.cgi?id=645075
|
||||
*/
|
||||
fixFirefoxAnchorBug : function() {
|
||||
if (document.location.hash)
|
||||
window.setTimeout(function() {
|
||||
document.location.href += '';
|
||||
}, 10);
|
||||
},
|
||||
|
||||
/**
|
||||
* highlight the search words provided in the url in the text
|
||||
*/
|
||||
highlightSearchWords : function() {
|
||||
var params = $.getQueryParameters();
|
||||
var terms = (params.highlight) ? params.highlight[0].split(/\s+/) : [];
|
||||
if (terms.length) {
|
||||
var body = $('div.body');
|
||||
if (!body.length) {
|
||||
body = $('body');
|
||||
}
|
||||
window.setTimeout(function() {
|
||||
$.each(terms, function() {
|
||||
body.highlightText(this.toLowerCase(), 'highlighted');
|
||||
});
|
||||
}, 10);
|
||||
$('<p class="highlight-link"><a href="javascript:Documentation.' +
|
||||
'hideSearchWords()">' + _('Hide Search Matches') + '</a></p>')
|
||||
.appendTo($('#searchbox'));
|
||||
}
|
||||
},
|
||||
|
||||
/**
|
||||
* init the domain index toggle buttons
|
||||
*/
|
||||
initIndexTable : function() {
|
||||
var togglers = $('img.toggler').click(function() {
|
||||
var src = $(this).attr('src');
|
||||
var idnum = $(this).attr('id').substr(7);
|
||||
$('tr.cg-' + idnum).toggle();
|
||||
if (src.substr(-9) == 'minus.png')
|
||||
$(this).attr('src', src.substr(0, src.length-9) + 'plus.png');
|
||||
else
|
||||
$(this).attr('src', src.substr(0, src.length-8) + 'minus.png');
|
||||
}).css('display', '');
|
||||
if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) {
|
||||
togglers.click();
|
||||
}
|
||||
},
|
||||
|
||||
/**
|
||||
* helper function to hide the search marks again
|
||||
*/
|
||||
hideSearchWords : function() {
|
||||
$('#searchbox .highlight-link').fadeOut(300);
|
||||
$('span.highlighted').removeClass('highlighted');
|
||||
},
|
||||
|
||||
/**
|
||||
* make the url absolute
|
||||
*/
|
||||
makeURL : function(relativeURL) {
|
||||
return DOCUMENTATION_OPTIONS.URL_ROOT + '/' + relativeURL;
|
||||
},
|
||||
|
||||
/**
|
||||
* get the current relative url
|
||||
*/
|
||||
getCurrentURL : function() {
|
||||
var path = document.location.pathname;
|
||||
var parts = path.split(/\//);
|
||||
$.each(DOCUMENTATION_OPTIONS.URL_ROOT.split(/\//), function() {
|
||||
if (this == '..')
|
||||
parts.pop();
|
||||
});
|
||||
var url = parts.join('/');
|
||||
return path.substring(url.lastIndexOf('/') + 1, path.length - 1);
|
||||
},
|
||||
|
||||
initOnKeyListeners: function() {
|
||||
$(document).keyup(function(event) {
|
||||
var activeElementType = document.activeElement.tagName;
|
||||
// don't navigate when in search box or textarea
|
||||
if (activeElementType !== 'TEXTAREA' && activeElementType !== 'INPUT' && activeElementType !== 'SELECT') {
|
||||
switch (event.keyCode) {
|
||||
case 37: // left
|
||||
var prevHref = $('link[rel="prev"]').prop('href');
|
||||
if (prevHref) {
|
||||
window.location.href = prevHref;
|
||||
return false;
|
||||
}
|
||||
case 39: // right
|
||||
var nextHref = $('link[rel="next"]').prop('href');
|
||||
if (nextHref) {
|
||||
window.location.href = nextHref;
|
||||
return false;
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
};
|
||||
|
||||
// quick alias for translations
|
||||
_ = Documentation.gettext;
|
||||
|
||||
$(document).ready(function() {
|
||||
Documentation.init();
|
||||
});
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 222 B |
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|
Before Width: | Height: | Size: 202 B |
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|
Before Width: | Height: | Size: 286 B |
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File diff suppressed because one or more lines are too long
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|
Before Width: | Height: | Size: 90 B |
Binary file not shown.
|
Before Width: | Height: | Size: 90 B |
@ -1,65 +0,0 @@
|
||||
.highlight .hll { background-color: #ffffcc }
|
||||
.highlight { background: #eeffcc; }
|
||||
.highlight .c { color: #408090; font-style: italic } /* Comment */
|
||||
.highlight .err { border: 1px solid #FF0000 } /* Error */
|
||||
.highlight .k { color: #007020; font-weight: bold } /* Keyword */
|
||||
.highlight .o { color: #666666 } /* Operator */
|
||||
.highlight .ch { color: #408090; font-style: italic } /* Comment.Hashbang */
|
||||
.highlight .cm { color: #408090; font-style: italic } /* Comment.Multiline */
|
||||
.highlight .cp { color: #007020 } /* Comment.Preproc */
|
||||
.highlight .cpf { color: #408090; font-style: italic } /* Comment.PreprocFile */
|
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.highlight .c1 { color: #408090; font-style: italic } /* Comment.Single */
|
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.highlight .cs { color: #408090; background-color: #fff0f0 } /* Comment.Special */
|
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.highlight .gd { color: #A00000 } /* Generic.Deleted */
|
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.highlight .ge { font-style: italic } /* Generic.Emph */
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.highlight .gr { color: #FF0000 } /* Generic.Error */
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.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
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.highlight .gi { color: #00A000 } /* Generic.Inserted */
|
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.highlight .go { color: #333333 } /* Generic.Output */
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.highlight .gp { color: #c65d09; font-weight: bold } /* Generic.Prompt */
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||||
.highlight .gs { font-weight: bold } /* Generic.Strong */
|
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.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
|
||||
.highlight .gt { color: #0044DD } /* Generic.Traceback */
|
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.highlight .kc { color: #007020; font-weight: bold } /* Keyword.Constant */
|
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.highlight .kd { color: #007020; font-weight: bold } /* Keyword.Declaration */
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.highlight .kn { color: #007020; font-weight: bold } /* Keyword.Namespace */
|
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.highlight .kp { color: #007020 } /* Keyword.Pseudo */
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.highlight .kr { color: #007020; font-weight: bold } /* Keyword.Reserved */
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.highlight .kt { color: #902000 } /* Keyword.Type */
|
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.highlight .m { color: #208050 } /* Literal.Number */
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.highlight .s { color: #4070a0 } /* Literal.String */
|
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.highlight .na { color: #4070a0 } /* Name.Attribute */
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.highlight .nb { color: #007020 } /* Name.Builtin */
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.highlight .nc { color: #0e84b5; font-weight: bold } /* Name.Class */
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.highlight .no { color: #60add5 } /* Name.Constant */
|
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.highlight .nd { color: #555555; font-weight: bold } /* Name.Decorator */
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.highlight .ni { color: #d55537; font-weight: bold } /* Name.Entity */
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.highlight .ne { color: #007020 } /* Name.Exception */
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.highlight .nf { color: #06287e } /* Name.Function */
|
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.highlight .nl { color: #002070; font-weight: bold } /* Name.Label */
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.highlight .nn { color: #0e84b5; font-weight: bold } /* Name.Namespace */
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.highlight .nt { color: #062873; font-weight: bold } /* Name.Tag */
|
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.highlight .nv { color: #bb60d5 } /* Name.Variable */
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.highlight .ow { color: #007020; font-weight: bold } /* Operator.Word */
|
||||
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
|
||||
.highlight .mb { color: #208050 } /* Literal.Number.Bin */
|
||||
.highlight .mf { color: #208050 } /* Literal.Number.Float */
|
||||
.highlight .mh { color: #208050 } /* Literal.Number.Hex */
|
||||
.highlight .mi { color: #208050 } /* Literal.Number.Integer */
|
||||
.highlight .mo { color: #208050 } /* Literal.Number.Oct */
|
||||
.highlight .sb { color: #4070a0 } /* Literal.String.Backtick */
|
||||
.highlight .sc { color: #4070a0 } /* Literal.String.Char */
|
||||
.highlight .sd { color: #4070a0; font-style: italic } /* Literal.String.Doc */
|
||||
.highlight .s2 { color: #4070a0 } /* Literal.String.Double */
|
||||
.highlight .se { color: #4070a0; font-weight: bold } /* Literal.String.Escape */
|
||||
.highlight .sh { color: #4070a0 } /* Literal.String.Heredoc */
|
||||
.highlight .si { color: #70a0d0; font-style: italic } /* Literal.String.Interpol */
|
||||
.highlight .sx { color: #c65d09 } /* Literal.String.Other */
|
||||
.highlight .sr { color: #235388 } /* Literal.String.Regex */
|
||||
.highlight .s1 { color: #4070a0 } /* Literal.String.Single */
|
||||
.highlight .ss { color: #517918 } /* Literal.String.Symbol */
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||||
.highlight .bp { color: #007020 } /* Name.Builtin.Pseudo */
|
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.highlight .vc { color: #bb60d5 } /* Name.Variable.Class */
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.highlight .vg { color: #bb60d5 } /* Name.Variable.Global */
|
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.highlight .vi { color: #bb60d5 } /* Name.Variable.Instance */
|
||||
.highlight .il { color: #208050 } /* Literal.Number.Integer.Long */
|
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@ -1,758 +0,0 @@
|
||||
/*
|
||||
* searchtools.js_t
|
||||
* ~~~~~~~~~~~~~~~~
|
||||
*
|
||||
* Sphinx JavaScript utilities for the full-text search.
|
||||
*
|
||||
* :copyright: Copyright 2007-2016 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
|
||||
/* Non-minified version JS is _stemmer.js if file is provided */
|
||||
/**
|
||||
* Porter Stemmer
|
||||
*/
|
||||
var Stemmer = function() {
|
||||
|
||||
var step2list = {
|
||||
ational: 'ate',
|
||||
tional: 'tion',
|
||||
enci: 'ence',
|
||||
anci: 'ance',
|
||||
izer: 'ize',
|
||||
bli: 'ble',
|
||||
alli: 'al',
|
||||
entli: 'ent',
|
||||
eli: 'e',
|
||||
ousli: 'ous',
|
||||
ization: 'ize',
|
||||
ation: 'ate',
|
||||
ator: 'ate',
|
||||
alism: 'al',
|
||||
iveness: 'ive',
|
||||
fulness: 'ful',
|
||||
ousness: 'ous',
|
||||
aliti: 'al',
|
||||
iviti: 'ive',
|
||||
biliti: 'ble',
|
||||
logi: 'log'
|
||||
};
|
||||
|
||||
var step3list = {
|
||||
icate: 'ic',
|
||||
ative: '',
|
||||
alize: 'al',
|
||||
iciti: 'ic',
|
||||
ical: 'ic',
|
||||
ful: '',
|
||||
ness: ''
|
||||
};
|
||||
|
||||
var c = "[^aeiou]"; // consonant
|
||||
var v = "[aeiouy]"; // vowel
|
||||
var C = c + "[^aeiouy]*"; // consonant sequence
|
||||
var V = v + "[aeiou]*"; // vowel sequence
|
||||
|
||||
var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0
|
||||
var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1
|
||||
var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1
|
||||
var s_v = "^(" + C + ")?" + v; // vowel in stem
|
||||
|
||||
this.stemWord = function (w) {
|
||||
var stem;
|
||||
var suffix;
|
||||
var firstch;
|
||||
var origword = w;
|
||||
|
||||
if (w.length < 3)
|
||||
return w;
|
||||
|
||||
var re;
|
||||
var re2;
|
||||
var re3;
|
||||
var re4;
|
||||
|
||||
firstch = w.substr(0,1);
|
||||
if (firstch == "y")
|
||||
w = firstch.toUpperCase() + w.substr(1);
|
||||
|
||||
// Step 1a
|
||||
re = /^(.+?)(ss|i)es$/;
|
||||
re2 = /^(.+?)([^s])s$/;
|
||||
|
||||
if (re.test(w))
|
||||
w = w.replace(re,"$1$2");
|
||||
else if (re2.test(w))
|
||||
w = w.replace(re2,"$1$2");
|
||||
|
||||
// Step 1b
|
||||
re = /^(.+?)eed$/;
|
||||
re2 = /^(.+?)(ed|ing)$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
re = new RegExp(mgr0);
|
||||
if (re.test(fp[1])) {
|
||||
re = /.$/;
|
||||
w = w.replace(re,"");
|
||||
}
|
||||
}
|
||||
else if (re2.test(w)) {
|
||||
var fp = re2.exec(w);
|
||||
stem = fp[1];
|
||||
re2 = new RegExp(s_v);
|
||||
if (re2.test(stem)) {
|
||||
w = stem;
|
||||
re2 = /(at|bl|iz)$/;
|
||||
re3 = new RegExp("([^aeiouylsz])\\1$");
|
||||
re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
|
||||
if (re2.test(w))
|
||||
w = w + "e";
|
||||
else if (re3.test(w)) {
|
||||
re = /.$/;
|
||||
w = w.replace(re,"");
|
||||
}
|
||||
else if (re4.test(w))
|
||||
w = w + "e";
|
||||
}
|
||||
}
|
||||
|
||||
// Step 1c
|
||||
re = /^(.+?)y$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
re = new RegExp(s_v);
|
||||
if (re.test(stem))
|
||||
w = stem + "i";
|
||||
}
|
||||
|
||||
// Step 2
|
||||
re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
suffix = fp[2];
|
||||
re = new RegExp(mgr0);
|
||||
if (re.test(stem))
|
||||
w = stem + step2list[suffix];
|
||||
}
|
||||
|
||||
// Step 3
|
||||
re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
suffix = fp[2];
|
||||
re = new RegExp(mgr0);
|
||||
if (re.test(stem))
|
||||
w = stem + step3list[suffix];
|
||||
}
|
||||
|
||||
// Step 4
|
||||
re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
|
||||
re2 = /^(.+?)(s|t)(ion)$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
re = new RegExp(mgr1);
|
||||
if (re.test(stem))
|
||||
w = stem;
|
||||
}
|
||||
else if (re2.test(w)) {
|
||||
var fp = re2.exec(w);
|
||||
stem = fp[1] + fp[2];
|
||||
re2 = new RegExp(mgr1);
|
||||
if (re2.test(stem))
|
||||
w = stem;
|
||||
}
|
||||
|
||||
// Step 5
|
||||
re = /^(.+?)e$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
re = new RegExp(mgr1);
|
||||
re2 = new RegExp(meq1);
|
||||
re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
|
||||
if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
|
||||
w = stem;
|
||||
}
|
||||
re = /ll$/;
|
||||
re2 = new RegExp(mgr1);
|
||||
if (re.test(w) && re2.test(w)) {
|
||||
re = /.$/;
|
||||
w = w.replace(re,"");
|
||||
}
|
||||
|
||||
// and turn initial Y back to y
|
||||
if (firstch == "y")
|
||||
w = firstch.toLowerCase() + w.substr(1);
|
||||
return w;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
/**
|
||||
* Simple result scoring code.
|
||||
*/
|
||||
var Scorer = {
|
||||
// Implement the following function to further tweak the score for each result
|
||||
// The function takes a result array [filename, title, anchor, descr, score]
|
||||
// and returns the new score.
|
||||
/*
|
||||
score: function(result) {
|
||||
return result[4];
|
||||
},
|
||||
*/
|
||||
|
||||
// query matches the full name of an object
|
||||
objNameMatch: 11,
|
||||
// or matches in the last dotted part of the object name
|
||||
objPartialMatch: 6,
|
||||
// Additive scores depending on the priority of the object
|
||||
objPrio: {0: 15, // used to be importantResults
|
||||
1: 5, // used to be objectResults
|
||||
2: -5}, // used to be unimportantResults
|
||||
// Used when the priority is not in the mapping.
|
||||
objPrioDefault: 0,
|
||||
|
||||
// query found in title
|
||||
title: 15,
|
||||
// query found in terms
|
||||
term: 5
|
||||
};
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
var splitChars = (function() {
|
||||
var result = {};
|
||||
var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648,
|
||||
1748, 1809, 2416, 2473, 2481, 2526, 2601, 2609, 2612, 2615, 2653, 2702,
|
||||
2706, 2729, 2737, 2740, 2857, 2865, 2868, 2910, 2928, 2948, 2961, 2971,
|
||||
2973, 3085, 3089, 3113, 3124, 3213, 3217, 3241, 3252, 3295, 3341, 3345,
|
||||
3369, 3506, 3516, 3633, 3715, 3721, 3736, 3744, 3748, 3750, 3756, 3761,
|
||||
3781, 3912, 4239, 4347, 4681, 4695, 4697, 4745, 4785, 4799, 4801, 4823,
|
||||
4881, 5760, 5901, 5997, 6313, 7405, 8024, 8026, 8028, 8030, 8117, 8125,
|
||||
8133, 8181, 8468, 8485, 8487, 8489, 8494, 8527, 11311, 11359, 11687, 11695,
|
||||
11703, 11711, 11719, 11727, 11735, 12448, 12539, 43010, 43014, 43019, 43587,
|
||||
43696, 43713, 64286, 64297, 64311, 64317, 64319, 64322, 64325, 65141];
|
||||
var i, j, start, end;
|
||||
for (i = 0; i < singles.length; i++) {
|
||||
result[singles[i]] = true;
|
||||
}
|
||||
var ranges = [[0, 47], [58, 64], [91, 94], [123, 169], [171, 177], [182, 184], [706, 709],
|
||||
[722, 735], [741, 747], [751, 879], [888, 889], [894, 901], [1154, 1161],
|
||||
[1318, 1328], [1367, 1368], [1370, 1376], [1416, 1487], [1515, 1519], [1523, 1568],
|
||||
[1611, 1631], [1642, 1645], [1750, 1764], [1767, 1773], [1789, 1790], [1792, 1807],
|
||||
[1840, 1868], [1958, 1968], [1970, 1983], [2027, 2035], [2038, 2041], [2043, 2047],
|
||||
[2070, 2073], [2075, 2083], [2085, 2087], [2089, 2307], [2362, 2364], [2366, 2383],
|
||||
[2385, 2391], [2402, 2405], [2419, 2424], [2432, 2436], [2445, 2446], [2449, 2450],
|
||||
[2483, 2485], [2490, 2492], [2494, 2509], [2511, 2523], [2530, 2533], [2546, 2547],
|
||||
[2554, 2564], [2571, 2574], [2577, 2578], [2618, 2648], [2655, 2661], [2672, 2673],
|
||||
[2677, 2692], [2746, 2748], [2750, 2767], [2769, 2783], [2786, 2789], [2800, 2820],
|
||||
[2829, 2830], [2833, 2834], [2874, 2876], [2878, 2907], [2914, 2917], [2930, 2946],
|
||||
[2955, 2957], [2966, 2968], [2976, 2978], [2981, 2983], [2987, 2989], [3002, 3023],
|
||||
[3025, 3045], [3059, 3076], [3130, 3132], [3134, 3159], [3162, 3167], [3170, 3173],
|
||||
[3184, 3191], [3199, 3204], [3258, 3260], [3262, 3293], [3298, 3301], [3312, 3332],
|
||||
[3386, 3388], [3390, 3423], [3426, 3429], [3446, 3449], [3456, 3460], [3479, 3481],
|
||||
[3518, 3519], [3527, 3584], [3636, 3647], [3655, 3663], [3674, 3712], [3717, 3718],
|
||||
[3723, 3724], [3726, 3731], [3752, 3753], [3764, 3772], [3774, 3775], [3783, 3791],
|
||||
[3802, 3803], [3806, 3839], [3841, 3871], [3892, 3903], [3949, 3975], [3980, 4095],
|
||||
[4139, 4158], [4170, 4175], [4182, 4185], [4190, 4192], [4194, 4196], [4199, 4205],
|
||||
[4209, 4212], [4226, 4237], [4250, 4255], [4294, 4303], [4349, 4351], [4686, 4687],
|
||||
[4702, 4703], [4750, 4751], [4790, 4791], [4806, 4807], [4886, 4887], [4955, 4968],
|
||||
[4989, 4991], [5008, 5023], [5109, 5120], [5741, 5742], [5787, 5791], [5867, 5869],
|
||||
[5873, 5887], [5906, 5919], [5938, 5951], [5970, 5983], [6001, 6015], [6068, 6102],
|
||||
[6104, 6107], [6109, 6111], [6122, 6127], [6138, 6159], [6170, 6175], [6264, 6271],
|
||||
[6315, 6319], [6390, 6399], [6429, 6469], [6510, 6511], [6517, 6527], [6572, 6592],
|
||||
[6600, 6607], [6619, 6655], [6679, 6687], [6741, 6783], [6794, 6799], [6810, 6822],
|
||||
[6824, 6916], [6964, 6980], [6988, 6991], [7002, 7042], [7073, 7085], [7098, 7167],
|
||||
[7204, 7231], [7242, 7244], [7294, 7400], [7410, 7423], [7616, 7679], [7958, 7959],
|
||||
[7966, 7967], [8006, 8007], [8014, 8015], [8062, 8063], [8127, 8129], [8141, 8143],
|
||||
[8148, 8149], [8156, 8159], [8173, 8177], [8189, 8303], [8306, 8307], [8314, 8318],
|
||||
[8330, 8335], [8341, 8449], [8451, 8454], [8456, 8457], [8470, 8472], [8478, 8483],
|
||||
[8506, 8507], [8512, 8516], [8522, 8525], [8586, 9311], [9372, 9449], [9472, 10101],
|
||||
[10132, 11263], [11493, 11498], [11503, 11516], [11518, 11519], [11558, 11567],
|
||||
[11622, 11630], [11632, 11647], [11671, 11679], [11743, 11822], [11824, 12292],
|
||||
[12296, 12320], [12330, 12336], [12342, 12343], [12349, 12352], [12439, 12444],
|
||||
[12544, 12548], [12590, 12592], [12687, 12689], [12694, 12703], [12728, 12783],
|
||||
[12800, 12831], [12842, 12880], [12896, 12927], [12938, 12976], [12992, 13311],
|
||||
[19894, 19967], [40908, 40959], [42125, 42191], [42238, 42239], [42509, 42511],
|
||||
[42540, 42559], [42592, 42593], [42607, 42622], [42648, 42655], [42736, 42774],
|
||||
[42784, 42785], [42889, 42890], [42893, 43002], [43043, 43055], [43062, 43071],
|
||||
[43124, 43137], [43188, 43215], [43226, 43249], [43256, 43258], [43260, 43263],
|
||||
[43302, 43311], [43335, 43359], [43389, 43395], [43443, 43470], [43482, 43519],
|
||||
[43561, 43583], [43596, 43599], [43610, 43615], [43639, 43641], [43643, 43647],
|
||||
[43698, 43700], [43703, 43704], [43710, 43711], [43715, 43738], [43742, 43967],
|
||||
[44003, 44015], [44026, 44031], [55204, 55215], [55239, 55242], [55292, 55295],
|
||||
[57344, 63743], [64046, 64047], [64110, 64111], [64218, 64255], [64263, 64274],
|
||||
[64280, 64284], [64434, 64466], [64830, 64847], [64912, 64913], [64968, 65007],
|
||||
[65020, 65135], [65277, 65295], [65306, 65312], [65339, 65344], [65371, 65381],
|
||||
[65471, 65473], [65480, 65481], [65488, 65489], [65496, 65497]];
|
||||
for (i = 0; i < ranges.length; i++) {
|
||||
start = ranges[i][0];
|
||||
end = ranges[i][1];
|
||||
for (j = start; j <= end; j++) {
|
||||
result[j] = true;
|
||||
}
|
||||
}
|
||||
return result;
|
||||
})();
|
||||
|
||||
function splitQuery(query) {
|
||||
var result = [];
|
||||
var start = -1;
|
||||
for (var i = 0; i < query.length; i++) {
|
||||
if (splitChars[query.charCodeAt(i)]) {
|
||||
if (start !== -1) {
|
||||
result.push(query.slice(start, i));
|
||||
start = -1;
|
||||
}
|
||||
} else if (start === -1) {
|
||||
start = i;
|
||||
}
|
||||
}
|
||||
if (start !== -1) {
|
||||
result.push(query.slice(start));
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
/**
|
||||
* Search Module
|
||||
*/
|
||||
var Search = {
|
||||
|
||||
_index : null,
|
||||
_queued_query : null,
|
||||
_pulse_status : -1,
|
||||
|
||||
init : function() {
|
||||
var params = $.getQueryParameters();
|
||||
if (params.q) {
|
||||
var query = params.q[0];
|
||||
$('input[name="q"]')[0].value = query;
|
||||
this.performSearch(query);
|
||||
}
|
||||
},
|
||||
|
||||
loadIndex : function(url) {
|
||||
$.ajax({type: "GET", url: url, data: null,
|
||||
dataType: "script", cache: true,
|
||||
complete: function(jqxhr, textstatus) {
|
||||
if (textstatus != "success") {
|
||||
document.getElementById("searchindexloader").src = url;
|
||||
}
|
||||
}});
|
||||
},
|
||||
|
||||
setIndex : function(index) {
|
||||
var q;
|
||||
this._index = index;
|
||||
if ((q = this._queued_query) !== null) {
|
||||
this._queued_query = null;
|
||||
Search.query(q);
|
||||
}
|
||||
},
|
||||
|
||||
hasIndex : function() {
|
||||
return this._index !== null;
|
||||
},
|
||||
|
||||
deferQuery : function(query) {
|
||||
this._queued_query = query;
|
||||
},
|
||||
|
||||
stopPulse : function() {
|
||||
this._pulse_status = 0;
|
||||
},
|
||||
|
||||
startPulse : function() {
|
||||
if (this._pulse_status >= 0)
|
||||
return;
|
||||
function pulse() {
|
||||
var i;
|
||||
Search._pulse_status = (Search._pulse_status + 1) % 4;
|
||||
var dotString = '';
|
||||
for (i = 0; i < Search._pulse_status; i++)
|
||||
dotString += '.';
|
||||
Search.dots.text(dotString);
|
||||
if (Search._pulse_status > -1)
|
||||
window.setTimeout(pulse, 500);
|
||||
}
|
||||
pulse();
|
||||
},
|
||||
|
||||
/**
|
||||
* perform a search for something (or wait until index is loaded)
|
||||
*/
|
||||
performSearch : function(query) {
|
||||
// create the required interface elements
|
||||
this.out = $('#search-results');
|
||||
this.title = $('<h2>' + _('Searching') + '</h2>').appendTo(this.out);
|
||||
this.dots = $('<span></span>').appendTo(this.title);
|
||||
this.status = $('<p style="display: none"></p>').appendTo(this.out);
|
||||
this.output = $('<ul class="search"/>').appendTo(this.out);
|
||||
|
||||
$('#search-progress').text(_('Preparing search...'));
|
||||
this.startPulse();
|
||||
|
||||
// index already loaded, the browser was quick!
