Merge pull request #6223 from prabhathc/feature/geomean

feature(geomean): add geomean function

draftlogs/6223_add.md

@@ -0,0 +1,2 @@
+ - Add geometric mean functionality and 'geometric mean ascending' + 'geometric mean descending' to `category_order` on cartesian axes [[#6223](https://github.com/plotly/plotly.js/pull/6223)]
+   with thanks to @acxz and @prabhathc for the contribution!

src/lib/index.js

@@ -115,6 +115,7 @@ var statsModule = require('./stats');
 lib.aggNums = statsModule.aggNums;
 lib.len = statsModule.len;
 lib.mean = statsModule.mean;
+lib.geometricMean = statsModule.geometricMean;
 lib.median = statsModule.median;
 lib.midRange = statsModule.midRange;
 lib.variance = statsModule.variance;

src/lib/stats.js

@@ -47,6 +47,11 @@ exports.mean = function(data, len) {
     return exports.aggNums(function(a, b) { return a + b; }, 0, data) / len;
 };
 
+exports.geometricMean = function(data, len) {
+    if(!len) len = exports.len(data);
+    return Math.pow(exports.aggNums(function(a, b) { return a * b; }, 1, data), 1 / len);
+};
+
 exports.midRange = function(numArr) {
     if(numArr === undefined || numArr.length === 0) return undefined;
     return (exports.aggNums(Math.max, null, numArr) + exports.aggNums(Math.min, null, numArr)) / 2;

src/plots/cartesian/layout_attributes.js

@@ -1202,6 +1202,7 @@ module.exports = {
             'max ascending', 'max descending',
             'sum ascending', 'sum descending',
             'mean ascending', 'mean descending',
+            'geometric mean ascending', 'geometric mean descending',
             'median ascending', 'median descending'
         ],
         dflt: 'trace',
@@ -1216,7 +1217,7 @@ module.exports = {
             'the *trace* mode. The unspecified categories will follow the categories in `categoryarray`.',
             'Set `categoryorder` to *total ascending* or *total descending* if order should be determined by the',
             'numerical order of the values.',
-            'Similarly, the order can be determined by the min, max, sum, mean or median of all the values.'
+            'Similarly, the order can be determined by the min, max, sum, mean, geometric mean or median of all the values.'
         ].join(' ')
     },
     categoryarray: {

src/plots/plots.js

@@ -3188,7 +3188,7 @@ plots.doCalcdata = function(gd, traces) {
     Registry.getComponentMethod('errorbars', 'calc')(gd);
 };
 
-var sortAxisCategoriesByValueRegex = /(total|sum|min|max|mean|median) (ascending|descending)/;
+var sortAxisCategoriesByValueRegex = /(total|sum|min|max|mean|geometric mean|median) (ascending|descending)/;
 
 function sortAxisCategoriesByValue(axList, gd) {
     var affectedTraces = [];
@@ -3223,6 +3223,7 @@ function sortAxisCategoriesByValue(axList, gd) {
         sum: function(values) {return Lib.aggNums(function(a, b) { return a + b;}, null, values);},
         total: function(values) {return Lib.aggNums(function(a, b) { return a + b;}, null, values);},
         mean: function(values) {return Lib.mean(values);},
+        'geometric mean': function(values) {return Lib.geometricMean(values);},
         median: function(values) {return Lib.median(values);}
     };
 

test/jasmine/tests/calcdata_test.js

@@ -1160,6 +1160,25 @@ describe('calculated data and points', function() {
                         checkAggregatedValue(baseMock, expectedAgg, false, done);
                     });
 
+                    it('takes the geometric mean of all values per category across traces of type ' + trace.type, function(done) {
+                        if(trace.type === 'ohlc' || trace.type === 'candlestick') return done();
+
+                        var type = trace.type;
+                        var data = [7, 2, 3];
+                        var data2 = [5, 4, 2];
+                        var baseMock = { data: [makeData(type, axName, cat, data), makeData(type, axName, cat, data2)], layout: {}};
+                        baseMock.layout[axName] = { type: 'category', categoryorder: 'geometric mean ascending'};
+
+                        var expectedAgg = [['a', Math.sqrt(data[0] * data2[0])], ['b', Math.sqrt(data[1] * data2[1])], ['c', Math.sqrt(data[2] * data2[2])]];
+                        // TODO: how to actually calc these? what do these even mean?
+                        if(type === 'histogram') expectedAgg = [['a', 2], ['b', 1], ['c', 1]];
+                        if(type === 'histogram2d') expectedAgg = [['a', 0], ['b', 0], ['c', 0]];
+                        if(type === 'contour' || type === 'heatmap') expectedAgg = [['a', 0], ['b', 0], ['c', 0]];
+                        if(type === 'histogram2dcontour') expectedAgg = [['a', 0], ['b', 0], ['c', 0]];
+
+                        checkAggregatedValue(baseMock, expectedAgg, false, done);
+                    });
+
                     it('takes the median of all values per category across traces of type ' + trace.type, function(done) {
                         var type = trace.type;
                         var data = [7, 2, 3];

test/jasmine/tests/lib_test.js

@@ -126,6 +126,24 @@ describe('Test lib.js:', function() {
         });
     });
 
+    describe('geometricMean() should', function() {
+        it('toss out non-numerics (strings)', function() {
+            var input = [1, 2, 'apple', 'orange'];
+            var res = Lib.geometricMean(input);
+            expect(res).toBeCloseTo(1.414, 3);
+        });
+        it('toss out non-numerics (NaN)', function() {
+            var input = [1, 2, NaN];
+            var res = Lib.geometricMean(input);
+            expect(res).toBeCloseTo(1.414, 3);
+        });
+        it('evaluate numbers which are passed around as text strings:', function() {
+            var input = ['1', '2'];
+            var res = Lib.geometricMean(input);
+            expect(res).toBeCloseTo(1.414, 3);
+        });
+    });
+
     describe('midRange() should', function() {
         it('should calculate the arithmetic mean of the maximum and minimum value of a given array', function() {
             var input = [1, 5.5, 6, 15, 10, 13];