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Modify project name; fix importing issues in classes and tests

parallel_struct_est
philpMartin 4 years ago
parent bb67087289
commit cc672796e5
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  101. Some files were not shown because too many files have changed in this diff Show More

@ -0,0 +1,10 @@
Metadata-Version: 1.0
Name: PyCTBN
Version: 1.0
Summary: A Continuous Time Bayesian Network Library
Home-page: https://github.com/philipMartini/CTBN_Project
Author: Filippo Martini
Author-email: f.martini@campus.unimib.it
License: MIT
Description: # CTBN_Project
Platform: UNKNOWN

@ -0,0 +1,22 @@
README.md
setup.py
PyCTBN.egg-info/PKG-INFO
PyCTBN.egg-info/SOURCES.txt
PyCTBN.egg-info/dependency_links.txt
PyCTBN.egg-info/not-zip-safe
PyCTBN.egg-info/requires.txt
PyCTBN.egg-info/top_level.txt
classes/__init__.py
classes/abstract_importer.py
classes/cache.py
classes/conditional_intensity_matrix.py
classes/json_importer.py
classes/json_importer_mod.py
classes/network_graph.py
classes/parameters_estimator.py
classes/sample_path.py
classes/set_of_cims.py
classes/simple_cvs_importer.py
classes/structure.py
classes/structure_estimator.py
classes/trajectory.py

@ -0,0 +1,3 @@
https://github.com/numpy/numpy
https://github.com/pandas-dev/pandas
https://github.com/networkx/networkx

@ -0,0 +1,3 @@
numpy
pandas
networkx

@ -1,36 +1,34 @@
import sys
sys.path.append("./classes/")
import glob
import os
import glob
import network_graph as ng
import sample_path as sp
import parameters_estimator as pe
import json_importer as ji
from PyCTBN.json_importer import JsonImporter
from PyCTBN.sample_path import SamplePath
from PyCTBN.network_graph import NetworkGraph
from PyCTBN.parameters_estimator import ParametersEstimator
def main():
read_files = glob.glob(os.path.join('./data', "*.json")) #Take all json files in this dir
#import data
importer = ji.JsonImporter(read_files[0], 'samples', 'dyn.str', 'variables', 'Time', 'Name', 1)
importer = JsonImporter(read_files[0], 'samples', 'dyn.str', 'variables', 'Time', 'Name', 1)
#Create a SamplePath Obj
s1 = sp.SamplePath(importer)
s1 = SamplePath(importer)
#Build The trajectries and the structural infos
s1.build_trajectories()
s1.build_structure()
print(s1.structure.edges)
print(s1.structure.nodes_values)
#From The Structure Object build the Graph
g = ng.NetworkGraph(s1.structure)
g = NetworkGraph(s1.structure)
#Select a node you want to estimate the parameters
node = g.nodes[2]
print("NOde", node)
print("Node", node)
#Init the _graph specifically for THIS node
g.fast_init(node)
#Use SamplePath and Grpah to create a ParametersEstimator Object
p1 = pe.ParametersEstimator(s1.trajectories, g)
p1 = ParametersEstimator(s1.trajectories, g)
#Init the peEst specifically for THIS node
p1.fast_init(node)
#Compute the parameters

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# Minimal makefile for Sphinx documentation
#
# You can set these variables from the command line, and also
# from the environment for the first two.
SPHINXOPTS ?=
SPHINXBUILD ?= sphinx-build
SOURCEDIR = .
BUILDDIR = _build
# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
.PHONY: help Makefile
# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 0c64bed84aa4ce76aedaca18241d82e7
tags: 645f666f9bcd5a90fca523b33c5a78b7

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.. PyCTBN documentation master file, created by
sphinx-quickstart on Mon Nov 30 16:37:03 2020.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
Welcome to PyCTBN's documentation!
==================================
.. toctree::
:maxdepth: 2
:caption: Contents:
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`

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abstract\_importer module
=========================
.. automodule:: abstract_importer
:members:
:undoc-members:
:show-inheritance:

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cache module
============
.. automodule:: cache
:members:
:undoc-members:
:show-inheritance:

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conditional\_intensity\_matrix module
=====================================
.. automodule:: conditional_intensity_matrix
:members:
:undoc-members:
:show-inheritance:

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json\_importer module
=====================
.. automodule:: json_importer
:members:
:undoc-members:
:show-inheritance:

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scripts
=======
.. toctree::
:maxdepth: 4
abstract_importer
cache
conditional_intensity_matrix
json_importer
network_graph
parameters_estimator
sample_path
set_of_cims
structure
structure_estimator
trajectory

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network\_graph module
=====================
.. automodule:: network_graph
:members:
:undoc-members:
:show-inheritance:

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parameters\_estimator module
============================
.. automodule:: parameters_estimator
:members:
:undoc-members:
:show-inheritance:

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sample\_path module
===================
.. automodule:: sample_path
:members:
:undoc-members:
:show-inheritance:

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set\_of\_cims module
====================
.. automodule:: set_of_cims
:members:
:undoc-members:
:show-inheritance:

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structure module
================
.. automodule:: structure
:members:
:undoc-members:
:show-inheritance:

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structure\_estimator module
===========================
.. automodule:: structure_estimator
:members:
:undoc-members:
:show-inheritance:

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trajectory module
=================
.. automodule:: trajectory
:members:
:undoc-members:
:show-inheritance:

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dl.field-list > dd {
padding-left: 0.5em;
margin-top: 0em;
margin-left: 0em;
margin-bottom: 0em;
}
dl {
margin-bottom: 15px;
}
dd > :first-child {
margin-top: 0px;
}
dd ul, dd table {
margin-bottom: 10px;
}
dd {
margin-top: 3px;
margin-bottom: 10px;
margin-left: 30px;
}
dl > dd:last-child,
dl > dd:last-child > :last-child {
margin-bottom: 0;
}
dt:target, span.highlighted {
background-color: #fbe54e;
}
rect.highlighted {
fill: #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;
}
.classifier:before {
font-style: normal;
margin: 0.5em;
content: ":";
}
abbr, acronym {
border-bottom: dotted 1px;
cursor: help;
}
/* -- code displays --------------------------------------------------------- */
pre {
overflow: auto;
overflow-y: hidden; /* fixes display issues on Chrome browsers */
}
pre, div[class*="highlight-"] {
clear: both;
}
span.pre {
-moz-hyphens: none;
-ms-hyphens: none;
-webkit-hyphens: none;
hyphens: none;
}
div[class*="highlight-"] {
margin: 1em 0;
}
td.linenos pre {
border: 0;
background-color: transparent;
color: #aaa;
}
table.highlighttable {
display: block;
}
table.highlighttable tbody {
display: block;
}
table.highlighttable tr {
display: flex;
}
table.highlighttable td {
margin: 0;
padding: 0;
}
table.highlighttable td.linenos {
padding-right: 0.5em;
}
table.highlighttable td.code {
flex: 1;
overflow: hidden;
}
.highlight .hll {
display: block;
}
div.highlight pre,
table.highlighttable pre {
margin: 0;
}
div.code-block-caption + div {
margin-top: 0;
}
div.code-block-caption {
margin-top: 1em;
padding: 2px 5px;
font-size: small;
}
div.code-block-caption code {
background-color: transparent;
}
table.highlighttable td.linenos,
span.linenos,
div.doctest > div.highlight span.gp { /* gp: Generic.Prompt */
user-select: none;
}
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 {
margin: 1em 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: absolute;
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;
}
}

@ -0,0 +1,2 @@
.fa:before{-webkit-font-smoothing:antialiased}.clearfix{*zoom:1}.clearfix:before,.clearfix:after{display:table;content:""}.clearfix:after{clear:both}@font-face{font-family:FontAwesome;font-weight:normal;font-style:normal;src:url("../font/fontawesome_webfont.eot");src:url("../font/fontawesome_webfont.eot?#iefix") format("embedded-opentype"),url("../font/fontawesome_webfont.woff") format("woff"),url("../font/fontawesome_webfont.ttf") format("truetype"),url("../font/fontawesome_webfont.svg#FontAwesome") format("svg")}.fa:before{display:inline-block;font-family:FontAwesome;font-style:normal;font-weight:normal;line-height:1;text-decoration:inherit}a .fa{display:inline-block;text-decoration:inherit}li .fa{display:inline-block}li .fa-large:before,li .fa-large:before{width:1.875em}ul.fas{list-style-type:none;margin-left:2em;text-indent:-0.8em}ul.fas li .fa{width:0.8em}ul.fas li .fa-large:before,ul.fas li .fa-large:before{vertical-align:baseline}.fa-book:before{content:""}.icon-book:before{content:""}.fa-caret-down:before{content:""}.icon-caret-down:before{content:""}.fa-caret-up:before{content:""}.icon-caret-up:before{content:""}.fa-caret-left:before{content:""}.icon-caret-left:before{content:""}.fa-caret-right:before{content:""}.icon-caret-right:before{content:""}.rst-versions{position:fixed;bottom:0;left:0;width:300px;color:#fcfcfc;background:#1f1d1d;border-top:solid 10px #343131;font-family:"Lato","proxima-nova","Helvetica Neue",Arial,sans-serif;z-index:400}.rst-versions a{color:#2980B9;text-decoration:none}.rst-versions .rst-badge-small{display:none}.rst-versions .rst-current-version{padding:12px;background-color:#272525;display:block;text-align:right;font-size:90%;cursor:pointer;color:#27AE60;*zoom:1}.rst-versions .rst-current-version:before,.rst-versions .rst-current-version:after{display:table;content:""}.rst-versions .rst-current-version:after{clear:both}.rst-versions .rst-current-version .fa{color:#fcfcfc}.rst-versions .rst-current-version .fa-book{float:left}.rst-versions .rst-current-version .icon-book{float:left}.rst-versions .rst-current-version.rst-out-of-date{background-color:#E74C3C;color:#fff}.rst-versions .rst-current-version.rst-active-old-version{background-color:#F1C40F;color:#000}.rst-versions.shift-up .rst-other-versions{display:block}.rst-versions .rst-other-versions{font-size:90%;padding:12px;color:gray;display:none}.rst-versions .rst-other-versions hr{display:block;height:1px;border:0;margin:20px 0;padding:0;border-top:solid 1px #413d3d}.rst-versions .rst-other-versions dd{display:inline-block;margin:0}.rst-versions .rst-other-versions dd a{display:inline-block;padding:6px;color:#fcfcfc}.rst-versions.rst-badge{width:auto;bottom:20px;right:20px;left:auto;border:none;max-width:300px}.rst-versions.rst-badge .icon-book{float:none}.rst-versions.rst-badge .fa-book{float:none}.rst-versions.rst-badge.shift-up .rst-current-version{text-align:right}.rst-versions.rst-badge.shift-up .rst-current-version .fa-book{float:left}.rst-versions.rst-badge.shift-up .rst-current-version .icon-book{float:left}.rst-versions.rst-badge .rst-current-version{width:auto;height:30px;line-height:30px;padding:0 6px;display:block;text-align:center}@media screen and (max-width: 768px){.rst-versions{width:85%;display:none}.rst-versions.shift{display:block}img{width:100%;height:auto}}
/*# sourceMappingURL=badge_only.css.map */

@ -0,0 +1,93 @@
body, .entry-container,
.wy-nav-side,
.wy-side-nav-search,
.fundo-claro,
.wy-menu-vertical li.current,
.rst-content dl:not(.docutils) dt,
code, .rst-content tt,
.wy-side-nav-search > a:hover, .wy-side-nav-search .wy-dropdown > a:hover,
.wy-nav-content{
background-color: rgb(24, 26, 27) !important;
}
h2 a, h2 a:visited, h2 a:hover {
color: rgb(209, 206, 199);
}
body {
color: rgb(209, 206, 199);
}
a, a:hover, a:visited {
color: rgb(113, 178, 234);
}
.wy-menu-vertical a {
color: #b3b3b3;
}
code, .rst-content tt {
color: #fff8f8;
border: 0;
}
codeblock, pre.literal-block, .rst-content .literal-block, .rst-content pre.literal-block, div[class^="highlight"] {
border: 1px solid #000;
}
.rst-content dl:not(.docutils) dl dt {
background: rgb(24, 26, 27) !important;
}
.wy-side-nav-search > a, .wy-side-nav-search .wy-dropdown > a {
color: #fcfcfc;
}
.wy-alert.wy-alert-info, .rst-content .note, .rst-content .wy-alert-info.attention, .rst-content .wy-alert-info.caution, .rst-content .wy-alert-info.danger, .rst-content .wy-alert-info.error, .rst-content .wy-alert-info.hint, .rst-content .wy-alert-info.important, .rst-content .wy-alert-info.tip, .rst-content .wy-alert-info.warning, .rst-content .seealso, .rst-content .wy-alert-info.admonition-todo,
.admonition.note code{
background: #535050 !important;
}
@media screen and (min-width: 768px) {
.wy-nav-side{
width: 224px;
}
.wy-nav-content-wrap{
margin-left: 200px;
background:rgb(24, 26, 27);
}
}
.wy-nav-content-wrap{
margin-left: 200px;
background: #343131;
}
.hentry {
border-bottom: 2px solid rgb(24, 26, 27);
}
.wy-alert.wy-alert-danger .wy-alert-title, .rst-content .wy-alert-danger.note .wy-alert-title, .rst-content .wy-alert-danger.attention .wy-alert-title, .rst-content .wy-alert-danger.caution .wy-alert-title, .rst-content .danger .wy-alert-title, .rst-content .error .wy-alert-title, .rst-content .wy-alert-danger.hint .wy-alert-title, .rst-content .wy-alert-danger.important .wy-alert-title, .rst-content .wy-alert-danger.tip .wy-alert-title, .rst-content .wy-alert-danger.warning .wy-alert-title, .rst-content .wy-alert-danger.seealso .wy-alert-title, .rst-content .wy-alert-danger.admonition-todo .wy-alert-title, .wy-alert.wy-alert-danger .rst-content .admonition-title, .rst-content .wy-alert.wy-alert-danger .admonition-title, .rst-content .wy-alert-danger.note .admonition-title, .rst-content .wy-alert-danger.attention .admonition-title, .rst-content .wy-alert-danger.caution .admonition-title, .rst-content .danger .admonition-title, .rst-content .error .admonition-title, .rst-content .wy-alert-danger.hint .admonition-title, .rst-content .wy-alert-danger.important .admonition-title, .rst-content .wy-alert-danger.tip .admonition-title, .rst-content .wy-alert-danger.warning .admonition-title, .rst-content .wy-alert-danger.seealso .admonition-title, .rst-content .wy-alert-danger.admonition-todo .admonition-title {
background: #db655a;
}
.wy-alert.wy-alert-danger, .rst-content .wy-alert-danger.note, .rst-content .wy-alert-danger.attention, .rst-content .wy-alert-danger.caution, .rst-content .danger, .rst-content .error, .rst-content .wy-alert-danger.hint, .rst-content .wy-alert-danger.important, .rst-content .wy-alert-danger.tip, .rst-content .wy-alert-danger.warning, .rst-content .wy-alert-danger.seealso, .rst-content .wy-alert-danger.admonition-todo {
background: #e18279;
color: #fff;
}
.wy-alert.wy-alert-warning, .rst-content .wy-alert-warning.note, .rst-content .attention, .rst-content .caution, .rst-content .wy-alert-warning.danger, .rst-content .wy-alert-warning.error, .rst-content .wy-alert-warning.hint, .rst-content .wy-alert-warning.important, .rst-content .wy-alert-warning.tip, .rst-content .warning, .rst-content .wy-alert-warning.seealso, .rst-content .admonition-todo {
background: #ca9f52;
color: #fff;
}
.wy-alert.wy-alert-warning .wy-alert-title, .rst-content .wy-alert-warning.note .wy-alert-title, .rst-content .attention .wy-alert-title, .rst-content .caution .wy-alert-title, .rst-content .wy-alert-warning.danger .wy-alert-title, .rst-content .wy-alert-warning.error .wy-alert-title, .rst-content .wy-alert-warning.hint .wy-alert-title, .rst-content .wy-alert-warning.important .wy-alert-title, .rst-content .wy-alert-warning.tip .wy-alert-title, .rst-content .warning .wy-alert-title, .rst-content .wy-alert-warning.seealso .wy-alert-title, .rst-content .admonition-todo .wy-alert-title, .wy-alert.wy-alert-warning .rst-content .admonition-title, .rst-content .wy-alert.wy-alert-warning .admonition-title, .rst-content .wy-alert-warning.note .admonition-title, .rst-content .attention .admonition-title, .rst-content .caution .admonition-title, .rst-content .wy-alert-warning.danger .admonition-title, .rst-content .wy-alert-warning.error .admonition-title, .rst-content .wy-alert-warning.hint .admonition-title, .rst-content .wy-alert-warning.important .admonition-title, .rst-content .wy-alert-warning.tip .admonition-title, .rst-content .warning .admonition-title, .rst-content .wy-alert-warning.seealso .admonition-title, .rst-content .admonition-todo .admonition-title {
background: #ca7a35;
}
.wy-body-for-nav {
background-image: none !important;
}

