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Copy pathsections.js
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executable file
·951 lines (830 loc) · 24.2 KB
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/**
* scrollVis - encapsulates
* all the code for the visualization
* using reusable charts pattern:
* http://bost.ocks.org/mike/chart/
*/
var scrollVis = function(trumpVisData) {
// constants to define the size
// and margins of the vis area.
var width = 600;
var height = 520;
var margin = {top:0, left:20, bottom:40, right:10};
// Keep track of which visualization
// we are on and which was the last
// index activated. When user scrolls
// quickly, we want to call all the
// activate functions that they pass.
var lastIndex = -1;
var activeIndex = 0;
// Sizing for the grid visualization
var squareSize = 6;
var squarePad = 2;
var numPerRow = width / (squareSize + squarePad);
// main svg used for visualization
var svg = null;
// d3 selection that will be used
// for displaying visualizations
var g = null;
// We will set the domain when the
// data is processed.
var xBarScale = d3.scale
8000
Linear()
.range([0, width]);
// The bar chart display is horizontal
// so we can use an ordinal scale
// to get width and y locations.
var yBarScale = d3.scaleBand()
.domain([0,1,2])
.range([0, height - 50])
.padding([0.1])
// Color is determined just by the index of the bars
var barColors = {0: "#008080", 1: "#399785", 2: "#5AAF8C"};
// The histogram display shows the
// first 30 minutes of data
// so the range goes from 0 to 30
var xHistScale = d3.scaleLinear()
.domain([0, 30])
.range([0, width - 20]);
var yHistScale = d3.scaleLinear()
.range([height, 0]);
// The color translation uses this
// scale to convert the progress
// through the section into a
// color value.
var coughColorScale = d3.scaleLinear()
.domain([0,1.0])
.range(["#008080", "red"]);
// You could probably get fancy and
// use just one axis, modifying the
// scale, but I will use two separate
// ones to keep things easy.
//var xAxisBar = d3.axisBottom(xBarScale)
//var xAxisHist = d3.axisLeft(xHistScale)
// .tickFormat(function(d) { return d + " min"; });
// When scrolling to a new section
// the activation function for that
// section is called.
var activateFunctions = [];
// If a section has an update function
// then it is called while scrolling
// through the section with the current
// progress through the section.
var updateFunctions = [];
var tweet_create_event = d3.dispatch('tweet_create_event')
/**
* chart
*
* @param selection - the current d3 selection(s)
* to draw the visualization in. For this
* example, we will be drawing it in #vis
*/
var chart = function(selection) {
selection.each(function(rawData) {
//console.log(rawData)
// create svg and give it a width and height
svg = d3.select(this).selectAll("svg").data([wordData]); //shouldn't rawData be bound here? wordData is defined below.
svg.enter().append("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.append("g")
.attr("id","viz_container")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
g = d3.select(this).selectAll("#viz_container");
// perform some preprocessing on raw data
var wordData = getWords(rawData);
// filter to just include filler words
var fillerWords = getFillerWords(wordData);
// get the counts of filler words for the
// bar chart display
var fillerCounts = groupByWord(fillerWords);
// set the bar scale's domain
var countMax = d3.max(fillerCounts, function(d) { return d.values;});
xBarScale.domain([0,countMax]);
// get aggregated histogram data
var histData = getHistogram(fillerWords);
// set histogram's domain
var histMax = d3.max(histData, function(d) { return d.y; });
yHistScale.domain([0, histMax]);
// get trumperVision data
//var trumpInsults = d3.json('data/2017-01-26_Trump_insults_NYT.json'
setupVis(wordData, fillerCounts, histData,trumpVisData);
setupSections();
});
};
/**
* setupVis - creates initial elements for all
* sections of the visualization.
*
* @param wordData - data object for each word.
* @param fillerCounts - nested data that includes
* element for each filler word type.
