From 675e6ba62daf0a2744a7f0624b6e905f49aea7af Mon Sep 17 00:00:00 2001 From: "Documenter.jl" Date: Mon, 30 Sep 2024 16:19:47 +0000 Subject: [PATCH] build based on 5fb46d4 --- previews/PR226/assets/documenter.js | 340 +++++++++++++++++ previews/PR226/assets/openstudy_diagram.svg | 124 +++++++ previews/PR226/assets/search.js | 267 ++++++++++++++ .../PR226/assets/themes/documenter-dark.css | 7 + .../PR226/assets/themes/documenter-light.css | 9 + previews/PR226/assets/themeswap.js | 66 ++++ previews/PR226/assets/warner.js | 49 +++ .../PR226/examples/custom_study/index.html | 53 +++ previews/PR226/examples/graf_files/index.html | 163 +++++++++ .../PR226/examples/modification/index.html | 39 ++ .../PR226/examples/reading_demands/index.html | 134 +++++++ .../examples/reading_parameters/index.html | 55 +++ .../examples/reading_relations/index.html | 48 +++ previews/PR226/index.html | 4 + previews/PR226/manual/index.html | 343 ++++++++++++++++++ .../openstudy_files/file_diagram/index.html | 2 + .../openstudy_files/model_template/index.html | 15 + previews/PR226/openstudy_files/pmd/index.html | 49 +++ .../openstudy_files/psrclasses/index.html | 25 ++ .../relation_mapper/index.html | 29 ++ .../psrdatabasesqlite/introduction/index.html | 2 + .../PR226/psrdatabasesqlite/rules/index.html | 71 ++++ .../psrdatabasesqlite/time_series/index.html | 123 +++++++ previews/PR226/search/index.html | 2 + previews/PR226/search_index.js | 3 + previews/PR226/siteinfo.js | 1 + .../sqlite_examples/migrations/index.html | 313 ++++++++++++++++ 27 files changed, 2336 insertions(+) create mode 100644 previews/PR226/assets/documenter.js create mode 100644 previews/PR226/assets/openstudy_diagram.svg create mode 100644 previews/PR226/assets/search.js create mode 100644 previews/PR226/assets/themes/documenter-dark.css create mode 100644 previews/PR226/assets/themes/documenter-light.css create mode 100644 previews/PR226/assets/themeswap.js create mode 100644 previews/PR226/assets/warner.js create mode 100644 previews/PR226/examples/custom_study/index.html create mode 100644 previews/PR226/examples/graf_files/index.html create mode 100644 previews/PR226/examples/modification/index.html create mode 100644 previews/PR226/examples/reading_demands/index.html create mode 100644 previews/PR226/examples/reading_parameters/index.html create mode 100644 previews/PR226/examples/reading_relations/index.html create mode 100644 previews/PR226/index.html create mode 100644 previews/PR226/manual/index.html create mode 100644 previews/PR226/openstudy_files/file_diagram/index.html create mode 100644 previews/PR226/openstudy_files/model_template/index.html create mode 100644 previews/PR226/openstudy_files/pmd/index.html create mode 100644 previews/PR226/openstudy_files/psrclasses/index.html create mode 100644 previews/PR226/openstudy_files/relation_mapper/index.html create mode 100644 previews/PR226/psrdatabasesqlite/introduction/index.html create mode 100644 previews/PR226/psrdatabasesqlite/rules/index.html create mode 100644 previews/PR226/psrdatabasesqlite/time_series/index.html create mode 100644 previews/PR226/search/index.html create mode 100644 previews/PR226/search_index.js create mode 100644 previews/PR226/siteinfo.js create mode 100644 previews/PR226/sqlite_examples/migrations/index.html diff --git a/previews/PR226/assets/documenter.js b/previews/PR226/assets/documenter.js new file mode 100644 index 00000000..32e27c51 --- /dev/null +++ b/previews/PR226/assets/documenter.js @@ -0,0 +1,340 @@ +// Generated by Documenter.jl +requirejs.config({ + paths: { + 'highlight-julia': 'https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.5.1/languages/julia.min', + 'headroom': 'https://cdnjs.cloudflare.com/ajax/libs/headroom/0.12.0/headroom.min', + 'jqueryui': 'https://cdnjs.cloudflare.com/ajax/libs/jqueryui/1.12.1/jquery-ui.min', + 'jquery': 'https://cdnjs.cloudflare.com/ajax/libs/jquery/3.6.0/jquery.min', + 'mathjax': 'https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/MathJax.js?config=TeX-AMS_HTML', + 'headroom-jquery': 'https://cdnjs.cloudflare.com/ajax/libs/headroom/0.12.0/jQuery.headroom.min', + 'highlight': 'https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.5.1/highlight.min', + 'highlight-julia-repl': 'https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.5.1/languages/julia-repl.min', + }, + shim: { + "highlight-julia": { + "deps": [ + "highlight" + ] + }, + "mathjax": { + "exports": "MathJax" + }, + "headroom-jquery": { + "deps": [ + "jquery", + "headroom" + ] + }, + "highlight-julia-repl": { + "deps": [ + "highlight" + ] + } +} +}); +//////////////////////////////////////////////////////////////////////////////// +require(['mathjax'], function(MathJax) { +MathJax.Hub.Config({ + "jax": [ + "input/TeX", + "output/HTML-CSS", + "output/NativeMML" + ], + "TeX": { + "equationNumbers": { + "autoNumber": "AMS" + } + }, + "tex2jax": { + "inlineMath": [ + [ + "$", + "$" + ], + [ + "\\(", + "\\)" + ] + ], + "processEscapes": true + }, + "config": [ + "MMLorHTML.js" + ], + "extensions": [ + "MathMenu.js", + "MathZoom.js", + "TeX/AMSmath.js", + "TeX/AMSsymbols.js", + "TeX/autobold.js", + "TeX/autoload-all.js" + ] +} +); + +}) +//////////////////////////////////////////////////////////////////////////////// +require(['jquery', 'highlight', 'highlight-julia', 'highlight-julia-repl'], function($) { +$(document).ready(function() { + hljs.highlightAll(); +}) + +}) +//////////////////////////////////////////////////////////////////////////////// +require([], function() { +function addCopyButtonCallbacks() { + for (const el of document.getElementsByTagName("pre")) { + const button = document.createElement("button"); + button.classList.add("copy-button", "fas", "fa-copy"); + el.appendChild(button); + + const success = function () { + button.classList.add("success", "fa-check"); + button.classList.remove("fa-copy"); + }; + + const failure = function () { + button.classList.add("error", "fa-times"); + button.classList.remove("fa-copy"); + }; + + button.addEventListener("click", function () { + copyToClipboard(el.innerText).then(success, failure); + + setTimeout(function () { + button.classList.add("fa-copy"); + button.classList.remove("success", "fa-check", "fa-times"); + }, 5000); + }); + } +} + +function copyToClipboard(text) { + // clipboard API is only available in secure contexts + if (window.navigator && window.navigator.clipboard) { + return window.navigator.clipboard.writeText(text); + } else { + return new Promise(function (resolve, reject) { + try { + const el = document.createElement("textarea"); + el.textContent = text; + el.style.position = "fixed"; + el.style.opacity = 0; + document.body.appendChild(el); + el.select(); + document.execCommand("copy"); + + resolve(); + } catch (err) { + reject(err); + } finally { + document.body.removeChild(el); + } + }); + } +} + +if (document.readyState === "loading") { + document.addEventListener("DOMContentLoaded", addCopyButtonCallbacks); +} else { + addCopyButtonCallbacks(); +} + +}) +//////////////////////////////////////////////////////////////////////////////// +require(['jquery', 'headroom', 'headroom-jquery'], function($, Headroom) { + +// Manages the top navigation bar (hides it when the user starts scrolling down on the +// mobile). +window.Headroom = Headroom; // work around buggy module loading? +$(document).ready(function() { + $('#documenter .docs-navbar').headroom({ + "tolerance": {"up": 10, "down": 10}, + }); +}) + +}) +//////////////////////////////////////////////////////////////////////////////// +require(['jquery'], function($) { + +// Modal settings dialog +$(document).ready(function() { + var settings = $('#documenter-settings'); + $('#documenter-settings-button').click(function(){ + settings.toggleClass('is-active'); + }); + // Close the dialog if X is clicked + $('#documenter-settings button.delete').click(function(){ + settings.removeClass('is-active'); + }); + // Close dialog if ESC is pressed + $(document).keyup(function(e) { + if (e.keyCode == 27) settings.removeClass('is-active'); + }); +}); + +}) +//////////////////////////////////////////////////////////////////////////////// +require(['jquery'], function($) { + +// Manages the showing and hiding of the sidebar. +$(document).ready(function() { + var sidebar = $("#documenter > .docs-sidebar"); + var sidebar_button = $("#documenter-sidebar-button") + sidebar_button.click(function(ev) { + ev.preventDefault(); + sidebar.toggleClass('visible'); + if (sidebar.hasClass('visible')) { + // Makes sure that the current menu item is visible in the sidebar. + $("#documenter .docs-menu a.is-active").focus(); + } + }); + $("#documenter > .docs-main").bind('click', function(ev) { + if ($(ev.target).is(sidebar_button)) { + return; + } + if (sidebar.hasClass('visible')) { + sidebar.removeClass('visible'); + } + }); +}) + +// Resizes the package name / sitename in the sidebar if it is too wide. +// Inspired by: https://github.com/davatron5000/FitText.js +$(document).ready(function() { + e = $("#documenter .docs-autofit"); + function resize() { + var L = parseInt(e.css('max-width'), 10); + var L0 = e.width(); + if(L0 > L) { + var h0 = parseInt(e.css('font-size'), 10); + e.css('font-size', L * h0 / L0); + // TODO: make sure it survives resizes? + } + } + // call once and then register events + resize(); + $(window).resize(resize); + $(window).on('orientationchange', resize); +}); + +// Scroll the navigation bar to the currently selected menu item +$(document).ready(function() { + var sidebar = $("#documenter .docs-menu").get(0); + var active = $("#documenter .docs-menu .is-active").get(0); + if(typeof active !== 'undefined') { + sidebar.scrollTop = active.offsetTop - sidebar.offsetTop - 15; + } +}) + +}) +//////////////////////////////////////////////////////////////////////////////// +require(['jquery'], function($) { + +function set_theme(theme) { + var active = null; + var disabled = []; + for (var i = 0; i < document.styleSheets.length; i++) { + var ss = document.styleSheets[i]; + var themename = ss.ownerNode.getAttribute("data-theme-name"); + if(themename === null) continue; // ignore non-theme stylesheets + // Find the active theme + if(themename === theme) active = ss; + else disabled.push(ss); + } + if(active !== null) { + active.disabled = false; + if(active.ownerNode.getAttribute("data-theme-primary") === null) { + document.getElementsByTagName('html')[0].className = "theme--" + theme; + } else { + document.getElementsByTagName('html')[0].className = ""; + } + disabled.forEach(function(ss){ + ss.disabled = true; + }); + } + + // Store the theme in localStorage + if(typeof(window.localStorage) !== "undefined") { + window.localStorage.setItem("documenter-theme", theme); + } else { + console.error("Browser does not support window.localStorage"); + } +} + +// Theme picker setup +$(document).ready(function() { + // onchange callback + $('#documenter-themepicker').change(function themepick_callback(ev){ + var themename = $('#documenter-themepicker option:selected').attr('value'); + set_theme(themename); + }); + + // Make sure that the themepicker displays the correct theme when the theme is retrieved + // from localStorage + if(typeof(window.localStorage) !== "undefined") { + var theme = window.localStorage.getItem("documenter-theme"); + if(theme !== null) { + $('#documenter-themepicker option').each(function(i,e) { + e.selected = (e.value === theme); + }) + } else { + $('#documenter-themepicker option').each(function(i,e) { + e.selected = $("html").hasClass(`theme--${e.value}`); + }) + } + } +}) + +}) +//////////////////////////////////////////////////////////////////////////////// +require(['jquery'], function($) { + +// update the version selector with info from the siteinfo.js and ../versions.js files +$(document).ready(function() { + // If the version selector is disabled with DOCUMENTER_VERSION_SELECTOR_DISABLED in the + // siteinfo.js file, we just return immediately and not display the version selector. + if (typeof DOCUMENTER_VERSION_SELECTOR_DISABLED === 'boolean' && DOCUMENTER_VERSION_SELECTOR_DISABLED) { + return; + } + + var version_selector = $("#documenter .docs-version-selector"); + var version_selector_select = $("#documenter .docs-version-selector select"); + + version_selector_select.change(function(x) { + target_href = version_selector_select.children("option:selected").get(0).value; + window.location.href = target_href; + }); + + // add the current version to the selector based on siteinfo.js, but only if the selector is empty + if (typeof DOCUMENTER_CURRENT_VERSION !== 'undefined' && $('#version-selector > option').length == 0) { + var option = $(""); + version_selector_select.append(option); + } + + if (typeof DOC_VERSIONS !== 'undefined') { + var existing_versions = version_selector_select.children("option"); + var existing_versions_texts = existing_versions.map(function(i,x){return x.text}); + DOC_VERSIONS.forEach(function(each) { + var version_url = documenterBaseURL + "/../" + each; + var existing_id = $.inArray(each, existing_versions_texts); + // if not already in the version selector, add it as a new option, + // otherwise update the old option with the URL and enable it + if (existing_id == -1) { + var option = $(""); + version_selector_select.append(option); + } else { + var option = existing_versions[existing_id]; + option.value = version_url; + option.disabled = false; + } + }); + } + + // only show the version selector if the selector has been populated + if (version_selector_select.children("option").length > 0) { + version_selector.toggleClass("visible"); + } +}) + +}) diff --git a/previews/PR226/assets/openstudy_diagram.svg b/previews/PR226/assets/openstudy_diagram.svg new file mode 100644 index 00000000..8fa21de9 --- /dev/null +++ b/previews/PR226/assets/openstudy_diagram.svg @@ -0,0 +1,124 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/previews/PR226/assets/search.js b/previews/PR226/assets/search.js new file mode 100644 index 00000000..c133f741 --- /dev/null +++ b/previews/PR226/assets/search.js @@ -0,0 +1,267 @@ +// Generated by Documenter.jl +requirejs.config({ + paths: { + 'lunr': 'https://cdnjs.cloudflare.com/ajax/libs/lunr.js/2.3.9/lunr.min', + 'lodash': 'https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/lodash.min', + 'jquery': 'https://cdnjs.cloudflare.com/ajax/libs/jquery/3.6.0/jquery.min', + } +}); +//////////////////////////////////////////////////////////////////////////////// +require(['jquery', 'lunr', 'lodash'], function($, lunr, _) { + +$(document).ready(function() { + // parseUri 1.2.2 + // (c) Steven Levithan + // MIT License + function parseUri (str) { + var o = parseUri.options, + m = o.parser[o.strictMode ? "strict" : "loose"].exec(str), + uri = {}, + i = 14; + + while (i--) uri[o.key[i]] = m[i] || ""; + + uri[o.q.name] = {}; + uri[o.key[12]].replace(o.q.parser, function ($0, $1, $2) { + if ($1) uri[o.q.name][$1] = $2; + }); + + return uri; + }; + parseUri.options = { + strictMode: false, + key: ["source","protocol","authority","userInfo","user","password","host","port","relative","path","directory","file","query","anchor"], + q: { + name: "queryKey", + parser: /(?:^|&)([^&=]*)=?([^&]*)/g + }, + parser: { + strict: /^(?:([^:\/?#]+):)?(?:\/\/((?:(([^:@]*)(?::([^:@]*))?)?@)?([^:\/?#]*)(?::(\d*))?))?((((?:[^?#\/]*\/)*)([^?#]*))(?:\?([^#]*))?(?:#(.*))?)/, + loose: /^(?:(?![^:@]+:[^:@\/]*@)([^:\/?#.]+):)?(?:\/\/)?((?:(([^:@]*)(?::([^:@]*))?)?@)?([^:\/?#]*)(?::(\d*))?)(((\/(?:[^?#](?![^?#\/]*\.[^?#\/.]+(?:[?#]|$)))*\/?)?([^?#\/]*))(?:\?([^#]*))?(?:#(.*))?)/ + } + }; + + $("#search-form").submit(function(e) { + e.preventDefault() + }) + + // list below is the lunr 2.1.3 list minus the intersect with names(Base) + // (all, any, get, in, is, only, which) and (do, else, for, let, where, while, with) + // ideally we'd just filter the original list but it's not available as a variable + lunr.stopWordFilter = lunr.generateStopWordFilter([ + 'a', + 'able', + 'about', + 'across', + 'after', + 'almost', + 'also', + 'am', + 'among', + 'an', + 'and', + 'are', + 'as', + 'at', + 'be', + 'because', + 'been', + 'but', + 'by', + 'can', + 'cannot', + 'could', + 'dear', + 'did', + 'does', + 'either', + 'ever', + 'every', + 'from', + 'got', + 'had', + 'has', + 'have', + 'he', + 'her', + 'hers', + 'him', + 'his', + 'how', + 'however', + 'i', + 'if', + 'into', + 'it', + 'its', + 'just', + 'least', + 'like', + 'likely', + 'may', + 'me', + 'might', + 'most', + 'must', + 'my', + 'neither', + 'no', + 'nor', + 'not', + 'of', + 'off', + 'often', + 'on', + 'or', + 'other', + 'our', + 'own', + 'rather', + 'said', + 'say', + 'says', + 'she', + 'should', + 'since', + 'so', + 'some', + 'than', + 'that', + 'the', + 'their', + 'them', + 'then', + 'there', + 'these', + 'they', + 'this', + 'tis', + 'to', + 'too', + 'twas', + 'us', + 'wants', + 'was', + 'we', + 'were', + 'what', + 'when', + 'who', + 'whom', + 'why', + 'will', + 'would', + 'yet', + 'you', + 'your' + ]) + + // add . as a separator, because otherwise "title": "Documenter.Anchors.add!" + // would not find anything if searching for "add!", only for the entire qualification + lunr.tokenizer.separator = /[\s\-\.]+/ + + // custom trimmer that doesn't strip @ and !, which are used in julia macro and function names + lunr.trimmer = function (token) { + return token.update(function (s) { + return s.replace(/^[^a-zA-Z0-9@!]+/, '').replace(/[^a-zA-Z0-9@!]+$/, '') + }) + } + + lunr.Pipeline.registerFunction(lunr.stopWordFilter, 'juliaStopWordFilter') + lunr.Pipeline.registerFunction(lunr.trimmer, 'juliaTrimmer') + + var index = lunr(function () { + this.ref('location') + this.field('title',{boost: 100}) + this.field('text') + documenterSearchIndex['docs'].forEach(function(e) { + this.add(e) + }, this) + }) + var store = {} + + documenterSearchIndex['docs'].forEach(function(e) { + store[e.location] = {title: e.title, category: e.category, page: e.page} + }) + + $(function(){ + searchresults = $('#documenter-search-results'); + searchinfo = $('#documenter-search-info'); + searchbox = $('#documenter-search-query'); + searchform = $('.docs-search'); + sidebar = $('.docs-sidebar'); + function update_search(querystring) { + tokens = lunr.tokenizer(querystring) + results = index.query(function (q) { + tokens.forEach(function (t) { + q.term(t.toString(), { + fields: ["title"], + boost: 100, + usePipeline: true, + editDistance: 0, + wildcard: lunr.Query.wildcard.NONE + }) + q.term(t.toString(), { + fields: ["title"], + boost: 10, + usePipeline: true, + editDistance: 2, + wildcard: lunr.Query.wildcard.NONE + }) + q.term(t.toString(), { + fields: ["text"], + boost: 1, + usePipeline: true, + editDistance: 0, + wildcard: lunr.Query.wildcard.NONE + }) + }) + }) + searchinfo.text("Number of results: " + results.length) + searchresults.empty() + results.forEach(function(result) { + data = store[result.ref] + link = $(''+data.title+'') + link.attr('href', documenterBaseURL+'/'+result.ref) + if (data.category != "page"){ + cat = $('('+data.category+', '+data.page+')') + } else { + cat = $('('+data.category+')') + } + li = $('
  • ').append(link).append(" ").append(cat) + searchresults.append(li) + }) + } + + function update_search_box() { + querystring = searchbox.val() + update_search(querystring) + } + + searchbox.keyup(_.debounce(update_search_box, 250)) + searchbox.change(update_search_box) + + // Disable enter-key form submission for the searchbox on the search page + // and just re-run search rather than refresh the whole page. + searchform.keypress( + function(event){ + if (event.which == '13') { + if (sidebar.hasClass('visible')) { + sidebar.removeClass('visible'); + } + update_search_box(); + event.preventDefault(); + } + } + ); + + search_query_uri = parseUri(window.location).queryKey["q"] + if(search_query_uri !== undefined) { + search_query = decodeURIComponent(search_query_uri.replace(/\+/g, '%20')) + searchbox.val(search_query) + } + update_search_box(); + }) +}) + +}) diff --git a/previews/PR226/assets/themes/documenter-dark.css b/previews/PR226/assets/themes/documenter-dark.css new file mode 100644 index 00000000..c94a294d --- /dev/null +++ b/previews/PR226/assets/themes/documenter-dark.css @@ -0,0 +1,7 @@ +@keyframes spinAround{from{transform:rotate(0deg)}to{transform:rotate(359deg)}}html.theme--documenter-dark .tabs,html.theme--documenter-dark .pagination-previous,html.theme--documenter-dark .pagination-next,html.theme--documenter-dark .pagination-link,html.theme--documenter-dark .pagination-ellipsis,html.theme--documenter-dark .breadcrumb,html.theme--documenter-dark .file,html.theme--documenter-dark .button,.is-unselectable,html.theme--documenter-dark .modal-close,html.theme--documenter-dark .delete{-webkit-touch-callout:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}html.theme--documenter-dark .navbar-link:not(.is-arrowless)::after,html.theme--documenter-dark .select:not(.is-multiple):not(.is-loading)::after{border:3px solid rgba(0,0,0,0);border-radius:2px;border-right:0;border-top:0;content:" 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kbd.button.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-dark.is-outlined.is-loading:focus::after,html.theme--documenter-dark .content kbd.button.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-dark.is-outlined.is-loading.is-focused::after,html.theme--documenter-dark .content kbd.button.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #ecf0f1 #ecf0f1 !important}html.theme--documenter-dark .button.is-dark.is-outlined[disabled],html.theme--documenter-dark .content kbd.button.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-dark.is-outlined,fieldset[disabled] html.theme--documenter-dark .content kbd.button.is-outlined{background-color:transparent;border-color:#282f2f;box-shadow:none;color:#282f2f}html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined,html.theme--documenter-dark .content 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.button.is-dark.is-inverted.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined.is-loading.is-hovered::after,html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined.is-loading:focus::after,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined.is-loading:focus::after,html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined.is-loading.is-focused::after,html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined.is-loading.is-focused::after{border-color:transparent transparent #282f2f #282f2f !important}html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined[disabled],html.theme--documenter-dark .content kbd.button.is-inverted.is-outlined[disabled],fieldset[disabled] html.theme--documenter-dark .button.is-dark.is-inverted.is-outlined,fieldset[disabled] html.theme--documenter-dark .content 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form.docs-search>input.button{border-radius:290486px;padding-left:1em;padding-right:1em}html.theme--documenter-dark .buttons{align-items:center;display:flex;flex-wrap:wrap;justify-content:flex-start}html.theme--documenter-dark .buttons .button{margin-bottom:0.5rem}html.theme--documenter-dark .buttons .button:not(:last-child):not(.is-fullwidth){margin-right:0.5rem}html.theme--documenter-dark .buttons:last-child{margin-bottom:-0.5rem}html.theme--documenter-dark .buttons:not(:last-child){margin-bottom:1rem}html.theme--documenter-dark .buttons.are-small .button:not(.is-normal):not(.is-medium):not(.is-large){border-radius:3px;font-size:.85em}html.theme--documenter-dark .buttons.are-medium .button:not(.is-small):not(.is-normal):not(.is-large){font-size:1.25rem}html.theme--documenter-dark .buttons.are-large .button:not(.is-small):not(.is-normal):not(.is-medium){font-size:1.5rem}html.theme--documenter-dark .buttons.has-addons 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a.navbar-item,html.theme--documenter-dark .navbar-link{cursor:pointer}html.theme--documenter-dark a.navbar-item:focus,html.theme--documenter-dark a.navbar-item:focus-within,html.theme--documenter-dark a.navbar-item:hover,html.theme--documenter-dark a.navbar-item.is-active,html.theme--documenter-dark .navbar-link:focus,html.theme--documenter-dark .navbar-link:focus-within,html.theme--documenter-dark .navbar-link:hover,html.theme--documenter-dark .navbar-link.is-active{background-color:rgba(0,0,0,0);color:#1abc9c}html.theme--documenter-dark .navbar-item{display:block;flex-grow:0;flex-shrink:0}html.theme--documenter-dark .navbar-item img{max-height:1.75rem}html.theme--documenter-dark .navbar-item.has-dropdown{padding:0}html.theme--documenter-dark .navbar-item.is-expanded{flex-grow:1;flex-shrink:1}html.theme--documenter-dark .navbar-item.is-tab{border-bottom:1px solid transparent;min-height:4rem;padding-bottom:calc(0.5rem - 1px)}html.theme--documenter-dark 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1055px){html.theme--documenter-dark .navbar>.container{display:block}html.theme--documenter-dark .navbar-brand .navbar-item,html.theme--documenter-dark .navbar-tabs .navbar-item{align-items:center;display:flex}html.theme--documenter-dark .navbar-link::after{display:none}html.theme--documenter-dark .navbar-menu{background-color:#375a7f;box-shadow:0 8px 16px rgba(10,10,10,0.1);padding:0.5rem 0}html.theme--documenter-dark .navbar-menu.is-active{display:block}html.theme--documenter-dark .navbar.is-fixed-bottom-touch,html.theme--documenter-dark .navbar.is-fixed-top-touch{left:0;position:fixed;right:0;z-index:30}html.theme--documenter-dark .navbar.is-fixed-bottom-touch{bottom:0}html.theme--documenter-dark .navbar.is-fixed-bottom-touch.has-shadow{box-shadow:0 -2px 3px rgba(10,10,10,0.1)}html.theme--documenter-dark .navbar.is-fixed-top-touch{top:0}html.theme--documenter-dark .navbar.is-fixed-top .navbar-menu,html.theme--documenter-dark .navbar.is-fixed-top-touch 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a.navbar-item:hover{background-color:rgba(0,0,0,0);color:#dbdee0}html.theme--documenter-dark .navbar-dropdown a.navbar-item.is-active{background-color:rgba(0,0,0,0);color:#1abc9c}.navbar.is-spaced html.theme--documenter-dark .navbar-dropdown,html.theme--documenter-dark .navbar-dropdown.is-boxed{border-radius:8px;border-top:none;box-shadow:0 8px 8px rgba(10,10,10,0.1), 0 0 0 1px rgba(10,10,10,0.1);display:block;opacity:0;pointer-events:none;top:calc(100% + (-4px));transform:translateY(-5px);transition-duration:86ms;transition-property:opacity, transform}html.theme--documenter-dark .navbar-dropdown.is-right{left:auto;right:0}html.theme--documenter-dark .navbar-divider{display:block}html.theme--documenter-dark .navbar>.container .navbar-brand,html.theme--documenter-dark .container>.navbar .navbar-brand{margin-left:-.75rem}html.theme--documenter-dark .navbar>.container .navbar-menu,html.theme--documenter-dark .container>.navbar .navbar-menu{margin-right:-.75rem}html.theme--documenter-dark .navbar.is-fixed-bottom-desktop,html.theme--documenter-dark .navbar.is-fixed-top-desktop{left:0;position:fixed;right:0;z-index:30}html.theme--documenter-dark .navbar.is-fixed-bottom-desktop{bottom:0}html.theme--documenter-dark .navbar.is-fixed-bottom-desktop.has-shadow{box-shadow:0 -2px 3px rgba(10,10,10,0.1)}html.theme--documenter-dark .navbar.is-fixed-top-desktop{top:0}html.theme--documenter-dark html.has-navbar-fixed-top-desktop,html.theme--documenter-dark body.has-navbar-fixed-top-desktop{padding-top:4rem}html.theme--documenter-dark html.has-navbar-fixed-bottom-desktop,html.theme--documenter-dark body.has-navbar-fixed-bottom-desktop{padding-bottom:4rem}html.theme--documenter-dark html.has-spaced-navbar-fixed-top,html.theme--documenter-dark body.has-spaced-navbar-fixed-top{padding-top:6rem}html.theme--documenter-dark html.has-spaced-navbar-fixed-bottom,html.theme--documenter-dark body.has-spaced-navbar-fixed-bottom{padding-bottom:6rem}html.theme--documenter-dark a.navbar-item.is-active,html.theme--documenter-dark .navbar-link.is-active{color:#1abc9c}html.theme--documenter-dark a.navbar-item.is-active:not(:focus):not(:hover),html.theme--documenter-dark .navbar-link.is-active:not(:focus):not(:hover){background-color:rgba(0,0,0,0)}html.theme--documenter-dark .navbar-item.has-dropdown:focus .navbar-link,html.theme--documenter-dark .navbar-item.has-dropdown:hover .navbar-link,html.theme--documenter-dark .navbar-item.has-dropdown.is-active .navbar-link{background-color:rgba(0,0,0,0)}}html.theme--documenter-dark .hero.is-fullheight-with-navbar{min-height:calc(100vh - 4rem)}html.theme--documenter-dark .pagination{font-size:15px;margin:-.25rem}html.theme--documenter-dark .pagination.is-small,html.theme--documenter-dark #documenter .docs-sidebar form.docs-search>input.pagination{font-size:.85em}html.theme--documenter-dark .pagination.is-medium{font-size:1.25rem}html.theme--documenter-dark .pagination.is-large{font-size:1.5rem}html.theme--documenter-dark .pagination.is-rounded .pagination-previous,html.theme--documenter-dark #documenter .docs-sidebar form.docs-search>input.pagination .pagination-previous,html.theme--documenter-dark .pagination.is-rounded .pagination-next,html.theme--documenter-dark #documenter .docs-sidebar form.docs-search>input.pagination .pagination-next{padding-left:1em;padding-right:1em;border-radius:290486px}html.theme--documenter-dark .pagination.is-rounded .pagination-link,html.theme--documenter-dark #documenter .docs-sidebar form.docs-search>input.pagination .pagination-link{border-radius:290486px}html.theme--documenter-dark .pagination,html.theme--documenter-dark .pagination-list{align-items:center;display:flex;justify-content:center;text-align:center}html.theme--documenter-dark .pagination-previous,html.theme--documenter-dark .pagination-next,html.theme--documenter-dark .pagination-link,html.theme--documenter-dark .pagination-ellipsis{font-size:1em;justify-content:center;margin:.25rem;padding-left:.5em;padding-right:.5em;text-align:center}html.theme--documenter-dark .pagination-previous,html.theme--documenter-dark .pagination-next,html.theme--documenter-dark .pagination-link{border-color:#5e6d6f;color:#1abc9c;min-width:2.25em}html.theme--documenter-dark .pagination-previous:hover,html.theme--documenter-dark .pagination-next:hover,html.theme--documenter-dark .pagination-link:hover{border-color:#8c9b9d;color:#1dd2af}html.theme--documenter-dark .pagination-previous:focus,html.theme--documenter-dark .pagination-next:focus,html.theme--documenter-dark .pagination-link:focus{border-color:#8c9b9d}html.theme--documenter-dark .pagination-previous:active,html.theme--documenter-dark .pagination-next:active,html.theme--documenter-dark .pagination-link:active{box-shadow:inset 0 1px 2px rgba(10,10,10,0.2)}html.theme--documenter-dark .pagination-previous[disabled],html.theme--documenter-dark 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ul.is-center{flex:none;justify-content:center;padding-left:0.75em;padding-right:0.75em}html.theme--documenter-dark .tabs ul.is-right{justify-content:flex-end;padding-left:0.75em}html.theme--documenter-dark .tabs .icon:first-child{margin-right:0.5em}html.theme--documenter-dark .tabs .icon:last-child{margin-left:0.5em}html.theme--documenter-dark .tabs.is-centered ul{justify-content:center}html.theme--documenter-dark .tabs.is-right ul{justify-content:flex-end}html.theme--documenter-dark .tabs.is-boxed a{border:1px solid transparent;border-radius:.4em .4em 0 0}html.theme--documenter-dark .tabs.is-boxed a:hover{background-color:#282f2f;border-bottom-color:#5e6d6f}html.theme--documenter-dark .tabs.is-boxed li.is-active a{background-color:#fff;border-color:#5e6d6f;border-bottom-color:rgba(0,0,0,0) !important}html.theme--documenter-dark .tabs.is-fullwidth li{flex-grow:1;flex-shrink:0}html.theme--documenter-dark .tabs.is-toggle 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Gets put into the tag.. +function set_theme_from_local_storage() { + // Intialize the theme to null, which means default + var theme = null; + // If the browser supports the localstorage and is not disabled then try to get the + // documenter theme + if(window.localStorage != null) { + // Get the user-picked theme from localStorage. May be `null`, which means the default + // theme. + theme = window.localStorage.getItem("documenter-theme"); + } + // Check if the browser supports user color preference + var darkPreference = false; + // Check if the users preference is for dark color scheme + if(window.matchMedia('(prefers-color-scheme: dark)').matches === true) { + darkPreference = true; + } + // Initialize a few variables for the loop: + // + // - active: will contain the index of the theme that should be active. Note that there + // is no guarantee that localStorage contains sane values. If `active` stays `null` + // we either could not find the theme or it is the default (primary) theme anyway. + // Either way, we then need to stick to the primary theme. + // + // - disabled: style sheets that should be disabled (i.e. all the theme style sheets + // that are not the currently active theme) + var active = null; var disabled = []; var darkTheme = null; + for (var i = 0; i < document.styleSheets.length; i++) { + var ss = document.styleSheets[i]; + // The tag of each style sheet is expected to have a data-theme-name attribute + // which must contain the name of the theme. The names in localStorage much match this. + var themename = ss.ownerNode.getAttribute("data-theme-name"); + // attribute not set => non-theme stylesheet => ignore + if(themename === null) continue; + // To distinguish the default (primary) theme, it needs to have the data-theme-primary + // attribute set. + var isprimary = (ss.ownerNode.getAttribute("data-theme-primary") !== null); + // Check if the theme is primary dark theme + var isDarkTheme = (ss.ownerNode.getAttribute("data-theme-primary-dark") !== null); + // If ss is for dark theme then set the value of darkTheme to the name of the theme + if(isDarkTheme) darkTheme = themename; + // If we find a matching theme (and it's not the default), we'll set active to non-null + if(themename === theme) active = i; + // Store the style sheets of inactive themes so that we could disable them + if(themename !== theme) disabled.push(ss); + } + if(active !== null) { + // If we did find an active theme, we'll (1) add the theme--$(theme) class to + document.getElementsByTagName('html')[0].className = "theme--" + theme; + // and (2) disable all the other theme stylesheets + disabled.forEach(function(ss){ + ss.disabled = true; + }); + } + else if(darkTheme !== null && darkPreference === true) { + // If we did find an active theme, we'll (1) add the theme--$(theme) class to + document.getElementsByTagName('html')[0].className = "theme--" + darkTheme; + // and (2) disable all the other theme stylesheets + disabled.forEach(function(ss){ + if (ss.ownerNode.getAttribute("data-theme-name") !== darkTheme) { + ss.disabled = true; + } + }); + } +} +set_theme_from_local_storage(); diff --git a/previews/PR226/assets/warner.js b/previews/PR226/assets/warner.js new file mode 100644 index 00000000..5531c885 --- /dev/null +++ b/previews/PR226/assets/warner.js @@ -0,0 +1,49 @@ +function maybeAddWarning () { + // DOCUMENTER_NEWEST is defined in versions.js, DOCUMENTER_CURRENT_VERSION and DOCUMENTER_STABLE + // in siteinfo.js. + // If either of these are undefined something went horribly wrong, so we abort. + if ( + window.DOCUMENTER_NEWEST === undefined || + window.DOCUMENTER_CURRENT_VERSION === undefined || + window.DOCUMENTER_STABLE === undefined + ) { + return + }; + + // Current version is not a version number, so we can't tell if it's the newest version. Abort. + if (!/v(\d+\.)*\d+/.test(window.DOCUMENTER_CURRENT_VERSION)) { + return + }; + + // Current version is newest version, so no need to add a warning. + if (window.DOCUMENTER_NEWEST === window.DOCUMENTER_CURRENT_VERSION) { + return + }; + + // Add a noindex meta tag (unless one exists) so that search engines don't index this version of the docs. + if (document.body.querySelector('meta[name="robots"]') === null) { + const meta = document.createElement('meta'); + meta.name = 'robots'; + meta.content = 'noindex'; + + document.getElementsByTagName('head')[0].appendChild(meta); + }; + + const div = document.createElement('div'); + div.classList.add('outdated-warning-overlay'); + const closer = document.createElement('button'); + closer.classList.add('outdated-warning-closer', 'delete'); + closer.addEventListener('click', function () { + document.body.removeChild(div); + }); + const href = window.documenterBaseURL + '/../' + window.DOCUMENTER_STABLE; + div.innerHTML = 'This documentation is not for the latest stable release, but for either the development version or an older release.
    Click here to go to the documentation for the latest stable release.'; + div.appendChild(closer); + document.body.appendChild(div); +}; + +if (document.readyState === 'loading') { + document.addEventListener('DOMContentLoaded', maybeAddWarning); +} else { + maybeAddWarning(); +}; diff --git a/previews/PR226/examples/custom_study/index.html b/previews/PR226/examples/custom_study/index.html new file mode 100644 index 00000000..9b088ed1 --- /dev/null +++ b/previews/PR226/examples/custom_study/index.html @@ -0,0 +1,53 @@ + +Customizing a Study · PSRClassesInterface.jl

    Customizing a Study

    In this tutorial you will learn how to customize several items of your study.