|
||||
if (this.hasIndex())
|
||||
this.query(query);
|
||||
else
|
||||
this.deferQuery(query);
|
||||
},
|
||||
|
||||
/**
|
||||
* execute search (requires search index to be loaded)
|
||||
*/
|
||||
query : function(query) {
|
||||
var i;
|
||||
var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"];
|
||||
|
||||
// stem the searchterms and add them to the correct list
|
||||
var stemmer = new Stemmer();
|
||||
var searchterms = [];
|
||||
var excluded = [];
|
||||
var hlterms = [];
|
||||
var tmp = splitQuery(query);
|
||||
var objectterms = [];
|
||||
for (i = 0; i < tmp.length; i++) {
|
||||
if (tmp[i] !== "") {
|
||||
objectterms.push(tmp[i].toLowerCase());
|
||||
}
|
||||
|
||||
if ($u.indexOf(stopwords, tmp[i].toLowerCase()) != -1 || tmp[i].match(/^\d+$/) ||
|
||||
tmp[i] === "") {
|
||||
// skip this "word"
|
||||
continue;
|
||||
}
|
||||
// stem the word
|
||||
var word = stemmer.stemWord(tmp[i].toLowerCase());
|
||||
// prevent stemmer from cutting word smaller than two chars
|
||||
if(word.length < 3 && tmp[i].length >= 3) {
|
||||
word = tmp[i];
|
||||
}
|
||||
var toAppend;
|
||||
// select the correct list
|
||||
if (word[0] == '-') {
|
||||
toAppend = excluded;
|
||||
word = word.substr(1);
|
||||
}
|
||||
else {
|
||||
toAppend = searchterms;
|
||||
hlterms.push(tmp[i].toLowerCase());
|
||||
}
|
||||
// only add if not already in the list
|
||||
if (!$u.contains(toAppend, word))
|
||||
toAppend.push(word);
|
||||
}
|
||||
var highlightstring = '?highlight=' + $.urlencode(hlterms.join(" "));
|
||||
|
||||
// console.debug('SEARCH: searching for:');
|
||||
// console.info('required: ', searchterms);
|
||||
// console.info('excluded: ', excluded);
|
||||
|
||||
// prepare search
|
||||
var terms = this._index.terms;
|
||||
var titleterms = this._index.titleterms;
|
||||
|
||||
// array of [filename, title, anchor, descr, score]
|
||||
var results = [];
|
||||
$('#search-progress').empty();
|
||||
|
||||
// lookup as object
|
||||
for (i = 0; i < objectterms.length; i++) {
|
||||
var others = [].concat(objectterms.slice(0, i),
|
||||
objectterms.slice(i+1, objectterms.length));
|
||||
results = results.concat(this.performObjectSearch(objectterms[i], others));
|
||||
}
|
||||
|
||||
// lookup as search terms in fulltext
|
||||
results = results.concat(this.performTermsSearch(searchterms, excluded, terms, titleterms));
|
||||
|
||||
// let the scorer override scores with a custom scoring function
|
||||
if (Scorer.score) {
|
||||
for (i = 0; i < results.length; i++)
|
||||
results[i][4] = Scorer.score(results[i]);
|
||||
}
|
||||
|
||||
// now sort the results by score (in opposite order of appearance, since the
|
||||
// display function below uses pop() to retrieve items) and then
|
||||
// alphabetically
|
||||
results.sort(function(a, b) {
|
||||
var left = a[4];
|
||||
var right = b[4];
|
||||
if (left > right) {
|
||||
return 1;
|
||||
} else if (left < right) {
|
||||
return -1;
|
||||
} else {
|
||||
// same score: sort alphabetically
|
||||
left = a[1].toLowerCase();
|
||||
right = b[1].toLowerCase();
|
||||
return (left > right) ? -1 : ((left < right) ? 1 : 0);
|
||||
}
|
||||
});
|
||||
|
||||
// for debugging
|
||||
//Search.lastresults = results.slice(); // a copy
|
||||
//console.info('search results:', Search.lastresults);
|
||||
|
||||
// print the results
|
||||
var resultCount = results.length;
|
||||
function displayNextItem() {
|
||||
// results left, load the summary and display it
|
||||
if (results.length) {
|
||||
var item = results.pop();
|
||||
var listItem = $('<li style="display:none"></li>');
|
||||
if (DOCUMENTATION_OPTIONS.FILE_SUFFIX === '') {
|
||||
// dirhtml builder
|
||||
var dirname = item[0] + '/';
|
||||
if (dirname.match(/\/index\/$/)) {
|
||||
dirname = dirname.substring(0, dirname.length-6);
|
||||
} else if (dirname == 'index/') {
|
||||
dirname = '';
|
||||
}
|
||||
listItem.append($('<a/>').attr('href',
|
||||
DOCUMENTATION_OPTIONS.URL_ROOT + dirname +
|
||||
highlightstring + item[2]).html(item[1]));
|
||||
} else {
|
||||
// normal html builders
|
||||
listItem.append($('<a/>').attr('href',
|
||||
item[0] + DOCUMENTATION_OPTIONS.FILE_SUFFIX +
|
||||
highlightstring + item[2]).html(item[1]));
|
||||
}
|
||||
if (item[3]) {
|
||||
listItem.append($('<span> (' + item[3] + ')</span>'));
|
||||
Search.output.append(listItem);
|
||||
listItem.slideDown(5, function() {
|
||||
displayNextItem();
|
||||
});
|
||||
} else if (DOCUMENTATION_OPTIONS.HAS_SOURCE) {
|
||||
var suffix = DOCUMENTATION_OPTIONS.SOURCELINK_SUFFIX;
|
||||
$.ajax({url: DOCUMENTATION_OPTIONS.URL_ROOT + '_sources/' + item[5] + (item[5].slice(-suffix.length) === suffix ? '' : suffix),
|
||||
dataType: "text",
|
||||
complete: function(jqxhr, textstatus) {
|
||||
var data = jqxhr.responseText;
|
||||
if (data !== '' && data !== undefined) {
|
||||
listItem.append(Search.makeSearchSummary(data, searchterms, hlterms));
|
||||
}
|
||||
Search.output.append(listItem);
|
||||
listItem.slideDown(5, function() {
|
||||
displayNextItem();
|
||||
});
|
||||
}});
|
||||
} else {
|
||||
// no source available, just display title
|
||||
Search.output.append(listItem);
|
||||
listItem.slideDown(5, function() {
|
||||
displayNextItem();
|
||||
});
|
||||
}
|
||||
}
|
||||
// search finished, update title and status message
|
||||
else {
|
||||
Search.stopPulse();
|
||||
Search.title.text(_('Search Results'));
|
||||
if (!resultCount)
|
||||
Search.status.text(_('Your search did not match any documents. Please make sure that all words are spelled correctly and that you\'ve selected enough categories.'));
|
||||
else
|
||||
Search.status.text(_('Search finished, found %s page(s) matching the search query.').replace('%s', resultCount));
|
||||
Search.status.fadeIn(500);
|
||||
}
|
||||
}
|
||||
displayNextItem();
|
||||
},
|
||||
|
||||
/**
|
||||
* search for object names
|
||||
*/
|
||||
performObjectSearch : function(object, otherterms) {
|
||||
var filenames = this._index.filenames;
|
||||
var docnames = this._index.docnames;
|
||||
var objects = this._index.objects;
|
||||
var objnames = this._index.objnames;
|
||||
var titles = this._index.titles;
|
||||
|
||||
var i;
|
||||
var results = [];
|
||||
|
||||
for (var prefix in objects) {
|
||||
for (var name in objects[prefix]) {
|
||||
var fullname = (prefix ? prefix + '.' : '') + name;
|
||||
if (fullname.toLowerCase().indexOf(object) > -1) {
|
||||
var score = 0;
|
||||
var parts = fullname.split('.');
|
||||
// check for different match types: exact matches of full name or
|
||||
// "last name" (i.e. last dotted part)
|
||||
if (fullname == object || parts[parts.length - 1] == object) {
|
||||
score += Scorer.objNameMatch;
|
||||
// matches in last name
|
||||
} else if (parts[parts.length - 1].indexOf(object) > -1) {
|
||||
score += Scorer.objPartialMatch;
|
||||
}
|
||||
var match = objects[prefix][name];
|
||||
var objname = objnames[match[1]][2];
|
||||
var title = titles[match[0]];
|
||||
// If more than one term searched for, we require other words to be
|
||||
// found in the name/title/description
|
||||
if (otherterms.length > 0) {
|
||||
var haystack = (prefix + ' ' + name + ' ' +
|
||||
objname + ' ' + title).toLowerCase();
|
||||
var allfound = true;
|
||||
for (i = 0; i < otherterms.length; i++) {
|
||||
if (haystack.indexOf(otherterms[i]) == -1) {
|
||||
allfound = false;
|
||||
break;
|
||||
}
|
||||
}
|
||||
if (!allfound) {
|
||||
continue;
|
||||
}
|
||||
}
|
||||
var descr = objname + _(', in ') + title;
|
||||
|
||||
var anchor = match[3];
|
||||
if (anchor === '')
|
||||
anchor = fullname;
|
||||
else if (anchor == '-')
|
||||
anchor = objnames[match[1]][1] + '-' + fullname;
|
||||
// add custom score for some objects according to scorer
|
||||
if (Scorer.objPrio.hasOwnProperty(match[2])) {
|
||||
score += Scorer.objPrio[match[2]];
|
||||
} else {
|
||||
score += Scorer.objPrioDefault;
|
||||
}
|
||||
results.push([docnames[match[0]], fullname, '#'+anchor, descr, score, filenames[match[0]]]);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return results;
|
||||
},
|
||||
|
||||
/**
|
||||
* search for full-text terms in the index
|
||||
*/
|
||||
performTermsSearch : function(searchterms, excluded, terms, titleterms) {
|
||||
var docnames = this._index.docnames;
|
||||
var filenames = this._index.filenames;
|
||||
var titles = this._index.titles;
|
||||
|
||||
var i, j, file;
|
||||
var fileMap = {};
|
||||
var scoreMap = {};
|
||||
var results = [];
|
||||
|
||||
// perform the search on the required terms
|
||||
for (i = 0; i < searchterms.length; i++) {
|
||||
var word = searchterms[i];
|
||||
var files = [];
|
||||
var _o = [
|
||||
{files: terms[word], score: Scorer.term},
|
||||
{files: titleterms[word], score: Scorer.title}
|
||||
];
|
||||
|
||||
// no match but word was a required one
|
||||
if ($u.every(_o, function(o){return o.files === undefined;})) {
|
||||
break;
|
||||
}
|
||||
// found search word in contents
|
||||
$u.each(_o, function(o) {
|
||||
var _files = o.files;
|
||||
if (_files === undefined)
|
||||
return
|
||||
|
||||
if (_files.length === undefined)
|
||||
_files = [_files];
|
||||
files = files.concat(_files);
|
||||
|
||||
// set score for the word in each file to Scorer.term
|
||||
for (j = 0; j < _files.length; j++) {
|
||||
file = _files[j];
|
||||
if (!(file in scoreMap))
|
||||
scoreMap[file] = {}
|
||||
scoreMap[file][word] = o.score;
|
||||
}
|
||||
});
|
||||
|
||||
// create the mapping
|
||||
for (j = 0; j < files.length; j++) {
|
||||
file = files[j];
|
||||
if (file in fileMap)
|
||||
fileMap[file].push(word);
|
||||
else
|
||||
fileMap[file] = [word];
|
||||
}
|
||||
}
|
||||
|
||||
// now check if the files don't contain excluded terms
|
||||
for (file in fileMap) {
|
||||
var valid = true;
|
||||
|
||||
// check if all requirements are matched
|
||||
if (fileMap[file].length != searchterms.length)
|
||||
continue;
|
||||
|
||||
// ensure that none of the excluded terms is in the search result
|
||||
for (i = 0; i < excluded.length; i++) {
|
||||
if (terms[excluded[i]] == file ||
|
||||
titleterms[excluded[i]] == file ||
|
||||
$u.contains(terms[excluded[i]] || [], file) ||
|
||||
$u.contains(titleterms[excluded[i]] || [], file)) {
|
||||
valid = false;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// if we have still a valid result we can add it to the result list
|
||||
if (valid) {
|
||||
// select one (max) score for the file.
|
||||
// for better ranking, we should calculate ranking by using words statistics like basic tf-idf...
|
||||
var score = $u.max($u.map(fileMap[file], function(w){return scoreMap[file][w]}));
|
||||
results.push([docnames[file], titles[file], '', null, score, filenames[file]]);
|
||||
}
|
||||
}
|
||||
return results;
|
||||
},
|
||||
|
||||
/**
|
||||
* helper function to return a node containing the
|
||||
* search summary for a given text. keywords is a list
|
||||
* of stemmed words, hlwords is the list of normal, unstemmed
|
||||
* words. the first one is used to find the occurrence, the
|
||||
* latter for highlighting it.
|
||||
*/
|
||||
makeSearchSummary : function(text, keywords, hlwords) {
|
||||
var textLower = text.toLowerCase();
|
||||
var start = 0;
|
||||
$.each(keywords, function() {
|
||||
var i = textLower.indexOf(this.toLowerCase());
|
||||
if (i > -1)
|
||||
start = i;
|
||||
});
|
||||
start = Math.max(start - 120, 0);
|
||||
var excerpt = ((start > 0) ? '...' : '') +
|
||||
$.trim(text.substr(start, 240)) +
|
||||
((start + 240 - text.length) ? '...' : '');
|
||||
var rv = $('<div class="context"></div>').text(excerpt);
|
||||
$.each(hlwords, function() {
|
||||
rv = rv.highlightText(this, 'highlighted');
|
||||
});
|
||||
return rv;
|
||||
}
|
||||
};
|
||||
|
||||
$(document).ready(function() {
|
||||
Search.init();
|
||||
});
|
||||
@ -1,999 +0,0 @@
|
||||
// Underscore.js 1.3.1
|
||||
// (c) 2009-2012 Jeremy Ashkenas, DocumentCloud Inc.
|
||||
// Underscore is freely distributable under the MIT license.
|
||||
// Portions of Underscore are inspired or borrowed from Prototype,
|
||||
// Oliver Steele's Functional, and John Resig's Micro-Templating.
|
||||
// For all details and documentation:
|
||||
// http://documentcloud.github.com/underscore
|
||||
|
||||
(function() {
|
||||
|
||||
// Baseline setup
|
||||
// --------------
|
||||
|
||||
// Establish the root object, `window` in the browser, or `global` on the server.
|
||||
var root = this;
|
||||
|
||||
// Save the previous value of the `_` variable.
|
||||
var previousUnderscore = root._;
|
||||
|
||||
// Establish the object that gets returned to break out of a loop iteration.
|
||||
var breaker = {};
|
||||
|
||||
// Save bytes in the minified (but not gzipped) version:
|
||||
var ArrayProto = Array.prototype, ObjProto = Object.prototype, FuncProto = Function.prototype;
|
||||
|
||||
// Create quick reference variables for speed access to core prototypes.
|
||||
var slice = ArrayProto.slice,
|
||||
unshift = ArrayProto.unshift,
|
||||
toString = ObjProto.toString,
|
||||
hasOwnProperty = ObjProto.hasOwnProperty;
|
||||
|
||||
// All **ECMAScript 5** native function implementations that we hope to use
|
||||
// are declared here.
|
||||
var
|
||||
nativeForEach = ArrayProto.forEach,
|
||||
nativeMap = ArrayProto.map,
|
||||
nativeReduce = ArrayProto.reduce,
|
||||
nativeReduceRight = ArrayProto.reduceRight,
|
||||
nativeFilter = ArrayProto.filter,
|
||||
nativeEvery = ArrayProto.every,
|
||||
nativeSome = ArrayProto.some,
|
||||
nativeIndexOf = ArrayProto.indexOf,
|
||||
nativeLastIndexOf = ArrayProto.lastIndexOf,
|
||||
nativeIsArray = Array.isArray,
|
||||
nativeKeys = Object.keys,
|
||||
nativeBind = FuncProto.bind;
|
||||
|
||||
// Create a safe reference to the Underscore object for use below.
|
||||
var _ = function(obj) { return new wrapper(obj); };
|
||||
|
||||
// Export the Underscore object for **Node.js**, with
|
||||
// backwards-compatibility for the old `require()` API. If we're in
|
||||
// the browser, add `_` as a global object via a string identifier,
|
||||
// for Closure Compiler "advanced" mode.
|
||||
if (typeof exports !== 'undefined') {
|
||||
if (typeof module !== 'undefined' && module.exports) {
|
||||
exports = module.exports = _;
|
||||
}
|
||||
exports._ = _;
|
||||
} else {
|
||||
root['_'] = _;
|
||||
}
|
||||
|
||||
// Current version.
|
||||
_.VERSION = '1.3.1';
|
||||
|
||||
// Collection Functions
|
||||
// --------------------
|
||||
|
||||
// The cornerstone, an `each` implementation, aka `forEach`.
|
||||
// Handles objects with the built-in `forEach`, arrays, and raw objects.
|
||||
// Delegates to **ECMAScript 5**'s native `forEach` if available.
|
||||
var each = _.each = _.forEach = function(obj, iterator, context) {
|
||||
if (obj == null) return;
|
||||
if (nativeForEach && obj.forEach === nativeForEach) {
|
||||
obj.forEach(iterator, context);
|
||||
} else if (obj.length === +obj.length) {
|
||||
for (var i = 0, l = obj.length; i < l; i++) {
|
||||
if (i in obj && iterator.call(context, obj[i], i, obj) === breaker) return;
|
||||
}
|
||||
} else {
|
||||
for (var key in obj) {
|
||||
if (_.has(obj, key)) {
|
||||
if (iterator.call(context, obj[key], key, obj) === breaker) return;
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// Return the results of applying the iterator to each element.
|
||||
// Delegates to **ECMAScript 5**'s native `map` if available.
|
||||
_.map = _.collect = function(obj, iterator, context) {
|
||||
var results = [];
|
||||
if (obj == null) return results;
|
||||
if (nativeMap && obj.map === nativeMap) return obj.map(iterator, context);
|
||||
each(obj, function(value, index, list) {
|
||||
results[results.length] = iterator.call(context, value, index, list);
|
||||
});
|
||||
if (obj.length === +obj.length) results.length = obj.length;
|
||||
return results;
|
||||
};
|
||||
|
||||
// **Reduce** builds up a single result from a list of values, aka `inject`,
|
||||
// or `foldl`. Delegates to **ECMAScript 5**'s native `reduce` if available.
|
||||
_.reduce = _.foldl = _.inject = function(obj, iterator, memo, context) {
|
||||
var initial = arguments.length > 2;
|
||||
if (obj == null) obj = [];
|
||||
if (nativeReduce && obj.reduce === nativeReduce) {
|
||||
if (context) iterator = _.bind(iterator, context);
|
||||
return initial ? obj.reduce(iterator, memo) : obj.reduce(iterator);
|
||||
}
|
||||
each(obj, function(value, index, list) {
|
||||
if (!initial) {
|
||||
memo = value;
|
||||
initial = true;
|
||||
} else {
|
||||
memo = iterator.call(context, memo, value, index, list);
|
||||
}
|
||||
});
|
||||
if (!initial) throw new TypeError('Reduce of empty array with no initial value');
|
||||
return memo;
|
||||
};
|
||||
|
||||
// The right-associative version of reduce, also known as `foldr`.
|
||||
// Delegates to **ECMAScript 5**'s native `reduceRight` if available.
|
||||
_.reduceRight = _.foldr = function(obj, iterator, memo, context) {
|
||||
var initial = arguments.length > 2;
|
||||
if (obj == null) obj = [];
|
||||
if (nativeReduceRight && obj.reduceRight === nativeReduceRight) {
|
||||
if (context) iterator = _.bind(iterator, context);
|
||||
return initial ? obj.reduceRight(iterator, memo) : obj.reduceRight(iterator);
|
||||
}
|
||||
var reversed = _.toArray(obj).reverse();
|
||||
if (context && !initial) iterator = _.bind(iterator, context);
|
||||
return initial ? _.reduce(reversed, iterator, memo, context) : _.reduce(reversed, iterator);
|
||||
};
|
||||
|
||||
// Return the first value which passes a truth test. Aliased as `detect`.
|
||||
_.find = _.detect = function(obj, iterator, context) {
|
||||
var result;
|
||||
any(obj, function(value, index, list) {
|
||||
if (iterator.call(context, value, index, list)) {
|
||||
result = value;
|
||||
return true;
|
||||
}
|
||||
});
|
||||
return result;
|
||||
};
|
||||
|
||||
// Return all the elements that pass a truth test.
|
||||
// Delegates to **ECMAScript 5**'s native `filter` if available.
|
||||
// Aliased as `select`.
|
||||
_.filter = _.select = function(obj, iterator, context) {
|
||||
var results = [];
|
||||
if (obj == null) return results;
|
||||
if (nativeFilter && obj.filter === nativeFilter) return obj.filter(iterator, context);
|
||||
each(obj, function(value, index, list) {
|
||||
if (iterator.call(context, value, index, list)) results[results.length] = value;
|
||||
});
|
||||
return results;
|
||||
};
|
||||
|
||||
// Return all the elements for which a truth test fails.
|
||||
_.reject = function(obj, iterator, context) {
|
||||
var results = [];
|
||||
if (obj == null) return results;
|
||||
each(obj, function(value, index, list) {
|
||||
if (!iterator.call(context, value, index, list)) results[results.length] = value;
|
||||
});
|
||||
return results;
|
||||
};
|
||||
|
||||
// Determine whether all of the elements match a truth test.
|
||||
// Delegates to **ECMAScript 5**'s native `every` if available.
|
||||
// Aliased as `all`.
|
||||
_.every = _.all = function(obj, iterator, context) {
|
||||
var result = true;
|
||||
if (obj == null) return result;
|
||||
if (nativeEvery && obj.every === nativeEvery) return obj.every(iterator, context);
|
||||
each(obj, function(value, index, list) {
|
||||
if (!(result = result && iterator.call(context, value, index, list))) return breaker;
|
||||
});
|
||||
return result;
|
||||
};
|
||||
|
||||
// Determine if at least one element in the object matches a truth test.
|
||||
// Delegates to **ECMAScript 5**'s native `some` if available.
