From 8cbb1414633265855a6b713682d14b6bac72a3bd Mon Sep 17 00:00:00 2001 From: YunchaoLiu Date: Sat, 8 Sep 2018 17:59:52 -0500 Subject: [PATCH] finsh function until expand_node_view --- assignment0.zip | Bin 0 -> 48428 bytes assignment0/assignment0.jpg | Bin 0 -> 50645 bytes assignment0/index.html | 10 +- assignment1.zip | Bin 0 -> 330083 bytes assignment1/README.md | 2 +- assignment1/part2.html | 66 ++++++ assignment2/.interactive_time_series.js.swp | Bin 0 -> 16384 bytes assignment2/README.md | 126 +++++++++++ assignment2/basictheme.css | 10 + assignment2/index.html | 21 ++ assignment2/interactive_time_series.js | 227 ++++++++++++++++++++ assignment2/japan_population.json | 1 + 12 files changed, 457 insertions(+), 6 deletions(-) create mode 100644 assignment0.zip create mode 100644 assignment0/assignment0.jpg create mode 100644 assignment1.zip create mode 100644 assignment2/.interactive_time_series.js.swp create mode 100644 assignment2/README.md create mode 100644 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experience with web development?' - var a3 = '' + var a3 = 'I have very limited experience' var q4 = 'What is your experience with D3?' - var a4 = '' + var a4 = 'none' var q5 = 'Have you used visualization tools and libraries before, such as Tableau, matplotlib, ggplot2, etc..?' - var a5 = '' + var a5 = 'Tableau, but for a very short time' var qs_and_as = [{'statement_type':'question','value':q1},{'statement_type':'answer','value':a1}, {'statement_type':'question','value':q2},{'statement_type':'answer','value':a2}, {'statement_type':'question','value':q3},{'statement_type':'answer','value':a3}, diff --git a/assignment1.zip b/assignment1.zip new file mode 100644 index 0000000000000000000000000000000000000000..b2177f68ff1e75575c6a4dda23a14574db8b60d8 GIT binary patch literal 330083 zcmaI6Q*bU!(6$?`C0TF?7?A%N>#C&k|9A2KI5-eI5Mx(YYfA@va|btOMs+o45b!G1cwH*BcwKid zSP)Q%hhkU|2uey25T*ZA(Ed9I0MSV%ke8(Hv?GE50oi~D0m1lRDo(~OZp;i;ZuWNn 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z)ayhabG^sTd21qo_+c5NDq0e`p&R0`=aC+8EZm6`J4z(9-&oWf(UF?Z>pj8_SK9+W zpl+fKuU=YPBFTN3k)kZrAmkBRto2}Ic4_F5Fc+-=@-!fQMt~$xE+?8sAx_c}j#Lj} zzfia#+226n`>hrvW#|y&{SN)_~-l&GpThKTQizXb*I=;ASP{u>{4pU ziBQ88Z&s_Q*v!4UR5{r$Ej#z=Pg$G$YR@mphM1)9j0mLlBl$V-uiJwJetLn+0A1Q5g@T&qNe5!W=m>xS-!=g zY!*l5^@y6}U9zIx7oj5N(C*iB^{QEVVx-9pB{4S71Q48jYGV~=4{EC$)>IR5 z6-whlQ-VotVTpq%^QApgOCfd+Tbqu<+(MaJo_yj$QL)1F9Xm~;<$!WC?1oiTuNS(0 zYdHS!g(x+9WMv*c35}z|n15tbCqY7s7G=+#q%L@(hfiB%sV92yluMAe&Z9CT53k7a zlygDIBN@tRQN}gHZFz{~_j;b|6XN8Lld?W3|8%kN + + + + Assignment 2 - Plotting Time Series Data + + + + + + + + diff --git a/assignment2/interactive_time_series.js b/assignment2/interactive_time_series.js new file mode 100644 index 0000000..ef3bb6c --- /dev/null +++ b/assignment2/interactive_time_series.js @@ -0,0 +1,227 @@ +// NOTE: these global variables will be constructed in plot_it! +var x_scale, y_scale, line_scale; +var actual_width, actual_height; + +// data type conversions, so we are working with floats and dates +function data_type_conversion(node) { + if(node.children.length > 0) { + for(var c = 0; c < node.children.length; c++) + data_type_conversion(node.children[c]); + return; + } + + var time_parser = is_music_time_series ? d3.timeParse('%Y-%m-%d') : d3.timeParse('%Y %B'); + node.counts.forEach(function(d) { + d.date = time_parser(d.date); + d.count = +d.count; + }); +} + +// add a 'parent' field to each node, so we can access parent data +function add_parent_links(node) { + for(var c = 0; c < node.children.length; c++) { + node.children[c].parent = node; + add_parent_links(node.children[c]); + } +} + +// go through all nodes and collect count data +function get_all_count_data(node, all_count_data) { + for(var p = 0; p < node.counts.length; p++) + all_count_data.push(node.counts[p].count); + for(var c = 0; c < node.children.length; c++) + get_all_count_data(node.children[c], all_count_data); +} + +// create a color for each node based on the tree hierarchy (this is manually coded up: categorical