@ -0,0 +1,494 @@
@import url("theme.css");
.wy-side-nav-search{
background-color: #595C5E;
}
.wy-side-nav-search input[type=text] {
border-color: #595C5E;
}
@media screen and (min-width: 768px) {
.wy-nav-side{
width: 224px;
}
.wy-nav-content-wrap{
margin-left: 200px;
background: #343131;
}
}
@media screen and (max-width: 768px) {
.wy-nav-content{
background-color: #343131;
}
}
.wy-nav-top{
background-color: #595C5E;
}
.wy-nav-content{
padding-top: 1%;
max-width: 100%;
background-color: #343131;
}
.rst-content{
margin-left: -3%;
}
pre{
font-size: 0.9em;
padding: 1%;
}
pre > span,
pre > p{
margin: 0;
font-size: 1em;
}
pre > span{
margin: 0;
}
.hentry{
padding-top: 2%;
padding-bottom: 5%;
padding-left: 3%;
padding-right: 3%;
border-bottom: 2px solid #343131;
}
.entry-container{
background-color: #fff; /*#EAEAEA; */
border-radius: 3px;
/* -webkit-box-shadow: 0 0 10px 8px rgba(50, 50, 50, 0.75); */
/* -moz-box-shadow: 0 0 10px 8px rgba(50, 50, 50, 0.75); */
/* box-shadow: 0 0 10px 8px rgba(50, 50, 50, 0.75); */
-webkit-box-shadow: 0 0 10px 8px rgba(2, 2, 2, 0.36);
-moz-box-shadow: 0 0 10px 8px rgba(2, 2, 2, 0.36);
box-shadow: 0 0 10px 8px rgba(2, 2, 2, 0.36);
position: relative;
z-index: 210;
}
.entry-content{
margin-right: 3%;
}
.wy-side-nav-search{
padding:0.639em
}
.wy-menu-vertical a:hover{
-webkit-box-shadow: 0 0 5px 5px rgba(20, 20, 20, 0.30);
-moz-box-shadow: 0 0 5px 5px rgba(20, 20, 20, 0.30);
box-shadow: 0 0 5px 5px rgba(20, 20, 20, 0.30);
}
.wy-menu-vertical a{
width: 90%
}
#comments,
#comment-form{
padding: 20px;
}
@media screen and (max-width: 1330px) {
.fancybox img{
width: 310px; /* 88px / 633px */
height: 206px;
}
}
@media screen and (max-width: 1241px) {
.fancybox img{
width: 280px;
height: 186px;
}
}
@media screen and (max-width: 1154px) {
.fancybox img{
width: 260px;
height: 173px;
}
}
.expander {
position: absolute;
top: 5px;
left: 5px;
width: 16px;
height: 16px;
padding: 4px;
background: white url(/static/blog/img/fsbtn.png) center center no-repeat;
z-index: 99999;
cursor: pointer;
}
/* 340 */
/* .rst-content img { */
/* margin-top: 8px; */
/* margin-left: 10px; */
/* margin-bottom: 5px; */
/* } */
/* 260 */
.rst-content .row img {
margin-top: 8px;
margin-left: 5px;
border-radius: 3px;
-webkit-box-shadow: 0 0 10px 5px rgba(2, 2, 2, 0.36);
-moz-box-shadow: 0 0 10px 5px /*rgba(50, 50, 50, 0.75)*/ rgba(2, 2, 2, 0.36);
box-shadow: 0 0 10px 5px rgba(2, 2, 2, 0.36);
}
.rst-content{
z-index: 210;
margin-top: -60px;
}
h2 a,
h2 a:visited,
h2 a:hover{
color: #404040;
}
.wy-menu-vertical li.on a, .wy-menu-vertical li.current>a {
color: #b3b3b3;
background: #4e4a4a;
box-shadow: 0 0 5px 5px rgba(20, 20, 20, 0.30);
border: none;
}
.wy-menu-vertical li.current {
background: #343131;
border: none;
}
.wy-menu-vertical li.current a{
border:none
}
.wy-alert.wy-alert-info .wy-alert-title, .rst-content .note .wy-alert-title, .rst-content .wy-alert-info.attention .wy-alert-title, .rst-content .wy-alert-info.caution .wy-alert-title, .rst-content .wy-alert-info.danger .wy-alert-title, .rst-content .wy-alert-info.error .wy-alert-title, .rst-content .wy-alert-info.hint .wy-alert-title, .rst-content .wy-alert-info.important .wy-alert-title, .rst-content .wy-alert-info.tip .wy-alert-title, .rst-content .wy-alert-info.warning .wy-alert-title, .rst-content .seealso .wy-alert-title, .rst-content .wy-alert-info.admonition-todo .wy-alert-title, .wy-alert.wy-alert-info .rst-content .admonition-title, .rst-content .wy-alert.wy-alert-info .admonition-title, .rst-content .note .admonition-title, .rst-content .wy-alert-info.attention .admonition-title, .rst-content .wy-alert-info.caution .admonition-title, .rst-content .wy-alert-info.danger .admonition-title, .rst-content .wy-alert-info.error .admonition-title, .rst-content .wy-alert-info.hint .admonition-title, .rst-content .wy-alert-info.important .admonition-title, .rst-content .wy-alert-info.tip .admonition-title, .rst-content .wy-alert-info.warning .admonition-title, .rst-content .seealso .admonition-title, .rst-content .wy-alert-info.admonition-todo .admonition-title {
background: #47494a;
}
.wy-alert.wy-alert-info, .rst-content .note, .rst-content .wy-alert-info.attention, .rst-content .wy-alert-info.caution, .rst-content .wy-alert-info.danger, .rst-content .wy-alert-info.error, .rst-content .wy-alert-info.hint, .rst-content .wy-alert-info.important, .rst-content .wy-alert-info.tip, .rst-content .wy-alert-info.warning, .rst-content .seealso, .rst-content .wy-alert-info.admonition-todo {
background: #ececec;
}
.wy-alert.wy-alert-danger, .rst-content .wy-alert-danger.note, .rst-content .wy-alert-danger.attention, .rst-content .wy-alert-danger.caution, .rst-content .danger, .rst-content .error, .rst-content .wy-alert-danger.hint, .rst-content .wy-alert-danger.important, .rst-content .wy-alert-danger.tip, .rst-content .wy-alert-danger.warning, .rst-content .wy-alert-danger.seealso, .rst-content .wy-alert-danger.admonition-todo {
background: #f0d5d2;
}
.wy-menu-vertical li.on a:hover,
.wy-menu-vertical li.current>a:hover {
background: #4e4a4a;
}
.wy-menu-vertical li.current a:hover {
background: #4e4a4a;
}
wy-menu-vertical li.toctree-l2.current>a {
color: #343131 !important;
}
.wy-menu-vertical li.toctree-l2.current>a {
background: #343131;
padding: 0.4045em 2.427em;
box-shadow: none;
}
.highlight{
background: #000 !important;
}
.highlight pre,
.highlight .mi,
.highlight .go{
color: #57de4e !important;
font-size: 0.9em !important;
}
.highlight .nt{
color: #8080ec;
}
.highlight .n, .highlight .nn,
.highlight .p, .highlight .o,
.highlight .nv,
.highlight .gp{
color: #57de4e;
}
.highlight .kn{
color: #47ffff !important;
}
.highlight .nc,
.highlight .nd{
color: #1c909e;
font-weight: normal;
}
.highlight .k, .highlight .bp{
color: #47ffff !important;
}
.highlight .kc {
color: #ae39ff;
font-weight: normal !important;
}
.highlight .nf,
.highlight .nb{
color: #87CEFA;
}
.highlight .s1, .highlight .s2, .highlight .s,
.highlight .sd, .highlight .si,
.highlight .se{
color: #FDF5E6;
}
.highlight .ow{
color: #47ffff;
}
.highlight .c1,
.highlight .c{
color: #d80e04;
}
.fundo-claro{
height: 88px;
background-color: #595C5E;
margin-left: -10%;
margin-top: -1.1%;
margin-right: -10%;
}
@media screen and (max-width: 980px) {
pre{
overflow-x: scroll;
}
}
@media screen and (max-width: 768px){
.fundo-claro{
display:none;
}
.rst-content{
z-index: 210;
margin-top: -20px;
}
}
.page{
width: 3%;
float:left;
}
.previous{
width: 10%
}
.paginator{
margin-top: 50px;
padding-bottom: 25px;
padding-left: 20px;
}
blockquote {
font-style: italic;
margin: 0 4.5em;
position: relative;
}
blockquote, q {
quotes: "" "";
}
blockquote:before {
color: #807f7f;
content: "\201C";
display: block;
font-family: "Droid Serif", "Times New Roman", serif;
font-size: 48px;
font-size: 4.8rem;
font-style: normal;
font-weight: bold;
line-height: 1;
position: absolute;
top: -15px;
left: -40px;
}
.flatpage{
}
.bkg-escuro{
background-color: #343131;
color: #b3b3b3;
}
.search-topo{
float: right;
padding-right: 7%;
margin-top: -1.5;
}
.fa-home:before, .icon-home:before {
content: url('../img/porao-branco.png');
}
/* fundo preto */
.entry-container-escuro{
background-color: #343131;
color: #b3b3b3;
padding: 15px;
}
.entry-container-escuro h2,
.entry-container-escuro h2 a,
.entry-container-escuro h2 a:visited,
.entry-container-escuro h2 a:hover,
.entry-container-escuro h4,
.entry-container-escuro .entry-info abbr{
color: #F9F4F4;
}
/* fim fundo preto */
.classe-correio textarea{
width: 60%;
min-height: 300px;
margin-left: -39.5%;
border-radius: 15px;
}
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background-color: #343131;
}
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width: 30%;
margin-bottom: 10px;
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color: #2980B9;
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color: #b3b3b3;
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color: #fcfcfc;
}
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color: #eac648;
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/* margin-bottom: 24px; */
/* background-color: #000; */
/* } */
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/*
* doctools.js
* ~~~~~~~~~~~
*
* Sphinx JavaScript utilities for all documentation.
*
* :copyright: Copyright 2007-2020 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, addItems) {
if (node.nodeType === 3) {
var val = node.nodeValue;
var pos = val.toLowerCase().indexOf(text);
if (pos >= 0 &&
!jQuery(node.parentNode).hasClass(className) &&
!jQuery(node.parentNode).hasClass("nohighlight")) {
var span;
var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg");
if (isInSVG) {
span = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
} else {
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);
if (isInSVG) {
var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect");
var bbox = node.parentElement.getBBox();
rect.x.baseVal.value = bbox.x;
rect.y.baseVal.value = bbox.y;
rect.width.baseVal.value = bbox.width;
rect.height.baseVal.value = bbox.height;
rect.setAttribute('class', className);
addItems.push({
"parent": node.parentNode,
"target": rect});
}
}
}
else if (!jQuery(node).is("button, select, textarea")) {
jQuery.each(node.childNodes, function() {
highlight(this, addItems);
});
}
}
var addItems = [];
var result = this.each(function() {
highlight(this, addItems);
});
for (var i = 0; i < addItems.length; ++i) {
jQuery(addItems[i].parent).before(addItems[i].target);
}
return result;
};
/*
* 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();
if (DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) {
this.initOnKeyListeners();
}
},
/**
* 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 && $.browser.mozilla)
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).keydown(function(event) {
var activeElementType = document.activeElement.tagName;
// don't navigate when in search box, textarea, dropdown or button
if (activeElementType !== 'TEXTAREA' && activeElementType !== 'INPUT' && activeElementType !== 'SELECT'
&& activeElementType !== 'BUTTON' && !event.altKey && !event.ctrlKey && !event.metaKey
&& !event.shiftKey) {
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();
});

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var DOCUMENTATION_OPTIONS = {
URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
VERSION: '',
LANGUAGE: 'None',
COLLAPSE_INDEX: false,
BUILDER: 'html',
FILE_SUFFIX: '.html',
LINK_SUFFIX: '.html',
HAS_SOURCE: true,
SOURCELINK_SUFFIX: '.txt',
NAVIGATION_WITH_KEYS: false
};

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// setting highlight for async stuff in python
var async_kw = ['async', 'await'];
jQuery.each(async_kw, function(i, kw){
var elements = jQuery(".highlight-python .n:contains('" + kw + "')");
jQuery.each(elements, function(j, el){
el = jQuery(el);
if (el.text() == kw){
el.removeClass('n');
el.addClass('kn');
};
});
});

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$( document ).ready(function() {
// Shift nav in mobile when clicking the menu.
$(document).on('click', "[data-toggle='wy-nav-top']", function() {
$("[data-toggle='wy-nav-shift']").toggleClass("shift");
$("[data-toggle='rst-versions']").toggleClass("shift");
});
// Close menu when you click a link.
$(document).on('click', ".wy-menu-vertical .current ul li a", function() {
$("[data-toggle='wy-nav-shift']").removeClass("shift");
$("[data-toggle='rst-versions']").toggleClass("shift");
});
$(document).on('click', "[data-toggle='rst-current-version']", function() {
$("[data-toggle='rst-versions']").toggleClass("shift-up");
});
// Make tables responsive
$("table.docutils:not(.field-list)").wrap("<div class='wy-table-responsive'></div>");
});
window.SphinxRtdTheme = (function (jquery) {
var stickyNav = (function () {
var navBar,
win,
stickyNavCssClass = 'stickynav',
applyStickNav = function () {
if (navBar.height() <= win.height()) {
navBar.addClass(stickyNavCssClass);
} else {
navBar.removeClass(stickyNavCssClass);
}
},
enable = function () {
applyStickNav();
win.on('resize', applyStickNav);
},
init = function () {
navBar = jquery('nav.wy-nav-side:first');
win = jquery(window);
};
jquery(init);
return {
enable : enable
};
}());
return {
StickyNav : stickyNav
};
}($));

@ -0,0 +1,297 @@
/*
* language_data.js
* ~~~~~~~~~~~~~~~~
*
* This script contains the language-specific data used by searchtools.js,
* namely the list of stopwords, stemmer, scorer and splitter.
*
* :copyright: Copyright 2007-2020 by the Sphinx team, see AUTHORS.
* :license: BSD, see LICENSE for details.
*
*/
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"];
/* 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;
}
}
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;
}