|
||||
// Aliased as `any`.
|
||||
var any = _.some = _.any = function(obj, iterator, context) {
|
||||
iterator || (iterator = _.identity);
|
||||
var result = false;
|
||||
if (obj == null) return result;
|
||||
if (nativeSome && obj.some === nativeSome) return obj.some(iterator, context);
|
||||
each(obj, function(value, index, list) {
|
||||
if (result || (result = iterator.call(context, value, index, list))) return breaker;
|
||||
});
|
||||
return !!result;
|
||||
};
|
||||
|
||||
// Determine if a given value is included in the array or object using `===`.
|
||||
// Aliased as `contains`.
|
||||
_.include = _.contains = function(obj, target) {
|
||||
var found = false;
|
||||
if (obj == null) return found;
|
||||
if (nativeIndexOf && obj.indexOf === nativeIndexOf) return obj.indexOf(target) != -1;
|
||||
found = any(obj, function(value) {
|
||||
return value === target;
|
||||
});
|
||||
return found;
|
||||
};
|
||||
|
||||
// Invoke a method (with arguments) on every item in a collection.
|
||||
_.invoke = function(obj, method) {
|
||||
var args = slice.call(arguments, 2);
|
||||
return _.map(obj, function(value) {
|
||||
return (_.isFunction(method) ? method || value : value[method]).apply(value, args);
|
||||
});
|
||||
};
|
||||
|
||||
// Convenience version of a common use case of `map`: fetching a property.
|
||||
_.pluck = function(obj, key) {
|
||||
return _.map(obj, function(value){ return value[key]; });
|
||||
};
|
||||
|
||||
// Return the maximum element or (element-based computation).
|
||||
_.max = function(obj, iterator, context) {
|
||||
if (!iterator && _.isArray(obj)) return Math.max.apply(Math, obj);
|
||||
if (!iterator && _.isEmpty(obj)) return -Infinity;
|
||||
var result = {computed : -Infinity};
|
||||
each(obj, function(value, index, list) {
|
||||
var computed = iterator ? iterator.call(context, value, index, list) : value;
|
||||
computed >= result.computed && (result = {value : value, computed : computed});
|
||||
});
|
||||
return result.value;
|
||||
};
|
||||
|
||||
// Return the minimum element (or element-based computation).
|
||||
_.min = function(obj, iterator, context) {
|
||||
if (!iterator && _.isArray(obj)) return Math.min.apply(Math, obj);
|
||||
if (!iterator && _.isEmpty(obj)) return Infinity;
|
||||
var result = {computed : Infinity};
|
||||
each(obj, function(value, index, list) {
|
||||
var computed = iterator ? iterator.call(context, value, index, list) : value;
|
||||
computed < result.computed && (result = {value : value, computed : computed});
|
||||
});
|
||||
return result.value;
|
||||
};
|
||||
|
||||
// Shuffle an array.
|
||||
_.shuffle = function(obj) {
|
||||
var shuffled = [], rand;
|
||||
each(obj, function(value, index, list) {
|
||||
if (index == 0) {
|
||||
shuffled[0] = value;
|
||||
} else {
|
||||
rand = Math.floor(Math.random() * (index + 1));
|
||||
shuffled[index] = shuffled[rand];
|
||||
shuffled[rand] = value;
|
||||
}
|
||||
});
|
||||
return shuffled;
|
||||
};
|
||||
|
||||
// Sort the object's values by a criterion produced by an iterator.
|
||||
_.sortBy = function(obj, iterator, context) {
|
||||
return _.pluck(_.map(obj, function(value, index, list) {
|
||||
return {
|
||||
value : value,
|
||||
criteria : iterator.call(context, value, index, list)
|
||||
};
|
||||
}).sort(function(left, right) {
|
||||
var a = left.criteria, b = right.criteria;
|
||||
return a < b ? -1 : a > b ? 1 : 0;
|
||||
}), 'value');
|
||||
};
|
||||
|
||||
// Groups the object's values by a criterion. Pass either a string attribute
|
||||
// to group by, or a function that returns the criterion.
|
||||
_.groupBy = function(obj, val) {
|
||||
var result = {};
|
||||
var iterator = _.isFunction(val) ? val : function(obj) { return obj[val]; };
|
||||
each(obj, function(value, index) {
|
||||
var key = iterator(value, index);
|
||||
(result[key] || (result[key] = [])).push(value);
|
||||
});
|
||||
return result;
|
||||
};
|
||||
|
||||
// Use a comparator function to figure out at what index an object should
|
||||
// be inserted so as to maintain order. Uses binary search.
|
||||
_.sortedIndex = function(array, obj, iterator) {
|
||||
iterator || (iterator = _.identity);
|
||||
var low = 0, high = array.length;
|
||||
while (low < high) {
|
||||
var mid = (low + high) >> 1;
|
||||
iterator(array[mid]) < iterator(obj) ? low = mid + 1 : high = mid;
|
||||
}
|
||||
return low;
|
||||
};
|
||||
|
||||
// Safely convert anything iterable into a real, live array.
|
||||
_.toArray = function(iterable) {
|
||||
if (!iterable) return [];
|
||||
if (iterable.toArray) return iterable.toArray();
|
||||
if (_.isArray(iterable)) return slice.call(iterable);
|
||||
if (_.isArguments(iterable)) return slice.call(iterable);
|
||||
return _.values(iterable);
|
||||
};
|
||||
|
||||
// Return the number of elements in an object.
|
||||
_.size = function(obj) {
|
||||
return _.toArray(obj).length;
|
||||
};
|
||||
|
||||
// Array Functions
|
||||
// ---------------
|
||||
|
||||
// Get the first element of an array. Passing **n** will return the first N
|
||||
// values in the array. Aliased as `head`. The **guard** check allows it to work
|
||||
// with `_.map`.
|
||||
_.first = _.head = function(array, n, guard) {
|
||||
return (n != null) && !guard ? slice.call(array, 0, n) : array[0];
|
||||
};
|
||||
|
||||
// Returns everything but the last entry of the array. Especcialy useful on
|
||||
// the arguments object. Passing **n** will return all the values in
|
||||
// the array, excluding the last N. The **guard** check allows it to work with
|
||||
// `_.map`.
|
||||
_.initial = function(array, n, guard) {
|
||||
return slice.call(array, 0, array.length - ((n == null) || guard ? 1 : n));
|
||||
};
|
||||
|
||||
// Get the last element of an array. Passing **n** will return the last N
|
||||
// values in the array. The **guard** check allows it to work with `_.map`.
|
||||
_.last = function(array, n, guard) {
|
||||
if ((n != null) && !guard) {
|
||||
return slice.call(array, Math.max(array.length - n, 0));
|
||||
} else {
|
||||
return array[array.length - 1];
|
||||
}
|
||||
};
|
||||
|
||||
// Returns everything but the first entry of the array. Aliased as `tail`.
|
||||
// Especially useful on the arguments object. Passing an **index** will return
|
||||
// the rest of the values in the array from that index onward. The **guard**
|
||||
// check allows it to work with `_.map`.
|
||||
_.rest = _.tail = function(array, index, guard) {
|
||||
return slice.call(array, (index == null) || guard ? 1 : index);
|
||||
};
|
||||
|
||||
// Trim out all falsy values from an array.
|
||||
_.compact = function(array) {
|
||||
return _.filter(array, function(value){ return !!value; });
|
||||
};
|
||||
|
||||
// Return a completely flattened version of an array.
|
||||
_.flatten = function(array, shallow) {
|
||||
return _.reduce(array, function(memo, value) {
|
||||
if (_.isArray(value)) return memo.concat(shallow ? value : _.flatten(value));
|
||||
memo[memo.length] = value;
|
||||
return memo;
|
||||
}, []);
|
||||
};
|
||||
|
||||
// Return a version of the array that does not contain the specified value(s).
|
||||
_.without = function(array) {
|
||||
return _.difference(array, slice.call(arguments, 1));
|
||||
};
|
||||
|
||||
// Produce a duplicate-free version of the array. If the array has already
|
||||
// been sorted, you have the option of using a faster algorithm.
|
||||
// Aliased as `unique`.
|
||||
_.uniq = _.unique = function(array, isSorted, iterator) {
|
||||
var initial = iterator ? _.map(array, iterator) : array;
|
||||
var result = [];
|
||||
_.reduce(initial, function(memo, el, i) {
|
||||
if (0 == i || (isSorted === true ? _.last(memo) != el : !_.include(memo, el))) {
|
||||
memo[memo.length] = el;
|
||||
result[result.length] = array[i];
|
||||
}
|
||||
return memo;
|
||||
}, []);
|
||||
return result;
|
||||
};
|
||||
|
||||
// Produce an array that contains the union: each distinct element from all of
|
||||
// the passed-in arrays.
|
||||
_.union = function() {
|
||||
return _.uniq(_.flatten(arguments, true));
|
||||
};
|
||||
|
||||
// Produce an array that contains every item shared between all the
|
||||
// passed-in arrays. (Aliased as "intersect" for back-compat.)
|
||||
_.intersection = _.intersect = function(array) {
|
||||
var rest = slice.call(arguments, 1);
|
||||
return _.filter(_.uniq(array), function(item) {
|
||||
return _.every(rest, function(other) {
|
||||
return _.indexOf(other, item) >= 0;
|
||||
});
|
||||
});
|
||||
};
|
||||
|
||||
// Take the difference between one array and a number of other arrays.
|
||||
// Only the elements present in just the first array will remain.
|
||||
_.difference = function(array) {
|
||||
var rest = _.flatten(slice.call(arguments, 1));
|
||||
return _.filter(array, function(value){ return !_.include(rest, value); });
|
||||
};
|
||||
|
||||
// Zip together multiple lists into a single array -- elements that share
|
||||
// an index go together.
|
||||
_.zip = function() {
|
||||
var args = slice.call(arguments);
|
||||
var length = _.max(_.pluck(args, 'length'));
|
||||
var results = new Array(length);
|
||||
for (var i = 0; i < length; i++) results[i] = _.pluck(args, "" + i);
|
||||
return results;
|
||||
};
|
||||
|
||||
// If the browser doesn't supply us with indexOf (I'm looking at you, **MSIE**),
|
||||
// we need this function. Return the position of the first occurrence of an
|
||||
// item in an array, or -1 if the item is not included in the array.
|
||||
// Delegates to **ECMAScript 5**'s native `indexOf` if available.
|
||||
// If the array is large and already in sort order, pass `true`
|
||||
// for **isSorted** to use binary search.
|
||||
_.indexOf = function(array, item, isSorted) {
|
||||
if (array == null) return -1;
|
||||
var i, l;
|
||||
if (isSorted) {
|
||||
i = _.sortedIndex(array, item);
|
||||
return array[i] === item ? i : -1;
|
||||
}
|
||||
if (nativeIndexOf && array.indexOf === nativeIndexOf) return array.indexOf(item);
|
||||
for (i = 0, l = array.length; i < l; i++) if (i in array && array[i] === item) return i;
|
||||
return -1;
|
||||
};
|
||||
|
||||
// Delegates to **ECMAScript 5**'s native `lastIndexOf` if available.
|
||||
_.lastIndexOf = function(array, item) {
|
||||
if (array == null) return -1;
|
||||
if (nativeLastIndexOf && array.lastIndexOf === nativeLastIndexOf) return array.lastIndexOf(item);
|
||||
var i = array.length;
|
||||
while (i--) if (i in array && array[i] === item) return i;
|
||||
return -1;
|
||||
};
|
||||
|
||||
// Generate an integer Array containing an arithmetic progression. A port of
|
||||
// the native Python `range()` function. See
|
||||
// [the Python documentation](http://docs.python.org/library/functions.html#range).
|
||||
_.range = function(start, stop, step) {
|
||||
if (arguments.length <= 1) {
|
||||
stop = start || 0;
|
||||
start = 0;
|
||||
}
|
||||
step = arguments[2] || 1;
|
||||
|
||||
var len = Math.max(Math.ceil((stop - start) / step), 0);
|
||||
var idx = 0;
|
||||
var range = new Array(len);
|
||||
|
||||
while(idx < len) {
|
||||
range[idx++] = start;
|
||||
start += step;
|
||||
}
|
||||
|
||||
return range;
|
||||
};
|
||||
|
||||
// Function (ahem) Functions
|
||||
// ------------------
|
||||
|
||||
// Reusable constructor function for prototype setting.
|
||||
var ctor = function(){};
|
||||
|
||||
// Create a function bound to a given object (assigning `this`, and arguments,
|
||||
// optionally). Binding with arguments is also known as `curry`.
|
||||
// Delegates to **ECMAScript 5**'s native `Function.bind` if available.
|
||||
// We check for `func.bind` first, to fail fast when `func` is undefined.
|
||||
_.bind = function bind(func, context) {
|
||||
var bound, args;
|
||||
if (func.bind === nativeBind && nativeBind) return nativeBind.apply(func, slice.call(arguments, 1));
|
||||
if (!_.isFunction(func)) throw new TypeError;
|
||||
args = slice.call(arguments, 2);
|
||||
return bound = function() {
|
||||
if (!(this instanceof bound)) return func.apply(context, args.concat(slice.call(arguments)));
|
||||
ctor.prototype = func.prototype;
|
||||
var self = new ctor;
|
||||
var result = func.apply(self, args.concat(slice.call(arguments)));
|
||||
if (Object(result) === result) return result;
|
||||
return self;
|
||||
};
|
||||
};
|
||||
|
||||
// Bind all of an object's methods to that object. Useful for ensuring that
|
||||
// all callbacks defined on an object belong to it.
|
||||
_.bindAll = function(obj) {
|
||||
var funcs = slice.call(arguments, 1);
|
||||
if (funcs.length == 0) funcs = _.functions(obj);
|
||||
each(funcs, function(f) { obj[f] = _.bind(obj[f], obj); });
|
||||
return obj;
|
||||
};
|
||||
|
||||
// Memoize an expensive function by storing its results.
|
||||
_.memoize = function(func, hasher) {
|
||||
var memo = {};
|
||||
hasher || (hasher = _.identity);
|
||||
return function() {
|
||||
var key = hasher.apply(this, arguments);
|
||||
return _.has(memo, key) ? memo[key] : (memo[key] = func.apply(this, arguments));
|
||||
};
|
||||
};
|
||||
|
||||
// Delays a function for the given number of milliseconds, and then calls
|
||||
// it with the arguments supplied.
|
||||
_.delay = function(func, wait) {
|
||||
var args = slice.call(arguments, 2);
|
||||
return setTimeout(function(){ return func.apply(func, args); }, wait);
|
||||
};
|
||||
|
||||
// Defers a function, scheduling it to run after the current call stack has
|
||||
// cleared.
|
||||
_.defer = function(func) {
|
||||
return _.delay.apply(_, [func, 1].concat(slice.call(arguments, 1)));
|
||||
};
|
||||
|
||||
// Returns a function, that, when invoked, will only be triggered at most once
|
||||
// during a given window of time.
|
||||
_.throttle = function(func, wait) {
|
||||
var context, args, timeout, throttling, more;
|
||||
var whenDone = _.debounce(function(){ more = throttling = false; }, wait);
|
||||
return function() {
|
||||
context = this; args = arguments;
|
||||
var later = function() {
|
||||
timeout = null;
|
||||
if (more) func.apply(context, args);
|
||||
whenDone();
|
||||
};
|
||||
if (!timeout) timeout = setTimeout(later, wait);
|
||||
if (throttling) {
|
||||
more = true;
|
||||
} else {
|
||||
func.apply(context, args);
|
||||
}
|
||||
whenDone();
|
||||
throttling = true;
|
||||
};
|
||||
};
|
||||
|
||||
// Returns a function, that, as long as it continues to be invoked, will not
|
||||
// be triggered. The function will be called after it stops being called for
|
||||
// N milliseconds.
|
||||
_.debounce = function(func, wait) {
|
||||
var timeout;
|
||||
return function() {
|
||||
var context = this, args = arguments;
|
||||
var later = function() {
|
||||
timeout = null;
|
||||
func.apply(context, args);
|
||||
};
|
||||
clearTimeout(timeout);
|
||||
timeout = setTimeout(later, wait);
|
||||
};
|
||||
};
|
||||
|
||||
// Returns a function that will be executed at most one time, no matter how
|
||||
// often you call it. Useful for lazy initialization.
|
||||
_.once = function(func) {
|
||||
var ran = false, memo;
|
||||
return function() {
|
||||
if (ran) return memo;
|
||||
ran = true;
|
||||
return memo = func.apply(this, arguments);
|
||||
};
|
||||
};
|
||||
|
||||
// Returns the first function passed as an argument to the second,
|
||||
// allowing you to adjust arguments, run code before and after, and
|
||||
// conditionally execute the original function.
|
||||
_.wrap = function(func, wrapper) {
|
||||
return function() {
|
||||
var args = [func].concat(slice.call(arguments, 0));
|
||||
return wrapper.apply(this, args);
|
||||
};
|
||||
};
|
||||
|
||||
// Returns a function that is the composition of a list of functions, each
|
||||
// consuming the return value of the function that follows.
|
||||
_.compose = function() {
|
||||
var funcs = arguments;
|
||||
return function() {
|
||||
var args = arguments;
|
||||
for (var i = funcs.length - 1; i >= 0; i--) {
|
||||
args = [funcs[i].apply(this, args)];
|
||||
}
|
||||
return args[0];
|
||||
};
|
||||
};
|
||||
|
||||
// Returns a function that will only be executed after being called N times.
|
||||
_.after = function(times, func) {
|
||||
if (times <= 0) return func();
|
||||
return function() {
|
||||
if (--times < 1) { return func.apply(this, arguments); }
|
||||
};
|
||||
};
|
||||
|
||||
// Object Functions
|
||||
// ----------------
|
||||
|
||||
// Retrieve the names of an object's properties.
|
||||
// Delegates to **ECMAScript 5**'s native `Object.keys`
|
||||
_.keys = nativeKeys || function(obj) {
|
||||
if (obj !== Object(obj)) throw new TypeError('Invalid object');
|
||||
var keys = [];
|
||||
for (var key in obj) if (_.has(obj, key)) keys[keys.length] = key;
|
||||
return keys;
|
||||
};
|
||||
|
||||
// Retrieve the values of an object's properties.
|
||||
_.values = function(obj) {
|
||||
return _.map(obj, _.identity);
|
||||
};
|
||||
|
||||
// Return a sorted list of the function names available on the object.
|
||||
// Aliased as `methods`
|
||||
_.functions = _.methods = function(obj) {
|
||||
var names = [];
|
||||
for (var key in obj) {
|
||||
if (_.isFunction(obj[key])) names.push(key);
|
||||
}
|
||||
return names.sort();
|
||||
};
|
||||
|
||||
// Extend a given object with all the properties in passed-in object(s).
|
||||
_.extend = function(obj) {
|
||||
each(slice.call(arguments, 1), function(source) {
|
||||
for (var prop in source) {
|
||||
obj[prop] = source[prop];
|
||||
}
|
||||
});
|
||||
return obj;
|
||||
};
|
||||
|
||||
// Fill in a given object with default properties.
|
||||
_.defaults = function(obj) {
|
||||
each(slice.call(arguments, 1), function(source) {
|
||||
for (var prop in source) {
|
||||
if (obj[prop] == null) obj[prop] = source[prop];
|
||||
}
|
||||
});
|
||||
return obj;
|
||||
};
|
||||
|
||||
// Create a (shallow-cloned) duplicate of an object.
|
||||
_.clone = function(obj) {
|
||||
if (!_.isObject(obj)) return obj;
|
||||
return _.isArray(obj) ? obj.slice() : _.extend({}, obj);
|
||||
};
|
||||
|
||||
// Invokes interceptor with the obj, and then returns obj.
|
||||
// The primary purpose of this method is to "tap into" a method chain, in
|
||||
// order to perform operations on intermediate results within the chain.
|
||||
_.tap = function(obj, interceptor) {
|
||||
interceptor(obj);
|
||||
return obj;
|
||||
};
|
||||
|
||||
// Internal recursive comparison function.
|
||||
function eq(a, b, stack) {
|
||||
// Identical objects are equal. `0 === -0`, but they aren't identical.
|
||||
// See the Harmony `egal` proposal: http://wiki.ecmascript.org/doku.php?id=harmony:egal.
|
||||
if (a === b) return a !== 0 || 1 / a == 1 / b;
|
||||
// A strict comparison is necessary because `null == undefined`.
|
||||
if (a == null || b == null) return a === b;
|
||||
// Unwrap any wrapped objects.
|
||||
if (a._chain) a = a._wrapped;
|
||||
if (b._chain) b = b._wrapped;
|
||||
// Invoke a custom `isEqual` method if one is provided.
|
||||
if (a.isEqual && _.isFunction(a.isEqual)) return a.isEqual(b);
|
||||
if (b.isEqual && _.isFunction(b.isEqual)) return b.isEqual(a);
|
||||
// Compare `[[Class]]` names.
|
||||
var className = toString.call(a);
|
||||
if (className != toString.call(b)) return false;
|
||||
switch (className) {
|
||||
// Strings, numbers, dates, and booleans are compared by value.
|
||||
case '[object String]':
|
||||
// Primitives and their corresponding object wrappers are equivalent; thus, `"5"` is
|
||||
// equivalent to `new String("5")`.
|
||||
return a == String(b);
|
||||
case '[object Number]':
|
||||
// `NaN`s are equivalent, but non-reflexive. An `egal` comparison is performed for
|
||||
// other numeric values.
|
||||
return a != +a ? b != +b : (a == 0 ? 1 / a == 1 / b : a == +b);
|
||||
case '[object Date]':
|
||||
case '[object Boolean]':
|
||||
// Coerce dates and booleans to numeric primitive values. Dates are compared by their
|
||||
// millisecond representations. Note that invalid dates with millisecond representations
|
||||
// of `NaN` are not equivalent.
|
||||
return +a == +b;
|
||||
// RegExps are compared by their source patterns and flags.
|
||||
case '[object RegExp]':
|
||||
return a.source == b.source &&
|
||||
a.global == b.global &&
|
||||
a.multiline == b.multiline &&
|
||||
a.ignoreCase == b.ignoreCase;
|
||||
}
|
||||
if (typeof a != 'object' || typeof b != 'object') return false;
|
||||
// Assume equality for cyclic structures. The algorithm for detecting cyclic
|
||||
// structures is adapted from ES 5.1 section 15.12.3, abstract operation `JO`.
|
||||
var length = stack.length;
|
||||
while (length--) {
|
||||
// Linear search. Performance is inversely proportional to the number of
|
||||
// unique nested structures.
|
||||
if (stack[length] == a) return true;
|
||||
}
|
||||
// Add the first object to the stack of traversed objects.
|
||||
stack.push(a);
|
||||
var size = 0, result = true;
|
||||
// Recursively compare objects and arrays.
|
||||
if (className == '[object Array]') {
|
||||
// Compare array lengths to determine if a deep comparison is necessary.
|
||||
size = a.length;
|
||||
result = size == b.length;
|
||||
if (result) {
|
||||
// Deep compare the contents, ignoring non-numeric properties.
|
||||
while (size--) {
|
||||
// Ensure commutative equality for sparse arrays.
|
||||
if (!(result = size in a == size in b && eq(a[size], b[size], stack))) break;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// Objects with different constructors are not equivalent.
|
||||
if ('constructor' in a != 'constructor' in b || a.constructor != b.constructor) return false;
|
||||
// Deep compare objects.
|
||||
for (var key in a) {
|
||||
if (_.has(a, key)) {
|
||||
// Count the expected number of properties.
|
||||
size++;
|
||||
// Deep compare each member.
|
||||
if (!(result = _.has(b, key) && eq(a[key], b[key], stack))) break;
|
||||
}
|
||||
}
|
||||
// Ensure that both objects contain the same number of properties.
|
||||
if (result) {
|
||||
for (key in b) {
|
||||
if (_.has(b, key) && !(size--)) break;
|
||||
}
|
||||
result = !size;
|
||||
}
|
||||
}
|
||||
// Remove the first object from the stack of traversed objects.
|
||||
stack.pop();
|
||||
return result;
|
||||
}
|
||||
|
||||
// Perform a deep comparison to check if two objects are equal.
|
||||
_.isEqual = function(a, b) {
|
||||
return eq(a, b, []);
|
||||
};
|
||||
|
||||
// Is a given array, string, or object empty?
|
||||
// An "empty" object has no enumerable own-properties.
|
||||
_.isEmpty = function(obj) {
|
||||
if (_.isArray(obj) || _.isString(obj)) return obj.length === 0;
|
||||
for (var key in obj) if (_.has(obj, key)) return false;
|
||||
return true;
|
||||
};
|
||||
|
||||
// Is a given value a DOM element?
|
||||
_.isElement = function(obj) {
|
||||
return !!(obj && obj.nodeType == 1);
|
||||
};
|
||||
|
||||
// Is a given value an array?
|
||||
// Delegates to ECMA5's native Array.isArray
|
||||
_.isArray = nativeIsArray || function(obj) {
|
||||
return toString.call(obj) == '[object Array]';
|
||||
};
|
||||
|
||||
// Is a given variable an object?
|
||||
_.isObject = function(obj) {
|
||||
return obj === Object(obj);
|
||||
};
|
||||
|
||||
// Is a given variable an arguments object?
|
||||
_.isArguments = function(obj) {
|
||||
return toString.call(obj) == '[object Arguments]';
|
||||
};
|
||||
if (!_.isArguments(arguments)) {
|
||||
_.isArguments = function(obj) {
|
||||
return !!(obj && _.has(obj, 'callee'));
|
||||
};
|
||||
}
|
||||
|
||||
// Is a given value a function?
|
||||
_.isFunction = function(obj) {
|
||||
return toString.call(obj) == '[object Function]';
|
||||
};
|
||||
|
||||
// Is a given value a string?
|
||||
_.isString = function(obj) {
|
||||
return toString.call(obj) == '[object String]';
|
||||
};
|
||||
|
||||
// Is a given value a number?
|
||||
_.isNumber = function(obj) {
|
||||
return toString.call(obj) == '[object Number]';
|
||||
};
|
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||||
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// -----------------
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
// The OOP Wrapper
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
@ -1,31 +0,0 @@
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||||
// Underscore.js 1.3.1
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||||
// (c) 2009-2012 Jeremy Ashkenas, DocumentCloud Inc.