* @param histData - binned histogram data
*/
setupVis = function(wordData, fillerCounts, histData, trumpVisData) {
// network viz
var selector = "network";
var network_selection = g.selectAll("g")
.data([trumpVisData])
.enter().append("g")
.attr("id",selector);
// create force simulation
Net = network(trumpVisData);
Net.width(width)
Net.height(height)
Net.node_opacity(1)
Net.data_groups([ "US Political","News","US Business","Random", "Foreign Interest","Famous"])
network_selection.call(Net)
// donald image
g.insert("image",":first-child")
.attr("class","TheDonald")
.attr("xlink:href","img/donald_cocktail.jpg")
.attr("x",width*0.56)
.attr("y",height*-0.05)
// count openvis title
g.append("text")
.attr("class", "sub-title openvis-title")
.attr("x", width / 2)
.attr("y", height / 1.4 + (height / 5))
.text("June 2015 - Jan 2017");
//tweet_create_event.on('tweet_create_event',opacityZero())
//tweet_create_event.call('tweet_create_event')
g.append("text")
.attr("class", "title openvis-title highlight")
.attr("x", width / 2)
.attr("y", (height / 3) )
//.attr("stroke","white")
//.attr("text-shadow","2px 2px white:")
.text("Tweet")
.style("stroke","#444")
.style("stroke-width","0.4px");
g.append("text")
.attr("class", "title openvis-title highlight")
.attr("x", width / 2)
.attr("y", (height / 2) )
//.attr("stroke","white")
//.attr("text-shadow","2px 2px white:")
.text("Bigly")
.style("stroke","#444")
.style("stroke-width","0.4px");
g.selectAll(".openvis-title")
.attr("opacity", 0);
// bar text & axis
g.append("g")
.attr("class","hbar xAxis")
.attr("opacity",0)
.attr("transform","translate ("+0+"," + Net.height()*Net.pEnd() + ")")
.call(d3.axisBottom(Net.hbar_xScale()));
// hbar legend
g.append("g")
.attr("class","hbar legend")
.attr("opacity",0)
.selectAll("circle")
.data(Net.group_array())
.enter().append('circle')
.attr("fill",d => Net.group_colorer()(d.group))
.attr("cx",height*0.97)
.attr("cy", d => Net.positionYScale()(d.group))
.attr("r",10)
.attr("stroke","white")
.attr("stroke-opacity",0.5);
g.append("g")
.attr("class","hbar legend-text")
.attr("opacity",0)
.selectAll("text")
.data(Net.group_array())
.enter().append('text')
.attr("fill","#767678")
.attr("x",height*0.99)
.attr("y", d => Net.positionYScale()(d.group)+3)
.attr("font-size", "13px")
.text(d=>d.group);
// hbar_breakout text & axis
g.append("g")
.attr("class","hbar_breakout xAxis")
.attr("opacity",0)
.attr("transform","translate ("+0+"," + Net.height()*0.10 + ")")
.call(d3.axisBottom(Net.hbar_xScale()));
// Hillary image
g.insert("image",":first-child")
.attr("class","hbar_breakout TheHill")
.attr("xlink:href","img/hillary_clinton_2.jpg")
.attr("x",Net.width()*0.80)
.attr("y",Net.height()*.13)
.attr("opacity",0)
.attr("width","80px")
// NYTimes image
g.insert("image",":first-child")
.attr("class","hbar_breakout NYT")
.attr("xlink:href","img/New_York_Times_logo_variation.jpg")
.attr("x",Net.width()*0.80)
.attr("y",Net.height()*0.30)
.attr("opacity",0)
.attr("width","80px")
// Cruz image
g.insert("image",":first-child")
.attr("class","hbar_breakout TheCruzer")
.attr("xlink:href","img/cruz-ted-bw.png")
.attr("x",Net.width()*0.82)
.attr("y",Net.height()*0.43)
.attr("opacity",0)
.attr("width","70px")
// The Jeb image
g.insert("image",":first-child")