    How we define the template for our studies

    First of all, it's important to understand how we define the default rules for each collection in our study.

    Let's take a look at the function PSRClassesInterface.create_study for the OpenStudy interface. It has the following signature:

    function create_study(
    +    ::OpenInterface;
    +    data_path::AbstractString = pwd(),
    +    pmd_files::Vector{String} = String[],
    +    pmds_path::AbstractString = PMD._PMDS_BASE_PATH,
    +    defaults_path::Union{AbstractString,Nothing} = PSRCLASSES_DEFAULTS_PATH,
    +    defaults::Union{Dict{String,Any},Nothing} = _load_defaults!(),
    +    netplan::Bool = false,
    +    model_template_path::Union{String,Nothing} = nothing,
    +    study_collection::String = "PSRStudy",
    +)

    From our other examples, you will notice that we have never filled most of these parameters, leaving them with their default values. However, the following are important for working with custom Studies:

    • pmd_files or pmds_path
    • model_template_path
    • defaults_path

    A PMD is a .pmd file where we define collections and the metadata for each of their attributes. A Model Template is a JSON file where we map the name of collections in the PMD to their names in our Study. Finally, Defaults is also a JSON file where we set the default values for some - or all - attributes in collections.

    When we create a study, we parse the PMD file(s) and the Model Template, creating the data.data_struct, a Dict that contains the metadata for attributes and their names.

    When we create an element, PSRI uses data.data_struct to check if the values for the attributes that we have filled are in agreement with their definition(if they should be Vectors, Floats, ...) and if any attribute is missing.

    Defining custom structures with new PMD file

    When you already have your structures defined in a PMD file, you don't need to create them in runtime. First, save this code as a .pmd file, where we define a Study collection, different from PSRStudy and a PSRExtra collection.

    DEFINE_MODEL MODL:Custom_Study_Config
    +	PARM REAL 		Value1
    +	PARM REAL 		Value3
    +	PARM STRING     Text
    +END_MODEL
    +
    +DEFINE_MODEL MODL:Extra_Collection
    +	PARM REAL 		ExtraValue
    +	PARM STRING     Text
    +END_MODEL

    Now we need a Model Template file, to map our PMD Model to collections. Just as we did before, copy the following code into a file, but save it as a .json this time.

    [
    +    {
    +        "classname": "CustomStudy",
    +        "models": ["Custom_Study_Config"]
    +    },
    +    {
    +        "classname": "PSRExtra",
    +        "models": ["Extra_Collection"]
    +    }
    +]

    After that, we can create a Study with PSRClassesInterface.create_study using a few extra mandatory parameters.

    import PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +
    +temp_path = joinpath(tempdir(), "PSRI")
    +json_path = joinpath(path_to_directory, "custom_json.json")
    +
    +data = PSRI.create_study(PSRI.OpenInterface(), 
    +    data_path = temp_path, 
    +    pmds_path = path_to_directory, 
    +    model_template_path = json_path, 
    +    study_collection = "CustomStudy", 
    +    defaults = Dict{String,Any}(
    +        "CustomStudy" => Dict{String,Any}(
    +            "AVId" => "avid", 
    +            "Text" => "custom", 
    +            "Value1" => 1.0, 
    +            "Value3" => 2.0, 
    +            "code" => Int32(10), 
    +            "name" => "name"
    +        )
    +    )
    +)
    +
    diff --git a/previews/PR226/examples/graf_files/index.html b/previews/PR226/examples/graf_files/index.html new file mode 100644 index 00000000..97f785ab --- /dev/null +++ b/previews/PR226/examples/graf_files/index.html @@ -0,0 +1,163 @@ + +Graf Files and Time Series · PSRClassesInterface.jl

    Graf Files and Time Series

    Time Series

    Some attributes in a Study represent a time series indexed by another attribute. Here we will be setting a time series for the attribute EmissionCost, from PSRGasEmission, which is indexed by DateEmissionCost.

    First we create a Dict with EmissionCost and DateEmissionCost data.

    using PSRClassesInterface
    +PSRI = PSRClassesInterface
    +using Dates
    +
    +series = Dict{String,Vector}(
    +    "DateEmissionCost" => [
    +        Dates.Date("1900-01-01"),
    +        Dates.Date("2013-01-01"),
    +        Dates.Date("2013-02-01")
    +    ],
    +    "EmissionCost" => [0.0,3.0,3.0]
    +    )
    Dict{String, Vector} with 2 entries:
    +  "DateEmissionCost" => [Date("1900-01-01"), Date("2013-01-01"), Date("2013-02-…
    +  "EmissionCost"     => [0.0, 3.0, 3.0]

    Then, we save the time series to the study using the function PSRClassesInterface.set_series!. Notice that when we are saving this time series, we are specifying the element from the collection that has this series, using its index.

    temp_path = joinpath(tempdir(), "PSRI")
    +
    +data = PSRI.create_study(PSRI.OpenInterface(), data_path = temp_path)
    +
    +PSRI.create_element!(data, "PSRGasEmission")
    +
    +PSRI.set_series!(
    +    data, 
    +    "PSRGasEmission", 
    +    "DateEmissionCost",
    +    1, # element index in collection
    +    series
    +    )

    Using a SeriesTable

    We can later retrieve the series for the element in the collection with PSRClassesInterface.get_series, which will return a SeriesTable object. It can be later displayed as a table in your terminal.

    When using this function, we need the collection, the element index and the attribute that indexes the elements.

    using DataFrames
    +series_table = PSRI.get_series(
    +    data, 
    +    "PSRGasEmission", 
    +    "DateEmissionCost", 
    +    1 # element index in collection
    +    )
    +
    +DataFrame(series_table)

    Graf files

    The data relative to a Study is usually stored in a JSON file, where an attribute can have its data indexed by time intervals, as presented earlier.

    However, when a time series attribute is multidimensional, it can be too large to be stored in a JSON. For these cases, we save the data in a separate file. We will refer to such file as Graf file. When an attribute has its information in a Graf file, there's an entry in the regular JSON file specifying it.

    In the following example, each PSRDemand object will have its attribute Duracao data associated with a time series, saved in the files duracao.hdr and duracao.bin. Objects are distinguished by the parmid attribute, which in this case has the AVId value of each PSRDemand element.

    A Graf file stores the values of an attribute for every element in a collection. So for this example, all values for the attribute Duracao will be store in the Graf file.

    "PSRGasEmission": [
    +    {
    +        "AVId": "Agent 1"
    +        "name": "psr_name"
    +    },
    +    {
    +        "AVId": "Agent 2"
    +        "name": "psr_name2"
    +    },
    +    {
    +        "AVId": "Agent 3"
    +        "name": "psr_name3"
    +    }
    +],
    +"GrafScenarios": [
    +    {
    +        "classname": "PSRDemand",
    +        "parmid": "AVId",
    +        "vector": "Duracao",
    +        "binary": [ "duracao.hdr", "duracao.bin" ]
    +    }
    +]

    Graf file format

    A Graf file composed of a header and a table with the following elements:

    • Stage
    • Scenario
    • Block
    • Agents (one entry for each agent)

    Each agent represents an element from the collection the graf file is linked to.

    Visual example of a graf file

    Using the previous example with PSRDemand objects, the Duracao for each object will be displayed in the Agents columns, that will take the name of the AVId attribute, resulting on the following:

    StgSceBlockAgent 1Agent 2Agent 3
    1111.05.010.0
    1121.56.511.5
    1132.07.012.0
    ..................

    Graf Header

    A Graf file header contains data about the time series contents. Some important information are whether the time series varies per block and/or per Scenario, the number of agents, the unit of measurement and on which stage it should start.

    Writing a time series into a Graf file

    In this example we will demonstrate how to save a time series into a csv or binary file. First, we create a random array which has the data for a time series:

    import PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +#Creates dummy data
    +n_blocks = 3
    +n_scenarios = 1
    +n_stages = 1
    +n_agents = 1
    +
    +time_series_data = rand(Float64, n_agents, n_blocks, n_scenarios, n_stages)
    +
    +nothing #hide

    There are two ways of saving the data to a file, save the data in the file directly or iteratively. To save the data directly use the function PSRClassesInterface.array_to_file by calling:

    FILE_PATH = joinpath(tempdir(), "example")
    +
    +PSRI.array_to_file(
    +    PSRI.OpenBinary.Writer,
    +    FILE_PATH,
    +    time_series_data,
    +    agents = ["Agent 1", "Agent 2", "Agent 3", "Agent 4", "Agent 5"],
    +    unit = "H";
    +    initial_stage = 3,
    +    initial_year = 2006,
    +)

    To save the data iteractively use the function PSRClassesInterface.open to create an PSRClassesInterface.AbstractWriter. Save the data of each registry to the file using the function PSRClassesInterface.write_registry and then close the data stream calling the function PSRClassesInterface.close.

    iow = PSRI.open(
    +    PSRI.OpenBinary.Writer,
    +    FILE_PATH,
    +    blocks = n_blocks,
    +    scenarios = n_scenarios,
    +    stages = n_stages,
    +    agents = ["Agent 1", "Agent 2", "Agent 3", "Agent 4", "Agent 5"],
    +    unit = "H",
    +    initial_stage = 1,
    +    initial_year = 2006,
    +)
    +
    +for stage = 1:n_stages, scenario = 1:n_scenarios, block = 1:n_blocks
    +    PSRI.write_registry(
    +        iow,
    +        time_series_data[:, block, scenario, stage],
    +        stage,
    +        scenario,
    +        block
    +    )
    +end
    +
    +PSRI.close(iow)

    Reading a time series from a graf file

    A similar logic can be used to read the data from a file. You can read it directly or iteratively. To read the data directly use the function PSRClassesInterface.file_to_array or PSRClassesInterface.file_to_array_and_header

    data_from_file = PSRI.file_to_array(
    +        PSRI.OpenBinary.Reader, 
    +        FILE_PATH;
    +        use_header=false
    +    )
    +
    +@assert all(isapprox.(data_from_file, time_series_data, atol=1E-7))
    +
    +data_from_file_and_header, header = PSRI.file_to_array_and_header(
    +        PSRI.OpenBinary.Reader, 
    +        FILE_PATH;
    +        use_header=false
    +    )
    +@assert all(isapprox.(data_from_file_and_header, time_series_data, atol=1E-7))

    To choose the agents order set use_header to true and label the agents in header.

    data_from_file = PSRI.file_to_array(
    +        PSRI.OpenBinary.Reader, 
    +        FILE_PATH;
    +        use_header=true,
    +        header=["Agent 5", "Agent 2", "Agent 3", "Agent 4", "Agent 1"]
    +    )
    +@assert all(isapprox.(data_from_file[1, :, :, :], time_series_data[end, :, :, :], atol=1E-7))
    +@assert all(isapprox.(data_from_file[end, :, :, :], time_series_data[1, :, :, :], atol=1E-7))

    To read the data iteractively use the function PSRClassesInterface.open to create an PSRClassesInterface.AbstractReader and read each registry iteratively. At the end you should close the PSRClassesInterface.AbstractReader by calling PSRClassesInterface.close

    ior = PSRI.open(
    +    PSRI.OpenBinary.Reader, 
    +    FILE_PATH;
    +    use_header = false
    +)
    +
    +data_from_file = zeros(n_agents, n_blocks, n_scenarios, n_stages)
    +
    +for stage = 1:n_stages, scenario = 1:n_scenarios, block = 1:n_blocks
    +    data_from_file[:, block, scenario, stage] = ior.data
    +    PSRI.next_registry(ior)
    +end
    +
    +PSRI.close(ior)
    +

    Using Graf files in a study

    As presented earlier, an attribute for a collection can have its data stored in a Graf file, all that being specified in the GrafScenarios entry of the study JSON.

    If you have a Graf file that should be linked to a study, you can use the function PSRClassesInterface.link_series_to_file to do so.

    PSRI.create_element!(data, "PSRDemand", "AVId" => "Agent 1")
    +PSRI.create_element!(data, "PSRDemand", "AVId" => "Agent 2")
    +PSRI.create_element!(data, "PSRDemand", "AVId" => "Agent 3")
    +PSRI.create_element!(data, "PSRDemand", "AVId" => "Agent 4")
    +PSRI.create_element!(data, "PSRDemand", "AVId" => "Agent 5")
    +
    +PSRI.link_series_to_file(
    +        data, 
    +        "PSRDemand", 
    +        "Duracao", 
    +        "AVId",
    +        FILE_PATH
    +    )

    Using a GrafTable

    We can retrieve the data stored in a Graf file using the PSRClassesInterface.get_graf_series function. This function returns a GrafTable object.

    When using this function, we need the collection and its attribute that is linked to a Graf file.

    graf_table = PSRI.get_graf_series(
    +        data,
    +        "PSRDemand",
    +        "Duracao";
    +        use_header = false
    +    )

    Once you have a GrafTable object, you can display it as a table in your terminal

    using DataFrames
    +
    +DataFrame(graf_table)

    Vector from graf file

    You can get a vector that corresponds to a row in a Graf file with the values for the agents correspoding to the current stage, scenario and block.

    For that, we will have to use the function PSRClassesInterface.mapped_vector.

    vec = PSRI.mapped_vector(
    +        data, 
    +        "PSRDemand", 
    +        "Duracao",
    +        Float64
    +    )

    The parameters that were used to retrieve the row value in the Graf table can be changed with the following functions:

    These methods don't automatically update the vector. For that, we use the function PSRClassesInterface.update_vectors!, which update all vectors from our Study.

    PSRI.update_vectors!(data)

    However, it might be interesting to update only one or a group of vectors. To be able to do that, we will have to set a filter tag when we create them.

    vec2 = PSRI.mapped_vector(
    +        data, 
    +        "PSRDemand", 
    +        "Duracao",
    +        Float64,
    +        filters = ["test_filter"]
    +    )

    Then, when we run:

    PSRI.update_vectors!(data, "test_filter")

    Comparison between a GrafTable and a SeriesTable

    In this section we have introduced some new concepts about table-like types. That being said, let's review the main differences between GrafTables and SeriesTables:

    • SeriesTable
      • Is linked to a single element from a collection
      • It can have time series of different attributes that are indexed to a single attribute (all belonging to the same element)
    • GrafTable
      • Is linked to the whole collection. So for an attribute, every element in the collection will have an entry in the graf file
      • It has the time series for only one attribute
    diff --git a/previews/PR226/examples/modification/index.html b/previews/PR226/examples/modification/index.html new file mode 100644 index 00000000..d27eaa07 --- /dev/null +++ b/previews/PR226/examples/modification/index.html @@ -0,0 +1,39 @@ + +Modifying a Study · PSRClassesInterface.jl

    Modifying a Study

    In this example we will be showing how to modify your study in runtime, adding/deleting elements, setting relations, ...

    Creating a Study

    You can modify an existing study or a new one with the following functions:

    In this example, we will be working with a new empty study.

    using PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +temp_path = joinpath(tempdir(), "PSRI")
    +
    +data = PSRI.create_study(PSRI.OpenInterface(); data_path = temp_path)

    Adding new elements

    You can only add elements from collections that are available for your study. Here we will be using our default study configuration, but in another example you can learn how to work with a custom study. You can check which collections are available with PSRI.get_collections(data).

    Every study already comes with a PSRStudy element. So now we can add some elements with the function PSRClassesInterface.create_element!, that returns the element's index in the collection.

    bus_1_index   = PSRI.create_element!(data, "PSRBus")
    +serie_1_index = PSRI.create_element!(data, "PSRSerie")

    When not specified, the attributes for the element are filled with their default values. But you can also set them manually. If you need, it is possible to see the attributes for a collection with PSRI.get_attributes(data, COLLECTION).

    bus_2_index = PSRI.create_element!(
    +    data, "PSRBus", 
    +    "name" => "bus_name", 
    +    "Kv" => 1.5, 
    +    "code"=> Int32(98), 
    +    "icca" => Int32(5), 
    +    "AVId" => "bus_id"
    +    )
    +
    +# You don't need to set all attributes
    +
    +bus_3_index = PSRI.create_element!(
    +    data, "PSRBus", 
    +    "code"=> Int32(10), 
    +    )

    Setting relations

    Some collections in a Study can have relations between some of their elements.

    A Relation has a source and a target element. We can check the available relations for an element when it is a source with PSRI.get_relations(COLLECTION). Just as for custom collections, you can learn how to customize relations in another tutorial.

    PSRI.set_related!(
    +    data, 
    +    "PSRSerie", 
    +    "PSRBus", 
    +    serie_1_index, 
    +    bus_1_index , 
    +    relation_type = PSRI.PMD.RELATION_FROM
    +    )
    +
    +PSRI.set_related!(
    +    data, 
    +    "PSRSerie", 
    +    "PSRBus", 
    +    serie_1_index, 
    +    bus_2_index , 
    +    relation_type = PSRI.PMD.RELATION_TO
    +    )

    Deleting elements

    We can delete an element using PSRClassesInterface.delete_element!.

    PSRI.delete_element!(data, "PSRBus", bus_3_index)

    However, if you try to delete an element that has a relation with any other, you will receive an error message.

    PSRI.delete_element!(data, "PSRSerie", serie_1_index)

    <span style="color:red">ERROR:</span> Element PSRSerie cannot be deleted because it has relations with other elements

    So first, you have to check the relations that the element has and delete them.

    To see the relations set to an element, use PSRClassesInterface.relations_summary, which returns a list with the target element, with its index, pointing to the source element, also with its index.

    PSRI.relations_summary(data, "PSRBus", bus_1_index)
    PSRI.relations_summary(data, "PSRBus", bus_2_index)
    PSRI.relations_summary(data, "PSRSerie", serie_1_index)

    Now we know that we have to delete two relations to be able to delete the PSRSerie element. For that, we use PSRClassesInterface.delete_relation!.

    PSRI.delete_relation!(data, "PSRSerie", "PSRBus", serie_1_index, bus_1_index)
    +PSRI.delete_relation!(data, "PSRSerie", "PSRBus", serie_1_index, bus_2_index)

    After that, we can easily delete our PSRSerie element.

    PSRI.delete_element!(data, "PSRSerie", serie_1_index)

    After that we can save our study to a JSON file, which can later be used to load the study again.

    PSRI.write_data(data)
    diff --git a/previews/PR226/examples/reading_demands/index.html b/previews/PR226/examples/reading_demands/index.html new file mode 100644 index 00000000..a309bb3b --- /dev/null +++ b/previews/PR226/examples/reading_demands/index.html @@ -0,0 +1,134 @@ + +Reading Demands · PSRClassesInterface.jl

    Reading Demands

    Determining elasticity and value of demands

    In this example we will read demand segments, obtain the value of demands, discover wheter each demand is elastic or inelastic, and then obtain the sums of demands by elasticity. The first step is to read the study data:

    using PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +PATH_CASE_EXAMPLE_DEM = joinpath(pathof(PSRI) |> dirname |> dirname, "test", "data", "case1")
    +
    +data = PSRI.load_study(
    +    PSRI.OpenInterface(),
    +    data_path = PATH_CASE_EXAMPLE_DEM
    +)

    Whereas the demand varies according to the stage, we must specify the stage by calling go_to_stage:

    target_stage = 1
    +PSRI.go_to_stage(data,target_stage)

    Now, we can read the demand segments and the map between demands and demand segments, and then obtain the value of each demand:

    dem_seg = PSRI.mapped_vector(data, "PSRDemandSegment", "Demanda", Float64, "block")
    +
    +seg2dem = PSRI.get_map(data, "PSRDemandSegment", "PSRDemand", relation_type = PSRI.PMD.RELATION_1_TO_1)
    +
    +dem_size = PSRI.max_elements(data, "PSRDemand")
    +
    +demand_values = zeros(dem_size)
    +
    +for demand = 1:dem_size
    +    demand_values[demand] = sum(dem_seg[i] for i = 1:length(dem_seg) if seg2dem[i] == demand)
    +end
    +
    +demand_values
    1-element Vector{Float64}:
    + 0.38948

    We can discover the elasticity of each demand by calling get_parms with the parameter Elastico:

    demands_elasticity = PSRI.get_parms(data, "PSRDemand", "Elastico", Int32)

    If demands_elasticity[i] == 0 it means that the demand at index i is inelastic, and elastic if demands_elasticity[i] == 1. We can now obtain the total demands of each elasticity:

    total_elastic_demand = 0.0
    +total_inelastic_demand = 0.0
    +
    +for i = 1:dem_size
    +    if demands_elasticity[i] == 0
    +        total_inelastic_demand += demand_values[i]
    +    else
    +        total_elastic_demand += demand_values[i]
    +    end
    +end

    Determining demands values of each bus

    Now we have the values of the demands, we can obtain the values of demand for each bus. Each demand has a set of loads, which define how much of this demand corresponds to each bus. We can begin by reading the loads and its relations with demands and buses:

    loads = PSRI.mapped_vector(data, "PSRLoad", "P", Float64, "block")
    +lod2dem = PSRI.get_map(data, "PSRLoad", "PSRDemand", relation_type = PSRI.PMD.RELATION_1_TO_1)
    +lod2bus = PSRI.get_map(data, "PSRLoad", "PSRBus", relation_type = PSRI.PMD.RELATION_1_TO_1)

    The values of the loads are weights in a kind of a weighted arithmetic mean of the buses for each demand. But the loads of each demand don't add up to 1, so they need to be normalized to represent fractions of the total:

    total_lod_bydem = zeros(dem_size)
    +lod_size = PSRI.max_elements(data, "PSRLoad")
    +
    +for i in 1:lod_size
    +    total_lod_bydem[lod2dem[i]] += loads[i]
    +end
    +
    +for i in 1:lod_size
    +    if total_lod_bydem[lod2dem[i]] > 0.0
    +        loads[i] = loads[i]/total_lod_bydem[lod2dem[i]]
    +    else
    +        loads[i] = 0.0
    +    end
    +end
    +
    +loads
    85-element Vector{Float64}:
    + 0.011461318051575926
    + 0.005730659025787963
    + 0.011461318051575926
    + 0.005730659025787963
    + 0.011461318051575926
    + 0.005730659025787963
    + 0.011461318051575926
    + 0.005730659025787963
    + 0.011461318051575926
    + 0.005730659025787963
    + ⋮
    + 0.011461318051575926
    + 0.011461318051575926
    + 0.011461318051575926
    + 0.011461318051575926
    + 0.011461318051575926
    + 0.005730659025787963
    + 0.005730659025787963
    + 0.011461318051575926
    + 0.005730659025787963

    Now we know the fraction of each demand that corresponds to each bus, and can easily define the total demand by bus:

    bus_size = PSRI.max_elements(data, "PSRBus")
    +
    +dem_bybus = zeros(bus_size)
    +
    +for lod = 1:lod_size
    +    fraction = loads[lod]
    +    dem = lod2dem[lod]
    +    bus = lod2bus[lod]
    +    dem_bybus[bus] += demand_values[dem]*fraction
    +end
    +
    +dem_bybus
    129-element Vector{Float64}:
    + 0.004463954154727791
    + 0.0022319770773638957
    + 0.0
    + 0.004463954154727791
    + 0.0022319770773638957
    + 0.004463954154727791
    + 0.0022319770773638957
    + 0.0
    + 0.004463954154727791
    + 0.0022319770773638957
    + ⋮
    + 0.0
    + 0.0
    + 0.0
    + 0.0
    + 0.0
    + 0.0
    + 0.0
    + 0.0
    + 0.0

    Calculating the energy prices of each thermal plant

    The energy prices in a thermal plant deppends on the the price of the fuel used, the specific consumption of this fuel and Operation and Maintenance cost. Again, we begin by reading the data:

    import PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +PATH_CASE_EXAMPLE_THER_PRICES = joinpath(pathof(PSRI) |> dirname |> dirname, "test", "data", "case1")
    +
    +data = PSRI.load_study(
    +    PSRI.OpenInterface(),
    +    data_path = PATH_CASE_EXAMPLE_THER_PRICES
    +)

    We discover the necessary infos of the thermal plants indirectly through PSRFuelConsumption:

    fuelcons2ther = PSRI.get_map(data,"PSRFuelConsumption", "PSRThermalPlant"; relation_type = PSRI.PMD.RELATION_1_TO_1)
    +
    +ther_size = PSRI.max_elements(data, "PSRThermalPlant")
    +fuelcons_size = PSRI.max_elements(data, "PSRFuelConsumption")
    +ther2fuelcons = [[fc for fc = 1:fuelcons_size if fuelcons2ther[fc] == t] for t = 1:ther_size]

    Next, we get the O&M cost, the specific consumption and the relation with fuels of our fuels consumptions. Then we get the cost of each fuel. After calling mapped_vector we must call update_vectors!.

    om_cost = PSRI.mapped_vector(data, "PSRFuelConsumption", "O&MCost", Float64)
    +spec_consum = PSRI.mapped_vector(data, "PSRFuelConsumption", "CEsp", Float64, "segment", "block")
    +fuelcons2fuel = PSRI.get_map(data, "PSRFuelConsumption", "PSRFuel"; relation_type = PSRI.PMD.RELATION_1_TO_1)
    +fuel_cost = PSRI.mapped_vector(data, "PSRFuel", "Custo", Float64)
    +
    +PSRI.update_vectors!(data)

    Now we can calculate the price of the energy unity of each fuel consumption for each thermal plant:

    ther_prices = [zeros(0) for _ = 1:ther_size]
    +for ther = 1:ther_size
    +    n_fuelcons = length(ther2fuelcons[ther])
    +    prices = zeros(n_fuelcons)
    +    for i = 1:n_fuelcons
    +        fuelcons = ther2fuelcons[ther][i]
    +        fuel = fuelcons2fuel[fuelcons]
    +        prices[i] = om_cost[fuelcons] + spec_consum[fuelcons]*fuel_cost[fuel]
    +    end
    +    ther_prices[ther] = prices
    +end
    +ther_prices
    5-element Vector{Vector{Float64}}:
    + [100.0]
    + [20.0]
    + [40.0]
    + [60.0]
    + [80.0]
    diff --git a/previews/PR226/examples/reading_parameters/index.html b/previews/PR226/examples/reading_parameters/index.html new file mode 100644 index 00000000..3fcfad1a --- /dev/null +++ b/previews/PR226/examples/reading_parameters/index.html @@ -0,0 +1,55 @@ + +Reading parameters · PSRClassesInterface.jl

    Reading parameters

    Reading configuration parameters

    Most cases have configuration parameters such as the maximum number of iterations, the discount rate, the deficit cost etc. The function PSRClassesInterface.configuration_parameter reads all the parameters from the cases.

    import PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +PATH_CASE_EXAMPLE_CONFIGS = joinpath(pathof(PSRI) |> dirname |> dirname, "test", "data", "case0")
    +
    +data = PSRI.load_study(
    +    PSRI.OpenInterface(),
    +    data_path = PATH_CASE_EXAMPLE_CONFIGS
    +)
    +
    +PSRI.configuration_parameter(data, "TaxaDesconto", 0.0)
    +PSRI.configuration_parameter(data, "MaximoIteracoes", 0)
    +PSRI.configuration_parameter(data, "MaximoIteracoes", 0)
    +PSRI.configuration_parameter(data, "MinOutflowPenalty", 0.0)
    +PSRI.configuration_parameter(data, "DeficitCost", [0.0])

    Reading basic thermal generator parameters

    In this example we will map parameters of thermal generators at each stage of the study to a struct. Suppose in this case that our thermal generators has the following attributes:

    Base.@kwdef mutable struct ThermalGenerators
    +    names::Vector{String} = String[]
    +    codes::Vector{Int32} = Int32[]
    +    generation_capacities::Vector{Float64} = Float64[]
    +    therm2sys::Vector{Int32} = Int32[]
    +end

    The first thing we must do is to initialize the reading procedure with the following commands:

    import PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +PATH_CASE_EXAMPLE_THERMALS = joinpath(pathof(PSRI) |> dirname |> dirname, "test", "data", "case0")
    +
    +data = PSRI.load_study(
    +    PSRI.OpenInterface(),
    +    data_path = PATH_CASE_EXAMPLE_THERMALS
    +)

    We can initialize the struct with the parameters of the first stage using the function PSRClassesInterface.mapped_vector

    therm_gen = ThermalGenerators()
    +therm_gen.names = PSRI.get_name(data, "PSRThermalPlant")
    +therm_gen.codes = PSRI.get_code(data, "PSRThermalPlant")
    +therm_gen.generation_capacities = PSRI.mapped_vector(data, "PSRThermalPlant", "PotInst", Float64)
    +therm_gen.therm2sys = PSRI.get_map(data, "PSRThermalPlant", "PSRSystem")

    And afterwards we can update the parameters for each stage as follows.

    for stage in 1:PSRI.total_stages(data)
    +    PSRI.go_to_stage(data, stage)
    +    PSRI.update_vectors!(data)
    +    println("Thermal generator 2 generation capacity at stage $stage $(therm_gen.generation_capacities[2])")
    +end
    Thermal generator 2 generation capacity at stage 1 5.0
    +Thermal generator 2 generation capacity at stage 2 5.0

    Reading basic battery parameters

    This example is very similar to "Reading basic thermal generator parameters", but it is necessary to be cautious about the difference between elements. For instance, batteries have different parameters than thermal generators, therefore, our data structure must be defined accordingly:

    Base.@kwdef mutable struct Batteries
    +    names::Vector{String} = String[]
    +    codes::Vector{Int32} = Int32[]
    +    charge_eff::Vector{Float64} = Float64[]
    +    bat2sys::Vector{Int32} = Int32[]
    +end

    Stardard proceadure of reading data from file:

    import PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +PATH_CASE_EXAMPLE_BATTERIES = joinpath(pathof(PSRI) |> dirname |> dirname, "test", "data", "case1")
    +
    +data = PSRI.load_study(
    +    PSRI.OpenInterface(),
    +    data_path = PATH_CASE_EXAMPLE_BATTERIES
    +)

    And now the struct may be instantiated by setting its appropriate parameters:

    batteries = Batteries()
    +batteries.names = PSRI.get_name(data, "PSRBattery")
    +batteries.codes = PSRI.get_code(data, "PSRBattery")
    +batteries.charge_eff = PSRI.mapped_vector(data, "PSRBattery", "ChargeEffic", Float64)
    +batteries.bat2sys = PSRI.get_map(data, "PSRBattery", "PSRSystem")
    diff --git a/previews/PR226/examples/reading_relations/index.html b/previews/PR226/examples/reading_relations/index.html new file mode 100644 index 00000000..281cf8cb --- /dev/null +++ b/previews/PR226/examples/reading_relations/index.html @@ -0,0 +1,48 @@ + +Reading Relations · PSRClassesInterface.jl

    Reading Relations

    Introduction to the PSRClassesInterface.get_map method

    There are two dispatches for the PSRClassesInterface.get_map function. The first requires the attribute name that represents the relation, while the second needs the PSRClassesInterface.PMD.RelationType between the elements.

