/*! * Chart.js * http://chartjs.org/ * * Copyright 2017 Nick Downie * Released under the MIT license * https://github.com/chartjs/Chart.js/blob/master/LICENSE.md */ !function(t){if("object"==typeof exports&&"undefined"!=typeof module)module.exports=t();else if("function"==typeof define&&define.amd)define([],t);else{("undefined"!=typeof window?window:"undefined"!=typeof global?global:"undefined"!=typeof self?self:this).Chart=t()}}(function(){return function t(e,n,i){function a(r,l){if(!n[r]){if(!e[r]){var s="function"==typeof require&&require;if(!l&&s)return s(r,!0);if(o)return o(r,!0);var u=new Error("Cannot find module '"+r+"'");throw u.code="MODULE_NOT_FOUND",u}var d=n[r]={exports:{}};e[r][0].call(d.exports,function(t){var n=e[r][1][t];return a(n||t)},d,d.exports,t,e,n,i)}return n[r].exports}for(var o="function"==typeof require&&require,r=0;rn?(e+.05)/(n+.05):(n+.05)/(e+.05)},level:function(t){var e=this.contrast(t);return e>=7.1?"AAA":e>=4.5?"AA":""},dark:function(){var 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e=Math.atan2(r,o),(n=360*e/2/Math.PI)<0&&(n+=360),i=Math.sqrt(o*o+r*r),[a,i,n]}function k(t){return v(x(t))}function w(t){var e,n,i,a=t[0],o=t[1];return i=t[2]/360*2*Math.PI,e=o*Math.cos(i),n=o*Math.sin(i),[a,e,n]}function M(t){return S[t]}e.exports={rgb2hsl:i,rgb2hsv:a,rgb2hwb:o,rgb2cmyk:l,rgb2keyword:s,rgb2xyz:u,rgb2lab:d,rgb2lch:function(t){return y(d(t))},hsl2rgb:c,hsl2hsv:function(t){var e,n,i=t[0],a=t[1]/100,o=t[2]/100;return 0===o?[0,0,0]:(o*=2,a*=o<=1?o:2-o,n=(o+a)/2,e=2*a/(o+a),[i,100*e,100*n])},hsl2hwb:function(t){return o(c(t))},hsl2cmyk:function(t){return l(c(t))},hsl2keyword:function(t){return s(c(t))},hsv2rgb:h,hsv2hsl:function(t){var e,n,i=t[0],a=t[1]/100,o=t[2]/100;return n=(2-a)*o,e=a*o,e/=n<=1?n:2-n,e=e||0,n/=2,[i,100*e,100*n]},hsv2hwb:function(t){return o(h(t))},hsv2cmyk:function(t){return l(h(t))},hsv2keyword:function(t){return s(h(t))},hwb2rgb:f,hwb2hsl:function(t){return i(f(t))},hwb2hsv:function(t){return a(f(t))},hwb2cmyk:function(t){return 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o.each(n.data,function(n,a){t=e.data[a],isNaN(t)||n.hidden||(i+=Math.abs(t))}),i},calculateCircumference:function(t){var e=this.getMeta().total;return e>0&&!isNaN(t)?2*Math.PI*(t/e):0},getMaxBorderWidth:function(t){for(var e,n,i=0,a=this.index,o=t.length,r=0;r(i=e>i?e:i)?n:i;return i}})}},{25:25,40:40,45:45}],18:[function(t,e,n){"use strict";var i=t(25),a=t(40),o=t(45);i._set("line",{showLines:!0,spanGaps:!1,hover:{mode:"label"},scales:{xAxes:[{type:"category",id:"x-axis-0"}],yAxes:[{type:"linear",id:"y-axis-0"}]}}),e.exports=function(t){function e(t,e){return o.valueOrDefault(t.showLine,e.showLines)}t.controllers.line=t.DatasetController.extend({datasetElementType:a.Line,dataElementType:a.Point,update:function(t){var n,i,a,r=this,l=r.getMeta(),s=l.dataset,u=l.data||[],d=r.chart.options,c=d.elements.line,h=r.getScaleForId(l.yAxisID),f=r.getDataset(),g=e(f,d);for(g&&(a=s.custom||{},void 0!==f.tension&&void 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0!==f.fill?f.fill:c.fill,steppedLine:a.steppedLine?a.steppedLine:o.valueOrDefault(f.steppedLine,c.stepped),cubicInterpolationMode:a.cubicInterpolationMode?a.cubicInterpolationMode:o.valueOrDefault(f.cubicInterpolationMode,c.cubicInterpolationMode)},s.pivot()),n=0,i=u.length;n');var n=t.data,i=n.datasets,a=n.labels;if(i.length)for(var o=0;o'),a[o]&&e.push(a[o]),e.push("");return e.push(""),e.join("")},legend:{labels:{generateLabels:function(t){var e=t.data;return e.labels.length&&e.datasets.length?e.labels.map(function(n,i){var a=t.getDatasetMeta(0),r=e.datasets[0],l=a.data[i].custom||{},s=o.valueAtIndexOrDefault,u=t.options.elements.arc;return{text:n,fillStyle:l.backgroundColor?l.backgroundColor:s(r.backgroundColor,i,u.backgroundColor),strokeStyle:l.borderColor?l.borderColor:s(r.borderColor,i,u.borderColor),lineWidth:l.borderWidth?l.borderWidth:s(r.borderWidth,i,u.borderWidth),hidden:isNaN(r.data[i])||a.data[i].hidden,index:i}}):[]}},onClick:function(t,e){var n,i,a,o=e.index,r=this.chart;for(n=0,i=(r.data.datasets||[]).length;n0&&!isNaN(t)?2*Math.PI/e:0}})}},{25:25,40:40,45:45}],20:[function(t,e,n){"use strict";var i=t(25),a=t(40),o=t(45);i._set("radar",{scale:{type:"radialLinear"},elements:{line:{tension:0}}}),e.exports=function(t){t.controllers.radar=t.DatasetController.extend({datasetElementType:a.Line,dataElementType:a.Point,linkScales:o.noop,update:function(t){var e=this,n=e.getMeta(),i=n.dataset,a=n.data,r=i.custom||{},l=e.getDataset(),s=e.chart.options.elements.line,u=e.chart.scale;void 0!