.attr("class","hbar_breakout TheJeb")
.attr("xlink:href","img/bush-jeb-bw.png")
.attr("x",Net.width()*0.76)
.attr("y",Net.height()*0.43)
.attr("opacity",0)
.attr("width","70px")
// The Marco image
g.insert("image",":first-child")
.attr("class","hbar_breakout TheMarco")
.attr("xlink:href","img/rubio-marco.png")
.attr("x",Net.width()*0.69)
.attr("y",Net.height()*0.43)
.attr("opacity",0)
.attr("width","70px")
// The Kasich image
g.insert("image",":first-child")
.attr("class","hbar_breakout TheKasich")
.attr("xlink:href","img/kasich-john-bw.png")
.attr("x",Net.width()*0.63)
.attr("y",Net.height()*0.43)
.attr("opacity",0)
.attr("width","70px")
// The Bern image
g.insert("image",":first-child")
.attr("class","hbar_breakout TheBern")
.attr("xlink:href","img/sanders-bernard_bw.png")
.attr("x",Net.width()*0.56)
.attr("y",Net.height()*0.43)
.attr("opacity",0)
.attr("width","70px")
// Mainstream Media
g.insert("image",":first-child")
.attr("class","hbar_breakout TheMedia")
.attr("xlink:href","img/Mainstream_Media_2.png")
.attr("x",Net.width()*0.79)
.attr("y",Net.height()*0.60)
.attr("opacity",0)
.attr("width","90px")
//
g.insert("image",":first-child")
.attr("class","hbar_breakout Others")
.append("text")
.attr("x",Net.width()*0.79)
.attr("y",Net.height()*0.50)
.attr("opacity",0)
.text("All Others")
/*
// Megan Kelly
g.insert("image",":first-child")
.attr("class","hbar_breakout TheMegan")
.attr("xlink:href","img/megan_kelly.jpg")
.attr("x",Net.width()*0.36)
.attr("y",Net.height()*0.79)
.attr("opacity",0)
.attr("width","50px")
// Elizabeth Warren
g.insert("image",":first-child")
.attr("class","hbar_breakout TheWarren")
.attr("xlink:href","img/elizabeth_warren.jpg")
.attr("x",Net.width()*0.54)
.attr("y",Net.height()*0.78)
.attr("opacity",0)
.attr("width","65px")
*/
// SNL image
g.insert("image",":first-child")
.attr("class","hbar_breakout SNL")
.attr("xlink:href","img/snl_1.jpg")
.attr("x",Net.width()*0.82)
.attr("y",Net.height()*0.72)
.attr("opacity",0)
.attr("width","90px")
/*
// Macy image
g.insert("image",":first-child")
.attr("class","hbar_breakout Macys")
.attr("xlink:href","img/macys.png")
.attr("x",Net.width()*0.06)
.attr("y",Net.height()*0.80)
.attr("opacity",0)
.attr("width","80px")
*/
// count filler word count title
g.append("text")
.attr("class", "title count-title highlight")
.attr("x", width / 2)
.attr("y", height / 2)
.text("2,200+")
.style("stroke","#444")
.style("stroke-width","0.4px");
g.append("text")
.attr("class", "sub-title count-title")
.attr("x", width / 2)
.attr("y", (height / 1.4) + (height / 5) )
.text("Direct Insults");
// create foreignObject container
g.insert("g",":first-child")
.attr("id","foreignObject_container")
.insert("foreignObject",":first-child")
.attr("id","tweet_render")
.attr("x",width*0.145)
.attr("y",height*0.22)
.attr("width",450);
// render Tweet in foreign object
twttr.ready(
function (twttr) {
twttr.widgets.createTweet(
'820764134857969666',
document.getElementById('tweet_render'),
{
theme: ''
, conversation: 'none'
, dnt: true
, hide_thread: true
}
);
//tweet opacity to 0
twttr.events.bind('rendered', function (event) {
var opacity=0;
if (Net.sim_mode() == "explode"){
opacity=1;
}
d3.selectAll(".twitter-tweet").style("opacity",opacity)
})
}
)
/*
// donald image
g.insert("image",":first-child")