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.highlight .hll { background-color: #ffffcc }
.highlight { background: #ffffff; }

@ -0,0 +1,514 @@
/*
* searchtools.js
* ~~~~~~~~~~~~~~~~
*
* Sphinx JavaScript utilities for the full-text search.
*
* :copyright: Copyright 2007-2020 by the Sphinx team, see AUTHORS.
* :license: BSD, see LICENSE for details.
*
*/
if (!Scorer) {
/**
* 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,
partialTitle: 7,
// query found in terms
term: 5,
partialTerm: 2
};
}
if (!splitQuery) {
function splitQuery(query) {
return query.split(/\s+/);
}
}
/**
* Search Module
*/
var Search = {
_index : null,
_queued_query : null,
_pulse_status : -1,
htmlToText : function(htmlString) {
var virtualDocument = document.implementation.createHTMLDocument('virtual');
var htmlElement = $(htmlString, virtualDocument);
htmlElement.find('.headerlink').remove();
docContent = htmlElement.find('[role=main]')[0];
if(docContent === undefined) {
console.warn("Content block not found. Sphinx search tries to obtain it " +
"via '[role=main]'. Could you check your theme or template.");
return "";
}
return docContent.textContent || docContent.innerText;
},
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 class="search-summary">&nbsp;</p>').appendTo(this.out);
this.output = $('<ul class="search"/>').appendTo(this.out);
$('#search-progress').text(_('Preparing search...'));
this.startPulse();
// index already loaded, the browser was quick!
if (this.hasIndex())
this.query(query);
else
this.deferQuery(query);
},
/**
* execute search (requires search index to be loaded)
*/
query : function(query) {
var i;
// stem the searchterms and add them to the correct list
var stemmer = new Stemmer();
var searchterms = [];
var excluded = [];
var hlterms = [];
var tmp = splitQuery(query);
var objectterms = [];
for (i = 0; i < tmp.length; i++) {
if (tmp[i] !== "") {
objectterms.push(tmp[i].toLowerCase());
}
if ($u.indexOf(stopwords, tmp[i].toLowerCase()) != -1 || tmp[i] === "") {
// 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 = $('<li style="display:none"></li>');
var requestUrl = "";
var linkUrl = "";
if (DOCUMENTATION_OPTIONS.BUILDER === 'dirhtml') {
// dirhtml builder
var dirname = item[0] + '/';
if (dirname.match(/\/index\/$/)) {
dirname = dirname.substring(0, dirname.length-6);
} else if (dirname == 'index/') {
dirname = '';
}
requestUrl = DOCUMENTATION_OPTIONS.URL_ROOT + dirname;
linkUrl = requestUrl;
} else {
// normal html builders
requestUrl = DOCUMENTATION_OPTIONS.URL_ROOT + item[0] + DOCUMENTATION_OPTIONS.FILE_SUFFIX;
linkUrl = item[0] + DOCUMENTATION_OPTIONS.LINK_SUFFIX;
}
listItem.append($('<a/>').attr('href',
linkUrl +
highlightstring + item[2]).html(item[1]));
if (item[3]) {
listItem.append($('<span> (' + item[3] + ')</span>'));
Search.output.append(listItem);
listItem.slideDown(5, function() {
displayNextItem();
});
} else if (DOCUMENTATION_OPTIONS.HAS_SOURCE) {
$.ajax({url: requestUrl,
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;
var fullnameLower = fullname.toLowerCase()
if (fullnameLower.indexOf(object) > -1) {
var score = 0;
var parts = fullnameLower.split('.');
// check for different match types: exact matches of full name or
// "last name" (i.e. last dotted part)
if (fullnameLower == 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}
];
// add support for partial matches
if (word.length > 2) {
for (var w in terms) {
if (w.match(word) && !terms[word]) {
_o.push({files: terms[w], score: Scorer.partialTerm})
}
}
for (var w in titleterms) {
if (w.match(word) && !titleterms[word]) {
_o.push({files: titleterms[w], score: Scorer.partialTitle})
}
}
}
// 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].indexOf(word) === -1)
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
var filteredTermCount = // as search terms with length < 3 are discarded: ignore
searchterms.filter(function(term){return term.length > 2}).length
if (
fileMap[file].length != searchterms.length &&
fileMap[file].length != filteredTermCount
) 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(htmlText, keywords, hlwords) {
var text = Search.htmlToText(htmlText);
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();
});

@ -0,0 +1,999 @@
// 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]';
};
// Is the given value `NaN`?
_.isNaN = function(obj) {
// `NaN` is the only value for which `===` is not reflexive.
return obj !== obj;
};
// Is a given value a boolean?
_.isBoolean = function(obj) {
return obj === true || obj === false || toString.call(obj) == '[object Boolean]';
};
// Is a given value a date?
_.isDate = function(obj) {
return toString.call(obj) == '[object Date]';
};
// Is the given value a regular expression?
_.isRegExp = function(obj) {
return toString.call(obj) == '[object RegExp]';
};
// Is a given value equal to null?
_.isNull = function(obj) {
return obj === null;
};
// Is a given variable undefined?
_.isUndefined = function(obj) {
return obj === void 0;
};
// Has own property?
_.has = function(obj, key) {
return hasOwnProperty.call(obj, key);
};
// Utility Functions
// -----------------
// Run Underscore.js in *noConflict* mode, returning the `_` variable to its
// previous owner. Returns a reference to the Underscore object.
_.noConflict = function() {
root._ = previousUnderscore;
return this;
};
// Keep the identity function around for default iterators.
_.identity = function(value) {
return value;
};
// Run a function **n** times.
_.times = function (n, iterator, context) {
for (var i = 0; i < n; i++) iterator.call(context, i);
};
// Escape a string for HTML interpolation.
_.escape = function(string) {
return (''+string).replace(/&/g, '&amp;').replace(/</g, '&lt;').replace(/>/g, '&gt;').replace(/"/g, '&quot;').replace(/'/g, '&#x27;').replace(/\//g,'&#x2F;');
};
// Add your own custom functions to the Underscore object, ensuring that
// they're correctly added to the OOP wrapper as well.
_.mixin = function(obj) {
each(_.functions(obj), function(name){
addToWrapper(name, _[name] = obj[name]);
});
};
// Generate a unique integer id (unique within the entire client session).
// Useful for temporary DOM ids.
var idCounter = 0;
_.uniqueId = function(prefix) {
var id = idCounter++;
return prefix ? prefix + id : id;
};
// By default, Underscore uses ERB-style template delimiters, change the
// following template settings to use alternative delimiters.
_.templateSettings = {
evaluate : /<%([\s\S]+?)%>/g,
interpolate : /<%=([\s\S]+?)%>/g,
escape : /<%-([\s\S]+?)%>/g
};
// When customizing `templateSettings`, if you don't want to define an
// interpolation, evaluation or escaping regex, we need one that is
// guaranteed not to match.
var noMatch = /.^/;
// Within an interpolation, evaluation, or escaping, remove HTML escaping
// that had been previously added.
var unescape = function(code) {
return code.replace(/\\\\/g, '\\').replace(/\\'/g, "'");
};
// JavaScript micro-templating, similar to John Resig's implementation.
// Underscore templating handles arbitrary delimiters, preserves whitespace,
// and correctly escapes quotes within interpolated code.
_.template = function(str, data) {
var c = _.templateSettings;
var tmpl = 'var __p=[],print=function(){__p.push.apply(__p,arguments);};' +
'with(obj||{}){__p.push(\'' +
str.replace(/\\/g, '\\\\')
.replace(/'/g, "\\'")
.replace(c.escape || noMatch, function(match, code) {
return "',_.escape(" + unescape(code) + "),'";
})
.replace(c.interpolate || noMatch, function(match, code) {
return "'," + unescape(code) + ",'";
})
.replace(c.evaluate || noMatch, function(match, code) {
return "');" + unescape(code).replace(/[\r\n\t]/g, ' ') + ";__p.push('";
})
.replace(/\r/g, '\\r')
.replace(/\n/g, '\\n')
.replace(/\t/g, '\\t')
+ "');}return __p.join('');";
var func = new Function('obj', '_', tmpl);
if (data) return func(data, _);
return function(data) {
return func.call(this, data, _);
};
};
// Add a "chain" function, which will delegate to the wrapper.
_.chain = function(obj) {
return _(obj).chain();
};
// The OOP Wrapper
// ---------------
// If Underscore is called as a function, it returns a wrapped object that
// can be used OO-style. This wrapper holds altered versions of all the
// underscore functions. Wrapped objects may be chained.
var wrapper = function(obj) { this._wrapped = obj; };
// Expose `wrapper.prototype` as `_.prototype`
_.prototype = wrapper.prototype;
// Helper function to continue chaining intermediate results.
var result = function(obj, chain) {
return chain ? _(obj).chain() : obj;
};
// A method to easily add functions to the OOP wrapper.
var addToWrapper = function(name, func) {
wrapper.prototype[name] = function() {
var args = slice.call(arguments);
unshift.call(args, this._wrapped);
return result(func.apply(_, args), this._chain);
};
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@ -0,0 +1,31 @@
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<h1 id="index">Index</h1>
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<a href="#A"><strong>A</strong></a>
| <a href="#B"><strong>B</strong></a>
| <a href="#C"><strong>C</strong></a>
| <a href="#D"><strong>D</strong></a>
| <a href="#E"><strong>E</strong></a>
| <a href="#F"><strong>F</strong></a>
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| <a href="#V"><strong>V</strong></a>
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<h2 id="A">A</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li>
abstract_importer
<ul>
<li><a href="rst/abstract_importer.html#module-abstract_importer">module</a>
</li>
</ul></li>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter">AbstractImporter (class in abstract_importer)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/set_of_cims.html#set_of_cims.SetOfCims.actual_cims">actual_cims() (set_of_cims.SetOfCims property)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.add_edges">add_edges() (network_graph.NetworkGraph method)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.add_nodes">add_nodes() (network_graph.NetworkGraph method)</a>
</li>
</ul></td>
</tr></table>
<h2 id="B">B</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/set_of_cims.html#set_of_cims.SetOfCims.build_cims">build_cims() (set_of_cims.SetOfCims method)</a>
</li>
<li><a href="rst/structure_estimator.html#structure_estimator.StructureEstimator.build_complete_graph">build_complete_graph() (structure_estimator.StructureEstimator method)</a>
</li>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.build_list_of_samples_array">build_list_of_samples_array() (abstract_importer.AbstractImporter method)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.build_p_comb_structure_for_a_node">build_p_comb_structure_for_a_node() (network_graph.NetworkGraph method)</a>
</li>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.build_sorter">build_sorter() (abstract_importer.AbstractImporter method)</a>
<ul>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.build_sorter">(json_importer.JsonImporter method)</a>
</li>
</ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/sample_path.html#sample_path.SamplePath.build_structure">build_structure() (sample_path.SamplePath method)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.build_time_columns_filtering_for_a_node">build_time_columns_filtering_for_a_node() (network_graph.NetworkGraph method)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.build_time_scalar_indexing_structure_for_a_node">build_time_scalar_indexing_structure_for_a_node() (network_graph.NetworkGraph method)</a>
</li>
<li><a href="rst/set_of_cims.html#set_of_cims.SetOfCims.build_times_and_transitions_structures">build_times_and_transitions_structures() (set_of_cims.SetOfCims method)</a>
</li>
<li><a href="rst/sample_path.html#sample_path.SamplePath.build_trajectories">build_trajectories() (sample_path.SamplePath method)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.build_transition_filtering_for_a_node">build_transition_filtering_for_a_node() (network_graph.NetworkGraph method)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.build_transition_scalar_indexing_structure_for_a_node">build_transition_scalar_indexing_structure_for_a_node() (network_graph.NetworkGraph method)</a>
</li>
</ul></td>
</tr></table>
<h2 id="C">C</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li>
cache
<ul>
<li><a href="rst/cache.html#module-cache">module</a>
</li>
</ul></li>
<li><a href="rst/cache.html#cache.Cache">Cache (class in cache)</a>
</li>
<li><a href="rst/conditional_intensity_matrix.html#conditional_intensity_matrix.ConditionalIntensityMatrix.cim">cim() (conditional_intensity_matrix.ConditionalIntensityMatrix property)</a>
</li>
<li><a href="rst/cache.html#cache.Cache.clear">clear() (cache.Cache method)</a>
</li>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.clear_concatenated_frame">clear_concatenated_frame() (abstract_importer.AbstractImporter method)</a>
</li>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.clear_data_frame_list">clear_data_frame_list() (json_importer.JsonImporter method)</a>
</li>
<li><a href="rst/structure_estimator.html#structure_estimator.StructureEstimator.complete_test">complete_test() (structure_estimator.StructureEstimator method)</a>
</li>
<li><a href="rst/trajectory.html#trajectory.Trajectory.complete_trajectory">complete_trajectory() (trajectory.Trajectory property)</a>
</li>
<li><a href="rst/conditional_intensity_matrix.html#conditional_intensity_matrix.ConditionalIntensityMatrix.compute_cim_coefficients">compute_cim_coefficients() (conditional_intensity_matrix.ConditionalIntensityMatrix method)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/parameters_estimator.html#parameters_estimator.ParametersEstimator.compute_parameters_for_node">compute_parameters_for_node() (parameters_estimator.ParametersEstimator method)</a>
</li>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.compute_row_delta_in_all_samples_frames">compute_row_delta_in_all_samples_frames() (abstract_importer.AbstractImporter method)</a>
</li>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.compute_row_delta_sigle_samples_frame">compute_row_delta_sigle_samples_frame() (abstract_importer.AbstractImporter method)</a>
</li>
<li><a href="rst/parameters_estimator.html#parameters_estimator.ParametersEstimator.compute_state_res_time_for_node">compute_state_res_time_for_node() (parameters_estimator.ParametersEstimator method)</a>
</li>
<li><a href="rst/parameters_estimator.html#parameters_estimator.ParametersEstimator.compute_state_transitions_for_a_node">compute_state_transitions_for_a_node() (parameters_estimator.ParametersEstimator method)</a>
</li>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.concatenated_samples">concatenated_samples() (abstract_importer.AbstractImporter property)</a>
</li>
<li>
conditional_intensity_matrix
<ul>
<li><a href="rst/conditional_intensity_matrix.html#module-conditional_intensity_matrix">module</a>
</li>
</ul></li>
<li><a href="rst/conditional_intensity_matrix.html#conditional_intensity_matrix.ConditionalIntensityMatrix">ConditionalIntensityMatrix (class in conditional_intensity_matrix)</a>
</li>
<li><a href="rst/structure_estimator.html#structure_estimator.StructureEstimator.ctpc_algorithm">ctpc_algorithm() (structure_estimator.StructureEstimator method)</a>
</li>
</ul></td>
</tr></table>
<h2 id="D">D</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.dataset_id">dataset_id() (abstract_importer.AbstractImporter method)</a>
<ul>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.dataset_id">(json_importer.JsonImporter method)</a>
</li>
</ul></li>
</ul></td>
</tr></table>
<h2 id="E">E</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.edges">edges() (network_graph.NetworkGraph property)</a>
<ul>
<li><a href="rst/structure.html#structure.Structure.edges">(structure.Structure property)</a>
</li>
</ul></li>
</ul></td>
</tr></table>
<h2 id="F">F</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.fast_init">fast_init() (network_graph.NetworkGraph method)</a>
<ul>
<li><a href="rst/parameters_estimator.html#parameters_estimator.ParametersEstimator.fast_init">(parameters_estimator.ParametersEstimator method)</a>
</li>
</ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.file_path">file_path() (abstract_importer.AbstractImporter property)</a>
</li>
<li><a href="rst/set_of_cims.html#set_of_cims.SetOfCims.filter_cims_with_mask">filter_cims_with_mask() (set_of_cims.SetOfCims method)</a>
</li>
<li><a href="rst/cache.html#cache.Cache.find">find() (cache.Cache method)</a>
</li>
</ul></td>
</tr></table>
<h2 id="G">G</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/structure_estimator.html#structure_estimator.StructureEstimator.generate_possible_sub_sets_of_size">generate_possible_sub_sets_of_size() (structure_estimator.StructureEstimator method)</a>
</li>
<li><a href="rst/set_of_cims.html#set_of_cims.SetOfCims.get_cims_number">get_cims_number() (set_of_cims.SetOfCims method)</a>
</li>
<li><a href="rst/structure.html#structure.Structure.get_node_id">get_node_id() (structure.Structure method)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.get_node_indx">get_node_indx() (network_graph.NetworkGraph method)</a>
<ul>
<li><a href="rst/structure.html#structure.Structure.get_node_indx">(structure.Structure method)</a>
</li>
</ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.get_ordered_by_indx_set_of_parents">get_ordered_by_indx_set_of_parents() (network_graph.NetworkGraph method)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.get_parents_by_id">get_parents_by_id() (network_graph.NetworkGraph method)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.get_positional_node_indx">get_positional_node_indx() (network_graph.NetworkGraph method)</a>
<ul>
<li><a href="rst/structure.html#structure.Structure.get_positional_node_indx">(structure.Structure method)</a>
</li>