    Here is how this function works:

    Let's say that in our study we have 3 PSRSerie and 2 PSRBus elements. There is a relation between elements of these two collections represented by an attribute 'no2', where PSRSerie is the source and PSRBus is the target.

    If we execute the following code:

    using PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +PSRI.create_element!(data, "PSRSerie")
    +PSRI.create_element!(data, "PSRSerie")
    +PSRI.create_element!(data, "PSRSerie")
    +PSRI.create_element!(data, "PSRBus")
    +PSRI.create_element!(data, "PSRBus")
    +
    +PSRI.set_related!(data, "PSRSerie", "PSRBus", 1, 2, relation_type = PSRI.PMD.RELATION_TO)
    +PSRI.set_related!(data, "PSRSerie", "PSRBus", 3, 1, relation_type = PSRI.PMD.RELATION_TO)
    +
    +PSRI.get_map(data, "PSRSerie", "PSRBus", "no2")

    We could, as an example, get the following vector:

    [ 2 , 0 , 1 ]

    This means that:

    • the source element of index 1 in the collection PSRSerie is related to the target element of index 2 in the collection PSRBus.
    • the source element of index 2 in the collection PSRSerie is not related to any element from collection PSRBus
    • the source element of index 3 in the collection PSRSerie is related to the target element of index 1 in the collection PSRBus.

    Note: There is also a PSRClassesInterface.get_vector_map method that works just as PSRClassesInterface.get_map.

    Now we can move to a more practical example.

    Determining subsystem from a certain hydro plant

    In this example we will demonstrate how to make a simple use of a relationship map. That will be achieved by determining a subsystem from a certain hydro plant through its parameters. The program will initiate by the standard reading procedure:

    
    +PATH_CASE_EXAMPLE_GAUGING = joinpath(pathof(PSRI) |> dirname |> dirname, "test", "data", "case2")
    +
    +data = PSRI.load_study(
    +    PSRI.OpenInterface(),
    +    data_path = PATH_CASE_EXAMPLE_GAUGING
    +)
    +; nothing # hide

    Next, the maps between hydroplants and systems is retrieved by the get_map method:

    hyd2sys = PSRI.get_map(data, "PSRHydroPlant","PSRSystem", "system")
    +; nothing # hide

    Determining buses from a certain thermal plant

    This case consists of a more advanced use of a relationship map. We'll determine which buses are linked to a given target thermal plant, while there is no direct relationship between both. Firstly, the study data is read:

    import PSRClassesInterface
    +const PSRI = PSRClassesInterface
    +
    +PATH_CASE_EXAMPLE_BUS = joinpath(pathof(PSRI) |> dirname |> dirname, "test", "data", "case1")
    +
    +data = PSRI.load_study(
    +    PSRI.OpenInterface(),
    +    data_path = PATH_CASE_EXAMPLE_BUS
    +)

    Whereas there is no direct link between buses and thermal plants, both are indirectly related through generators. Therefore, we must identify those relationships by calling get_map for each:

    gen2thermal = PSRI.get_map(data, "PSRGenerator","PSRThermalPlant", "plant")
    +gen2bus = PSRI.get_map(data, "PSRGenerator", "PSRBus", "bus")

    Next, we can find which generators are linked to our target thermal plant by the indexes of gen2the:

    target_thermal = 1
    +target_generator = findall(isequal(target_thermal), gen2thermal)

    target_generator now holds the indexes of generators that are linked to the buses we are trying to identify. With those at hand, the indexes of the buses are easily identifiable by:

    targetBus = gen2bus[target_generator]

    Determining which buses are connected by each circuit

    Each circuit connects two buses, it starts from a bus and goes to another. In this example we'll discover these buses for each circuit and then we'll build an incidence matrix of buses by circuits. The first step is to read the data:

    
    +PATH_CASE_EXAMPLE_CIR_BUS = joinpath(pathof(PSRI) |> dirname |> dirname, "test", "data", "case1")
    +
    +data = PSRI.load_study(
    +    PSRI.OpenInterface(),
    +    data_path = PATH_CASE_EXAMPLE_CIR_BUS
    +)
    +; nothing # hide

    Next, we get from which bus each circuit starts and which bus it goes to with get_map:

    cir2bus_to = PSRI.get_map(data, "PSRSerie", "PSRBus", "no1")
    +cir2bus_from = PSRI.get_map(data, "PSRSerie", "PSRBus", "no2")
    +; nothing # hide

    Now we can build the incidence matrix. Each row corresponds to a circuit and each column corresponds to a bus. The element at the index (i,j) is -1 if the circuit i starts from the bus j, 1 if it goes to this bus, and 0 if they both have no relation:

    bus_size = PSRI.max_elements(data, "PSRBus")
    +cir_size = PSRI.max_elements(data, "PSRSerie")
    +incidence_matrix = zeros(Float64, cir_size, bus_size)
    +for cir = 1:cir_size
    +    incidence_matrix[cir, cir2bus_from[cir]] = -1.0
    +    incidence_matrix[cir, cir2bus_to[cir]] = 1.0
    +end
    +incidence_matrix
    diff --git a/previews/PR226/index.html b/previews/PR226/index.html new file mode 100644 index 00000000..d626dc9e --- /dev/null +++ b/previews/PR226/index.html @@ -0,0 +1,4 @@ + +Home · PSRClassesInterface.jl

    PSRClassesInterface Documentation

    PSRClassesInterface, or PSRI, is a Julia package that provides an interface to read and write open-source formats for PSR models. It is comprised of three main modules:

    • OpenStudy: Reads and writes data in the JSON format
    • OpenBinary: Reads and writes time series data in the binary format
    • PSRDatabaseSQLite: Reads and writes data in the SQL format

    Installation

    This package is registered so you can simply add it using Julia's Pkg manager:

    julia> import Pkg
    +
    +julia> Pkg.add("PSRClassesInterface")

    Contributing

    Users are encouraged to contributing by opening issues and opening pull requests. If you wish to implement a feature please follow the JuMP Style Guide

    diff --git a/previews/PR226/manual/index.html b/previews/PR226/manual/index.html new file mode 100644 index 00000000..b733600e --- /dev/null +++ b/previews/PR226/manual/index.html @@ -0,0 +1,343 @@ + +Manual · PSRClassesInterface.jl

    Manual

    The PSRClassesInterface module provides interfaces to access data structured by PSR to be used in its models. Currently there are two main interfaces.

    • The interface for studies. This interface is designed to read parameters from the files, some examples are deficit costs, fuel costs, currency, storage capacity etc.
    • The interface for reading and writing time series data. Time series data in the context of most studies have 4 dimensions (agents, stages, scenarios and blocks). Since studies of renewables with multiple agents, scenarios and stages can get quite big, we have designed different formats that are optimized to some objective (human readability, size, fast reading and writing, etc.).

    Both interfaces are defined as a set of methods that need to be implemented to make a different file format work. In this manual we will describe the abstract methods and give concrete examples of code to perform the work needed.

    When using the PSRClassesInterface package in your codebase we strongly advise you to create a constant PSRI to keep the code concise and explicitly declare that a certain function came from PSRClassesInterface. This can be done by adding the following code to the top of the code

    using PSRClassesInterface
    +const PSRI = PSRClassesInterface

    Initialize Study

    PSRClassesInterface.load_studyFunction
    load_study(::AbstractStudyInterface; kwargs...)

    Initialize all data structures of the study.

    Differences between the OpenInterface and ClassicInterface

    Each study interface has its own set of kwargs... The easiest way to inspect the current available options is searching for this function on the Github repo of the desired interface.

    Example:

    data = PSRI.load_study(
    +    PSRI.OpenInterface();
    +    data_path = PATH_CASE_EXAMPLE_BATTERIES,
    +)
    source
    PSRClassesInterface.max_elementsFunction
    max_elements(data::AbstractData, collection::String)

    Returns an Int32 with the maximum number of elements for a given collection.

    Example:

    PSRI.max_elements(data, "PSRThermalPlant")
    source

    Study dimensions

    PSRClassesInterface.StageTypeType
    PSRI.StageType

    Possible stage types used in for reading and writing time series files.

    The current possible stage types are:

    STAGE_UNKNOWN
    +STAGE_WEEK
    +STAGE_MONTH
    +STAGE_3MONTHS
    +STAGE_HOUR
    +STAGE_DAY
    +STAGE_13MONTHS
    +STAGE_2MONTHS
    +STAGE_4MONTHS
    +STAGE_6MONTHS
    +STAGE_YEAR
    +STAGE_DECADE
    source

    Study duration and blocking

    PSRClassesInterface.BlockDurationMode
    +PSRClassesInterface.stage_duration
    +PSRClassesInterface.block_duration
    +PSRClassesInterface.block_from_stage_hour

    Read Scalar Attributes

    PSRClassesInterface.configuration_parameterFunction
    configuration_parameter(
    +    data::AbstractData,
    +    attribute::String,
    +    default::T
    +) where T <: MainTypes

    Returns the required configuration parameter from the case. If the parameter is not registered returns the default value.

    configuration_parameter(
    +    data::AbstractData,
    +    attribute::String,
    +    default::Vector{T},
    +) where T <: MainTypes

    Returns the rquired configuration parameters from the case that are vectors that are vectors. If the parameter is not registered returns the default value.

    Examples:

    PSRI.configuration_parameter(data, "MaximoIteracoes", 0)
    +PSRI.configuration_parameter(data, "MinOutflowPenalty", 0.0)
    PSRI.configuration_parameter(data, "DeficitCost", [0.0])
    source
    PSRClassesInterface.get_codeFunction
    get_code(data::AbstractData, collection::String)

    Returns a Vector{Int32} containing the code of each element in collection.

    Example:

    PSRI.get_code(data, "PSRThermalPlant")
    source
    PSRClassesInterface.get_nameFunction
    get_name(data::AbstractData, collection::String)

    Returns a Vector{String} containing the name of each element in collection.

    Example:

    PSRI.get_name(data, "PSRThermalPlant")
    +PSRI.get_name(data, "PSRGaugingStation")
    source
    PSRClassesInterface.get_parmFunction
    get_parm(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    index::Integer,
    +    ::Type{T};
    +    default::T = _default_value(T),
    +) where T

    Returns a T containing the the value from attribute of collection. This function is used to get data from collections that don't vary over time.

    Example:

    PSRI.get_parm(data, "PSRBattery", "Einic", Float64, 1)
    +PSRI.get_parm(data, "PSRBattery", "ChargeRamp", Float64, 1)
    +PSRI.get_parm(data, "PSRBattery", "DischargeRamp", Float64, 1)
    source
    PSRClassesInterface.get_parm_1dFunction
    get_parm_1d(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    index::Integer,
    +    ::Type{T};
    +    default::T = _default_value(T),
    +) where T

    Returns a T containing the the value from attribute of collection. This function is used to get data from collections that don't vary over time.

    Example:

    PSRI.get_parm_1d(data, "PSRHydroPlant", "FP", Float64, 1)
    +PSRI.get_parm_1d(data, "PSRHydroPlant", "FP.VOL", Float64, 1)
    source
    PSRClassesInterface.get_parmsFunction
    get_parms(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    ::Type{T};
    +    validate::Bool = true,
    +    ignore::Bool = false,
    +    default::T = _default_value(T),
    +) where T

    Returns a Vector{T} containing the elements in collection to a vector in julia. This function is used to get data from collections that don't vary over time

    Example:

    PSRI.get_parms(data, "PSRBattery", "Einic", Float64)
    +PSRI.get_parms(data, "PSRBattery", "ChargeRamp", Float64)
    +PSRI.get_parms(data, "PSRBattery", "DischargeRamp", Float64)
    source
    PSRClassesInterface.get_parms_1dFunction
    get_parms_1d(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    ::Type{T};
    +    validate::Bool = true,
    +    ignore::Bool = false,
    +    default::T = _default_value(T),
    +) where T

    Returns a Vector{T} containing the elements in collection to a vector in julia. This function is used to get data from collections that don't vary over time

    Example:

    PSRI.get_parm_1d(data, "PSRHydroPlant", "FP", Float64)
    +PSRI.get_parm_1d(data, "PSRHydroPlant", "FP.VOL", Float64)
    source

    Read Vector Attributes

    Time controller

    PSRClassesInterface.mapped_vectorFunction
    mapped_vector(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    ::Type{T},
    +    dim1::String="",
    +    dim2::String="";
    +    ignore::Bool=false,
    +    map_key = collection, # reference for PSRMap pointer, if empty use class name
    +    filters = String[], # for calling just within a subset instead of the full call
    +) where T

    Maps a Vector{T} containing the elements in collection to a vector in julia. When the function update_vectors! is called the elements of the vector will be updated to the according elements registered at the current data.time_controller.

    Example:

    existing = PSRI.mapped_vector(data, "PSRThermalPlant", "Existing", Int32)
    +pot_inst = PSRI.mapped_vector(data, "PSRThermalPlant", "PotInst", Float64)

    For more information please read the example Reading basic thermal generator parameters

    Differences between the OpenInterface and ClassicInterface

    When using mapped_vector in the OpenInterface mode the vector will be mapped with the correct values at first hand. When using mapped_vector in the ClassicInterface mode you should call update_vectors! to get the good values for the collection, otherwise you might only get a vector of zeros.

    source
    PSRClassesInterface.go_to_dimensionFunction
    go_to_dimension(data::AbstractData, name::String, value::Integer)

    Moves time controller reference of vectors indexed by dimension name to the index value.

    Example:

    cesp = PSRI.mapped_vector(data, "PSRThermalPlant", "CEsp", Float64, "segment", "block")
    +
    +PSRI.go_to_stage(data, 1)
    +
    +PSRI.go_to_dimension(data, "segment", 1)
    +PSRI.go_to_dimension(data, "block", 1)
    source
    PSRClassesInterface.update_vectors!Function
    update_vectors!(data::AbstractData)

    Update all mapped vectors according to the time controller inside data.

    update_vectors!(data::AbstractData, filters::Vector{String})

    Update filtered classes of mapped vectors according to the time controller inside data.

    source

    Direct access

    PSRClassesInterface.get_vectorFunction
    PSRI.get_vector(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    index::Integer,
    +    ::Type{T};
    +    default::T = _default_value(T),
    +) where T

    Returns a Vector{T} of entries of the attribute of collection at the element with index index.

    Example:

    PSRI.get_vector(data, "PSRGaugingStation", "Vazao", 1, Float64)
    +PSRI.get_vector(data, "PSRGaugingStation", "Data", 1, Dates.Date)
    source
    PSRClassesInterface.get_vector_1dFunction
    PSRI.get_vector_1d(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    index::Integer,
    +    ::Type{T};
    +    default::T = _default_value(T),
    +) where T

    Returns a Vector{Vector{T}} of entries of the attribute of collection at the element with index index. The outer vector contains one entry per index in dimension 1, while the inner vector is sized according to the main vector index which is tipicaaly time.

    Example:

    PSRI.get_vector_1d(data, "PSRArea", "Export", 1, Float64)
    +PSRI.get_vector_1d(data, "PSRLoad", "P", 1, Float64)
    source
    PSRClassesInterface.get_vector_2dFunction
    PSRI.get_vector_2d(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    index::Integer,
    +    ::Type{T};
    +    default::T = _default_value(T),
    +) where T

    Returns a Matrix{Vector{T}} of entries of the attribute of collection at the element with index index. The outer matrix contains one entry per index in dimension 1 and dimension 2, while the inner vector is sized according to the main vector index which is tipicaaly time.

    Example:

    PSRI.get_vector_2d(data, "PSRThermalPlant", "CEsp", 1, Float64)
    +PSRI.get_vector_2d(data, "PSRFuelConsumption", "CEsp", 1, Float64)
    source
    PSRClassesInterface.get_vectorsFunction
    PSRI.get_vectors(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    ::Type{T};
    +    default::T = _default_value(T),
    +) where T

    Returns a Vector{Vector{T}} of entries of the attribute of collection. Each entry of the outer vector corresponding to an element of the collection.

    Example:

    PSRI.get_vectors(data, "PSRGaugingStation", "Vazao", Float64)
    +PSRI.get_vectors(data, "PSRGaugingStation", "Data", Dates.Date)
    source
    PSRClassesInterface.get_vectors_1dFunction
    PSRI.get_vectors_1d(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    ::Type{T},
    +) where T

    Returns a Vector{Vector{Vector{T}}} of entries of the attribute of collection. Each entry of the outer vector corresponding to an element of the collection. For the containt of the 2 inner vectors see get_vector_1d.

    Example:

    PSRI.get_vectors_1d(data, "PSRArea", "Export", Float64)
    +PSRI.get_vectors_1d(data, "PSRLoad", "P", Float64)
    source
    PSRClassesInterface.get_vectors_2dFunction
    PSRI.get_vectors_2d(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +    ::Type{T},
    +) where T

    Returns a Vector{Matrix{Vector{T}}} of entries of the attribute of collection. Each entry of the outer vector corresponding to an element of the collection. For the containt of the Matrix{Vector{T}} see get_vector_2d.

    Example:

    PSRI.get_vectors_2d(data, "PSRThermalPlant", "CEsp", Float64)
    +PSRI.get_vectors_2d(data, "PSRFuelConsumption", "CEsp", Float64)
    source
    PSRClassesInterface.get_nonempty_vectorFunction
    get_nonempty_vector(
    +    data::AbstractData,
    +    colllection::String,
    +    attribute::String,
    +)

    Returns a vector of booleans with the number of elements of the collection. true means the vector associated with the given attribute is non-emepty, false means it is empty.

    Example:

    PSRI.get_nonempty_vector(data, "PSRThermalPlant", "ChroGerMin")
    +PSRI.get_nonempty_vector(data, "PSRThermalPlant", "SpinningReserve")
    source
    PSRClassesInterface.get_seriesFunction
    function get_series(
    +    data::Data,
    +    collection::String,
    +    indexing_attribute::String,
    +    index::Int,
    +)

    Retrieves a SeriesTable object with all attributes from an element that are indexed by index_attr.

    Example

    julia> PSRI.get_series(data, "PSRThermalPlant", "Data", 1)
    +Dict{String, Vector} with 13 entries:
    +  "GerMin"   => [0.0]
    +  "GerMax"   => [888.0]
    +  "NGas"     => [nothing]
    +  "IH"       => [0.0]
    +  "ICP"      => [0.0]
    +  "Data"     => ["1900-01-01"]
    +  "CoefE"    => [1.0]
    +  "PotInst"  => [888.0]
    +  "Existing" => [0]
    +  "sfal"     => [0]
    +  "NAdF"     => [0]
    +  "Unidades" => [1]
    +  "StartUp"  => [0.0]
    source

    Relations between collections

    Missing docstring.

    Missing docstring for PSRClassesInterface.RelationType. Check Documenter's build log for details.

    PSRClassesInterface.get_referencesFunction
    get_references(
    +    data::AbstractData,
    +    lst_from::String,
    +    lst_to::String;
    +    relation_type::RelationType = RELATION_1_TO_1, # type of the direct relation
    +)

    Retrurn a Vector{String} with the references between collections given a certain RelationType.

    source
    PSRClassesInterface.get_vector_referencesFunction
    get_vector_references(
    +    data::AbstractData,
    +    lst_from::String,
    +    lst_to::String;
    +    relation_type::RelationType = RELATION_1_TO_N, # type of the direct relation
    +)

    Retrurn a Vector{Vector{String}} with the references between collections given a certain RelationType.

    source
    PSRClassesInterface.get_mapFunction
    get_map(
    +    data::AbstractData,
    +    lst_from::String,
    +    lst_to::String;
    +    allow_empty::Bool = true,
    +    relation_type::RelationType = RELATION_1_TO_1, # type of the direct relation
    +)

    Returns a Vector{Int32} with the map between collections given a certain RelationType. If the map is a vector [3, 2, 1] it means that the element 1 of lst_from is related to the element 3 of lst_to. If the relation does not exist it might return -1 or some garbage value.

    Examples:

    PSRI.get_map(data, "PSRBattery", "PSRSystem")
    +PSRI.get_map(data, "PSRMaintenanceData", "PSRThermalPlant")
    +
    +PSRI.get_map(
    +    data,
    +    "PSRHydroPlant",
    +    "PSRHydroPlant";
    +    relation_type = PSRI.PMD.RELATION_TURBINE_TO,
    +)
    +PSRI.get_map(
    +    data,
    +    "PSRHydroPlant",
    +    "PSRHydroPlant";
    +    relation_type = PSRI.PMD.RELATION_SPILL_TO,
    +)
    +PSRI.get_map(
    +    data,
    +    "PSRHydroPlant",
    +    "PSRHydroPlant";
    +    relation_type = PSRI.PMD.RELATION_INFILTRATE_TO,
    +)
    +PSRI.get_map(
    +    data,
    +    "PSRHydroPlant",
    +    "PSRHydroPlant";
    +    relation_type = PSRI.PMD.RELATION_STORED_ENERGY_DONWSTREAM,
    +)
    source
    PSRClassesInterface.get_vector_mapFunction
    get_vector_map(
    +    data::AbstractData,
    +    collection_from::String,
    +    collection_to::String;
    +    relation_type::RelationType = RELATION_1_TO_N,
    +)

    Returns a Vector{Vector{Int32}} to represent the relation between each element of collection_from to multiple elements of collection_to.

    Since multiple relations might be available one might need to specify relation_type.

    Example:

    PSRI.get_vector_map(data, "PSRInterconnectionSumData", "PSRInterconnection")
    +PSRI.get_vector_map(data, "PSRReserveGenerationConstraintData", "PSRHydroPlant")
    +PSRI.get_vector_map(
    +    data,
    +    "PSRReserveGenerationConstraintData",
    +    "PSRThermalPlant";
    +    relation_type = PSRI.PMD.RELATION_BACKED,
    +)
    source
    PSRClassesInterface.get_reverse_mapFunction
    get_reverse_map(
    +    data::AbstractData,
    +    lst_from::String,
    +    lst_to::String;
    +    original_relation_type::RelationType = RELATION_1_TO_1,
    +)

    Obtains the relation between lst_from and lst_to though original_relation_type. But returns a Vector{Int32} with the relation reversed. Some relations cannot be reversed this way since they are not bijections, in this case use get_reverse_vector_map.

    See also get_map, get_vector_map, get_reverse_vector_map.

    Example:

    PSRI.get_reverse_map(data, "PSRMaintenanceData", "PSRHydroPlant")
    +# which is te reverse of
    +PSRI.get_map(data, "PSRMaintenanceData", "PSRHydroPlant")
    +
    +PSRI.get_reverse_map(data, "PSRGenerator", "PSRThermalPlant")
    +# which is the reverse of
    +PSRI.get_map(data, "PSRGenerator", "PSRThermalPlant")
    source
    PSRClassesInterface.get_reverse_vector_mapFunction
    get_reverse_vector_map(
    +    data::AbstractData,
    +    lst_from::String,
    +    lst_to::String;
    +    original_relation_type::RelationType = RELATION_1_TO_N,
    +)

    Obtains the relation between lst_from and lst_to though original_relation_type. But returns a Vector{Vector{Int32}} with the relation reversed.

    Some relations are bijections, in these cases it is also possible to use use get_reverse_map.

    See also get_map, get_vector_map, get_reverse_vector_map.

    Example:

    # upstream turbining hydros
    +PSRI.get_reverse_vector_map(
    +    data,
    +    "PSRHydroPlant",
    +    "PSRHydroPlant";
    +    original_relation_type = PSRI.PMD.RELATION_TURBINE_TO,
    +)
    +# which is the reverse of
    +PSRI.get_map(
    +    data,
    +    "PSRHydroPlant",
    +    "PSRHydroPlant";
    +    relation_type = PSRI.PMD.RELATION_TURBINE_TO,
    +)
    +
    +PSRI.get_reverse_vector_map(
    +    data,
    +    "PSRGenerator",
    +    "PSRBus";
    +    original_relation_type = PSRI.PMD.RELATION_1_TO_1,
    +)
    +# which is the reverse of
    +PSRI.get_map(data, "PSRGenerator", "PSRBus")
    source
    PSRClassesInterface.get_relatedFunction
    get_related(
    +    data::AbstractData,
    +    source::String,
    +    target::String,
    +    source_index::Integer,
    +    relation_type = RELATION_1_TO_1,
    +)

    Returns the index of the element in collection target related to the element in the collection source element indexed by source_index according to the scalar relation relation_type.

    source
    PSRClassesInterface.get_vector_relatedFunction
    get_vector_related(
    +    data::AbstractData,
    +    source::String,
    +    target::String,
    +    source_index::Integer,
    +    relation_type = RELATION_1_TO_N,
    +)

    Returns the vector of indices of the elements in collection target related to the element in the collection source element indexed by source_index according to the scalar relation relation_type.

    source

    Reflection

    PSRClassesInterface.get_attribute_dim1Function
    get_attribute_dim1(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::string,
    +    index::Integer;
    +)

    Returns the size of dimension 1 of attribute from collection at element index. Errors if attribute has zero dimensions.

    source
    PSRClassesInterface.get_attribute_dim2Function
    get_attribute_dim2(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::string,
    +    index::Integer;
    +)

    Returns the size of dimension 2 of attribute from collection at element index. Errors if attribute has zero or one dimensions.

    source
    PSRClassesInterface.get_attribute_structFunction
    get_attribute_struct(
    +    data::AbstractData,
    +    collection::String,
    +    attribute::String,
    +)

    Returns a struct of type Attribute with fields:

    • name::String = attribute name
    • is_vector::Bool = true if attribute is a vector (tipically, varies in time)
    • type::DataType = attribute type (tipically: Int32, Float64, String, Dates.Date)
    • dim::Int = number of additional dimensions
    • index::String = if a vector represents the indexing vector (might be empty)
    source
    PSRClassesInterface.get_data_structFunction
    get_attribute_struct(data::AbstractData)

    Return a struct of type DataStruct with collection names (strings) as keys and maps from attributes names (string) to attributes data definitions Attribute.

    source
    PSRClassesInterface.get_attributes_indexed_byFunction
    get_attributes_indexed_by(
    +    data::AbstractData,
    +    collection::String,
    +    indexing_attribute::String
    +)

    Return Vector{String} of valid vector attributes from collection that are indexed by indexing_attribute.

    source
    PSRClassesInterface.get_relationsFunction
    get_relations(data::AbstractData, collection::String)

    Returns a Tuple{String, Vector{PMD.Relation}} with relating collection and their relation type associated to collection.

    source

    Read and Write Graf files

    Open and Close

    PSRClassesInterface.openFunction
    PSRI.open(::Type{<:AbstractWriter}, path::String; kwargs...)

    Method for opening file and registering time series data. If specified file doesn't exist, the method will create it, otherwise, the previous one will be overwritten. Returns updated AbstractWriter instance.

    Arguments:

    • writer: AbstractWriter instance to be used for opening file.

    • path: path to file.

    Keyword arguments:

    • blocks: case's number of blocks.

    • scenarios: case's number of scenarios.

    • stages: case's number of stages.

    • agents: list of element names.

    • unit: dimension of the elements' data.

    • is_hourly: if data is hourly. If yes, block dimension will be ignored.

    • hour_discretization: sub-hour parameter to discretize an hour into minutes.

    • name_length: length of element names.

    • block_type: case's type of block.

    • scenarios_type: case's type of scenario.

    • stage_type: case's type of stage.

    • initial_stage: stage at which to start registry.

    • initial_year: year at which to start registry.

    • allow_unsafe_name_length: allow element names outside safety bounds.

    Examples:

    Method for opening file and reading time series data. Returns updated AbstractReader instance.

    Arguments:

    • reader::Type{<:AbstractReader}: AbstractReader instance to be used for opening file.

    • path::String: path to file.

    Keyword arguments:

    • is_hourly::Bool: if data to be read is hourly, other than blockly.

    • stage_type::PSRI.StageType: the PSRClassesInterface.StageType of the data, defaults to PSRI.STAGE_MONTH.

    • header::Vector{String}: if file has a header with metadata.

    • use_header::Bool: if data from header should be retrieved.

    • first_stage::Dates.Date: stage at which start reading.

    • verbose_header::Bool: if data from header should be displayed during execution.

    Examples:

    source

    Write entire file

    Write registry

    PSRClassesInterface.write_registryFunction
    PSRI.write_registry(
    +    iow::AbstractWriter,
    +    data::Vector{T},
    +    stage::Integer,
    +    scenario::Integer = 1,
    +    block::Integer = 1,
    +) where T <: Real

    Writes a data row into opened file through PSRClassesInterface.AbstractWriter instance.

    Arguments:

    • iow: PSRI.AbstractWriter instance to be used for accessing file.

    • data: elements data to be written.

    • stage: stage of the data to be written.

    • scenario: scenarios of the data to be written.

    • block: block of the data to be written.

    source

    Header information

    Read entire file

    PSRClassesInterface.file_to_arrayFunction
    PSRI.file_to_array(::Type{T}, path::String; use_header::Bool = true, header::Vector{String} = String[]) where T <: AbstractReader

    Write a file to an array

    source

    Read registry

    PSRClassesInterface.gotoFunction
    PSRI.goto(
    +    ior::AbstractReader, 
    +    t::Integer, 
    +    s::Integer = 1, 
    +    b::Integer = 1
    +)

    Goes to the registry of the stage t, scenario s and block b.

    source

    File conversion

    Reader mapper

    Missing docstring.

    Missing docstring for PSRClassesInterface.add_reader!. Check Documenter's build log for details.

    Modification API

    PSRClassesInterface.create_element!Function
    create_element!(
    +    data::Data,
    +    collection::String,
    +    ps::Pair{String,<:Any};
    +    default::Union{Dict{String,Any},Nothing} = nothing
    +)

    Creates a new instance of the given collection and returns its index.

    Example:

    index = PSRI.create_element!(data, "PSRClass")
    +
    +PSRI.set_parm!(data, "PSRClass", index, "PSRAttr", value)
    source
    PSRClassesInterface.set_parm!Function
    set_parm!(
    +    data::Data,
    +    collection::String,
    +    attribute::String,
    +    index::Integer,
    +    value::T,
    +) where {T <: MainTypes}

    Defines the value of a scalar parameter.

    source
    PSRClassesInterface.set_vector!Function
    function set_vector!(
    +    data::Data,
    +    collection::String,
    +    attribute::String,
    +    index::Int,
    +    buffer::Vector{T}
    +) where {T<:MainTypes}

    Updates a data vector according to the given buffer. Note: Modifying current vector length is not allowed: use set_series! instead.

    source
    PSRClassesInterface.set_series!Function
    function set_series!(
    +    data::Data,
    +    collection::String,
    +    index_attr::String,
    +    index::Int,
    +    buffer::Dict{String,Vector}
    +)

    Updates serial (indexed) data. All columns must be the same as before. The series length is allowed to be changed, but all vectors in the new series must have equal length.

    julia> series = Dict{String, Vector}(
    +         "GerMin" => [0.0, 1.0],
    +         "GerMax" => [888.0, 777.0],
    +         "NGas" => [nothing, nothing],
    +         "IH" => [0.0, 0.0],
    +         "CoefE" => [1.0, 2.0],
    +         "PotInst" => [888.0, 777.0],
    +         "ICP" => [0.0, 0.0],
    +         "Data" => ["1900-01-01", "1900-01-02"],
    +         "Existing" => [0, 0],
    +         "sfal" => [0, 1],
    +         "NAdF" => [0, 0],
    +         "Unidades" => [1, 1],
    +         "StartUp" => [0.0, 2.0]
    +       );
    +
    +julia> PSRI.set_series!(data, "PSRThermalPlant", 1, "Data", series)
    source
    PSRClassesInterface.set_related!Function
    set_related!(
    +    data::AbstractData,
    +    source::String,
    +    target::String,
    +    source_index::Integer,
    +    target_index::Integer;
    +    relation_type = RELATION_1_TO_1,
    +)

    Sets the element source_index from collection source to be related to the element target_index from collection target in the scalar relation of type relation_type.

    source
    PSRClassesInterface.set_vector_related!Function
    set_vector_related!(
    +    data::AbstractData,
    +    source::String,
    +    target::String,
    +    source_index::Integer,
    +    target_index::Vector{<:Integer};
    +    relation_type = RELATION_1_TO_N,
    +)

    Sets the element source_index from collection source to be related to the elements in target_index from collection target in the vector relation of type relation_type.

    source
    diff --git a/previews/PR226/openstudy_files/file_diagram/index.html b/previews/PR226/openstudy_files/file_diagram/index.html new file mode 100644 index 00000000..818c9696 --- /dev/null +++ b/previews/PR226/openstudy_files/file_diagram/index.html @@ -0,0 +1,2 @@ + +OpenStudy Files and Structs 101 · PSRClassesInterface.jl

    OpenStudy Files and Structs 101

    When creating or loading a study using the OpenStudy framework, PSRI uses different files. This flowchart shows the order in which the files are used.

