前言

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" alt="" />

在Extjs 中。 单一的 Column Chart 的展示效果如上。

定义的过程例如以下：

1.  创建一个 Ext.chart.Chart

2. 创建两个坐标轴。 axes

一个 Category 类型的横坐标用来显示日期

一个Numeric 类型的纵坐标用来显示数据

3. 配置显示的图 series

配置 column 类型的柱状图。

详细代码例如以下：

<!--

 Author : oscar999

 Date :

 ALL RIGHTS RESERVED

-->

<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">

<html>

<head>

<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">

<title>Insert title here</title>

<script type="text/javascript" src="../lib/extjs/ext-all.js"></script>

<link rel="stylesheet" type="text/css" href="../lib/extjs/resources/ext-theme-neptune/ext-theme-neptune-all.css" />

<script>

Ext.onReady(function(){

    window.generateData = function(n, floor){

        var data = [],

            p = (Math.random() *  11) + 1,

            i;

        floor = (!floor && floor !== 0)?

20 : floor;

        for (i = 0; i < (n || 12); i++) {

            data.push({

                name: Ext.Date.monthNames[i % 12],

                data1: Math.floor(Math.max((Math.random() * 100), floor)),

                data2: Math.floor(Math.max((Math.random() * 100), floor)),

                data3: Math.floor(Math.max((Math.random() * 100), floor)),

                data4: Math.floor(Math.max((Math.random() * 100), floor)),

                data5: Math.floor(Math.max((Math.random() * 100), floor)),

                data6: Math.floor(Math.max((Math.random() * 100), floor)),

                data7: Math.floor(Math.max((Math.random() * 100), floor)),

                data8: Math.floor(Math.max((Math.random() * 100), floor)),

                data9: Math.floor(Math.max((Math.random() * 100), floor))

            });

        }

        return data;

    };

    var store1 = Ext.create('Ext.data.JsonStore', {

        fields: ['name', 'data1', 'data2', 'data3', 'data4', 'data5', 'data6', 'data7', 'data9', 'data9'],

        data: generateData()

    });

    var chart = Ext.create('Ext.chart.Chart', {

        style: 'background:#fff',

        animate: true,

        shadow: true,

        store: store1,

        //maxWidth: 500,

        //columnWidth : 0.1,

        axes: [{

            type: 'Numeric',

            position: 'left',

            fields: ['data1'],

            label: {

                renderer: Ext.util.Format.numberRenderer('0,0')

            },

            title: 'Number of Hits',

            grid: true,

            minimum: 0

        }, {

            type: 'Category',

            position: 'bottom',

            fields: ['name'],

            //categoryNames:new String("111"),

            title: 'Month of the Year'

        }],

        series: [{

            type: 'column',

            axis: 'left',

            highlight: true,

            tips: {

              trackMouse: true,

              width: 140,

              height: 28,

              renderer: function(storeItem, item) {

                this.setTitle(storeItem.get('name') + ': ' + storeItem.get('data1') + ' $');

              }

            },

            label: {

              display: 'insideEnd',

              'text-anchor': 'middle',

                field: 'data1',

                //renderer: Ext.util.Format.numberRenderer('0'),

                orientation: 'vertical',

                color: '#FFF'

            },

            style:{

            	opacity: 0.95

            	//,width:100

            },

            //xPadding:{left:100,right:100},

            xField: 'name',

            yField: 'data1'

        }]

    });

var win = Ext.create('Ext.window.Window', {

    width: 800,

    height: 600,

    minHeight: 400,

    minWidth: 550,

    hidden: false,

    maximizable: true,

    title: 'Column Chart',

    autoShow: true,

    layout: 'fit',

    tbar: [{

        text: 'Save Chart',

        handler: function() {

            Ext.MessageBox.confirm('Confirm Download', 'Would you like to download the chart as an image?', function(choice){

                if(choice == 'yes'){

                    chart.save({

                        type: 'image/png'

                    });

                }

            });

        }

    }, {

        text: 'Reload Data',

        handler: function() {

            // Add a short delay to prevent fast sequential clicks

            window.loadTask.delay(100, function() {

                store1.loadData(generateData());

            });

        }

    }],

    items: chart

});

});