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||||
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||||
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||||
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||||
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|
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|
||||
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|
||||
/*
|
||||
* websupport.js
|
||||
* ~~~~~~~~~~~~~
|
||||
*
|
||||
* sphinx.websupport utilities for all documentation.
|
||||
*
|
||||
* :copyright: Copyright 2007-2016 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
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|
||||
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|
||||
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|
||||
var textarea = this;
|
||||
|
||||
$.fn.autogrow.resize(textarea);
|
||||
|
||||
$(textarea)
|
||||
.focus(function() {
|
||||
textarea.interval = setInterval(function() {
|
||||
$.fn.autogrow.resize(textarea);
|
||||
}, 500);
|
||||
})
|
||||
.blur(function() {
|
||||
clearInterval(textarea.interval);
|
||||
});
|
||||
});
|
||||
};
|
||||
|
||||
$.fn.autogrow.resize = function(textarea) {
|
||||
var lineHeight = parseInt($(textarea).css('line-height'), 10);
|
||||
var lines = textarea.value.split('\n');
|
||||
var columns = textarea.cols;
|
||||
var lineCount = 0;
|
||||
$.each(lines, function() {
|
||||
lineCount += Math.ceil(this.length / columns) || 1;
|
||||
});
|
||||
var height = lineHeight * (lineCount + 1);
|
||||
$(textarea).css('height', height);
|
||||
};
|
||||
})(jQuery);
|
||||
|
||||
(function($) {
|
||||
var comp, by;
|
||||
|
||||
function init() {
|
||||
initEvents();
|
||||
initComparator();
|
||||
}
|
||||
|
||||
function initEvents() {
|
||||
$(document).on("click", 'a.comment-close', function(event) {
|
||||
event.preventDefault();
|
||||
hide($(this).attr('id').substring(2));
|
||||
});
|
||||
$(document).on("click", 'a.vote', function(event) {
|
||||
event.preventDefault();
|
||||
handleVote($(this));
|
||||
});
|
||||
$(document).on("click", 'a.reply', function(event) {
|
||||
event.preventDefault();
|
||||
openReply($(this).attr('id').substring(2));
|
||||
});
|
||||
$(document).on("click", 'a.close-reply', function(event) {
|
||||
event.preventDefault();
|
||||
closeReply($(this).attr('id').substring(2));
|
||||
});
|
||||
$(document).on("click", 'a.sort-option', function(event) {
|
||||
event.preventDefault();
|
||||
handleReSort($(this));
|
||||
});
|
||||
$(document).on("click", 'a.show-proposal', function(event) {
|
||||
event.preventDefault();
|
||||
showProposal($(this).attr('id').substring(2));
|
||||
});
|
||||
$(document).on("click", 'a.hide-proposal', function(event) {
|
||||
event.preventDefault();
|
||||
hideProposal($(this).attr('id').substring(2));
|
||||
});
|
||||
$(document).on("click", 'a.show-propose-change', function(event) {
|
||||
event.preventDefault();
|
||||
showProposeChange($(this).attr('id').substring(2));
|
||||
});
|
||||
$(document).on("click", 'a.hide-propose-change', function(event) {
|
||||
event.preventDefault();
|
||||
hideProposeChange($(this).attr('id').substring(2));
|
||||
});
|
||||
$(document).on("click", 'a.accept-comment', function(event) {
|
||||
event.preventDefault();
|
||||
acceptComment($(this).attr('id').substring(2));
|
||||
});
|
||||
$(document).on("click", 'a.delete-comment', function(event) {
|
||||
event.preventDefault();
|
||||
deleteComment($(this).attr('id').substring(2));
|
||||
});
|
||||
$(document).on("click", 'a.comment-markup', function(event) {
|
||||
event.preventDefault();
|
||||
toggleCommentMarkupBox($(this).attr('id').substring(2));
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Set comp, which is a comparator function used for sorting and
|
||||
* inserting comments into the list.
|
||||
*/
|
||||
function setComparator() {
|
||||
// If the first three letters are "asc", sort in ascending order
|
||||
// and remove the prefix.
|
||||
if (by.substring(0,3) == 'asc') {
|
||||
var i = by.substring(3);
|
||||
comp = function(a, b) { return a[i] - b[i]; };
|
||||
} else {
|
||||
// Otherwise sort in descending order.
|
||||
comp = function(a, b) { return b[by] - a[by]; };
|
||||
}
|
||||
|
||||
// Reset link styles and format the selected sort option.
|
||||
$('a.sel').attr('href', '#').removeClass('sel');
|
||||
$('a.by' + by).removeAttr('href').addClass('sel');
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a comp function. If the user has preferences stored in
|
||||
* the sortBy cookie, use those, otherwise use the default.
|
||||
*/
|
||||
function initComparator() {
|
||||
by = 'rating'; // Default to sort by rating.
|
||||
// If the sortBy cookie is set, use that instead.
|
||||
if (document.cookie.length > 0) {
|
||||
var start = document.cookie.indexOf('sortBy=');
|
||||
if (start != -1) {
|
||||
start = start + 7;
|
||||
var end = document.cookie.indexOf(";", start);
|
||||
if (end == -1) {
|
||||
end = document.cookie.length;
|
||||
by = unescape(document.cookie.substring(start, end));
|
||||
}
|
||||
}
|
||||
}
|
||||
setComparator();
|
||||
}
|
||||
|
||||
/**
|
||||
* Show a comment div.
|
||||
*/
|
||||
function show(id) {
|
||||
$('#ao' + id).hide();
|
||||
$('#ah' + id).show();
|
||||
var context = $.extend({id: id}, opts);
|
||||
var popup = $(renderTemplate(popupTemplate, context)).hide();
|
||||
popup.find('textarea[name="proposal"]').hide();
|
||||
popup.find('a.by' + by).addClass('sel');
|
||||
var form = popup.find('#cf' + id);
|
||||
form.submit(function(event) {
|
||||
event.preventDefault();
|
||||
addComment(form);
|
||||
});
|
||||
$('#s' + id).after(popup);
|
||||
popup.slideDown('fast', function() {
|
||||
getComments(id);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Hide a comment div.
|
||||
*/
|
||||
function hide(id) {
|
||||
$('#ah' + id).hide();
|
||||
$('#ao' + id).show();
|
||||
var div = $('#sc' + id);
|
||||
div.slideUp('fast', function() {
|
||||
div.remove();
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Perform an ajax request to get comments for a node
|
||||
* and insert the comments into the comments tree.
|
||||
*/
|
||||
function getComments(id) {
|
||||
$.ajax({
|
||||
type: 'GET',
|
||||
url: opts.getCommentsURL,
|
||||
data: {node: id},
|
||||
success: function(data, textStatus, request) {
|
||||
var ul = $('#cl' + id);
|
||||
var speed = 100;
|
||||
$('#cf' + id)
|
||||
.find('textarea[name="proposal"]')
|
||||
.data('source', data.source);
|
||||
|
||||
if (data.comments.length === 0) {
|
||||
ul.html('<li>No comments yet.</li>');
|
||||
ul.data('empty', true);
|
||||
} else {
|
||||
// If there are comments, sort them and put them in the list.
|
||||
var comments = sortComments(data.comments);
|
||||
speed = data.comments.length * 100;
|
||||
appendComments(comments, ul);
|
||||
ul.data('empty', false);
|
||||
}
|
||||
$('#cn' + id).slideUp(speed + 200);
|
||||
ul.slideDown(speed);
|
||||
},
|
||||
error: function(request, textStatus, error) {
|
||||
showError('Oops, there was a problem retrieving the comments.');
|
||||
},
|
||||
dataType: 'json'
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Add a comment via ajax and insert the comment into the comment tree.
|
||||
*/
|
||||
function addComment(form) {
|
||||
var node_id = form.find('input[name="node"]').val();
|
||||
var parent_id = form.find('input[name="parent"]').val();
|
||||
var text = form.find('textarea[name="comment"]').val();
|
||||
var proposal = form.find('textarea[name="proposal"]').val();
|
||||
|
||||
if (text == '') {
|
||||
showError('Please enter a comment.');
|
||||
return;
|
||||
}
|
||||
|
||||
// Disable the form that is being submitted.
|
||||
form.find('textarea,input').attr('disabled', 'disabled');
|
||||
|
||||
// Send the comment to the server.
|
||||
$.ajax({
|
||||
type: "POST",
|
||||
url: opts.addCommentURL,
|
||||
dataType: 'json',
|
||||
data: {
|
||||
node: node_id,
|
||||
parent: parent_id,
|
||||
text: text,
|
||||
proposal: proposal
|
||||
},
|
||||
success: function(data, textStatus, error) {
|
||||
// Reset the form.
|
||||
if (node_id) {
|
||||
hideProposeChange(node_id);
|
||||
}
|
||||
form.find('textarea')
|
||||
.val('')
|
||||
.add(form.find('input'))
|
||||
.removeAttr('disabled');
|
||||
var ul = $('#cl' + (node_id || parent_id));
|
||||
if (ul.data('empty')) {
|
||||
$(ul).empty();
|
||||
ul.data('empty', false);
|
||||
}
|
||||
insertComment(data.comment);
|
||||
var ao = $('#ao' + node_id);
|
||||
ao.find('img').attr({'src': opts.commentBrightImage});
|
||||
if (node_id) {
|
||||
// if this was a "root" comment, remove the commenting box
|
||||
// (the user can get it back by reopening the comment popup)
|
||||
$('#ca' + node_id).slideUp();
|
||||
}
|
||||
},
|
||||
error: function(request, textStatus, error) {
|
||||
form.find('textarea,input').removeAttr('disabled');
|
||||
showError('Oops, there was a problem adding the comment.');
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Recursively append comments to the main comment list and children
|
||||
* lists, creating the comment tree.
|
||||
*/
|
||||
function appendComments(comments, ul) {
|
||||
$.each(comments, function() {
|
||||
var div = createCommentDiv(this);
|
||||
ul.append($(document.createElement('li')).html(div));
|
||||
appendComments(this.children, div.find('ul.comment-children'));
|
||||
// To avoid stagnating data, don't store the comments children in data.
|
||||
this.children = null;
|
||||
div.data('comment', this);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* After adding a new comment, it must be inserted in the correct
|
||||
* location in the comment tree.
|
||||
*/
|
||||
function insertComment(comment) {
|
||||
var div = createCommentDiv(comment);
|
||||
|
||||
// To avoid stagnating data, don't store the comments children in data.
|
||||
comment.children = null;
|
||||
div.data('comment', comment);
|
||||
|
||||
var ul = $('#cl' + (comment.node || comment.parent));
|
||||
var siblings = getChildren(ul);
|
||||
|
||||
var li = $(document.createElement('li'));
|
||||
li.hide();
|
||||
|
||||
// Determine where in the parents children list to insert this comment.
|
||||
for(i=0; i < siblings.length; i++) {
|
||||
if (comp(comment, siblings[i]) <= 0) {
|
||||
$('#cd' + siblings[i].id)
|
||||
.parent()
|
||||
.before(li.html(div));
|
||||
li.slideDown('fast');
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
||||
// If we get here, this comment rates lower than all the others,
|
||||
// or it is the only comment in the list.
|
||||
ul.append(li.html(div));
|
||||
li.slideDown('fast');
|
||||
}
|
||||
|
||||
function acceptComment(id) {
|
||||
$.ajax({
|
||||
type: 'POST',
|
||||
url: opts.acceptCommentURL,
|
||||
data: {id: id},
|
||||
success: function(data, textStatus, request) {
|
||||
$('#cm' + id).fadeOut('fast');
|
||||
$('#cd' + id).removeClass('moderate');
|
||||
},
|
||||
error: function(request, textStatus, error) {
|
||||
showError('Oops, there was a problem accepting the comment.');
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
function deleteComment(id) {
|
||||
$.ajax({
|
||||
type: 'POST',
|
||||
url: opts.deleteCommentURL,
|
||||
data: {id: id},
|
||||
success: function(data, textStatus, request) {
|
||||
var div = $('#cd' + id);
|
||||
if (data == 'delete') {
|
||||
// Moderator mode: remove the comment and all children immediately
|
||||
div.slideUp('fast', function() {
|
||||
div.remove();
|
||||
});
|
||||
return;
|
||||
}
|
||||
// User mode: only mark the comment as deleted
|
||||
div
|
||||
.find('span.user-id:first')
|
||||
.text('[deleted]').end()
|
||||
.find('div.comment-text:first')
|
||||
.text('[deleted]').end()
|
||||
.find('#cm' + id + ', #dc' + id + ', #ac' + id + ', #rc' + id +
|
||||
', #sp' + id + ', #hp' + id + ', #cr' + id + ', #rl' + id)
|
||||
.remove();
|
||||
var comment = div.data('comment');
|
||||
comment.username = '[deleted]';
|
||||
comment.text = '[deleted]';
|
||||
div.data('comment', comment);
|
||||
},
|
||||
error: function(request, textStatus, error) {
|
||||
showError('Oops, there was a problem deleting the comment.');
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
function showProposal(id) {
|
||||
$('#sp' + id).hide();
|
||||
$('#hp' + id).show();
|
||||
$('#pr' + id).slideDown('fast');
|
||||
}
|
||||
|
||||
function hideProposal(id) {
|
||||
$('#hp' + id).hide();
|
||||
$('#sp' + id).show();
|
||||
$('#pr' + id).slideUp('fast');
|
||||
}
|
||||
|
||||
function showProposeChange(id) {
|
||||
$('#pc' + id).hide();
|
||||
$('#hc' + id).show();
|
||||
var textarea = $('#pt' + id);
|
||||
textarea.val(textarea.data('source'));
|
||||
$.fn.autogrow.resize(textarea[0]);
|
||||
textarea.slideDown('fast');
|
||||
}
|
||||
|
||||
function hideProposeChange(id) {
|
||||
$('#hc' + id).hide();
|
||||
$('#pc' + id).show();
|
||||
var textarea = $('#pt' + id);
|
||||
textarea.val('').removeAttr('disabled');
|
||||
textarea.slideUp('fast');
|
||||
}
|
||||
|
||||
function toggleCommentMarkupBox(id) {
|
||||
$('#mb' + id).toggle();
|
||||
}
|
||||
|
||||
/** Handle when the user clicks on a sort by link. */
|
||||
function handleReSort(link) {
|
||||
var classes = link.attr('class').split(/\s+/);
|
||||
for (var i=0; i<classes.length; i++) {
|
||||
if (classes[i] != 'sort-option') {
|
||||
by = classes[i].substring(2);
|
||||
}
|
||||
}
|
||||
setComparator();
|
||||
// Save/update the sortBy cookie.
|
||||
var expiration = new Date();
|
||||
expiration.setDate(expiration.getDate() + 365);
|
||||
document.cookie= 'sortBy=' + escape(by) +
|
||||
';expires=' + expiration.toUTCString();
|
||||
$('ul.comment-ul').each(function(index, ul) {
|
||||
var comments = getChildren($(ul), true);
|
||||
comments = sortComments(comments);
|
||||
appendComments(comments, $(ul).empty());
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Function to process a vote when a user clicks an arrow.
|
||||
*/
|
||||
function handleVote(link) {
|
||||
if (!opts.voting) {
|
||||
showError("You'll need to login to vote.");
|
||||
return;
|
||||
}
|
||||
|
||||
var id = link.attr('id');
|
||||
if (!id) {
|
||||
// Didn't click on one of the voting arrows.
|
||||
return;
|
||||
}
|
||||
// If it is an unvote, the new vote value is 0,
|
||||
// Otherwise it's 1 for an upvote, or -1 for a downvote.
|
||||
var value = 0;
|
||||
if (id.charAt(1) != 'u') {
|
||||
value = id.charAt(0) == 'u' ? 1 : -1;
|
||||
}
|
||||
// The data to be sent to the server.
|
||||
var d = {
|
||||
comment_id: id.substring(2),
|
||||
value: value
|
||||
};
|
||||
|
||||
// Swap the vote and unvote links.
|
||||
link.hide();
|
||||
$('#' + id.charAt(0) + (id.charAt(1) == 'u' ? 'v' : 'u') + d.comment_id)
|
||||
.show();
|
||||
|
||||
// The div the comment is displayed in.
|
||||
var div = $('div#cd' + d.comment_id);
|
||||
var data = div.data('comment');
|
||||
|
||||
// If this is not an unvote, and the other vote arrow has
|
||||
// already been pressed, unpress it.
|
||||
if ((d.value !== 0) && (data.vote === d.value * -1)) {
|
||||
$('#' + (d.value == 1 ? 'd' : 'u') + 'u' + d.comment_id).hide();
|
||||
$('#' + (d.value == 1 ? 'd' : 'u') + 'v' + d.comment_id).show();
|
||||
}
|
||||
|
||||
// Update the comments rating in the local data.
|
||||
data.rating += (data.vote === 0) ? d.value : (d.value - data.vote);
|
||||
data.vote = d.value;
|
||||
div.data('comment', data);
|
||||
|
||||
// Change the rating text.
|
||||
div.find('.rating:first')
|
||||
.text(data.rating + ' point' + (data.rating == 1 ? '' : 's'));
|
||||
|
||||
// Send the vote information to the server.
|
||||
$.ajax({
|
||||
type: "POST",
|
||||
url: opts.processVoteURL,
|
||||
data: d,
|
||||
error: function(request, textStatus, error) {
|
||||
showError('Oops, there was a problem casting that vote.');
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Open a reply form used to reply to an existing comment.
|
||||
*/
|
||||
function openReply(id) {
|
||||
// Swap out the reply link for the hide link
|
||||
$('#rl' + id).hide();
|
||||
$('#cr' + id).show();
|
||||
|
||||
// Add the reply li to the children ul.
|
||||
var div = $(renderTemplate(replyTemplate, {id: id})).hide();
|
||||
$('#cl' + id)
|
||||
.prepend(div)
|
||||
// Setup the submit handler for the reply form.
|
||||
.find('#rf' + id)
|
||||
.submit(function(event) {
|
||||
event.preventDefault();
|
||||
addComment($('#rf' + id));
|
||||
closeReply(id);
|
||||
})
|
||||
.find('input[type=button]')
|
||||
.click(function() {
|
||||
closeReply(id);
|
||||
});
|
||||
div.slideDown('fast', function() {
|
||||
$('#rf' + id).find('textarea').focus();
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Close the reply form opened with openReply.
|
||||
*/
|
||||
function closeReply(id) {
|
||||
// Remove the reply div from the DOM.
|
||||
$('#rd' + id).slideUp('fast', function() {
|
||||
$(this).remove();
|
||||
});
|
||||
|
||||
// Swap out the hide link for the reply link
|
||||
$('#cr' + id).hide();
|
||||
$('#rl' + id).show();
|
||||
}
|
||||
|
||||
/**
|
||||
* Recursively sort a tree of comments using the comp comparator.
|
||||
*/
|
||||
function sortComments(comments) {
|
||||
comments.sort(comp);
|
||||
$.each(comments, function() {
|
||||
this.children = sortComments(this.children);
|
||||
});
|
||||
return comments;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the children comments from a ul. If recursive is true,
|
||||
* recursively include childrens' children.
|
||||
*/
|
||||
function getChildren(ul, recursive) {
|
||||
var children = [];
|
||||
ul.children().children("[id^='cd']")
|
||||
.each(function() {
|
||||
var comment = $(this).data('comment');
|
||||
if (recursive)
|
||||
comment.children = getChildren($(this).find('#cl' + comment.id), true);
|
||||
children.push(comment);
|
||||
});
|
||||
return children;
|
||||
}
|
||||
|
||||
/** Create a div to display a comment in. */
|
||||
function createCommentDiv(comment) {
|
||||
if (!comment.displayed && !opts.moderator) {
|
||||
return $('<div class="moderate">Thank you! Your comment will show up '
|
||||
+ 'once it is has been approved by a moderator.</div>');
|
||||
}
|
||||
// Prettify the comment rating.
|
||||
comment.pretty_rating = comment.rating + ' point' +
|
||||
(comment.rating == 1 ? '' : 's');
|
||||
// Make a class (for displaying not yet moderated comments differently)
|
||||
comment.css_class = comment.displayed ? '' : ' moderate';
|
||||
// Create a div for this comment.
|
||||
var context = $.extend({}, opts, comment);
|
||||
var div = $(renderTemplate(commentTemplate, context));
|
||||
|
||||
// If the user has voted on this comment, highlight the correct arrow.
|
||||
if (comment.vote) {
|
||||
var direction = (comment.vote == 1) ? 'u' : 'd';
|
||||
div.find('#' + direction + 'v' + comment.id).hide();
|
||||
div.find('#' + direction + 'u' + comment.id).show();
|
||||
}
|
||||
|
||||
if (opts.moderator || comment.text != '[deleted]') {
|
||||
div.find('a.reply').show();
|
||||
if (comment.proposal_diff)
|
||||
div.find('#sp' + comment.id).show();
|
||||
if (opts.moderator && !comment.displayed)
|
||||
div.find('#cm' + comment.id).show();
|
||||
if (opts.moderator || (opts.username == comment.username))
|
||||
div.find('#dc' + comment.id).show();
|
||||
}
|
||||
return div;
|
||||
}
|
||||
|
||||
/**
|
||||
* A simple template renderer. Placeholders such as <%id%> are replaced
|
||||
* by context['id'] with items being escaped. Placeholders such as <#id#>
|
||||
* are not escaped.