    1. The classes and their attributes are defined in a PMD file.
    2. Then, a Model Template file is used to map the classes to collections in the study.
    3. Using the Model Template and the PMD file, the Data Struct file is created.
    4. PSRI loads the Data Struct, Relation Mapper and Defaults files into structs and create a study, whose data will be stored in a file named psrclasses.json.

    OpenStudy Diagram

    How the structs are used

    Creating an element

    When creating an element from a collection, OpenStudy uses the Data Struct, Relation Mapper and Defaults files to check if:

    • The collection is defined in the Data Struct file.
    • The element has all the attributes defined in the Data Struct file.
    • In the case where the element does not have all the attributes, the Defaults file has the remaining ones.

    Creating a relation

    When creating a relation between two collections, OpenStudy uses the Relation Mapper to check if:

    • The relation is defined in the Relation Mapper
    • The elements exist in the study
    diff --git a/previews/PR226/openstudy_files/model_template/index.html b/previews/PR226/openstudy_files/model_template/index.html new file mode 100644 index 00000000..1b0ff9b1 --- /dev/null +++ b/previews/PR226/openstudy_files/model_template/index.html @@ -0,0 +1,15 @@ + +Model Template · PSRClassesInterface.jl

    Model Template

    The models defined in a PMD file are mapped to collections in an OpenStudy instance with a Model Template file.

    A Model Template is a JSON file with the following syntax.

    [
    +    {
    +        "classname": "CustomCollection",
    +        "models": [
    +            "Custom_Model_v1"
    +        ]
    +    },
    +    {
    +        "classname": "SecondCollection",
    +        "models": [
    +            "Another_Custom_Model_v1"
    +        ]
    +    }
    +]

    Inside classname you define the name of the collection that represents a model stated in models. This model is defined in a PMD file.

    To learn more about how to use custom PMD files with Model Templates, see the Customizing a Study example.

    diff --git a/previews/PR226/openstudy_files/pmd/index.html b/previews/PR226/openstudy_files/pmd/index.html new file mode 100644 index 00000000..847cfe43 --- /dev/null +++ b/previews/PR226/openstudy_files/pmd/index.html @@ -0,0 +1,49 @@ + +PMD · PSRClassesInterface.jl

    PMD

    Tip

    We have a syntax highlighter for .pmd files available on Visual Studio's Marktetplace

    Warning

    The syntax for PMD files is case-sensitive

    PMD files are used to define models accross multiple PSR software. It stores metadata about every attribute and relation.

    Good practices

    In order to make the PMD file more readable and easier to maintain, we recommend the following good practices:

    • Decide whether you want to use PascalCase, snake_case or camelCase and stick to it.
    • Always write the name for the Attributes and Collections in English.
    • Do not use special characters other than "_" (underscore) in the names.
    • Define understandable names for the Attributes and Collections, as other users may use your model in the future.

    Defining a model

    To define a model Custom_Model_v1, you need to use the following structure:

    DEFINE_MODEL MODL:Custom_Model_v1
    +
    +	...
    +
    +END_MODEL

    Defining a parameter

    A parameter can be either a VECTOR or a PARM.

    PARM

    DEFINE_MODEL MODL:Custom_Model_v1
    +
    +	...
    +
    +	PARM INTEGER Iterations
    +	PARM REAL Price
    +	PARM STRING Name
    +	PARM DATE DateOfEvent
    +
    +	...
    +
    +END_MODEL

    VECTOR

    A VECTOR parameter can store the same types as a PARM. Additionally can have an indexing parameter attribute.

    Let's say that you have a vector Cost where each index corresponds to a cost in a specific date. We can use an auxiliary indexing vector CostDates to access the cost value correspondent to a given date (see the Graf Files and Time Series example).

    DEFINE_MODEL MODL:Custom_Model_v1
    +
    +	...
    +
    +	VECTOR DATE CostDates
    +	VECTOR REAL Cost INDEX CostDates
    +
    +	...
    +
    +END_MODEL

    Parameters with dimension

    A VECTOR or PARM parameter can change according to a given Stage, Scenario and/or Block dimension (see the Graf Files and Time Series example). We can specify whether a parameter is dimensioned using the following syntax:

    DEFINE_MODEL MODL:Custom_Model_v1
    +
    +	...
    +
    +	PARM INTEGER Iterations DIM(block)
    +
    +	VECTOR REAL Duration DIM(block) 
    +
    +	VECTOR DATE CostDates
    +	VECTOR REAL Cost DIM(block,segment) INDEX CostDates 
    +
    +	...
    +
    +END_MODEL

    REFERENCE

    Besides REAL, INTEGER, STRING and DATE, there is a fith attribute type labeled REFERENCE. It can be stored either in a VECTOR or a PARM.

    A REFERENCE represents a relation between two models(or collections, when considering a PSRI study).

    It has the following structure:

    DEFINE_MODEL MODL:Custom_Model_v1
    +
    +	...
    +
    +	PARM REFERENCE Plant TargetCollection  
    +
    +	VECTOR REFERENCE Items SecondTargetCollection
    +
    +	...
    +
    +END_MODEL

    In this example, our CustomModelv1 model has two relations:

    • a relation of 1 to 1 (for being a PARM parameter) with elements of collection TargetCollection
    • a relation of 1 to N (for being a VECTOR parameter) with elements of collection SecondTargetCollection

    The Plant and Items parameters store the reference_id of the corresponding elements from collections TargetCollection and SecondTargetCollection, respectively.

    Note that the names TargetCollection and SecondTargetCollection are the name of the collections inside the study, not their name in the PMD file. This difference between names is explained in the Model Template manual.

    Also, we define a REFERENCE only in the models which play the role of source.

    There is another way to define relations in a study. For that, see the Relation Mapper manual.

    diff --git a/previews/PR226/openstudy_files/psrclasses/index.html b/previews/PR226/openstudy_files/psrclasses/index.html new file mode 100644 index 00000000..a71b9271 --- /dev/null +++ b/previews/PR226/openstudy_files/psrclasses/index.html @@ -0,0 +1,25 @@ + +psrclasses.json and Defaults · PSRClassesInterface.jl

    psrclasses.json and Defaults

    The psrclasses.json file stores the data from the OpenStudy model.

    It has the following structure:

    {
    +    "CustomCollection": {
    +        "AVId": "string",
    +        "name": "name",
    +        "code": 0,
    +        "Values": [
    +            0.0
    +        ],
    +        "Cost": 1.5
    +    },
    +    "SecondCollection": {
    +        "AVId": "string2",
    +        "name": "name2",
    +        "Type": 3,
    +        "Generation(1)": [
    +            0.0,2.0
    +        ],
    +        "Generation(2)": [
    +            5.0,3.0
    +        ],
    +        "code":1
    +    }
    +}
    +
    Note

    In the SecondCollection there are two parameters Generation(1) and Generation(2). They represent the values for the parameter Generation in two different dimensions.

    Defaults

    The defaults.json file stores the default values for the parameters in the PSRI study. It has the same structure as the psrclasses.json. It is not a mandatory file, but it can be useful for the case when there are missing parameters for an element being created.

    diff --git a/previews/PR226/openstudy_files/relation_mapper/index.html b/previews/PR226/openstudy_files/relation_mapper/index.html new file mode 100644 index 00000000..07bdc869 --- /dev/null +++ b/previews/PR226/openstudy_files/relation_mapper/index.html @@ -0,0 +1,29 @@ + +Relation Mapper · PSRClassesInterface.jl

    Relation Mapper

    If you have already checked the PMD manual, you know that a PMD file can define relations between models. When these relations are parsed, they are stored in a Julia dictionary, the Relation Mapper.

    Relation Mapper JSON file

    However, it is also possible to fill the Relation Mapper with a JSON file, that follows the same structure as OpenStudy's dictionary for relations.

    In the example below, we have a Relation Mapper file with the following information:

    • The model CustomModel has two relations defined, one with SecondCollection and another with ThirdCollection.
      • The relation with SecondCollection is a 1_to_1 relation, and the parameter is called system.
      • The relation with ThirdCollection is a 1_to_N relation, and the parameter is called station.
    • The model SecondCollection has two relations with FourthCollection.
      • The first relation with FourthCollection is a FROM relation, and the parameter is called no1.
      • The second relation with FourthCollection is a TO relation, and the parameter is called no2.
    💭 Reminder

    The relation parameter stores the reference_id from the element of the Target Collection. See PMD manual

    {
    +    "CustomCollection": {
    +        "SecondCollection": {
    +            "system": {
    +                "is_vector": false,
    +                "type": "1_TO_1"
    +            }
    +        },
    +        "ThirdCollection": {
    +            "station": {
    +                "is_vector": true,
    +                "type": "1_TO_N"
    +            }
    +        }
    +    },
    +    "SecondCollection": {
    +        "FourthCollection": {
    +            "no1": {
    +                "is_vector": false,
    +                "type": "FROM"
    +            },
    +            "no2": {
    +                "is_vector": false,
    +                "type": "TO"
    +            }
    +        }
    +    }
    +}
    diff --git a/previews/PR226/psrdatabasesqlite/introduction/index.html b/previews/PR226/psrdatabasesqlite/introduction/index.html new file mode 100644 index 00000000..b5bd42ff --- /dev/null +++ b/previews/PR226/psrdatabasesqlite/introduction/index.html @@ -0,0 +1,2 @@ + +SQLite 101 · PSRClassesInterface.jl

    SQLite 101

    SQLite is a software library that provides a relational database management system. The lite in SQLite means light weight in terms of setup, database administration, and required resource. SQLite does NOT require a server to run.

    Although PSRI provides a simplified interface, similar to PSRI.OpenStudy, to read and write data in SQLite format, it is important to understand the basics of SQLite.

    To learn the basics, we recommend the following resources:

    Tip

    We recommend using SQLiteStudio to debug and visualize your SQLite database. You can download it here.

    diff --git a/previews/PR226/psrdatabasesqlite/rules/index.html b/previews/PR226/psrdatabasesqlite/rules/index.html new file mode 100644 index 00000000..8d0ad991 --- /dev/null +++ b/previews/PR226/psrdatabasesqlite/rules/index.html @@ -0,0 +1,71 @@ + +PSRDatabaseSQLite · PSRClassesInterface.jl

    PSRDatabaseSQLite

    Following PSRI's OpenStudy standards, SQL schemas for the PSRDatabaseSQLite framework should follow the conventions described in this document. Note that this is a tool for creating and developing some kinds of applications. Not all tools will need to use this framework.

    SQL Schema Conventions

    Collections

    • The Table name should be the same as the name of the Collection.
    • The Table name of a Collection should beging with a capital letter and be in singular form.
    • In case of a Collection with a composite name, the Table name should written in Pascal Case.
    • The Table must contain a primary key named id that is an INTEGER. You should use the AUTOINCREMENT keyword to automatically generate the id for each element.

    Examples:

    CREATE TABLE Resource (
    +    id INTEGER PRIMARY KEY AUTOINCREMENT,
    +    label TEXT UNIQUE NOT NULL,
    +    some_type TEXT
    +) STRICT;
    +
    +CREATE TABLE ThermalPlant(
    +    id INTEGER PRIMARY KEY AUTOINCREMENT,
    +    label TEXT UNIQUE NOT NULL,
    +    minimum_generation REAL DEFAULT 0
    +) STRICT;

    Configuration collection

    Every database definition must have a Configuration, which will store information from the case. The column label is not mandatory for a Configuration collection.

    CREATE TABLE Configuration (
    +    id INTEGER PRIMARY KEY AUTOINCREMENT,
    +    value1 REAL NOT NULL DEFAULT 100,
    +) STRICT;

    Non-vector Attributes

    • The name of an Attribute should be in snake case and be in singular form.
    • If the attribute's name is label, it should be stored as a TEXT and have the UNIQUE and NOT NULL constraints.

    Example:

    CREATE TABLE ThermalPlant(
    +    id INTEGER PRIMARY KEY AUTOINCREMENT,
    +    label TEXT UNIQUE NOT NULL,
    +    minimum_generation REAL NOT NULL
    +    some_example_of_attribute REAL
    +) STRICT;

    If an attribute name starts with date it should be stored as a TEXT and indicates a date that will be mapped to a DateTime object.

    Example:

    CREATE TABLE ThermalPlant(
    +    id INTEGER PRIMARY KEY AUTOINCREMENT,
    +    label TEXT UNIQUE NOT NULL,
    +    minimum_generation REAL NOT NULL,
    +    date_of_construction TEXT
    +) STRICT;

    If an attribute name starts with the name of another collection it should be stored as a INTEGER and indicates a relation with another collection. It should never have the NOT NULL constraint. All references should always declare the ON UPDATE CASCADE ON DELETE CASCADE constraint. In the example below the attribute gaugingstation_id indicates that the collection Plant has an id relation with the collection GaugingStation and the attribute plant_spill_to indicates that the collection Plant has a spill_to relation with itself.

    Example:

    CREATE TABLE Plant(
    +    id INTEGER PRIMARY KEY AUTOINCREMENT,
    +    label TEXT UNIQUE NOT NULL,
    +    capacity REAL NOT NULL,
    +    gaugingstation_id INTEGER,
    +    plant_spill_to INTEGER,
    +    FOREIGN KEY(gaugingstation_id) REFERENCES GaugingStation(id) ON UPDATE CASCADE ON DELETE CASCADE,
    +    FOREIGN KEY(plant_spill_to) REFERENCES Plant(id) ON UPDATE SET NULL ON DELETE CASCADE
    +) STRICT;

    Vector Attributes

    • In case of a vector attribute, a table should be created with its name indicating the name of the Collection and the name of a group of the attribute, separated by _vector_, such as COLLECTION_vector_GROUP_OF_ATTRIBUTES.

    • The table must contain a Column named id and another named vector_index.

    • There must be a Column named after the attributes names, which will store the value of the attribute for the specified element id and index vector_index.

    These groups are used to store vectors that should have the same size. If two vectors don't necessarily have the same size, they should be stored in different groups.

    Example:

    CREATE TABLE ThermalPlant_vector_some_group(
    +    id INTEGER,
    +    vector_index INTEGER NOT NULL,
    +    some_value REAL NOT NULL,
    +    some_other_value REAL,
    +    FOREIGN KEY (id) REFERENCES ThermalPlant(id) ON UPDATE CASCADE ON DELETE CASCADE,
    +    PRIMARY KEY (id, vector_index)
    +) STRICT;

    Example of a small time series

    CREATE TABLE ThermalPlant_vector_some_group(
    +    id INTEGER,
    +    vector_index INTEGER NOT NULL,
    +    date_of_modification REAL NOT NULL,
    +    capacity REAL,
    +    FOREIGN KEY (id) REFERENCES ThermalPlant(id) ON UPDATE CASCADE ON DELETE CASCADE,
    +    PRIMARY KEY (id, vector_index)
    +) STRICT;

    A vector relation with another collection should be stored in a table of vector groups and be defined the same way as a vector attribute. To tell that it is a relation with another collection, the name of the relational attribute should be the name of the target collection followed by the relation type defined as _relation_type, i.e. gaugingstation_id indicated that the collection HydroPlant has an id relation with the collection GaugingStation. If the name of the attribute was gaugingstation_one_to_one, it would indicate that the collection HydroPlant has a relation one_to_one with the collection GaugingStation.

    CREATE TABLE HydroPlant_vector_GaugingStation(
    +    id INTEGER,
    +    vector_index INTEGER NOT NULL,
    +    conversion_factor REAL NOT NULL,
    +    gaugingstation_id INTEGER,
    +    FOREIGN KEY (gaugingstation_id) REFERENCES GaugingStation(id) ON UPDATE CASCADE ON DELETE CASCADE,
    +    PRIMARY KEY (id, vector_index)
    +) STRICT;
    +

    Time Series Files

    • All Time Series files for the elements from a Collection should be stored in a Table

    • The Table name should be the same as the name of the Collection followed by _time_series_files, such as COLLECTION_vector_ATTRIBUTE.

    • Each Column of the table should be named after the name of the attribute.

    • Each Column should store the path to the file containing the time series data.

    Example:

    CREATE TABLE Plant_time_series_files (
    +    generation TEXT,
    +    cost TEXT
    +) STRICT;

    Time Series

    • Time Series stored in the database should be stored in a table with the name of the Collection followed by _time_series_ and the name of the attribute group, such a COLLECTION_time_series_GROUP_OF_ATTRIBUTES.

    Notice that it is quite similar to the vector attributes, but without the vector_index column. Instead, a mandatory column named date_time should be created to store the date of the time series data.

    Example:

    CREATE TABLE Resource_time_series_group1 (
    +    id INTEGER, 
    +    date_time TEXT NOT NULL,
    +    some_vector1 REAL,
    +    some_vector2 REAL,
    +    FOREIGN KEY(id) REFERENCES Resource(id) ON DELETE CASCADE ON UPDATE CASCADE,
    +    PRIMARY KEY (id, date_time)
    +) STRICT; 
    Tip

    For more information on how to handle time series data, please refer to the Time Series section.

    Migrations

    Migrations are an important part of the DatabaseSQLite framework. They are used to update the database schema to a new version without the need to delete the database and create a new one from scratch. Migrations are defined by two separate .sql files that are stored in the migrations directory of the model. The first file is the up migration and it is used to update the database schema to a new version. The second file is the down migration and it is used to revert the changes made by the up migration. Migrations are stored in directories in the model and they have a specific naming convention. The name of the migration folder should be the number of the version (e.g. /migrations/1/).

    database/migrations
    +├── 1
    +│   ├── up.sql
    +│   └── down.sql
    +└── 2
    +    ├── up.sql
    +    └── down.sql

    Creating a migration

    It is advised to create new migrations using the functions from DatabaseSQLite. First you need to make sure that the migrations directory is registered by the function DatabaseSQLite.set_migrations_folder and after that you can create a new migration using the function DatabaseSQLite.create_migration. This function will create a new migration file with the name and version specified by the user. The migration file will contain a template for the migration.

    Running migrations

    To run migrations you need to use the function DatabaseSQLite.apply_migrations!. There are various versions of this function, each one tailored to make something easier for the user.

    Testing migrations

    It is very important to test if the migrations of a certain model are working as expected, so the user can be sure that the database schema is updated correctly. To test migrations you need to use the function DatabaseSQLite.test_migrations(). It is highly advised that each model has one of these functions in their test suite to make sure that the migrations are working as expected.

    diff --git a/previews/PR226/psrdatabasesqlite/time_series/index.html b/previews/PR226/psrdatabasesqlite/time_series/index.html new file mode 100644 index 00000000..10f6955b --- /dev/null +++ b/previews/PR226/psrdatabasesqlite/time_series/index.html @@ -0,0 +1,123 @@ + +Time Series · PSRClassesInterface.jl

    Time Series

    It is possible to store time series data in your database. Time series in PSRDatabaseSQLite are very flexible. You can have missing values, and you can have sparse data.

    There is a specific table format that must be followed. Consider the following example:

    CREATE TABLE Resource (
    +    id INTEGER PRIMARY KEY AUTOINCREMENT,
    +    label TEXT UNIQUE NOT NULL
    +) STRICT;
    +
    +CREATE TABLE Resource_time_series_group1 (
    +    id INTEGER, 
    +    date_time TEXT NOT NULL,
    +    some_vector1 REAL,
    +    some_vector2 REAL,
    +    FOREIGN KEY(id) REFERENCES Resource(id) ON DELETE CASCADE ON UPDATE CASCADE,
    +    PRIMARY KEY (id, date_time)
    +) STRICT; 

    It is mandatory for a time series to be indexed by a date_time column with the following format: YYYY-MM-DD HH:MM:SS. You can use the Dates.jl package for handling this format.

    using Dates
    +date = DateTime(2024, 3, 1) # 2024-03-01T00:00:00 (March 1st, 2024)

    Notice that in this example, there are two value columns some_vector1 and some_vector2. You can have as many value columns as you want. You can also separate the time series data into different tables, by creating a table Resource_time_series_group2 for example.

    It is also possible to add more dimensions to your time series, such as block and scenario.

    CREATE TABLE Resource_time_series_group2 (
    +    id INTEGER, 
    +    date_time TEXT NOT NULL,
    +    block INTEGER NOT NULL,
    +    some_vector3 REAL,
    +    some_vector4 REAL,
    +    FOREIGN KEY(id) REFERENCES Resource(id) ON DELETE CASCADE ON UPDATE CASCADE,
    +    PRIMARY KEY (id, date_time, block)
    +) STRICT; 

    Rules

    Time series in PSRDatabaseSQLite are very flexible. You can have missing values, and you can have sparse data.

    If you are querying for a time series row entry that has a missing value, it first checks if there is a data with a date_time earlier than the queried date_time. If there is, it returns the value of the previous data. If there is no data earlier than the queried date_time, it returns a specified value according to the type of data you are querying.

    • For Float64, it returns NaN.
    • For Int64, it returns typemin(Int).
    • For String, it returns "" (empty String).
    • For DateTime, it returns typemin(DateTime).

    For example, if you have the following data:

    Datesome_vector1(Float64)some_vector2(Float64)
    20201.0missing
    2021missing1.0
    20223.0missing
    1. If you query for some_vector1 at 2020, it returns 1.0.
    2. If you query for some_vector2 at 2020, it returns NaN.
    3. If you query for some_vector1 at 2021, it returns 1.0.
    4. If you query for some_vector2 at 2021, it returns 1.0.
    5. If you query for some_vector1 at 2022, it returns 3.0.
    6. If you query for some_vector2 at 2022, it returns 1.0.

    Inserting data

    When creating a new element that has a time series, you can pass this information via a DataFrame. Consider the collection Resource with the two time series tables Resource_time_series_group1 and Resource_time_series_group2.

    using DataFrames
    +using Dates
    +using PSRClassesInterface
    +PSRDatabaseSQLite = PSRClassesInterface.PSRDatabaseSQLite
    +
    +db = PSRDatabaseSQLite.create_empty_db_from_schema(db_path, path_schema; force = true)
    +
    +PSRDatabaseSQLite.create_element!(db, "Configuration"; label = "Toy Case", value1 = 1.0)
    +
    +df_group1 = DataFrame(;
    +        date_time = [DateTime(2000), DateTime(2001), DateTime(2002)],
    +        some_vector1 = [missing, 1.0, 2.0],
    +        some_vector2 = [1.0, missing, 5.0],
    +    )
    +
    +df_group2 = DataFrame(;
    +            date_time = [
    +                DateTime(2000),
    +                DateTime(2000),
    +                DateTime(2000),
    +                DateTime(2000),
    +                DateTime(2001),
    +                DateTime(2001),
    +                DateTime(2001),
    +                DateTime(2009),
    +            ],
    +            block = [1, 1, 1, 1, 2, 2, 2, 2],
    +            some_vector3 = [1.0, 2.0, 3.0, 4.0, 1, 2, 3, 4],
    +            some_vector4 = [1.0, 2.0, 3.0, 4.0, 1, 2, 3, 4],
    +        )
    +
    +
    +PSRDatabaseSQLite.create_element!(
    +    db,
    +    "Resource";
    +    label = "Resource 1",
    +    group1 = df_group1,
    +    group2 = df_group2,
    +)

    It is also possible to insert a single row of a time series. This is useful when you want to insert a specific dimension entry. This way of inserting time series is less efficient than inserting a whole DataFrame.

    using DataFrames
    +using Dates
    +using PSRClassesInterface
    +PSRDatabaseSQLite = PSRClassesInterface.PSRDatabaseSQLite
    +
    +db = PSRDatabaseSQLite.create_empty_db_from_schema(db_path, path_schema; force = true)
    +
    +PSRDatabaseSQLite.create_element!(db, "Configuration"; label = "Toy Case", value1 = 1.0)
    +
    +PSRDatabaseSQLite.create_element!(
    +    db,
    +    "Resource";
    +    label = "Resource 1"
    +)
    +
    +PSRDatabaseSQLite.add_time_series_row!(
    +    db,
    +    "Resource",
    +    "some_vector1",
    +    "Resource 1",
    +    10.0; # new value
    +    date_time = DateTime(2000)
    +)
    +
    +PSRDatabaseSQLite.add_time_series_row!(
    +    db,
    +    "Resource",
    +    "some_vector1",
    +    "Resource 1",
    +    11.0; # new value
    +    date_time = DateTime(2001)
    +)

    Reading data

    You can read the information from the time series in two different ways.

    Reading as a table

    First, you can read the whole time series table for a given value, as a DataFrame.

    df = PSRDatabaseSQLite.read_time_series_table(
    +    db,
    +    "Resource",
    +    "some_vector1",
    +    "Resource 1",
    +)

    Reading a single row

    It is also possible to read a single row of the time series in the form of an array. This is useful when you want to query a specific dimension entry. For this function, there are performance improvements when reading the data via caching the previous and next non-missing values.

    values = PSRDatabaseSQLite.read_time_series_row(
    +    db,
    +    "Resource",
    +    "some_vector1",
    +    Float64;
    +    date_time = DateTime(2020)
    +)

    When querying a row, all values should non-missing. However, if there is a missing value, the function will return the previous non-missing value. And if even the previous value is missing, it will return a specified value according to the type of data you are querying.

    • For Float64, it returns NaN.
    • For Int64, it returns typemin(Int).
    • For String, it returns "" (empty String).
    • For DateTime, it returns typemin(DateTime).

    For example, if you have the following data for the time series some_vector1:

    DateResource 1Resource 2
    20201.0missing
    2021missing1.0
    20223.0missing
    1. If you query at 2020, it returns [1.0, NaN].
    2. If you query at 2021, it returns [1.0, 1.0].
    3. If you query at 2022, it returns [3.0, 1.0].

    Updating data

    When updating one of the entries of a time series for a given element and attribute, you need to specify the exact dimension values of the row you want to update.

    For example, consider a time series that has block and data_time dimensions.

    PSRDatabaseSQLite.update_time_series_row!(
    +    db,
    +    "Resource",
    +    "some_vector3",
    +    "Resource 1",
    +    10.0; # new value
    +    date_time = DateTime(2000),
    +    block = 1
    +)

    Deleting data

    You can delete the whole time series of an element for a given time series group. Consider the following table:

    CREATE TABLE Resource_time_series_group1 (
    +    id INTEGER, 
    +    date_time TEXT NOT NULL,
    +    some_vector1 REAL,
    +    some_vector2 REAL,
    +    FOREIGN KEY(id) REFERENCES Resource(id) ON DELETE CASCADE ON UPDATE CASCADE,
    +    PRIMARY KEY (id, date_time)
    +) STRICT; 

    This table represents a "group" that stores two time series some_vector1 and some_vector2. You can delete all the data from this group by calling the following function:

    PSRDatabaseSQLite.delete_time_series!(
    +    db,
    +    "Resource",
    +    "group1",
    +    "Resource 1",
    +)

    When trying to read a time series that has been deleted, the function will return an empty DataFrame.

    diff --git a/previews/PR226/search/index.html b/previews/PR226/search/index.html new file mode 100644 index 00000000..44ead048 --- /dev/null +++ b/previews/PR226/search/index.html @@ -0,0 +1,2 @@ + +Search · PSRClassesInterface.jl

    Loading search...