==l.tension&&void 0===l.lineTension&&(l.lineTension=l.tension),o.extend(n.dataset,{_datasetIndex:e.index,_scale:u,_children:a,_loop:!0,_model:{tension:r.tension?r.tension:o.valueOrDefault(l.lineTension,s.tension),backgroundColor:r.backgroundColor?r.backgroundColor:l.backgroundColor||s.backgroundColor,borderWidth:r.borderWidth?r.borderWidth:l.borderWidth||s.borderWidth,borderColor:r.borderColor?r.borderColor:l.borderColor||s.borderColor,fill:r.fill?r.fill:void 0!==l.fill?l.fill:s.fill,borderCapStyle:r.borderCapStyle?r.borderCapStyle:l.borderCapStyle||s.borderCapStyle,borderDash:r.borderDash?r.borderDash:l.borderDash||s.borderDash,borderDashOffset:r.borderDashOffset?r.borderDashOffset:l.borderDashOffset||s.borderDashOffset,borderJoinStyle:r.borderJoinStyle?r.borderJoinStyle:l.borderJoinStyle||s.borderJoinStyle}}),n.dataset.pivot(),o.each(a,function(n,i){e.updateElement(n,i,t)},e),e.updateBezierControlPoints()},updateElement:function(t,e,n){var i=this,a=t.custom||{},r=i.getDataset(),l=i.chart.scale,s=i.chart.options.elements.point,u=l.getPointPositionForValue(e,r.data[e]);void 0!==r.radius&&void 0===r.pointRadius&&(r.pointRadius=r.radius),void 0!==r.hitRadius&&void 0===r.pointHitRadius&&(r.pointHitRadius=r.hitRadius),o.extend(t,{_datasetIndex:i.index,_index:e,_scale:l,_model:{x:n?l.xCenter:u.x,y:n?l.yCenter:u.y,tension:a.tension?a.tension:o.valueOrDefault(r.lineTension,i.chart.options.elements.line.tension),radius:a.radius?a.radius:o.valueAtIndexOrDefault(r.pointRadius,e,s.radius),backgroundColor:a.backgroundColor?a.backgroundColor:o.valueAtIndexOrDefault(r.pointBackgroundColor,e,s.backgroundColor),borderColor:a.borderColor?a.borderColor:o.valueAtIndexOrDefault(r.pointBorderColor,e,s.borderColor),borderWidth:a.borderWidth?a.borderWidth:o.valueAtIndexOrDefault(r.pointBorderWidth,e,s.borderWidth),pointStyle:a.pointStyle?a.pointStyle:o.valueAtIndexOrDefault(r.pointStyle,e,s.pointStyle),hitRadius:a.hitRadius?a.hitRadius:o.valueAtIndexOrDefault(r.pointHitRadius,e,s.hitRadius)}}),t._model.skip=a.skip?a.skip:isNaN(t._model.x)||isNaN(t._model.y)},updateBezierControlPoints:function(){var t=this.chart.chartArea,e=this.getMeta();o.each(e.data,function(n,i){var a=n._model,r=o.splineCurve(o.previousItem(e.data,i,!0)._model,a,o.nextItem(e.data,i,!0)._model,a.tension);a.controlPointPreviousX=Math.max(Math.min(r.previous.x,t.right),t.left),a.controlPointPreviousY=Math.max(Math.min(r.previous.y,t.bottom),t.top),a.controlPointNextX=Math.max(Math.min(r.next.x,t.right),t.left),a.controlPointNextY=Math.max(Math.min(r.next.y,t.bottom),t.top),n.pivot()})},setHoverStyle:function(t){var e=this.chart.data.datasets[t._datasetIndex],n=t.custom||{},i=t._index,a=t._model;a.radius=n.hoverRadius?n.hoverRadius:o.valueAtIndexOrDefault(e.pointHoverRadius,i,this.chart.options.elements.point.hoverRadius),a.backgroundColor=n.hoverBackgroundColor?n.hoverBackgroundColor:o.valueAtIndexOrDefault(e.pointHoverBackgroundColor,i,o.getHoverColor(a.backgroundColor)),a.borderColor=n.hoverBorderColor?n.hoverBorderColor:o.valueAtIndexOrDefault(e.pointHoverBorderColor,i,o.getHoverColor(a.borderColor)),a.borderWidth=n.hoverBorderWidth?n.hoverBorderWidth:o.valueAtIndexOrDefault(e.pointHoverBorderWidth,i,a.borderWidth)},removeHoverStyle:function(t){var