.attr("class","TheDonald count-title")
.attr("xlink:href","img/trump_point1.png")
.attr("x",width*0)
.attr("y",height*0.6)
.attr("width","200px")
*/
g.selectAll(".count-title")
.attr("opacity", 0);
// people title
g.append("text")
.attr("class", "title square highlight")
.attr("x", width / 2)
.attr("y", height / 2)
.text("300+")
.style("stroke","#444")
.style("stroke-width","0.4px");
g.append("text")
.attr("class", "sub-title square")
.attr("x", width / 2)
.attr("y", height / 1.4 + (height / 5) )
.text("Insultees");
g.selectAll(".square")
.attr("opacity", 0);
// histogram
// bar text & axis
g.append("g")
.attr("class","histogram xAxis1")
.attr("opacity",0)
.attr("transform","translate ("+0+"," + (Net.height_max()+45.0) + ")")
.call(d3.axisBottom(Net.xHistScale()));
g.append("g")
.attr("class","histogram xAxis2")
.attr("opacity",0)
.attr("transform","translate ("+0+"," + (Net.height_max()+5.0) + ")")
.call(d3.axisBottom(Net.xHistScale()));
// count openvis title
g.append("text")
.attr("class", "sub-title histogram_txt")
.attr("opacity",0)
.attr("x", width / 2)
.attr("y", height / 3 + (height / 5) )
.text("");
/*
g.append("text")
.attr("class", "title histogram_txt highlight")
.attr("opacity",0)
.attr("x", width / 2)
.attr("y", (height / 6) )
//.attr("stroke","white")
//.attr("text-shadow","2px 2px white:")
.text("");
g.append("text")
.attr("class", "title histogram_txt highlight")
.attr("opacity",0)
.attr("x", width / 2)
.attr("y", (height / 3) )
.text("Insult Count");
*/
var yHistAxis = d3.axisLeft(Net.yHistScale2())
.tickValues([1,5,10,15,20,25])
g.append("g")
.attr("class","histogram xAxis2")
.attr("opacity",0)
.attr("transform","translate ("+ 0 +"," + 0 + ")")
.call(yHistAxis);
// barchart
var bars = g.selectAll(".bar").data(fillerCounts);
bars.enter()
.append("div")
.attr("class", "bar")
var barText = g.selectAll(".bar-text").data(fillerCounts);
barText.enter()
.append("text")
.attr("class", "bar-text")
// histogram
var hist = g.selectAll(".hist").data(histData);
hist.enter().append("div")
.attr("class", "hist")
.attr("opacity", 0);
};
/**
* setupSections - each section is activated
* by a separate function. Here we associate
* these functions to the sections based on
* the section's index.
*
*/
setupSections = function() {
// activateFunctions are called each
// time the active section changes
activateFunctions[0] = showTitle;
activateFunctions[1] = showFillerTitle;
activateFunctions[2] = showGrid;
activateFunctions[3] = highlightGrid;
activateFunctions[4] = showBar;
activateFunctions[5] = showHistPart;
activateFunctions[6] = showHistAll;
activateFunctions[7] = showTweet;
activateFunctions[8] = showHistAll;
// updateFunctions are called while
// in a particular section to update
// the scroll progress in that section.
// Most sections do not need to be updated
// for all scrolling and so are set to
// no-op functions.
for(var i = 0; i < 9; i++) {
updateFunctions[i] = function() {};
}
updateFunctions[7] = updateCough;
};
/**
* ACTIVATE FUNCTIONS
*
* These will be called their
* section is scrolled to.
*
* General pattern is to ensure
* all content for the current section
* is transitioned in, while hiding
* the content for the previous section
* as well as the next section (as the
* user may be scrolling up or down).