</ul></li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.get_states_number">get_states_number() (network_graph.NetworkGraph method)</a>
<ul>
<li><a href="rst/structure.html#structure.Structure.get_states_number">(structure.Structure method)</a>
</li>
</ul></li>
</ul></td>
</tr></table>
<h2 id="I">I</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.import_data">import_data() (abstract_importer.AbstractImporter method)</a>
<ul>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.import_data">(json_importer.JsonImporter method)</a>
</li>
</ul></li>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.import_sampled_cims">import_sampled_cims() (json_importer.JsonImporter method)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.import_structure">import_structure() (json_importer.JsonImporter method)</a>
</li>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.import_trajectories">import_trajectories() (json_importer.JsonImporter method)</a>
</li>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.import_variables">import_variables() (json_importer.JsonImporter method)</a>
</li>
<li><a href="rst/structure_estimator.html#structure_estimator.StructureEstimator.independence_test">independence_test() (structure_estimator.StructureEstimator method)</a>
</li>
</ul></td>
</tr></table>
<h2 id="J">J</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li>
json_importer
<ul>
<li><a href="rst/json_importer.html#module-json_importer">module</a>
</li>
</ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/json_importer.html#json_importer.JsonImporter">JsonImporter (class in json_importer)</a>
</li>
</ul></td>
</tr></table>
<h2 id="M">M</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li>
module
<ul>
<li><a href="rst/abstract_importer.html#module-abstract_importer">abstract_importer</a>
</li>
<li><a href="rst/cache.html#module-cache">cache</a>
</li>
<li><a href="rst/conditional_intensity_matrix.html#module-conditional_intensity_matrix">conditional_intensity_matrix</a>
</li>
<li><a href="rst/json_importer.html#module-json_importer">json_importer</a>
</li>
<li><a href="rst/network_graph.html#module-network_graph">network_graph</a>
</li>
<li><a href="rst/parameters_estimator.html#module-parameters_estimator">parameters_estimator</a>
</li>
<li><a href="rst/sample_path.html#module-sample_path">sample_path</a>
</li>
<li><a href="rst/set_of_cims.html#module-set_of_cims">set_of_cims</a>
</li>
<li><a href="rst/structure.html#module-structure">structure</a>
</li>
<li><a href="rst/structure_estimator.html#module-structure_estimator">structure_estimator</a>
</li>
<li><a href="rst/trajectory.html#module-trajectory">trajectory</a>
</li>
</ul></li>
</ul></td>
</tr></table>
<h2 id="N">N</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li>
network_graph
<ul>
<li><a href="rst/network_graph.html#module-network_graph">module</a>
</li>
</ul></li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph">NetworkGraph (class in network_graph)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.nodes">nodes() (network_graph.NetworkGraph property)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.nodes_indexes">nodes_indexes() (network_graph.NetworkGraph property)</a>
<ul>
<li><a href="rst/structure.html#structure.Structure.nodes_indexes">(structure.Structure property)</a>
</li>
</ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/structure.html#structure.Structure.nodes_labels">nodes_labels() (structure.Structure property)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.nodes_values">nodes_values() (network_graph.NetworkGraph property)</a>
<ul>
<li><a href="rst/structure.html#structure.Structure.nodes_values">(structure.Structure property)</a>
</li>
</ul></li>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.normalize_trajectories">normalize_trajectories() (json_importer.JsonImporter method)</a>
</li>
</ul></td>
</tr></table>
<h2 id="O">O</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/structure_estimator.html#structure_estimator.StructureEstimator.one_iteration_of_CTPC_algorithm">one_iteration_of_CTPC_algorithm() (structure_estimator.StructureEstimator method)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.one_level_normalizing">one_level_normalizing() (json_importer.JsonImporter method)</a>
</li>
</ul></td>
</tr></table>
<h2 id="P">P</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.p_combs">p_combs() (network_graph.NetworkGraph property)</a>
<ul>
<li><a href="rst/set_of_cims.html#set_of_cims.SetOfCims.p_combs">(set_of_cims.SetOfCims property)</a>
</li>
</ul></li>
<li>
parameters_estimator
<ul>
<li><a href="rst/parameters_estimator.html#module-parameters_estimator">module</a>
</li>
</ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/parameters_estimator.html#parameters_estimator.ParametersEstimator">ParametersEstimator (class in parameters_estimator)</a>
</li>
<li><a href="rst/cache.html#cache.Cache.put">put() (cache.Cache method)</a>
</li>
</ul></td>
</tr></table>
<h2 id="R">R</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/json_importer.html#json_importer.JsonImporter.read_json_file">read_json_file() (json_importer.JsonImporter method)</a>
</li>
</ul></td>
</tr></table>
<h2 id="S">S</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li>
sample_path
<ul>
<li><a href="rst/sample_path.html#module-sample_path">module</a>
</li>
</ul></li>
<li><a href="rst/sample_path.html#sample_path.SamplePath">SamplePath (class in sample_path)</a>
</li>
<li><a href="rst/structure_estimator.html#structure_estimator.StructureEstimator.save_results">save_results() (structure_estimator.StructureEstimator method)</a>
</li>
<li>
set_of_cims
<ul>
<li><a href="rst/set_of_cims.html#module-set_of_cims">module</a>
</li>
</ul></li>
<li><a href="rst/set_of_cims.html#set_of_cims.SetOfCims">SetOfCims (class in set_of_cims)</a>
</li>
<li><a href="rst/trajectory.html#trajectory.Trajectory.size">size() (trajectory.Trajectory method)</a>
</li>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.sorter">sorter() (abstract_importer.AbstractImporter property)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/conditional_intensity_matrix.html#conditional_intensity_matrix.ConditionalIntensityMatrix.state_residence_times">state_residence_times() (conditional_intensity_matrix.ConditionalIntensityMatrix property)</a>
</li>
<li><a href="rst/conditional_intensity_matrix.html#conditional_intensity_matrix.ConditionalIntensityMatrix.state_transition_matrix">state_transition_matrix() (conditional_intensity_matrix.ConditionalIntensityMatrix property)</a>
</li>
<li>
structure
<ul>
<li><a href="rst/structure.html#module-structure">module</a>
</li>
</ul></li>
<li><a href="rst/structure.html#structure.Structure">Structure (class in structure)</a>
</li>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.structure">structure() (abstract_importer.AbstractImporter property)</a>
<ul>
<li><a href="rst/sample_path.html#sample_path.SamplePath.structure">(sample_path.SamplePath property)</a>
</li>
</ul></li>
<li>
structure_estimator
<ul>
<li><a href="rst/structure_estimator.html#module-structure_estimator">module</a>
</li>
</ul></li>
<li><a href="rst/structure_estimator.html#structure_estimator.StructureEstimator">StructureEstimator (class in structure_estimator)</a>
</li>
</ul></td>
</tr></table>
<h2 id="T">T</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.time_filtering">time_filtering() (network_graph.NetworkGraph property)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.time_scalar_indexing_strucure">time_scalar_indexing_strucure() (network_graph.NetworkGraph property)</a>
</li>
<li><a href="rst/trajectory.html#trajectory.Trajectory.times">times() (trajectory.Trajectory property)</a>
</li>
<li><a href="rst/sample_path.html#sample_path.SamplePath.total_variables_count">total_variables_count() (sample_path.SamplePath property)</a>
</li>
<li><a href="rst/structure.html#structure.Structure.total_variables_number">total_variables_number() (structure.Structure property)</a>
</li>
<li><a href="rst/sample_path.html#sample_path.SamplePath.trajectories">trajectories() (sample_path.SamplePath property)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li>
trajectory
<ul>
<li><a href="rst/trajectory.html#module-trajectory">module</a>
</li>
</ul></li>
<li><a href="rst/trajectory.html#trajectory.Trajectory">Trajectory (class in trajectory)</a>
</li>
<li><a href="rst/trajectory.html#trajectory.Trajectory.trajectory">trajectory() (trajectory.Trajectory property)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.transition_filtering">transition_filtering() (network_graph.NetworkGraph property)</a>
</li>
<li><a href="rst/network_graph.html#network_graph.NetworkGraph.transition_scalar_indexing_structure">transition_scalar_indexing_structure() (network_graph.NetworkGraph property)</a>
</li>
</ul></td>
</tr></table>
<h2 id="V">V</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="rst/abstract_importer.html#abstract_importer.AbstractImporter.variables">variables() (abstract_importer.AbstractImporter property)</a>
</li>
</ul></td>
</tr></table>
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<div class="section" id="module-abstract_importer">
<span id="abstract-importer-module"></span><h1>abstract_importer module<a class="headerlink" href="#module-abstract_importer" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="abstract_importer.AbstractImporter">
<em class="property">class </em><code class="sig-prename descclassname">abstract_importer.</code><code class="sig-name descname">AbstractImporter</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">file_path</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span><a class="headerlink" href="#abstract_importer.AbstractImporter" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">abc.ABC</span></code></p>
<p>Abstract class that exposes all the necessary methods to process the trajectories and the net structure.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>file_path</strong> (<em>str</em>) – the file path</p>
</dd>
<dt class="field-even">_concatenated_samples</dt>
<dd class="field-even"><p>Dataframe containing the concatenation of all the processed trajectories</p>
</dd>
<dt class="field-odd">_df_structure</dt>
<dd class="field-odd"><p>Dataframe containing the structure of the network (edges)</p>
</dd>
<dt class="field-even">_df_variables</dt>
<dd class="field-even"><p>Dataframe containing the nodes cardinalities</p>
</dd>
<dt class="field-odd">_sorter</dt>
<dd class="field-odd"><p>A list containing the columns header (excluding the time column) of the <cite>_concatenated_samples</cite></p>
</dd>
</dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.build_list_of_samples_array">
<code class="sig-name descname">build_list_of_samples_array</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data_frame</span><span class="p">:</span> <span class="n">pandas.core.frame.DataFrame</span></em><span class="sig-paren">)</span> &#x2192; List<a class="headerlink" href="#abstract_importer.AbstractImporter.build_list_of_samples_array" title="Permalink to this definition"></a></dt>
<dd><p>Builds a List containing the columns of data_frame and converts them to a numpy array.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>data_frame</strong> (<em>pandas.Dataframe</em>) – the dataframe from which the columns have to be extracted and converted</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the resulting list of numpy arrays</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>List</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.build_sorter">
<em class="property">abstract </em><code class="sig-name descname">build_sorter</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">sample_frame</span><span class="p">:</span> <span class="n">pandas.core.frame.DataFrame</span></em><span class="sig-paren">)</span> &#x2192; List<a class="headerlink" href="#abstract_importer.AbstractImporter.build_sorter" title="Permalink to this definition"></a></dt>
<dd><p>Initializes the <code class="docutils literal notranslate"><span class="pre">_sorter</span></code> class member from a trajectory dataframe, exctracting the header of the frame
and keeping ONLY the variables symbolic labels, cutting out the time label in the header.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sample_frame</strong> (<em>pandas.DataFrame</em>) – The dataframe from which extract the header</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>A list containing the processed header.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>List</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.clear_concatenated_frame">
<code class="sig-name descname">clear_concatenated_frame</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#abstract_importer.AbstractImporter.clear_concatenated_frame" title="Permalink to this definition"></a></dt>
<dd><p>Removes all values in the dataframe concatenated_samples.</p>
</dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.compute_row_delta_in_all_samples_frames">
<code class="sig-name descname">compute_row_delta_in_all_samples_frames</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">df_samples_list</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#abstract_importer.AbstractImporter.compute_row_delta_in_all_samples_frames" title="Permalink to this definition"></a></dt>
<dd><p>Calls the method <code class="docutils literal notranslate"><span class="pre">compute_row_delta_sigle_samples_frame</span></code> on every dataframe present in the list
<code class="docutils literal notranslate"><span class="pre">df_samples_list</span></code>.
Concatenates the result in the dataframe <code class="docutils literal notranslate"><span class="pre">concatanated_samples</span></code></p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>df_samples_list</strong> (<em>List</em>) – the datframe’s list to be processed and concatenated</p>
</dd>
</dl>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>The Dataframe sample_frame has to follow the column structure of this header:
Header of sample_frame = [Time | Variable values]
The class member self._sorter HAS to be properly INITIALIZED (See class members definition doc)</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>After the call of this method the class member <code class="docutils literal notranslate"><span class="pre">concatanated_samples</span></code> will contain all processed
and merged trajectories</p>
</div>
</dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.compute_row_delta_sigle_samples_frame">
<code class="sig-name descname">compute_row_delta_sigle_samples_frame</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">sample_frame</span><span class="p">:</span> <span class="n">pandas.core.frame.DataFrame</span></em>, <em class="sig-param"><span class="n">columns_header</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">shifted_cols_header</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; pandas.core.frame.DataFrame<a class="headerlink" href="#abstract_importer.AbstractImporter.compute_row_delta_sigle_samples_frame" title="Permalink to this definition"></a></dt>
<dd><p>Computes the difference between each value present in th time column.
Copies and shift by one position up all the values present in the remaining columns.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>sample_frame</strong> (<em>pandas.Dataframe</em>) – the traj to be processed</p></li>
<li><p><strong>columns_header</strong> (<em>List</em>) – the original header of sample_frame</p></li>
<li><p><strong>shifted_cols_header</strong> (<em>List</em>) – a copy of columns_header with changed names of the contents</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>The processed dataframe</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>pandas.Dataframe</p>
</dd>
</dl>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>the Dataframe <code class="docutils literal notranslate"><span class="pre">sample_frame</span></code> has to follow the column structure of this header:
Header of sample_frame = [Time | Variable values]</p>
</div>
</dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.concatenated_samples">
<em class="property">property </em><code class="sig-name descname">concatenated_samples</code><a class="headerlink" href="#abstract_importer.AbstractImporter.concatenated_samples" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.dataset_id">
<em class="property">abstract </em><code class="sig-name descname">dataset_id</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; object<a class="headerlink" href="#abstract_importer.AbstractImporter.dataset_id" title="Permalink to this definition"></a></dt>
<dd><p>If the original dataset contains multiple dataset, this method returns a unique id to identify the current
dataset</p>
</dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.file_path">
<em class="property">property </em><code class="sig-name descname">file_path</code><a class="headerlink" href="#abstract_importer.AbstractImporter.file_path" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.import_data">
<em class="property">abstract </em><code class="sig-name descname">import_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#abstract_importer.AbstractImporter.import_data" title="Permalink to this definition"></a></dt>
<dd><p>Imports all the trajectories, variables cardinalities, and net edges.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>The class members <code class="docutils literal notranslate"><span class="pre">_df_variables</span></code> and <code class="docutils literal notranslate"><span class="pre">_df_structure</span></code> HAVE to be properly constructed
as Pandas Dataframes with the following structure:
Header of _df_structure = [From_Node | To_Node]
Header of _df_variables = [Variable_Label | Variable_Cardinality]</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>See :class:<code class="docutils literal notranslate"><span class="pre">JsonImporter</span></code> for an example of implementation of this method.</p>