      diff --git a/previews/PR226/search_index.js b/previews/PR226/search_index.js new file mode 100644 index 00000000..b8182924 --- /dev/null +++ b/previews/PR226/search_index.js @@ -0,0 +1,3 @@ +var documenterSearchIndex = {"docs": +[{"location":"examples/modification/#Modifying-a-Study","page":"Modifying a Study","title":"Modifying a Study","text":"","category":"section"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"In this example we will be showing how to modify your study in runtime, adding/deleting elements, setting relations, ...","category":"page"},{"location":"examples/modification/#Creating-a-Study","page":"Modifying a Study","title":"Creating a Study","text":"","category":"section"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"You can modify an existing study or a new one with the following functions:","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRClassesInterface.create_study → to create a new study;\nPSRClassesInterface.load_study → to load an old study.","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"In this example, we will be working with a new empty study.","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"using PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\ntemp_path = joinpath(tempdir(), \"PSRI\")\n\ndata = PSRI.create_study(PSRI.OpenInterface(); data_path = temp_path)","category":"page"},{"location":"examples/modification/#Adding-new-elements","page":"Modifying a Study","title":"Adding new elements","text":"","category":"section"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"You can only add elements from collections that are available for your study. Here we will be using our default study configuration, but in another example you can learn how to work with a custom study. You can check which collections are available with PSRI.get_collections(data).","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"Every study already comes with a PSRStudy element. So now we can add some elements with the function PSRClassesInterface.create_element!, that returns the element's index in the collection.","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"bus_1_index = PSRI.create_element!(data, \"PSRBus\")\nserie_1_index = PSRI.create_element!(data, \"PSRSerie\")","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"When not specified, the attributes for the element are filled with their default values. But you can also set them manually. If you need, it is possible to see the attributes for a collection with PSRI.get_attributes(data, COLLECTION).","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"bus_2_index = PSRI.create_element!(\n data, \"PSRBus\", \n \"name\" => \"bus_name\", \n \"Kv\" => 1.5, \n \"code\"=> Int32(98), \n \"icca\" => Int32(5), \n \"AVId\" => \"bus_id\"\n )\n\n# You don't need to set all attributes\n\nbus_3_index = PSRI.create_element!(\n data, \"PSRBus\", \n \"code\"=> Int32(10), \n )","category":"page"},{"location":"examples/modification/#Setting-relations","page":"Modifying a Study","title":"Setting relations","text":"","category":"section"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"Some collections in a Study can have relations between some of their elements. ","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"A Relation has a source and a target element. We can check the available relations for an element when it is a source with PSRI.get_relations(COLLECTION). Just as for custom collections, you can learn how to customize relations in another tutorial.","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRI.set_related!(\n data, \n \"PSRSerie\", \n \"PSRBus\", \n serie_1_index, \n bus_1_index , \n relation_type = PSRI.PMD.RELATION_FROM\n )\n\nPSRI.set_related!(\n data, \n \"PSRSerie\", \n \"PSRBus\", \n serie_1_index, \n bus_2_index , \n relation_type = PSRI.PMD.RELATION_TO\n )","category":"page"},{"location":"examples/modification/#Deleting-elements","page":"Modifying a Study","title":"Deleting elements","text":"","category":"section"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"We can delete an element using PSRClassesInterface.delete_element!. ","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRI.delete_element!(data, \"PSRBus\", bus_3_index)","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"However, if you try to delete an element that has a relation with any other, you will receive an error message. ","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRI.delete_element!(data, \"PSRSerie\", serie_1_index)","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"ERROR: Element PSRSerie cannot be deleted because it has relations with other elements","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"So first, you have to check the relations that the element has and delete them.","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"To see the relations set to an element, use PSRClassesInterface.relations_summary, which returns a list with the target element, with its index, pointing to the source element, also with its index.","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRI.relations_summary(data, \"PSRBus\", bus_1_index)","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRI.relations_summary(data, \"PSRBus\", bus_2_index)","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRI.relations_summary(data, \"PSRSerie\", serie_1_index)","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"Now we know that we have to delete two relations to be able to delete the PSRSerie element. For that, we use PSRClassesInterface.delete_relation!.","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRI.delete_relation!(data, \"PSRSerie\", \"PSRBus\", serie_1_index, bus_1_index)\nPSRI.delete_relation!(data, \"PSRSerie\", \"PSRBus\", serie_1_index, bus_2_index)","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"After that, we can easily delete our PSRSerie element.","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRI.delete_element!(data, \"PSRSerie\", serie_1_index)","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"After that we can save our study to a JSON file, which can later be used to load the study again.","category":"page"},{"location":"examples/modification/","page":"Modifying a Study","title":"Modifying a Study","text":"PSRI.write_data(data)","category":"page"},{"location":"examples/reading_parameters/#Reading-parameters","page":"Reading parameters","title":"Reading parameters","text":"","category":"section"},{"location":"examples/reading_parameters/#Reading-configuration-parameters","page":"Reading parameters","title":"Reading configuration parameters","text":"","category":"section"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"Most cases have configuration parameters such as the maximum number of iterations, the discount rate, the deficit cost etc. The function PSRClassesInterface.configuration_parameter reads all the parameters from the cases.","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"import PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\nPATH_CASE_EXAMPLE_CONFIGS = joinpath(pathof(PSRI) |> dirname |> dirname, \"test\", \"data\", \"case0\")\n\ndata = PSRI.load_study(\n PSRI.OpenInterface(),\n data_path = PATH_CASE_EXAMPLE_CONFIGS\n)\n\nPSRI.configuration_parameter(data, \"TaxaDesconto\", 0.0)\nPSRI.configuration_parameter(data, \"MaximoIteracoes\", 0)\nPSRI.configuration_parameter(data, \"MaximoIteracoes\", 0)\nPSRI.configuration_parameter(data, \"MinOutflowPenalty\", 0.0)\nPSRI.configuration_parameter(data, \"DeficitCost\", [0.0])\n; nothing # hide","category":"page"},{"location":"examples/reading_parameters/#Reading-basic-thermal-generator-parameters","page":"Reading parameters","title":"Reading basic thermal generator parameters","text":"","category":"section"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"In this example we will map parameters of thermal generators at each stage of the study to a struct. Suppose in this case that our thermal generators has the following attributes:","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"Base.@kwdef mutable struct ThermalGenerators\n names::Vector{String} = String[]\n codes::Vector{Int32} = Int32[]\n generation_capacities::Vector{Float64} = Float64[]\n therm2sys::Vector{Int32} = Int32[]\nend\n; nothing # hide","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"The first thing we must do is to initialize the reading procedure with the following commands:","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"import PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\nPATH_CASE_EXAMPLE_THERMALS = joinpath(pathof(PSRI) |> dirname |> dirname, \"test\", \"data\", \"case0\")\n\ndata = PSRI.load_study(\n PSRI.OpenInterface(),\n data_path = PATH_CASE_EXAMPLE_THERMALS\n)\n; nothing # hide","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"We can initialize the struct with the parameters of the first stage using the function PSRClassesInterface.mapped_vector","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"therm_gen = ThermalGenerators()\ntherm_gen.names = PSRI.get_name(data, \"PSRThermalPlant\")\ntherm_gen.codes = PSRI.get_code(data, \"PSRThermalPlant\")\ntherm_gen.generation_capacities = PSRI.mapped_vector(data, \"PSRThermalPlant\", \"PotInst\", Float64)\ntherm_gen.therm2sys = PSRI.get_map(data, \"PSRThermalPlant\", \"PSRSystem\")\n; nothing # hide","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"And afterwards we can update the parameters for each stage as follows.","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"for stage in 1:PSRI.total_stages(data)\n PSRI.go_to_stage(data, stage)\n PSRI.update_vectors!(data)\n println(\"Thermal generator 2 generation capacity at stage $stage $(therm_gen.generation_capacities[2])\")\nend\n; nothing # hide","category":"page"},{"location":"examples/reading_parameters/#Reading-basic-battery-parameters","page":"Reading parameters","title":"Reading basic battery parameters","text":"","category":"section"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"This example is very similar to \"Reading basic thermal generator parameters\", but it is necessary to be cautious about the difference between elements. For instance, batteries have different parameters than thermal generators, therefore, our data structure must be defined accordingly:","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"Base.@kwdef mutable struct Batteries\n names::Vector{String} = String[]\n codes::Vector{Int32} = Int32[]\n charge_eff::Vector{Float64} = Float64[]\n bat2sys::Vector{Int32} = Int32[]\nend\n; nothing # hide","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"Stardard proceadure of reading data from file:","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"import PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\nPATH_CASE_EXAMPLE_BATTERIES = joinpath(pathof(PSRI) |> dirname |> dirname, \"test\", \"data\", \"case1\")\n\ndata = PSRI.load_study(\n PSRI.OpenInterface(),\n data_path = PATH_CASE_EXAMPLE_BATTERIES\n)\n; nothing # hide","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"And now the struct may be instantiated by setting its appropriate parameters:","category":"page"},{"location":"examples/reading_parameters/","page":"Reading parameters","title":"Reading parameters","text":"batteries = Batteries()\nbatteries.names = PSRI.get_name(data, \"PSRBattery\")\nbatteries.codes = PSRI.get_code(data, \"PSRBattery\")\nbatteries.charge_eff = PSRI.mapped_vector(data, \"PSRBattery\", \"ChargeEffic\", Float64)\nbatteries.bat2sys = PSRI.get_map(data, \"PSRBattery\", \"PSRSystem\")\n; nothing # hide","category":"page"},{"location":"openstudy_files/model_template/#Model-Template","page":"Model Template","title":"Model Template","text":"","category":"section"},{"location":"openstudy_files/model_template/","page":"Model Template","title":"Model Template","text":"The models defined in a PMD file are mapped to collections in an OpenStudy instance with a Model Template file.","category":"page"},{"location":"openstudy_files/model_template/","page":"Model Template","title":"Model Template","text":"A Model Template is a JSON file with the following syntax.","category":"page"},{"location":"openstudy_files/model_template/","page":"Model Template","title":"Model Template","text":"[\n {\n \"classname\": \"CustomCollection\",\n \"models\": [\n \"Custom_Model_v1\"\n ]\n },\n {\n \"classname\": \"SecondCollection\",\n \"models\": [\n \"Another_Custom_Model_v1\"\n ]\n }\n]","category":"page"},{"location":"openstudy_files/model_template/","page":"Model Template","title":"Model Template","text":"Inside classname you define the name of the collection that represents a model stated in models. This model is defined in a PMD file.","category":"page"},{"location":"openstudy_files/model_template/","page":"Model Template","title":"Model Template","text":"To learn more about how to use custom PMD files with Model Templates, see the Customizing a Study example.","category":"page"},{"location":"examples/reading_relations/#Reading-Relations","page":"Reading Relations","title":"Reading Relations","text":"","category":"section"},{"location":"examples/reading_relations/#Introduction-to-the-[PSRClassesInterface.get_map](@ref)-method","page":"Reading Relations","title":"Introduction to the PSRClassesInterface.get_map method","text":"","category":"section"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"There are two dispatches for the PSRClassesInterface.get_map function. The first requires the attribute name that represents the relation, while the second needs the PSRClassesInterface.PMD.RelationType between the elements.","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Here is how this function works:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Let's say that in our study we have 3 PSRSerie and 2 PSRBus elements. There is a relation between elements of these two collections represented by an attribute 'no2', where PSRSerie is the source and PSRBus is the target.","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"If we execute the following code:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"using PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\nPSRI.create_element!(data, \"PSRSerie\")\nPSRI.create_element!(data, \"PSRSerie\")\nPSRI.create_element!(data, \"PSRSerie\")\nPSRI.create_element!(data, \"PSRBus\")\nPSRI.create_element!(data, \"PSRBus\")\n\nPSRI.set_related!(data, \"PSRSerie\", \"PSRBus\", 1, 2, relation_type = PSRI.PMD.RELATION_TO)\nPSRI.set_related!(data, \"PSRSerie\", \"PSRBus\", 3, 1, relation_type = PSRI.PMD.RELATION_TO)\n\nPSRI.get_map(data, \"PSRSerie\", \"PSRBus\", \"no2\")","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"We could, as an example, get the following vector:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"[ 2 , 0 , 1 ]","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"This means that:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"the source element of index 1 in the collection PSRSerie is related to the target element of index 2 in the collection PSRBus. \nthe source element of index 2 in the collection PSRSerie is not related to any element from collection PSRBus\nthe source element of index 3 in the collection PSRSerie is related to the target element of index 1 in the collection PSRBus. ","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Note: There is also a PSRClassesInterface.get_vector_map method that works just as PSRClassesInterface.get_map. ","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Now we can move to a more practical example.","category":"page"},{"location":"examples/reading_relations/#Determining-subsystem-from-a-certain-hydro-plant","page":"Reading Relations","title":"Determining subsystem from a certain hydro plant","text":"","category":"section"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"In this example we will demonstrate how to make a simple use of a relationship map. That will be achieved by determining a subsystem from a certain hydro plant through its parameters. The program will initiate by the standard reading procedure:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"\nPATH_CASE_EXAMPLE_GAUGING = joinpath(pathof(PSRI) |> dirname |> dirname, \"test\", \"data\", \"case2\")\n\ndata = PSRI.load_study(\n PSRI.OpenInterface(),\n data_path = PATH_CASE_EXAMPLE_GAUGING\n)\n; nothing # hide","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Next, the maps between hydroplants and systems is retrieved by the get_map method:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"hyd2sys = PSRI.get_map(data, \"PSRHydroPlant\",\"PSRSystem\", \"system\")\n; nothing # hide","category":"page"},{"location":"examples/reading_relations/#Determining-buses-from-a-certain-thermal-plant","page":"Reading Relations","title":"Determining buses from a certain thermal plant","text":"","category":"section"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"This case consists of a more advanced use of a relationship map. We'll determine which buses are linked to a given target thermal plant, while there is no direct relationship between both. Firstly, the study data is read:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"import PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\nPATH_CASE_EXAMPLE_BUS = joinpath(pathof(PSRI) |> dirname |> dirname, \"test\", \"data\", \"case1\")\n\ndata = PSRI.load_study(\n PSRI.OpenInterface(),\n data_path = PATH_CASE_EXAMPLE_BUS\n)\n; nothing # hide","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Whereas there is no direct link between buses and thermal plants, both are indirectly related through generators. Therefore, we must identify those relationships by calling get_map for each:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"gen2thermal = PSRI.get_map(data, \"PSRGenerator\",\"PSRThermalPlant\", \"plant\")\ngen2bus = PSRI.get_map(data, \"PSRGenerator\", \"PSRBus\", \"bus\")\n; nothing # hide","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Next, we can find which generators are linked to our target thermal plant by the indexes of gen2the:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"target_thermal = 1\ntarget_generator = findall(isequal(target_thermal), gen2thermal)\n; nothing # hide","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"target_generator now holds the indexes of generators that are linked to the buses we are trying to identify. With those at hand, the indexes of the buses are easily identifiable by:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"targetBus = gen2bus[target_generator]\n; nothing # hide","category":"page"},{"location":"examples/reading_relations/#Determining-which-buses-are-connected-by-each-circuit","page":"Reading Relations","title":"Determining which buses are connected by each circuit","text":"","category":"section"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Each circuit connects two buses, it starts from a bus and goes to another. In this example we'll discover these buses for each circuit and then we'll build an incidence matrix of buses by circuits. The first step is to read the data:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"\nPATH_CASE_EXAMPLE_CIR_BUS = joinpath(pathof(PSRI) |> dirname |> dirname, \"test\", \"data\", \"case1\")\n\ndata = PSRI.load_study(\n PSRI.OpenInterface(),\n data_path = PATH_CASE_EXAMPLE_CIR_BUS\n)\n; nothing # hide","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Next, we get from which bus each circuit starts and which bus it goes to with get_map:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"cir2bus_to = PSRI.get_map(data, \"PSRSerie\", \"PSRBus\", \"no1\")\ncir2bus_from = PSRI.get_map(data, \"PSRSerie\", \"PSRBus\", \"no2\")\n; nothing # hide","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"Now we can build the incidence matrix. Each row corresponds to a circuit and each column corresponds to a bus. The element at the index (i,j) is -1 if the circuit i starts from the bus j, 1 if it goes to this bus, and 0 if they both have no relation:","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"bus_size = PSRI.max_elements(data, \"PSRBus\")\ncir_size = PSRI.max_elements(data, \"PSRSerie\")\nincidence_matrix = zeros(Float64, cir_size, bus_size)\nfor cir = 1:cir_size\n incidence_matrix[cir, cir2bus_from[cir]] = -1.0\n incidence_matrix[cir, cir2bus_to[cir]] = 1.0\nend\nincidence_matrix","category":"page"},{"location":"examples/reading_relations/","page":"Reading Relations","title":"Reading Relations","text":"","category":"page"},{"location":"openstudy_files/psrclasses/#psrclasses.json-and-Defaults","page":"psrclasses.json and Defaults","title":"psrclasses.json and Defaults","text":"","category":"section"},{"location":"openstudy_files/psrclasses/","page":"psrclasses.json and Defaults","title":"psrclasses.json and Defaults","text":"The psrclasses.json file stores the data from the OpenStudy model.","category":"page"},{"location":"openstudy_files/psrclasses/","page":"psrclasses.json and Defaults","title":"psrclasses.json and Defaults","text":"It has the following structure:","category":"page"},{"location":"openstudy_files/psrclasses/","page":"psrclasses.json and Defaults","title":"psrclasses.json and Defaults","text":"{\n \"CustomCollection\": {\n \"AVId\": \"string\",\n \"name\": \"name\",\n \"code\": 0,\n \"Values\": [\n 0.0\n ],\n \"Cost\": 1.5\n },\n \"SecondCollection\": {\n \"AVId\": \"string2\",\n \"name\": \"name2\",\n \"Type\": 3,\n \"Generation(1)\": [\n 0.0,2.0\n ],\n \"Generation(2)\": [\n 5.0,3.0\n ],\n \"code\":1\n }\n}\n","category":"page"},{"location":"openstudy_files/psrclasses/","page":"psrclasses.json and Defaults","title":"psrclasses.json and Defaults","text":"note: Note\nIn the SecondCollection there are two parameters Generation(1) and Generation(2). They represent the values for the parameter Generation in two different dimensions.","category":"page"},{"location":"openstudy_files/psrclasses/#Defaults","page":"psrclasses.json and Defaults","title":"Defaults","text":"","category":"section"},{"location":"openstudy_files/psrclasses/","page":"psrclasses.json and Defaults","title":"psrclasses.json and Defaults","text":"The defaults.json file stores the default values for the parameters in the PSRI study. It has the same structure as the psrclasses.json. It is not a mandatory file, but it can be useful for the case when there are missing parameters for an element being created.","category":"page"},{"location":"psrdatabasesqlite/time_series/#Time-Series","page":"Time Series","title":"Time Series","text":"","category":"section"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"It is possible to store time series data in your database. Time series in PSRDatabaseSQLite are very flexible. You can have missing values, and you can have sparse data. ","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"There is a specific table format that must be followed. Consider the following example:","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"CREATE TABLE Resource (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n label TEXT UNIQUE NOT NULL\n) STRICT;\n\nCREATE TABLE Resource_time_series_group1 (\n id INTEGER, \n date_time TEXT NOT NULL,\n some_vector1 REAL,\n some_vector2 REAL,\n FOREIGN KEY(id) REFERENCES Resource(id) ON DELETE CASCADE ON UPDATE CASCADE,\n PRIMARY KEY (id, date_time)\n) STRICT; ","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"It is mandatory for a time series to be indexed by a date_time column with the following format: YYYY-MM-DD HH:MM:SS. You can use the Dates.jl package for handling this format.","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"using Dates\ndate = DateTime(2024, 3, 1) # 2024-03-01T00:00:00 (March 1st, 2024)","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"Notice that in this example, there are two value columns some_vector1 and some_vector2. You can have as many value columns as you want. You can also separate the time series data into different tables, by creating a table Resource_time_series_group2 for example.","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"It is also possible to add more dimensions to your time series, such as block and scenario.","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"CREATE TABLE Resource_time_series_group2 (\n id INTEGER, \n date_time TEXT NOT NULL,\n block INTEGER NOT NULL,\n some_vector3 REAL,\n some_vector4 REAL,\n FOREIGN KEY(id) REFERENCES Resource(id) ON DELETE CASCADE ON UPDATE CASCADE,\n PRIMARY KEY (id, date_time, block)\n) STRICT; ","category":"page"},{"location":"psrdatabasesqlite/time_series/#Rules","page":"Time Series","title":"Rules","text":"","category":"section"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"Time series in PSRDatabaseSQLite are very flexible. You can have missing values, and you can have sparse data. ","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"If you are querying for a time series row entry that has a missing value, it first checks if there is a data with a date_time earlier than the queried date_time. If there is, it returns the value of the previous data. If there is no data earlier than the queried date_time, it returns a specified value according to the type of data you are querying.","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"For Float64, it returns NaN.\nFor Int64, it returns typemin(Int).\nFor String, it returns \"\" (empty String).\nFor DateTime, it returns typemin(DateTime).","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"For example, if you have the following data:","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"Date some_vector1(Float64) some_vector2(Float64)\n2020 1.0 missing\n2021 missing 1.0\n2022 3.0 missing","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"If you query for some_vector1 at 2020, it returns 1.0. \nIf you query for some_vector2 at 2020, it returns NaN. \nIf you query for some_vector1 at 2021, it returns 1.0. \nIf you query for some_vector2 at 2021, it returns 1.0. \nIf you query for some_vector1 at 2022, it returns 3.0. \nIf you query for some_vector2 at 2022, it returns 1.0.","category":"page"},{"location":"psrdatabasesqlite/time_series/#Inserting-data","page":"Time Series","title":"Inserting data","text":"","category":"section"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"When creating a new element that has a time series, you can pass this information via a DataFrame. Consider the collection Resource with the two time series tables Resource_time_series_group1 and Resource_time_series_group2.","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"using DataFrames\nusing Dates\nusing PSRClassesInterface\nPSRDatabaseSQLite = PSRClassesInterface.PSRDatabaseSQLite\n\ndb = PSRDatabaseSQLite.create_empty_db_from_schema(db_path, path_schema; force = true)\n\nPSRDatabaseSQLite.create_element!(db, \"Configuration\"; label = \"Toy Case\", value1 = 1.0)\n\ndf_group1 = DataFrame(;\n date_time = [DateTime(2000), DateTime(2001), DateTime(2002)],\n some_vector1 = [missing, 1.0, 2.0],\n some_vector2 = [1.0, missing, 5.0],\n )\n\ndf_group2 = DataFrame(;\n date_time = [\n DateTime(2000),\n DateTime(2000),\n DateTime(2000),\n DateTime(2000),\n DateTime(2001),\n DateTime(2001),\n DateTime(2001),\n DateTime(2009),\n ],\n block = [1, 1, 1, 1, 2, 2, 2, 2],\n some_vector3 = [1.0, 2.0, 3.0, 4.0, 1, 2, 3, 4],\n some_vector4 = [1.0, 2.0, 3.0, 4.0, 1, 2, 3, 4],\n )\n\n\nPSRDatabaseSQLite.create_element!(\n db,\n \"Resource\";\n label = \"Resource 1\",\n group1 = df_group1,\n group2 = df_group2,\n)","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"It is also possible to insert a single row of a time series. This is useful when you want to insert a specific dimension entry. This way of inserting time series is less efficient than inserting a whole DataFrame.","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"using DataFrames\nusing Dates\nusing PSRClassesInterface\nPSRDatabaseSQLite = PSRClassesInterface.PSRDatabaseSQLite\n\ndb = PSRDatabaseSQLite.create_empty_db_from_schema(db_path, path_schema; force = true)\n\nPSRDatabaseSQLite.create_element!(db, \"Configuration\"; label = \"Toy Case\", value1 = 1.0)\n\nPSRDatabaseSQLite.create_element!(\n db,\n \"Resource\";\n label = \"Resource 1\"\n)\n\nPSRDatabaseSQLite.add_time_series_row!(\n db,\n \"Resource\",\n \"some_vector1\",\n \"Resource 1\",\n 10.0; # new value\n date_time = DateTime(2000)\n)\n\nPSRDatabaseSQLite.add_time_series_row!(\n db,\n \"Resource\",\n \"some_vector1\",\n \"Resource 1\",\n 11.0; # new value\n date_time = DateTime(2001)\n)","category":"page"},{"location":"psrdatabasesqlite/time_series/#Reading-data","page":"Time Series","title":"Reading data","text":"","category":"section"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"You can read the information from the time series in two different ways.","category":"page"},{"location":"psrdatabasesqlite/time_series/#Reading-as-a-table","page":"Time Series","title":"Reading as a table","text":"","category":"section"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"First, you can read the whole time series table for a given value, as a DataFrame.","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"df = PSRDatabaseSQLite.read_time_series_table(\n db,\n \"Resource\",\n \"some_vector1\",\n \"Resource 1\",\n)","category":"page"},{"location":"psrdatabasesqlite/time_series/#Reading-a-single-row","page":"Time Series","title":"Reading a single row","text":"","category":"section"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"It is also possible to read a single row of the time series in the form of an array. This is useful when you want to query a specific dimension entry. For this function, there are performance improvements when reading the data via caching the previous and next non-missing values. ","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"values = PSRDatabaseSQLite.read_time_series_row(\n db,\n \"Resource\",\n \"some_vector1\",\n Float64;\n date_time = DateTime(2020)\n)","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"When querying a row, all values should non-missing. However, if there is a missing value, the function will return the previous non-missing value. And if even the previous value is missing, it will return a specified value according to the type of data you are querying.","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"For Float64, it returns NaN.\nFor Int64, it returns typemin(Int).\nFor String, it returns \"\" (empty String).\nFor DateTime, it returns typemin(DateTime).","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"For example, if you have the following data for the time series some_vector1:","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"Date Resource 1 Resource 2\n2020 1.0 missing\n2021 missing 1.0\n2022 3.0 missing","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"If you query at 2020, it returns [1.0, NaN]. \nIf you query at 2021, it returns [1.0, 1.0]. \nIf you query at 2022, it returns [3.0, 1.0]. ","category":"page"},{"location":"psrdatabasesqlite/time_series/#Updating-data","page":"Time Series","title":"Updating data","text":"","category":"section"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"When updating one of the entries of a time series for a given element and attribute, you need to specify the exact dimension values of the row you want to update. ","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"For example, consider a time series that has block and data_time dimensions.","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"PSRDatabaseSQLite.update_time_series_row!(\n db,\n \"Resource\",\n \"some_vector3\",\n \"Resource 1\",\n 10.0; # new value\n date_time = DateTime(2000),\n block = 1\n)","category":"page"},{"location":"psrdatabasesqlite/time_series/#Deleting-data","page":"Time Series","title":"Deleting data","text":"","category":"section"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"You can delete the whole time series of an element for a given time series group. Consider the following table:","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"CREATE TABLE Resource_time_series_group1 (\n id INTEGER, \n date_time TEXT NOT NULL,\n some_vector1 REAL,\n some_vector2 REAL,\n FOREIGN KEY(id) REFERENCES Resource(id) ON DELETE CASCADE ON UPDATE CASCADE,\n PRIMARY KEY (id, date_time)\n) STRICT; ","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"This table represents a \"group\" that stores two time series some_vector1 and some_vector2. You can delete all the data from this group by calling the following function:","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"PSRDatabaseSQLite.delete_time_series!(\n db,\n \"Resource\",\n \"group1\",\n \"Resource 1\",\n)","category":"page"},{"location":"psrdatabasesqlite/time_series/","page":"Time Series","title":"Time Series","text":"When trying to read a time series that has been deleted, the function will return an empty DataFrame.","category":"page"},{"location":"manual/#Manual","page":"Manual","title":"Manual","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"The PSRClassesInterface module provides interfaces to access data structured by PSR to be used in its models. Currently there are two main interfaces. ","category":"page"},{"location":"manual/","page":"Manual","title":"Manual","text":"The interface for studies. This interface is designed to read parameters from the files, some examples are deficit costs, fuel costs, currency, storage capacity etc.\nThe interface for reading and writing time series data. Time series data in the context of most studies have 4 dimensions (agents, stages, scenarios and blocks). Since studies of renewables with multiple agents, scenarios and stages can get quite big, we have designed different formats that are optimized to some objective (human readability, size, fast reading and writing, etc.).","category":"page"},{"location":"manual/","page":"Manual","title":"Manual","text":"Both interfaces are defined as a set of methods that need to be implemented to make a different file format work. In this manual we will describe the abstract methods and give concrete examples of code to perform the work needed.","category":"page"},{"location":"manual/","page":"Manual","title":"Manual","text":"When using the PSRClassesInterface package in your codebase we strongly advise you to create a constant PSRI to keep the code concise and explicitly declare that a certain function came from PSRClassesInterface. This can be done by adding the following code to the top of the code","category":"page"},{"location":"manual/","page":"Manual","title":"Manual","text":"using PSRClassesInterface\nconst PSRI = PSRClassesInterface","category":"page"},{"location":"manual/#Initialize-Study","page":"Manual","title":"Initialize Study","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.AbstractData\nPSRClassesInterface.AbstractStudyInterface\nPSRClassesInterface.load_study\nPSRClassesInterface.description\nPSRClassesInterface.max_elements","category":"page"},{"location":"manual/#PSRClassesInterface.AbstractData","page":"Manual","title":"PSRClassesInterface.AbstractData","text":"AbstractData\n\n\n\n\n\n","category":"type"},{"location":"manual/#PSRClassesInterface.AbstractStudyInterface","page":"Manual","title":"PSRClassesInterface.AbstractStudyInterface","text":"AbstractStudyInterface\n\n\n\n\n\n","category":"type"},{"location":"manual/#PSRClassesInterface.load_study","page":"Manual","title":"PSRClassesInterface.load_study","text":"load_study(::AbstractStudyInterface; kwargs...)\n\nInitialize all data structures of the study.\n\nnote: Differences between the OpenInterface and ClassicInterface\nEach study interface has its own set of kwargs... The easiest way to inspect the current available options is searching for this function on the Github repo of the desired interface.\n\nExample:\n\ndata = PSRI.load_study(\n PSRI.OpenInterface();\n data_path = PATH_CASE_EXAMPLE_BATTERIES,\n)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.description","page":"Manual","title":"PSRClassesInterface.description","text":"description(data::AbstractData)\n\nReturns the study description if available.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.max_elements","page":"Manual","title":"PSRClassesInterface.max_elements","text":"max_elements(data::AbstractData, collection::String)\n\nReturns an Int32 with the maximum number of elements for a given collection.\n\nExample:\n\nPSRI.max_elements(data, \"PSRThermalPlant\")\n\n\n\n\n\n","category":"function"},{"location":"manual/#Study-dimensions","page":"Manual","title":"Study dimensions","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.StageType\nPSRClassesInterface.total_stages\nPSRClassesInterface.total_scenarios\nPSRClassesInterface.total_blocks\nPSRClassesInterface.total_openings\nPSRClassesInterface.total_stages_per_year","category":"page"},{"location":"manual/#PSRClassesInterface.StageType","page":"Manual","title":"PSRClassesInterface.StageType","text":"PSRI.StageType\n\nPossible stage types used in for reading and writing time series files.\n\nThe current possible stage types are:\n\nSTAGE_UNKNOWN\nSTAGE_WEEK\nSTAGE_MONTH\nSTAGE_3MONTHS\nSTAGE_HOUR\nSTAGE_DAY\nSTAGE_13MONTHS\nSTAGE_2MONTHS\nSTAGE_4MONTHS\nSTAGE_6MONTHS\nSTAGE_YEAR\nSTAGE_DECADE\n\n\n\n\n\n","category":"type"},{"location":"manual/#PSRClassesInterface.total_stages","page":"Manual","title":"PSRClassesInterface.total_stages","text":"total_stages(data::AbstractData)\n\nReturns the total number of stages of the case.\n\nExample:\n\nPSRI.total_stages(data)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.total_scenarios","page":"Manual","title":"PSRClassesInterface.total_scenarios","text":"total_scenarios(data::AbstractData)\n\nReturns the total number of scenarios of the case.\n\nExample:\n\nPSRI.total_scenarios(data)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.total_blocks","page":"Manual","title":"PSRClassesInterface.total_blocks","text":"total_blocks(data::AbstractData)\n\nReturns the total number of blocks of the case.\n\nExample:\n\nPSRI.total_blocks(data)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.total_openings","page":"Manual","title":"PSRClassesInterface.total_openings","text":"total_openings(data::AbstractData)\n\nReturns the total number of openings of the case.\n\nExample:\n\nPSRI.total_openings(data)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.total_stages_per_year","page":"Manual","title":"PSRClassesInterface.total_stages_per_year","text":"total_stages_per_year(data::AbstractData)\n\nReturns the total number of stages per year of the case.\n\nExample:\n\nPSRI.total_stages_per_year(data)\n\n\n\n\n\n","category":"function"},{"location":"manual/#Study-duration-and-blocking","page":"Manual","title":"Study duration and blocking","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.BlockDurationMode\nPSRClassesInterface.stage_duration\nPSRClassesInterface.block_duration\nPSRClassesInterface.block_from_stage_hour","category":"page"},{"location":"manual/#Read-Scalar-Attributes","page":"Manual","title":"Read Scalar Attributes","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.configuration_parameter\nPSRClassesInterface.get_code\nPSRClassesInterface.get_name\nPSRClassesInterface.get_parm\nPSRClassesInterface.get_parm_1d\nPSRClassesInterface.get_parms\nPSRClassesInterface.get_parms_1d","category":"page"},{"location":"manual/#PSRClassesInterface.configuration_parameter","page":"Manual","title":"PSRClassesInterface.configuration_parameter","text":"configuration_parameter(\n data::AbstractData,\n attribute::String,\n default::T\n) where T <: MainTypes\n\nReturns the required configuration parameter from the case. If the parameter is not registered returns the default value.\n\nconfiguration_parameter(\n data::AbstractData,\n attribute::String,\n default::Vector{T},\n) where T <: MainTypes\n\nReturns the rquired configuration parameters from the case that are vectors that are vectors. If the parameter is not registered returns the default value.\n\nExamples:\n\nPSRI.configuration_parameter(data, \"MaximoIteracoes\", 0)\nPSRI.configuration_parameter(data, \"MinOutflowPenalty\", 0.0)\n\nPSRI.configuration_parameter(data, \"DeficitCost\", [0.0])\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_code","page":"Manual","title":"PSRClassesInterface.get_code","text":"get_code(data::AbstractData, collection::String)\n\nReturns a Vector{Int32} containing the code of each element in collection.\n\nExample:\n\nPSRI.get_code(data, \"PSRThermalPlant\")\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_name","page":"Manual","title":"PSRClassesInterface.get_name","text":"get_name(data::AbstractData, collection::String)\n\nReturns a Vector{String} containing the name of each element in collection.\n\nExample:\n\nPSRI.get_name(data, \"PSRThermalPlant\")\nPSRI.get_name(data, \"PSRGaugingStation\")\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_parm","page":"Manual","title":"PSRClassesInterface.get_parm","text":"get_parm(\n data::AbstractData,\n collection::String,\n attribute::String,\n index::Integer,\n ::Type{T};\n default::T = _default_value(T),\n) where T\n\nReturns a T containing the the value from attribute of collection. This function is used to get data from collections that don't vary over time.\n\nExample:\n\nPSRI.get_parm(data, \"PSRBattery\", \"Einic\", Float64, 1)\nPSRI.get_parm(data, \"PSRBattery\", \"ChargeRamp\", Float64, 1)\nPSRI.get_parm(data, \"PSRBattery\", \"DischargeRamp\", Float64, 1)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_parm_1d","page":"Manual","title":"PSRClassesInterface.get_parm_1d","text":"get_parm_1d(\n data::AbstractData,\n collection::String,\n attribute::String,\n index::Integer,\n ::Type{T};\n default::T = _default_value(T),\n) where T\n\nReturns a T containing the the value from attribute of collection. This function is used to get data from collections that don't vary over time.\n\nExample:\n\nPSRI.get_parm_1d(data, \"PSRHydroPlant\", \"FP\", Float64, 1)\nPSRI.get_parm_1d(data, \"PSRHydroPlant\", \"FP.VOL\", Float64, 1)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_parms","page":"Manual","title":"PSRClassesInterface.get_parms","text":"get_parms(\n data::AbstractData,\n collection::String,\n attribute::String,\n ::Type{T};\n validate::Bool = true,\n ignore::Bool = false,\n default::T = _default_value(T),\n) where T\n\nReturns a Vector{T} containing the elements in collection to a vector in julia. This function is used to get data from collections that don't vary over time\n\nExample:\n\nPSRI.get_parms(data, \"PSRBattery\", \"Einic\", Float64)\nPSRI.get_parms(data, \"PSRBattery\", \"ChargeRamp\", Float64)\nPSRI.get_parms(data, \"PSRBattery\", \"DischargeRamp\", Float64)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_parms_1d","page":"Manual","title":"PSRClassesInterface.get_parms_1d","text":"get_parms_1d(\n data::AbstractData,\n collection::String,\n attribute::String,\n ::Type{T};\n validate::Bool = true,\n ignore::Bool = false,\n default::T = _default_value(T),\n) where T\n\nReturns a Vector{T} containing the elements in collection to a vector in julia. This function is used to get data from collections that don't vary over time\n\nExample:\n\nPSRI.get_parm_1d(data, \"PSRHydroPlant\", \"FP\", Float64)\nPSRI.get_parm_1d(data, \"PSRHydroPlant\", \"FP.VOL\", Float64)\n\n\n\n\n\n","category":"function"},{"location":"manual/#Read-Vector-Attributes","page":"Manual","title":"Read Vector Attributes","text":"","category":"section"},{"location":"manual/#Time-controller","page":"Manual","title":"Time controller","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.mapped_vector\nPSRClassesInterface.go_to_stage\nPSRClassesInterface.go_to_dimension\nPSRClassesInterface.update_vectors!","category":"page"},{"location":"manual/#PSRClassesInterface.mapped_vector","page":"Manual","title":"PSRClassesInterface.mapped_vector","text":"mapped_vector(\n data::AbstractData,\n collection::String,\n attribute::String,\n ::Type{T},\n dim1::String=\"\",\n dim2::String=\"\";\n ignore::Bool=false,\n map_key = collection, # reference for PSRMap pointer, if empty use class name\n filters = String[], # for calling just within a subset instead of the full call\n) where T\n\nMaps a Vector{T} containing the elements in collection to a vector in julia. When the function update_vectors! is called the elements of the vector will be updated to the according elements registered at the current data.time_controller.\n\nExample:\n\nexisting = PSRI.mapped_vector(data, \"PSRThermalPlant\", \"Existing\", Int32)\npot_inst = PSRI.mapped_vector(data, \"PSRThermalPlant\", \"PotInst\", Float64)\n\nFor more information please read the example Reading basic thermal generator parameters\n\nnote: Differences between the OpenInterface and ClassicInterface\nWhen using mapped_vector in the OpenInterface mode the vector will be mapped with the correct values at first hand. When using mapped_vector in the ClassicInterface mode you should call update_vectors! to get the good values for the collection, otherwise you might only get a vector of zeros.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.go_to_stage","page":"Manual","title":"PSRClassesInterface.go_to_stage","text":"go_to_stage(data::AbstractData, stage::Integer)\n\nGoes to the stage in the data time controller.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.go_to_dimension","page":"Manual","title":"PSRClassesInterface.go_to_dimension","text":"go_to_dimension(data::AbstractData, name::String, value::Integer)\n\nMoves time controller reference of vectors indexed by dimension name to the index value.\n\nExample:\n\ncesp = PSRI.mapped_vector(data, \"PSRThermalPlant\", \"CEsp\", Float64, \"segment\", \"block\")\n\nPSRI.go_to_stage(data, 1)\n\nPSRI.go_to_dimension(data, \"segment\", 1)\nPSRI.go_to_dimension(data, \"block\", 1)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.update_vectors!","page":"Manual","title":"PSRClassesInterface.update_vectors!","text":"update_vectors!(data::AbstractData)\n\nUpdate all mapped vectors according to the time controller inside data.\n\nupdate_vectors!(data::AbstractData, filters::Vector{String})\n\nUpdate filtered classes of mapped vectors according to the time controller inside data.\n\n\n\n\n\n","category":"function"},{"location":"manual/#Direct-access","page":"Manual","title":"Direct access","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.get_vector\nPSRClassesInterface.get_vector_1d\nPSRClassesInterface.get_vector_2d\nPSRClassesInterface.get_vectors\nPSRClassesInterface.get_vectors_1d\nPSRClassesInterface.get_vectors_2d\nPSRClassesInterface.get_nonempty_vector\nPSRClassesInterface.get_series","category":"page"},{"location":"manual/#PSRClassesInterface.get_vector","page":"Manual","title":"PSRClassesInterface.get_vector","text":"PSRI.get_vector(\n data::AbstractData,\n collection::String,\n attribute::String,\n index::Integer,\n ::Type{T};\n default::T = _default_value(T),\n) where T\n\nReturns a Vector{T} of entries of the attribute of collection at the element with index index.\n\nExample:\n\nPSRI.get_vector(data, \"PSRGaugingStation\", \"Vazao\", 1, Float64)\nPSRI.get_vector(data, \"PSRGaugingStation\", \"Data\", 1, Dates.Date)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_vector_1d","page":"Manual","title":"PSRClassesInterface.get_vector_1d","text":"PSRI.get_vector_1d(\n data::AbstractData,\n collection::String,\n attribute::String,\n index::Integer,\n ::Type{T};\n default::T = _default_value(T),\n) where T\n\nReturns a Vector{Vector{T}} of entries of the attribute of collection at the element with index index. The outer vector contains one entry per index in dimension 1, while the inner vector is sized according to the main vector index which is tipicaaly time.\n\nExample:\n\nPSRI.get_vector_1d(data, \"PSRArea\", \"Export\", 1, Float64)\nPSRI.get_vector_1d(data, \"PSRLoad\", \"P\", 1, Float64)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_vector_2d","page":"Manual","title":"PSRClassesInterface.get_vector_2d","text":"PSRI.get_vector_2d(\n data::AbstractData,\n collection::String,\n attribute::String,\n index::Integer,\n ::Type{T};\n default::T = _default_value(T),\n) where T\n\nReturns a Matrix{Vector{T}} of entries of the attribute of collection at the element with index index. The outer matrix contains one entry per index in dimension 1 and dimension 2, while the inner vector is sized according to the main vector index which is tipicaaly time.