|
||||
*/
|
||||
function renderTemplate(template, context) {
|
||||
var esc = $(document.createElement('div'));
|
||||
|
||||
function handle(ph, escape) {
|
||||
var cur = context;
|
||||
$.each(ph.split('.'), function() {
|
||||
cur = cur[this];
|
||||
});
|
||||
return escape ? esc.text(cur || "").html() : cur;
|
||||
}
|
||||
|
||||
return template.replace(/<([%#])([\w\.]*)\1>/g, function() {
|
||||
return handle(arguments[2], arguments[1] == '%' ? true : false);
|
||||
});
|
||||
}
|
||||
|
||||
/** Flash an error message briefly. */
|
||||
function showError(message) {
|
||||
$(document.createElement('div')).attr({'class': 'popup-error'})
|
||||
.append($(document.createElement('div'))
|
||||
.attr({'class': 'error-message'}).text(message))
|
||||
.appendTo('body')
|
||||
.fadeIn("slow")
|
||||
.delay(2000)
|
||||
.fadeOut("slow");
|
||||
}
|
||||
|
||||
/** Add a link the user uses to open the comments popup. */
|
||||
$.fn.comment = function() {
|
||||
return this.each(function() {
|
||||
var id = $(this).attr('id').substring(1);
|
||||
var count = COMMENT_METADATA[id];
|
||||
var title = count + ' comment' + (count == 1 ? '' : 's');
|
||||
var image = count > 0 ? opts.commentBrightImage : opts.commentImage;
|
||||
var addcls = count == 0 ? ' nocomment' : '';
|
||||
$(this)
|
||||
.append(
|
||||
$(document.createElement('a')).attr({
|
||||
href: '#',
|
||||
'class': 'sphinx-comment-open' + addcls,
|
||||
id: 'ao' + id
|
||||
})
|
||||
.append($(document.createElement('img')).attr({
|
||||
src: image,
|
||||
alt: 'comment',
|
||||
title: title
|
||||
}))
|
||||
.click(function(event) {
|
||||
event.preventDefault();
|
||||
show($(this).attr('id').substring(2));
|
||||
})
|
||||
)
|
||||
.append(
|
||||
$(document.createElement('a')).attr({
|
||||
href: '#',
|
||||
'class': 'sphinx-comment-close hidden',
|
||||
id: 'ah' + id
|
||||
})
|
||||
.append($(document.createElement('img')).attr({
|
||||
src: opts.closeCommentImage,
|
||||
alt: 'close',
|
||||
title: 'close'
|
||||
}))
|
||||
.click(function(event) {
|
||||
event.preventDefault();
|
||||
hide($(this).attr('id').substring(2));
|
||||
})
|
||||
);
|
||||
});
|
||||
};
|
||||
|
||||
var opts = {
|
||||
processVoteURL: '/_process_vote',
|
||||
addCommentURL: '/_add_comment',
|
||||
getCommentsURL: '/_get_comments',
|
||||
acceptCommentURL: '/_accept_comment',
|
||||
deleteCommentURL: '/_delete_comment',
|
||||
commentImage: '/static/_static/comment.png',
|
||||
closeCommentImage: '/static/_static/comment-close.png',
|
||||
loadingImage: '/static/_static/ajax-loader.gif',
|
||||
commentBrightImage: '/static/_static/comment-bright.png',
|
||||
upArrow: '/static/_static/up.png',
|
||||
downArrow: '/static/_static/down.png',
|
||||
upArrowPressed: '/static/_static/up-pressed.png',
|
||||
downArrowPressed: '/static/_static/down-pressed.png',
|
||||
voting: false,
|
||||
moderator: false
|
||||
};
|
||||
|
||||
if (typeof COMMENT_OPTIONS != "undefined") {
|
||||
opts = jQuery.extend(opts, COMMENT_OPTIONS);
|
||||
}
|
||||
|
||||
var popupTemplate = '\
|
||||
<div class="sphinx-comments" id="sc<%id%>">\
|
||||
<p class="sort-options">\
|
||||
Sort by:\
|
||||
<a href="#" class="sort-option byrating">best rated</a>\
|
||||
<a href="#" class="sort-option byascage">newest</a>\
|
||||
<a href="#" class="sort-option byage">oldest</a>\
|
||||
</p>\
|
||||
<div class="comment-header">Comments</div>\
|
||||
<div class="comment-loading" id="cn<%id%>">\
|
||||
loading comments... <img src="<%loadingImage%>" alt="" /></div>\
|
||||
<ul id="cl<%id%>" class="comment-ul"></ul>\
|
||||
<div id="ca<%id%>">\
|
||||
<p class="add-a-comment">Add a comment\
|
||||
(<a href="#" class="comment-markup" id="ab<%id%>">markup</a>):</p>\
|
||||
<div class="comment-markup-box" id="mb<%id%>">\
|
||||
reStructured text markup: <i>*emph*</i>, <b>**strong**</b>, \
|
||||
<code>``code``</code>, \
|
||||
code blocks: <code>::</code> and an indented block after blank line</div>\
|
||||
<form method="post" id="cf<%id%>" class="comment-form" action="">\
|
||||
<textarea name="comment" cols="80"></textarea>\
|
||||
<p class="propose-button">\
|
||||
<a href="#" id="pc<%id%>" class="show-propose-change">\
|
||||
Propose a change ▹\
|
||||
</a>\
|
||||
<a href="#" id="hc<%id%>" class="hide-propose-change">\
|
||||
Propose a change ▿\
|
||||
</a>\
|
||||
</p>\
|
||||
<textarea name="proposal" id="pt<%id%>" cols="80"\
|
||||
spellcheck="false"></textarea>\
|
||||
<input type="submit" value="Add comment" />\
|
||||
<input type="hidden" name="node" value="<%id%>" />\
|
||||
<input type="hidden" name="parent" value="" />\
|
||||
</form>\
|
||||
</div>\
|
||||
</div>';
|
||||
|
||||
var commentTemplate = '\
|
||||
<div id="cd<%id%>" class="sphinx-comment<%css_class%>">\
|
||||
<div class="vote">\
|
||||
<div class="arrow">\
|
||||
<a href="#" id="uv<%id%>" class="vote" title="vote up">\
|
||||
<img src="<%upArrow%>" />\
|
||||
</a>\
|
||||
<a href="#" id="uu<%id%>" class="un vote" title="vote up">\
|
||||
<img src="<%upArrowPressed%>" />\
|
||||
</a>\
|
||||
</div>\
|
||||
<div class="arrow">\
|
||||
<a href="#" id="dv<%id%>" class="vote" title="vote down">\
|
||||
<img src="<%downArrow%>" id="da<%id%>" />\
|
||||
</a>\
|
||||
<a href="#" id="du<%id%>" class="un vote" title="vote down">\
|
||||
<img src="<%downArrowPressed%>" />\
|
||||
</a>\
|
||||
</div>\
|
||||
</div>\
|
||||
<div class="comment-content">\
|
||||
<p class="tagline comment">\
|
||||
<span class="user-id"><%username%></span>\
|
||||
<span class="rating"><%pretty_rating%></span>\
|
||||
<span class="delta"><%time.delta%></span>\
|
||||
</p>\
|
||||
<div class="comment-text comment"><#text#></div>\
|
||||
<p class="comment-opts comment">\
|
||||
<a href="#" class="reply hidden" id="rl<%id%>">reply ▹</a>\
|
||||
<a href="#" class="close-reply" id="cr<%id%>">reply ▿</a>\
|
||||
<a href="#" id="sp<%id%>" class="show-proposal">proposal ▹</a>\
|
||||
<a href="#" id="hp<%id%>" class="hide-proposal">proposal ▿</a>\
|
||||
<a href="#" id="dc<%id%>" class="delete-comment hidden">delete</a>\
|
||||
<span id="cm<%id%>" class="moderation hidden">\
|
||||
<a href="#" id="ac<%id%>" class="accept-comment">accept</a>\
|
||||
</span>\
|
||||
</p>\
|
||||
<pre class="proposal" id="pr<%id%>">\
|
||||
<#proposal_diff#>\
|
||||
</pre>\
|
||||
<ul class="comment-children" id="cl<%id%>"></ul>\
|
||||
</div>\
|
||||
<div class="clearleft"></div>\
|
||||
</div>\
|
||||
</div>';
|
||||
|
||||
var replyTemplate = '\
|
||||
<li>\
|
||||
<div class="reply-div" id="rd<%id%>">\
|
||||
<form id="rf<%id%>">\
|
||||
<textarea name="comment" cols="80"></textarea>\
|
||||
<input type="submit" value="Add reply" />\
|
||||
<input type="button" value="Cancel" />\
|
||||
<input type="hidden" name="parent" value="<%id%>" />\
|
||||
<input type="hidden" name="node" value="" />\
|
||||
</form>\
|
||||
</div>\
|
||||
</li>';
|
||||
|
||||
$(document).ready(function() {
|
||||
init();
|
||||
});
|
||||
})(jQuery);
|
||||
|
||||
$(document).ready(function() {
|
||||
// add comment anchors for all paragraphs that are commentable
|
||||
$('.sphinx-has-comment').comment();
|
||||
|
||||
// highlight search words in search results
|
||||
$("div.context").each(function() {
|
||||
var params = $.getQueryParameters();
|
||||
var terms = (params.q) ? params.q[0].split(/\s+/) : [];
|
||||
var result = $(this);
|
||||
$.each(terms, function() {
|
||||
result.highlightText(this.toLowerCase(), 'highlighted');
|
||||
});
|
||||
});
|
||||
|
||||
// directly open comment window if requested
|
||||
var anchor = document.location.hash;
|
||||
if (anchor.substring(0, 9) == '#comment-') {
|
||||
$('#ao' + anchor.substring(9)).click();
|
||||
document.location.hash = '#s' + anchor.substring(9);
|
||||
}
|
||||
});
|
||||
@ -1,96 +0,0 @@
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
||||
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
||||
|
||||
|
||||
<html xmlns="http://www.w3.org/1999/xhtml">
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
|
||||
<title><no title> — Soil 0.1 documentation</title>
|
||||
|
||||
<link rel="stylesheet" href="_static/alabaster.css" type="text/css" />
|
||||
<link rel="stylesheet" href="_static/pygments.css" type="text/css" />
|
||||
|
||||
<script type="text/javascript">
|
||||
var DOCUMENTATION_OPTIONS = {
|
||||
URL_ROOT: './',
|
||||
VERSION: '0.1',
|
||||
COLLAPSE_INDEX: false,
|
||||
FILE_SUFFIX: '.html',
|
||||
HAS_SOURCE: true,
|
||||
SOURCELINK_SUFFIX: '.txt'
|
||||
};
|
||||
</script>
|
||||
<script type="text/javascript" src="_static/jquery.js"></script>
|
||||
<script type="text/javascript" src="_static/underscore.js"></script>
|
||||
<script type="text/javascript" src="_static/doctools.js"></script>
|
||||
<link rel="index" title="Index" href="genindex.html" />
|
||||
<link rel="search" title="Search" href="search.html" />
|
||||
<link rel="prev" title="Models" href="models.html" />
|
||||
|
||||
<link rel="stylesheet" href="_static/custom.css" type="text/css" />
|
||||
|
||||
|
||||
<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
|
||||
|
||||
</head>
|
||||
<body role="document">
|
||||
|
||||
|
||||
<div class="document">
|
||||
<div class="documentwrapper">
|
||||
<div class="bodywrapper">
|
||||
<div class="body" role="main">
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="index.html">Documentation overview</a><ul>
|
||||
<li>Previous: <a href="models.html" title="previous chapter">Models</a></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div role="note" aria-label="source link">
|
||||
<h3>This Page</h3>
|
||||
<ul class="this-page-menu">
|
||||
<li><a href="_sources/demo.rst.txt"
|
||||
rel="nofollow">Show Source</a></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<form class="search" action="search.html" method="get">
|
||||
<div><input type="text" name="q" /></div>
|
||||
<div><input type="submit" value="Go" /></div>
|
||||
<input type="hidden" name="check_keywords" value="yes" />
|
||||
<input type="hidden" name="area" value="default" />
|
||||
</form>
|
||||
</div>
|
||||
<script type="text/javascript">$('#searchbox').show(0);</script>
|
||||
</div>
|
||||
</div>
|
||||
<div class="clearer"></div>
|
||||
</div>
|
||||
<div class="footer">
|
||||
©2017, GSI.
|
||||
|
||||
|
|
||||
Powered by <a href="http://sphinx-doc.org/">Sphinx 1.5.1</a>
|
||||
& <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.9</a>
|
||||
|
||||
|
|
||||
<a href="_sources/demo.rst.txt"
|
||||
rel="nofollow">Page source</a>
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
@ -1,94 +0,0 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
||||
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
||||
|
||||
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<div class="section" id="developing-new-models">
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<h1>Developing new models<a class="headerlink" href="#developing-new-models" title="Permalink to this headline">¶</a></h1>
|
||||
<p>This document describes how to develop a new analysis model.</p>
|
||||
<div class="section" id="what-is-a-model">
|
||||
<h2>What is a model?<a class="headerlink" href="#what-is-a-model" title="Permalink to this headline">¶</a></h2>
|
||||
<p>A model defines the behaviour of the agents with a view to assessing their effects on the system as a whole.
|
||||
In practice, a model consists of at least two parts:</p>
|
||||
<ul class="simple">
|
||||
<li>Python module: the actual code that describes the behaviour.</li>
|
||||
<li>Setting up the variables in the Settings JSON file.</li>
|
||||
</ul>
|
||||
<p>This separation allows us to run the simulation with different agents.</p>
|
||||
</div>
|
||||
<div class="section" id="models-code">
|
||||
<h2>Models Code<a class="headerlink" href="#models-code" title="Permalink to this headline">¶</a></h2>
|
||||
<p>All the models are imported to the main file. The initialization look like this:</p>
|
||||
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">settings</span>
|
||||
|
||||
<span class="n">networkStatus</span> <span class="o">=</span> <span class="p">{}</span> <span class="c1"># Dict that will contain the status of every agent in the network</span>
|
||||
|
||||
<span class="n">sentimentCorrelationNodeArray</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">settings</span><span class="o">.</span><span class="n">network_params</span><span class="p">[</span><span class="s2">"number_of_nodes"</span><span class="p">]):</span>
|
||||
<span class="n">sentimentCorrelationNodeArray</span><span class="o">.</span><span class="n">append</span><span class="p">({</span><span class="s1">'id'</span><span class="p">:</span> <span class="n">x</span><span class="p">})</span>
|
||||
<span class="c1"># Initialize agent states. Let's assume everyone is normal.</span>
|
||||
<span class="n">init_states</span> <span class="o">=</span> <span class="p">[{</span><span class="s1">'id'</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span> <span class="p">}</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">settings</span><span class="o">.</span><span class="n">network_params</span><span class="p">[</span><span class="s2">"number_of_nodes"</span><span class="p">])]</span>
|
||||
<span class="c1"># add keys as as necessary, but "id" must always refer to that state category</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>A new model have to inherit the BaseBehaviour class which is in the same module.
|
||||
There are two basics methods:</p>
|
||||
<ul class="simple">
|
||||
<li>__init__</li>
|
||||
<li>step: used to define the behaviour over time.</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div class="section" id="variable-initialization">
|
||||
<h2>Variable Initialization<a class="headerlink" href="#variable-initialization" title="Permalink to this headline">¶</a></h2>
|
||||
<p>The different parameters of the model have to be initialize in the Simulation Settings JSON file which will be
|
||||
passed as a parameter to the simulation.</p>
|
||||
<div class="code json highlight-default"><div class="highlight"><pre><span></span><span class="p">{</span>
|
||||
<span class="s2">"agent"</span><span class="p">:</span> <span class="p">[</span><span class="s2">"SISaModel"</span><span class="p">,</span><span class="s2">"ControlModelM2"</span><span class="p">],</span>
|
||||
|
||||
<span class="s2">"neutral_discontent_spon_prob"</span><span class="p">:</span> <span class="mf">0.04</span><span class="p">,</span>
|
||||
<span class="s2">"neutral_discontent_infected_prob"</span><span class="p">:</span> <span class="mf">0.04</span><span class="p">,</span>
|
||||
<span class="s2">"neutral_content_spon_prob"</span><span class="p">:</span> <span class="mf">0.18</span><span class="p">,</span>
|
||||
<span class="s2">"neutral_content_infected_prob"</span><span class="p">:</span> <span class="mf">0.02</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"discontent_neutral"</span><span class="p">:</span> <span class="mf">0.13</span><span class="p">,</span>
|
||||
<span class="s2">"discontent_content"</span><span class="p">:</span> <span class="mf">0.07</span><span class="p">,</span>
|
||||
<span class="s2">"variance_d_c"</span><span class="p">:</span> <span class="mf">0.02</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"content_discontent"</span><span class="p">:</span> <span class="mf">0.009</span><span class="p">,</span>
|
||||
<span class="s2">"variance_c_d"</span><span class="p">:</span> <span class="mf">0.003</span><span class="p">,</span>
|
||||
<span class="s2">"content_neutral"</span><span class="p">:</span> <span class="mf">0.088</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"standard_variance"</span><span class="p">:</span> <span class="mf">0.055</span><span class="p">,</span>
|
||||
|
||||
|
||||
<span class="s2">"prob_neutral_making_denier"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"prob_infect"</span><span class="p">:</span> <span class="mf">0.075</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"prob_cured_healing_infected"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
<span class="s2">"prob_cured_vaccinate_neutral"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"prob_vaccinated_healing_infected"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
<span class="s2">"prob_vaccinated_vaccinate_neutral"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
<span class="s2">"prob_generate_anti_rumor"</span><span class="p">:</span> <span class="mf">0.035</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>In this file you will also define the models you are going to simulate. You can simulate as many models as you want.
|
||||
The simulation returns one result for each model, executing each model separately. For the usage, see <a class="reference internal" href="usage.html"><span class="doc">Usage</span></a>.</p>
|
||||
</div>
|
||||
<div class="section" id="example-model">
|
||||
<h2>Example Model<a class="headerlink" href="#example-model" title="Permalink to this headline">¶</a></h2>
|
||||
<p>In this section, we will implement a Sentiment Correlation Model.</p>
|
||||
<p>The class would look like this:</p>
|
||||
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">..BaseBehaviour</span> <span class="k">import</span> <span class="o">*</span>
|
||||
<span class="kn">from</span> <span class="nn">..</span> <span class="k">import</span> <span class="n">sentimentCorrelationNodeArray</span>
|
||||
|
||||
<span class="k">class</span> <span class="nc">SentimentCorrelationModel</span><span class="p">(</span><span class="n">BaseBehaviour</span><span class="p">):</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">environment</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">agent_id</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">state</span><span class="o">=</span><span class="p">()):</span>
|
||||
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">__init__</span><span class="p">(</span><span class="n">environment</span><span class="o">=</span><span class="n">environment</span><span class="p">,</span> <span class="n">agent_id</span><span class="o">=</span><span class="n">agent_id</span><span class="p">,</span> <span class="n">state</span><span class="o">=</span><span class="n">state</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">outside_effects_prob</span> <span class="o">=</span> <span class="n">environment</span><span class="o">.</span><span class="n">environment_params</span><span class="p">[</span><span class="s1">'outside_effects_prob'</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">anger_prob</span> <span class="o">=</span> <span class="n">environment</span><span class="o">.</span><span class="n">environment_params</span><span class="p">[</span><span class="s1">'anger_prob'</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">joy_prob</span> <span class="o">=</span> <span class="n">environment</span><span class="o">.</span><span class="n">environment_params</span><span class="p">[</span><span class="s1">'joy_prob'</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sadness_prob</span> <span class="o">=</span> <span class="n">environment</span><span class="o">.</span><span class="n">environment_params</span><span class="p">[</span><span class="s1">'sadness_prob'</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">disgust_prob</span> <span class="o">=</span> <span class="n">environment</span><span class="o">.</span><span class="n">environment_params</span><span class="p">[</span><span class="s1">'disgust_prob'</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">time_awareness</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">):</span> <span class="c1"># In this model we have 4 sentiments</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">time_awareness</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># 0-> Anger, 1-> joy, 2->sadness, 3 -> disgust</span>
|
||||
<span class="n">sentimentCorrelationNodeArray</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">id</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">env</span><span class="o">.</span><span class="n">now</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">step</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">now</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">behaviour</span><span class="p">()</span> <span class="c1"># Method which define the behaviour</span>
|
||||
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">now</span><span class="p">)</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>The variables will be modified by the user, so you have to include them in the Simulation Settings JSON file.</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
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|
||||
<h3><a href="index.html">Table Of Contents</a></h3>
|
||||
<ul>
|
||||
<li><a class="reference internal" href="#">Developing new models</a><ul>
|
||||
<li><a class="reference internal" href="#what-is-a-model">What is a model?</a></li>
|
||||
<li><a class="reference internal" href="#models-code">Models Code</a></li>
|
||||
<li><a class="reference internal" href="#variable-initialization">Variable Initialization</a></li>
|
||||
<li><a class="reference internal" href="#example-model">Example Model</a></li>
|
||||
</ul>
|
||||
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|
||||
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|
||||
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|
||||
<h3>Related Topics</h3>
|
||||
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|
||||
<li><a href="index.html">Documentation overview</a><ul>
|
||||
<li>Previous: <a href="usage.html" title="previous chapter">Usage</a></li>
|
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|
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<div class="section" id="usage">
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<h1>Usage<a class="headerlink" href="#usage" title="Permalink to this headline">¶</a></h1>
|
||||
<p>First of all, you need to install the package. See <a class="reference internal" href="installation.html"><span class="doc">Installation</span></a> for installation instructions.</p>
|
||||
<div class="section" id="simulation-settings">
|
||||
<h2>Simulation Settings<a class="headerlink" href="#simulation-settings" title="Permalink to this headline">¶</a></h2>
|
||||
<p>Once installed, before running a simulation, you need to configure it.</p>
|
||||
<ul>
|
||||
<li><p class="first">In the Settings JSON file you will find the configuration of the network.</p>
|
||||
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="p">{</span>
|
||||
<span class="s2">"network_type"</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
|
||||
<span class="s2">"number_of_nodes"</span><span class="p">:</span> <span class="mi">1000</span><span class="p">,</span>
|
||||
<span class="s2">"max_time"</span><span class="p">:</span> <span class="mi">50</span><span class="p">,</span>
|
||||
<span class="s2">"num_trials"</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
|
||||
<span class="s2">"timeout"</span><span class="p">:</span> <span class="mi">2</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
</li>
|
||||
<li><p class="first">In the Settings JSON file, you will also find the configuration of the models.</p>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div class="section" id="network-types">
|
||||
<h2>Network Types<a class="headerlink" href="#network-types" title="Permalink to this headline">¶</a></h2>
|
||||
<p>There are three types of network implemented, but you could add more.</p>
|
||||
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="k">if</span> <span class="n">settings</span><span class="o">.</span><span class="n">network_type</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">complete_graph</span><span class="p">(</span><span class="n">settings</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">settings</span><span class="o">.</span><span class="n">network_type</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">barabasi_albert_graph</span><span class="p">(</span><span class="n">settings</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">settings</span><span class="o">.</span><span class="n">network_type</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
|
||||
<span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">margulis_gabber_galil_graph</span><span class="p">(</span><span class="n">settings</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="c1"># More types of networks can be added here</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section" id="models-settings">
|
||||
<h2>Models Settings<a class="headerlink" href="#models-settings" title="Permalink to this headline">¶</a></h2>
|
||||
<p>After having configured the simulation, the next step is setting up the variables of the models.
|
||||
For this, you will need to modify the Settings JSON file again.</p>
|
||||
<div class="code json highlight-default"><div class="highlight"><pre><span></span><span class="p">{</span>
|
||||
<span class="s2">"agent"</span><span class="p">:</span> <span class="p">[</span><span class="s2">"SISaModel"</span><span class="p">,</span><span class="s2">"ControlModelM2"</span><span class="p">],</span>
|
||||
|
||||
<span class="s2">"neutral_discontent_spon_prob"</span><span class="p">:</span> <span class="mf">0.04</span><span class="p">,</span>
|
||||
<span class="s2">"neutral_discontent_infected_prob"</span><span class="p">:</span> <span class="mf">0.04</span><span class="p">,</span>
|
||||
<span class="s2">"neutral_content_spon_prob"</span><span class="p">:</span> <span class="mf">0.18</span><span class="p">,</span>
|
||||
<span class="s2">"neutral_content_infected_prob"</span><span class="p">:</span> <span class="mf">0.02</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"discontent_neutral"</span><span class="p">:</span> <span class="mf">0.13</span><span class="p">,</span>
|
||||
<span class="s2">"discontent_content"</span><span class="p">:</span> <span class="mf">0.07</span><span class="p">,</span>
|
||||
<span class="s2">"variance_d_c"</span><span class="p">:</span> <span class="mf">0.02</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"content_discontent"</span><span class="p">:</span> <span class="mf">0.009</span><span class="p">,</span>
|
||||
<span class="s2">"variance_c_d"</span><span class="p">:</span> <span class="mf">0.003</span><span class="p">,</span>
|
||||
<span class="s2">"content_neutral"</span><span class="p">:</span> <span class="mf">0.088</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"standard_variance"</span><span class="p">:</span> <span class="mf">0.055</span><span class="p">,</span>
|
||||
|
||||
|
||||
<span class="s2">"prob_neutral_making_denier"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"prob_infect"</span><span class="p">:</span> <span class="mf">0.075</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"prob_cured_healing_infected"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
<span class="s2">"prob_cured_vaccinate_neutral"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
|
||||
<span class="s2">"prob_vaccinated_healing_infected"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
<span class="s2">"prob_vaccinated_vaccinate_neutral"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
|
||||
<span class="s2">"prob_generate_anti_rumor"</span><span class="p">:</span> <span class="mf">0.035</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>In this file you will define the different models you are going to simulate. You can simulate as many models
|
||||
as you want. Each model will be simulated separately.</p>
|
||||
<p>After setting up the models, you have to initialize the parameters of each one. You will find the parameters needed
|
||||
in the documentation of each model.</p>
|
||||
<p>Parameter validation will fail if a required parameter without a default has not been provided.</p>
|
||||
</div>
|
||||
<div class="section" id="running-the-simulation">
|
||||
<h2>Running the Simulation<a class="headerlink" href="#running-the-simulation" title="Permalink to this headline">¶</a></h2>
|
||||
<p>After setting all the configuration, you will be able to run the simulation. All you need to do is execute:</p>
|
||||
<div class="code bash highlight-default"><div class="highlight"><pre><span></span><span class="n">python3</span> <span class="n">soil</span><span class="o">.</span><span class="n">py</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>The simulation will return a dynamic graph .gexf file which could be visualized with
|
||||
<a class="reference external" href="https://gephi.org/users/download/">Gephi</a>.</p>
|
||||
<p>It will also return one .png picture for each model simulated.</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
</div>
|
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<h3><a href="index.html">Table Of Contents</a></h3>
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<ul>
|
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<li><a class="reference internal" href="#">Usage</a><ul>
|
||||
<li><a class="reference internal" href="#simulation-settings">Simulation Settings</a></li>
|
||||
<li><a class="reference internal" href="#network-types">Network Types</a></li>
|
||||
<li><a class="reference internal" href="#models-settings">Models Settings</a></li>
|
||||
<li><a class="reference internal" href="#running-the-simulation">Running the Simulation</a></li>
|
||||
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|
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|
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|
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|
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<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="index.html">Documentation overview</a><ul>
|
||||
<li>Previous: <a href="installation.html" title="previous chapter">Installation</a></li>
|
||||
<li>Next: <a href="models.html" title="next chapter">Developing new models</a></li>
|
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|
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||||
Installation
|
||||
------------
|
||||
The latest version can be installed through GitLab.
|
||||
|
||||
The easiest way to install Soil is through pip:
|
||||
|
||||
.. code:: bash
|
||||
|
||||
pip install soil
|
||||
|
||||
|
||||
Now test that it worked by running the command line tool
|
||||
|
||||
.. code:: bash
|
||||
|
||||
git clone https://lab.cluster.gsi.dit.upm.es/soil/soil.git
|
||||
soil --help
|
||||
|
||||
Or using soil programmatically:
|
||||
|
||||
.. code:: python
|
||||
|
||||
import soil
|
||||
print(soil.__version__)
|
||||
|
||||
The latest version can be installed through `GitLab <https://lab.cluster.gsi.dit.upm.es/soil/soil.git>`_.
|
||||
|
||||
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@ -0,0 +1,194 @@
|
||||
Quickstart
|
||||
----------
|
||||
|
||||
This section shows how to run simulations from simulation configuration files.
|
||||
First of all, you need to install the package (See :doc:`installation`)
|
||||
|
||||
Simulation configuration files are ``json`` or ``yaml`` files that define all the parameters of a simulation.
|
||||
Here's an example (``example.yml``).