*
*/
/**
* showTitle - initial title
*
* hides: count title
* (no previous step to hide)
* shows: intro title
*
*/
opacityZero = function(){
console.log("opacityZero()")
g.selectAll(".count-title")
.transition()
.duration(0)
.attr("opacity", 0);
g.selectAll(".openvis-title")
.transition()
.duration(0)
.attr("opacity", 0.0);
g.selectAll(".TheDonald")
.transition()
.duration(1000)
.attr("opacity", 0);
g.selectAll(".bar-text")
.transition()
.duration(0)
.attr("opacity", 0);
g.selectAll(".hbar")
.transition()
.duration(0)
.attr("opacity", 0);
g.selectAll(".hbar_breakout")
.transition()
.duration(0)
.attr("opacity", 0);
g.selectAll(".square")
.transition()
.duration(0)
.attr("opacity", 0)
g.selectAll(".fill-square")
.transition()
.duration(0)
.attr("opacity", 0);
g.selectAll(".xAxis1")
.transition()
.duration(0)
.attr("opacity", 0);
g.selectAll(".xAxis2")
.transition()
.duration(0)
.attr("opacity", 0);
g.selectAll(".hist")
.transition()
.duration(0)
.style("opacity", 0);
g.selectAll(".histogram_txt")
.transition()
.duration(0)
.style("opacity", 0);
d3.selectAll(".twitter-tweet").style("opacity",0)
}
function showTitle() {
Net.sim_mode("center")
opacityZero()
g.selectAll(".openvis-title")
.transition()
.duration(600)
.attr("opacity", 1.0);
g.selectAll(".TheDonald")
.transition()
.duration(3000)
.attr("opacity", 1);
}
/**
* showFillerTitle - filler counts
*
* hides: intro title
* hides: square grid
* shows: filler count title
*
*/
function showFillerTitle() {
opacityZero()
Net.sim_mode("explode")
d3.selectAll(".twitter-tweet")
.transition()
.duration(0)
.style("opacity",1)
}
/**
* showGrid - square grid
*
* hides: filler count title
* hides: filler highlight in grid
* shows: square grid
*
*/
function showGrid() {
opacityZero()
Net.sim_mode("expand")
g.selectAll(".count-title")
.transition()
.duration(600)
.attr("opacity", 1.0);
//.attr("fill", "#ddd");
}
/**
* highlightGrid - show fillers in grid
*
* hides: barchart, text and axis
* shows: square grid and highlighted
* filler words. also ensures squares
* are moved back to their place in the grid
*/
function highlightGrid() {
Net.sim_mode('grid')
opacityZero()
// use named transition to ensure
// move happens even if other
// transitions are interrupted.
g.selectAll(".square")
.transition()
.duration(600)
.attr("opacity", 1.0);
}
function showBar() {
// ensure the axis to histogram one
//showAxis(xAxisHist);
Net.sim_mode("hbar")
opacityZero()
g.selectAll(".hbar")
.transition()
.duration(600)
.attr("opacity", 1.0);
}
/**
* showHistPart - shows the first part
* of the histogram of filler words
*
* hides: barchart
* hides: last half of histogram
* shows: first half of histogram
*
*/
function showHistPart() {
Net.sim_mode("hbar_breakout")
// ensure bar axis is set
//showAxis(xAxisBar);
opacityZero()
g.selectAll(".hbar_breakout")
.transition()
.duration(600)
.attr("opacity", 1);
// switch the axis to histogram one
//Net.sim_mode("hist")
//Net.collision_factor(4)
//Net.sim_mode("set_collision")
}
function showHistAll() {
Net.sim_mode("hist")
opacityZero()
g.selectAll(".histogram.xAxis2")
.transition()
.duration(600)
.attr("opacity", 1);
g.selectAll(".histogram_txt")
.transition()
.duration(0)
.style("opacity", 1);
}
function showTweet() {
opacityZero()
Net.sim_mode("explode")
d3.selectAll(".twitter-tweet")
.transition()
.duration(0)
.style("opacity",1)
}
function showAxis(axis) {
opacityZero()
}
function hideAxis() {
opacityZero()
}
/**
* UPDATE FUNCTIONS
*
* These will be called within a section
* as the user scrolls through it.