\n\nExample:\n\nPSRI.get_vector_2d(data, \"PSRThermalPlant\", \"CEsp\", 1, Float64)\nPSRI.get_vector_2d(data, \"PSRFuelConsumption\", \"CEsp\", 1, Float64)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_vectors","page":"Manual","title":"PSRClassesInterface.get_vectors","text":"PSRI.get_vectors(\n data::AbstractData,\n collection::String,\n attribute::String,\n ::Type{T};\n default::T = _default_value(T),\n) where T\n\nReturns a Vector{Vector{T}} of entries of the attribute of collection. Each entry of the outer vector corresponding to an element of the collection.\n\nExample:\n\nPSRI.get_vectors(data, \"PSRGaugingStation\", \"Vazao\", Float64)\nPSRI.get_vectors(data, \"PSRGaugingStation\", \"Data\", Dates.Date)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_vectors_1d","page":"Manual","title":"PSRClassesInterface.get_vectors_1d","text":"PSRI.get_vectors_1d(\n data::AbstractData,\n collection::String,\n attribute::String,\n ::Type{T},\n) where T\n\nReturns a Vector{Vector{Vector{T}}} of entries of the attribute of collection. Each entry of the outer vector corresponding to an element of the collection. For the containt of the 2 inner vectors see get_vector_1d.\n\nExample:\n\nPSRI.get_vectors_1d(data, \"PSRArea\", \"Export\", Float64)\nPSRI.get_vectors_1d(data, \"PSRLoad\", \"P\", Float64)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_vectors_2d","page":"Manual","title":"PSRClassesInterface.get_vectors_2d","text":"PSRI.get_vectors_2d(\n data::AbstractData,\n collection::String,\n attribute::String,\n ::Type{T},\n) where T\n\nReturns a Vector{Matrix{Vector{T}}} of entries of the attribute of collection. Each entry of the outer vector corresponding to an element of the collection. For the containt of the Matrix{Vector{T}} see get_vector_2d.\n\nExample:\n\nPSRI.get_vectors_2d(data, \"PSRThermalPlant\", \"CEsp\", Float64)\nPSRI.get_vectors_2d(data, \"PSRFuelConsumption\", \"CEsp\", Float64)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_nonempty_vector","page":"Manual","title":"PSRClassesInterface.get_nonempty_vector","text":"get_nonempty_vector(\n data::AbstractData,\n colllection::String,\n attribute::String,\n)\n\nReturns a vector of booleans with the number of elements of the collection. true means the vector associated with the given attribute is non-emepty, false means it is empty.\n\nExample:\n\nPSRI.get_nonempty_vector(data, \"PSRThermalPlant\", \"ChroGerMin\")\nPSRI.get_nonempty_vector(data, \"PSRThermalPlant\", \"SpinningReserve\")\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_series","page":"Manual","title":"PSRClassesInterface.get_series","text":"function get_series(\n data::Data,\n collection::String,\n indexing_attribute::String,\n index::Int,\n)\n\nRetrieves a SeriesTable object with all attributes from an element that are indexed by index_attr.\n\nExample\n\njulia> PSRI.get_series(data, \"PSRThermalPlant\", \"Data\", 1)\nDict{String, Vector} with 13 entries:\n \"GerMin\" => [0.0]\n \"GerMax\" => [888.0]\n \"NGas\" => [nothing]\n \"IH\" => [0.0]\n \"ICP\" => [0.0]\n \"Data\" => [\"1900-01-01\"]\n \"CoefE\" => [1.0]\n \"PotInst\" => [888.0]\n \"Existing\" => [0]\n \"sfal\" => [0]\n \"NAdF\" => [0]\n \"Unidades\" => [1]\n \"StartUp\" => [0.0]\n\n\n\n\n\n","category":"function"},{"location":"manual/#Relations-between-collections","page":"Manual","title":"Relations between collections","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.RelationType\nPSRClassesInterface.is_vector_relation\nPSRClassesInterface.get_references\nPSRClassesInterface.get_vector_references\nPSRClassesInterface.get_map\nPSRClassesInterface.get_vector_map\nPSRClassesInterface.get_reverse_map\nPSRClassesInterface.get_reverse_vector_map\nPSRClassesInterface.get_related\nPSRClassesInterface.get_vector_related","category":"page"},{"location":"manual/#PSRClassesInterface.is_vector_relation","page":"Manual","title":"PSRClassesInterface.is_vector_relation","text":"is_vector_relation(relation::PSRI.PMD.RelationType)\n\nReturns true is relation is a vector relation.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_references","page":"Manual","title":"PSRClassesInterface.get_references","text":"get_references(\n data::AbstractData,\n lst_from::String,\n lst_to::String;\n relation_type::RelationType = RELATION_1_TO_1, # type of the direct relation\n)\n\nRetrurn a Vector{String} with the references between collections given a certain RelationType.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_vector_references","page":"Manual","title":"PSRClassesInterface.get_vector_references","text":"get_vector_references(\n data::AbstractData,\n lst_from::String,\n lst_to::String;\n relation_type::RelationType = RELATION_1_TO_N, # type of the direct relation\n)\n\nRetrurn a Vector{Vector{String}} with the references between collections given a certain RelationType.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_map","page":"Manual","title":"PSRClassesInterface.get_map","text":"get_map(\n data::AbstractData,\n lst_from::String,\n lst_to::String;\n allow_empty::Bool = true,\n relation_type::RelationType = RELATION_1_TO_1, # type of the direct relation\n)\n\nReturns a Vector{Int32} with the map between collections given a certain RelationType. If the map is a vector [3, 2, 1] it means that the element 1 of lst_from is related to the element 3 of lst_to. If the relation does not exist it might return -1 or some garbage value.\n\nExamples:\n\nPSRI.get_map(data, \"PSRBattery\", \"PSRSystem\")\nPSRI.get_map(data, \"PSRMaintenanceData\", \"PSRThermalPlant\")\n\nPSRI.get_map(\n data,\n \"PSRHydroPlant\",\n \"PSRHydroPlant\";\n relation_type = PSRI.PMD.RELATION_TURBINE_TO,\n)\nPSRI.get_map(\n data,\n \"PSRHydroPlant\",\n \"PSRHydroPlant\";\n relation_type = PSRI.PMD.RELATION_SPILL_TO,\n)\nPSRI.get_map(\n data,\n \"PSRHydroPlant\",\n \"PSRHydroPlant\";\n relation_type = PSRI.PMD.RELATION_INFILTRATE_TO,\n)\nPSRI.get_map(\n data,\n \"PSRHydroPlant\",\n \"PSRHydroPlant\";\n relation_type = PSRI.PMD.RELATION_STORED_ENERGY_DONWSTREAM,\n)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_vector_map","page":"Manual","title":"PSRClassesInterface.get_vector_map","text":"get_vector_map(\n data::AbstractData,\n collection_from::String,\n collection_to::String;\n relation_type::RelationType = RELATION_1_TO_N,\n)\n\nReturns a Vector{Vector{Int32}} to represent the relation between each element of collection_from to multiple elements of collection_to.\n\nSince multiple relations might be available one might need to specify relation_type.\n\nExample:\n\nPSRI.get_vector_map(data, \"PSRInterconnectionSumData\", \"PSRInterconnection\")\nPSRI.get_vector_map(data, \"PSRReserveGenerationConstraintData\", \"PSRHydroPlant\")\nPSRI.get_vector_map(\n data,\n \"PSRReserveGenerationConstraintData\",\n \"PSRThermalPlant\";\n relation_type = PSRI.PMD.RELATION_BACKED,\n)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_reverse_map","page":"Manual","title":"PSRClassesInterface.get_reverse_map","text":"get_reverse_map(\n data::AbstractData,\n lst_from::String,\n lst_to::String;\n original_relation_type::RelationType = RELATION_1_TO_1,\n)\n\nObtains the relation between lst_from and lst_to though original_relation_type. But returns a Vector{Int32} with the relation reversed. Some relations cannot be reversed this way since they are not bijections, in this case use get_reverse_vector_map.\n\nSee also get_map, get_vector_map, get_reverse_vector_map.\n\nExample:\n\nPSRI.get_reverse_map(data, \"PSRMaintenanceData\", \"PSRHydroPlant\")\n# which is te reverse of\nPSRI.get_map(data, \"PSRMaintenanceData\", \"PSRHydroPlant\")\n\nPSRI.get_reverse_map(data, \"PSRGenerator\", \"PSRThermalPlant\")\n# which is the reverse of\nPSRI.get_map(data, \"PSRGenerator\", \"PSRThermalPlant\")\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_reverse_vector_map","page":"Manual","title":"PSRClassesInterface.get_reverse_vector_map","text":"get_reverse_vector_map(\n data::AbstractData,\n lst_from::String,\n lst_to::String;\n original_relation_type::RelationType = RELATION_1_TO_N,\n)\n\nObtains the relation between lst_from and lst_to though original_relation_type. But returns a Vector{Vector{Int32}} with the relation reversed.\n\nSome relations are bijections, in these cases it is also possible to use use get_reverse_map.\n\nSee also get_map, get_vector_map, get_reverse_vector_map.\n\nExample:\n\n# upstream turbining hydros\nPSRI.get_reverse_vector_map(\n data,\n \"PSRHydroPlant\",\n \"PSRHydroPlant\";\n original_relation_type = PSRI.PMD.RELATION_TURBINE_TO,\n)\n# which is the reverse of\nPSRI.get_map(\n data,\n \"PSRHydroPlant\",\n \"PSRHydroPlant\";\n relation_type = PSRI.PMD.RELATION_TURBINE_TO,\n)\n\nPSRI.get_reverse_vector_map(\n data,\n \"PSRGenerator\",\n \"PSRBus\";\n original_relation_type = PSRI.PMD.RELATION_1_TO_1,\n)\n# which is the reverse of\nPSRI.get_map(data, \"PSRGenerator\", \"PSRBus\")\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_related","page":"Manual","title":"PSRClassesInterface.get_related","text":"get_related(\n data::AbstractData,\n source::String,\n target::String,\n source_index::Integer,\n relation_type = RELATION_1_TO_1,\n)\n\nReturns the index of the element in collection target related to the element in the collection source element indexed by source_index according to the scalar relation relation_type.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_vector_related","page":"Manual","title":"PSRClassesInterface.get_vector_related","text":"get_vector_related(\n data::AbstractData,\n source::String,\n target::String,\n source_index::Integer,\n relation_type = RELATION_1_TO_N,\n)\n\nReturns the vector of indices of the elements in collection target related to the element in the collection source element indexed by source_index according to the scalar relation relation_type.\n\n\n\n\n\n","category":"function"},{"location":"manual/#Reflection","page":"Manual","title":"Reflection","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.get_attribute_dim1\nPSRClassesInterface.get_attribute_dim2\nPSRClassesInterface.get_collections\nPSRClassesInterface.get_attributes\nPSRClassesInterface.get_attribute_struct\nPSRClassesInterface.get_data_struct\nPSRClassesInterface.Attribute\nPSRClassesInterface.get_attributes_indexed_by\nPSRClassesInterface.get_relations\nPSRClassesInterface.get_attribute_dim","category":"page"},{"location":"manual/#PSRClassesInterface.get_attribute_dim1","page":"Manual","title":"PSRClassesInterface.get_attribute_dim1","text":"get_attribute_dim1(\n data::AbstractData,\n collection::String,\n attribute::string,\n index::Integer;\n)\n\nReturns the size of dimension 1 of attribute from collection at element index. Errors if attribute has zero dimensions.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_attribute_dim2","page":"Manual","title":"PSRClassesInterface.get_attribute_dim2","text":"get_attribute_dim2(\n data::AbstractData,\n collection::String,\n attribute::string,\n index::Integer;\n)\n\nReturns the size of dimension 2 of attribute from collection at element index. Errors if attribute has zero or one dimensions.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_collections","page":"Manual","title":"PSRClassesInterface.get_collections","text":"get_collections(data::AbstractData)\n\nReturn Vector{String} of valid collections (depends on loaded pmd files).\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_attributes","page":"Manual","title":"PSRClassesInterface.get_attributes","text":"get_attributes(data::AbstractData, collection::String)\n\nReturn Vector{String} of valid attributes from collection.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_attribute_struct","page":"Manual","title":"PSRClassesInterface.get_attribute_struct","text":"get_attribute_struct(\n data::AbstractData,\n collection::String,\n attribute::String,\n)\n\nReturns a struct of type Attribute with fields:\n\nname::String = attribute name\nis_vector::Bool = true if attribute is a vector (tipically, varies in time)\ntype::DataType = attribute type (tipically: Int32, Float64, String, Dates.Date)\ndim::Int = number of additional dimensions\nindex::String = if a vector represents the indexing vector (might be empty)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_data_struct","page":"Manual","title":"PSRClassesInterface.get_data_struct","text":"get_attribute_struct(data::AbstractData)\n\nReturn a struct of type DataStruct with collection names (strings) as keys and maps from attributes names (string) to attributes data definitions Attribute.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.Attribute","page":"Manual","title":"PSRClassesInterface.Attribute","text":"struct Attribute\n name::String\n is_vector::Bool\n type::DataType\n dim::Int\n index::String\nend\n\n\n\n\n\n","category":"type"},{"location":"manual/#PSRClassesInterface.get_attributes_indexed_by","page":"Manual","title":"PSRClassesInterface.get_attributes_indexed_by","text":"get_attributes_indexed_by(\n data::AbstractData,\n collection::String,\n indexing_attribute::String\n)\n\nReturn Vector{String} of valid vector attributes from collection that are indexed by indexing_attribute.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_relations","page":"Manual","title":"PSRClassesInterface.get_relations","text":"get_relations(data::AbstractData, collection::String)\n\nReturns a Tuple{String, Vector{PMD.Relation}} with relating collection and their relation type associated to collection.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.get_attribute_dim","page":"Manual","title":"PSRClassesInterface.get_attribute_dim","text":"get_attribute_dim(attribute_struct::Attribute)\n\n\n\n\n\n","category":"function"},{"location":"manual/#Read-and-Write-Graf-files","page":"Manual","title":"Read and Write Graf files","text":"","category":"section"},{"location":"manual/#Open-and-Close","page":"Manual","title":"Open and Close","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.AbstractReader\nPSRClassesInterface.AbstractWriter\nPSRClassesInterface.open\nPSRClassesInterface.close","category":"page"},{"location":"manual/#PSRClassesInterface.AbstractReader","page":"Manual","title":"PSRClassesInterface.AbstractReader","text":"PSRI.AbstractReader\n\n\n\n\n\n","category":"type"},{"location":"manual/#PSRClassesInterface.AbstractWriter","page":"Manual","title":"PSRClassesInterface.AbstractWriter","text":"PSRI.AbstractWriter\n\n\n\n\n\n","category":"type"},{"location":"manual/#PSRClassesInterface.open","page":"Manual","title":"PSRClassesInterface.open","text":"PSRI.open(::Type{<:AbstractWriter}, path::String; kwargs...)\n\nMethod for opening file and registering time series data. If specified file doesn't exist, the method will create it, otherwise, the previous one will be overwritten. Returns updated AbstractWriter instance.\n\nArguments:\n\nwriter: AbstractWriter instance to be used for opening file.\npath: path to file.\n\nKeyword arguments:\n\nblocks: case's number of blocks.\nscenarios: case's number of scenarios.\nstages: case's number of stages.\nagents: list of element names.\nunit: dimension of the elements' data.\nis_hourly: if data is hourly. If yes, block dimension will be ignored.\nhour_discretization: sub-hour parameter to discretize an hour into minutes.\nname_length: length of element names.\nblock_type: case's type of block.\nscenarios_type: case's type of scenario.\nstage_type: case's type of stage.\ninitial_stage: stage at which to start registry.\ninitial_year: year at which to start registry.\nallow_unsafe_name_length: allow element names outside safety bounds.\n\nExamples:\n\nWriting and reading a time series into a file\n\nPSRI.open(reader::Type{<:AbstractReader}, path::String; kwargs...)\n\nMethod for opening file and reading time series data. Returns updated AbstractReader instance.\n\nArguments:\n\nreader::Type{<:AbstractReader}: AbstractReader instance to be used for opening file.\npath::String: path to file.\n\nKeyword arguments:\n\nis_hourly::Bool: if data to be read is hourly, other than blockly.\nstage_type::PSRI.StageType: the PSRClassesInterface.StageType of the data, defaults to PSRI.STAGE_MONTH.\nheader::Vector{String}: if file has a header with metadata.\nuse_header::Bool: if data from header should be retrieved.\nfirst_stage::Dates.Date: stage at which start reading.\nverbose_header::Bool: if data from header should be displayed during execution.\n\nExamples:\n\nWriting and reading a time series into a file\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.close","page":"Manual","title":"PSRClassesInterface.close","text":"PSRI.close(ior::AbstractReader)\n\nCloses the PSRClassesInterface.AbstractReader instance.\n\n\nPSRI.close(iow::AbstractWriter)\n\nCloses the PSRClassesInterface.AbstractWriter instance.\n\n\n\n\n\n","category":"function"},{"location":"manual/#Write-entire-file","page":"Manual","title":"Write entire file","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.array_to_file","category":"page"},{"location":"manual/#PSRClassesInterface.array_to_file","page":"Manual","title":"PSRClassesInterface.array_to_file","text":"PSRI.array_to_file\n\n\n\n\n\n","category":"function"},{"location":"manual/#Write-registry","page":"Manual","title":"Write registry","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.write_registry","category":"page"},{"location":"manual/#PSRClassesInterface.write_registry","page":"Manual","title":"PSRClassesInterface.write_registry","text":"PSRI.write_registry(\n iow::AbstractWriter,\n data::Vector{T},\n stage::Integer,\n scenario::Integer = 1,\n block::Integer = 1,\n) where T <: Real\n\nWrites a data row into opened file through PSRClassesInterface.AbstractWriter instance.\n\nArguments:\n\niow: PSRI.AbstractWriter instance to be used for accessing file.\ndata: elements data to be written.\nstage: stage of the data to be written.\nscenario: scenarios of the data to be written.\nblock: block of the data to be written.\n\n\n\n\n\n","category":"function"},{"location":"manual/#Header-information","page":"Manual","title":"Header information","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.is_hourly\nPSRClassesInterface.hour_discretization\nPSRClassesInterface.max_stages\nPSRClassesInterface.max_scenarios\nPSRClassesInterface.max_blocks\nPSRClassesInterface.max_blocks_current\nPSRClassesInterface.max_blocks_stage\nPSRClassesInterface.max_agents\nPSRClassesInterface.stage_type\nPSRClassesInterface.initial_stage\nPSRClassesInterface.initial_year\nPSRClassesInterface.data_unit\nPSRClassesInterface.agent_names","category":"page"},{"location":"manual/#PSRClassesInterface.is_hourly","page":"Manual","title":"PSRClassesInterface.is_hourly","text":"PSRI.is_hourly(ior::AbstractReader)\n\nReturns a Bool indicating whether the data in the file read by PSRClassesInterface.AbstractReader is hourly.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.hour_discretization","page":"Manual","title":"PSRClassesInterface.hour_discretization","text":"PSRI.hour_discretization(ior::AbstractReader)\n\nReturns an Int indicating the hour discretization.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.max_stages","page":"Manual","title":"PSRClassesInterface.max_stages","text":"PSRI.max_stages(ior::AbstractReader)\n\nReturns an Int indicating maximum number of stages in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.max_scenarios","page":"Manual","title":"PSRClassesInterface.max_scenarios","text":"PSRI.max_scenarios(ior::AbstractReader)\n\nReturns an Int indicating maximum number of scenarios in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.max_blocks","page":"Manual","title":"PSRClassesInterface.max_blocks","text":"PSRI.max_blocks(ior::AbstractReader)\n\nReturns an Int indicating maximum number of blocks in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.max_blocks_current","page":"Manual","title":"PSRClassesInterface.max_blocks_current","text":"PSRI.max_blocks_current(ior::AbstractReader)\n\nReturns an Int indicating maximum number of blocks in the cuurent stage in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.max_blocks_stage","page":"Manual","title":"PSRClassesInterface.max_blocks_stage","text":"PSRI.max_blocks_stage(ior::AbstractReader, t::Integer)\n\nReturns an Int indicating maximum number of blocks in the stage t in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.max_agents","page":"Manual","title":"PSRClassesInterface.max_agents","text":"PSRI.max_agents(ior::AbstractReader)\n\nReturns an Int indicating maximum number of agents in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.stage_type","page":"Manual","title":"PSRClassesInterface.stage_type","text":"stage_type\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.initial_stage","page":"Manual","title":"PSRClassesInterface.initial_stage","text":"PSRI.initial_stage(ior::AbstractReader)\n\nReturns an Int indicating the initial stage in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.initial_year","page":"Manual","title":"PSRClassesInterface.initial_year","text":"PSRI.initial_year(ior::AbstractReader)\n\nReturns an Int indicating the initial year in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.data_unit","page":"Manual","title":"PSRClassesInterface.data_unit","text":"PSRI.data_unit(ior::AbstractReader)\n\nReturns a String indicating the unit of the data in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.agent_names","page":"Manual","title":"PSRClassesInterface.agent_names","text":"PSRI.agent_names(ior::AbstractReader)\n\nReturns a Vector{String} with the agent names in the file read by PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#Read-entire-file","page":"Manual","title":"Read entire file","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.file_to_array\nPSRClassesInterface.file_to_array_and_header","category":"page"},{"location":"manual/#PSRClassesInterface.file_to_array","page":"Manual","title":"PSRClassesInterface.file_to_array","text":"PSRI.file_to_array(::Type{T}, path::String; use_header::Bool = true, header::Vector{String} = String[]) where T <: AbstractReader\n\nWrite a file to an array\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.file_to_array_and_header","page":"Manual","title":"PSRClassesInterface.file_to_array_and_header","text":"PSRI.file_to_array_and_header(::Type{T}, path::String; use_header::Bool = true, header::Vector{String} = String[]) where T <: AbstractReader\n\nWrite a file to an array and header\n\n\n\n\n\n","category":"function"},{"location":"manual/#Read-registry","page":"Manual","title":"Read registry","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.current_stage\nPSRClassesInterface.current_scenario\nPSRClassesInterface.current_block\nPSRClassesInterface.goto\nPSRClassesInterface.next_registry","category":"page"},{"location":"manual/#PSRClassesInterface.current_stage","page":"Manual","title":"PSRClassesInterface.current_stage","text":"PSRI.current_stage(ior::AbstractReader)\n\nReturns an Int indicating the current stage in the stream of the PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.current_scenario","page":"Manual","title":"PSRClassesInterface.current_scenario","text":"PSRI.current_scenario(ior::AbstractReader)\n\nReturns an Int indicating the current scenarios in the stream of the PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.current_block","page":"Manual","title":"PSRClassesInterface.current_block","text":"PSRI.current_block(ior::AbstractReader)\n\nReturns an Int indicating the current block in the stream of the PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.goto","page":"Manual","title":"PSRClassesInterface.goto","text":"PSRI.goto(\n ior::AbstractReader, \n t::Integer, \n s::Integer = 1, \n b::Integer = 1\n)\n\nGoes to the registry of the stage t, scenario s and block b.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.next_registry","page":"Manual","title":"PSRClassesInterface.next_registry","text":"PSRI.next_registry(ior::AbstractReader)\n\nGoes to the next registry on the PSRClassesInterface.AbstractReader.\n\n\n\n\n\n","category":"function"},{"location":"manual/#File-conversion","page":"Manual","title":"File conversion","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.convert_file\nPSRClassesInterface.add_reader!","category":"page"},{"location":"manual/#PSRClassesInterface.convert_file","page":"Manual","title":"PSRClassesInterface.convert_file","text":"convert_file\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.add_reader!","page":"Manual","title":"PSRClassesInterface.add_reader!","text":"add_reader!\n\n\n\n\n\n","category":"function"},{"location":"manual/#Reader-mapper","page":"Manual","title":"Reader mapper","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.ReaderMapper\nPSRClassesInterface.add_reader!\n\nPSRClassesInterface.close","category":"page"},{"location":"manual/#PSRClassesInterface.ReaderMapper","page":"Manual","title":"PSRClassesInterface.ReaderMapper","text":"ReaderMapper{T}\n\n\n\n\n\n","category":"type"},{"location":"manual/#Modification-API","page":"Manual","title":"Modification API","text":"","category":"section"},{"location":"manual/","page":"Manual","title":"Manual","text":"PSRClassesInterface.create_study\nPSRClassesInterface.create_element!\nPSRClassesInterface.set_parm!\nPSRClassesInterface.set_vector!\nPSRClassesInterface.set_series!\nPSRClassesInterface.write_data\nPSRClassesInterface.set_related!\nPSRClassesInterface.set_vector_related!","category":"page"},{"location":"manual/#PSRClassesInterface.create_study","page":"Manual","title":"PSRClassesInterface.create_study","text":"create_study(::AbstractStudyInterface; kwargs...)\n\nReturns the Data object of a new study.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.create_element!","page":"Manual","title":"PSRClassesInterface.create_element!","text":"create_element!(\n data::Data,\n collection::String,\n ps::Pair{String,<:Any};\n default::Union{Dict{String,Any},Nothing} = nothing\n)\n\nCreates a new instance of the given collection and returns its index.\n\nExample:\n\nindex = PSRI.create_element!(data, \"PSRClass\")\n\nPSRI.set_parm!(data, \"PSRClass\", index, \"PSRAttr\", value)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.set_parm!","page":"Manual","title":"PSRClassesInterface.set_parm!","text":"set_parm!(\n data::Data,\n collection::String,\n attribute::String,\n index::Integer,\n value::T,\n) where {T <: MainTypes}\n\nDefines the value of a scalar parameter.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.set_vector!","page":"Manual","title":"PSRClassesInterface.set_vector!","text":"function set_vector!(\n data::Data,\n collection::String,\n attribute::String,\n index::Int,\n buffer::Vector{T}\n) where {T<:MainTypes}\n\nUpdates a data vector according to the given buffer. Note: Modifying current vector length is not allowed: use set_series! instead.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.set_series!","page":"Manual","title":"PSRClassesInterface.set_series!","text":"function set_series!(\n data::Data,\n collection::String,\n index_attr::String,\n index::Int,\n buffer::Dict{String,Vector}\n)\n\nUpdates serial (indexed) data. All columns must be the same as before. The series length is allowed to be changed, but all vectors in the new series must have equal length.\n\njulia> series = Dict{String, Vector}(\n \"GerMin\" => [0.0, 1.0],\n \"GerMax\" => [888.0, 777.0],\n \"NGas\" => [nothing, nothing],\n \"IH\" => [0.0, 0.0],\n \"CoefE\" => [1.0, 2.0],\n \"PotInst\" => [888.0, 777.0],\n \"ICP\" => [0.0, 0.0],\n \"Data\" => [\"1900-01-01\", \"1900-01-02\"],\n \"Existing\" => [0, 0],\n \"sfal\" => [0, 1],\n \"NAdF\" => [0, 0],\n \"Unidades\" => [1, 1],\n \"StartUp\" => [0.0, 2.0]\n );\n\njulia> PSRI.set_series!(data, \"PSRThermalPlant\", 1, \"Data\", series)\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.write_data","page":"Manual","title":"PSRClassesInterface.write_data","text":"write_data(data::Data, path::String)\n\nWrites data to file in JSON format.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.set_related!","page":"Manual","title":"PSRClassesInterface.set_related!","text":"set_related!(\n data::AbstractData,\n source::String,\n target::String,\n source_index::Integer,\n target_index::Integer;\n relation_type = RELATION_1_TO_1,\n)\n\nSets the element source_index from collection source to be related to the element target_index from collection target in the scalar relation of type relation_type.\n\n\n\n\n\n","category":"function"},{"location":"manual/#PSRClassesInterface.set_vector_related!","page":"Manual","title":"PSRClassesInterface.set_vector_related!","text":"set_vector_related!(\n data::AbstractData,\n source::String,\n target::String,\n source_index::Integer,\n target_index::Vector{<:Integer};\n relation_type = RELATION_1_TO_N,\n)\n\nSets the element source_index from collection source to be related to the elements in target_index from collection target in the vector relation of type relation_type.\n\n\n\n\n\n","category":"function"},{"location":"psrdatabasesqlite/introduction/#SQLite-101","page":"SQLite 101","title":"SQLite 101","text":"","category":"section"},{"location":"psrdatabasesqlite/introduction/","page":"SQLite 101","title":"SQLite 101","text":"SQLite is a software library that provides a relational database management system. The lite in SQLite means light weight in terms of setup, database administration, and required resource. SQLite does NOT require a server to run.","category":"page"},{"location":"psrdatabasesqlite/introduction/","page":"SQLite 101","title":"SQLite 101","text":"Although PSRI provides a simplified interface, similar to PSRI.OpenStudy, to read and write data in SQLite format, it is important to understand the basics of SQLite.","category":"page"},{"location":"psrdatabasesqlite/introduction/","page":"SQLite 101","title":"SQLite 101","text":"To learn the basics, we recommend the following resources:","category":"page"},{"location":"psrdatabasesqlite/introduction/","page":"SQLite 101","title":"SQLite 101","text":"SQLite Tutorial\nSQLite Documentation","category":"page"},{"location":"psrdatabasesqlite/introduction/","page":"SQLite 101","title":"SQLite 101","text":"tip: Tip\nWe recommend using SQLiteStudio to debug and visualize your SQLite database. You can download it here.","category":"page"},{"location":"openstudy_files/file_diagram/#OpenStudy-Files-and-Structs-101","page":"OpenStudy Files and Structs 101","title":"OpenStudy Files and Structs 101","text":"","category":"section"},{"location":"openstudy_files/file_diagram/","page":"OpenStudy Files and Structs 101","title":"OpenStudy Files and Structs 101","text":"When creating or loading a study using the OpenStudy framework, PSRI uses different files. This flowchart shows the order in which the files are used.","category":"page"},{"location":"openstudy_files/file_diagram/","page":"OpenStudy Files and Structs 101","title":"OpenStudy Files and Structs 101","text":"The classes and their attributes are defined in a PMD file.\nThen, a Model Template file is used to map the classes to collections in the study.\nUsing the Model Template and the PMD file, the Data Struct file is created.\nPSRI loads the Data Struct, Relation Mapper and Defaults files into structs and create a study, whose data will be stored in a file named psrclasses.json.","category":"page"},{"location":"openstudy_files/file_diagram/","page":"OpenStudy Files and Structs 101","title":"OpenStudy Files and Structs 101","text":"(Image: OpenStudy Diagram)","category":"page"},{"location":"openstudy_files/file_diagram/#How-the-structs-are-used","page":"OpenStudy Files and Structs 101","title":"How the structs are used","text":"","category":"section"},{"location":"openstudy_files/file_diagram/#Creating-an-element","page":"OpenStudy Files and Structs 101","title":"Creating an element","text":"","category":"section"},{"location":"openstudy_files/file_diagram/","page":"OpenStudy Files and Structs 101","title":"OpenStudy Files and Structs 101","text":"When creating an element from a collection, OpenStudy uses the Data Struct, Relation Mapper and Defaults files to check if:","category":"page"},{"location":"openstudy_files/file_diagram/","page":"OpenStudy Files and Structs 101","title":"OpenStudy Files and Structs 101","text":"The collection is defined in the Data Struct file.\nThe element has all the attributes defined in the Data Struct file.\nIn the case where the element does not have all the attributes, the Defaults file has the remaining ones.","category":"page"},{"location":"openstudy_files/file_diagram/#Creating-a-relation","page":"OpenStudy Files and Structs 101","title":"Creating a relation","text":"","category":"section"},{"location":"openstudy_files/file_diagram/","page":"OpenStudy Files and Structs 101","title":"OpenStudy Files and Structs 101","text":"When creating a relation between two collections, OpenStudy uses the Relation Mapper to check if:","category":"page"},{"location":"openstudy_files/file_diagram/","page":"OpenStudy Files and Structs 101","title":"OpenStudy Files and Structs 101","text":"The relation is defined in the Relation Mapper\nThe elements exist in the study","category":"page"},{"location":"openstudy_files/relation_mapper/#Relation-Mapper","page":"Relation Mapper","title":"Relation Mapper","text":"","category":"section"},{"location":"openstudy_files/relation_mapper/","page":"Relation Mapper","title":"Relation Mapper","text":"If you have already checked the PMD manual, you know that a PMD file can define relations between models. When these relations are parsed, they are stored in a Julia dictionary, the Relation Mapper.","category":"page"},{"location":"openstudy_files/relation_mapper/#Relation-Mapper-JSON-file","page":"Relation Mapper","title":"Relation Mapper JSON file","text":"","category":"section"},{"location":"openstudy_files/relation_mapper/","page":"Relation Mapper","title":"Relation Mapper","text":"However, it is also possible to fill the Relation Mapper with a JSON file, that follows the same structure as OpenStudy's dictionary for relations.","category":"page"},{"location":"openstudy_files/relation_mapper/","page":"Relation Mapper","title":"Relation Mapper","text":"In the example below, we have a Relation Mapper file with the following information:","category":"page"},{"location":"openstudy_files/relation_mapper/","page":"Relation Mapper","title":"Relation Mapper","text":"The model CustomModel has two relations defined, one with SecondCollection and another with ThirdCollection.\nThe relation with SecondCollection is a 1_to_1 relation, and the parameter is called system. \nThe relation with ThirdCollection is a 1_to_N relation, and the parameter is called station. \nThe model SecondCollection has two relations with FourthCollection.\nThe first relation with FourthCollection is a FROM relation, and the parameter is called no1.\nThe second relation with FourthCollection is a TO relation, and the parameter is called no2.","category":"page"},{"location":"openstudy_files/relation_mapper/","page":"Relation Mapper","title":"Relation Mapper","text":"info: 💭 Reminder\nThe relation parameter stores the reference_id from the element of the Target Collection. See PMD manual","category":"page"},{"location":"openstudy_files/relation_mapper/","page":"Relation Mapper","title":"Relation Mapper","text":"{\n \"CustomCollection\": {\n \"SecondCollection\": {\n \"system\": {\n \"is_vector\": false,\n \"type\": \"1_TO_1\"\n }\n },\n \"ThirdCollection\": {\n \"station\": {\n \"is_vector\": true,\n \"type\": \"1_TO_N\"\n }\n }\n },\n \"SecondCollection\": {\n \"FourthCollection\": {\n \"no1\": {\n \"is_vector\": false,\n \"type\": \"FROM\"\n },\n \"no2\": {\n \"is_vector\": false,\n \"type\": \"TO\"\n }\n }\n }\n}","category":"page"},{"location":"examples/graf_files/#Graf-Files-and-Time-Series","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"","category":"section"},{"location":"examples/graf_files/#Time-Series","page":"Graf Files and Time Series","title":"Time Series","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"Some attributes in a Study represent a time series indexed by another attribute. Here we will be setting a time series for the attribute EmissionCost, from PSRGasEmission, which is indexed by DateEmissionCost.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"First we create a Dict with EmissionCost and DateEmissionCost data.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"using PSRClassesInterface\nPSRI = PSRClassesInterface\nusing Dates\n\nseries = Dict{String,Vector}(\n \"DateEmissionCost\" => [\n Dates.Date(\"1900-01-01\"),\n Dates.Date(\"2013-01-01\"),\n Dates.Date(\"2013-02-01\")\n ],\n \"EmissionCost\" => [0.0,3.0,3.0]\n )","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"Then, we save the time series to the study using the function PSRClassesInterface.set_series!. Notice that when we are saving this time series, we are specifying the element from the collection that has this series, using its index.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"temp_path = joinpath(tempdir(), \"PSRI\")\n\ndata = PSRI.create_study(PSRI.OpenInterface(), data_path = temp_path)\n\nPSRI.create_element!(data, \"PSRGasEmission\")\n\nPSRI.set_series!(\n data, \n \"PSRGasEmission\", \n \"DateEmissionCost\",\n 1, # element index in collection\n series\n )","category":"page"},{"location":"examples/graf_files/#Using-a-SeriesTable","page":"Graf Files and Time Series","title":"Using a SeriesTable","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"We can later retrieve the series for the element in the collection with PSRClassesInterface.get_series, which will return a SeriesTable object. It can be later displayed as a table in your terminal.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"When using this function, we need the collection, the element index and the attribute that indexes the elements.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"using DataFrames\nseries_table = PSRI.get_series(\n data, \n \"PSRGasEmission\", \n \"DateEmissionCost\", \n 1 # element index in collection\n )\n\nDataFrame(series_table)","category":"page"},{"location":"examples/graf_files/#Graf-files","page":"Graf Files and Time Series","title":"Graf files","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"The data relative to a Study is usually stored in a JSON file, where an attribute can have its data indexed by time intervals, as presented earlier.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"However, when a time series attribute is multidimensional, it can be too large to be stored in a JSON. For these cases, we save the data in a separate file. We will refer to such file as Graf file. When an attribute has its information in a Graf file, there's an entry in the regular JSON file specifying it. ","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"In the following example, each PSRDemand object will have its attribute Duracao data associated with a time series, saved in the files duracao.hdr and duracao.bin. Objects are distinguished by the parmid attribute, which in this case has the AVId value of each PSRDemand element. ","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"A Graf file stores the values of an attribute for every element in a collection. So for this example, all values for the attribute Duracao will be store in the Graf file.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"\"PSRGasEmission\": [\n {\n \"AVId\": \"Agent 1\"\n \"name\": \"psr_name\"\n },\n {\n \"AVId\": \"Agent 2\"\n \"name\": \"psr_name2\"\n },\n {\n \"AVId\": \"Agent 3\"\n \"name\": \"psr_name3\"\n }\n],\n\"GrafScenarios\": [\n {\n \"classname\": \"PSRDemand\",\n \"parmid\": \"AVId\",\n \"vector\": \"Duracao\",\n \"binary\": [ \"duracao.hdr\", \"duracao.bin\" ]\n }\n]","category":"page"},{"location":"examples/graf_files/#Graf-file-format","page":"Graf Files and Time Series","title":"Graf file format","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"A Graf file composed of a header and a table with the following elements:","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"Stage \nScenario \nBlock\nAgents (one entry for each agent)","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"Each agent represents an element from the collection the graf file is linked to.","category":"page"},{"location":"examples/graf_files/#Visual-example-of-a-graf-file","page":"Graf Files and Time Series","title":"Visual example of a graf file","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"Using the previous example with PSRDemand objects, the Duracao for each object will be displayed in the Agents columns, that will take the name of the AVId attribute, resulting on the following:","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"Stg Sce Block Agent 1 Agent 2 Agent 3\n1 1 1 1.0 5.0 10.0\n1 1 2 1.5 6.5 11.5\n1 1 3 2.0 7.0 12.0\n... ... ... ... ... ...","category":"page"},{"location":"examples/graf_files/#Graf-Header","page":"Graf Files and Time Series","title":"Graf Header","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"A Graf file header contains data about the time series contents. Some important information are whether the time series varies per block and/or per Scenario, the number of agents, the unit of measurement and on which stage it should start. ","category":"page"},{"location":"examples/graf_files/#Writing-a-time-series-into-a-Graf-file","page":"Graf Files and Time Series","title":"Writing a time series into a Graf file","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"In this example we will demonstrate how to save a time series into a csv or binary file. First, we create a random array which has the data for a time series:","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"import PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\n#Creates dummy data\nn_blocks = 3\nn_scenarios = 1\nn_stages = 1\nn_agents = 1\n\ntime_series_data = rand(Float64, n_agents, n_blocks, n_scenarios, n_stages)\n\nnothing #hide","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"There are two ways of saving the data to a file, save the data in the file directly or iteratively. To save the data directly use the function PSRClassesInterface.array_to_file by calling:","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"FILE_PATH = joinpath(tempdir(), \"example\")\n\nPSRI.array_to_file(\n PSRI.OpenBinary.Writer,\n FILE_PATH,\n time_series_data,\n agents = [\"Agent 1\", \"Agent 2\", \"Agent 3\", \"Agent 4\", \"Agent 5\"],\n unit = \"H\";\n initial_stage = 3,\n initial_year = 2006,\n)","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"To save the data iteractively use the function PSRClassesInterface.open to create an PSRClassesInterface.AbstractWriter. Save the data of each registry to the file using the function PSRClassesInterface.write_registry and then close the data stream calling the function PSRClassesInterface.close.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"iow = PSRI.open(\n PSRI.OpenBinary.Writer,\n FILE_PATH,\n blocks = n_blocks,\n scenarios = n_scenarios,\n stages = n_stages,\n agents = [\"Agent 1\", \"Agent 2\", \"Agent 3\", \"Agent 4\", \"Agent 5\"],\n unit = \"H\",\n initial_stage = 1,\n initial_year = 2006,\n)\n\nfor stage = 1:n_stages, scenario = 1:n_scenarios, block = 1:n_blocks\n PSRI.write_registry(\n iow,\n time_series_data[:, block, scenario, stage],\n stage,\n scenario,\n block\n )\nend\n\nPSRI.close(iow)","category":"page"},{"location":"examples/graf_files/#Reading-a-time-series-from-a-graf-file","page":"Graf Files and Time Series","title":"Reading a time series from a graf file","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"A similar logic can be used to read the data from a file. You can read it directly or iteratively. To read the data directly use the function PSRClassesInterface.file_to_array or PSRClassesInterface.file_to_array_and_header","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"data_from_file = PSRI.file_to_array(\n PSRI.OpenBinary.Reader, \n FILE_PATH;\n use_header=false\n )\n\n@assert all(isapprox.(data_from_file, time_series_data, atol=1E-7))\n\ndata_from_file_and_header, header = PSRI.file_to_array_and_header(\n PSRI.OpenBinary.Reader, \n FILE_PATH;\n use_header=false\n )\n@assert all(isapprox.(data_from_file_and_header, time_series_data, atol=1E-7))","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"To choose the agents order set use_header to true and label the agents in header.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"data_from_file = PSRI.file_to_array(\n PSRI.OpenBinary.Reader, \n FILE_PATH;\n use_header=true,\n header=[\"Agent 5\", \"Agent 2\", \"Agent 3\", \"Agent 4\", \"Agent 1\"]\n )\n@assert all(isapprox.(data_from_file[1, :, :, :], time_series_data[end, :, :, :], atol=1E-7))\n@assert all(isapprox.(data_from_file[end, :, :, :], time_series_data[1, :, :, :], atol=1E-7))","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"To read the data iteractively use the function PSRClassesInterface.open to create an PSRClassesInterface.AbstractReader and read each registry iteratively. At the end you should close the PSRClassesInterface.AbstractReader by calling PSRClassesInterface.close","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"ior = PSRI.open(\n PSRI.OpenBinary.Reader, \n FILE_PATH;\n use_header = false\n)\n\ndata_from_file = zeros(n_agents, n_blocks, n_scenarios, n_stages)\n\nfor stage = 1:n_stages, scenario = 1:n_scenarios, block = 1:n_blocks\n data_from_file[:, block, scenario, stage] = ior.data\n PSRI.next_registry(ior)\nend\n\nPSRI.close(ior)\n","category":"page"},{"location":"examples/graf_files/#Using-Graf-files-in-a-study","page":"Graf Files and Time Series","title":"Using Graf files in a study","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"As presented earlier, an attribute for a collection can have its data stored in a Graf file, all that being specified in the GrafScenarios entry of the study JSON. ","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"If you have a Graf file that should be linked to a study, you can use the function PSRClassesInterface.link_series_to_file to do so.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"PSRI.create_element!(data, \"PSRDemand\", \"AVId\" => \"Agent 1\")\nPSRI.create_element!(data, \"PSRDemand\", \"AVId\" => \"Agent 2\")\nPSRI.create_element!(data, \"PSRDemand\", \"AVId\" => \"Agent 3\")\nPSRI.create_element!(data, \"PSRDemand\", \"AVId\" => \"Agent 4\")\nPSRI.create_element!(data, \"PSRDemand\", \"AVId\" => \"Agent 5\")\n\nPSRI.link_series_to_file(\n data, \n \"PSRDemand\", \n \"Duracao\", \n \"AVId\",\n FILE_PATH\n )","category":"page"},{"location":"examples/graf_files/#Using-a-GrafTable","page":"Graf Files and Time Series","title":"Using a GrafTable","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"We can retrieve the data stored in a Graf file using the PSRClassesInterface.get_graf_series function. This function returns a GrafTable object. ","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"When using this function, we need the collection and its attribute that is linked to a Graf file.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"graf_table = PSRI.get_graf_series(\n data,\n \"PSRDemand\",\n \"Duracao\";\n use_header = false\n )","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"Once you have a GrafTable object, you can display it as a table in your terminal","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"using DataFrames\n\nDataFrame(graf_table)","category":"page"},{"location":"examples/graf_files/#Vector-from-graf-file","page":"Graf Files and Time Series","title":"Vector from graf file","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"You can get a vector that corresponds to a row in a Graf file with the values for the agents correspoding to the current stage, scenario and block.