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
---
|
||||
name: MyExampleSimulation
|
||||
max_time: 50
|
||||
num_trials: 3
|
||||
timeout: 2
|
||||
network_params:
|
||||
network_type: barabasi_albert_graph
|
||||
n: 100
|
||||
m: 2
|
||||
agent_distribution:
|
||||
- agent_type: SISaModel
|
||||
weight: 1
|
||||
state:
|
||||
id: content
|
||||
- agent_type: SISaModel
|
||||
weight: 1
|
||||
state:
|
||||
id: discontent
|
||||
- agent_type: SISaModel
|
||||
weight: 8
|
||||
state:
|
||||
id: neutral
|
||||
environment_params:
|
||||
prob_infect: 0.075
|
||||
|
||||
Now run the simulation with the command line tool:
|
||||
|
||||
.. code:: bash
|
||||
|
||||
soil example.yml
|
||||
|
||||
Once the simulation finishes, its results will be stored in a folder named ``MyExampleSimulation``.
|
||||
Four types of objects are saved by default: a pickle of the simulation, a ``YAML`` representation of the simulation (to re-launch it), for every trial, a csv file with the content of the state of every network node and the environment parameters at every step of the simulation as well as the network in gephi format (``gexf``).
|
||||
|
||||
|
||||
.. code::
|
||||
|
||||
soil_output
|
||||
├── Sim_prob_0
|
||||
│ ├── Sim_prob_0.dumped.yml
|
||||
│ ├── Sim_prob_0.simulation.pickle
|
||||
│ ├── Sim_prob_0_trial_0.environment.csv
|
||||
│ └── Sim_prob_0_trial_0.gexf
|
||||
|
||||
|
||||
This example configuration will run three trials of a simulation containing a randomly generated network.
|
||||
The 100 nodes in the network will be SISaModel agents, 10% of them will start in the content state, 10% in the discontent state, and the remaining 80% in the neutral state.
|
||||
All agents will have access to the environment, which only contains one variable, ``prob_infected``.
|
||||
The state of the agents will be updated every 2 seconds (``timeout``).
|
||||
|
||||
|
||||
Network
|
||||
=======
|
||||
|
||||
The network topology for the simulation can be loaded from an existing network file or generated with one of the random network generation methods from networkx.
|
||||
|
||||
Loading a network
|
||||
#################
|
||||
|
||||
To load an existing network, specify its path in the configuration:
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
---
|
||||
network_params:
|
||||
path: /tmp/mynetwork.gexf
|
||||
|
||||
Soil will try to guess what networkx method to use to read the file based on its extension.
|
||||
However, we only test using ``gexf`` files.
|
||||
|
||||
Generating a random network
|
||||
###########################
|
||||
|
||||
To generate a random network using one of networkx's built-in methods, specify the `graph generation algorithm <https://networkx.github.io/documentation/development/reference/generators.html>`_ and other parameters.
|
||||
For example, the following configuration is equivalent to :code:`nx.complete_graph(100)`:
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
network_params:
|
||||
network_type: complete_graph
|
||||
n: 100
|
||||
|
||||
Environment
|
||||
============
|
||||
The environment is the place where the shared state of the simulation is stored.
|
||||
For instance, the probability of certain events.
|
||||
The configuration file may specify the initial value of the environment parameters:
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
environment_params:
|
||||
daily_probability_of_earthquake: 0.001
|
||||
number_of_earthquakes: 0
|
||||
|
||||
Agents
|
||||
======
|
||||
Agents are a way of modelling behavior.
|
||||
Agents can be characterized with two variables: an agent type (``agent_type``) and its state.
|
||||
Only one agent is executed at a time (generally, every ``timeout`` seconds), and it has access to its state and the environment parameters.
|
||||
Through the environment, it can access the network topology and the state of other agents.
|
||||
|
||||
There are three three types of agents according to how they are added to the simulation: network agents, environment agent, and other agents.
|
||||
|
||||
Network Agents
|
||||
##############
|
||||
Network agents are attached to a node in the topology.
|
||||
The configuration file allows you to specify how agents will be mapped to topology nodes.
|
||||
|
||||
The simplest way is to specify a single type of agent.
|
||||
Hence, every node in the network will have an associated agent of that type.
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
agent_type: SISaModel
|
||||
|
||||
It is also possible to add more than one type of agent to the simulation, and to control the ratio of each type (``weight``).
|
||||
For instance, with following configuration, it is five times more likely for a node to be assigned a CounterModel type than a SISaModel type.
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
agent_distribution:
|
||||
- agent_type: SISaModel
|
||||
weight: 1
|
||||
- agent_type: CounterModel
|
||||
weight: 5
|
||||
|
||||
In addition to agent type, you may also add a custom initial state to the distribution.
|
||||
This is very useful to add the same agent type with different states.
|
||||
e.g., to populate the network with SISaModel, roughly 10% of them with a discontent state:
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
agent_distribution:
|
||||
- agent_type: SISaModel
|
||||
weight: 9
|
||||
state:
|
||||
id: neutral
|
||||
- agent_type: SISaModel
|
||||
weight: 1
|
||||
state:
|
||||
id: discontent
|
||||
|
||||
Lastly, the configuration may include initial state for one or more nodes.
|
||||
For instance, to add a state for the two nodes in this configuration:
|
||||
|
||||
.. code:: yaml
|
||||
|
||||
agent_type: SISaModel
|
||||
network:
|
||||
network_type: complete_graph
|
||||
n: 2
|
||||
states:
|
||||
- id: content
|
||||
- id: discontent
|
||||
|
||||
|
||||
Or to add state only to specific nodes (by ``id``).
|
||||
For example, to apply special skills to Linux Torvalds in a simulation:
|
||||
|
||||
.. literalinclude:: ../examples/torvalds.yml
|
||||
:language: yaml
|
||||
|
||||
|
||||
Environment Agents
|
||||
##################
|
||||
In addition to network agents, more agents can be added to the simulation.
|
||||
These agens are programmed in much the same way as network agents, the only difference is that they will not be assigned to network nodes.
|
||||
|
||||
|
||||
.. code::
|
||||
|
||||
environment_agents:
|
||||
- agent_type: MyAgent
|
||||
state:
|
||||
mood: happy
|
||||
- agent_type: DummyAgent
|
||||
|
||||
|
||||
Visualizing the results
|
||||
=======================
|
||||
|
||||
The simulation will return a dynamic graph .gexf file which could be visualized with
|
||||
`Gephi <https://gephi.org/users/download/>`__.
|
||||
@ -1,99 +0,0 @@
|
||||
Usage
|
||||
-----
|
||||
|
||||
First of all, you need to install the package. See :doc:`installation` for installation instructions.
|
||||
|
||||
Simulation Settings
|
||||
===================
|
||||
|
||||
Once installed, before running a simulation, you need to configure it.
|
||||
|
||||
* In the Settings JSON file you will find the configuration of the network.
|
||||
|
||||
.. code:: python
|
||||
|
||||
{
|
||||
"network_type": 1,
|
||||
"number_of_nodes": 1000,
|
||||
"max_time": 50,
|
||||
"num_trials": 1,
|
||||
"timeout": 2
|
||||
}
|
||||
|
||||
* In the Settings JSON file, you will also find the configuration of the models.
|
||||
|
||||
Network Types
|
||||
=============
|
||||
|
||||
There are three types of network implemented, but you could add more.
|
||||
|
||||
.. code:: python
|
||||
|
||||
if settings.network_type == 0:
|
||||
G = nx.complete_graph(settings.number_of_nodes)
|
||||
if settings.network_type == 1:
|
||||
G = nx.barabasi_albert_graph(settings.number_of_nodes, 10)
|
||||
if settings.network_type == 2:
|
||||
G = nx.margulis_gabber_galil_graph(settings.number_of_nodes, None)
|
||||
# More types of networks can be added here
|
||||
|
||||
Models Settings
|
||||
===============
|
||||
|
||||
After having configured the simulation, the next step is setting up the variables of the models.
|
||||
For this, you will need to modify the Settings JSON file again.
|
||||
|
||||
.. code:: json
|
||||
|
||||
{
|
||||
"agent": ["SISaModel","ControlModelM2"],
|
||||
|
||||
"neutral_discontent_spon_prob": 0.04,
|
||||
"neutral_discontent_infected_prob": 0.04,
|
||||
"neutral_content_spon_prob": 0.18,
|
||||
"neutral_content_infected_prob": 0.02,
|
||||
|
||||
"discontent_neutral": 0.13,
|
||||
"discontent_content": 0.07,
|
||||
"variance_d_c": 0.02,
|
||||
|
||||
"content_discontent": 0.009,
|
||||
"variance_c_d": 0.003,
|
||||
"content_neutral": 0.088,
|
||||
|
||||
"standard_variance": 0.055,
|
||||
|
||||
|
||||
"prob_neutral_making_denier": 0.035,
|
||||
|
||||
"prob_infect": 0.075,
|
||||
|
||||
"prob_cured_healing_infected": 0.035,
|
||||
"prob_cured_vaccinate_neutral": 0.035,
|
||||
|
||||
"prob_vaccinated_healing_infected": 0.035,
|
||||
"prob_vaccinated_vaccinate_neutral": 0.035,
|
||||
"prob_generate_anti_rumor": 0.035
|
||||
}
|
||||
|
||||
In this file you will define the different models you are going to simulate. You can simulate as many models
|
||||
as you want. Each model will be simulated separately.
|
||||
|
||||
After setting up the models, you have to initialize the parameters of each one. You will find the parameters needed
|
||||
in the documentation of each model.
|
||||
|
||||
Parameter validation will fail if a required parameter without a default has not been provided.
|
||||
|
||||
Running the Simulation
|
||||
======================
|
||||
|
||||
After setting all the configuration, you will be able to run the simulation. All you need to do is execute:
|
||||
|
||||
.. code:: bash
|
||||
|
||||
python3 soil.py
|
||||
|
||||
The simulation will return a dynamic graph .gexf file which could be visualized with
|
||||
`Gephi <https://gephi.org/users/download/>`__.
|
||||
|
||||
It will also return one .png picture for each model simulated.
|
||||
@ -0,0 +1,24 @@
|
||||
---
|
||||
name: simple
|
||||
dir_path: "/tmp/"
|
||||
num_trials: 3
|
||||
max_time: 100
|
||||
interval: 1
|
||||
network_params:
|
||||
generator: complete_graph
|
||||
n: 10
|
||||
network_agents:
|
||||
- agent_type: CounterModel
|
||||
weight: 1
|
||||
state:
|
||||
id: 0
|
||||
- agent_type: AggregatedCounter
|
||||
weight: 0.2
|
||||
environment_agents: []
|
||||
environment_params:
|
||||
am_i_complete: true
|
||||
default_state:
|
||||
incidents: 0
|
||||
states:
|
||||
- name: 'The first node'
|
||||
- name: 'The second node'
|
||||
@ -0,0 +1,17 @@
|
||||
default_state: {}
|
||||
environment_agents: []
|
||||
environment_params: {prob_neighbor_spread: 0.0, prob_tv_spread: 0.01}
|
||||
interval: 1
|
||||
max_time: 20
|
||||
name: Sim_prob_0
|
||||
network_agents:
|
||||
- agent_type: NewsSpread
|
||||
state: {has_tv: false}
|
||||
weight: 1
|
||||
- agent_type: NewsSpread
|
||||
state: {has_tv: true}
|
||||
weight: 2
|
||||
network_params: {generator: erdos_renyi_graph, n: 500, p: 0.1}
|
||||
num_trials: 1
|
||||
states:
|
||||
- {has_tv: true}
|
||||
@ -0,0 +1,20 @@
|
||||
import soil
|
||||
import random
|
||||
|
||||
class NewsSpread(soil.agents.FSM):
|
||||
@soil.agents.default_state
|
||||
@soil.agents.state
|
||||
def neutral(self):
|
||||
r = random.random()
|
||||
if self['has_tv'] and r < self.env['prob_tv_spread']:
|
||||
return self.infected
|
||||
return
|
||||
|
||||
@soil.agents.state
|
||||
def infected(self):
|
||||
prob_infect = self.env['prob_neighbor_spread']
|
||||
for neighbor in self.get_neighboring_agents(state_id=self.neutral.id):
|
||||
r = random.random()
|
||||
if r < prob_infect:
|
||||
neighbor.state['id'] = self.infected.id
|
||||
return
|
||||
@ -0,0 +1,2 @@
|
||||
balkian Torvalds {}
|
||||
anonymous Torvalds {}
|
||||
@ -0,0 +1,14 @@
|
||||
---
|
||||
name: torvalds_example
|
||||
max_time: 1
|
||||
interval: 2
|
||||
agent_type: CounterModel
|
||||
default_state:
|
||||
skill_level: 'beginner'
|
||||
network_params:
|
||||
path: 'torvalds.edgelist'
|
||||
states:
|
||||
Torvalds:
|
||||
skill_level: 'God'
|
||||
balkian:
|
||||
skill_level: 'developer'
|
||||
@ -1,38 +0,0 @@
|
||||
import settings
|
||||
from nxsim import BaseNetworkAgent
|
||||
from .. import networkStatus
|
||||
|
||||
|
||||
class BaseBehaviour(BaseNetworkAgent):
|
||||
|
||||
def __init__(self, environment=None, agent_id=0, state=()):
|
||||
super().__init__(environment=environment, agent_id=agent_id, state=state)
|
||||
self._attrs = {}
|
||||
|
||||
@property
|
||||
def attrs(self):
|
||||
now = self.env.now
|
||||
if now not in self._attrs:
|
||||
self._attrs[now] = {}
|
||||
return self._attrs[now]
|
||||
|
||||
@attrs.setter
|
||||
def attrs(self, value):
|
||||
self._attrs[self.env.now] = value
|
||||
|
||||
def run(self):
|
||||
while True:
|
||||
self.step(self.env.now)
|
||||
yield self.env.timeout(settings.network_params["timeout"])
|
||||
|
||||
def step(self, now):
|
||||
networkStatus['agent_%s'% self.id] = self.to_json()
|
||||
|
||||
def to_json(self):
|
||||
final = {}
|
||||
for stamp, attrs in self._attrs.items():
|
||||
for a in attrs:
|
||||
if a not in final:
|
||||
final[a] = {}
|
||||
final[a][stamp] = attrs[a]
|
||||
return final
|
||||
@ -1 +0,0 @@
|
||||
from .BaseBehaviour import BaseBehaviour
|
||||
@ -1,46 +0,0 @@
|
||||
import random
|
||||
from ..BaseBehaviour import *
|
||||
from .. import sentimentCorrelationNodeArray
|
||||
|
||||
|
||||
class BassModel(BaseBehaviour):
|
||||
"""
|
||||
Settings:
|
||||
innovation_prob
|
||||
|
||||
imitation_prob
|
||||
"""
|
||||
|
||||
def __init__(self, environment=None, agent_id=0, state=()):
|
||||
super().__init__(environment=environment, agent_id=agent_id, state=state)
|
||||
self.innovation_prob = environment.environment_params['innovation_prob']
|
||||
self.imitation_prob = environment.environment_params['imitation_prob']
|
||||
sentimentCorrelationNodeArray[self.id][self.env.now] = 0
|
||||
|
||||
def step(self, now):
|
||||
self.behaviour()
|
||||
super().step(now)
|
||||
|
||||
def behaviour(self):
|
||||
# Outside effects
|
||||
if random.random() < self.innovation_prob:
|
||||
if self.state['id'] == 0:
|
||||
self.state['id'] = 1
|
||||
sentimentCorrelationNodeArray[self.id][self.env.now] = 1
|
||||
else:
|
||||
pass
|
||||
|
||||
self.attrs['status'] = self.state['id']
|
||||
return
|
||||
|
||||
# Imitation effects
|
||||
if self.state['id'] == 0:
|
||||
aware_neighbors = self.get_neighboring_agents(state_id=1)
|
||||
num_neighbors_aware = len(aware_neighbors)
|
||||
if random.random() < (self.imitation_prob*num_neighbors_aware):
|
||||
self.state['id'] = 1
|
||||
sentimentCorrelationNodeArray[self.id][self.env.now] = 1
|
||||
|
||||
else:
|
||||
pass
|
||||
self.attrs['status'] = self.state['id']
|
||||
@ -1 +0,0 @@
|
||||
from .BassModel import BassModel
|
||||
@ -1 +0,0 @@
|
||||
from .BigMarketModel import BigMarketModel
|
||||
@ -1 +0,0 @@
|
||||
from .IndependentCascadeModel import IndependentCascadeModel
|
||||
@ -1,112 +0,0 @@
|
||||
import settings
|
||||
import random
|
||||
import numpy as np
|
||||
from ..BaseBehaviour import *
|
||||
from .. import init_states
|
||||
|
||||
|
||||
class SpreadModelM2(BaseBehaviour):
|
||||
"""
|
||||
Settings:
|
||||
prob_neutral_making_denier
|
||||
|
||||
prob_infect
|
||||
|
||||
prob_cured_healing_infected
|
||||
|
||||
prob_cured_vaccinate_neutral
|
||||
|
||||
prob_vaccinated_healing_infected
|
||||
|
||||
prob_vaccinated_vaccinate_neutral
|
||||
|
||||
prob_generate_anti_rumor
|
||||
"""
|
||||
|
||||
init_states[random.randint(0, settings.network_params["number_of_nodes"])] = {'id': 1}
|
||||
init_states[random.randint(0, settings.network_params["number_of_nodes"])] = {'id': 1}
|
||||
|
||||
def __init__(self, environment=None, agent_id=0, state=()):
|
||||
super().__init__(environment=environment, agent_id=agent_id, state=state)
|
||||
|
||||
self.prob_neutral_making_denier = np.random.normal(environment.environment_params['prob_neutral_making_denier'],
|
||||
environment.environment_params['standard_variance'])
|
||||
|
||||
self.prob_infect = np.random.normal(environment.environment_params['prob_infect'],
|
||||
environment.environment_params['standard_variance'])
|
||||
|
||||
self.prob_cured_healing_infected = np.random.normal(environment.environment_params['prob_cured_healing_infected'],
|
||||
environment.environment_params['standard_variance'])
|
||||
self.prob_cured_vaccinate_neutral = np.random.normal(environment.environment_params['prob_cured_vaccinate_neutral'],
|
||||
environment.environment_params['standard_variance'])
|
||||
|
||||
self.prob_vaccinated_healing_infected = np.random.normal(environment.environment_params['prob_vaccinated_healing_infected'],
|
||||
environment.environment_params['standard_variance'])
|
||||
self.prob_vaccinated_vaccinate_neutral = np.random.normal(environment.environment_params['prob_vaccinated_vaccinate_neutral'],
|
||||
environment.environment_params['standard_variance'])
|
||||
self.prob_generate_anti_rumor = np.random.normal(environment.environment_params['prob_generate_anti_rumor'],
|
||||
environment.environment_params['standard_variance'])
|
||||
|
||||
def step(self, now):
|
||||
|
||||
if self.state['id'] == 0: # Neutral
|
||||
self.neutral_behaviour()
|
||||
elif self.state['id'] == 1: # Infected
|
||||
self.infected_behaviour()
|
||||
elif self.state['id'] == 2: # Cured
|
||||
self.cured_behaviour()
|
||||
elif self.state['id'] == 3: # Vaccinated
|
||||
self.vaccinated_behaviour()
|
||||
|
||||
self.attrs['status'] = self.state['id']
|
||||
super().step(now)
|
||||
|
||||
def neutral_behaviour(self):
|
||||
|
||||
# Infected
|
||||
infected_neighbors = self.get_neighboring_agents(state_id=1)
|
||||
if len(infected_neighbors) > 0:
|
||||
if random.random() < self.prob_neutral_making_denier:
|
||||
self.state['id'] = 3 # Vaccinated making denier
|
||||
|
||||
def infected_behaviour(self):
|
||||
|
||||
# Neutral
|
||||
neutral_neighbors = self.get_neighboring_agents(state_id=0)
|
||||
for neighbor in neutral_neighbors:
|
||||
if random.random() < self.prob_infect:
|
||||
neighbor.state['id'] = 1 # Infected
|
||||
|
||||
def cured_behaviour(self):
|
||||
|
||||
# Vaccinate
|
||||
neutral_neighbors = self.get_neighboring_agents(state_id=0)
|
||||
for neighbor in neutral_neighbors:
|
||||
if random.random() < self.prob_cured_vaccinate_neutral:
|
||||
neighbor.state['id'] = 3 # Vaccinated
|
||||
|
||||
# Cure
|
||||
infected_neighbors = self.get_neighboring_agents(state_id=1)
|
||||
for neighbor in infected_neighbors:
|
||||
if random.random() < self.prob_cured_healing_infected:
|
||||
neighbor.state['id'] = 2 # Cured
|
||||
|
||||
def vaccinated_behaviour(self):
|
||||
|
||||
# Cure
|
||||
infected_neighbors = self.get_neighboring_agents(state_id=1)
|
||||
for neighbor in infected_neighbors:
|
||||
if random.random() < self.prob_cured_healing_infected:
|
||||
neighbor.state['id'] = 2 # Cured
|
||||
|
||||
# Vaccinate
|
||||
neutral_neighbors = self.get_neighboring_agents(state_id=0)
|
||||
for neighbor in neutral_neighbors:
|
||||
if random.random() < self.prob_cured_vaccinate_neutral:
|
||||
neighbor.state['id'] = 3 # Vaccinated
|
||||
|
||||
# Generate anti-rumor
|
||||
infected_neighbors_2 = self.get_neighboring_agents(state_id=1)
|
||||
for neighbor in infected_neighbors_2:
|
||||
if random.random() < self.prob_generate_anti_rumor:
|
||||
neighbor.state['id'] = 2 # Cured
|
||||
@ -1,2 +0,0 @@
|
||||
from .ControlModelM2 import ControlModelM2
|
||||
from .SpreadModelM2 import SpreadModelM2
|
||||
@ -1 +0,0 @@
|
||||
from .SISaModel import SISaModel
|
||||
@ -1 +0,0 @@
|
||||
from .SentimentCorrelationModel import SentimentCorrelationModel
|
||||
@ -1,8 +0,0 @@
|
||||
from .models import *
|
||||
from .BaseBehaviour import *
|
||||
from .BassModel import *
|
||||
from .BigMarketModel import *
|
||||
from .IndependentCascadeModel import *
|
||||
from .ModelM2 import *
|
||||
from .SentimentCorrelationModel import *
|
||||
from .SISaModel import *
|
||||
@ -1,10 +0,0 @@
|
||||
import settings
|
||||
|
||||
networkStatus = {} # Dict that will contain the status of every agent in the network
|
||||
|
||||
sentimentCorrelationNodeArray = []
|
||||
for x in range(0, settings.network_params["number_of_nodes"]):
|
||||
sentimentCorrelationNodeArray.append({'id': x})