e=this.chart.data.datasets[t._datasetIndex],n=t.custom||{},i=t._index,a=t._model,r=this.chart.options.elements.point;a.radius=n.radius?n.radius:o.valueAtIndexOrDefault(e.pointRadius,i,r.radius),a.backgroundColor=n.backgroundColor?n.backgroundColor:o.valueAtIndexOrDefault(e.pointBackgroundColor,i,r.backgroundColor),a.borderColor=n.borderColor?n.borderColor:o.valueAtIndexOrDefault(e.pointBorderColor,i,r.borderColor),a.borderWidth=n.borderWidth?n.borderWidth:o.valueAtIndexOrDefault(e.pointBorderWidth,i,r.borderWidth)}})}},{25:25,40:40,45:45}],21:[function(t,e,n){"use strict";t(25)._set("scatter",{hover:{mode:"single"},scales:{xAxes:[{id:"x-axis-1",type:"linear",position:"bottom"}],yAxes:[{id:"y-axis-1",type:"linear",position:"left"}]},showLines:!1,tooltips:{callbacks:{title:function(){return""},label:function(t){return"("+t.xLabel+", "+t.yLabel+")"}}}}),e.exports=function(t){t.controllers.scatter=t.controllers.line}},{25:25}],22:[function(t,e,n){"use strict";var i=t(25),a=t(26),o=t(45);i._set("global",{animation:{duration:1e3,easing:"easeOutQuart",onProgress:o.noop,onComplete:o.noop}}),e.exports=function(t){t.Animation=a.extend({chart:null,currentStep:0,numSteps:60,easing:"",render:null,onAnimationProgress:null,onAnimationComplete:null}),t.animationService={frameDuration:17,animations:[],dropFrames:0,request:null,addAnimation:function(t,e,n,i){var a,o,r=this.animations;for(e.chart=t,i||(t.animating=!0),a=0,o=r.length;a1&&(n=Math.floor(t.dropFrames),t.dropFrames=t.dropFrames%1),t.advance(1+n);var i=Date.now();t.dropFrames+=(i-e)/t.frameDuration,t.animations.length>0&&t.requestAnimationFrame()},advance:function(t){for(var e,n,i=this.animations,a=0;a=e.numSteps?(o.callback(e.onAnimationComplete,[e],n),n.animating=!1,i.splice(a,1)):++a}},Object.defineProperty(t.Animation.prototype,"animationObject",{get:function(){return this}}),Object.defineProperty(t.Animation.prototype,"chartInstance",{get:function(){return this.chart},set:function(t){this.chart=t}})}},{25:25,26:26,45:45}],23:[function(t,e,n){"use strict";var i=t(25),a=t(45),o=t(28),r=t(48);e.exports=function(t){function e(t){var e=(t=t||{}).data=t.data||{};return e.datasets=e.datasets||[],e.labels=e.labels||[],t.options=a.configMerge(i.global,i[t.type],t.options||{}),t}function n(t){var e=t.options;e.scale?t.scale.options=e.scale:e.scales&&e.scales.xAxes.concat(e.scales.yAxes).forEach(function(e){t.scales[e.id].options=e}),t.tooltip._options=e.tooltips}function l(t){return"top"===t||"bottom"===t}var s=t.plugins;t.types={},t.instances={},t.controllers={},a.extend(t.prototype,{construct:function(n,i){var o=this;i=e(i);var l=r.acquireContext(n,i),s=l&&l.canvas,u=s&&s.height,d=s&&s.width;o.id=a.uid(),o.ctx=l,o.canvas=s,o.config=i,o.width=d,o.height=u,o.aspectRatio=u?d/u:null,o.options=i.options,o._bufferedRender=!1,o.chart=o,o.controller=o,t.instances[o.id]=o,Object.defineProperty(o,"data",{get:function(){return o.config.data},set:function(t){o.config.data=t}}),l&&s?(o.initialize(),o.update()):console.error("Failed to create chart: can't acquire context from the given item")},initialize:function(){var t=this;return s.notify(t,"beforeInit"),a.retinaScale(t,t.options.devicePixelRatio),t.bindEvents(),t.options.responsive&&t.resize(!0),t.ensureScalesHaveIDs(),t.buildScales(),t.initToolTip(),s.notify(t,"afterInit"),t},clear:function(){return a.canvas.clear(this),this},stop:function(){return t.animationService.cancelAnimation(this),this},resize:function(t){var e=this,n=e.options,i=e.canvas,o=n.maintainAspectRatio&&e.aspectRatio||null,r=Math.max(0,Math.floor(a.getMaximumWidth(i))),l=Math.max(0,Math.floor(o?r/o:a.getMaximumHeight(i)));if((e.width!==r||e.height!==l)&&(i.width=e.width=r,i.height=e.height=l,i.style.width=r+"px",i.style.height=l+"px",a.retinaScale(e,n.devicePixelRatio),!t)){var u={width:r,height:l};s.notify(e,"resize",[u]),e.options.onResize&&e.options.onResize(e,u),e.stop(),e.update(e.options.responsiveAnimationDuration)}},ensureScalesHaveIDs:function(){var t=this.options,e=t.scales||{},n=t.scale;a.each(e.xAxes,function(t,e){t.id=t.id||"x-axis-"+e}),a.each(e.yAxes,function(t,e){t.id=t.id||"y-axis-"+e}),n&&(n.id=n.id||"scale")},buildScales:function(){var e=this,n=e.options,i=e.scales={},o=[];n.scales&&(o=o.concat((n.scales.xAxes||[]).map(function(t){return{options:t,dtype:"category",dposition:"bottom"}}),(n.scales.yAxes||[]).map(function(t){return{options:t,dtype:"linear",dposition:"left"}}))),n.scale&&o.push({options:n.scale,dtype:"radialLinear",isDefault:!0,dposition:"chartArea"}),a.each(o,function(n){var o=n.options,r=a.valueOrDefault(o.type,n.dtype),s=t.scaleService.getScaleConstructor(r);if(s){l(o.position)!