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calc.js
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/**
* Copyright 2012-2017, Plotly, Inc.
* All rights reserved.
*
* This source code is licensed under the MIT license found in the
* LICENSE file in the root directory of this source tree.
*/
'use strict';
var isNumeric = require('fast-isnumeric');
var Lib = require('../../lib');
var Axes = require('../../plots/cartesian/axes');
var binFunctions = require('./bin_functions');
var normFunctions = require('./norm_functions');
var doAvg = require('./average');
var cleanBins = require('./clean_bins');
module.exports = function calc(gd, trace) {
// ignore as much processing as possible (and including in autorange) if bar is not visible
if(trace.visible !== true) return;
// depending on orientation, set position and size axes and data ranges
// note: this logic for choosing orientation is duplicated in graph_obj->setstyles
var pos = [],
size = [],
i,
pa = Axes.getFromId(gd,
trace.orientation === 'h' ? (trace.yaxis || 'y') : (trace.xaxis || 'x')),
maindata = trace.orientation === 'h' ? 'y' : 'x',
counterdata = {x: 'y', y: 'x'}[maindata],
calendar = trace[maindata + 'calendar'];
cleanBins(trace, pa, maindata);
// prepare the raw data
var pos0 = pa.makeCalcdata(trace, maindata);
// calculate the bins
var binAttr = maindata + 'bins',
binspec;
if((trace['autobin' + maindata] !== false) || !(binAttr in trace)) {
binspec = Axes.autoBin(pos0, pa, trace['nbins' + maindata], false, calendar);
// adjust for CDF edge cases
if(trace.cumulative && (trace.currentbin !== 'include')) {
if(trace.direction === 'decreasing') {
binspec.start = pa.c2r(pa.r2c(binspec.start) - binspec.size);
}
else {
binspec.end = pa.c2r(pa.r2c(binspec.end) + binspec.size);
}
}
// copy bin info back to the source and full data.
trace._input[binAttr] = trace[binAttr] = binspec;
}
else {
binspec = trace[binAttr];
}
var nonuniformBins = typeof binspec.size === 'string',
bins = nonuniformBins ? [] : binspec,
// make the empty bin array
i2,
binend,
n,
inc = [],
counts = [],
total = 0,
norm = trace.histnorm,
func = trace.histfunc,
densitynorm = norm.indexOf('density') !== -1,
extremefunc = func === 'max' || func === 'min',
sizeinit = extremefunc ? null : 0,
binfunc = binFunctions.count,
normfunc = normFunctions[norm],
doavg = false,
pr2c = function(v) { return pa.r2c(v, 0, calendar); },
rawCounterData;
if(Array.isArray(trace[counterdata]) && func !== 'count') {
rawCounterData = trace[counterdata];
doavg = func === 'avg';
binfunc = binFunctions[func];
}
// create the bins (and any extra arrays needed)
// assume more than 5000 bins is an error, so we don't crash the browser
i = pr2c(binspec.start);
// decrease end a little in case of rounding errors
binend = pr2c(binspec.end) + (i - Axes.tickIncrement(i, binspec.size, false, calendar)) / 1e6;
while(i < binend && pos.length < 5000) {
i2 = Axes.tickIncrement(i, binspec.size, false, calendar);
pos.push((i + i2) / 2);
size.push(sizeinit);
// nonuniform bins (like months) we need to search,
// rather than straight calculate the bin we're in
if(nonuniformBins) bins.push(i);
// nonuniform bins also need nonuniform normalization factors
if(densitynorm) inc.push(1 / (i2 - i));
if(doavg) counts.push(0);
i = i2;
}
// for date axes we need bin bounds to be calcdata. For nonuniform bins
// we already have this, but uniform with start/end/size they're still strings.
if(!nonuniformBins && pa.type === 'date') {
bins = {
start: pr2c(bins.start),
end: pr2c(bins.end),
size: bins.size
};
}
var nMax = size.length;
// bin the data
for(i = 0; i < pos0.length; i++) {
n = Lib.findBin(pos0[i], bins);
if(n >= 0 && n < nMax) total += binfunc(n, i, size, rawCounterData, counts);
}
// average and/or normalize the data, if needed
if(doavg) total = doAvg(size, counts);
if(normfunc) normfunc(size, total, inc);
// after all normalization etc, now we can accumulate if desired
if(trace.cumulative) cdf(size, trace.direction, trace.currentbin);
var serieslen = Math.min(pos.length, size.length),
cd = [],
firstNonzero = 0,
lastNonzero = serieslen - 1;
// look for empty bins at the ends to remove, so autoscale omits them
for(i = 0; i < serieslen; i++) {
if(size[i]) {
firstNonzero = i;
break;
}
}
for(i = serieslen - 1; i > firstNonzero; i--) {
if(size[i]) {
lastNonzero = i;
break;
}
}
// create the "calculated data" to plot
for(i = firstNonzero; i <= lastNonzero; i++) {
if((isNumeric(pos[i]) && isNumeric(size[i]))) {
cd.push({p: pos[i], s: size[i], b: 0});
}
}
return cd;
};
function cdf(size, direction, currentbin) {
var i,
vi,
prevSum;
function firstHalfPoint(i) {
prevSum = size[i];
size[i] /= 2;
}
function nextHalfPoint(i) {
vi = size[i];
size[i] = prevSum + vi / 2;
prevSum += vi;
}
if(currentbin === 'half') {
if(direction === 'increasing') {
firstHalfPoint(0);
for(i = 1; i < size.length; i++) {
nextHalfPoint(i);
}
}
else {
firstHalfPoint(size.length - 1);
for(i = size.length - 2; i >= 0; i--) {
nextHalfPoint(i);
}
}
}
else if(direction === 'increasing') {
for(i = 1; i < size.length; i++) {
size[i] += size[i - 1];
}
// 'exclude' is identical to 'include' just shifted one bin over
if(currentbin === 'exclude') {
size.unshift(0);
size.pop();
}
}
else {
for(i = size.length - 2; i >= 0; i--) {
size[i] += size[i + 1];
}
if(currentbin === 'exclude') {
size.push(0);
size.shift();
}
}
}