</script>

</head>

<body>

</body>

</html>

怎样设置坐标轴的长度

针对上面的样例， 坐标轴的长度是Extjs依据数据大小自己主动运算并设置的。

假设须要手动定义这个长度的话，改怎样设置呢？

对于Numeric这样的坐标轴来说， 有maximum 和 minimun 这样的參数能够配置。

并且配置也非常easy了， 就不多介绍了。

这里仅仅是对红色的部分做一个伏笔（这样的设置对于配置 堆叠的图形不使用）

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多个图形。 两个纵坐标轴

有的状况下， 可能会使用多个图形，

由于图形的范围不同，可能须要使用两个纵坐标轴。

相似的情景能够是这样：

有三个图， 两个柱状图。 一个折线图

折线图和柱状图的数据范围或是单位可能不同。

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" alt="" />

这里看上去好像是一个折线图和一个柱状图。

事实上是有两个柱状图， 仅仅只是一个被还有一个盖住了。

出现这样的状况的原因是在定义的时候， 往series 中加入了两个column 的chart.

这样的状况的源代码是：

<!--

 Author : oscar999

 Date :

 ALL RIGHTS RESERVED

-->

<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">

<html>

<head>

<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">

<title>Insert title here</title>

<script type="text/javascript" src="../lib/extjs/ext-all.js"></script>

<link rel="stylesheet" type="text/css" href="../lib/extjs/resources/ext-theme-neptune/ext-theme-neptune-all.css" />

<script>

Ext.onReady(function(){

    window.generateData = function(n, floor){

        var data = [],

            p = (Math.random() *  11) + 1,

            i;

        floor = (!floor && floor !== 0)? 20 : floor;

        for (i = 0; i < (n || 12); i++) {

            data.push({

                name: Ext.Date.monthNames[i % 12],

                data1: (i+1)*8,

                data2: (i+1)*10,

                data3: (i+1)*8

            });

        }

        return data;

    };

    var store1 = Ext.create('Ext.data.JsonStore', {

        fields: ['name', 'data1', 'data2', 'data3', 'data4', 'data5', 'data6', 'data7', 'data9', 'data9'],

        data: generateData()

    });

    var chart = Ext.create('Ext.chart.Chart', {

        style: 'background:#fff',

        animate: true,

        shadow: true,

        store: store1,

        legend:'right',

        axes: [{

            type: 'Numeric',

            position: 'left',

            fields: ['data1','data2'],

            label: {

                renderer: Ext.util.Format.numberRenderer('0,0')

            },

            title: 'Number of Hits',

            grid: true

        },{

            type: 'Numeric',

            position: 'right',

            fields: ['data3'],

            label: {

                renderer: Ext.util.Format.numberRenderer('0,0')

            },

            //title: 'Number of Hits',

            grid: true

        }, {

            type: 'Category',

            position: 'bottom',

            fields: ['name'],

            title: 'Month of the Year'

        }],

        series: [{

            type: 'column',

            axis: 'left',

            highlight: true,

            tips: {

              trackMouse: true,

              width: 140,

              height: 28,

              renderer: function(storeItem, item) {

                this.setTitle(storeItem.get('name') + ': ' + storeItem.get('data1') + ' $');

              }

            },

            label: {

              display: 'insideEnd',

              'text-anchor': 'middle',

                field: 'data1',

                //renderer: Ext.util.Format.numberRenderer('0'),

                orientation: 'vertical',

                color: '#FFF'

            },

            style:{

            	opacity: 0.95

            	//,width:100

            },

            //xPadding:{left:100,right:100},

            xField: 'name',

            yField: ['data1']

        }

        ,{

            type: 'column',

            axis: 'left',

            highlight: true,

            tips: {

              trackMouse: true,

              width: 140,

              height: 28,

              renderer: function(storeItem, item) {

                this.setTitle(storeItem.get('name') + ': ' + storeItem.get('data2') + ' $');

              }

            },

            label: {

              display: 'insideEnd',

              'text-anchor': 'middle',

                field: ['data1','data2'],

                //renderer: Ext.util.Format.numberRenderer('0'),

                orientation: 'vertical',

                color: '#FFF'

            },

            style:{

            	opacity: 0.95

            	//,width:100

            },

            //xPadding:{left:100,right:100},

            xField: 'name',

            yField: ['data2']