</div>
</dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.sorter">
<em class="property">property </em><code class="sig-name descname">sorter</code><a class="headerlink" href="#abstract_importer.AbstractImporter.sorter" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.structure">
<em class="property">property </em><code class="sig-name descname">structure</code><a class="headerlink" href="#abstract_importer.AbstractImporter.structure" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="abstract_importer.AbstractImporter.variables">
<em class="property">property </em><code class="sig-name descname">variables</code><a class="headerlink" href="#abstract_importer.AbstractImporter.variables" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<div class="section" id="module-cache">
<span id="cache-module"></span><h1>cache module<a class="headerlink" href="#module-cache" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="cache.Cache">
<em class="property">class </em><code class="sig-prename descclassname">cache.</code><code class="sig-name descname">Cache</code><a class="headerlink" href="#cache.Cache" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>This class acts as a cache of <code class="docutils literal notranslate"><span class="pre">SetOfCims</span></code> objects for a node.</p>
<dl class="field-list simple">
<dt class="field-odd">_list_of_sets_of_parents</dt>
<dd class="field-odd"><p>a list of <code class="docutils literal notranslate"><span class="pre">Sets</span></code> objects of the parents to which the cim in cache at SAME
index is related</p>
</dd>
<dt class="field-even">_actual_cache</dt>
<dd class="field-even"><p>a list of setOfCims objects</p>
</dd>
</dl>
<dl class="py method">
<dt id="cache.Cache.clear">
<code class="sig-name descname">clear</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#cache.Cache.clear" title="Permalink to this definition"></a></dt>
<dd><p>Clear the contents both of <code class="docutils literal notranslate"><span class="pre">_actual_cache</span></code> and <code class="docutils literal notranslate"><span class="pre">_list_of_sets_of_parents</span></code>.</p>
</dd></dl>
<dl class="py method">
<dt id="cache.Cache.find">
<code class="sig-name descname">find</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">parents_comb</span><span class="p">:</span> <span class="n">Set</span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="set_of_cims.html#set_of_cims.SetOfCims" title="set_of_cims.SetOfCims">set_of_cims.SetOfCims</a><a class="headerlink" href="#cache.Cache.find" title="Permalink to this definition"></a></dt>
<dd><p>Tries to find in cache given the symbolic parents combination <code class="docutils literal notranslate"><span class="pre">parents_comb</span></code> the <code class="docutils literal notranslate"><span class="pre">SetOfCims</span></code>
related to that <code class="docutils literal notranslate"><span class="pre">parents_comb</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>parents_comb</strong> (<em>Set</em>) – the parents related to that <code class="docutils literal notranslate"><span class="pre">SetOfCims</span></code></p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>A <code class="docutils literal notranslate"><span class="pre">SetOfCims</span></code> object if the <code class="docutils literal notranslate"><span class="pre">parents_comb</span></code> index is found in <code class="docutils literal notranslate"><span class="pre">_list_of_sets_of_parents</span></code>.
None otherwise.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference internal" href="set_of_cims.html#set_of_cims.SetOfCims" title="set_of_cims.SetOfCims">SetOfCims</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="cache.Cache.put">
<code class="sig-name descname">put</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">parents_comb</span><span class="p">:</span> <span class="n">Set</span></em>, <em class="sig-param"><span class="n">socim</span><span class="p">:</span> <span class="n"><a class="reference internal" href="set_of_cims.html#set_of_cims.SetOfCims" title="set_of_cims.SetOfCims">set_of_cims.SetOfCims</a></span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#cache.Cache.put" title="Permalink to this definition"></a></dt>
<dd><p>Place in cache the <code class="docutils literal notranslate"><span class="pre">SetOfCims</span></code> object, and the related symbolic index <code class="docutils literal notranslate"><span class="pre">parents_comb</span></code> in
<code class="docutils literal notranslate"><span class="pre">_list_of_sets_of_parents</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>parents_comb</strong> (<em>Set</em>) – the symbolic set index</p></li>
<li><p><strong>socim</strong> (<a class="reference internal" href="set_of_cims.html#set_of_cims.SetOfCims" title="set_of_cims.SetOfCims"><em>SetOfCims</em></a>) – the related SetOfCims object</p></li>
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<div class="section" id="module-conditional_intensity_matrix">
<span id="conditional-intensity-matrix-module"></span><h1>conditional_intensity_matrix module<a class="headerlink" href="#module-conditional_intensity_matrix" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="conditional_intensity_matrix.ConditionalIntensityMatrix">
<em class="property">class </em><code class="sig-prename descclassname">conditional_intensity_matrix.</code><code class="sig-name descname">ConditionalIntensityMatrix</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">state_residence_times</span><span class="p">:</span> <span class="n">numpy.array</span></em>, <em class="sig-param"><span class="n">state_transition_matrix</span><span class="p">:</span> <span class="n">numpy.array</span></em><span class="sig-paren">)</span><a class="headerlink" href="#conditional_intensity_matrix.ConditionalIntensityMatrix" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Abstracts the Conditional Intesity matrix of a node as aggregation of the state residence times vector
and state transition matrix and the actual CIM matrix.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>state_residence_times</strong> (<em>numpy.array</em>) – state residence times vector</p></li>
<li><p><strong>state_transition_matrix</strong> (<em>numpy.ndArray</em>) – the transitions count matrix</p></li>
</ul>
</dd>
<dt class="field-even">_cim</dt>
<dd class="field-even"><p>the actual cim of the node</p>
</dd>
</dl>
<dl class="py method">
<dt id="conditional_intensity_matrix.ConditionalIntensityMatrix.cim">
<em class="property">property </em><code class="sig-name descname">cim</code><a class="headerlink" href="#conditional_intensity_matrix.ConditionalIntensityMatrix.cim" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="conditional_intensity_matrix.ConditionalIntensityMatrix.compute_cim_coefficients">
<code class="sig-name descname">compute_cim_coefficients</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#conditional_intensity_matrix.ConditionalIntensityMatrix.compute_cim_coefficients" title="Permalink to this definition"></a></dt>
<dd><p>Compute the coefficients of the matrix _cim by using the following equality q_xx’ = M[x, x’] / T[x].
The class member <code class="docutils literal notranslate"><span class="pre">_cim</span></code> will contain the computed cim</p>
</dd></dl>
<dl class="py method">
<dt id="conditional_intensity_matrix.ConditionalIntensityMatrix.state_residence_times">
<em class="property">property </em><code class="sig-name descname">state_residence_times</code><a class="headerlink" href="#conditional_intensity_matrix.ConditionalIntensityMatrix.state_residence_times" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="conditional_intensity_matrix.ConditionalIntensityMatrix.state_transition_matrix">
<em class="property">property </em><code class="sig-name descname">state_transition_matrix</code><a class="headerlink" href="#conditional_intensity_matrix.ConditionalIntensityMatrix.state_transition_matrix" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<div class="section" id="module-json_importer">
<span id="json-importer-module"></span><h1>json_importer module<a class="headerlink" href="#module-json_importer" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="json_importer.JsonImporter">
<em class="property">class </em><code class="sig-prename descclassname">json_importer.</code><code class="sig-name descname">JsonImporter</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">file_path</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">samples_label</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">structure_label</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">variables_label</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">time_key</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">variables_key</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">array_indx</span><span class="p">:</span> <span class="n">int</span></em><span class="sig-paren">)</span><a class="headerlink" href="#json_importer.JsonImporter" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="abstract_importer.html#abstract_importer.AbstractImporter" title="abstract_importer.AbstractImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">abstract_importer.AbstractImporter</span></code></a></p>
<p>Implements the abstracts methods of AbstractImporter and adds all the necessary methods to process and prepare the data in json ext.
with the following structure:
[0]</p>
<blockquote>
<div><p><a href="#id1"><span class="problematic" id="id2">|</span></a>_ dyn.cims
<a href="#id3"><span class="problematic" id="id4">|</span></a>_ dyn.str
<a href="#id5"><span class="problematic" id="id6">|</span></a>_ samples
<a href="#id7"><span class="problematic" id="id8">|</span></a>_ variabels</p>
</div></blockquote>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>file_path</strong> (<em>string</em>) – the path of the file that contains tha data to be imported</p></li>
<li><p><strong>samples_label</strong> (<em>string</em>) – the reference key for the samples in the trajectories</p></li>
<li><p><strong>structure_label</strong> (<em>string</em>) – the reference key for the structure of the network data</p></li>
<li><p><strong>variables_label</strong> (<em>string</em>) – the reference key for the cardinalites of the nodes data</p></li>
<li><p><strong>time_key</strong> (<em>string</em>) – the key used to identify the timestamps in each trajectory</p></li>
<li><p><strong>variables_key</strong> (<em>string</em>) – the key used to identify the names of the variables in the net</p></li>
<li><p><strong>array_indx</strong> (<em>int</em>) – the index of the outer JsonArray to exctract the data from</p></li>
</ul>
</dd>
<dt class="field-even">_df_samples_list</dt>
<dd class="field-even"><p>a Dataframe list in which every dataframe contains a trajectory</p>
</dd>
</dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.build_sorter">
<code class="sig-name descname">build_sorter</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">sample_frame</span><span class="p">:</span> <span class="n">pandas.core.frame.DataFrame</span></em><span class="sig-paren">)</span> &#x2192; List<a class="headerlink" href="#json_importer.JsonImporter.build_sorter" title="Permalink to this definition"></a></dt>
<dd><p>Implements the abstract method build_sorter of the <code class="xref py py-class docutils literal notranslate"><span class="pre">AbstractImporter</span></code> for this dataset</p>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.clear_data_frame_list">
<code class="sig-name descname">clear_data_frame_list</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#json_importer.JsonImporter.clear_data_frame_list" title="Permalink to this definition"></a></dt>
<dd><p>Removes all values present in the dataframes in the list <code class="docutils literal notranslate"><span class="pre">_df_samples_list</span></code>.</p>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.dataset_id">
<code class="sig-name descname">dataset_id</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; object<a class="headerlink" href="#json_importer.JsonImporter.dataset_id" title="Permalink to this definition"></a></dt>
<dd><p>If the original dataset contains multiple dataset, this method returns a unique id to identify the current
dataset</p>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.import_data">
<code class="sig-name descname">import_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#json_importer.JsonImporter.import_data" title="Permalink to this definition"></a></dt>
<dd><p>Implements the abstract method of <code class="xref py py-class docutils literal notranslate"><span class="pre">AbstractImporter</span></code></p>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.import_sampled_cims">
<code class="sig-name descname">import_sampled_cims</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">raw_data</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">indx</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">cims_key</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; Dict<a class="headerlink" href="#json_importer.JsonImporter.import_sampled_cims" title="Permalink to this definition"></a></dt>
<dd><p>Imports the synthetic CIMS in the dataset in a dictionary, using variables labels
as keys for the set of CIMS of a particular node.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>raw_data</strong> (<em>List</em>) – List of Dicts</p></li>
<li><p><strong>indx</strong> (<em>int</em>) – The index of the array from which the data have to be extracted</p></li>
<li><p><strong>cims_key</strong> (<em>string</em>) – the key where the json object cims are placed</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a dictionary containing the sampled CIMS for all the variables in the net</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Dictionary</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.import_structure">
<code class="sig-name descname">import_structure</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">raw_data</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; pandas.core.frame.DataFrame<a class="headerlink" href="#json_importer.JsonImporter.import_structure" title="Permalink to this definition"></a></dt>
<dd><p>Imports in a dataframe the data in the list raw_data at the key <code class="docutils literal notranslate"><span class="pre">_structure_label</span></code></p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>raw_data</strong> (<em>List</em>) – List of Dicts</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Dataframe containg the starting node a ending node of every arc of the network</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>pandas.Dataframe</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.import_trajectories">
<code class="sig-name descname">import_trajectories</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">raw_data</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; List<a class="headerlink" href="#json_importer.JsonImporter.import_trajectories" title="Permalink to this definition"></a></dt>
<dd><p>Imports the trajectories from the list of dicts <code class="docutils literal notranslate"><span class="pre">raw_data</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>raw_data</strong> (<em>List</em>) – List of Dicts</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>List of dataframes containing all the trajectories</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>List</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.import_variables">
<code class="sig-name descname">import_variables</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">raw_data</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; pandas.core.frame.DataFrame<a class="headerlink" href="#json_importer.JsonImporter.import_variables" title="Permalink to this definition"></a></dt>
<dd><p>Imports the data in <code class="docutils literal notranslate"><span class="pre">raw_data</span></code> at the key <code class="docutils literal notranslate"><span class="pre">_variables_label</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>raw_data</strong> (<em>List</em>) – List of Dicts</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Datframe containg the variables simbolic labels and their cardinalities</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>pandas.Dataframe</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.normalize_trajectories">
<code class="sig-name descname">normalize_trajectories</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">raw_data</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">indx</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">trajectories_key</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; List<a class="headerlink" href="#json_importer.JsonImporter.normalize_trajectories" title="Permalink to this definition"></a></dt>
<dd><p>Extracts the trajectories in <code class="docutils literal notranslate"><span class="pre">raw_data</span></code> at the index <code class="docutils literal notranslate"><span class="pre">index</span></code> at the key <code class="docutils literal notranslate"><span class="pre">trajectories</span> <span class="pre">key</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>raw_data</strong> (<em>List</em>) – List of Dicts</p></li>
<li><p><strong>indx</strong> (<em>int</em>) – The index of the array from which the data have to be extracted</p></li>
<li><p><strong>trajectories_key</strong> (<em>string</em>) – the key of the trajectories objects</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>A list of daframes containg the trajectories</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>List</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.one_level_normalizing">