|
||||
# Initialize agent states. Let's assume everyone is normal.
|
||||
init_states = [{'id': 0, } for _ in range(settings.network_params["number_of_nodes"])]
|
||||
# add keys as as necessary, but "id" must always refer to that state category
|
||||
File diff suppressed because one or more lines are too long
@ -1,62 +0,0 @@
|
||||
[
|
||||
{
|
||||
"network_type": 1,
|
||||
"number_of_nodes": 1000,
|
||||
"max_time": 50,
|
||||
"num_trials": 1,
|
||||
"timeout": 2
|
||||
},
|
||||
|
||||
{
|
||||
"agent": ["SISaModel","ControlModelM2"],
|
||||
|
||||
|
||||
"bite_prob": 0.01,
|
||||
"heal_prob": 0.01,
|
||||
|
||||
"innovation_prob": 0.001,
|
||||
"imitation_prob": 0.005,
|
||||
|
||||
"outside_effects_prob": 0.2,
|
||||
"anger_prob": 0.06,
|
||||
"joy_prob": 0.05,
|
||||
"sadness_prob": 0.02,
|
||||
"disgust_prob": 0.02,
|
||||
|
||||
"enterprises": ["BBVA", "Santander", "Bankia"],
|
||||
|
||||
"tweet_probability_users": 0.44,
|
||||
"tweet_relevant_probability": 0.25,
|
||||
"tweet_probability_about": [0.15, 0.15, 0.15],
|
||||
"sentiment_about": [0, 0, 0],
|
||||
|
||||
"tweet_probability_enterprises": [0.3, 0.3, 0.3],
|
||||
|
||||
"neutral_discontent_spon_prob": 0.04,
|
||||
"neutral_discontent_infected_prob": 0.04,
|
||||
"neutral_content_spon_prob": 0.18,
|
||||
"neutral_content_infected_prob": 0.02,
|
||||
|
||||
"discontent_neutral": 0.13,
|
||||
"discontent_content": 0.07,
|
||||
"variance_d_c": 0.02,
|
||||
|
||||
"content_discontent": 0.009,
|
||||
"variance_c_d": 0.003,
|
||||
"content_neutral": 0.088,
|
||||
|
||||
"standard_variance": 0.055,
|
||||
|
||||
|
||||
"prob_neutral_making_denier": 0.035,
|
||||
|
||||
"prob_infect": 0.075,
|
||||
|
||||
"prob_cured_healing_infected": 0.035,
|
||||
"prob_cured_vaccinate_neutral": 0.035,
|
||||
|
||||
"prob_vaccinated_healing_infected": 0.035,
|
||||
"prob_vaccinated_vaccinate_neutral": 0.035,
|
||||
"prob_generate_anti_rumor": 0.035
|
||||
}
|
||||
]
|
||||
@ -1,67 +0,0 @@
|
||||
# General configuration
|
||||
import json
|
||||
|
||||
with open('settings.json', 'r') as f:
|
||||
settings = json.load(f)
|
||||
|
||||
network_params = settings[0]
|
||||
environment_params = settings[1]
|
||||
|
||||
|
||||
'''
|
||||
environment_params = {
|
||||
# Zombie model
|
||||
'bite_prob': 0.01, # 0-1
|
||||
'heal_prob': 0.01, # 0-1
|
||||
|
||||
# Bass model
|
||||
'innovation_prob': 0.001,
|
||||
'imitation_prob': 0.005,
|
||||
|
||||
# Sentiment Correlation model
|
||||
'outside_effects_prob': 0.2,
|
||||
'anger_prob': 0.06,
|
||||
'joy_prob': 0.05,
|
||||
'sadness_prob': 0.02,
|
||||
'disgust_prob': 0.02,
|
||||
|
||||
# Big Market model
|
||||
## Names
|
||||
'enterprises': ["BBVA", "Santander", "Bankia"],
|
||||
## Users
|
||||
'tweet_probability_users': 0.44,
|
||||
'tweet_relevant_probability': 0.25,
|
||||
'tweet_probability_about': [0.15, 0.15, 0.15],
|
||||
'sentiment_about': [0, 0, 0], # Default values
|
||||
## Enterprises
|
||||
'tweet_probability_enterprises': [0.3, 0.3, 0.3],
|
||||
|
||||
# SISa
|
||||
'neutral_discontent_spon_prob': 0.04,
|
||||
'neutral_discontent_infected_prob': 0.04,
|
||||
'neutral_content_spon_prob': 0.18,
|
||||
'neutral_content_infected_prob': 0.02,
|
||||
|
||||
'discontent_neutral': 0.13,
|
||||
'discontent_content': 0.07,
|
||||
'variance_d_c': 0.02,
|
||||
|
||||
'content_discontent': 0.009,
|
||||
'variance_c_d': 0.003,
|
||||
'content_neutral': 0.088,
|
||||
|
||||
'standard_variance': 0.055,
|
||||
|
||||
# Spread Model M2 and Control Model M2
|
||||
'prob_neutral_making_denier': 0.035,
|
||||
|
||||
'prob_infect': 0.075,
|
||||
|
||||
'prob_cured_healing_infected': 0.035,
|
||||
'prob_cured_vaccinate_neutral': 0.035,
|
||||
|
||||
'prob_vaccinated_healing_infected': 0.035,
|
||||
'prob_vaccinated_vaccinate_neutral': 0.035,
|
||||
'prob_generate_anti_rumor': 0.035
|
||||
}
|
||||
'''
|
||||
@ -0,0 +1,39 @@
|
||||
import pip
|
||||
from setuptools import setup
|
||||
# parse_requirements() returns generator of pip.req.InstallRequirement objects
|
||||
from pip.req import parse_requirements
|
||||
from soil import __version__
|
||||
|
||||
try:
|
||||
install_reqs = parse_requirements(
|
||||
"requirements.txt", session=pip.download.PipSession())
|
||||
test_reqs = parse_requirements(
|
||||
"test-requirements.txt", session=pip.download.PipSession())
|
||||
except AttributeError:
|
||||
install_reqs = parse_requirements("requirements.txt")
|
||||
test_reqs = parse_requirements("test-requirements.txt")
|
||||
|
||||
install_reqs = [str(ir.req) for ir in install_reqs]
|
||||
test_reqs = [str(ir.req) for ir in test_reqs]
|
||||
|
||||
|
||||
setup(
|
||||
name='soil',
|
||||
packages=['soil'], # this must be the same as the name above
|
||||
version=__version__,
|
||||
description=('An Agent-Based Social Simulator for Social Networks'),
|
||||
author='J. Fernando Sanchez',
|
||||
author_email='jf.sanchez@upm.es',
|
||||
url='https://github.com/gsi-upm/soil', # use the URL to the github repo
|
||||
download_url='https://github.com/gsi-upm/soil/archive/{}.tar.gz'.format(
|
||||
__version__),
|
||||
keywords=['agent', 'social', 'simulator'],
|
||||
classifiers=[],
|
||||
install_requires=install_reqs,
|
||||
tests_require=test_reqs,
|
||||
setup_requires=['pytest-runner', ],
|
||||
include_package_data=True,
|
||||
entry_points={
|
||||
'console_scripts':
|
||||
['soil = soil.__init__:main']
|
||||
})
|
||||
Binary file not shown.
@ -0,0 +1,63 @@
|
||||
---
|
||||
name: ControlModelM2_sim
|
||||
max_time: 50
|
||||
num_trials: 1
|
||||
timeout: 2
|
||||
network_params:
|
||||
generator: barabasi_albert_graph
|
||||
n: 100
|
||||
m: 2
|
||||
agent_distribution:
|
||||
- agent_type: ControlModelM2
|
||||
weight: 0.1
|
||||
state:
|
||||
id: 1
|
||||
- agent_type: ControlModelM2
|
||||
weight: 0.9
|
||||
state:
|
||||
id: 0
|
||||
environment_params:
|
||||
prob_neutral_making_denier: 0.035
|
||||
prob_infect: 0.075
|
||||
prob_cured_healing_infected: 0.035
|
||||
prob_cured_vaccinate_neutral: 0.035
|
||||
prob_vaccinated_healing_infected: 0.035
|
||||
prob_vaccinated_vaccinate_neutral: 0.035
|
||||
prob_generate_anti_rumor: 0.035
|
||||
standard_variance: 0.055
|
||||
---
|
||||
name: SISA_sm
|
||||
max_time: 50
|
||||
num_trials: 2
|
||||
timeout: 2
|
||||
network_params:
|
||||
generator: erdos_renyi_graph
|
||||
n: 10000
|
||||
p: 0.05
|
||||
#other_agents:
|
||||
# - agent_type: DrawingAgent
|
||||
agent_distribution:
|
||||
- agent_type: SISaModel
|
||||
weight: 1
|
||||
state:
|
||||
id: content
|
||||
- agent_type: SISaModel
|
||||
weight: 1
|
||||
state:
|
||||
id: neutral
|
||||
- agent_type: SISaModel
|
||||
weight: 1
|
||||
state:
|
||||
id: discontent
|
||||
environment_params:
|
||||
neutral_discontent_spon_prob: 0.04
|
||||
neutral_discontent_infected_prob: 0.04
|
||||
neutral_content_spon_prob: 0.18
|
||||
neutral_content_infected_prob: 0.02
|
||||
discontent_neutral: 0.13
|
||||
discontent_content: 0.07
|
||||
variance_d_c: 0.02
|
||||
content_discontent: 0.009
|
||||
variance_c_d: 0.003
|
||||
content_neutral: 0.088
|
||||
standard_variance: 0.055
|
||||
@ -1,144 +0,0 @@
|
||||
from models import *
|
||||
from nxsim import NetworkSimulation
|
||||
# import numpy
|
||||
from matplotlib import pyplot as plt
|
||||
import networkx as nx
|
||||
import settings
|
||||
import models
|
||||
import math
|
||||
import json
|
||||
|
||||
|
||||
#################
|
||||
# Visualization #
|
||||
#################
|
||||
|
||||
def visualization(graph_name):
|
||||
|
||||
for x in range(0, settings.network_params["number_of_nodes"]):
|
||||
attributes = {}
|
||||
spells = []
|
||||
for attribute in models.networkStatus["agent_%s" % x]:
|
||||
if attribute == 'visible':
|
||||
lastvisible = False
|
||||
laststep = 0
|
||||
for t_step in models.networkStatus["agent_%s" % x][attribute]:
|
||||
nowvisible = models.networkStatus["agent_%s" % x][attribute][t_step]
|
||||
if nowvisible and not lastvisible:
|
||||
laststep = t_step
|
||||
if not nowvisible and lastvisible:
|
||||
spells.append((laststep, t_step))
|
||||
|
||||
lastvisible = nowvisible
|
||||
if lastvisible:
|
||||
spells.append((laststep, None))
|
||||
else:
|
||||
emotionStatusAux = []
|
||||
for t_step in models.networkStatus["agent_%s" % x][attribute]:
|
||||
prec = 2
|
||||
output = math.floor(models.networkStatus["agent_%s" % x][attribute][t_step] * (10 ** prec)) / (10 ** prec) # 2 decimals
|
||||
emotionStatusAux.append((output, t_step, t_step + settings.network_params["timeout"]))
|
||||
attributes[attribute] = emotionStatusAux
|
||||
if spells:
|
||||
G.add_node(x, attributes, spells=spells)
|
||||
else:
|
||||
G.add_node(x, attributes)
|
||||
|
||||
print("Done!")
|
||||
|
||||
with open('data.txt', 'w') as outfile:
|
||||
json.dump(models.networkStatus, outfile, sort_keys=True, indent=4, separators=(',', ': '))
|
||||
|
||||
nx.write_gexf(G, graph_name+".gexf", version="1.2draft")
|
||||
|
||||
|
||||
###########
|
||||
# Results #
|
||||
###########
|
||||
|
||||
def results(model_name):
|
||||
x_values = []
|
||||
infected_values = []
|
||||
neutral_values = []
|
||||
cured_values = []
|
||||
vaccinated_values = []
|
||||
|
||||
attribute_plot = 'status'
|
||||
for time in range(0, settings.network_params["max_time"]):
|
||||
value_infectados = 0
|
||||
value_neutral = 0
|
||||
value_cured = 0
|
||||
value_vaccinated = 0
|
||||
real_time = time * settings.network_params["timeout"]
|
||||
activity = False
|
||||
for x in range(0, settings.network_params["number_of_nodes"]):
|
||||
if attribute_plot in models.networkStatus["agent_%s" % x]:
|
||||
if real_time in models.networkStatus["agent_%s" % x][attribute_plot]:
|
||||
if models.networkStatus["agent_%s" % x][attribute_plot][real_time] == 1: ## Infected
|
||||
value_infectados += 1
|
||||
activity = True
|
||||
if models.networkStatus["agent_%s" % x][attribute_plot][real_time] == 0: ## Neutral
|
||||
value_neutral += 1
|
||||
activity = True
|
||||
if models.networkStatus["agent_%s" % x][attribute_plot][real_time] == 2: ## Cured
|
||||
value_cured += 1
|
||||
activity = True
|
||||
if models.networkStatus["agent_%s" % x][attribute_plot][real_time] == 3: ## Vaccinated
|
||||
value_vaccinated += 1
|
||||
activity = True
|
||||
|
||||
if activity:
|
||||
x_values.append(real_time)
|
||||
infected_values.append(value_infectados)
|
||||
neutral_values.append(value_neutral)
|
||||
cured_values.append(value_cured)
|
||||
vaccinated_values.append(value_vaccinated)
|
||||
activity = False
|
||||
|
||||
fig1 = plt.figure()
|
||||
ax1 = fig1.add_subplot(111)
|
||||
|
||||
infected_line = ax1.plot(x_values, infected_values, label='Infected')
|
||||
neutral_line = ax1.plot(x_values, neutral_values, label='Neutral')
|
||||
cured_line = ax1.plot(x_values, cured_values, label='Cured')
|
||||
vaccinated_line = ax1.plot(x_values, vaccinated_values, label='Vaccinated')
|
||||
ax1.legend()
|
||||
fig1.savefig(model_name + '.png')
|
||||
# plt.show()
|
||||
|
||||
|
||||
####################
|
||||
# Network creation #
|
||||
####################
|
||||
|
||||
if settings.network_params["network_type"] == 0:
|
||||
G = nx.complete_graph(settings.network_params["number_of_nodes"])
|
||||
if settings.network_params["network_type"] == 1:
|
||||
G = nx.barabasi_albert_graph(settings.network_params["number_of_nodes"], 10)
|
||||
if settings.network_params["network_type"] == 2:
|
||||
G = nx.margulis_gabber_galil_graph(settings.network_params["number_of_nodes"], None)
|
||||
# More types of networks can be added here
|
||||
|
||||
##############
|
||||
# Simulation #
|
||||
##############
|
||||
|
||||
agents = settings.environment_params['agent']
|
||||
|
||||
print("Using Agent(s): {agents}".format(agents=agents))
|
||||
|
||||
if len(agents) > 1:
|
||||
for agent in agents:
|
||||
sim = NetworkSimulation(topology=G, states=init_states, agent_type=locals()[agent], max_time=settings.network_params["max_time"],
|
||||
num_trials=settings.network_params["num_trials"], logging_interval=1.0, **settings.environment_params)
|
||||
sim.run_simulation()
|
||||
print(str(agent))
|
||||
results(str(agent))
|
||||
visualization(str(agent))
|
||||
else:
|
||||
agent = agents[0]
|
||||
sim = NetworkSimulation(topology=G, states=init_states, agent_type=locals()[agent], max_time=settings.network_params["max_time"],
|
||||
num_trials=settings.network_params["num_trials"], logging_interval=1.0, **settings.environment_params)
|
||||
sim.run_simulation()
|
||||
results(str(agent))
|
||||
visualization(str(agent))
|
||||
@ -1,394 +0,0 @@
|
||||
from nxsim import NetworkSimulation
|
||||
from nxsim import BaseNetworkAgent
|
||||
from nxsim import BaseLoggingAgent
|
||||
from random import randint
|
||||
from matplotlib import pyplot as plt
|
||||
import random
|
||||
import numpy as np
|
||||
import networkx as nx
|
||||
import settings
|
||||
|
||||
|
||||
settings.init()
|
||||
|
||||
if settings.network_type == 0:
|
||||
G = nx.complete_graph(settings.number_of_nodes)
|
||||
if settings.network_type == 1:
|
||||
G = nx.barabasi_albert_graph(settings.number_of_nodes,3)
|
||||
if settings.network_type == 2:
|
||||
G = nx.margulis_gabber_galil_graph(settings.number_of_nodes, None)
|
||||
|
||||
|
||||
myList=[]
|
||||
networkStatus=[]
|
||||
for x in range(0, settings.number_of_nodes):
|
||||
networkStatus.append({'id':x})
|
||||
|
||||
|
||||
|
||||
# # Just like subclassing a process in SimPy
|
||||
# class MyAgent(BaseNetworkAgent):
|
||||
# def __init__(self, environment=None, agent_id=0, state=()): # Make sure to have these three keyword arguments
|
||||
# super().__init__(environment=environment, agent_id=agent_id, state=state)
|
||||
# # Add your own attributes here
|
||||
|
||||
# def run(self):
|
||||
# # Add your behaviors here
|
||||
|
||||
|
||||
|
||||
|
||||
class SentimentCorrelationModel(BaseNetworkAgent):
|
||||
def __init__(self, environment=None, agent_id=0, state=()):
|
||||
super().__init__(environment=environment, agent_id=agent_id, state=state)
|
||||
self.outside_effects_prob = settings.outside_effects_prob
|
||||
self.anger_prob = settings.anger_prob
|
||||
self.joy_prob = settings.joy_prob
|
||||
self.sadness_prob = settings.sadness_prob
|
||||
self.disgust_prob = settings.disgust_prob
|
||||
self.time_awareness=[]
|
||||
for i in range(4):
|
||||
self.time_awareness.append(0) #0-> Anger, 1-> joy, 2->sadness, 3 -> disgust
|
||||
networkStatus[self.id][self.env.now]=0
|
||||
|
||||
|
||||
def run(self):
|
||||
while True:
|
||||
if self.env.now > 10:
|
||||
G.add_node(205)
|
||||
G.add_edge(205,0)
|
||||
angry_neighbors_1_time_step=[]
|
||||
joyful_neighbors_1_time_step=[]
|
||||
sad_neighbors_1_time_step=[]
|
||||
disgusted_neighbors_1_time_step=[]
|
||||
|
||||
|
||||
angry_neighbors = self.get_neighboring_agents(state_id=1)
|
||||
for x in angry_neighbors:
|
||||
if x.time_awareness[0] > (self.env.now-500):
|
||||
angry_neighbors_1_time_step.append(x)
|
||||
num_neighbors_angry = len(angry_neighbors_1_time_step)
|
||||
|
||||
|
||||
joyful_neighbors = self.get_neighboring_agents(state_id=2)
|
||||
for x in joyful_neighbors:
|
||||
if x.time_awareness[1] > (self.env.now-500):
|
||||
joyful_neighbors_1_time_step.append(x)
|
||||
num_neighbors_joyful = len(joyful_neighbors_1_time_step)
|
||||
|
||||
|
||||
sad_neighbors = self.get_neighboring_agents(state_id=3)
|
||||
for x in sad_neighbors:
|
||||
if x.time_awareness[2] > (self.env.now-500):
|
||||
sad_neighbors_1_time_step.append(x)
|
||||
num_neighbors_sad = len(sad_neighbors_1_time_step)
|
||||
|
||||
|
||||
disgusted_neighbors = self.get_neighboring_agents(state_id=4)
|
||||
for x in disgusted_neighbors:
|
||||
if x.time_awareness[3] > (self.env.now-500):
|
||||
disgusted_neighbors_1_time_step.append(x)
|
||||
num_neighbors_disgusted = len(disgusted_neighbors_1_time_step)
|
||||
|
||||
# #Outside effects. Asignamos un estado aleatorio
|
||||
# if random.random() < settings.outside_effects_prob:
|
||||
# if self.state['id'] == 0:
|
||||
# self.state['id'] = random.randint(1,4)
|
||||
# myList.append(self.id)
|
||||
# networkStatus[self.id][self.env.now]=self.state['id'] #Almaceno cuando se ha infectado para la red dinamica
|
||||
# self.time_awareness = self.env.now #Para saber cuando se han contagiado
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
# else:
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
|
||||
|
||||
# #Imitation effects-Joy
|
||||
|
||||
# if random.random() < (settings.joy_prob*(num_neighbors_joyful)/10):
|
||||
# myList.append(self.id)
|
||||
# self.state['id'] = 2
|
||||
# networkStatus[self.id][self.env.now]=2
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
|
||||
|
||||
# #Imitation effects-Sadness
|
||||
|
||||
# if random.random() < (settings.sadness_prob*(num_neighbors_sad)/10):
|
||||
# myList.append(self.id)
|
||||
# self.state['id'] = 3
|
||||
# networkStatus[self.id][self.env.now]=3
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
|
||||
|
||||
# #Imitation effects-Disgust
|
||||
|
||||
# if random.random() < (settings.disgust_prob*(num_neighbors_disgusted)/10):
|
||||
# myList.append(self.id)
|
||||
# self.state['id'] = 4
|
||||
# networkStatus[self.id][self.env.now]=4
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
|
||||
# #Imitation effects-Anger
|
||||
|
||||
# if random.random() < (settings.anger_prob*(num_neighbors_angry)/10):
|
||||
# myList.append(self.id)
|
||||
# self.state['id'] = 1
|
||||
# networkStatus[self.id][self.env.now]=1
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
|
||||
###########################################
|
||||
|
||||
|
||||
anger_prob= settings.anger_prob+(len(angry_neighbors_1_time_step)*settings.anger_prob)
|
||||
print("anger_prob " + str(anger_prob))
|
||||
joy_prob= settings.joy_prob+(len(joyful_neighbors_1_time_step)*settings.joy_prob)
|
||||
print("joy_prob " + str(joy_prob))
|
||||
sadness_prob = settings.sadness_prob+(len(sad_neighbors_1_time_step)*settings.sadness_prob)
|
||||
print("sadness_prob "+ str(sadness_prob))
|
||||
disgust_prob = settings.disgust_prob+(len(disgusted_neighbors_1_time_step)*settings.disgust_prob)
|
||||
print("disgust_prob " + str(disgust_prob))
|
||||
outside_effects_prob= settings.outside_effects_prob
|
||||
print("outside_effects_prob " + str(outside_effects_prob))
|
||||
|
||||
|
||||
num = random.random()
|
||||
|
||||
|
||||
if(num<outside_effects_prob):
|
||||
self.state['id'] = random.randint(1,4)
|
||||
myList.append(self.id)
|
||||
networkStatus[self.id][self.env.now]=self.state['id'] #Almaceno cuando se ha infectado para la red dinamica
|
||||
self.time_awareness[self.state['id']-1] = self.env.now
|
||||
yield self.env.timeout(settings.timeout)
|
||||
|
||||
|
||||
if(num<anger_prob):
|
||||
|
||||
myList.append(self.id)
|
||||
self.state['id'] = 1
|
||||
networkStatus[self.id][self.env.now]=1
|
||||
self.time_awareness[self.state['id']-1] = self.env.now
|
||||
elif (num<joy_prob+anger_prob and num>anger_prob):
|
||||
|
||||
myList.append(self.id)
|
||||
self.state['id'] = 2
|
||||
networkStatus[self.id][self.env.now]=2
|
||||
self.time_awareness[self.state['id']-1] = self.env.now
|
||||
elif (num<sadness_prob+anger_prob+joy_prob and num>joy_prob+anger_prob):
|
||||
|
||||
myList.append(self.id)
|
||||
self.state['id'] = 3
|
||||
networkStatus[self.id][self.env.now]=3
|
||||
self.time_awareness[self.state['id']-1] = self.env.now
|
||||
elif (num<disgust_prob+sadness_prob+anger_prob+joy_prob and num>sadness_prob+anger_prob+joy_prob):
|
||||
|
||||
myList.append(self.id)
|
||||
self.state['id'] = 4
|
||||
networkStatus[self.id][self.env.now]=4
|
||||
self.time_awareness[self.state['id']-1] = self.env.now
|
||||
|
||||
yield self.env.timeout(settings.timeout)
|
||||
|
||||
|
||||
# anger_propagation = settings.anger_prob*num_neighbors_angry/10
|
||||
# joy_propagation = anger_propagation + (settings.joy_prob*num_neighbors_joyful/10)
|
||||
# sadness_propagation = joy_propagation + (settings.sadness_prob*num_neighbors_sad/10)
|
||||
# disgust_propagation = sadness_propagation + (settings.disgust_prob*num_neighbors_disgusted/10)
|