        }

        ,

        {

            type: 'line',

            axis: 'right',

            highlight: true,

            tips: {

              trackMouse: true,

              width: 140,

              height: 28,

              renderer: function(storeItem, item) {

                this.setTitle(storeItem.get('name') + ': ' + storeItem.get('data3') + ' $');

              }

            },

            label: {

              display: 'insideEnd',

              'text-anchor': 'middle',

                field: 'data3',

                //renderer: Ext.util.Format.numberRenderer('0'),

                orientation: 'vertical',

                color: '#FFF'

            },

            style:{

            	opacity: 0.95

            	//,width:100

            },

            //xPadding:{left:100,right:100},

            xField: 'name',

            yField: 'data3'

        }]

    });

var win = Ext.create('Ext.window.Window', {

    width: 800,

    height: 600,

    minHeight: 400,

    minWidth: 550,

    hidden: false,

    maximizable: true,

    title: 'Column Chart',

    autoShow: true,

    layout: 'fit',

    tbar: [{

        text: 'Save Chart',

        handler: function() {

            Ext.MessageBox.confirm('Confirm Download', 'Would you like to download the chart as an image?', function(choice){

                if(choice == 'yes'){

                    chart.save({

                        type: 'image/png'

                    });

                }

            });

        }

    }, {

        text: 'Reload Data',

        handler: function() {

            // Add a short delay to prevent fast sequential clicks

            window.loadTask.delay(100, function() {

                store1.loadData(generateData());

            });

        }

    }],

    items: chart

});

});

</script>

</head>

<body>

</body>

</html>

基本上这不是我们想要的效果。

我们要的效果应该是这样：

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" 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这是完美的呈现方式。

完美方式实现的思想是：

1  创建两个坐标轴。 axes

一个 Category 类型的横坐标用来显示日期

一个Numeric 类型的纵坐标用来显示柱状图数据

一个Numeric 类型的纵坐标用来显示折线图数据

2.  series 加入一个 column Chart.  stacked.

以上定义完毕之后。 会发生基本上都正常， 可是有一点就是， 左右的两个纵坐标的尺度可能不同。

通过配置maximum 和maximum 来设置坐标并不会生效。

这里就要提到上面框出的maximum配置的红色部分了， 由于这个配置对于堆叠的图已经不适用了。

堆叠图性的左右坐标一致

为什么会出现左右坐标不一致的状况， 看一看Extjs 的 Ext.chart.axis.Numeric 的定义

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" alt="" />

原来是这个地方有限制。这应该是Extjs 有意为之了， 至于原因是什么，尚不可知。

无论这样。先去除这个限制得到想要的效果。

解决方式就是定义一个和  Ext.chart.axis.Numeric 相似的坐标定义

/**

 * Add by Oscar999

 */

Ext.define('Ext.chart.axis.StackedNumeric', {

    /* Begin Definitions */

    extend: 'Ext.chart.axis.Axis',

    alternateClassName: 'Ext.chart.StackedNumericAxis',

    /* End Definitions */

    type: 'StackedNumeric',

    // @private

    isNumericAxis: true,

    alias: 'axis.stackednumeric',

    uses: ['Ext.data.Store'],

    constructor: function(config) {

        var me = this,

            hasLabel = !!(config.label && config.label.renderer),

            label;

        me.callParent([config]);

        label = me.label;

        if (config.constrain == null) {

            me.constrain = (config.minimum != null && config.maximum != null);

        }

        if (!hasLabel) {

            label.renderer = function(v) {

                return me.roundToDecimal(v, me.decimals);

            };

        }

    },

    roundToDecimal: function(v, dec) {

        var val = Math.pow(10, dec || 0);

        return Math.round(v * val) / val;

    },

    /**

     * @cfg {Number} minimum

     * The minimum value drawn by the axis. If not set explicitly, the axis

     * minimum will be calculated automatically. It is ignored for stacked charts.

     */

    minimum: NaN,

    /**

     * @cfg {Number} maximum

     * The maximum value drawn by the axis. If not set explicitly, the axis

     * maximum will be calculated automatically. It is ignored for stacked charts.

