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Duck Similarity (Galileo)
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svg = d3.select('svg') | |
width = svg.node().getBoundingClientRect().width | |
height = svg.node().getBoundingClientRect().height | |
simcolor = d3.scale.linear() | |
.domain([0,1]) | |
.range([d3.hcl(20,0,100),d3.hcl(20,75,25)]) | |
.interpolate(d3.interpolateHcl) | |
matrix = svg.append('g') | |
.attr('transform', 'translate(360,140)') | |
SIZE = 13 | |
d3.json '//wafi.iit.cnr.it/webvis/tmp/dbpedia/galileo_matrix.json', (data) -> | |
index = {} | |
items = [] | |
data.forEach (e1) -> | |
items.push e1.k1 | |
index[e1.k1] = {} | |
e1.similarities.forEach (e2) -> | |
index[e1.k1][e2.k2] = e2.sim | |
console.debug 'Computing hierarchical clustering...' | |
clusters = clusterfck.hcluster( | |
items, | |
(a,b) -> 1-index[a][b], | |
clusterfck.SINGLE_LINKAGE | |
) | |
tree = tree_utils.binary_to_std(clusters) | |
sequence = tree_utils.get_leaves(tree).map (d) -> d.value | |
matrix_data = [] | |
sequence.forEach (k1) -> | |
e1 = {k1: k1, similarities: []} | |
matrix_data.push e1 | |
sequence.forEach (k2) -> | |
e1.similarities.push {k2: k2, sim: index[k1][k2]} | |
rows = matrix.selectAll('.row') | |
.data(matrix_data) | |
enter_rows = rows.enter().append('g') | |
.attr('class', 'row') | |
.attr('transform', (d,i) -> "translate(0,#{SIZE*i})") | |
cells = rows.selectAll('.cell') | |
.data((row) -> row.similarities) | |
cells.enter().append('rect') | |
.attr('class', 'cell') | |
.attr('width', SIZE) | |
.attr('height', SIZE) | |
.attr('transform', (d, i) -> "translate(#{SIZE*i},0)") | |
.attr('fill', (d) -> simcolor(d.sim)) | |
.append('title') | |
.text((d) -> | |
k1 = d3.select(this.parentNode.parentNode).datum().k1.replace('http://dbpedia.org/resource/','') | |
k2 = d.k2.replace('http://dbpedia.org/resource/','') | |
return "#{k1}\n [#{d3.format('%')(d.sim)}]\n#{k2}" | |
) | |
matrix.append('rect') | |
.attr('class','border') | |
.attr('x', -1) | |
.attr('y', -1) | |
.attr('width', SIZE*matrix_data.length+2) | |
.attr('height', SIZE*matrix_data.length+2) | |
hlabels = matrix.selectAll('.hlabel') | |
.data(matrix_data) | |
hlabels.enter().append('a') | |
.attr('xlink:href', (d) -> d.k1) | |
.append('text') | |
.attr('class','hlabel') | |
.text((d) -> d.k1.replace('http://dbpedia.org/resource/','')) | |
.attr('transform', (d,i) -> "translate(0,#{SIZE*i})") | |
.attr('dy', '1em') | |
.attr('dx', -6) | |
.classed('highlighted', (d) -> d.k1 is 'http://dbpedia.org/resource/Galileo_Galilei') | |
vlabels = matrix.selectAll('.vlabel') | |
.data(matrix_data) | |
vlabels.enter().append('a') | |
.attr('xlink:href', (d) -> d.k1) | |
.append('text') | |
.attr('class','vlabel') | |
.text((d) -> d.k1.replace('http://dbpedia.org/resource/','')) | |
.attr('transform', (d,i) -> "translate(#{SIZE*i},0) rotate(-90)") | |
.attr('dy', '1em') | |
.attr('dx', 6) | |
.classed('highlighted', (d) -> d.k1 is 'http://dbpedia.org/resource/Galileo_Galilei') | |
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svg { | |
background: white; | |
} | |
.border { | |
stroke-width: 1; | |
stroke: #CCC; | |
fill: none; | |
shape-rendering: crispEdges; | |
} | |
.cell { | |
stroke-width: 1; | |
stroke: white; | |
shape-rendering: crispEdges; | |
} | |
.hlabel, .vlabel { | |
fill: #333; | |
font-family: sans-serif; | |
font-size: 10px; | |
} | |
.hlabel { | |
text-anchor: end; | |
} | |
.vlabel { | |
text-anchor: start; | |
} | |
.highlighted { | |
font-weight: bold; | |
fill: black; | |
} | |
.hlabel:hover, .vlabel:hover { | |
fill: red; | |
} |
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<!DOCTYPE html> | |
<html> | |
<head> | |
<meta charset="utf-8"> | |
<meta name="description" content="Duck Similarity (Galileo)" /> | |
<title>Duck Similarity (Galileo)</title> | |
<link type="text/css" href="index.css" rel="stylesheet"/> | |
<script src="http://d3js.org/d3.v3.min.js"></script> | |