colors for many categories is really tricky!) +function create_color(root_node) { + // black color for root + root_node.color = d3.rgb(0,0,0); + var hue_scale = d3.scaleLinear().domain([0,root_node.children.length-1]).range([10,250]) + for(var c = 0; c < root_node.children.length; c++) { + var child_node = root_node.children[c]; + var interpolator = d3.interpolateLab(d3.hsl(hue_scale(c),0.8,0.3), d3.hsl(hue_scale(c),0.8,0.8)) + child_node.color = interpolator(0.5); + for(var d = 0; d < child_node.children.length; d++) + child_node.children[d].color = interpolator(d / (child_node.children.length-1)); + } +} + +// TODO: create a time series for each non-leaf node (`counts`) that aggregates its count data and dates - same format as `counts` in leaves +function aggregate_counts(node) { + //console.log("node_name:" +node.name); + + if(node.children.length > 0) {//not leave node + node.counts = []; + var population =0; + var date_data = {count:population, date : ''}; + var c = 0; + var i = 0; + var k = 30; + var flag = true; + for(i=0; (flag == true) && (i< k);i++, population = 0){ + + for(c = 0; c < node.children.length; c++){ + + child_counts = aggregate_counts(node.children[c]); + //console.log("i: "+i +", definition:" +child_counts[i]); + //console.log(aggregate_counts(node.children[0])[0].date); + if(child_counts[i] == undefined){ + flag = false + //console.log('break'); + break; + } + date_child_counts = child_counts[i]; + //console.log("i: "+i + ", c:" + c); + population += date_child_counts.count; + date = date_child_counts.date; + date_data = {count: population, date:date } + + }//for loop (var c) + + if(flag != false){ + + node.counts.push(date_data); + + } + flag = true; + }//for loop (var i) + + }//if(node.children.length>0) + + if(node.name == 'Japan'){ + console.log(node); + } + return node.counts//, node.counts.date]; + + +} + +// TODO: create/set `view_series` field to false for `node` and all of its children +function reset_node_views(node) { + //console.log('reset'); + node.view_series = false; + if (node.children.length>0){ + + for(var i =0; i< node.children.length; i++){ + + reset_node_views(node.children[i]); + + } + + } + + if(node.name == 'Japan'){ + console.log(node); + } + +} + +// TODO: traverse tree, adding nodes where `view_series` is set to true to `node_array` +function collect_viewable_nodes(node, node_array) { +//console.log("collect"); + if(node.view_series == true){ + + node.children.push(node_array); + + } + if(node.children != undefined){ + + if (node.children.length>0){ + + for (var i =0; i< node.children.length; i++){ + + collect_viewable_nodes(node.children[i], node_array); + + } + } + + } + if(node.name == 'Japan'){ + console.log(node); + } + +} + +// TODO: make `node` no longer visible, but its immediate children visible (if a child, nothing to do) - modify `view_series`! +function expand_node_view(node) { + node.view_series = false; + if(node.children.length>0){ + for(var i = 0; i< node.children.length; i++){ + + node.children[i].view_series = true; + + } + } + +} + +// TODO: make the parent of `node` visible, but the subtree rooted at `node` should not be visible (hint `reset_node_views`) (if a parent, nothing to do) - modify `view_series`! +function collapse_node_view(node) { +} + +// TODO: does all of the visualization -> get the time series to view (`collect_viewable_nodes`), data join, setup interactions +function visualize_time_series(root_node, is_collapsing, selected_node) { + var node_array = []; + collect_viewable_nodes(root_node, node_array); + + // TODO: data join for line plot + //d3.select('rect').append('path').datum(root_node) + // .attr('d', d=>d) + // .attr('fill', 'none') + // .attr('stroke', '#777777') + // .attr('stroke-width', '3'); + // TODO: remove old series + + // TODO: add new series + + // TODO: setup interactions + + // TODO: data join for text + + // TODO: text labels - remove old ones (fade them out via opacity) + + // TODO: text labels - add new ones (fade them in via opacity) +} + +function