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"For that, we will have to use the function PSRClassesInterface.mapped_vector. ","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"vec = PSRI.mapped_vector(\n data, \n \"PSRDemand\", \n \"Duracao\",\n Float64\n )","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"The parameters that were used to retrieve the row value in the Graf table can be changed with the following functions:","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"PSRClassesInterface.go_to_stage\nPSRClassesInterface.go_to_scenario\nPSRClassesInterface.go_to_block","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"These methods don't automatically update the vector. For that, we use the function PSRClassesInterface.update_vectors!, which update all vectors from our Study.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"PSRI.update_vectors!(data)","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"However, it might be interesting to update only one or a group of vectors. To be able to do that, we will have to set a filter tag when we create them.","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"vec2 = PSRI.mapped_vector(\n data, \n \"PSRDemand\", \n \"Duracao\",\n Float64,\n filters = [\"test_filter\"]\n )","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"Then, when we run:","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"PSRI.update_vectors!(data, \"test_filter\")","category":"page"},{"location":"examples/graf_files/#Comparison-between-a-GrafTable-and-a-SeriesTable","page":"Graf Files and Time Series","title":"Comparison between a GrafTable and a SeriesTable","text":"","category":"section"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"In this section we have introduced some new concepts about table-like types. That being said, let's review the main differences between GrafTables and SeriesTables:","category":"page"},{"location":"examples/graf_files/","page":"Graf Files and Time Series","title":"Graf Files and Time Series","text":"SeriesTable\nIs linked to a single element from a collection\nIt can have time series of different attributes that are indexed to a single attribute (all belonging to the same element)\nGrafTable\nIs linked to the whole collection. So for an attribute, every element in the collection will have an entry in the graf file\nIt has the time series for only one attribute","category":"page"},{"location":"examples/custom_study/#Customizing-a-Study","page":"Customizing a Study","title":"Customizing a Study","text":"","category":"section"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"In this tutorial you will learn how to customize several items of your study.","category":"page"},{"location":"examples/custom_study/#How-we-define-the-template-for-our-studies","page":"Customizing a Study","title":"How we define the template for our studies","text":"","category":"section"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"First of all, it's important to understand how we define the default rules for each collection in our study.","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"Let's take a look at the function PSRClassesInterface.create_study for the OpenStudy interface. It has the following signature:","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"function create_study(\n ::OpenInterface;\n data_path::AbstractString = pwd(),\n pmd_files::Vector{String} = String[],\n pmds_path::AbstractString = PMD._PMDS_BASE_PATH,\n defaults_path::Union{AbstractString,Nothing} = PSRCLASSES_DEFAULTS_PATH,\n defaults::Union{Dict{String,Any},Nothing} = _load_defaults!(),\n netplan::Bool = false,\n model_template_path::Union{String,Nothing} = nothing,\n study_collection::String = \"PSRStudy\",\n)","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"From our other examples, you will notice that we have never filled most of these parameters, leaving them with their default values. However, the following are important for working with custom Studies:","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"pmd_files or pmds_path\nmodel_template_path\ndefaults_path","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"A PMD is a .pmd file where we define collections and the metadata for each of their attributes. A Model Template is a JSON file where we map the name of collections in the PMD to their names in our Study. Finally, Defaults is also a JSON file where we set the default values for some - or all - attributes in collections.","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"When we create a study, we parse the PMD file(s) and the Model Template, creating the data.data_struct, a Dict that contains the metadata for attributes and their names. ","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"When we create an element, PSRI uses data.data_struct to check if the values for the attributes that we have filled are in agreement with their definition(if they should be Vectors, Floats, ...) and if any attribute is missing. ","category":"page"},{"location":"examples/custom_study/#Defining-custom-structures-with-new-PMD-file","page":"Customizing a Study","title":"Defining custom structures with new PMD file","text":"","category":"section"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"When you already have your structures defined in a PMD file, you don't need to create them in runtime. First, save this code as a .pmd file, where we define a Study collection, different from PSRStudy and a PSRExtra collection. ","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"DEFINE_MODEL MODL:Custom_Study_Config\n\tPARM REAL \t\tValue1\n\tPARM REAL \t\tValue3\n\tPARM STRING Text\nEND_MODEL\n\nDEFINE_MODEL MODL:Extra_Collection\n\tPARM REAL \t\tExtraValue\n\tPARM STRING Text\nEND_MODEL","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"Now we need a Model Template file, to map our PMD Model to collections. Just as we did before, copy the following code into a file, but save it as a .json this time.","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"[\n {\n \"classname\": \"CustomStudy\",\n \"models\": [\"Custom_Study_Config\"]\n },\n {\n \"classname\": \"PSRExtra\",\n \"models\": [\"Extra_Collection\"]\n }\n]","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"After that, we can create a Study with PSRClassesInterface.create_study using a few extra mandatory parameters.","category":"page"},{"location":"examples/custom_study/","page":"Customizing a Study","title":"Customizing a Study","text":"import PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\n\ntemp_path = joinpath(tempdir(), \"PSRI\")\njson_path = joinpath(path_to_directory, \"custom_json.json\")\n\ndata = PSRI.create_study(PSRI.OpenInterface(), \n data_path = temp_path, \n pmds_path = path_to_directory, \n model_template_path = json_path, \n study_collection = \"CustomStudy\", \n defaults = Dict{String,Any}(\n \"CustomStudy\" => Dict{String,Any}(\n \"AVId\" => \"avid\", \n \"Text\" => \"custom\", \n \"Value1\" => 1.0, \n \"Value3\" => 2.0, \n \"code\" => Int32(10), \n \"name\" => \"name\"\n )\n )\n)\n","category":"page"},{"location":"examples/reading_demands/#Reading-Demands","page":"Reading Demands","title":"Reading Demands","text":"","category":"section"},{"location":"examples/reading_demands/#Determining-elasticity-and-value-of-demands","page":"Reading Demands","title":"Determining elasticity and value of demands","text":"","category":"section"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"In this example we will read demand segments, obtain the value of demands, discover wheter each demand is elastic or inelastic, and then obtain the sums of demands by elasticity. The first step is to read the study data:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"using PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\nPATH_CASE_EXAMPLE_DEM = joinpath(pathof(PSRI) |> dirname |> dirname, \"test\", \"data\", \"case1\")\n\ndata = PSRI.load_study(\n PSRI.OpenInterface(),\n data_path = PATH_CASE_EXAMPLE_DEM\n)\n; nothing # hide","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"Whereas the demand varies according to the stage, we must specify the stage by calling go_to_stage:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"target_stage = 1\nPSRI.go_to_stage(data,target_stage)","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"Now, we can read the demand segments and the map between demands and demand segments, and then obtain the value of each demand:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"dem_seg = PSRI.mapped_vector(data, \"PSRDemandSegment\", \"Demanda\", Float64, \"block\")\n\nseg2dem = PSRI.get_map(data, \"PSRDemandSegment\", \"PSRDemand\", relation_type = PSRI.PMD.RELATION_1_TO_1)\n\ndem_size = PSRI.max_elements(data, \"PSRDemand\")\n\ndemand_values = zeros(dem_size)\n\nfor demand = 1:dem_size\n demand_values[demand] = sum(dem_seg[i] for i = 1:length(dem_seg) if seg2dem[i] == demand)\nend\n\ndemand_values","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"We can discover the elasticity of each demand by calling get_parms with the parameter Elastico:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"demands_elasticity = PSRI.get_parms(data, \"PSRDemand\", \"Elastico\", Int32)\n; nothing # hide","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"If demands_elasticity[i] == 0 it means that the demand at index i is inelastic, and elastic if demands_elasticity[i] == 1. We can now obtain the total demands of each elasticity:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"total_elastic_demand = 0.0\ntotal_inelastic_demand = 0.0\n\nfor i = 1:dem_size\n if demands_elasticity[i] == 0\n total_inelastic_demand += demand_values[i]\n else\n total_elastic_demand += demand_values[i]\n end\nend","category":"page"},{"location":"examples/reading_demands/#Determining-demands-values-of-each-bus","page":"Reading Demands","title":"Determining demands values of each bus","text":"","category":"section"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"Now we have the values of the demands, we can obtain the values of demand for each bus. Each demand has a set of loads, which define how much of this demand corresponds to each bus. We can begin by reading the loads and its relations with demands and buses:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"loads = PSRI.mapped_vector(data, \"PSRLoad\", \"P\", Float64, \"block\")\nlod2dem = PSRI.get_map(data, \"PSRLoad\", \"PSRDemand\", relation_type = PSRI.PMD.RELATION_1_TO_1)\nlod2bus = PSRI.get_map(data, \"PSRLoad\", \"PSRBus\", relation_type = PSRI.PMD.RELATION_1_TO_1)\n; nothing # hide","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"The values of the loads are weights in a kind of a weighted arithmetic mean of the buses for each demand. But the loads of each demand don't add up to 1, so they need to be normalized to represent fractions of the total:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"total_lod_bydem = zeros(dem_size)\nlod_size = PSRI.max_elements(data, \"PSRLoad\")\n\nfor i in 1:lod_size\n total_lod_bydem[lod2dem[i]] += loads[i]\nend\n\nfor i in 1:lod_size\n if total_lod_bydem[lod2dem[i]] > 0.0\n loads[i] = loads[i]/total_lod_bydem[lod2dem[i]]\n else\n loads[i] = 0.0\n end\nend\n\nloads","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"Now we know the fraction of each demand that corresponds to each bus, and can easily define the total demand by bus:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"bus_size = PSRI.max_elements(data, \"PSRBus\")\n\ndem_bybus = zeros(bus_size)\n\nfor lod = 1:lod_size\n fraction = loads[lod]\n dem = lod2dem[lod]\n bus = lod2bus[lod] \n dem_bybus[bus] += demand_values[dem]*fraction\nend\n\ndem_bybus","category":"page"},{"location":"examples/reading_demands/#Calculating-the-energy-prices-of-each-thermal-plant","page":"Reading Demands","title":"Calculating the energy prices of each thermal plant","text":"","category":"section"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"The energy prices in a thermal plant deppends on the the price of the fuel used, the specific consumption of this fuel and Operation and Maintenance cost. Again, we begin by reading the data:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"import PSRClassesInterface\nconst PSRI = PSRClassesInterface\n\nPATH_CASE_EXAMPLE_THER_PRICES = joinpath(pathof(PSRI) |> dirname |> dirname, \"test\", \"data\", \"case1\")\n\ndata = PSRI.load_study(\n PSRI.OpenInterface(),\n data_path = PATH_CASE_EXAMPLE_THER_PRICES\n)\n; nothing # hide","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"We discover the necessary infos of the thermal plants indirectly through PSRFuelConsumption:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"fuelcons2ther = PSRI.get_map(data,\"PSRFuelConsumption\", \"PSRThermalPlant\"; relation_type = PSRI.PMD.RELATION_1_TO_1)\n\nther_size = PSRI.max_elements(data, \"PSRThermalPlant\")\nfuelcons_size = PSRI.max_elements(data, \"PSRFuelConsumption\")\nther2fuelcons = [[fc for fc = 1:fuelcons_size if fuelcons2ther[fc] == t] for t = 1:ther_size]\n; nothing # hide","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"Next, we get the O&M cost, the specific consumption and the relation with fuels of our fuels consumptions. Then we get the cost of each fuel. After calling mapped_vector we must call update_vectors!.","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"om_cost = PSRI.mapped_vector(data, \"PSRFuelConsumption\", \"O&MCost\", Float64)\nspec_consum = PSRI.mapped_vector(data, \"PSRFuelConsumption\", \"CEsp\", Float64, \"segment\", \"block\")\nfuelcons2fuel = PSRI.get_map(data, \"PSRFuelConsumption\", \"PSRFuel\"; relation_type = PSRI.PMD.RELATION_1_TO_1)\nfuel_cost = PSRI.mapped_vector(data, \"PSRFuel\", \"Custo\", Float64)\n\nPSRI.update_vectors!(data)","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"Now we can calculate the price of the energy unity of each fuel consumption for each thermal plant:","category":"page"},{"location":"examples/reading_demands/","page":"Reading Demands","title":"Reading Demands","text":"ther_prices = [zeros(0) for _ = 1:ther_size]\nfor ther = 1:ther_size\n n_fuelcons = length(ther2fuelcons[ther])\n prices = zeros(n_fuelcons)\n for i = 1:n_fuelcons\n fuelcons = ther2fuelcons[ther][i]\n fuel = fuelcons2fuel[fuelcons]\n prices[i] = om_cost[fuelcons] + spec_consum[fuelcons]*fuel_cost[fuel]\n end\n ther_prices[ther] = prices\nend\nther_prices","category":"page"},{"location":"openstudy_files/pmd/#PMD","page":"PMD","title":"PMD","text":"","category":"section"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"tip: Tip\nWe have a syntax highlighter for .pmd files available on Visual Studio's Marktetplace","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"warning: Warning\nThe syntax for PMD files is case-sensitive ","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"PMD files are used to define models accross multiple PSR software. It stores metadata about every attribute and relation.","category":"page"},{"location":"openstudy_files/pmd/#Good-practices","page":"PMD","title":"Good practices","text":"","category":"section"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"In order to make the PMD file more readable and easier to maintain, we recommend the following good practices:","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"Decide whether you want to use PascalCase, snake_case or camelCase and stick to it.\nAlways write the name for the Attributes and Collections in English.\nDo not use special characters other than \"_\" (underscore) in the names.\nDefine understandable names for the Attributes and Collections, as other users may use your model in the future.","category":"page"},{"location":"openstudy_files/pmd/#Defining-a-model","page":"PMD","title":"Defining a model","text":"","category":"section"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"To define a model Custom_Model_v1, you need to use the following structure:","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"DEFINE_MODEL MODL:Custom_Model_v1\n\n\t...\n\nEND_MODEL","category":"page"},{"location":"openstudy_files/pmd/#Defining-a-parameter","page":"PMD","title":"Defining a parameter","text":"","category":"section"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"A parameter can be either a VECTOR or a PARM.","category":"page"},{"location":"openstudy_files/pmd/#PARM","page":"PMD","title":"PARM","text":"","category":"section"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"DEFINE_MODEL MODL:Custom_Model_v1\n\n\t...\n\n\tPARM INTEGER Iterations\n\tPARM REAL Price\n\tPARM STRING Name\n\tPARM DATE DateOfEvent\n\n\t...\n\nEND_MODEL","category":"page"},{"location":"openstudy_files/pmd/#VECTOR","page":"PMD","title":"VECTOR","text":"","category":"section"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"A VECTOR parameter can store the same types as a PARM. Additionally can have an indexing parameter attribute.","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"Let's say that you have a vector Cost where each index corresponds to a cost in a specific date. We can use an auxiliary indexing vector CostDates to access the cost value correspondent to a given date (see the Graf Files and Time Series example).","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"DEFINE_MODEL MODL:Custom_Model_v1\n\n\t...\n\n\tVECTOR DATE CostDates\n\tVECTOR REAL Cost INDEX CostDates\n\n\t...\n\nEND_MODEL","category":"page"},{"location":"openstudy_files/pmd/#Parameters-with-dimension","page":"PMD","title":"Parameters with dimension","text":"","category":"section"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"A VECTOR or PARM parameter can change according to a given Stage, Scenario and/or Block dimension (see the Graf Files and Time Series example). We can specify whether a parameter is dimensioned using the following syntax:","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"DEFINE_MODEL MODL:Custom_Model_v1\n\n\t...\n\n\tPARM INTEGER Iterations DIM(block)\n\n\tVECTOR REAL Duration DIM(block) \n\n\tVECTOR DATE CostDates\n\tVECTOR REAL Cost DIM(block,segment) INDEX CostDates \n\n\t...\n\nEND_MODEL","category":"page"},{"location":"openstudy_files/pmd/#REFERENCE","page":"PMD","title":"REFERENCE","text":"","category":"section"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"Besides REAL, INTEGER, STRING and DATE, there is a fith attribute type labeled REFERENCE. It can be stored either in a VECTOR or a PARM.","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"A REFERENCE represents a relation between two models(or collections, when considering a PSRI study).","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"It has the following structure:","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"DEFINE_MODEL MODL:Custom_Model_v1\n\n\t...\n\n\tPARM REFERENCE Plant TargetCollection \n\n\tVECTOR REFERENCE Items SecondTargetCollection\n\n\t...\n\nEND_MODEL","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"In this example, our CustomModelv1 model has two relations:","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"a relation of 1 to 1 (for being a PARM parameter) with elements of collection TargetCollection\na relation of 1 to N (for being a VECTOR parameter) with elements of collection SecondTargetCollection","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"The Plant and Items parameters store the reference_id of the corresponding elements from collections TargetCollection and SecondTargetCollection, respectively.","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"Note that the names TargetCollection and SecondTargetCollection are the name of the collections inside the study, not their name in the PMD file. This difference between names is explained in the Model Template manual.","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"Also, we define a REFERENCE only in the models which play the role of source. ","category":"page"},{"location":"openstudy_files/pmd/","page":"PMD","title":"PMD","text":"There is another way to define relations in a study. For that, see the Relation Mapper manual.","category":"page"},{"location":"sqlite_examples/migrations/#Migration-Examples","page":"Migration Examples","title":"Migration Examples","text":"","category":"section"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"Migrations are a way to manage the evolution of the database schema over time. As mentioned in the documentation for PSRDatabaseSQLite, migrations are defined by two separate .sql files that are stored in the migrations directory of the model. The first file is the up migration and it is used to update the database schema to a new version. The second file is the down migration and it is used to revert the changes made by the up migration. Migrations are stored in directories in the model and they have a specific naming convention. The name of the migration folder should be the number of the version (e.g. /migrations/1/).","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"In this section, we will provide some examples of migrations. First, let us start with the first migration, the one that creates the initial database schema.","category":"page"},{"location":"sqlite_examples/migrations/#Adding-two-tables-to-the-database","page":"Migration Examples","title":"Adding two tables to the database","text":"","category":"section"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 1; -- Set the database version to 1\nPRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity\n\n-- Create the Configuration table\nCREATE TABLE Configuration (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n value TEXT NOT NULL\n) ;\n\n-- Create Plant table\nCREATE TABLE Plant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n bus_name TEXT NOT NULL\n) ;","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"This schema is the up.sql migration for version 1. It creates two tables, Configuration and Plant. Now we have to create the down.sql migration for version 1. This migration should drop the tables created in the up.sql migration.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 0; -- Set the database version to 0\n-- Drop the Configuration table\nDROP TABLE Configuration;\n-- Drop the Plant table\nDROP TABLE Plant;","category":"page"},{"location":"sqlite_examples/migrations/#Adding-a-new-column","page":"Migration Examples","title":"Adding a new column","text":"","category":"section"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"Now let us create a migration that adds a new column to the Configuration and Plant tables.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 2; -- Set the database version to 2\nPRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity\n\n-- Add the description column to the Configuration table\nALTER TABLE Configuration ADD COLUMN description TEXT;\n\n-- Add the type column to the Plant table\nALTER TABLE Plant ADD COLUMN type INTEGER NOT NULL DEFAULT 0;","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"This is the up.sql migration for version 2. The down.sql migration should remove the column added in the up.sql migration.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 1; -- Set the database version to 1\n\n-- Remove the description column from the Configuration table\nALTER TABLE Configuration DROP COLUMN description;\n\n-- Remove the type column from the Plant table\nALTER TABLE Plant DROP COLUMN type;","category":"page"},{"location":"sqlite_examples/migrations/#Renaming-a-table","page":"Migration Examples","title":"Renaming a table","text":"","category":"section"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"Let us create a migration that renames the Plant table to PowerPlant.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 3; -- Set the database version to 3\nPRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity\n\n-- Rename the Plant table to PowerPlant\nALTER TABLE Plant RENAME TO PowerPlant;","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"This is the up.sql migration for version 3. The down.sql migration should rename the PowerPlant table back to Plant.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 2; -- Set the database version to 2\n\n-- Rename the PowerPlant table to Plant\nALTER TABLE PowerPlant RENAME TO Plant;","category":"page"},{"location":"sqlite_examples/migrations/#Adding-a-foreign-key-constraint","page":"Migration Examples","title":"Adding a foreign key constraint","text":"","category":"section"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"Let us create a migration that adds a foreign key constraint to the PowerPlant table. First, we need to create a new table, Resource, that will be referenced by the PowerPlant table.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"Adding a foreign key constraint, however, is not as trivial as adding a column or renaming a table. We need to follow these steps:","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"Disable foreign key constraints\nStart a transaction\nCreate an auxiliary new_PowerPlant table with the new column and the foreign key constraint\nCopy the data from the PowerPlant table to the new_PowerPlant table\nDrop the PowerPlant table\nRename the new_PowerPlant table to PowerPlant\nCheck if any foreign key constraints were violatet with PRAGMA foreign_key_check\nCommit the transaction\nEnable foreign key constraints ","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 4; -- Set the database version to 4\nPRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity\n\n-- Create the Resource table\nCREATE TABLE Resource (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL\n) ;\n\n-- Disable foreign key constraints\nPRAGMA foreign_keys = OFF;\n\n-- Start a transaction\nBEGIN TRANSACTION;\n\n-- Create the new PowerPlant table\nCREATE TABLE new_PowerPlant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n bus_name TEXT NOT NULL,\n type INTEGER NOT NULL DEFAULT 0,\n resource_id INTEGER,\n FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE\n) ;\n\n-- Copy the data from the PowerPlant table to the new PowerPlant table\nINSERT INTO new_PowerPlant (id, label, capacity, bus_name, type)\nSELECT id, label, capacity, bus_name, type FROM PowerPlant;\n\n-- Drop the PowerPlant table\nDROP TABLE PowerPlant;\n\n-- Rename the new PowerPlant table to PowerPlant\nALTER TABLE new_PowerPlant RENAME TO PowerPlant;\n\n-- Check if any foreign key constraints were violated\nPRAGMA foreign_key_check;\n\n-- Commit the transaction\nCOMMIT;\n\n-- Enable foreign key constraints\nPRAGMA foreign_keys = ON;","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"Now, the down.sql migration should revert the changes made by the up.sql migration.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 3; -- Set the database version to 3\n\n-- Disable foreign key constraints\nPRAGMA foreign_keys = OFF;\n\n-- Start a transaction\nBEGIN TRANSACTION;\n\n-- Create the new PowerPlant table\nCREATE TABLE new_PowerPlant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n bus_name TEXT NOT NULL,\n type INTEGER NOT NULL DEFAULT 0\n) ;\n\n-- Copy the data from the PowerPlant table to the new PowerPlant table\nINSERT INTO new_PowerPlant (id, label, capacity, bus_name, type)\nSELECT id, label, capacity, bus_name, type FROM PowerPlant;\n\n-- Drop the PowerPlant table\nDROP TABLE PowerPlant;\n\n-- Rename the new PowerPlant table to PowerPlant\nALTER TABLE new_PowerPlant RENAME TO PowerPlant;\n\n-- Check if any foreign key constraints were violated\nPRAGMA foreign_key_check;\n\n-- Commit the transaction\nCOMMIT;\n\n-- Enable foreign key constraints\nPRAGMA foreign_keys = ON;\n\n-- Drop the Resource table\nDROP TABLE Resource;","category":"page"},{"location":"sqlite_examples/migrations/#Dividing-a-table-into-two-tables","page":"Migration Examples","title":"Dividing a table into two tables","text":"","category":"section"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"Let us create a migration that divides the PowerPlant table into two tables, HydroPlant and ThermalPlant. HydroPlant corresponds to the rows with type = 0 and ThermalPlant corresponds to the rows with type = 1.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 5; -- Set the database version to 5\n\n\n\nPRAGMA foreign_keys = OFF;\nBEGIN TRANSACTION;\n\n-- Create the HydroPlant table\nCREATE TABLE HydroPlant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n bus_name TEXT NOT NULL,\n resource_id INTEGER,\n FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE\n) ;\n\n-- Create the ThermalPlant table\nCREATE TABLE ThermalPlant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n bus_name TEXT NOT NULL,\n resource_id INTEGER,\n FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE\n) ;\n\n-- Fill the HydroPlant table\nINSERT INTO HydroPlant (id, label, capacity, bus_name, resource_id)\nSELECT id, label, capacity, bus_name, resource_id FROM PowerPlant WHERE type = 0;\n\n-- Fill the ThermalPlant table\nINSERT INTO ThermalPlant (id, label, capacity, bus_name, resource_id)\nSELECT id, label, capacity, bus_name, resource_id FROM PowerPlant WHERE type = 1;\n\n-- Drop the PowerPlant table\nDROP TABLE PowerPlant;\n\nPRAGMA foreign_key_check;\nCOMMIT;\nPRAGMA foreign_keys = ON;\n","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"This is the up.sql migration for version 5. The down.sql migration should revert the changes made by the up.sql migration.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 4; -- Set the database version to 4\nPRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity\n\n-- Create the PowerPlant table\nCREATE TABLE PowerPlant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n type INTEGER NOT NULL DEFAULT 0,\n bus_name TEXT NOT NULL,\n resource_id INTEGER,\n FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE\n) ;\n\n-- Fill the PowerPlant table\nINSERT INTO PowerPlant (id, label, capacity, bus_name, type, resource_id)\nSELECT id, label, capacity, bus_name, 0, resource_id FROM HydroPlant;\n\nINSERT INTO PowerPlant (id, label, capacity, bus_name, type, resource_id)\nSELECT id, label, capacity, bus_name, 1, resource_id FROM ThermalPlant;\n\n-- Drop the HydroPlant table\nDROP TABLE HydroPlant;\n\n-- Drop the ThermalPlant table\nDROP TABLE ThermalPlant;","category":"page"},{"location":"sqlite_examples/migrations/#Create-a-table-with-data-from-another-table","page":"Migration Examples","title":"Create a table with data from another table","text":"","category":"section"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"Let us create a migration that adds a new Table Bus with data from the HydroPlant and ThermalPlant tables. These tables already have a column bus_name that will be used to fill the Bus table. After creating the Bus table, we will remove the bus_name column from the HydroPlant and ThermalPlant tables. Moreover, the bus_name column in the PowerPlant table will be replaced by a bus_id column that references the Bus table.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 6; -- Set the database version to 6\nPRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity\n\n-- Create the Bus table\nCREATE TABLE Bus (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL\n) ;\n\n-- Fill the Bus table\nINSERT INTO Bus (label)\nSELECT DISTINCT bus_name FROM HydroPlant;\n\nINSERT INTO Bus (label)\nSELECT DISTINCT bus_name FROM ThermalPlant;\n\nPRAGMA foreign_keys = OFF;\nBEGIN TRANSACTION;\n\n-- Add foreign key \nCREATE TABLE new_HydroPlant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n resource_id INTEGER,\n bus_id INTEGER,\n FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE,\n FOREIGN KEY (bus_id) REFERENCES Bus(id) ON UPDATE CASCADE ON DELETE CASCADE\n) ;\n\nCREATE TABLE new_ThermalPlant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n resource_id INTEGER,\n bus_id INTEGER,\n FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE,\n FOREIGN KEY (bus_id) REFERENCES Bus(id) ON UPDATE CASCADE ON DELETE CASCADE\n) ;\n\n-- Copy the data from the HydroPlant table to the new HydroPlant table\nINSERT INTO new_HydroPlant (id, label, capacity, resource_id)\nSELECT id, label, capacity, resource_id FROM HydroPlant;\n\n-- Copy the data from the ThermalPlant table to the new ThermalPlant table\nINSERT INTO new_ThermalPlant (id, label, capacity, resource_id)\nSELECT id, label, capacity, resource_id FROM ThermalPlant;\n\n-- Add data for the bus_id column\nUPDATE new_HydroPlant SET bus_id = (SELECT Bus.id FROM Bus\nINNER JOIN HydroPlant ON Bus.label = HydroPlant.bus_name AND \nHydroPlant.id = new_HydroPlant.id\n);\nUPDATE new_ThermalPlant SET bus_id = (SELECT Bus.id FROM Bus\nINNER JOIN ThermalPlant ON Bus.label = ThermalPlant.bus_name AND\nThermalPlant.id = new_ThermalPlant.id\n);\n\n-- Drop tables\nDROP TABLE HydroPlant;\nDROP TABLE ThermalPlant;\n\n-- Rename tables\nALTER TABLE new_HydroPlant RENAME TO HydroPlant;\nALTER TABLE new_ThermalPlant RENAME TO ThermalPlant;\n\nPRAGMA foreign_key_check;\nCOMMIT;\nPRAGMA foreign_keys = ON;","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"This is the up.sql migration for version 6. The down.sql migration should revert the changes made by the up.sql migration.","category":"page"},{"location":"sqlite_examples/migrations/","page":"Migration Examples","title":"Migration Examples","text":"PRAGMA user_version = 5; -- Set the database version to 5\n\n\nPRAGMA foreign_keys = OFF;\nBEGIN TRANSACTION;\n\n-- Create auxiliary tables\nCREATE TABLE new_HydroPlant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n resource_id INTEGER,\n bus_name TEXT,\n FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE\n) ;\n\nCREATE TABLE new_ThermalPlant (\n id INTEGER PRIMARY KEY,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n resource_id INTEGER,\n bus_name TEXT,\n FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE\n) ;\n\n-- Copy the data from the HydroPlant table to the new HydroPlant table\nINSERT INTO new_HydroPlant (id, label, capacity, resource_id)\nSELECT id, label, capacity, resource_id FROM HydroPlant;\n\n-- Copy the data from the ThermalPlant table to the new ThermalPlant table\nINSERT INTO new_ThermalPlant (id, label, capacity, resource_id)\nSELECT id, label, capacity, resource_id FROM ThermalPlant;\n\n-- Add data for the bus_name column\nUPDATE new_HydroPlant SET bus_name = (SELECT Bus.label FROM Bus\nINNER JOIN HydroPlant ON Bus.id = HydroPlant.bus_id AND \nHydroPlant.id = new_HydroPlant.id\n);\n\nUPDATE new_ThermalPlant SET bus_name = (SELECT Bus.label FROM Bus\nINNER JOIN ThermalPlant ON Bus.id = ThermalPlant.bus_id AND\nThermalPlant.id = new_ThermalPlant.id\n);\n\n-- Drop tables\nDROP TABLE HydroPlant;\nDROP TABLE ThermalPlant;\n\n-- Rename tables\nALTER TABLE new_HydroPlant RENAME TO HydroPlant;\nALTER TABLE new_ThermalPlant RENAME TO ThermalPlant;\n\n-- Drop the Bus table\nDROP TABLE Bus;\n\nPRAGMA foreign_key_check;\nCOMMIT;\nPRAGMA foreign_keys = ON;","category":"page"},{"location":"psrdatabasesqlite/rules/#PSRDatabaseSQLite","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Following PSRI's OpenStudy standards, SQL schemas for the PSRDatabaseSQLite framework should follow the conventions described in this document. Note that this is a tool for creating and developing some kinds of applications. Not all tools will need to use this framework.","category":"page"},{"location":"psrdatabasesqlite/rules/#SQL-Schema-Conventions","page":"PSRDatabaseSQLite","title":"SQL Schema Conventions","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/#Collections","page":"PSRDatabaseSQLite","title":"Collections","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"The Table name should be the same as the name of the Collection.\nThe Table name of a Collection should beging with a capital letter and be in singular form.\nIn case of a Collection with a composite name, the Table name should written in Pascal Case.\nThe Table must contain a primary key named id that is an INTEGER. You should use the AUTOINCREMENT keyword to automatically generate the id for each element.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Examples:","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE Resource (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n label TEXT UNIQUE NOT NULL,\n some_type TEXT\n) STRICT;\n\nCREATE TABLE ThermalPlant(\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n label TEXT UNIQUE NOT NULL,\n minimum_generation REAL DEFAULT 0\n) STRICT;","category":"page"},{"location":"psrdatabasesqlite/rules/#Configuration-collection","page":"PSRDatabaseSQLite","title":"Configuration collection","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Every database definition must have a Configuration, which will store information from the case. The column label is not mandatory for a Configuration collection.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE Configuration (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n value1 REAL NOT NULL DEFAULT 100,\n) STRICT;","category":"page"},{"location":"psrdatabasesqlite/rules/#Non-vector-Attributes","page":"PSRDatabaseSQLite","title":"Non-vector Attributes","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"The name of an Attribute should be in snake case and be in singular form.\nIf the attribute's name is label, it should be stored as a TEXT and have the UNIQUE and NOT NULL constraints.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Example:","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE ThermalPlant(\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n label TEXT UNIQUE NOT NULL,\n minimum_generation REAL NOT NULL\n some_example_of_attribute REAL\n) STRICT;","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"If an attribute name starts with date it should be stored as a TEXT and indicates a date that will be mapped to a DateTime object.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Example:","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE ThermalPlant(\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n label TEXT UNIQUE NOT NULL,\n minimum_generation REAL NOT NULL,\n date_of_construction TEXT\n) STRICT;","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"If an attribute name starts with the name of another collection it should be stored as a INTEGER and indicates a relation with another collection. It should never have the NOT NULL constraint. All references should always declare the ON UPDATE CASCADE ON DELETE CASCADE constraint. In the example below the attribute gaugingstation_id indicates that the collection Plant has an id relation with the collection GaugingStation and the attribute plant_spill_to indicates that the collection Plant has a spill_to relation with itself.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Example:","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE Plant(\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n label TEXT UNIQUE NOT NULL,\n capacity REAL NOT NULL,\n gaugingstation_id INTEGER,\n plant_spill_to INTEGER,\n FOREIGN KEY(gaugingstation_id) REFERENCES GaugingStation(id) ON UPDATE CASCADE ON DELETE CASCADE,\n FOREIGN KEY(plant_spill_to) REFERENCES Plant(id) ON UPDATE SET NULL ON DELETE CASCADE\n) STRICT;","category":"page"},{"location":"psrdatabasesqlite/rules/#Vector-Attributes","page":"PSRDatabaseSQLite","title":"Vector Attributes","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"In case of a vector attribute, a table should be created with its name indicating the name of the Collection and the name of a group of the attribute, separated by _vector_, such as COLLECTION_vector_GROUP_OF_ATTRIBUTES.\nThe table must contain a Column named id and another named vector_index.\nThere must be a Column named after the attributes names, which will store the value of the attribute for the specified element id and index vector_index.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"These groups are used to store vectors that should have the same size. If two vectors don't necessarily have the same size, they should be stored in different groups.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Example:","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE ThermalPlant_vector_some_group(\n id INTEGER,\n vector_index INTEGER NOT NULL,\n some_value REAL NOT NULL,\n some_other_value REAL,\n FOREIGN KEY (id) REFERENCES ThermalPlant(id) ON UPDATE CASCADE ON DELETE CASCADE,\n PRIMARY KEY (id, vector_index)\n) STRICT;","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Example of a small time series","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE ThermalPlant_vector_some_group(\n id INTEGER,\n vector_index INTEGER NOT NULL,\n date_of_modification REAL NOT NULL,\n capacity REAL,\n FOREIGN KEY (id) REFERENCES ThermalPlant(id) ON UPDATE CASCADE ON DELETE CASCADE,\n PRIMARY KEY (id, vector_index)\n) STRICT;","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"A vector relation with another collection should be stored in a table of vector groups and be defined the same way as a vector attribute. To tell that it is a relation with another collection, the name of the relational attribute should be the name of the target collection followed by the relation type defined as _relation_type, i.e. gaugingstation_id indicated that the collection HydroPlant has an id relation with the collection GaugingStation. If the name of the attribute was gaugingstation_one_to_one, it would indicate that the collection HydroPlant has a relation one_to_one with the collection GaugingStation.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE HydroPlant_vector_GaugingStation(\n id INTEGER,\n vector_index INTEGER NOT NULL,\n conversion_factor REAL NOT NULL,\n gaugingstation_id INTEGER,\n FOREIGN KEY (gaugingstation_id) REFERENCES GaugingStation(id) ON UPDATE CASCADE ON DELETE CASCADE,\n PRIMARY KEY (id, vector_index)\n) STRICT;\n","category":"page"},{"location":"psrdatabasesqlite/rules/#Time-Series-Files","page":"PSRDatabaseSQLite","title":"Time Series Files","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"All Time Series files for the elements from a Collection should be stored in a Table\nThe Table name should be the same as the name of the Collection followed by _time_series_files, such as COLLECTION_vector_ATTRIBUTE.\nEach Column of the table should be named after the name of the attribute.\nEach Column should store the path to the file containing the time series data.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Example:","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE Plant_time_series_files (\n generation TEXT,\n cost TEXT\n) STRICT;","category":"page"},{"location":"psrdatabasesqlite/rules/#Time-Series","page":"PSRDatabaseSQLite","title":"Time Series","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Time Series stored in the database should be stored in a table with the name of the Collection followed by _time_series_ and the name of the attribute group, such a COLLECTION_time_series_GROUP_OF_ATTRIBUTES.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Notice that it is quite similar to the vector attributes, but without the vector_index column. Instead, a mandatory column named date_time should be created to store the date of the time series data.","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Example:","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"CREATE TABLE Resource_time_series_group1 (\n id INTEGER, \n date_time TEXT NOT NULL,\n some_vector1 REAL,\n some_vector2 REAL,\n FOREIGN KEY(id) REFERENCES Resource(id) ON DELETE CASCADE ON UPDATE CASCADE,\n PRIMARY KEY (id, date_time)\n) STRICT; ","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"tip: Tip\n","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"For more information on how to handle time series data, please refer to the Time Series section.","category":"page"},{"location":"psrdatabasesqlite/rules/#Migrations","page":"PSRDatabaseSQLite","title":"Migrations","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"Migrations are an important part of the DatabaseSQLite framework. They are used to update the database schema to a new version without the need to delete the database and create a new one from scratch. Migrations are defined by two separate .sql files that are stored in the migrations directory of the model. The first file is the up migration and it is used to update the database schema to a new version. The second file is the down migration and it is used to revert the changes made by the up migration. Migrations are stored in directories in the model and they have a specific naming convention. The name of the migration folder should be the number of the version (e.g. /migrations/1/).","category":"page"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"database/migrations\n├── 1\n│ ├── up.sql\n│ └── down.sql\n└── 2\n ├── up.sql\n └── down.sql","category":"page"},{"location":"psrdatabasesqlite/rules/#Creating-a-migration","page":"PSRDatabaseSQLite","title":"Creating a migration","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"It is advised to create new migrations using the functions from DatabaseSQLite. First you need to make sure that the migrations directory is registered by the function DatabaseSQLite.set_migrations_folder and after that you can create a new migration using the function DatabaseSQLite.create_migration. This function will create a new migration file with the name and version specified by the user. The migration file will contain a template for the migration.","category":"page"},{"location":"psrdatabasesqlite/rules/#Running-migrations","page":"PSRDatabaseSQLite","title":"Running migrations","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"To run migrations you need to use the function DatabaseSQLite.apply_migrations!. There are various versions of this function, each one tailored to make something easier for the user.","category":"page"},{"location":"psrdatabasesqlite/rules/#Testing-migrations","page":"PSRDatabaseSQLite","title":"Testing migrations","text":"","category":"section"},{"location":"psrdatabasesqlite/rules/","page":"PSRDatabaseSQLite","title":"PSRDatabaseSQLite","text":"It is very important to test if the migrations of a certain model are working as expected, so the user can be sure that the database schema is updated correctly. To test migrations you need to use the function DatabaseSQLite.test_migrations(). It is highly advised that each model has one of these functions in their test suite to make sure that the migrations are working as expected.","category":"page"},{"location":"#PSRClassesInterface-Documentation","page":"Home","title":"PSRClassesInterface Documentation","text":"","category":"section"},{"location":"","page":"Home","title":"Home","text":"PSRClassesInterface, or PSRI, is a Julia package that provides an interface to read and write open-source formats for PSR models. It is comprised of three main modules:","category":"page"},{"location":"","page":"Home","title":"Home","text":"OpenStudy: Reads and writes data in the JSON format\nOpenBinary: Reads and writes time series data in the binary format\nPSRDatabaseSQLite: Reads and writes data in the SQL format","category":"page"},{"location":"#Installation","page":"Home","title":"Installation","text":"","category":"section"},{"location":"","page":"Home","title":"Home","text":"This package is registered so you can simply add it using Julia's Pkg manager:","category":"page"},{"location":"","page":"Home","title":"Home","text":"julia> import Pkg\n\njulia> Pkg.add(\"PSRClassesInterface\")","category":"page"},{"location":"#Contributing","page":"Home","title":"Contributing","text":"","category":"section"},{"location":"","page":"Home","title":"Home","text":"Users are encouraged to contributing by opening issues and opening pull requests. If you wish to implement a feature please follow the JuMP Style Guide","category":"page"}] +} diff --git a/previews/PR226/siteinfo.js b/previews/PR226/siteinfo.js new file mode 100644 index 00000000..6ea48938 --- /dev/null +++ b/previews/PR226/siteinfo.js @@ -0,0 +1 @@ +var DOCUMENTER_CURRENT_VERSION = "previews/PR226"; diff --git a/previews/PR226/sqlite_examples/migrations/index.html b/previews/PR226/sqlite_examples/migrations/index.html new file mode 100644 index 00000000..d221862e --- /dev/null +++ b/previews/PR226/sqlite_examples/migrations/index.html @@ -0,0 +1,313 @@ + +Migration Examples · PSRClassesInterface.jl