     */

    maximum: NaN,

    /**

     * @cfg {Boolean} constrain

     * If true, the values of the chart will be rendered only if they belong between minimum and maximum.

     * If false, all values of the chart will be rendered, regardless of whether they belong between minimum and maximum or not.

     * Default's true if maximum and minimum is specified. It is ignored for stacked charts.

     */

    constrain: true,

    /**

     * @cfg {Number} decimals

     * The number of decimals to round the value to.

     */

    decimals: 2,

    /**

     * @cfg {String} scale

     * The scaling algorithm to use on this axis. May be "linear" or

     * "logarithmic".  Currently only linear scale is implemented.

     * @private

     */

    scale: "linear",

    // @private constrains to datapoints between minimum and maximum only

    doConstrain: function() {

        var me = this,

            chart = me.chart,

            store = chart.getChartStore(),

            items = store.data.items,

            d, dLen, record,

            series = chart.series.items,

            fields = me.fields,

            ln = fields.length,

            range = me.calcEnds(),

            min = range.from, max = range.to, i, l,

            useAcum = false,

            value, data = [],

            addRecord;

        for (d = 0, dLen = items.length; d < dLen; d++) {

            addRecord = true;

            record = items[d];

            for (i = 0; i < ln; i++) {

                value = record.get(fields[i]);

                if (me.type == 'Time' && typeof value == "string") {

                    value = Date.parse(value);

                }

                if (+value < +min) {

                    addRecord = false;

                    break;

                }

                if (+value > +max) {

                    addRecord = false;

                    break;

                }

            }

            if (addRecord) {

                data.push(record);

            }

        }

        chart.setSubStore(new Ext.data.Store({

            model: store.model,

            data: data

        }));

    },

    /**

     * @cfg {String} position

     * Indicates the position of the axis relative to the chart

     */

    position: 'left',

    /**

     * @cfg {Boolean} adjustMaximumByMajorUnit

     * Indicates whether to extend maximum beyond data's maximum to the nearest

     * majorUnit.

     */

    adjustMaximumByMajorUnit: false,

    /**

     * @cfg {Boolean} adjustMinimumByMajorUnit

     * Indicates whether to extend the minimum beyond data's minimum to the

     * nearest majorUnit.

     */

    adjustMinimumByMajorUnit: false,

    // applying constraint

    processView: function() {

        var me = this;

        if (me.constrain) {

            me.doConstrain();

        }

    },

    // @private apply data.

    applyData: function() {

        this.callParent();

        return this.calcEnds();

    }

});

这一段建议是单独放在一个js 文件里。 通过导入的方式使用。

以下给出一个放在同一份文件里完整的源代码：

<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">

<html>

<head>

<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">

<title>Insert title here</title>

<script type="text/javascript" src="../lib/extjs/ext-all.js"></script>

<script>

/*Ext.define('mtk.chart.axis.Numeric',

{

	extend : 'Ext.chart.axis.Numeric',

	type: 'stackedNumeric',

	initComponent: function(config) {

		this.processView = function() {

		    var me = this,

		        chart = me.chart,

		        series = chart.series.items,

		        i, l;

		    for (i = 0, l = series.length; i < l; i++) {

		        if (series[i].stacked) {

		            // Do not constrain stacked charts (bar, column, or area).

		            delete me.minimum;

		            delete me.maximum;

		            me.constrain = false;

		            break;

		        }

		    }

		    if (me.constrain) {

		        me.doConstrain();

		    }

		};

		this.callParent([config]);

	}

});*/

Ext.define('Ext.chart.axis.StackedNumeric', {

    /* Begin Definitions */

    extend: 'Ext.chart.axis.Axis',

    alternateClassName: 'Ext.chart.StackedNumericAxis',

    /* End Definitions */

    type: 'StackedNumeric',

    // @private

    isNumericAxis: true,

    alias: 'axis.stackednumeric',

    uses: ['Ext.data.Store'],

    constructor: function(config) {

        var me = this,

            hasLabel = !!(config.label && config.label.renderer),

            label;

        me.callParent([config]);

        label = me.label;

        if (config.constrain == null) {

            me.constrain = (config.minimum != null && config.maximum != null);

        }

        if (!hasLabel) {

            label.renderer = function(v) {

                return me.roundToDecimal(v, me.decimals);

            };

        }

    },

    roundToDecimal: function(v, dec) {

        var val = Math.pow(10, dec || 0);

        return Math.round(v * val) / val;

    },

    /**

     * @cfg {Number} minimum

     * The minimum value drawn by the axis. If not set explicitly, the axis

     * minimum will be calculated automatically. It is ignored for stacked charts.