plot_it() { + // some preprocessing + data_type_conversion(count_tree); + add_parent_links(count_tree); + count_tree.parent = null; + create_color(count_tree); + + // First things first: we aggregate the time series data: non-leaf nodes should aggregate their child nodes in some sense (e.g. mean) + aggregate_counts(count_tree); + + // Second: we initialize the nodes as to whether or not to visualize them - first, lets assume we aren't viewing any of them ... + reset_node_views(count_tree); + + // ... and then set the root node view to be true (have to view something to start!) + count_tree.view_series = true; + + // visualization setup: width, height, padding, actual width and height + var width = 800, height = 800; + var pad = 80; + actual_width = width-2*pad; + actual_height = height-2*pad; + // add svg element of width x height + d3.select('body').append('svg').attr('width', width).attr('height', height); + // add transformation element to center the main plotting area by pad, assign it an id since we will be primarily selecting it + d3.select('svg').append('g').attr('transform', 'translate('+pad+','+pad+')').attr('id', 'mainplot'); + // add element to have a nice backdrop for our plot! + d3.select('#mainplot').append('rect').attr('width', actual_width).attr('height', actual_height).attr('fill', '#999999').attr('opacity', 0.4) + + // TODO: setting up scales: we need to compute the minimum and maximum of our count data and dates; so first, lets get our count data from all nodes, then compute min/max + + // TODO: for the min/max of dates, they are equivalent across nodes, so just map the root node's dates to an array, compute min and max + + // TODO: compute the x and y scales for the line plots + + // TODO: setup the line scale + + // TODO: setup axes from the scales + + // visualize data! + visualize_time_series(count_tree, false); +} diff --git a/assignment2/japan_population.json b/assignment2/japan_population.json new file mode 100644 index 0000000..8475f07 --- /dev/null +++ b/assignment2/japan_population.json @@ -0,0 +1 @@ +{"name": "Japan", "children": [{"name": "Honshu", "children": [{"name": "Akita-ken", "counts": [{"count": "898537", "date": "1920 October"}, {"count": "936408", "date": "1925 October"}, {"count": "987706", "date": "1930 October"}, {"count": "1037744", "date": "1935 October"}, {"count": "1052275", "date": "1940 October"}, {"count": "1048769", "date": "1944 April"}, {"count": "1211871", "date": "1945 November"}, {"count": "1195813", "date": "1946 May"}, {"count": "1257398", "date": "1947 October"}, {"count": "1283710", "date": "1948 August"}, {"count": "1309031", "date": "1950 October"}, {"count": "1348871", "date": "1955 October"}, {"count": "1335580", "date": "1960 October"}, {"count": "1279835", "date": "1965 October"}, {"count": "1241376", "date": "1970 October"}, {"count": "1232481", "date": "1975 October"}, {"count": "1256745", "date": 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"date": "1965 October"}, {"count": "1427520", "date": "1970 October"}, {"count": "1468646", "date": "1975 October"}, {"count": "1523907", "date": "1980 October"}, {"count": "1524448", "date": "1985 October"}, {"count": "1482873", "date": "1990 October"}, {"count": "1481663", "date": "1995 October"}, {"count": "1475728", "date": "2000 October"}, {"count": "1436657", "date": "2005 October"}, {"count": "1373339", "date": "2010 October"}, {"count": "1308649", "date": "2015 October"}], "children": []}, {"name": "Fukui-ken", "counts": [{"count": "599155", "date": "1920 October"}, {"count": "597899", "date": "1925 October"}, {"count": "618144", "date": "1930 October"}, {"count": "646659", "date": "1935 October"}, {"count": "643904", "date": "1940 October"}, {"count": "621933", "date": "1944 April"}, {"count": "724856", "date": "1945 November"}, {"count": "695703", "date": "1946 May"}, {"count": "726264", "date": "1947 October"}, {"count": "733374", "date": "1948 August"}, {"count": "752374", 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