<code class="sig-name descname">one_level_normalizing</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">raw_data</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">indx</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">key</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; pandas.core.frame.DataFrame<a class="headerlink" href="#json_importer.JsonImporter.one_level_normalizing" title="Permalink to this definition"></a></dt>
<dd><p>Extracts the one-level nested data in the list <code class="docutils literal notranslate"><span class="pre">raw_data</span></code> at the index <code class="docutils literal notranslate"><span class="pre">indx</span></code> at the key <code class="docutils literal notranslate"><span class="pre">key</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>raw_data</strong> (<em>List</em>) – List of Dicts</p></li>
<li><p><strong>indx</strong> (<em>int</em>) – The index of the array from which the data have to be extracted</p></li>
<li><p><strong>key</strong> (<em>string</em>) – the key for the Dicts from which exctract data</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>A normalized dataframe</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>pandas.Datframe</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="json_importer.JsonImporter.read_json_file">
<code class="sig-name descname">read_json_file</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; List<a class="headerlink" href="#json_importer.JsonImporter.read_json_file" title="Permalink to this definition"></a></dt>
<dd><p>Reads the JSON file in the path self.filePath</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>The contents of the json file</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>List</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
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<div class="section" id="module-network_graph">
<span id="network-graph-module"></span><h1>network_graph module<a class="headerlink" href="#module-network_graph" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="network_graph.NetworkGraph">
<em class="property">class </em><code class="sig-prename descclassname">network_graph.</code><code class="sig-name descname">NetworkGraph</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">graph_struct</span><span class="p">:</span> <span class="n"><a class="reference internal" href="structure.html#structure.Structure" title="structure.Structure">structure.Structure</a></span></em><span class="sig-paren">)</span><a class="headerlink" href="#network_graph.NetworkGraph" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Abstracts the infos contained in the Structure class in the form of a directed graph.
Has the task of creating all the necessary filtering and indexing structures for parameters estimation</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>graph_struct</strong> (<a class="reference internal" href="structure.html#structure.Structure" title="structure.Structure"><em>Structure</em></a>) – the <code class="docutils literal notranslate"><span class="pre">Structure</span></code> object from which infos about the net will be extracted</p>
</dd>
<dt class="field-even">_graph</dt>
<dd class="field-even"><p>directed graph</p>
</dd>
<dt class="field-odd">_aggregated_info_about_nodes_parents</dt>
<dd class="field-odd"><p>a structure that contains all the necessary infos
about every parents of the node of which all the indexing and filtering structures will be constructed.</p>
</dd>
<dt class="field-even">_time_scalar_indexing_structure</dt>
<dd class="field-even"><p>the indexing structure for state res time estimation</p>
</dd>
<dt class="field-odd">_transition_scalar_indexing_structure</dt>
<dd class="field-odd"><p>the indexing structure for transition computation</p>
</dd>
<dt class="field-even">_time_filtering</dt>
<dd class="field-even"><p>the columns filtering structure used in the computation of the state res times</p>
</dd>
<dt class="field-odd">_transition_filtering</dt>
<dd class="field-odd"><p>the columns filtering structure used in the computation of the transition
from one state to another</p>
</dd>
<dt class="field-even">_p_combs_structure</dt>
<dd class="field-even"><p>all the possible parents states combination for the node of interest</p>
</dd>
</dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.add_edges">
<code class="sig-name descname">add_edges</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">list_of_edges</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#network_graph.NetworkGraph.add_edges" title="Permalink to this definition"></a></dt>
<dd><p>Add the edges to the <code class="docutils literal notranslate"><span class="pre">_graph</span></code> contained in the list <code class="docutils literal notranslate"><span class="pre">list_of_edges</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>list_of_edges</strong> (<em>List</em>) – the list containing of tuples containing the edges</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.add_nodes">
<code class="sig-name descname">add_nodes</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">list_of_nodes</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#network_graph.NetworkGraph.add_nodes" title="Permalink to this definition"></a></dt>
<dd><p>Adds the nodes to the <code class="docutils literal notranslate"><span class="pre">_graph</span></code> contained in the list of nodes <code class="docutils literal notranslate"><span class="pre">list_of_nodes</span></code>.
Sets all the properties that identify a nodes (index, positional index, cardinality)</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>list_of_nodes</strong> (<em>List</em>) – the nodes to add to <code class="docutils literal notranslate"><span class="pre">_graph</span></code></p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.build_p_comb_structure_for_a_node">
<code class="sig-name descname">build_p_comb_structure_for_a_node</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">parents_values</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; numpy.ndarray<a class="headerlink" href="#network_graph.NetworkGraph.build_p_comb_structure_for_a_node" title="Permalink to this definition"></a></dt>
<dd><p>Builds the combinatorial structure that contains the combinations of all the values contained in
<code class="docutils literal notranslate"><span class="pre">parents_values</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>parents_values</strong> (<em>List</em>) – the cardinalities of the nodes</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>A numpy matrix containing a grid of the combinations</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>numpy.ndArray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.build_time_columns_filtering_for_a_node">
<code class="sig-name descname">build_time_columns_filtering_for_a_node</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_indx</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">p_indxs</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; numpy.ndarray<a class="headerlink" href="#network_graph.NetworkGraph.build_time_columns_filtering_for_a_node" title="Permalink to this definition"></a></dt>
<dd><p>Builds the necessary structure to filter the desired columns indicated by <code class="docutils literal notranslate"><span class="pre">node_indx</span></code> and <code class="docutils literal notranslate"><span class="pre">p_indxs</span></code>
in the dataset.
This structute will be used in the computation of the state res times.
:param node_indx: the index of the node
:type node_indx: int
:param p_indxs: the indexes of the node’s parents
:type p_indxs: List
:return: The filtering structure for times estimation
:rtype: numpy.ndArray</p>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.build_time_scalar_indexing_structure_for_a_node">
<code class="sig-name descname">build_time_scalar_indexing_structure_for_a_node</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">parents_vals</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; numpy.ndarray<a class="headerlink" href="#network_graph.NetworkGraph.build_time_scalar_indexing_structure_for_a_node" title="Permalink to this definition"></a></dt>
<dd><p>Builds an indexing structure for the computation of state residence times values.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>node_id</strong> (<em>string</em>) – the node label</p></li>
<li><p><strong>parents_vals</strong> (<em>List</em>) – the caridinalites of the node’s parents</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>The time indexing structure</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>numpy.ndArray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.build_transition_filtering_for_a_node">
<code class="sig-name descname">build_transition_filtering_for_a_node</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_indx</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">p_indxs</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; numpy.ndarray<a class="headerlink" href="#network_graph.NetworkGraph.build_transition_filtering_for_a_node" title="Permalink to this definition"></a></dt>
<dd><p>Builds the necessary structure to filter the desired columns indicated by <code class="docutils literal notranslate"><span class="pre">node_indx</span></code> and <code class="docutils literal notranslate"><span class="pre">p_indxs</span></code>
in the dataset.
This structure will be used in the computation of the state transitions values.
:param node_indx: the index of the node
:type node_indx: int
:param p_indxs: the indexes of the node’s parents
:type p_indxs: List
:return: The filtering structure for transitions estimation
:rtype: numpy.ndArray</p>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.build_transition_scalar_indexing_structure_for_a_node">
<code class="sig-name descname">build_transition_scalar_indexing_structure_for_a_node</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">parents_vals</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; numpy.ndarray<a class="headerlink" href="#network_graph.NetworkGraph.build_transition_scalar_indexing_structure_for_a_node" title="Permalink to this definition"></a></dt>
<dd><p>Builds an indexing structure for the computation of state transitions values.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>node_id</strong> (<em>string</em>) – the node label</p></li>
<li><p><strong>parents_vals</strong> (<em>List</em>) – the caridinalites of the node’s parents</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>The transition indexing structure</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>numpy.ndArray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.edges">
<em class="property">property </em><code class="sig-name descname">edges</code><a class="headerlink" href="#network_graph.NetworkGraph.edges" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.fast_init">
<code class="sig-name descname">fast_init</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#network_graph.NetworkGraph.fast_init" title="Permalink to this definition"></a></dt>
<dd><p>Initializes all the necessary structures for parameters estimation of the node identified by the label
node_id</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>node_id</strong> (<em>string</em>) – the label of the node</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.get_node_indx">
<code class="sig-name descname">get_node_indx</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span></em><span class="sig-paren">)</span> &#x2192; int<a class="headerlink" href="#network_graph.NetworkGraph.get_node_indx" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.get_ordered_by_indx_set_of_parents">
<code class="sig-name descname">get_ordered_by_indx_set_of_parents</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; Tuple<a class="headerlink" href="#network_graph.NetworkGraph.get_ordered_by_indx_set_of_parents" title="Permalink to this definition"></a></dt>
<dd><p>Builds the aggregated structure that holds all the infos relative to the parent set of the node, namely
(parents_labels, parents_indexes, parents_cardinalities).</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>node</strong> (<em>string</em>) – the label of the node</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a tuple containing all the parent set infos</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Tuple</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.get_parents_by_id">
<code class="sig-name descname">get_parents_by_id</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span></em><span class="sig-paren">)</span> &#x2192; List<a class="headerlink" href="#network_graph.NetworkGraph.get_parents_by_id" title="Permalink to this definition"></a></dt>
<dd><p>Returns a list of labels of the parents of the node <code class="docutils literal notranslate"><span class="pre">node_id</span></code></p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>node_id</strong> (<em>string</em>) – the node label</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a List of labels of the parents</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>List</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.get_positional_node_indx">
<code class="sig-name descname">get_positional_node_indx</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span></em><span class="sig-paren">)</span> &#x2192; int<a class="headerlink" href="#network_graph.NetworkGraph.get_positional_node_indx" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.get_states_number">
<code class="sig-name descname">get_states_number</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span></em><span class="sig-paren">)</span> &#x2192; int<a class="headerlink" href="#network_graph.NetworkGraph.get_states_number" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.nodes">
<em class="property">property </em><code class="sig-name descname">nodes</code><a class="headerlink" href="#network_graph.NetworkGraph.nodes" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.nodes_indexes">
<em class="property">property </em><code class="sig-name descname">nodes_indexes</code><a class="headerlink" href="#network_graph.NetworkGraph.nodes_indexes" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.nodes_values">
<em class="property">property </em><code class="sig-name descname">nodes_values</code><a class="headerlink" href="#network_graph.NetworkGraph.nodes_values" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.p_combs">
<em class="property">property </em><code class="sig-name descname">p_combs</code><a class="headerlink" href="#network_graph.NetworkGraph.p_combs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.time_filtering">
<em class="property">property </em><code class="sig-name descname">time_filtering</code><a class="headerlink" href="#network_graph.NetworkGraph.time_filtering" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.time_scalar_indexing_strucure">
<em class="property">property </em><code class="sig-name descname">time_scalar_indexing_strucure</code><a class="headerlink" href="#network_graph.NetworkGraph.time_scalar_indexing_strucure" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.transition_filtering">
<em class="property">property </em><code class="sig-name descname">transition_filtering</code><a class="headerlink" href="#network_graph.NetworkGraph.transition_filtering" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="network_graph.NetworkGraph.transition_scalar_indexing_structure">
<em class="property">property </em><code class="sig-name descname">transition_scalar_indexing_structure</code><a class="headerlink" href="#network_graph.NetworkGraph.transition_scalar_indexing_structure" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
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<div class="section" id="module-parameters_estimator">
<span id="parameters-estimator-module"></span><h1>parameters_estimator module<a class="headerlink" href="#module-parameters_estimator" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="parameters_estimator.ParametersEstimator">
<em class="property">class </em><code class="sig-prename descclassname">parameters_estimator.</code><code class="sig-name descname">ParametersEstimator</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">trajectories</span><span class="p">:</span> <span class="n"><a class="reference internal" href="trajectory.html#trajectory.Trajectory" title="trajectory.Trajectory">trajectory.Trajectory</a></span></em>, <em class="sig-param"><span class="n">net_graph</span><span class="p">:</span> <span class="n"><a class="reference internal" href="network_graph.html#network_graph.NetworkGraph" title="network_graph.NetworkGraph">network_graph.NetworkGraph</a></span></em><span class="sig-paren">)</span><a class="headerlink" href="#parameters_estimator.ParametersEstimator" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Has the task of computing the cims of particular node given the trajectories and the net structure
in the graph <code class="docutils literal notranslate"><span class="pre">_net_graph</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>trajectories</strong> (<a class="reference internal" href="trajectory.html#trajectory.Trajectory" title="trajectory.Trajectory"><em>Trajectory</em></a>) – the trajectories</p></li>
<li><p><strong>net_graph</strong> (<a class="reference internal" href="network_graph.html#network_graph.NetworkGraph" title="network_graph.NetworkGraph"><em>NetworkGraph</em></a>) – the net structure</p></li>
</ul>
</dd>
<dt class="field-even">_single_set_of_cims</dt>
<dd class="field-even"><p>the set of cims object that will hold the cims of the node</p>
