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galaxy/config/plugins/visualizations/scatterplot/static/numeric-column-stats.js
T

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3.0 KiB
JavaScript

var numericColumnStats = function( data, keys ){
var console = console || { debug: function(){} },
stats = {};
// precondition: keys is an array of keys accessible on each data in data
if( !keys || !keys.length ){
throw new Error( 'keys is a required parameter and must be an array:' + keys );
}
if( !data || !data.length ){
return stats;
}
function parseVal( val ){
if( val === null ){
throw new Error( 'Null value' );
}
val = Number( val );
if( isNaN( val ) || !isFinite( val ) ){
throw new Error( 'NaN or non-finite number' );
}
return val;
}
// does this effect the data in the other thread?
[ 'min', 'max', 'sum', 'mean', 'median', 'count' ].forEach( function( name, i ){
stats[ name ] = new Array( keys.length );
});
var keyIndex = 0,
separatedCols = new Array( keys.length );
keys.forEach( function( key, keyIndex ){
stats.min[ keyIndex ] = 0;
stats.max[ keyIndex ] = 0;
stats.sum[ keyIndex ] = 0;
separatedCols[ keyIndex ] = [];
});
// work backwards to prevent co-modification problems while splitting up data into columns
for( var dataIndex=( data.length - 1 ); dataIndex>=0; dataIndex-=1 ){
var datum = data.pop( dataIndex );
for( keyIndex=0; keyIndex<keys.length; keyIndex+=1 ){
var key = keys[ keyIndex ],
datumColVal = datum[ key ];
try {
//NOTE: parsing value as number
datumColVal = parseVal( datumColVal );
} catch( e ){
continue;
}
// separate the columns
separatedCols[ keyIndex ].unshift( datumColVal );
// get the other stats
stats.min[ keyIndex ] = Math.min( stats.min[ keyIndex ], datumColVal );
stats.max[ keyIndex ] = Math.max( stats.max[ keyIndex ], datumColVal );
stats.sum[ keyIndex ] += datumColVal;
}
}
// get counts, mean, median
function comparator( a, b ){
if( a < b ){ return -1; }
if( a < b ){ return 1; }
return 0;
}
for( keyIndex=0; keyIndex<keys.length; keyIndex+=1 ){
var count = separatedCols[ keyIndex ].length,
sum = stats.sum[ keyIndex ];
stats.count[ keyIndex ] = count;
stats.mean[ keyIndex ] = ( sum / count );
// sort columns for median
separatedCols[ keyIndex ].sort( comparator );
// odd count -> straight forward median
var middleDataIndex = Math.floor( count / 2 );
if( count % 2 === 1 ){
stats.median[ keyIndex ] = separatedCols[ keyIndex ][ middleDataIndex ];
} else {
var middleValA = separatedCols[ keyIndex ][ middleDataIndex ],
middleValB = separatedCols[ keyIndex ][( middleDataIndex + 1 )];
stats.median[ keyIndex ] = ( middleValA + middleValB ) / 2;
}
}
return stats;
};