      Migration Examples

      Migrations are a way to manage the evolution of the database schema over time. As mentioned in the documentation for PSRDatabaseSQLite, migrations are defined by two separate .sql files that are stored in the migrations directory of the model. The first file is the up migration and it is used to update the database schema to a new version. The second file is the down migration and it is used to revert the changes made by the up migration. Migrations are stored in directories in the model and they have a specific naming convention. The name of the migration folder should be the number of the version (e.g. /migrations/1/).

      In this section, we will provide some examples of migrations. First, let us start with the first migration, the one that creates the initial database schema.

      Adding two tables to the database

      PRAGMA user_version = 1; -- Set the database version to 1
      +PRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity
      +
      +-- Create the Configuration table
      +CREATE TABLE Configuration (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    value TEXT NOT NULL
      +) ;
      +
      +-- Create Plant table
      +CREATE TABLE Plant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    bus_name TEXT NOT NULL
      +) ;

      This schema is the up.sql migration for version 1. It creates two tables, Configuration and Plant. Now we have to create the down.sql migration for version 1. This migration should drop the tables created in the up.sql migration.

      PRAGMA user_version = 0; -- Set the database version to 0
      +-- Drop the Configuration table
      +DROP TABLE Configuration;
      +-- Drop the Plant table
      +DROP TABLE Plant;

      Adding a new column

      Now let us create a migration that adds a new column to the Configuration and Plant tables.

      PRAGMA user_version = 2; -- Set the database version to 2
      +PRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity
      +
      +-- Add the description column to the Configuration table
      +ALTER TABLE Configuration ADD COLUMN description TEXT;
      +
      +-- Add the type column to the Plant table
      +ALTER TABLE Plant ADD COLUMN type INTEGER NOT NULL DEFAULT 0;

      This is the up.sql migration for version 2. The down.sql migration should remove the column added in the up.sql migration.

      PRAGMA user_version = 1; -- Set the database version to 1
      +
      +-- Remove the description column from the Configuration table
      +ALTER TABLE Configuration DROP COLUMN description;
      +
      +-- Remove the type column from the Plant table
      +ALTER TABLE Plant DROP COLUMN type;

      Renaming a table

      Let us create a migration that renames the Plant table to PowerPlant.

      PRAGMA user_version = 3; -- Set the database version to 3
      +PRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity
      +
      +-- Rename the Plant table to PowerPlant
      +ALTER TABLE Plant RENAME TO PowerPlant;

      This is the up.sql migration for version 3. The down.sql migration should rename the PowerPlant table back to Plant.

      PRAGMA user_version = 2; -- Set the database version to 2
      +
      +-- Rename the PowerPlant table to Plant
      +ALTER TABLE PowerPlant RENAME TO Plant;

      Adding a foreign key constraint

      Let us create a migration that adds a foreign key constraint to the PowerPlant table. First, we need to create a new table, Resource, that will be referenced by the PowerPlant table.

      Adding a foreign key constraint, however, is not as trivial as adding a column or renaming a table. We need to follow these steps:

      1. Disable foreign key constraints
      2. Start a transaction
      3. Create an auxiliary new_PowerPlant table with the new column and the foreign key constraint
      4. Copy the data from the PowerPlant table to the new_PowerPlant table
      5. Drop the PowerPlant table
      6. Rename the new_PowerPlant table to PowerPlant
      7. Check if any foreign key constraints were violatet with PRAGMA foreign_key_check
      8. Commit the transaction
      9. Enable foreign key constraints
      PRAGMA user_version = 4; -- Set the database version to 4
      +PRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity
      +
      +-- Create the Resource table
      +CREATE TABLE Resource (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL
      +) ;
      +
      +-- Disable foreign key constraints
      +PRAGMA foreign_keys = OFF;
      +
      +-- Start a transaction
      +BEGIN TRANSACTION;
      +
      +-- Create the new PowerPlant table
      +CREATE TABLE new_PowerPlant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    bus_name TEXT NOT NULL,
      +    type INTEGER NOT NULL DEFAULT 0,
      +    resource_id INTEGER,
      +    FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE
      +) ;
      +
      +-- Copy the data from the PowerPlant table to the new PowerPlant table
      +INSERT INTO new_PowerPlant (id, label, capacity, bus_name, type)
      +SELECT id, label, capacity, bus_name, type FROM PowerPlant;
      +
      +-- Drop the PowerPlant table
      +DROP TABLE PowerPlant;
      +
      +-- Rename the new PowerPlant table to PowerPlant
      +ALTER TABLE new_PowerPlant RENAME TO PowerPlant;
      +
      +-- Check if any foreign key constraints were violated
      +PRAGMA foreign_key_check;
      +
      +-- Commit the transaction
      +COMMIT;
      +
      +-- Enable foreign key constraints
      +PRAGMA foreign_keys = ON;

      Now, the down.sql migration should revert the changes made by the up.sql migration.

      PRAGMA user_version = 3; -- Set the database version to 3
      +
      +-- Disable foreign key constraints
      +PRAGMA foreign_keys = OFF;
      +
      +-- Start a transaction
      +BEGIN TRANSACTION;
      +
      +-- Create the new PowerPlant table
      +CREATE TABLE new_PowerPlant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    bus_name TEXT NOT NULL,
      +    type INTEGER NOT NULL DEFAULT 0
      +) ;
      +
      +-- Copy the data from the PowerPlant table to the new PowerPlant table
      +INSERT INTO new_PowerPlant (id, label, capacity, bus_name, type)
      +SELECT id, label, capacity, bus_name, type FROM PowerPlant;
      +
      +-- Drop the PowerPlant table
      +DROP TABLE PowerPlant;
      +
      +-- Rename the new PowerPlant table to PowerPlant
      +ALTER TABLE new_PowerPlant RENAME TO PowerPlant;
      +
      +-- Check if any foreign key constraints were violated
      +PRAGMA foreign_key_check;
      +
      +-- Commit the transaction
      +COMMIT;
      +
      +-- Enable foreign key constraints
      +PRAGMA foreign_keys = ON;
      +
      +-- Drop the Resource table
      +DROP TABLE Resource;

      Dividing a table into two tables

      Let us create a migration that divides the PowerPlant table into two tables, HydroPlant and ThermalPlant. HydroPlant corresponds to the rows with type = 0 and ThermalPlant corresponds to the rows with type = 1.

      PRAGMA user_version = 5; -- Set the database version to 5
      +
      +
      +
      +PRAGMA foreign_keys = OFF;
      +BEGIN TRANSACTION;
      +
      +-- Create the HydroPlant table
      +CREATE TABLE HydroPlant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    bus_name TEXT NOT NULL,
      +    resource_id INTEGER,
      +    FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE
      +) ;
      +
      +-- Create the ThermalPlant table
      +CREATE TABLE ThermalPlant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    bus_name TEXT NOT NULL,
      +    resource_id INTEGER,
      +    FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE
      +) ;
      +
      +-- Fill the HydroPlant table
      +INSERT INTO HydroPlant (id, label, capacity, bus_name, resource_id)
      +SELECT id, label, capacity, bus_name, resource_id FROM PowerPlant WHERE type = 0;
      +
      +-- Fill the ThermalPlant table
      +INSERT INTO ThermalPlant (id, label, capacity, bus_name, resource_id)
      +SELECT id, label, capacity, bus_name, resource_id FROM PowerPlant WHERE type = 1;
      +
      +-- Drop the PowerPlant table
      +DROP TABLE PowerPlant;
      +
      +PRAGMA foreign_key_check;
      +COMMIT;
      +PRAGMA foreign_keys = ON;
      +

      This is the up.sql migration for version 5. The down.sql migration should revert the changes made by the up.sql migration.

      PRAGMA user_version = 4; -- Set the database version to 4
      +PRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity
      +
      +-- Create the PowerPlant table
      +CREATE TABLE PowerPlant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    type INTEGER NOT NULL DEFAULT 0,
      +    bus_name TEXT NOT NULL,
      +    resource_id INTEGER,
      +    FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE
      +) ;
      +
      +-- Fill the PowerPlant table
      +INSERT INTO PowerPlant (id, label, capacity, bus_name, type, resource_id)
      +SELECT id, label, capacity, bus_name, 0, resource_id FROM HydroPlant;
      +
      +INSERT INTO PowerPlant (id, label, capacity, bus_name, type, resource_id)
      +SELECT id, label, capacity, bus_name, 1, resource_id FROM ThermalPlant;
      +
      +-- Drop the HydroPlant table
      +DROP TABLE HydroPlant;
      +
      +-- Drop the ThermalPlant table
      +DROP TABLE ThermalPlant;

      Create a table with data from another table

      Let us create a migration that adds a new Table Bus with data from the HydroPlant and ThermalPlant tables. These tables already have a column bus_name that will be used to fill the Bus table. After creating the Bus table, we will remove the bus_name column from the HydroPlant and ThermalPlant tables. Moreover, the bus_name column in the PowerPlant table will be replaced by a bus_id column that references the Bus table.

      PRAGMA user_version = 6; -- Set the database version to 6
      +PRAGMA foreign_keys = ON; -- Enable foreign keys to enforce referential integrity
      +
      +-- Create the Bus table
      +CREATE TABLE Bus (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL
      +) ;
      +
      +-- Fill the Bus table
      +INSERT INTO Bus (label)
      +SELECT DISTINCT bus_name FROM HydroPlant;
      +
      +INSERT INTO Bus (label)
      +SELECT DISTINCT bus_name FROM ThermalPlant;
      +
      +PRAGMA foreign_keys = OFF;
      +BEGIN TRANSACTION;
      +
      +-- Add foreign key 
      +CREATE TABLE new_HydroPlant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    resource_id INTEGER,
      +    bus_id INTEGER,
      +    FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE,
      +    FOREIGN KEY (bus_id) REFERENCES Bus(id) ON UPDATE CASCADE ON DELETE CASCADE
      +) ;
      +
      +CREATE TABLE new_ThermalPlant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    resource_id INTEGER,
      +    bus_id INTEGER,
      +    FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE,
      +    FOREIGN KEY (bus_id) REFERENCES Bus(id) ON UPDATE CASCADE ON DELETE CASCADE
      +) ;
      +
      +-- Copy the data from the HydroPlant table to the new HydroPlant table
      +INSERT INTO new_HydroPlant (id, label, capacity, resource_id)
      +SELECT id, label, capacity, resource_id FROM HydroPlant;
      +
      +-- Copy the data from the ThermalPlant table to the new ThermalPlant table
      +INSERT INTO new_ThermalPlant (id, label, capacity, resource_id)
      +SELECT id, label, capacity, resource_id FROM ThermalPlant;
      +
      +-- Add data for the bus_id column
      +UPDATE new_HydroPlant SET bus_id = (SELECT Bus.id FROM Bus
      +INNER JOIN HydroPlant ON Bus.label = HydroPlant.bus_name AND 
      +HydroPlant.id = new_HydroPlant.id
      +);
      +UPDATE new_ThermalPlant SET bus_id = (SELECT Bus.id FROM Bus
      +INNER JOIN ThermalPlant ON Bus.label = ThermalPlant.bus_name AND
      +ThermalPlant.id = new_ThermalPlant.id
      +);
      +
      +-- Drop tables
      +DROP TABLE HydroPlant;
      +DROP TABLE ThermalPlant;
      +
      +-- Rename tables
      +ALTER TABLE new_HydroPlant RENAME TO HydroPlant;
      +ALTER TABLE new_ThermalPlant RENAME TO ThermalPlant;
      +
      +PRAGMA foreign_key_check;
      +COMMIT;
      +PRAGMA foreign_keys = ON;

      This is the up.sql migration for version 6. The down.sql migration should revert the changes made by the up.sql migration.

      PRAGMA user_version = 5; -- Set the database version to 5
      +
      +
      +PRAGMA foreign_keys = OFF;
      +BEGIN TRANSACTION;
      +
      +-- Create auxiliary tables
      +CREATE TABLE new_HydroPlant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    resource_id INTEGER,
      +    bus_name TEXT,
      +    FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE
      +) ;
      +
      +CREATE TABLE new_ThermalPlant (
      +    id INTEGER PRIMARY KEY,
      +    label TEXT UNIQUE NOT NULL,
      +    capacity REAL NOT NULL,
      +    resource_id INTEGER,
      +    bus_name TEXT,
      +    FOREIGN KEY (resource_id) REFERENCES Resource(id) ON UPDATE CASCADE ON DELETE CASCADE
      +) ;
      +
      +-- Copy the data from the HydroPlant table to the new HydroPlant table
      +INSERT INTO new_HydroPlant (id, label, capacity, resource_id)
      +SELECT id, label, capacity, resource_id FROM HydroPlant;
      +
      +-- Copy the data from the ThermalPlant table to the new ThermalPlant table
      +INSERT INTO new_ThermalPlant (id, label, capacity, resource_id)
      +SELECT id, label, capacity, resource_id FROM ThermalPlant;
      +
      +-- Add data for the bus_name column
      +UPDATE new_HydroPlant SET bus_name = (SELECT Bus.label FROM Bus
      +INNER JOIN HydroPlant ON Bus.id = HydroPlant.bus_id AND 
      +HydroPlant.id = new_HydroPlant.id
      +);
      +
      +UPDATE new_ThermalPlant SET bus_name = (SELECT Bus.label FROM Bus
      +INNER JOIN ThermalPlant ON Bus.id = ThermalPlant.bus_id AND
      +ThermalPlant.id = new_ThermalPlant.id
      +);
      +
      +-- Drop tables
      +DROP TABLE HydroPlant;
      +DROP TABLE ThermalPlant;
      +
      +-- Rename tables
      +ALTER TABLE new_HydroPlant RENAME TO HydroPlant;
      +ALTER TABLE new_ThermalPlant RENAME TO ThermalPlant;
      +
      +-- Drop the Bus table
      +DROP TABLE Bus;
      +
      +PRAGMA foreign_key_check;
      +COMMIT;
      +PRAGMA foreign_keys = ON;