</dd>
</dl>
<dl class="py method">
<dt id="parameters_estimator.ParametersEstimator.compute_parameters_for_node">
<code class="sig-name descname">compute_parameters_for_node</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="set_of_cims.html#set_of_cims.SetOfCims" title="set_of_cims.SetOfCims">set_of_cims.SetOfCims</a><a class="headerlink" href="#parameters_estimator.ParametersEstimator.compute_parameters_for_node" title="Permalink to this definition"></a></dt>
<dd><p>Compute the CIMS of the node identified by the label <code class="docutils literal notranslate"><span class="pre">node_id</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>node_id</strong> (<em>string</em>) – the node label</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>A SetOfCims object filled with the computed CIMS</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference internal" href="set_of_cims.html#set_of_cims.SetOfCims" title="set_of_cims.SetOfCims">SetOfCims</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="parameters_estimator.ParametersEstimator.compute_state_res_time_for_node">
<code class="sig-name descname">compute_state_res_time_for_node</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_indx</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">times</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">trajectory</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">cols_filter</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">scalar_indexes_struct</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">T</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#parameters_estimator.ParametersEstimator.compute_state_res_time_for_node" title="Permalink to this definition"></a></dt>
<dd><p>Compute the state residence times for a node and fill the matrix <code class="docutils literal notranslate"><span class="pre">T</span></code> with the results</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>node_indx</strong> (<em>int</em>) – the index of the node</p></li>
<li><p><strong>times</strong> (<em>numpy.array</em>) – the times deltas vector</p></li>
<li><p><strong>trajectory</strong> (<em>numpy.ndArray</em>) – the trajectory</p></li>
<li><p><strong>cols_filter</strong> (<em>numpy.array</em>) – the columns filtering structure</p></li>
<li><p><strong>scalar_indexes_struct</strong> (<em>numpy.array</em>) – the indexing structure</p></li>
<li><p><strong>T</strong> (<em>numpy.ndArray</em>) – the state residence times vectors</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="parameters_estimator.ParametersEstimator.compute_state_transitions_for_a_node">
<code class="sig-name descname">compute_state_transitions_for_a_node</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_indx</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">trajectory</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">cols_filter</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">scalar_indexing</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">M</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em><span class="sig-paren">)</span><a class="headerlink" href="#parameters_estimator.ParametersEstimator.compute_state_transitions_for_a_node" title="Permalink to this definition"></a></dt>
<dd><p>Compute the state residence times for a node and fill the matrices <code class="docutils literal notranslate"><span class="pre">M</span></code> with the results.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>node_indx</strong> (<em>int</em>) – the index of the node</p></li>
<li><p><strong>trajectory</strong> (<em>numpy.ndArray</em>) – the trajectory</p></li>
<li><p><strong>cols_filter</strong> (<em>numpy.array</em>) – the columns filtering structure</p></li>
<li><p><strong>scalar_indexing</strong> (<em>numpy.array</em>) – the indexing structure</p></li>
<li><p><strong>M</strong> (<em>numpy.ndArray</em>) – the state transitions matrices</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="parameters_estimator.ParametersEstimator.fast_init">
<code class="sig-name descname">fast_init</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#parameters_estimator.ParametersEstimator.fast_init" title="Permalink to this definition"></a></dt>
<dd><p>Initializes all the necessary structures for the parameters estimation for the node <code class="docutils literal notranslate"><span class="pre">node_id</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>node_id</strong> (<em>string</em>) – the node label</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
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<div class="section" id="module-sample_path">
<span id="sample-path-module"></span><h1>sample_path module<a class="headerlink" href="#module-sample_path" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="sample_path.SamplePath">
<em class="property">class </em><code class="sig-prename descclassname">sample_path.</code><code class="sig-name descname">SamplePath</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">importer</span><span class="p">:</span> <span class="n"><a class="reference internal" href="abstract_importer.html#abstract_importer.AbstractImporter" title="abstract_importer.AbstractImporter">abstract_importer.AbstractImporter</a></span></em><span class="sig-paren">)</span><a class="headerlink" href="#sample_path.SamplePath" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Aggregates all the informations about the trajectories, the real structure of the sampled net and variables
cardinalites. Has the task of creating the objects <code class="docutils literal notranslate"><span class="pre">Trajectory</span></code> and <code class="docutils literal notranslate"><span class="pre">Structure</span></code> that will
contain the mentioned data.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>importer</strong> (<a class="reference internal" href="abstract_importer.html#abstract_importer.AbstractImporter" title="abstract_importer.AbstractImporter"><em>AbstractImporter</em></a>) – the Importer objects that will import ad process data</p>
</dd>
<dt class="field-even">_trajectories</dt>
<dd class="field-even"><p>the <code class="docutils literal notranslate"><span class="pre">Trajectory</span></code> object that will contain all the concatenated trajectories</p>
</dd>
<dt class="field-odd">_structure</dt>
<dd class="field-odd"><p>the <code class="docutils literal notranslate"><span class="pre">Structure</span></code> Object that will contain all the structurral infos about the net</p>
</dd>
<dt class="field-even">_total_variables_count</dt>
<dd class="field-even"><p>the number of variables in the net</p>
</dd>
</dl>
<dl class="py method">
<dt id="sample_path.SamplePath.build_structure">
<code class="sig-name descname">build_structure</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#sample_path.SamplePath.build_structure" title="Permalink to this definition"></a></dt>
<dd><p>Builds the <code class="docutils literal notranslate"><span class="pre">Structure</span></code> object that aggregates all the infos about the net.</p>
</dd></dl>
<dl class="py method">
<dt id="sample_path.SamplePath.build_trajectories">
<code class="sig-name descname">build_trajectories</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#sample_path.SamplePath.build_trajectories" title="Permalink to this definition"></a></dt>
<dd><p>Builds the Trajectory object that will contain all the trajectories.
Clears all the unused dataframes in <code class="docutils literal notranslate"><span class="pre">_importer</span></code> Object</p>
</dd></dl>
<dl class="py method">
<dt id="sample_path.SamplePath.structure">
<em class="property">property </em><code class="sig-name descname">structure</code><a class="headerlink" href="#sample_path.SamplePath.structure" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="sample_path.SamplePath.total_variables_count">
<em class="property">property </em><code class="sig-name descname">total_variables_count</code><a class="headerlink" href="#sample_path.SamplePath.total_variables_count" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="sample_path.SamplePath.trajectories">
<em class="property">property </em><code class="sig-name descname">trajectories</code><a class="headerlink" href="#sample_path.SamplePath.trajectories" title="Permalink to this definition"></a></dt>
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<div class="section" id="module-set_of_cims">
<span id="set-of-cims-module"></span><h1>set_of_cims module<a class="headerlink" href="#module-set_of_cims" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="set_of_cims.SetOfCims">
<em class="property">class </em><code class="sig-prename descclassname">set_of_cims.</code><code class="sig-name descname">SetOfCims</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">parents_states_number</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">node_states_number</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">p_combs</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em><span class="sig-paren">)</span><a class="headerlink" href="#set_of_cims.SetOfCims" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Aggregates all the CIMS of the node identified by the label _node_id.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>node_id</strong> – the node label</p></li>
<li><p><strong>parents_states_number</strong> (<em>List</em>) – the cardinalities of the parents</p></li>
<li><p><strong>node_states_number</strong> (<em>int</em>) – the caridinality of the node</p></li>
<li><p><strong>p_combs</strong> (<em>numpy.ndArray</em>) – the p_comb structure bound to this node</p></li>
</ul>
</dd>
<dt class="field-even">_state_residence_time</dt>
<dd class="field-even"><p>matrix containing all the state residence time vectors for the node</p>
</dd>
<dt class="field-odd">_transition_matrices</dt>
<dd class="field-odd"><p>matrix containing all the transition matrices for the node</p>
</dd>
<dt class="field-even">_actual_cims</dt>
<dd class="field-even"><p>the cims of the node</p>
</dd>
</dl>
<dl class="py method">
<dt id="set_of_cims.SetOfCims.actual_cims">
<em class="property">property </em><code class="sig-name descname">actual_cims</code><a class="headerlink" href="#set_of_cims.SetOfCims.actual_cims" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="set_of_cims.SetOfCims.build_cims">
<code class="sig-name descname">build_cims</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">state_res_times</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">transition_matrices</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#set_of_cims.SetOfCims.build_cims" title="Permalink to this definition"></a></dt>
<dd><p>Build the <code class="docutils literal notranslate"><span class="pre">ConditionalIntensityMatrix</span></code> objects given the state residence times and transitions matrices.
Compute the cim coefficients.The class member <code class="docutils literal notranslate"><span class="pre">_actual_cims</span></code> will contain the computed cims.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>state_res_times</strong> (<em>numpy.ndArray</em>) – the state residence times matrix</p></li>
<li><p><strong>transition_matrices</strong> (<em>numpy.ndArray</em>) – the transition matrices</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="set_of_cims.SetOfCims.build_times_and_transitions_structures">
<code class="sig-name descname">build_times_and_transitions_structures</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#set_of_cims.SetOfCims.build_times_and_transitions_structures" title="Permalink to this definition"></a></dt>
<dd><p>Initializes at the correct dimensions the state residence times matrix and the state transition matrices.</p>
</dd></dl>
<dl class="py method">
<dt id="set_of_cims.SetOfCims.filter_cims_with_mask">
<code class="sig-name descname">filter_cims_with_mask</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">mask_arr</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">comb</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; numpy.ndarray<a class="headerlink" href="#set_of_cims.SetOfCims.filter_cims_with_mask" title="Permalink to this definition"></a></dt>
<dd><p>Filter the cims contained in the array <code class="docutils literal notranslate"><span class="pre">_actual_cims</span></code> given the boolean mask <code class="docutils literal notranslate"><span class="pre">mask_arr</span></code> and the index
<code class="docutils literal notranslate"><span class="pre">comb</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>mask_arr</strong> (<em>numpy.array</em>) – the boolean mask that indicates which parent to consider</p></li>
<li><p><strong>comb</strong> (<em>numpy.array</em>) – the state/s of the filtered parents</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Array of <code class="docutils literal notranslate"><span class="pre">ConditionalIntensityMatrix</span></code> objects</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>numpy.array</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="set_of_cims.SetOfCims.get_cims_number">
<code class="sig-name descname">get_cims_number</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#set_of_cims.SetOfCims.get_cims_number" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="set_of_cims.SetOfCims.p_combs">
<em class="property">property </em><code class="sig-name descname">p_combs</code><a class="headerlink" href="#set_of_cims.SetOfCims.p_combs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
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<div class="section" id="module-structure">
<span id="structure-module"></span><h1>structure module<a class="headerlink" href="#module-structure" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="structure.Structure">
<em class="property">class </em><code class="sig-prename descclassname">structure.</code><code class="sig-name descname">Structure</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">nodes_labels_list</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">nodes_indexes_arr</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">nodes_vals_arr</span><span class="p">:</span> <span class="n">numpy.ndarray</span></em>, <em class="sig-param"><span class="n">edges_list</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">total_variables_number</span><span class="p">:</span> <span class="n">int</span></em><span class="sig-paren">)</span><a class="headerlink" href="#structure.Structure" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Contains all the infos about the network structure(nodes labels, nodes caridinalites, edges, indexes)</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>nodes_labels_list</strong> (<em>List</em>) – the symbolic names of the variables</p></li>
<li><p><strong>nodes_indexes_arr</strong> (<em>numpy.ndArray</em>) – the indexes of the nodes</p></li>
<li><p><strong>nodes_vals_arr</strong> (<em>numpy.ndArray</em>) – the cardinalites of the nodes</p></li>
<li><p><strong>edges_list</strong> (<em>List</em>) – the edges of the network</p></li>
<li><p><strong>total_variables_number</strong> (<em>int</em>) – the total number of variables in the net</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt id="structure.Structure.edges">
<em class="property">property </em><code class="sig-name descname">edges</code><a class="headerlink" href="#structure.Structure.edges" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="structure.Structure.get_node_id">
<code class="sig-name descname">get_node_id</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_indx</span><span class="p">:</span> <span class="n">int</span></em><span class="sig-paren">)</span> &#x2192; str<a class="headerlink" href="#structure.Structure.get_node_id" title="Permalink to this definition"></a></dt>
<dd><p>Given the <code class="docutils literal notranslate"><span class="pre">node_index</span></code> returns the node label.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>node_indx</strong> (<em>int</em>) – the node index</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the node label</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>string</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="structure.Structure.get_node_indx">
<code class="sig-name descname">get_node_indx</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; int<a class="headerlink" href="#structure.Structure.get_node_indx" title="Permalink to this definition"></a></dt>
<dd><p>Given the <code class="docutils literal notranslate"><span class="pre">node_index</span></code> returns the node label.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>node_id</strong> (<em>string</em>) – the node label</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the node index</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>int</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="structure.Structure.get_positional_node_indx">
<code class="sig-name descname">get_positional_node_indx</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_id</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; int<a class="headerlink" href="#structure.Structure.get_positional_node_indx" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="structure.Structure.get_states_number">
<code class="sig-name descname">get_states_number</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; int<a class="headerlink" href="#structure.Structure.get_states_number" title="Permalink to this definition"></a></dt>
<dd><p>Given the node label <code class="docutils literal notranslate"><span class="pre">node</span></code> returns the cardinality of the node.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>node</strong> (<em>string</em>) – the node label</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the node cardinality</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>int</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="structure.Structure.nodes_indexes">