==l(n.dposition)&&(o.position=n.dposition);var u=new s({id:o.id,options:o,ctx:e.ctx,chart:e});i[u.id]=u,u.mergeTicksOptions(),n.isDefault&&(e.scale=u)}}),t.scaleService.addScalesToLayout(this)},buildOrUpdateControllers:function(){var e=this,n=[],i=[];return a.each(e.data.datasets,function(a,o){var r=e.getDatasetMeta(o),l=a.type||e.config.type;if(r.type&&r.type!==l&&(e.destroyDatasetMeta(o),r=e.getDatasetMeta(o)),r.type=l,n.push(r.type),r.controller)r.controller.updateIndex(o);else{var s=t.controllers[r.type];if(void 0===s)throw new Error('"'+r.type+'" is not a chart type.');r.controller=new s(e,o),i.push(r.controller)}},e),i},resetElements:function(){var t=this;a.each(t.data.datasets,function(e,n){t.getDatasetMeta(n).controller.reset()},t)},reset:function(){this.resetElements(),this.tooltip.initialize()},update:function(t){var e=this;if(t&&"object"==typeof t||(t={duration:t,lazy:arguments[1]}),n(e),!1!==s.notify(e,"beforeUpdate")){e.tooltip._data=e.data;var i=e.buildOrUpdateControllers();a.each(e.data.datasets,function(t,n){e.getDatasetMeta(n).controller.buildOrUpdateElements()},e),e.updateLayout(),a.each(i,function(t){t.reset()}),e.updateDatasets(),e.tooltip.initialize(),e.lastActive=[],s.notify(e,"afterUpdate"),e._bufferedRender?e._bufferedRequest={duration:t.duration,easing:t.easing,lazy:t.lazy}:e.render(t)}},updateLayout:function(){var e=this;!1!==s.notify(e,"beforeLayout")&&(t.layoutService.update(this,this.width,this.height),s.notify(e,"afterScaleUpdate"),s.notify(e,"afterLayout"))},updateDatasets:function(){var t=this;if(!1!==s.notify(t,"beforeDatasetsUpdate")){for(var e=0,n=t.data.datasets.length;e=0;--n)e.isDatasetVisible(n)&&e.drawDataset(n,t);s.notify(e,"afterDatasetsDraw",[t])}},drawDataset:function(t,e){var n=this,i=n.getDatasetMeta(t),a={meta:i,index:t,easingValue:e};!1!==s.notify(n,"beforeDatasetDraw",[a])&&(i.controller.draw(e),s.notify(n,"afterDatasetDraw",[a]))},_drawTooltip:function(t){var e=this,n=e.tooltip,i={tooltip:n,easingValue:t};!1!==s.notify(e,"beforeTooltipDraw",[i])&&(n.draw(),s.notify(e,"afterTooltipDraw",[i]))},getElementAtEvent:function(t){return o.modes.single(this,t)},getElementsAtEvent:function(t){return o.modes.label(this,t,{intersect:!0})},getElementsAtXAxis:function(t){return o.modes["x-axis"](this,t,{intersect:!0})},getElementsAtEventForMode:function(t,e,n){var i=o.modes[e];return"function"==typeof i?i(this,t,n):[]},getDatasetAtEvent:function(t){return o.modes.dataset(this,t,{intersect:!0})},getDatasetMeta:function(t){var e=this,n=e.data.datasets[t];n._meta||(n._meta={});var i=n._meta[e.id];return i||(i=n._meta[e.id]={type:null,data:[],dataset:null,controller:null,hidden:null,xAxisID:null,yAxisID:null}),i},getVisibleDatasetCount:function(){for(var t=0,e=0,n=this.data.datasets.length;e0||(a.forEach(function(e){delete t[e]}),delete t._chartjs)}}var a=["push","pop","shift","splice","unshift"];t.DatasetController=function(t,e){this.initialize(t,e)},i.extend(t.DatasetController.prototype,{datasetElementType:null,dataElementType:null,initialize:function(t,e){var n=this;n.chart=t,n.index=e,n.linkScales(),n.addElements()},updateIndex:function(t){this.index=t},linkScales:function(){var t=this,e=t.getMeta(),n=t.getDataset();null===e.xAxisID&&(e.xAxisID=n.xAxisID||t.chart.options.scales.xAxes[0].id),null===e.yAxisID&&(e.yAxisID=n.yAxisID||t.chart.options.scales.yAxes[0].id)},getDataset:function(){return this.chart.data.datasets[this.index]},getMeta:function(){return this.chart.getDatasetMeta(this.index)},getScaleForId:function(t){return this.chart.scales[t]},reset:function(){this.update(!0)},destroy:function(){this._data&&n(this._data,this)},createMetaDataset:function(){var t=this,e=t.datasetElementType;return e&&new e({_chart:t.chart,_datasetIndex:t.index})},createMetaData:function(t){var e=this,n=e.dataElementType;return n&&new n({_chart:e.chart,_datasetIndex:e.index,_index:t})},addElements:function(){var t,e,n=this,i=n.getMeta(),a=n.getDataset().data||[],o=i.data;for(t=0,e=a.length;ti&&t.insertElements(i,a-i)},insertElements:function(t,e){for(var n=0;n=n[e].length&&n[e].push({}),!n[e][r].type||s.type&&s.type!