     */

    minimum: NaN,

    /**

     * @cfg {Number} maximum

     * The maximum value drawn by the axis. If not set explicitly, the axis

     * maximum will be calculated automatically. It is ignored for stacked charts.

     */

    maximum: NaN,

    /**

     * @cfg {Boolean} constrain

     * If true, the values of the chart will be rendered only if they belong between minimum and maximum.

     * If false, all values of the chart will be rendered, regardless of whether they belong between minimum and maximum or not.

     * Default's true if maximum and minimum is specified. It is ignored for stacked charts.

     */

    constrain: true,

    /**

     * @cfg {Number} decimals

     * The number of decimals to round the value to.

     */

    decimals: 2,

    /**

     * @cfg {String} scale

     * The scaling algorithm to use on this axis. May be "linear" or

     * "logarithmic".  Currently only linear scale is implemented.

     * @private

     */

    scale: "linear",

    // @private constrains to datapoints between minimum and maximum only

    doConstrain: function() {

        var me = this,

            chart = me.chart,

            store = chart.getChartStore(),

            items = store.data.items,

            d, dLen, record,

            series = chart.series.items,

            fields = me.fields,

            ln = fields.length,

            range = me.calcEnds(),

            min = range.from, max = range.to, i, l,

            useAcum = false,

            value, data = [],

            addRecord;

        for (d = 0, dLen = items.length; d < dLen; d++) {

            addRecord = true;

            record = items[d];

            for (i = 0; i < ln; i++) {

                value = record.get(fields[i]);

                if (me.type == 'Time' && typeof value == "string") {

                    value = Date.parse(value);

                }

                if (+value < +min) {

                    addRecord = false;

                    break;

                }

                if (+value > +max) {

                    addRecord = false;

                    break;

                }

            }

            if (addRecord) {

                data.push(record);

            }

        }

        chart.setSubStore(new Ext.data.Store({

            model: store.model,

            data: data

        }));

    },

    /**

     * @cfg {String} position

     * Indicates the position of the axis relative to the chart

     */

    position: 'left',

    /**

     * @cfg {Boolean} adjustMaximumByMajorUnit

     * Indicates whether to extend maximum beyond data's maximum to the nearest

     * majorUnit.

     */

    adjustMaximumByMajorUnit: false,

    /**

     * @cfg {Boolean} adjustMinimumByMajorUnit

     * Indicates whether to extend the minimum beyond data's minimum to the

     * nearest majorUnit.

     */

    adjustMinimumByMajorUnit: false,

    // applying constraint

    processView: function() {

        /*var me = this,

            chart = me.chart,

            series = chart.series.items,

            i, l;

        for (i = 0, l = series.length; i < l; i++) {

            if (series[i].stacked) {

                // Do not constrain stacked charts (bar, column, or area).

                delete me.minimum;

                delete me.maximum;

                me.constrain = false;

                break;

            }

        }

        if (me.constrain) {

            me.doConstrain();

        }*/

        var me = this;

        if (me.constrain) {

            me.doConstrain();

        }

    },

    // @private apply data.

    applyData: function() {

        this.callParent();

        return this.calcEnds();

    }

});

</script>

<link rel="stylesheet" type="text/css" href="../lib/extjs/resources/ext-theme-neptune/ext-theme-neptune-all.css" />