<em class="property">property </em><code class="sig-name descname">nodes_indexes</code><a class="headerlink" href="#structure.Structure.nodes_indexes" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="structure.Structure.nodes_labels">
<em class="property">property </em><code class="sig-name descname">nodes_labels</code><a class="headerlink" href="#structure.Structure.nodes_labels" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="structure.Structure.nodes_values">
<em class="property">property </em><code class="sig-name descname">nodes_values</code><a class="headerlink" href="#structure.Structure.nodes_values" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="structure.Structure.total_variables_number">
<em class="property">property </em><code class="sig-name descname">total_variables_number</code><a class="headerlink" href="#structure.Structure.total_variables_number" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
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<div class="section" id="module-structure_estimator">
<span id="structure-estimator-module"></span><h1>structure_estimator module<a class="headerlink" href="#module-structure_estimator" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="structure_estimator.StructureEstimator">
<em class="property">class </em><code class="sig-prename descclassname">structure_estimator.</code><code class="sig-name descname">StructureEstimator</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">sample_path</span><span class="p">:</span> <span class="n"><a class="reference internal" href="sample_path.html#sample_path.SamplePath" title="sample_path.SamplePath">sample_path.SamplePath</a></span></em>, <em class="sig-param"><span class="n">exp_test_alfa</span><span class="p">:</span> <span class="n">float</span></em>, <em class="sig-param"><span class="n">chi_test_alfa</span><span class="p">:</span> <span class="n">float</span></em><span class="sig-paren">)</span><a class="headerlink" href="#structure_estimator.StructureEstimator" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Has the task of estimating the network structure given the trajectories in <code class="docutils literal notranslate"><span class="pre">samplepath</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>sample_path</strong> (<a class="reference internal" href="sample_path.html#sample_path.SamplePath" title="sample_path.SamplePath"><em>SamplePath</em></a>) – the _sample_path object containing the trajectories and the real structure</p></li>
<li><p><strong>exp_test_alfa</strong> (<em>float</em>) – the significance level for the exponential Hp test</p></li>
<li><p><strong>chi_test_alfa</strong> (<em>float</em>) – the significance level for the chi Hp test</p></li>
</ul>
</dd>
<dt class="field-even">_nodes</dt>
<dd class="field-even"><p>the nodes labels</p>
</dd>
<dt class="field-odd">_nodes_vals</dt>
<dd class="field-odd"><p>the nodes cardinalities</p>
</dd>
<dt class="field-even">_nodes_indxs</dt>
<dd class="field-even"><p>the nodes indexes</p>
</dd>
<dt class="field-odd">_complete_graph</dt>
<dd class="field-odd"><p>the complete directed graph built using the nodes labels in <code class="docutils literal notranslate"><span class="pre">_nodes</span></code></p>
</dd>
<dt class="field-even">_cache</dt>
<dd class="field-even"><p>the Cache object</p>
</dd>
</dl>
<dl class="py method">
<dt id="structure_estimator.StructureEstimator.build_complete_graph">
<code class="sig-name descname">build_complete_graph</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">node_ids</span><span class="p">:</span> <span class="n">List</span></em><span class="sig-paren">)</span> &#x2192; networkx.classes.digraph.DiGraph<a class="headerlink" href="#structure_estimator.StructureEstimator.build_complete_graph" title="Permalink to this definition"></a></dt>
<dd><p>Builds a complete directed graph (no self loops) given the nodes labels in the list <code class="docutils literal notranslate"><span class="pre">node_ids</span></code>:</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>node_ids</strong> (<em>List</em>) – the list of nodes labels</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a complete Digraph Object</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>networkx.DiGraph</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="structure_estimator.StructureEstimator.complete_test">
<code class="sig-name descname">complete_test</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">test_parent</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">test_child</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">parent_set</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">child_states_numb</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">tot_vars_count</span><span class="p">:</span> <span class="n">int</span></em><span class="sig-paren">)</span> &#x2192; bool<a class="headerlink" href="#structure_estimator.StructureEstimator.complete_test" title="Permalink to this definition"></a></dt>
<dd><p>Performs a complete independence test on the directed graphs G1 = {test_child U parent_set}
G2 = {G1 U test_parent} (added as an additional parent of the test_child).
Generates all the necessary structures and datas to perform the tests.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>test_parent</strong> (<em>string</em>) – the node label of the test parent</p></li>
<li><p><strong>test_child</strong> (<em>string</em>) – the node label of the child</p></li>
<li><p><strong>parent_set</strong> (<em>List</em>) – the common parent set</p></li>
<li><p><strong>child_states_numb</strong> (<em>int</em>) – the cardinality of the <code class="docutils literal notranslate"><span class="pre">test_child</span></code></p></li>
<li><p><strong>tot_vars_count</strong> (<em>int</em>) – the total number of variables in the net</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>True iff test_child and test_parent are independent given the sep_set parent_set. False otherwise</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>bool</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="structure_estimator.StructureEstimator.ctpc_algorithm">
<code class="sig-name descname">ctpc_algorithm</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#structure_estimator.StructureEstimator.ctpc_algorithm" title="Permalink to this definition"></a></dt>
<dd><p>Compute the CTPC algorithm over the entire net.</p>
</dd></dl>
<dl class="py method">
<dt id="structure_estimator.StructureEstimator.generate_possible_sub_sets_of_size">
<code class="sig-name descname">generate_possible_sub_sets_of_size</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">u</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">size</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">parent_label</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; Iterator<a class="headerlink" href="#structure_estimator.StructureEstimator.generate_possible_sub_sets_of_size" title="Permalink to this definition"></a></dt>
<dd><p>Creates a list containing all possible subsets of the list <code class="docutils literal notranslate"><span class="pre">u</span></code> of size <code class="docutils literal notranslate"><span class="pre">size</span></code>,
that do not contains a the node identified by <code class="docutils literal notranslate"><span class="pre">parent_label</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>u</strong> (<em>List</em>) – the list of nodes</p></li>
<li><p><strong>size</strong> (<em>int</em>) – the size of the subsets</p></li>
<li><p><strong>parent_label</strong> (<em>string</em>) – the node to exclude in the subsets generation</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>an Iterator Object containing a list of lists</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>Iterator</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="structure_estimator.StructureEstimator.independence_test">
<code class="sig-name descname">independence_test</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">child_states_numb</span><span class="p">:</span> <span class="n">int</span></em>, <em class="sig-param"><span class="n">cim1</span><span class="p">:</span> <span class="n"><a class="reference internal" href="conditional_intensity_matrix.html#conditional_intensity_matrix.ConditionalIntensityMatrix" title="conditional_intensity_matrix.ConditionalIntensityMatrix">conditional_intensity_matrix.ConditionalIntensityMatrix</a></span></em>, <em class="sig-param"><span class="n">cim2</span><span class="p">:</span> <span class="n"><a class="reference internal" href="conditional_intensity_matrix.html#conditional_intensity_matrix.ConditionalIntensityMatrix" title="conditional_intensity_matrix.ConditionalIntensityMatrix">conditional_intensity_matrix.ConditionalIntensityMatrix</a></span></em><span class="sig-paren">)</span> &#x2192; bool<a class="headerlink" href="#structure_estimator.StructureEstimator.independence_test" title="Permalink to this definition"></a></dt>
<dd><p>Compute the actual independence test using two cims.
It is performed first the exponential test and if the null hypothesis is not rejected,
it is performed also the chi_test.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>child_states_numb</strong> (<em>int</em>) – the cardinality of the test child</p></li>
<li><p><strong>cim1</strong> (<a class="reference internal" href="conditional_intensity_matrix.html#conditional_intensity_matrix.ConditionalIntensityMatrix" title="conditional_intensity_matrix.ConditionalIntensityMatrix"><em>ConditionalIntensityMatrix</em></a>) – a cim belonging to the graph without test parent</p></li>
<li><p><strong>cim2</strong> (<a class="reference internal" href="conditional_intensity_matrix.html#conditional_intensity_matrix.ConditionalIntensityMatrix" title="conditional_intensity_matrix.ConditionalIntensityMatrix"><em>ConditionalIntensityMatrix</em></a>) – a cim belonging to the graph with test parent</p></li>
</ul>
</dd>
</dl>
<p>:return:True iff both tests do NOT reject the null hypothesis of indipendence. False otherwise.
:rtype: bool</p>
</dd></dl>
<dl class="py method">
<dt id="structure_estimator.StructureEstimator.one_iteration_of_CTPC_algorithm">
<code class="sig-name descname">one_iteration_of_CTPC_algorithm</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">var_id</span><span class="p">:</span> <span class="n">str</span></em>, <em class="sig-param"><span class="n">tot_vars_count</span><span class="p">:</span> <span class="n">int</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#structure_estimator.StructureEstimator.one_iteration_of_CTPC_algorithm" title="Permalink to this definition"></a></dt>
<dd><p>Performs an iteration of the CTPC algorithm using the node <code class="docutils literal notranslate"><span class="pre">var_id</span></code> as <code class="docutils literal notranslate"><span class="pre">test_child</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>var_id</strong> (<em>string</em>) – the node label of the test child</p></li>
<li><p><strong>tot_vars_count</strong> (<em>int</em>) – the number of _nodes in the net</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="structure_estimator.StructureEstimator.save_results">
<code class="sig-name descname">save_results</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#structure_estimator.StructureEstimator.save_results" title="Permalink to this definition"></a></dt>
<dd><p>Save the estimated Structure to a .json file in the path where the data are loaded from.
The file is named as the input dataset but the <a href="#id1"><span class="problematic" id="id2">results_</span></a> word is appendend to the results file.</p>
</dd></dl>
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<div class="section" id="module-trajectory">
<span id="trajectory-module"></span><h1>trajectory module<a class="headerlink" href="#module-trajectory" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="trajectory.Trajectory">
<em class="property">class </em><code class="sig-prename descclassname">trajectory.</code><code class="sig-name descname">Trajectory</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">list_of_columns</span><span class="p">:</span> <span class="n">List</span></em>, <em class="sig-param"><span class="n">original_cols_number</span><span class="p">:</span> <span class="n">int</span></em><span class="sig-paren">)</span><a class="headerlink" href="#trajectory.Trajectory" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Abstracts the infos about a complete set of trajectories, represented as a numpy array of doubles (the time deltas)
and a numpy matrix of ints (the changes of states).</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>list_of_columns</strong> (<em>List</em>) – the list containing the times array and values matrix</p></li>
<li><p><strong>original_cols_number</strong> (<em>int</em>) – total number of cols in the data</p></li>
</ul>
</dd>
<dt class="field-even">_actual_trajectory</dt>
<dd class="field-even"><p>the trajectory containing also the duplicated/shifted values</p>
</dd>
<dt class="field-odd">_times</dt>
<dd class="field-odd"><p>the array containing the time deltas</p>
</dd>
</dl>
<dl class="py method">
<dt id="trajectory.Trajectory.complete_trajectory">
<em class="property">property </em><code class="sig-name descname">complete_trajectory</code><a class="headerlink" href="#trajectory.Trajectory.complete_trajectory" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dt id="trajectory.Trajectory.size">
<code class="sig-name descname">size</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#trajectory.Trajectory.size" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dt id="trajectory.Trajectory.times">
<em class="property">property </em><code class="sig-name descname">times</code><a class="headerlink" href="#trajectory.Trajectory.times" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="trajectory.Trajectory.trajectory">
<em class="property">property </em><code class="sig-name descname">trajectory</code><a class="headerlink" href="#trajectory.Trajectory.trajectory" title="Permalink to this definition"></a></dt>
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html_theme_path = [sphinx_pdj_theme.get_html_theme_path()]
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']

@ -0,0 +1,20 @@
.. PyCTBN documentation master file, created by
sphinx-quickstart on Mon Nov 30 16:37:03 2020.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
Welcome to PyCTBN's documentation!
==================================
.. toctree::
:maxdepth: 2
:caption: Contents:
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`

@ -0,0 +1,35 @@
@ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=.
set BUILDDIR=_build
if "%1" == "" goto help
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.http://sphinx-doc.org/
exit /b 1
)
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
goto end
:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
:end
popd

@ -0,0 +1,7 @@
abstract\_importer module
=========================
.. automodule:: abstract_importer
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,7 @@
cache module
============
.. automodule:: cache
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,7 @@
conditional\_intensity\_matrix module
=====================================
.. automodule:: conditional_intensity_matrix
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,7 @@
json\_importer module
=====================
.. automodule:: json_importer
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,17 @@
scripts
=======
.. toctree::
:maxdepth: 4
abstract_importer
cache
conditional_intensity_matrix
json_importer
network_graph
parameters_estimator
sample_path
set_of_cims
structure
structure_estimator
trajectory

@ -0,0 +1,7 @@
network\_graph module
=====================
.. automodule:: network_graph
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,7 @@
parameters\_estimator module
============================
.. automodule:: parameters_estimator
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,7 @@
sample\_path module
===================
.. automodule:: sample_path
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,7 @@
set\_of\_cims module
====================
.. automodule:: set_of_cims
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,7 @@
structure module
================
.. automodule:: structure
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,7 @@
structure\_estimator module
===========================
.. automodule:: structure_estimator
:members:
:undoc-members:
:show-inheritance:

@ -0,0 +1,7 @@
trajectory module
=================
.. automodule:: trajectory
:members:
:undoc-members:
:show-inheritance:

@ -1,6 +1,4 @@
import sys
sys.path.append("./classes/")
from abc import ABC, abstractmethod
import pandas as pd
import typing

@ -1,7 +1,7 @@
import sys
sys.path.append("./classes/")
import typing
import set_of_cims as sofc
#import set_of_cims as sofc
from .set_of_cims import SetOfCims
class Cache:
@ -18,7 +18,7 @@ class Cache:
self._list_of_sets_of_parents = []
self._actual_cache = []
def find(self, parents_comb: typing.Set) -> sofc.SetOfCims:
def find(self, parents_comb: typing.Set) -> SetOfCims:
"""
Tries to find in cache given the symbolic parents combination ``parents_comb`` the ``SetOfCims``
related to that ``parents_comb``.
@ -35,7 +35,7 @@ class Cache:
except ValueError:
return None
def put(self, parents_comb: typing.Set, socim: sofc.SetOfCims) -> None:
def put(self, parents_comb: typing.Set, socim: SetOfCims) -> None:
"""Place in cache the ``SetOfCims`` object, and the related symbolic index ``parents_comb`` in
``_list_of_sets_of_parents``.

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