<script src="//wafi.iit.cnr.it/webvis/tmp/clusterfck.js"></script> | |
<script src="//wafi.iit.cnr.it/webvis/libs/jigmaps/zip.js"></script> | |
<script src="//wafi.iit.cnr.it/webvis/libs/jigmaps/tree_utils.js"></script> | |
</head> | |
<body> | |
<svg height="500" width="960"></svg> | |
<script src="index.js"></script> | |
</body> | |
</html> |
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(function() { | |
var SIZE, height, matrix, simcolor, svg, width; | |
svg = d3.select('svg'); | |
width = svg.node().getBoundingClientRect().width; | |
height = svg.node().getBoundingClientRect().height; | |
simcolor = d3.scale.linear().domain([0, 1]).range([d3.hcl(20, 0, 100), d3.hcl(20, 75, 25)]).interpolate(d3.interpolateHcl); | |
matrix = svg.append('g').attr('transform', 'translate(360,140)'); | |
SIZE = 13; | |
d3.json('//wafi.iit.cnr.it/webvis/tmp/dbpedia/galileo_matrix.json', function(data) { | |
var cells, clusters, enter_rows, hlabels, index, items, matrix_data, rows, sequence, tree, vlabels; | |
index = {}; | |
items = []; | |
data.forEach(function(e1) { | |
items.push(e1.k1); | |
index[e1.k1] = {}; | |
return e1.similarities.forEach(function(e2) { | |
return index[e1.k1][e2.k2] = e2.sim; | |
}); | |
}); | |
console.debug('Computing hierarchical clustering...'); | |
clusters = clusterfck.hcluster(items, function(a, b) { | |
return 1 - index[a][b]; | |
}, clusterfck.SINGLE_LINKAGE); | |
tree = tree_utils.binary_to_std(clusters); | |
sequence = tree_utils.get_leaves(tree).map(function(d) { | |
return d.value; | |
}); | |
matrix_data = []; | |
sequence.forEach(function(k1) { | |
var e1; | |
e1 = { | |
k1: k1, | |
similarities: [] | |
}; | |
matrix_data.push(e1); | |
return sequence.forEach(function(k2) { | |
return e1.similarities.push({ | |
k2: k2, | |
sim: index[k1][k2] | |
}); | |
}); | |
}); | |
rows = matrix.selectAll('.row').data(matrix_data); | |
enter_rows = rows.enter().append('g').attr('class', 'row').attr('transform', function(d, i) { | |
return "translate(0," + (SIZE * i) + ")"; | |
}); | |
cells = rows.selectAll('.cell').data(function(row) { | |
return row.similarities; | |
}); | |
cells.enter().append('rect').attr('class', 'cell').attr('width', SIZE).attr('height', SIZE).attr('transform', function(d, i) { | |
return "translate(" + (SIZE * i) + ",0)"; | |
}).attr('fill', function(d) { | |
return simcolor(d.sim); | |
}).append('title').text(function(d) { | |
var k1, k2; | |
k1 = d3.select(this.parentNode.parentNode).datum().k1.replace('http://dbpedia.org/resource/', ''); | |
k2 = d.k2.replace('http://dbpedia.org/resource/', ''); | |
return "" + k1 + "\n [" + (d3.format('%')(d.sim)) + "]\n" + k2; | |
}); | |
matrix.append('rect').attr('class', 'border').attr('x', -1).attr('y', -1).attr('width', SIZE * matrix_data.length + 2).attr('height', SIZE * matrix_data.length + 2); | |
hlabels = matrix.selectAll('.hlabel').data(matrix_data); | |
hlabels.enter().append('a').attr('xlink:href', function(d) { | |
return d.k1; | |
}).append('text').attr('class', 'hlabel').text(function(d) { | |
return d.k1.replace('http://dbpedia.org/resource/', ''); | |
}).attr('transform', function(d, i) { | |
return "translate(0," + (SIZE * i) + ")"; | |
}).attr('dy', '1em').attr('dx', -6).classed('highlighted', function(d) { | |
return d.k1 === 'http://dbpedia.org/resource/Galileo_Galilei'; | |
}); | |
vlabels = matrix.selectAll('.vlabel').data(matrix_data); | |
return vlabels.enter().append('a').attr('xlink:href', function(d) { | |
return d.k1; | |
}).append('text').attr('class', 'vlabel').text(function(d) { | |
return d.k1.replace('http://dbpedia.org/resource/', ''); | |
}).attr('transform', function(d, i) { | |
return "translate(" + (SIZE * i) + ",0) rotate(-90)"; | |
}).attr('dy', '1em').attr('dx', 6).classed('highlighted', function(d) { | |
return d.k1 === 'http://dbpedia.org/resource/Galileo_Galilei'; | |
}); | |
}); | |
}).call(this); |
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