clustergrammer
Version:
This is a clustergram implemented in D3.js. I started from the example http://bost.ocks.org/mike/miserables/ and added the following features
53 lines (41 loc) • 1.28 kB
JavaScript
var get_filter_default_state = require('./get_filter_default_state');
module.exports = function make_filter_title(params, filter_type){
var filter_title = {};
var title = {};
var type = {};
filter_title.state = get_filter_default_state(params.viz.filter_data, filter_type);
type.top = filter_type.split('_')[0];
type.node = filter_type.split('_')[1];
type.measure = filter_type.split('_')[2];
if (type.node === 'row'){
title.node = 'rows';
} else {
title.node = 'columns';
}
if (type.top === 'N'){
// filter_title.suffix = ' '+title.node;
filter_title.suffix = '';
}
if (type.top === 'pct'){
filter_title.suffix = '%';
}
if (type.measure == 'sum'){
title.measure = 'sum';
} else if (type.measure == 'var'){
title.measure = 'variance';
}
if (type.measure === 'sum'){
filter_title.text = 'Top '+ title.node + ' ' + title.measure+': ';
}
if (type.measure === 'var'){
filter_title.text = 'Top '+ title.node + ' ' + title.measure+': ';
}
// Enrichr specific rules
if ( _.keys(params.viz.possible_filters).indexOf('enr_score_type') > -1 ){
if (type.node === 'col'){
filter_title.text = 'Top Enriched Terms: ';
filter_title.suffix = '';
}
}
return filter_title;
};