*
* We use an immediate transition to
* update visual elements based on
* how far the user has scrolled
*
*/
/**
* updateCough - increase/decrease
* cough text and color
*
* @param progress - 0.0 - 1.0 -
* how far user has scrolled in section
*/
function updateCough(progress) {
//opacityZero()
}
/**
* DATA FUNCTIONS
*
* Used to coerce the data into the
* formats we need to visualize
*
*/
/**
* getWords - maps raw data to
* array of data objects. There is
* one data object for each word in the speach
* data.
*
* This function converts some attributes into
* numbers and adds attributes used in the visualization
*
* @param rawData - data read in from file
*/
function getWords(rawData) {
return rawData.map(function(d,i) {
// is this word a filler word?
d.filler = (d.filler === "1") ? true : false;
// time in seconds word was spoken
d.time = +d.time;
// time in minutes word was spoken
d.min = Math.floor(d.time / 60);
// positioning for square visual
// stored here to make it easier
// to keep track of.
d.col = i % numPerRow;
d.x = d.col * (squareSize + squarePad);
d.row = Math.floor(i / numPerRow);
d.y = d.row * (squareSize + squarePad);
return d;
});
}
/**
* getFillerWords - returns array of
* only filler words
*
* @param data - word data from getWords
*/
function getFillerWords(data) {
return data.filter(function(d) {return d.filler; });
}
/**
* getHistogram - use d3's histogram layout
* to generate histogram bins for our word data
*
* @param data - word data. we use filler words
* from getFillerWords
*/
function getHistogram(data) {
// only get words from the first 30 minutes
var thirtyMins = data.filter(function(d) { return d.min < 30; });
// bin data into 2 minutes chuncks
// from 0 - 31 minutes
return d3.histogram()
.value(function(d) { return d.min; })
//.bins(d3.range(0,31,2))
(thirtyMins);
}
/**
* groupByWord - group words together
* using nest. Used to get counts for
* barcharts.
*
* @param words
*/
function groupByWord(words) {
return d3.nest()
.key(function(d) { return d.word; })
.rollup(function(v) { return v.length; })
.entries(words)
.sort(function(a,b) {return b.values - a.values;});
}
/**
* activate -
*
* @param index - index of the activated section
*/
chart.activate = function(index) {
activeIndex = index;
var sign = (activeIndex - lastIndex) < 0 ? -1 : 1;
var scrolledSections = d3.range(lastIndex + sign, activeIndex + sign, sign);
scrolledSections.forEach(function(i) {
activateFunctions[i]();
});
lastIndex = activeIndex;
};
/**
* update
*
* @param index
* @param progress
*/
chart.update = function(index, progress) {
updateFunctions[index](progress);
};
// return chart function
return chart;
};
/**
* display - called once data
* has been loaded.
* sets up the scroller and
* displays the visualization.
*
* @param data - loaded tsv data
*/
function display(error,data,trumpVisData) {
// create a new plot and
// display it
//console.log(trumpVisData)
var plot = scrollVis(trumpVisData);
d3.select("#vis")
.datum(data)
.call(plot);
// setup scroll functionality
var scroll = scroller()
.container(d3.select('#graphic'));
// pass in .step selection as the steps
scroll(d3.selectAll('.step'));
// setup event handling
scroll.on('active', function(index) {
// highlight current step text
d3.selectAll('.step')
.style('opacity', function(d,i) { return i == index ? 1 : 0.1; });
// activate current section
plot.activate(index);
});
scroll.on('progress', function(index, progress){
plot.update(index, progress);
});
}
// load data and display
//d3.tsv("data/words.tsv", display);
var q = d3.queue();
q.defer(d3.tsv, 'data/words.tsv')
.defer(d3.json, "data/2017-01-27_full_insult_list.json")
.await(display);