<script>

Ext.onReady(function(){

    window.generateData = function(n, floor){

        var data = [],

            p = (Math.random() *  11) + 1,

            i;

        floor = (!floor && floor !== 0)? 20 : floor;

        for (i = 0; i < (n || 12); i++) {

            data.push({

                name: Ext.Date.monthNames[i % 12],

                /*data1: Math.floor(Math.max((Math.random() * 100), floor)),

                data2: Math.floor(Math.max((Math.random() * 100), floor)),

                data3: Math.floor(Math.max((Math.random() * 100), floor)),

                data4: Math.floor(Math.max((Math.random() * 100), floor)),

                data5: Math.floor(Math.max((Math.random() * 100), floor)),

                data6: Math.floor(Math.max((Math.random() * 100), floor)),

                data7: Math.floor(Math.max((Math.random() * 100), floor)),

                data8: Math.floor(Math.max((Math.random() * 100), floor)),

                data9: Math.floor(Math.max((Math.random() * 100), floor))*/

                data1: (i+1)*8,

                data2: (i+1)*8,

                data3: (i+1)*8,

                data4: (i+1)*8,

                data5: (i+1)*8,

                data6: (i+1)*8,

                data7: (i+1)*8,

                data8: (i+1)*8,

                data9: (i+1)*8

            });

        }

        return data;

    };

    var store1 = Ext.create('Ext.data.JsonStore', {

        fields: ['name', 'data1', 'data2', 'data3', 'data4', 'data5', 'data6', 'data7', 'data9', 'data9'],

        data: generateData()

    });

    var chart = Ext.create('Ext.chart.Chart', {

        style: 'background:#fff',

        animate: true,

        shadow: true,

        store: store1,

        //maxWidth: 500,

        //columnWidth : 0.1,

        legend:'right',

        axes: [{

            type: 'StackedNumeric',

            position: 'left',

            fields: ['data1','data2'],

            label: {

                renderer: Ext.util.Format.numberRenderer('0,0')

            },

            title: 'Number of Hits',

            grid: true,

            minimum: 0,

            maximum:200

        },{

            type: 'StackedNumeric',

            position: 'right',

            fields: ['data3'],

            label: {

                renderer: Ext.util.Format.numberRenderer('0,0')

            },

            //title: 'Number of Hits',

            grid: true,

            minimum: 0,

            maximum:200

        }, {

            type: 'Category',

            position: 'bottom',

            fields: ['name'],

            //categoryNames:new String("111"),

            title: 'Month of the Year'

        }],

        series: [{

            type: 'column',

            axis: 'left',

            //stacked:false,

            stacked:true,

            highlight: true,

            tips: {

              trackMouse: true,

              width: 140,

              height: 28,

              renderer: function(storeItem, item) {

                this.setTitle(storeItem.get('name') + ': ' + storeItem.get('data1') + ' $');

              }

            },

            label: {

              display: 'insideEnd',

              'text-anchor': 'middle',

                field: ['data1','data2'],

                //renderer: Ext.util.Format.numberRenderer('0'),

                orientation: 'vertical',

                color: '#FFF'

            },

            style:{

            	opacity: 0.95

            	//,width:100

            },

            //xPadding:{left:100,right:100},

            xField: 'name',

            yField: ['data1','data2']

        }

        ,

        {

            type: 'line',

            axis: 'right',

            highlight: true,

            tips: {

              trackMouse: true,

              width: 140,

              height: 28,

              renderer: function(storeItem, item) {

                this.setTitle(storeItem.get('name') + ': ' + storeItem.get('data3') + ' $');

              }

            },

            label: {

              display: 'insideEnd',

              'text-anchor': 'middle',

                field: 'data3',

                //renderer: Ext.util.Format.numberRenderer('0'),

                orientation: 'vertical',

                color: '#FFF'

            },

            style:{

            	opacity: 0.95

            	//,width:100

            },

            //xPadding:{left:100,right:100},

            xField: 'name',

            yField: 'data3'

        }]

    });

var win = Ext.create('Ext.window.Window', {

    width: 800,

    height: 600,

    minHeight: 400,

    minWidth: 550,

    hidden: false,

    maximizable: true,

    title: 'Column Chart',

    autoShow: true,

    layout: 'fit',

    tbar: [{

        text: 'Save Chart',

        handler: function() {

            Ext.MessageBox.confirm('Confirm Download', 'Would you like to download the chart as an image?', function(choice){

                if(choice == 'yes'){

                    chart.save({

                        type: 'image/png'

                    });

                }

            });

        }

    }, {

        text: 'Reload Data',

        handler: function() {

            // Add a short delay to prevent fast sequential clicks

            window.loadTask.delay(100, function() {

                store1.loadData(generateData());

            });

        }

    }],

    items: chart

});

});

</script>

</head>

<body>

</body>

</html>