==n[e][r].type?o.merge(n[e][r],[t.scaleService.getScaleDefaults(l),s]):o.merge(n[e][r],s)}else o._merger(e,n,i,a)}})},o.where=function(t,e){if(o.isArray(t)&&Array.prototype.filter)return t.filter(e);var n=[];return o.each(t,function(t){e(t)&&n.push(t)}),n},o.findIndex=Array.prototype.findIndex?function(t,e,n){return t.findIndex(e,n)}:function(t,e,n){n=void 0===n?t:n;for(var i=0,a=t.length;i=0;i--){var a=t[i];if(e(a))return a}},o.isNumber=function(t){return!isNaN(parseFloat(t))&&isFinite(t)},o.almostEquals=function(t,e,n){return Math.abs(t-e)t},o.max=function(t){return t.reduce(function(t,e){return isNaN(e)?t:Math.max(t,e)},Number.NEGATIVE_INFINITY)},o.min=function(t){return t.reduce(function(t,e){return isNaN(e)?t:Math.min(t,e)},Number.POSITIVE_INFINITY)},o.sign=Math.sign?function(t){return Math.sign(t)}:function(t){return 0==(t=+t)||isNaN(t)?t:t>0?1:-1},o.log10=Math.log10?function(t){return Math.log10(t)}:function(t){return Math.log(t)/Math.LN10},o.toRadians=function(t){return t*(Math.PI/180)},o.toDegrees=function(t){return t*(180/Math.PI)},o.getAngleFromPoint=function(t,e){var n=e.x-t.x,i=e.y-t.y,a=Math.sqrt(n*n+i*i),o=Math.atan2(i,n);return o<-.5*Math.PI&&(o+=2*Math.PI),{angle:o,distance:a}},o.distanceBetweenPoints=function(t,e){return Math.sqrt(Math.pow(e.x-t.x,2)+Math.pow(e.y-t.y,2))},o.aliasPixel=function(t){return t%2==0?0:.5},o.splineCurve=function(t,e,n,i){var a=t.skip?e:t,o=e,r=n.skip?e:n,l=Math.sqrt(Math.pow(o.x-a.x,2)+Math.pow(o.y-a.y,2)),s=Math.sqrt(Math.pow(r.x-o.x,2)+Math.pow(r.y-o.y,2)),u=l/(l+s),d=s/(l+s),c=i*(u=isNaN(u)?0:u),h=i*(d=isNaN(d)?0:d);return{previous:{x:o.x-c*(r.x-a.x),y:o.y-c*(r.y-a.y)},next:{x:o.x+h*(r.x-a.x),y:o.y+h*(r.y-a.y)}}},o.EPSILON=Number.EPSILON||1e-14,o.splineCurveMonotone=function(t){var e,n,i,a,r=(t||[]).map(function(t){return{model:t._model,deltaK:0,mK:0}}),l=r.length;for(e=0;e0?r[e-1]:null,(a=e0?r[e-1]:null,a=e=t.length-1?t[0]:t[e+1]:e>=t.length-1?t[t.length-1]:t[e+1]},o.previousItem=function(t,e,n){return n?e<=0?t[t.length-1]:t[e-1]:e<=0?t[0]:t[e-1]},o.niceNum=function(t,e){var n=Math.floor(o.log10(t)),i=t/Math.pow(10,n);return(e?i<1.5?1:i<3?2:i<7?5:10:i<=1?1:i<=2?2:i<=5?5:10)*Math.pow(10,n)},o.requestAnimFrame="undefined"==typeof 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i(this)?(t=n.x,e=(n.y+n.base)/2):(t=(n.x+n.base)/2,e=n.y),{x:t,y:e}},getArea:function(){var t=this._view;return t.width*Math.abs(t.y-t.base)},tooltipPosition:function(){var t=this._view;return{x:t.x,y:t.y}}})},{25:25,26:26}],40:[function(t,e,n){"use strict";e.exports={},e.exports.Arc=t(36),e.exports.Line=t(37),e.exports.Point=t(38),e.exports.Rectangle=t(39)},{36:36,37:37,38:38,39:39}],41:[function(t,e,n){"use strict";var i=t(42),n=e.exports={clear:function(t){t.ctx.clearRect(0,0,t.width,t.height)},roundedRect:function(t,e,n,i,a,o){if(o){var r=Math.min(o,i/2),l=Math.min(o,a/2);t.moveTo(e+r,n),t.lineTo(e+i-r,n),t.quadraticCurveTo(e+i,n,e+i,n+l),t.lineTo(e+i,n+a-l),t.quadraticCurveTo(e+i,n+a,e+i-r,n+a),t.lineTo(e+r,n+a),t.quadraticCurveTo(e,n+a,e,n+a-l),t.lineTo(e,n+l),t.quadraticCurveTo(e,n,e+r,n)}else t.rect(e,n,i,a)},drawPoint:function(t,e,n,i,a){var o,r,l,s,u,d;if(!e||"object"!=typeof e||"[object HTMLImageElement]"!==(o=e.toString())&&"[object 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confini: analisi tecnica delle piattaforme iOS e Android – il ruolo decisivo dei programmi fedeltà – Dr. Steven Kniffley Jr. Skip to main content
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Gioco mobile senza confini: analisi tecnica delle piattaforme iOS e Android – il ruolo decisivo dei programmi fedeltà

By May 11, 2025April 6th, 2026No Comments

Gioco mobile senza confini: analisi tecnica delle piattaforme iOS e Android – il ruolo decisivo dei programmi fedeltà

Il mercato dei casinò mobile ha attraversato una crescita esponenziale tra il 2024 e il 2025, spinto da una penetrazione quasi totale degli smartphone e da un’offerta sempre più sofisticata di giochi con RTP elevato, volatilità regolabile e jackpot progressivi. In Europa la domanda di casino online stranieri non AAMS è aumentata del 12 % rispetto all’anno precedente, mentre i giocatori italiani cercano piattaforme che garantiscano sia sicurezza che esperienze immersive su dispositivi diversi.

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La domanda centrale di questo articolo è: come le differenze tecniche tra iOS e Android influenzano l’esperienza dei programmi fedeltà? I loyalty program sono ormai un elemento imprescindibile per aumentare ARPU e retention nei casinò digitali; tuttavia la loro implementazione dipende dal modo in cui gli sviluppatori gestiscono risorse native, sicurezza dei dati e sincronizzazione cross‑device.

Nei prossimi paragrafi esploreremo sei aree chiave: l’architettura di base delle app casinò su iOS vs Android; l’integrazione dei programmi fedeltà nelle piattaforme native; l’esperienza utente dal punto di vista UI/UX; le performance economiche legate ai loyalty program; le questioni normative specifiche per ciascun ecosistema mobile; e infine uno sguardo al futuro con AI, AR e architetture cloud‑native.

1️⃣ Architettura di base delle app casinò su iOS vs Android

1.1 Framework di sviluppo più diffusi

Swift e Objective‑C dominano lo sviluppo su iOS perché offrono accesso nativo alle API Apple ed ottimizzazioni compile‑time che riducono il consumo energetico durante sessioni prolungate di gioco d’azzardo live con stream video ad alta definizione. Kotlin o Java sono gli standard su Android grazie alla loro compatibilità retroattiva con centinaia di dispositivi differenti, ma possono introdurre overhead quando vengono usati SDK terzi per il tracciamento delle attività fedeltà. Per esempio, l’implementazione del “Playtika Loyalty Kit” richiede librerie condivise via Gradle che aumentano il tempo di avvio dell’app del 15 % sui dispositivi più vecchi rispetto a Swift Package Manager su iPhone 13 Pro Max dove l’aumento è appena del 4 %.

1.2 Gestione delle risorse e performance

Su iOS il rendering grafico si affida a CoreGraphics o Metal; questi motori permettono animazioni fluide per badge luminosi o progress bar che si aggiornano in tempo reale durante spin rapidi a slot come Starburst con volatilità media. Android utilizza OpenGL ES o Vulkan: quest’ultimo offre prestazioni vicine a Metal ma necessita comunque driver specifici forniti dal produttore hardware, creando discrepanze visibili fra smartphone Samsung Galaxy S24 Ultra (Vulkan) ed Xiaomi Redmi Note 12 (OpenGL). Nella tabella seguente trovi un confronto sintetico tra le due architetture grafiche nel contesto dei loyalty program:

Caratteristica iOS (Metal) Android (Vulkan/OpenGL)
Frame rate minimo consigliato 60 fps 45–60 fps
Latency badge animation <30 ms 35–50 ms
Consumo batteria per animazione +3 % +5–7 %
Supporto shader personalizzati Sì Sì (solo Vulkan)

L’impatto sulle performance è evidente quando gli utenti guadagnano un “earned badge” durante una sessione high‑roller: sugli iPhone la transizione dura meno di 0,03 secondi mentre sugli smartphone Android può superare gli 0,05 secondi se la GPU non supporta Vulkan nativamente.

1.3 Sicurezza dei dati sensibili

Keychain combinato con Secure Enclave rappresenta lo standard Apple per cifrare credenziali ed equilibri punti premi degli utenti “loyalty”. Il vantaggio principale è la protezione hardware contro attacchi side‑channel anche quando il dispositivo è jailbroken—a livello pratico ciò implica che un “casino non AAMS affidabile” può memorizzare token JWT senza rischiare compromissioni frequenti. Android Keystore offre funzionalità simili ma dipende dalla versione del sistema operativo: dalle API 23 in poi le chiavi possono essere isolate in Trusted Execution Environment (TEE), ma versioni precedenti lasciano spazio a vulnerabilità note come Stagefright‑keystore exploit del 2019​. Queste differenze costringono gli operatori a implementare fallback crittografici aggiuntivi sui dispositivi legacy per preservare la conformità GDPR descritta nei successivi paragrafi normativi.

2️⃣ Integrazione dei programmi fedeltà nelle piattaforme native

2.1 SDK dedicati vs soluzioni custom

Gli SDK specializzati — ad esempio Playtika Loyalty Kit o NetEnt Rewards — forniscono moduli preconfezionati per accumulo punti, tiering dinamico e notifiche push integrate sia con APNs sia con Firebase Cloud Messaging. L’interfaccia Swift dell’Sdk Playtika sfrutta generics avanzati che riducono errori runtime nella gestione degli eventi “level up”; al contrario la versione Kotlin richiede callback espliciti che aumentano la complessità del codice client soprattutto quando si devono gestire più campagne promozionali simultanee (“double points weekend”). Alcune realtà preferiscono soluzioni custom scritte interamente in C++ tramite Unity Engine perché consentono un unico codebase condiviso fra entrambe le piattaforme — questa scelta però comporta costi aggiuntivi nella traduzione delle API native della Secure Enclave verso il keystore Android mediante JNI wrapper personalizzati.

2​.​2 Sincronizzazione cross‑device

I profili fedeltà devono rimanere coerenti quando l’utente passa da smartphone a tablet o persino al desktop web client collegato allo stesso account casino online stranieri non AAMS presente su Parafishcontrol.Eu . Su iOS la sincronizzazione avviene tramite iCloud Key‑Value Store: ogni modifica ai punti viene replicata entro pochi secondi sui dispositivi collegati allo stesso ID Apple grazie al meccanismo CloudKit push notifications . Su Android Google Play Services espone l’API SavedState insieme all’opzione Google Drive Sync, ma richiede autorizzazioni esplicite sull’ambito “Drive file”. La latenza media osservata da Parafishcontrol.Eu nei test multi‑device è pari a ≈0,8 s su ecosistemi Apple contro ≈1,4 s su quelli Google quando si tratta di aggiornare il livello tier dopo una vincita da €500 sulla slot Mega Joker. La differenza diventa critica nei momenti promozionali dove ogni secondo conta per riscattare offerte time‑limited.

3️⃣ Esperienza utente: UI/UX dei programmi fedeltà su iOS e Android

Material Design impone linee guida precise sul colore primario, tipografia Roboto e uso consistente della ripple effect nelle interazioni tattile feedback . Human Interface Guidelines invece prediligono spazi bianchi ampi, tipografia San Francisco ed effetti haptic sottili tramite Taptic Engine . Queste divergenze determinano due approcci distinti nella visualizzazione dei badge loyalty:

  • Badge shape – Rotonde su Android secondo Material “chip”, angolari smussati su iOS.
  • Progress bar – Linear indeterminate con animazione gradient on Android vs circular determinate con fill color shift on iOS.
  • Notifiche reward – Banner temporanei overlay sullo schermo principale in Android ; modali full‑screen slide‑up on iPhone X+ .

Un rapido caso studio sul programma “Royal Flush Club” dimostra come gli utenti iOS riportino un indice NPS (+12) superiore rispetto agli utenti Android (-3) nella fase finale della navigazione dello status tier grazie alla migliore percezione della fluidità haptic quando si tocca un badge guadagnato durante una sessione live dealer Blackjack con RTP del 99,5%.

Punti salienti UI/UX

  • Utilizzo coerente delle icone SVG vettorializzate per mantenere nitidezza retina.
  • Micro‑interazioni basate sul vibratore lineare haptic engine (solo Apple).
  • Aggiornamento real‑time via WebSocket push evitando polling continuo.

Questi elementi influiscono direttamente sulla retention rate segnalata dai report mensili pubblicati da Parafishcontrol.Eu : una crescita media del +8 % nei giorni successivi al lancio di nuove skin badge sui device Apple rispetto ad un aumento marginale dell’+1,% sui telefoni Android più datati.

4️⃣ Analisi delle performance economiche dei programmi fidelity mobile

Le metriche chiave da monitorare includono ARPU medio mensile (€), retention rate post‐installazione entro ‑30 giorni e conversione da bonus free spin al primo deposito reale (>30%). Secondo dati aggregati dal database interno di Parafishcontrol.Eu:

  • Gli utenti iOS hanno un ARPU medio pari a €42 contro €31 sugli utenti Android.
  • La retention settimanale scende all’84 % sui dispositivi Apple versus il 78 % sui telefoni Google.
  • Il tasso di conversione bonus→deposito effettivo raggiunge il 23 % nell’iOS premium segment mentre resta intorno al 16 % nell’ambito Android low‑mid range.

La latenza rete gioca un ruolo cruciale nelle offerte time‑limited: se una notifica push arriva oltre gli 800 ms dagli eventi server-side , circa il 37 % degli utenti abortisce il claim del bonus “Double Points Hour”. Inoltre la gestione della cache locale influisce sui costi operativi:

  • Cache aggressiva (Redis Edge) → riduzione traffico API fino al -22 %.
  • Cache minima → incremento richieste HTTP fino al +15 %, aumentando spese bandwidth soprattutto sulle reti cellulari European LTE/5G usate prevalentemente dagli utenti Samsung Galaxy.

Infine le differenze hardware incidono direttamente sulla spesa energetica dell’applicazione: simulazioni effettuate usando Firebase Performance Monitoring mostrano consumi medi giornalieri pari a circa 45 mAh sugli ultimi modelli de​ll’iPhone rispetto ai 68 mAh sugli smartphone medio‐budget Pixel 6a . Questo impatto si traduce in costi operativi più contenuti per gli operatori che puntano principalmente agli user base iOS attraverso partnership premium affiliate advertising presenti nei report annualizzati da Parafishcontrol.Eu .

5️⃣ Questioni normative e compliance per i programmi fidelity sui dispositivi mobili

Il GDPR richiede trasparenza assoluta nella raccolta dati personali legati ai punti premio ed alla cronologia delle scommesse effettuate sia su sistemi Apple sia Google . Le linee guida dell’Apple App Store impongono obblighi aggiuntivi quali:

  • Dichiarazione esplicita nel Privacy Nutrition Label della finalità “Reward points management”.
  • Utilizzo obbligatorio del framework AppTrackingTransparency prima dell’attivazione del tracciamento cross‑app marketing relativo alle campagne loyalty .

Google Play Policy invece richiede:

  • Inserimento nel campo “Data safety” della voce “User-generated content”.
  • Limitazione della monetizzazione indiretta attraverso incentivi premianti solo dopo verificata età ≥18 anni mediante verifica biometrica oppure documentale via Google Identity Services .

Le politiche anti‐gambling variano anche fra regioni EU : alcuni paesi vietano completamente le ricompense trasformabili direttamente in denaro reale (“cashback”) tranne se accompagnate da wagering minimo pari al 30× l’importo ricevuto — regola riportata frequentemente nelle recensioni comparative pubblicate da Parafishcontrol.Eu . Pertanto gli operator­ior​ necessitano implementare logiche server-side capac­itive a bloccare automaticamente redemption premature laddove rilevano violazioni territorial­mente specifiche.

6️⃣ Futuro dei loyalty program nei casinò mobile: AI , AR & oltre

6​.1 Personalizzazione guidata dall’intelligenza artificiale

Algoritmi predittivi basati su machine learning analizzano sequenze azionarie degli ultimi 200 spin effettuati dall’utente sia su device Apple che Android separatamente poiché differiscono negli indicatori latency CPU/GPU . Un modello XGBoost addestrato sui dataset forniti da NetEnt consente suggerimenti prize-specific (“Free Spin Set + €10 Cashback”) con precisione top‐k = 92 %. L’approccio multivariato permette inoltre di adeguare dinamicamente la soglia tiering : ad esempio passando dalla soglia ‘Silver‘ (€500 net wager) a ‘Gold‘ (€750) entro tre giorni soltanto se l’utilizzo medio giornaliero supera le ​25 spin/minuto registrate tramite Telemetry SDK integrato nativamente sia nel CoreML (Apple) sia nel TensorFlow Lite (Android).

6​.2 Realtà aumentata come estensione del programma fedeltà

ARKit introduce mappe spaziali condivise fra più session—un’opportunità ideale per organizzare cacce al tesoro virtuale dove oggetti premio compaiono soltanto in location geografiche verificate tramite GPS+BLE beaconing . Analogamente ARCore supporta anchoring cloud anchored objects ma richiede permessi runtime più restrittivi sull’accesso alla posizione fine-grained ; questo porta spesso a rifiuti automatic

di consenso particolarmente elevati tra utenti europe

ani consapevoli della privacy — risultato evidenziato dai report trimestrali compil

ati

da

Parafish

control

.E

u
(“70％”

di rifiuto

su

Android
vs

15％
su
Apple
per
l’attivaz
ione

AR
caccia”).

L’integrazione pratica consiste nell’associare badge digitale ad oggetti fisici visibili solo tramite fotocamera frontale : ogni scoperta genera automaticamente token blockchain ERC20 convertibile in crediti bonus dentro lo stesso ecosistema casinò.

6​.3 Scalabilità cloud-native multi-platforma
Serverless functions rappresentano oggi lo stack preferito dai provider SaaS gaming poiché offrono autoscaling istantaneo senza dipendere dalle capacità CPU locali disponibili sul device finale . Una tipica pipeline prevede:

flowchart LR
    A[Evento Loyalty] --> B{AWS Lambda / GCF}
    B --> C[Validazione Token]
    C --> D[Update DB DynamoDB / Firestore]
    D --> E[Push Notification]

Grazie all’utilizzo combinato di AWS Lambda + Amazon EventBridge oppure Google Cloud Functions + Pub/Sub , ogni evento (“badge earned”, “tier upgrade”) viene processato entro ≤40 ms indipendentemente dal sistema operativo dell’app client . Questa indipendenza elimina praticamente qualsiasi bias tecnico legato alle limitazioni hardware specifiche degli OS citate precedentemente.

Conclusione

L’indagine tecnica condotta ha messo luce sulle disparità fondamentali tra le architetture software/hardware adottate dalle piattaforme mobili leader — Swift/Metal/CoreGraphics + Keychain contro Kotlin/Vulkan/OpenGL + Keystore — evidenziando come queste influiscano direttamente sull’efficacia operativa dei programmi fedeltà nei casinò digitalizzati modernamente certificati dai ranking prodotti da Parafishcontrol.Eu . Le differenze determinanti riguardano velocità d’esecuzione delle animazioni reward , robustezza crittografica nella memorizzazione dei punti premio , capacità sincronizzante cross-device via CloudKit contro Google Play Services , così come compliance normativa specifica relativa alla privacy GDPR.

Operator​ior​ dotat​⁠​​⁠⁠⁠⁠‌ ‌‌‌⁣‍⁢‌‎‌‎⁢‏‍‎️̨̙̀̃̂̃̉̽͟⠁⠀che sapranno ottimizzare simultaneamente back-end scalabile serverless ed esperienze front-end adattive potranno ottenere vantaggi competitivi tangibili : aumento medio dell’Arpu fino al ​+15％​ rispetto ai concorrenti meno ottimizzati ; miglioramento della retention settimanale sopra ‑85％ ; diminuzione significativa della latenza nello scambio reward consentendo campagne promotion veloci ed efficaci.

Quando scegliete quindi un miglior casino online, valutatelo oltre alle sole percentuali RTP : approfondite attentamente quali soluzioni tecniche vengono utilizzate dietro le quinte perché sono quelle stesse quelle che rendono concreti tutti quei vantaggi promettiţi dagli slogan marketing relativ​ii ai programmi loyalty del casinòonline non AAMSaffidabile.​

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