||||
# outside_effects_propagation = disgust_propagation + settings.outside_effects_prob
|
||||
|
||||
# if (num<anger_propagation):
|
||||
# if(self.state['id'] !=0):
|
||||
# myList.append(self.id)
|
||||
# self.state['id'] = 1
|
||||
# networkStatus[self.id][self.env.now]=1
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
# if (num<joy_propagation):
|
||||
# if(self.state['id'] !=0):
|
||||
# myList.append(self.id)
|
||||
# self.state['id'] = 2
|
||||
# networkStatus[self.id][self.env.now]=2
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
# if(num<sadness_propagation):
|
||||
# if(self.state['id'] !=0):
|
||||
# myList.append(self.id)
|
||||
# self.state['id'] = 3
|
||||
# networkStatus[self.id][self.env.now]=3
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
# # if(num<disgust_propagation):
|
||||
# # if(self.state['id'] !=0):
|
||||
# # myList.append(self.id)
|
||||
# # self.state['id'] = 4
|
||||
# # networkStatus[self.id][self.env.now]=4
|
||||
# # yield self.env.timeout(settings.timeout)
|
||||
# if(num <outside_effects_propagation):
|
||||
# if self.state['id'] == 0:
|
||||
# self.state['id'] = random.randint(1,4)
|
||||
# myList.append(self.id)
|
||||
# networkStatus[self.id][self.env.now]=self.state['id'] #Almaceno cuando se ha infectado para la red dinamica
|
||||
# self.time_awareness = self.env.now #Para saber cuando se han contagiado
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
# else:
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
# else:
|
||||
# yield self.env.timeout(settings.timeout)
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
class BassModel(BaseNetworkAgent):
|
||||
def __init__(self, environment=None, agent_id=0, state=()):
|
||||
super().__init__(environment=environment, agent_id=agent_id, state=state)
|
||||
self.innovation_prob = settings.innovation_prob
|
||||
self.imitation_prob = settings.imitation_prob
|
||||
networkStatus[self.id][self.env.now]=0
|
||||
|
||||
def run(self):
|
||||
while True:
|
||||
|
||||
|
||||
#Outside effects
|
||||
if random.random() < settings.innovation_prob:
|
||||
if self.state['id'] == 0:
|
||||
self.state['id'] = 1
|
||||
myList.append(self.id)
|
||||
networkStatus[self.id][self.env.now]=1
|
||||
yield self.env.timeout(settings.timeout)
|
||||
else:
|
||||
yield self.env.timeout(settings.timeout)
|
||||
|
||||
#Imitation effects
|
||||
if self.state['id'] == 0:
|
||||
aware_neighbors = self.get_neighboring_agents(state_id=1)
|
||||
num_neighbors_aware = len(aware_neighbors)
|
||||
if random.random() < (settings.imitation_prob*num_neighbors_aware):
|
||||
myList.append(self.id)
|
||||
self.state['id'] = 1
|
||||
networkStatus[self.id][self.env.now]=1
|
||||
yield self.env.timeout(settings.timeout)
|
||||
else:
|
||||
yield self.env.timeout(settings.timeout)
|
||||
|
||||
class IndependentCascadeModel(BaseNetworkAgent):
|
||||
def __init__(self, environment=None, agent_id=0, state=()):
|
||||
super().__init__(environment=environment, agent_id=agent_id, state=state)
|
||||
self.innovation_prob = settings.innovation_prob
|
||||
self.imitation_prob = settings.imitation_prob
|
||||
self.time_awareness = 0
|
||||
networkStatus[self.id][self.env.now]=0
|
||||
|
||||
def run(self):
|
||||
while True:
|
||||
aware_neighbors_1_time_step=[]
|
||||
#Outside effects
|
||||
if random.random() < settings.innovation_prob:
|
||||
if self.state['id'] == 0:
|
||||
self.state['id'] = 1
|
||||
myList.append(self.id)
|
||||
networkStatus[self.id][self.env.now]=1
|
||||
self.time_awareness = self.env.now #Para saber cuando se han contagiado
|
||||
yield self.env.timeout(settings.timeout)
|
||||
else:
|
||||
yield self.env.timeout(settings.timeout)
|
||||
|
||||
#Imitation effects
|
||||
if self.state['id'] == 0:
|
||||
aware_neighbors = self.get_neighboring_agents(state_id=1)
|
||||
for x in aware_neighbors:
|
||||
if x.time_awareness == (self.env.now-1):
|
||||
aware_neighbors_1_time_step.append(x)
|
||||
num_neighbors_aware = len(aware_neighbors_1_time_step)
|
||||
if random.random() < (settings.imitation_prob*num_neighbors_aware):
|
||||
myList.append(self.id)
|
||||
self.state['id'] = 1
|
||||
networkStatus[self.id][self.env.now]=1
|
||||
yield self.env.timeout(settings.timeout)
|
||||
else:
|
||||
yield self.env.timeout(settings.timeout)
|
||||
|
||||
|
||||
class ZombieOutbreak(BaseNetworkAgent):
|
||||
def __init__(self, environment=None, agent_id=0, state=()):
|
||||
super().__init__(environment=environment, agent_id=agent_id, state=state)
|
||||
self.bite_prob = settings.bite_prob
|
||||
networkStatus[self.id][self.env.now]=0
|
||||
|
||||
|
||||
def run(self):
|
||||
while True:
|
||||
if random.random() < settings.heal_prob:
|
||||
if self.state['id'] == 1:
|
||||
self.zombify()
|
||||
yield self.env.timeout(settings.timeout)
|
||||
else:
|
||||
yield self.env.timeout(settings.timeout)
|
||||
else:
|
||||
if self.state['id'] == 1:
|
||||
print("Soy el zombie " + str(self.id) + " y me voy a curar porque el num aleatorio ha sido " + str(num))
|
||||
networkStatus[self.id][self.env.now]=0
|
||||
if self.id in myList:
|
||||
myList.remove(self.id)
|
||||
self.state['id'] = 0
|
||||
yield self.env.timeout(settings.timeout)
|
||||
else:
|
||||
yield self.env.timeout(settings.timeout)
|
||||
|
||||
|
||||
def zombify(self):
|
||||
normal_neighbors = self.get_neighboring_agents(state_id=0)
|
||||
for neighbor in normal_neighbors:
|
||||
if random.random() < self.bite_prob:
|
||||
print("Soy el zombie " + str(self.id) + " y voy a contagiar a " + str(neighbor.id))
|
||||
neighbor.state['id'] = 1 # zombie
|
||||
myList.append(neighbor.id)
|
||||
networkStatus[self.id][self.env.now]=1
|
||||
networkStatus[neighbor.id][self.env.now]=1
|
||||
print(self.env.now, "Soy el zombie: "+ str(self.id), "Mi vecino es: "+ str(neighbor.id), sep='\t')
|
||||
break
|
||||
|
||||
|
||||
# Initialize agent states. Let's assume everyone is normal.
|
||||
init_states = [{'id': 0, } for _ in range(settings.number_of_nodes)] # add keys as as necessary, but "id" must always refer to that state category
|
||||
|
||||
# Seed a zombie
|
||||
#init_states[5] = {'id': 1}
|
||||
#init_states[3] = {'id': 1}
|
||||
|
||||
sim = NetworkSimulation(topology=G, states=init_states, agent_type=SentimentCorrelationModel,
|
||||
max_time=settings.max_time, num_trials=settings.num_trials, logging_interval=1.0)
|
||||
|
||||
|
||||
sim.run_simulation()
|
||||
|
||||
myList = sorted(myList, key=int)
|
||||
#print("Los zombies son: " + str(myList))
|
||||
|
||||
trial = BaseLoggingAgent.open_trial_state_history(dir_path='sim_01', trial_id=0)
|
||||
zombie_census = [sum([1 for node_id, state in g.items() if state['id'] == 1]) for t,g in trial.items()]
|
||||
|
||||
#for x in range(len(myList)):
|
||||
# G.node[myList[x]]['viz'] = {'color': {'r': 255, 'g': 0, 'b': 0, 'a': 0}}
|
||||
|
||||
#G.node[1]['viz'] = {'color': {'r': 255, 'g': 0, 'b': 0, 'a': 0}}
|
||||
|
||||
#lista = nx.nodes(G)
|
||||
#print('Nodos: ' + str(lista))
|
||||
for x in range(0, settings.number_of_nodes):
|
||||
networkStatusAux=[]
|
||||
for tiempo in networkStatus[x]:
|
||||
if tiempo != 'id':
|
||||
networkStatusAux.append((networkStatus[x][tiempo],tiempo,None))
|
||||
G.add_node(x, zombie= networkStatusAux)
|
||||
#print(networkStatus)
|
||||
|
||||
|
||||
nx.write_gexf(G,"test.gexf", version="1.2draft")
|
||||
plt.plot(zombie_census)
|
||||
plt.draw() # pyplot draw()
|
||||
plt.savefig("zombie.png")
|
||||
#print(networkStatus)
|
||||
#nx.draw(G)
|
||||
#plt.show()
|
||||
#plt.savefig("path.png")
|
||||
@ -0,0 +1,42 @@
|
||||
import importlib
|
||||
import sys
|
||||
import os
|
||||
|
||||
__version__ = "0.9.2"
|
||||
|
||||
try:
|
||||
basestring
|
||||
except NameError:
|
||||
basestring = str
|
||||
|
||||
from . import agents
|
||||
from . import simulation
|
||||
from . import environment
|
||||
from . import utils
|
||||
from . import settings
|
||||
|
||||
|
||||
def main():
|
||||
import argparse
|
||||
from . import simulation
|
||||
|
||||
parser = argparse.ArgumentParser(description='Run a SOIL simulation')
|
||||
parser.add_argument('file', type=str,
|
||||
nargs="?",
|
||||
default='simulation.yml',
|
||||
help='python module containing the simulation configuration.')
|
||||
parser.add_argument('--module', '-m', type=str,
|
||||
help='file containing the code of any custom agents.')
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
if args.module:
|
||||
sys.path.append(os.getcwd())
|
||||
importlib.import_module(args.module)
|
||||
|
||||
print('Loading config file: {}'.format(args.file))
|
||||
simulation.run_from_config(args.file)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@ -0,0 +1,123 @@
|
||||
import nxsim
|
||||
from collections import OrderedDict
|
||||
from copy import deepcopy
|
||||
import json
|
||||
|
||||
from functools import wraps
|
||||
|
||||
|
||||
class BaseAgent(nxsim.BaseAgent):
|
||||
"""
|
||||
A special simpy BaseAgent that keeps track of its state history.
|
||||
"""
|
||||
|
||||
def __init__(self, *args, **kwargs):
|
||||
self._history = OrderedDict()
|
||||
self._neighbors = None
|
||||
super().__init__(*args, **kwargs)
|
||||
self._history[None] = deepcopy(self.state)
|
||||
|
||||
@property
|
||||
def now(self):
|
||||
try:
|
||||
return self.env.now
|
||||
except AttributeError:
|
||||
# No environment
|
||||
return None
|
||||
|
||||
def run(self):
|
||||
while True:
|
||||
res = self.step()
|
||||
self._history[self.env.now] = deepcopy(self.state)
|
||||
yield res or self.env.timeout(self.env.interval)
|
||||
|
||||
def step(self):
|
||||
pass
|
||||
|
||||
def to_json(self):
|
||||
return json.dumps(self._history)
|
||||
|
||||
class NetworkAgent(BaseAgent, nxsim.BaseNetworkAgent):
|
||||
|
||||
def count_agents(self, state_id=None, limit_neighbors=False):
|
||||
if limit_neighbors:
|
||||
agents = self.global_topology.neighbors(self.id)
|
||||
else:
|
||||
agents = self.global_topology.nodes()
|
||||
count = 0
|
||||
for agent in agents:
|
||||
if state_id and state_id != self.global_topology.node[agent]['agent'].state['id']:
|
||||
continue
|
||||
count += 1
|
||||
return count
|
||||
|
||||
def count_neighboring_agents(self, state_id=None):
|
||||
return self.count_agents(state_id, limit_neighbors=True)
|
||||
|
||||
|
||||
def state(func):
|
||||
|
||||
@wraps(func)
|
||||
def func_wrapper(self):
|
||||
when = None
|
||||
next_state = func(self)
|
||||
try:
|
||||
next_state, when = next_state
|
||||
except TypeError:
|
||||
pass
|
||||
if next_state:
|
||||
try:
|
||||
self.state['id'] = next_state.id
|
||||
except AttributeError:
|
||||
raise NotImplemented('State id %s is not valid.' % next_state)
|
||||
return when
|
||||
|
||||
func_wrapper.id = func.__name__
|
||||
func_wrapper.is_default = False
|
||||
return func_wrapper
|
||||
|
||||
|
||||
def default_state(func):
|
||||
func.is_default = True
|
||||
return func
|
||||
|
||||
|
||||
class MetaFSM(type):
|
||||
def __init__(cls, name, bases, nmspc):
|
||||
super(MetaFSM, cls).__init__(name, bases, nmspc)
|
||||
states = {}
|
||||
# Re-use states from inherited classes
|
||||
default_state = None
|
||||
for i in bases:
|
||||
if isinstance(i, MetaFSM):
|
||||
for state_id, state in i.states.items():
|
||||
if state.is_default:
|
||||
default_state = state
|
||||
states[state_id] = state
|
||||
|
||||
# Add new states
|
||||
for name, func in nmspc.items():
|
||||
if hasattr(func, 'id'):
|
||||
if func.is_default:
|
||||
default_state = func
|
||||
states[func.id] = func
|
||||
cls.default_state = default_state
|
||||
cls.states = states
|
||||
|
||||
|
||||
class FSM(BaseAgent, metaclass=MetaFSM):
|
||||
def __init__(self, *args, **kwargs):
|
||||
super(FSM, self).__init__(*args, **kwargs)
|
||||
if 'id' not in self.state:
|
||||
self.state['id'] = self.default_state.id
|
||||
|
||||
def step(self):
|
||||
if 'id' in self.state:
|
||||
next_state = self.state['id']
|
||||
elif self.default_state:
|
||||
next_state = self.default_state.id
|
||||
else:
|
||||
raise Exception('{} has no valid state id or default state'.format(self))
|
||||
if next_state not in self.states:
|
||||
raise Exception('{} is not a valid id for {}'.format(next_state, self))
|
||||
self.states[next_state](self)
|
||||
@ -0,0 +1,40 @@
|
||||
import random
|
||||
from . import NetworkAgent
|
||||
|
||||
|
||||
class BassModel(NetworkAgent):
|
||||
"""
|
||||
Settings:
|
||||
innovation_prob
|
||||
imitation_prob
|
||||
"""
|
||||
|
||||
def __init__(self, environment, agent_id, state):
|
||||
super().__init__(environment=environment, agent_id=agent_id, state=state)
|
||||
env_params = environment.environment_params
|
||||
self.state['sentimentCorrelation'] = 0
|
||||
|
||||
def step(self):
|
||||
self.behaviour()
|
||||
|
||||
def behaviour(self):
|
||||
# Outside effects
|
||||
if random.random() < self.state_params['innovation_prob']:
|
||||
if self.state['id'] == 0:
|
||||
self.state['id'] = 1
|
||||
self.state['sentimentCorrelation'] = 1
|
||||
else:
|
||||
pass
|
||||
|
||||
return
|
||||
|
||||
# Imitation effects
|
||||
if self.state['id'] == 0:
|
||||
aware_neighbors = self.get_neighboring_agents(state_id=1)
|
||||
num_neighbors_aware = len(aware_neighbors)
|
||||
if random.random() < (self.state_params['imitation_prob']*num_neighbors_aware):
|
||||
self.state['id'] = 1
|
||||
self.state['sentimentCorrelation'] = 1
|
||||
|
||||
else:
|
||||
pass
|
||||
@ -0,0 +1,31 @@
|
||||
from . import NetworkAgent
|
||||
|
||||
|
||||
class CounterModel(NetworkAgent):
|
||||
"""
|
||||
Dummy behaviour. It counts the number of nodes in the network and neighbors
|
||||
in each step and adds it to its state.
|
||||
"""
|
||||
|
||||
def step(self):
|
||||
# Outside effects
|
||||
total = len(self.get_all_agents())
|
||||
neighbors = len(self.get_neighboring_agents())
|
||||
self.state['times'] = self.state.get('times', 0) + 1
|
||||
self.state['neighbors'] = neighbors
|
||||
self.state['total'] = total
|
||||
|
||||
|
||||
class AggregatedCounter(NetworkAgent):
|
||||
"""
|
||||
Dummy behaviour. It counts the number of nodes in the network and neighbors
|
||||
in each step and adds it to its state.
|
||||
"""
|
||||
|
||||
def step(self):
|
||||
# Outside effects
|
||||
total = len(self.get_all_agents())
|
||||
neighbors = len(self.get_neighboring_agents())
|
||||
self.state['times'] = self.state.get('times', 0) + 1
|
||||
self.state['neighbors'] = self.state.get('neighbors', 0) + neighbors
|
||||
self.state['total'] = self.state.get('total', 0) + total
|
||||
@ -0,0 +1,18 @@
|
||||
from . import BaseAgent
|
||||
|
||||
import os.path
|
||||
import matplotlib
|
||||
import matplotlib.pyplot as plt
|
||||
import networkx as nx
|
||||
|
||||
|
||||
class DrawingAgent(BaseAgent):
|
||||
"""
|
||||
Agent that draws the state of the network.
|
||||
"""
|
||||
|
||||
def step(self):
|
||||
# Outside effects
|
||||
f = plt.figure()
|
||||
nx.draw(self.env.G, node_size=10, width=0.2, pos=nx.spring_layout(self.env.G, scale=100), ax=f.add_subplot(111))
|
||||
f.savefig(os.path.join(self.env.sim().dir_path, "graph-"+str(self.env.now)+".png"))
|
||||
@ -0,0 +1,166 @@
|
||||
# networkStatus = {} # Dict that will contain the status of every agent in the network
|
||||
# sentimentCorrelationNodeArray = []
|
||||
# for x in range(0, settings.network_params["number_of_nodes"]):
|
||||
# sentimentCorrelationNodeArray.append({'id': x})
|
||||
# Initialize agent states. Let's assume everyone is normal.
|
||||
|
||||
|
||||
import nxsim
|
||||
from collections import OrderedDict
|
||||
from copy import deepcopy
|
||||
import json
|
||||
|
||||
from functools import wraps
|
||||
|
||||
|
||||
agent_types = {}
|
||||
|
||||
|
||||
class MetaAgent(type):
|
||||
def __init__(cls, name, bases, nmspc):
|
||||
super(MetaAgent, cls).__init__(name, bases, nmspc)
|
||||
agent_types[name] = cls
|
||||
|
||||
|
||||
class BaseAgent(nxsim.BaseAgent, metaclass=MetaAgent):
|
||||
"""
|
||||
A special simpy BaseAgent that keeps track of its state history.
|
||||
"""
|
||||
|
||||
def __init__(self, *args, **kwargs):
|
||||
self._history = OrderedDict()
|
||||
self._neighbors = None
|
||||
super().__init__(*args, **kwargs)
|
||||
|
||||
def __getitem__(self, key):
|
||||
if isinstance(key, tuple):
|
||||
k, t_step = key
|
||||
if k is not None:
|
||||
if t_step is not None:
|
||||
return self._history[t_step][k]
|
||||
else:
|
||||
return {tt: tv.get(k, None) for tt, tv in self._history.items()}
|
||||
else:
|
||||
return self._history[t_step]
|
||||
return self.state[key]
|
||||
|
||||
def __setitem__(self, key, value):
|
||||
self.state[key] = value
|
||||
|
||||
def save_state(self):
|
||||
self._history[self.now] = deepcopy(self.state)
|
||||
|
||||
@property
|
||||
def now(self):
|
||||
try:
|
||||
return self.env.now
|
||||
except AttributeError:
|
||||
# No environment
|
||||
return None
|
||||
|
||||
def run(self):
|
||||
while True:
|
||||
res = self.step()
|
||||
yield res or self.env.timeout(self.env.interval)
|
||||
|
||||
def step(self):
|
||||
pass
|
||||
|
||||
def to_json(self):
|
||||
return json.dumps(self._history)
|
||||
|
||||
|
||||
class NetworkAgent(BaseAgent, nxsim.BaseNetworkAgent):
|
||||
|
||||
def count_agents(self, state_id=None, limit_neighbors=False):
|
||||
if limit_neighbors:
|
||||
agents = self.global_topology.neighbors(self.id)
|
||||
else:
|
||||
agents = self.global_topology.nodes()
|
||||
count = 0
|
||||
for agent in agents:
|
||||
if state_id and state_id != self.global_topology.node[agent]['agent'].state['id']:
|
||||
continue
|
||||
count += 1
|
||||
return count
|
||||
|
||||
def count_neighboring_agents(self, state_id=None):
|
||||
return self.count_agents(state_id, limit_neighbors=True)
|
||||
|
||||
|
||||
def state(func):
|
||||
|
||||
@wraps(func)
|
||||
def func_wrapper(self):
|
||||
when = None
|
||||
next_state = func(self)
|
||||
try:
|
||||
next_state, when = next_state
|
||||
except TypeError:
|
||||
pass
|
||||
if next_state:
|
||||
try:
|
||||
self.state['id'] = next_state.id
|
||||
except AttributeError:
|
||||
raise NotImplemented('State id %s is not valid.' % next_state)
|
||||
return when
|
||||
|
||||
func_wrapper.id = func.__name__
|
||||
func_wrapper.is_default = False
|
||||
return func_wrapper
|
||||
|
||||
|
||||
def default_state(func):
|
||||
func.is_default = True
|
||||
return func
|
||||
|
||||
|
||||
class MetaFSM(MetaAgent):
|
||||
def __init__(cls, name, bases, nmspc):
|
||||
super(MetaFSM, cls).__init__(name, bases, nmspc)
|
||||
states = {}
|
||||
# Re-use states from inherited classes
|
||||
default_state = None
|
||||
for i in bases:
|
||||
if isinstance(i, MetaFSM):
|
||||
for state_id, state in i.states.items():
|
||||
if state.is_default:
|
||||
default_state = state
|
||||
states[state_id] = state
|
||||
|
||||
# Add new states
|
||||
for name, func in nmspc.items():
|
||||
if hasattr(func, 'id'):
|
||||
if func.is_default:
|
||||
default_state = func
|
||||
states[func.id] = func
|
||||
cls.default_state = default_state
|
||||
cls.states = states
|
||||
|
||||
|
||||
class FSM(BaseAgent, metaclass=MetaFSM):
|
||||
def __init__(self, *args, **kwargs):
|
||||
super(FSM, self).__init__(*args, **kwargs)
|
||||
if 'id' not in self.state:
|
||||
self.state['id'] = self.default_state.id
|
||||
|
||||
def step(self):
|
||||
if 'id' in self.state:
|
||||
next_state = self.state['id']
|
||||
elif self.default_state:
|
||||
next_state = self.default_state.id
|
||||
else:
|
||||
raise Exception('{} has no valid state id or default state'.format(self))
|
||||
if next_state not in self.states:
|
||||
raise Exception('{} is not a valid id for {}'.format(next_state, self))
|
||||
self.states[next_state](self)
|
||||
|
||||
|
||||
from .BassModel import *
|
||||
from .BigMarketModel import *
|
||||
from .IndependentCascadeModel import *
|
||||
from .ModelM2 import *
|
||||
from .SentimentCorrelationModel import *
|
||||
from .SISaModel import *
|
||||
from .CounterModel import *
|
||||
from .DrawingAgent import *
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue