Documentation

- Introduction
- Getting started
- Navigation
- Layout, Grid & Cartons
- Welcome screen
- Themes
- UI elements
- Update System
- Notifications
- Modals
- Tooltips
- Animations
- Charts
- Editor
- Gallery
- Icons
- Tables
- Error pages
- Maps & Location
- iPhone web app
- Licenses & Attributions

# Charts

Pastel includes two chart plugins:

1. One of the best jQuery plugins that has ever existed, flot.js - maintained by Ole Laursen. Flot makes handsome (client-side) charts. Best part is that it's rendered with the HTML5's canvas element. It includes a lot of features and great documentation, which is included at this very page (starts at Flot Reference.) I have written a few words on how to reveal colored tooltips on data point hover just below.

2. A tiny plugin written by me called Orbit. It's a tiny experiment, just for fun! It creates four circles with a pointer that is animated by CSS (can be set in JS.) I hope it somehow can help you to visualize data in a smart way.

## Orbit charts

Only works in WebKit and newer versions of Firefox at the moment. It degrades beautifully in all browsers though, even in Internet Explorer 8 - the orbit is just a bit square. Make an orbit chart like this:

    $("#orbit_1").orbit(
        {
            animation: "rollIn",
            texture: false,
            one: {color: "#F6BCAD", tooltip: "Research In Motion", speed: 10},
            two: {color: "#C3C48D", tooltip: "Apple", speed: 1},
            three: {color: "#7BB392"},
            four: {color: "#343738"}
        }
    );

If you don't pass anything on, a default orbit will just be shown. You can change the parameters color, tooltip and speed in the four orbits. For the chart itself you can disable the texture (true by default) and provide another CSS3 animation that's included with Pastel.

## Color tooltips

Color tooltips, or colour tooltips as the Brits insists, are not part of the Flot.js plugin. Luckily it's very easy to listen for hover on data points, so I wrote a small plugin ($.tooltipColor) which automatically makes a beautiful color tooltip based on the hovered series. You need to declare colors to every data set to make it work.

We make some random data:

    var d1 = [];
    for (var i = 0; i <= 10; i += 1)
        d1.push([i, parseInt(Math.random() * 250)]);

    var d2 = [];
    for (var i = 0; i <= 10; i += 1)
        d2.push([i, parseInt(Math.random() * 200)]);

    var d3 = [];
    for (var i = 0; i <= 10; i += 0.4)
        d3.push([i, parseInt(Math.random() * 140)]);

If you want to provide the data yourself, use the following pattern:

    var ownData = [ [0, 42], [1, 50], [2, 65] ];

Next we initialize the flot plugin:

    $.plot($("#chart_linear_stack"), [ { data: d1, label: "iPhone", color: "#333333" }, { data: d2, label: "iPad", color: "#3B8686" }, { data: d3, label: "Mac", color: "#79BD9A" } ], {
        series: {
           stack: stack,
           lines: { show: lines, fill: 0.8, steps: steps, clickable: true, lineWidth: 2 },
           bars: { show: bars, barWidth: 0.6 },
           points: { show: true }
        },
        grid: { hoverable: true }
    });

A nice looking chart should now appear. If you want to enable a color tooltip for that particular chart, simply apply this to your javascript:

    $("#chart_linear_stack").tooltipColor();

If you want to change the tooltip's label (the default is visitors) simply apply this:

    $("#chart_linear_stack").tooltipColor("devices");

Done deal! My little plugin actually creates a gradient with color shades a bit lighter and a bit darker together with a blurred and colored shadow.

Beside bringing some beautiful alpha transparent overlays into your charts, they have a useful purpose as well. Without colors, it can be difficult to distinguish data points close to each other.

## Included plugins

Whether you use the combined version of Pastel (where everything is in the app.js-file) or use the chart demo as a starting point, I've included a few plugins with the standard flot.js installation to minimize the number of HTTP requests:

- Curved lines
- Cross hair
- Fill between
- Navigation
- Pie charts
- Automatic resize
- Selection
- Stacked charts

# Flot Reference

Notice: This is the original flot.js documentation.

Consider a call to the plot function:

    var plot = $.plot(placeholder, data, options)

The placeholder is a jQuery object or DOM element or jQuery expression that the plot will be put into. This placeholder needs to have its width and height set as explained in the README (go read that now if you haven't, it's short). The plot will modify some properties of the placeholder so it's recommended you simply pass in a div that you don't use for anything else. Make sure you check any fancy styling you apply to the div, e.g. background images have been reported to be a problem on IE 7.

The format of the data is documented below, as is the available options. The plot object returned from the call has some methods you can call. These are documented separately below.

Note that in general Flot gives no guarantees if you change any of the objects you pass in to the plot function or get out of it since they're not necessarily deep-copied.

## Data Format

The data is an array of data series:

    [ series1, series2, ... ]

A series can either be raw data or an object with properties. The raw data format is an array of points:

    [ [x1, y1], [x2, y2], ... ]

E.g.

    [ [1, 3], [2, 14.01], [3.5, 3.14] ]

Note that to simplify the internal logic in Flot both the x and y values must be numbers (even if specifying time series, see below for how to do this). This is a common problem because you might retrieve data from the database and serialize them directly to JSON without noticing the wrong type. If you're getting mysterious errors, double check that you're inputting numbers and not strings.

If a null is specified as a point or if one of the coordinates is null or couldn't be converted to a number, the point is ignored when drawing. As a special case, a null value for lines is interpreted as a line segment end, i.e. the points before and after the null value are not connected.

Lines and points take two coordinates. For filled lines and bars, you can specify a third coordinate which is the bottom of the filled area/bar (defaults to 0).

The format of a single series object is as follows:

      {
        color: color or number
        data: rawdata
        label: string
        lines: specific lines options
        bars: specific bars options
        points: specific points options
        xaxis: number
        yaxis: number
        clickable: boolean
        hoverable: boolean
        shadowSize: number
      }

You don't have to specify any of them except the data, the rest are options that will get default values. Typically you'd only specify label and data, like this:

      {
        label: "y = 3",
        data: [[0, 3], [10, 3]]
      }

The label is used for the legend, if you don't specify one, the series will not show up in the legend.

If you don't specify color, the series will get a color from the auto-generated colors. The color is either a CSS color specification (like "rgb(255, 100, 123)") or an integer that specifies which of auto-generated colors to select, e.g. 0 will get color no. 0, etc.

The latter is mostly useful if you let the user add and remove series, in which case you can hard-code the color index to prevent the colors from jumping around between the series.

The "xaxis" and "yaxis" options specify which axis to use. The axes are numbered from 1 (default), so { yaxis: 2} means that the series should be plotted against the second y axis.

"clickable" and "hoverable" can be set to false to disable interactivity for specific series if interactivity is turned on in the plot, see below.

The rest of the options are all documented below as they are the same as the default options passed in via the options parameter in the plot commmand. When you specify them for a specific data series, they will override the default options for the plot for that data series.

Here's a complete example of a simple data specification:

      [ { label: "Foo", data: [ [10, 1], [17, -14], [30, 5] ] },
        { label: "Bar", data: [ [11, 13], [19, 11], [30, -7] ] } ]

## Plot Options

All options are completely optional. They are documented individually below, to change them you just specify them in an object, e.g.

      var options = {
        series: {
          lines: { show: true },
          points: { show: true }
        }
      };
      $.plot(placeholder, data, options);

## Customizing the legend

      legend: {
        show: boolean
        labelFormatter: null or (fn: string, series object -> string)
        labelBoxBorderColor: color
        noColumns: number
        position: "ne" or "nw" or "se" or "sw"
        margin: number of pixels or [x margin, y margin]
        backgroundColor: null or color
        backgroundOpacity: number between 0 and 1
        container: null or jQuery object/DOM element/jQuery expression
      }

The legend is generated as a table with the data series labels and small label boxes with the color of the series. If you want to format the labels in some way, e.g. make them to links, you can pass in a function for "labelFormatter". Here's an example that makes them clickable:

      labelFormatter: function(label, series) {
        // series is the series object for the label
        return '<a href="#' + label + '">' + label + '</a>';
      }

"noColumns" is the number of columns to divide the legend table into. "position" specifies the overall placement of the legend within the plot (top-right, top-left, etc.) and margin the distance to the plot edge (this can be either a number or an array of two numbers like [x, y]). "backgroundColor" and "backgroundOpacity" specifies the background. The default is a partly transparent auto-detected background.

If you want the legend to appear somewhere else in the DOM, you can specify "container" as a jQuery object/expression to put the legend table into. The "position" and "margin" etc. options will then be ignored. Note that Flot will overwrite the contents of the container.

## Customizing the axes

      xaxis, yaxis: {
        show: null or true/false
        position: "bottom" or "top" or "left" or "right"
        mode: null or "time"

        color: null or color spec
        tickColor: null or color spec

        min: null or number
        max: null or number
        autoscaleMargin: null or number

        transform: null or fn: number -> number
        inverseTransform: null or fn: number -> number

        ticks: null or number or ticks array or (fn: range -> ticks array)
        tickSize: number or array
        minTickSize: number or array
        tickFormatter: (fn: number, object -> string) or string
        tickDecimals: null or number

        labelWidth: null or number
        labelHeight: null or number
        reserveSpace: null or true

        tickLength: null or number

        alignTicksWithAxis: null or number
      }

All axes have the same kind of options. The following describes how to configure one axis, see below for what to do if you've got more than one x axis or y axis.

If you don't set the "show" option (i.e. it is null), visibility is auto-detected, i.e. the axis will show up if there's data associated with it. You can override this by setting the "show" option to true or false.

The "position" option specifies where the axis is placed, bottom or top for x axes, left or right for y axes. The "mode" option determines how the data is interpreted, the default of null means as decimal numbers. Use "time" for time series data, see the time series data section.

The "color" option determines the color of the labels and ticks for the axis (default is the grid color). For more fine-grained control you can also set the color of the ticks separately with "tickColor" (otherwise it's autogenerated as the base color with some transparency).

The options "min"/"max" are the precise minimum/maximum value on the scale. If you don't specify either of them, a value will automatically be chosen based on the minimum/maximum data values. Note that Flot always examines all the data values you feed to it, even if a restriction on another axis may make some of them invisible (this makes interactive use more stable).

The "autoscaleMargin" is a bit esoteric: it's the fraction of margin that the scaling algorithm will add to avoid that the outermost points ends up on the grid border. Note that this margin is only applied when a min or max value is not explicitly set. If a margin is specified, the plot will furthermore extend the axis end-point to the nearest whole tick. The default value is "null" for the x axes and 0.02 for y axes which seems appropriate for most cases.

"transform" and "inverseTransform" are callbacks you can put in to change the way the data is drawn. You can design a function to compress or expand certain parts of the axis non-linearly, e.g. suppress weekends or compress far away points with a logarithm or some other means. When Flot draws the plot, each value is first put through the transform function. Here's an example, the x axis can be turned into a natural logarithm axis with the following code:

      xaxis: {
        transform: function (v) { return Math.log(v); },
        inverseTransform: function (v) { return Math.exp(v); }
      }

Similarly, for reversing the y axis so the values appear in inverse order:

      yaxis: {
        transform: function (v) { return -v; },
        inverseTransform: function (v) { return -v; }
      }

Note that for finding extrema, Flot assumes that the transform function does not reorder values (it should be monotone).

The inverseTransform is simply the inverse of the transform function (so v == inverseTransform(transform(v)) for all relevant v). It is required for converting from canvas coordinates to data coordinates, e.g. for a mouse interaction where a certain pixel is clicked. If you don't use any interactive features of Flot, you may not need it.

The rest of the options deal with the ticks.

If you don't specify any ticks, a tick generator algorithm will make some for you. The algorithm has two passes. It first estimates how many ticks would be reasonable and uses this number to compute a nice round tick interval size. Then it generates the ticks.

You can specify how many ticks the algorithm aims for by setting "ticks" to a number. The algorithm always tries to generate reasonably round tick values so even if you ask for three ticks, you might get five if that fits better with the rounding. If you don't want any ticks at all, set "ticks" to 0 or an empty array.

Another option is to skip the rounding part and directly set the tick interval size with "tickSize". If you set it to 2, you'll get ticks at 2, 4, 6, etc. Alternatively, you can specify that you just don't want ticks at a size less than a specific tick size with "minTickSize". Note that for time series, the format is an array like [2, "month"], see the next section.

If you want to completely override the tick algorithm, you can specify an array for "ticks", either like this:

      ticks: [0, 1.2, 2.4]

Or like this where the labels are also customized:

      ticks: [[0, "zero"], [1.2, "one mark"], [2.4, "two marks"]]

You can mix the two if you like.

For extra flexibility you can specify a function as the "ticks" parameter. The function will be called with an object with the axis min and max and should return a ticks array. Here's a simplistic tick generator that spits out intervals of pi, suitable for use on the x axis for trigonometric functions:

      function piTickGenerator(axis) {
        var res = [], i = Math.floor(axis.min / Math.PI);
        do {
          var v = i * Math.PI;
          res.push([v, i + "\u03c0"]);
          ++i;
        } while (v < axis.max);

        return res;
      }

You can control how the ticks look like with "tickDecimals", the number of decimals to display (default is auto-detected).

Alternatively, for ultimate control over how ticks are formatted you can provide a function to "tickFormatter". The function is passed two parameters, the tick value and an axis object with information, and should return a string. The default formatter looks like this:

      function formatter(val, axis) {
        return val.toFixed(axis.tickDecimals);
      }

The axis object has "min" and "max" with the range of the axis, "tickDecimals" with the number of decimals to round the value to and "tickSize" with the size of the interval between ticks as calculated by the automatic axis scaling algorithm (or specified by you). Here's an example of a custom formatter:

      function suffixFormatter(val, axis) {
        if (val > 1000000)
          return (val / 1000000).toFixed(axis.tickDecimals) + " MB";
        else if (val > 1000)
          return (val / 1000).toFixed(axis.tickDecimals) + " kB";
        else
          return val.toFixed(axis.tickDecimals) + " B";
      }

"labelWidth" and "labelHeight" specifies a fixed size of the tick labels in pixels. They're useful in case you need to align several plots. "reserveSpace" means that even if an axis isn't shown, Flot should reserve space for it - it is useful in combination with labelWidth and labelHeight for aligning multi-axis charts.

"tickLength" is the length of the tick lines in pixels. By default, the innermost axes will have ticks that extend all across the plot, while any extra axes use small ticks. A value of null means use the default, while a number means small ticks of that length - set it to 0 to hide the lines completely.

If you set "alignTicksWithAxis" to the number of another axis, e.g. alignTicksWithAxis: 1, Flot will ensure that the autogenerated ticks of this axis are aligned with the ticks of the other axis. This may improve the looks, e.g. if you have one y axis to the left and one to the right, because the grid lines will then match the ticks in both ends. The trade-off is that the forced ticks won't necessarily be at natural places.

## Multiple axes

If you need more than one x axis or y axis, you need to specify for each data series which axis they are to use, as described under the format of the data series, e.g. { data: [...], yaxis: 2 } specifies that a series should be plotted against the second y axis.

To actually configure that axis, you can't use the xaxis/yaxis options directly - instead there are two arrays in the options:

       xaxes: []
       yaxes: []

Here's an example of configuring a single x axis and two y axes (we can leave options of the first y axis empty as the defaults are fine):

      {
        xaxes: [ { position: "top" } ],
        yaxes: [ { }, { position: "right", min: 20 } ]
      }

The arrays get their default values from the xaxis/yaxis settings, so say you want to have all y axes start at zero, you can simply specify yaxis: { min: 0 } instead of adding a min parameter to all the axes.

Generally, the various interfaces in Flot dealing with data points either accept an xaxis/yaxis parameter to specify which axis number to use (starting from 1), or lets you specify the coordinate directly as x2/x3/... or x2axis/x3axis/... instead of "x" or "xaxis".

## Time series data

Time series are a bit more difficult than scalar data because calendars don't follow a simple base 10 system. For many cases, Flot abstracts most of this away, but it can still be a bit difficult to get the data into Flot. So we'll first discuss the data format.

The time series support in Flot is based on Javascript timestamps, i.e. everywhere a time value is expected or handed over, a Javascript timestamp number is used. This is a number, not a Date object. A Javascript timestamp is the number of milliseconds since January 1, 1970 00:00:00 UTC. This is almost the same as Unix timestamps, except it's in milliseconds, so remember to multiply by 1000!

You can see a timestamp like this

      alert((new Date()).getTime())

Normally you want the timestamps to be displayed according to a certain time zone, usually the time zone in which the data has been produced. However, Flot always displays timestamps according to UTC. It has to as the only alternative with core Javascript is to interpret the timestamps according to the time zone that the visitor is in, which means that the ticks will shift unpredictably with the time zone and daylight savings of each visitor.

So given that there's no good support for custom time zones in Javascript, you'll have to take care of this server-side.

The easiest way to think about it is to pretend that the data production time zone is UTC, even if it isn't. So if you have a datapoint at 2002-02-20 08:00, you can generate a timestamp for eight o'clock UTC even if it really happened eight o'clock UTC+0200.

In PHP you can get an appropriate timestamp with `strtotime("2002-02-20 UTC") * 1000`, in Python with `calendar.timegm(datetime_object.timetuple()) * 1000`, in .NET with something like:

      public static int GetJavascriptTimestamp(System.DateTime input)
      {
        System.TimeSpan span = new System.TimeSpan(System.DateTime.Parse("1/1/1970").Ticks);
        System.DateTime time = input.Subtract(span);
        return (long)(time.Ticks / 10000);
      }

Javascript also has some support for parsing date strings, so it is possible to generate the timestamps manually client-side.

If you've already got the real UTC timestamp, it's too late to use the pretend trick described above. But you can fix up the timestamps by adding the time zone offset, e.g. for UTC+0200 you would add 2 hours to the UTC timestamp you got. Then it'll look right on the plot. Most programming environments have some means of getting the timezone offset for a specific date (note that you need to get the offset for each individual timestamp to account for daylight savings).

Once you've gotten the timestamps into the data and specified "time" as the axis mode, Flot will automatically generate relevant ticks and format them. As always, you can tweak the ticks via the "ticks" option - just remember that the values should be timestamps (numbers), not Date objects.

Tick generation and formatting can also be controlled separately through the following axis options:

      minTickSize: array
      timeformat: null or format string
      monthNames: null or array of size 12 of strings
      twelveHourClock: boolean

Here "timeformat" is a format string to use. You might use it like this:

      xaxis: {
        mode: "time"
        timeformat: "%y/%m/%d"
      }

This will result in tick labels like "2000/12/24". The following specifiers are supported

      %h: hours
      %H: hours (left-padded with a zero)
      %M: minutes (left-padded with a zero)
      %S: seconds (left-padded with a zero)
      %d: day of month (1-31), use %0d for zero-padding
      %m: month (1-12), use %0m for zero-padding
      %y: year (four digits)
      %b: month name (customizable)
      %p: am/pm, additionally switches %h/%H to 12 hour instead of 24
      %P: AM/PM (uppercase version of %p)

Inserting a zero like %0m or %0d means that the specifier will be left-padded with a zero if it's only single-digit. So %y-%0m-%0d results in unambigious ISO timestamps like 2007-05-10 (for May 10th).

You can customize the month names with the "monthNames" option. For instance, for Danish you might specify:

      monthNames: ["jan", "feb", "mar", "apr", "maj", "jun", "jul", "aug", "sep", "okt", "nov", "dec"]

If you set "twelveHourClock" to true, the autogenerated timestamps will use 12 hour AM/PM timestamps instead of 24 hour.

The format string and month names are used by a very simple built-in format function that takes a date object, a format string (and optionally an array of month names) and returns the formatted string. If needed, you can access it as $.plot.formatDate(date, formatstring, monthNames) or even replace it with another more advanced function from a date library if you're feeling adventurous.

If everything else fails, you can control the formatting by specifying a custom tick formatter function as usual. Here's a simple example which will format December 24 as 24/12:

      tickFormatter: function (val, axis) {
        var d = new Date(val);
        return d.getUTCDate() + "/" + (d.getUTCMonth() + 1);
      }

Note that for the time mode "tickSize" and "minTickSize" are a bit special in that they are arrays on the form "[value, unit]" where unit is one of "second", "minute", "hour", "day", "month" and "year". So you can specify

      minTickSize: [1, "month"]

to get a tick interval size of at least 1 month and correspondingly, if axis.tickSize is [2, "day"] in the tick formatter, the ticks have been produced with two days in-between.

## Customizing the data series

      series: {
        lines, points, bars: {
          show: boolean
          lineWidth: number
          fill: boolean or number
          fillColor: null or color/gradient
        }

        points: {
          radius: number
          symbol: "circle" or function
        }

        bars: {
          barWidth: number
          align: "left" or "center"
          horizontal: boolean
        }

        lines: {
          steps: boolean
        }

        shadowSize: number
      }

      colors: [ color1, color2, ... ]

The options inside "series: {}" are copied to each of the series. So you can specify that all series should have bars by putting it in the global options, or override it for individual series by specifying bars in a particular the series object in the array of data.

The most important options are "lines", "points" and "bars" that specify whether and how lines, points and bars should be shown for each data series. In case you don't specify anything at all, Flot will default to showing lines (you can turn this off with lines: { show: false }). You can specify the various types independently of each other, and Flot will happily draw each of them in turn (this is probably only useful for lines and points), e.g.

      var options = {
        series: {
          lines: { show: true, fill: true, fillColor: "rgba(255, 255, 255, 0.8)" },
          points: { show: true, fill: false }
        }
      };

"lineWidth" is the thickness of the line or outline in pixels. You can set it to 0 to prevent a line or outline from being drawn; this will also hide the shadow.

"fill" is whether the shape should be filled. For lines, this produces area graphs. You can use "fillColor" to specify the color of the fill. If "fillColor" evaluates to false (default for everything except points which are filled with white), the fill color is auto-set to the color of the data series. You can adjust the opacity of the fill by setting fill to a number between 0 (fully transparent) and 1 (fully opaque).

For bars, fillColor can be a gradient, see the gradient documentation below. "barWidth" is the width of the bars in units of the x axis (or the y axis if "horizontal" is true), contrary to most other measures that are specified in pixels. For instance, for time series the unit is milliseconds so 24 * 60 * 60 * 1000 produces bars with the width of a day. "align" specifies whether a bar should be left-aligned (default) or centered on top of the value it represents. When "horizontal" is on, the bars are drawn horizontally, i.e. from the y axis instead of the x axis; note that the bar end points are still defined in the same way so you'll probably want to swap the coordinates if you've been plotting vertical bars first.

For lines, "steps" specifies whether two adjacent data points are connected with a straight (possibly diagonal) line or with first a horizontal and then a vertical line. Note that this transforms the data by adding extra points.

For points, you can specify the radius and the symbol. The only built-in symbol type is circles, for other types you can use a plugin or define them yourself by specifying a callback:

      function cross(ctx, x, y, radius, shadow) {
          var size = radius * Math.sqrt(Math.PI) / 2;
          ctx.moveTo(x - size, y - size);
          ctx.lineTo(x + size, y + size);
          ctx.moveTo(x - size, y + size);
          ctx.lineTo(x + size, y - size);
      }

The parameters are the drawing context, x and y coordinates of the center of the point, a radius which corresponds to what the circle would have used and whether the call is to draw a shadow (due to limited canvas support, shadows are currently faked through extra draws). It's good practice to ensure that the area covered by the symbol is the same as for the circle with the given radius, this ensures that all symbols have approximately the same visual weight.

"shadowSize" is the default size of shadows in pixels. Set it to 0 to remove shadows.

The "colors" array specifies a default color theme to get colors for the data series from. You can specify as many colors as you like, like this:

      colors: ["#d18b2c", "#dba255", "#919733"]

If there are more data series than colors, Flot will try to generate extra colors by lightening and darkening colors in the theme.

## Customizing the grid

      grid: {
        show: boolean
        aboveData: boolean
        color: color
        backgroundColor: color/gradient or null
        labelMargin: number
        axisMargin: number
        markings: array of markings or (fn: axes -> array of markings)
        borderWidth: number
        borderColor: color or null
        minBorderMargin: number or null
        clickable: boolean
        hoverable: boolean
        autoHighlight: boolean
        mouseActiveRadius: number
      }

The grid is the thing with the axes and a number of ticks. Many of the things in the grid are configured under the individual axes, but not all. "color" is the color of the grid itself whereas "backgroundColor" specifies the background color inside the grid area, here null means that the background is transparent. You can also set a gradient, see the gradient documentation below.

You can turn off the whole grid including tick labels by setting "show" to false. "aboveData" determines whether the grid is drawn above the data or below (below is default).

"labelMargin" is the space in pixels between tick labels and axis line, and "axisMargin" is the space in pixels between axes when there are two next to each other. Note that you can style the tick labels with CSS, e.g. to change the color. They have class "tickLabel".

"borderWidth" is the width of the border around the plot. Set it to 0 to disable the border. You can also set "borderColor" if you want the border to have a different color than the grid lines. "minBorderMargin" controls the default minimum margin around the border - it's used to make sure that points aren't accidentally clipped by the canvas edge so by default the value is computed from the point radius.

"markings" is used to draw simple lines and rectangular areas in the background of the plot. You can either specify an array of ranges on the form { xaxis: { from, to }, yaxis: { from, to } } (with multiple axes, you can specify coordinates for other axes instead, e.g. as x2axis/x3axis/...) or with a function that returns such an array given the axes for the plot in an object as the first parameter.

You can set the color of markings by specifying "color" in the ranges object. Here's an example array:

      markings: [ { xaxis: { from: 0, to: 2 }, yaxis: { from: 10, to: 10 }, color: "#bb0000" }, ... ]

If you leave out one of the values, that value is assumed to go to the border of the plot. So for example if you only specify { xaxis: { from: 0, to: 2 } } it means an area that extends from the top to the bottom of the plot in the x range 0-2.

A line is drawn if from and to are the same, e.g.

      markings: [ { yaxis: { from: 1, to: 1 } }, ... ]

would draw a line parallel to the x axis at y = 1. You can control the line width with "lineWidth" in the range object.

An example function that makes vertical stripes might look like this:

      markings: function (axes) {
        var markings = [];
        for (var x = Math.floor(axes.xaxis.min); x < axes.xaxis.max; x += 2)
          markings.push({ xaxis: { from: x, to: x + 1 } });
        return markings;
      }

If you set "clickable" to true, the plot will listen for click events on the plot area and fire a "plotclick" event on the placeholder with a position and a nearby data item object as parameters. The coordinates are available both in the unit of the axes (not in pixels) and in global screen coordinates.

Likewise, if you set "hoverable" to true, the plot will listen for mouse move events on the plot area and fire a "plothover" event with the same parameters as the "plotclick" event. If "autoHighlight" is true (the default), nearby data items are highlighted automatically. If needed, you can disable highlighting and control it yourself with the highlight/unhighlight plot methods described elsewhere.

You can use "plotclick" and "plothover" events like this:

    $.plot($("#placeholder"), [ d ], { grid: { clickable: true } });

    $("#placeholder").bind("plotclick", function (event, pos, item) {
        alert("You clicked at " + pos.x + ", " + pos.y);
        // axis coordinates for other axes, if present, are in pos.x2, pos.x3, ...
        // if you need global screen coordinates, they are pos.pageX, pos.pageY

        if (item) {
          highlight(item.series, item.datapoint);
          alert("You clicked a point!");
        }
    });

The item object in this example is either null or a nearby object on the form:

      item: {
          datapoint: the point, e.g. [0, 2]
          dataIndex: the index of the point in the data array
          series: the series object
          seriesIndex: the index of the series
          pageX, pageY: the global screen coordinates of the point
      }

For instance, if you have specified the data like this

    $.plot($("#placeholder"), [ { label: "Foo", data: [[0, 10], [7, 3]] } ], ...);

and the mouse is near the point (7, 3), "datapoint" is [7, 3], "dataIndex" will be 1, "series" is a normalized series object with among other things the "Foo" label in series.label and the color in series.color, and "seriesIndex" is 0. Note that plugins and options that transform the data can shift the indexes from what you specified in the original data array.

If you use the above events to update some other information and want to clear out that info in case the mouse goes away, you'll probably also need to listen to "mouseout" events on the placeholder div.

"mouseActiveRadius" specifies how far the mouse can be from an item and still activate it. If there are two or more points within this radius, Flot chooses the closest item. For bars, the top-most bar (from the latest specified data series) is chosen.

If you want to disable interactivity for a specific data series, you can set "hoverable" and "clickable" to false in the options for that series, like this { data: [...], label: "Foo", clickable: false }.

## Specifying gradients

A gradient is specified like this:

      { colors: [ color1, color2, ... ] }

For instance, you might specify a background on the grid going from black to gray like this:

      grid: {
        backgroundColor: { colors: ["#000", "#999"] }
      }

For the series you can specify the gradient as an object that specifies the scaling of the brightness and the opacity of the series color, e.g.

      { colors: [{ opacity: 0.8 }, { brightness: 0.6, opacity: 0.8 } ] }

where the first color simply has its alpha scaled, whereas the second is also darkened. For instance, for bars the following makes the bars gradually disappear, without outline:

      bars: {
          show: true,
          lineWidth: 0,
          fill: true,
          fillColor: { colors: [ { opacity: 0.8 }, { opacity: 0.1 } ] }
      }

Flot currently only supports vertical gradients drawn from top to bottom because that's what works with IE.

## Plot Methods

The Plot object returned from the plot function has some methods you can call:

- highlight(series, datapoint)

  Highlight a specific datapoint in the data series. You can either specify the actual objects, e.g. if you got them from a "plotclick" event, or you can specify the indices, e.g. highlight(1, 3) to highlight the fourth point in the second series (remember, zero-based indexing).

- unhighlight(series, datapoint) or unhighlight()

  Remove the highlighting of the point, same parameters as highlight.

  If you call unhighlight with no parameters, e.g. as plot.unhighlight(), all current highlights are removed.

- setData(data)

  You can use this to reset the data used. Note that axis scaling, ticks, legend etc. will not be recomputed (use setupGrid() to do that). You'll probably want to call draw() afterwards.

  You can use this function to speed up redrawing a small plot if you know that the axes won't change. Put in the new data with setData(newdata), call draw(), and you're good to go. Note that for large datasets, almost all the time is consumed in draw() plotting the data so in this case don't bother.

- setupGrid()

  Recalculate and set axis scaling, ticks, legend etc.

  Note that because of the drawing model of the canvas, this function will immediately redraw (actually reinsert in the DOM) the labels and the legend, but not the actual tick lines because they're drawn on the canvas. You need to call draw() to get the canvas redrawn.

- draw()

  Redraws the plot canvas.

- triggerRedrawOverlay()

  Schedules an update of an overlay canvas used for drawing interactive things like a selection and point highlights. This is mostly useful for writing plugins. The redraw doesn't happen immediately, instead a timer is set to catch multiple successive redraws (e.g. from a mousemove). You can get to the overlay by setting up a drawOverlay hook.

- width()/height()

  Gets the width and height of the plotting area inside the grid. This is smaller than the canvas or placeholder dimensions as some extra space is needed (e.g. for labels).

- offset()

  Returns the offset of the plotting area inside the grid relative to the document, useful for instance for calculating mouse positions (event.pageX/Y minus this offset is the pixel position inside the plot).

- pointOffset({ x: xpos, y: ypos })

  Returns the calculated offset of the data point at (x, y) in data space within the placeholder div. If you are working with multiple axes, you can specify the x and y axis references, e.g.

  `o = pointOffset({ x: xpos, y: ypos, xaxis: 2, yaxis: 3 })
  // o.left and o.top now contains the offset within the div`

- resize()

  Tells Flot to resize the drawing canvas to the size of the placeholder. You need to run setupGrid() and draw() afterwards as canvas resizing is a destructive operation. This is used internally by the resize plugin.

- shutdown()

  Cleans up any event handlers Flot has currently registered. This is used internally.

There are also some members that let you peek inside the internal workings of Flot which is useful in some cases. Note that if you change something in the objects returned, you're changing the objects used by Flot to keep track of its state, so be careful.

- getData()

  Returns an array of the data series currently used in normalized form with missing settings filled in according to the global options. So for instance to find out what color Flot has assigned to the data series, you could do this:

  `var series = plot.getData();
  for (var i = 0; i < series.length; ++i)
  alert(series[i].color);`

  A notable other interesting field besides color is datapoints which has a field "points" with the normalized data points in a flat array (the field "pointsize" is the increment in the flat array to get to the next point so for a dataset consisting only of (x,y) pairs it would be 2).

- getAxes()

  Gets an object with the axes. The axes are returned as the attributes of the object, so for instance getAxes().xaxis is the x axis.

  Various things are stuffed inside an axis object, e.g. you could use getAxes().xaxis.ticks to find out what the ticks are for the xaxis. Two other useful attributes are p2c and c2p, functions for transforming from data point space to the canvas plot space and back. Both returns values that are offset with the plot offset. Check the Flot source code for the complete set of attributes (or output an axis with console.log() and inspect it).

  With multiple axes, the extra axes are returned as x2axis, x3axis, etc., e.g. getAxes().y2axis is the second y axis. You can check y2axis.used to see whether the axis is associated with any data points and y2axis.show to see if it is currently shown.

- getPlaceholder()

  Returns placeholder that the plot was put into. This can be useful for plugins for adding DOM elements or firing events.

- getCanvas()

  Returns the canvas used for drawing in case you need to hack on it yourself. You'll probably need to get the plot offset too.

- getPlotOffset()

  Gets the offset that the grid has within the canvas as an object with distances from the canvas edges as "left", "right", "top", "bottom". I.e., if you draw a circle on the canvas with the center placed at (left, top), its center will be at the top-most, left corner of the grid.

- getOptions()

  Gets the options for the plot, normalized, with default values filled in. You get a reference to actual values used by Flot, so if you modify the values in here, Flot will use the new values. If you change something, you probably have to call draw() or setupGrid() or triggerRedrawOverlay() to see the change.

## Hooks

In addition to the public methods, the Plot object also has some hooks that can be used to modify the plotting process. You can install a callback function at various points in the process, the function then gets access to the internal data structures in Flot.

Here's an overview of the phases Flot goes through:

1. Plugin initialization, parsing options
2. Constructing the canvases used for drawing
3. Set data: parsing data specification, calculating colors, copying raw data points into internal format, normalizing them, finding max/min for axis auto-scaling
4. Grid setup: calculating axis spacing, ticks, inserting tick labels, the legend
5. Draw: drawing the grid, drawing each of the series in turn
6. Setting up event handling for interactive features
7. Responding to events, if any
8. Shutdown: this mostly happens in case a plot is overwritten

Each hook is simply a function which is put in the appropriate array. You can add them through the "hooks" option, and they are also available after the plot is constructed as the "hooks" attribute on the returned plot object, e.g.

      // define a simple draw hook
      function hellohook(plot, canvascontext) { alert("hello!"); };

      // pass it in, in an array since we might want to specify several
      var plot = $.plot(placeholder, data, { hooks: { draw: [hellohook] } });

      // we can now find it again in plot.hooks.draw[0] unless a plugin
      // has added other hooks

The available hooks are described below. All hook callbacks get the plot object as first parameter. You can find some examples of defined hooks in the plugins bundled with Flot.

### processOptions [phase 1]

    function(plot, options)

Called after Flot has parsed and merged options. Useful in the instance where customizations beyond simple merging of default values is needed. A plugin might use it to detect that it has been enabled and then turn on or off other options.

### processRawData [phase 3]

    function(plot, series, data, datapoints)

Called before Flot copies and normalizes the raw data for the given series. If the function fills in datapoints.points with normalized points and sets datapoints.pointsize to the size of the points, Flot will skip the copying/normalization step for this series.

In any case, you might be interested in setting datapoints.format, an array of objects for specifying how a point is normalized and how it interferes with axis scaling.

The default format array for points is something along the lines of:

    [
         { x: true, number: true, required: true },
         { y: true, number: true, required: true }
    ]

The first object means that for the first coordinate it should be taken into account when scaling the x axis, that it must be a number, and that it is required - so if it is null or cannot be converted to a number, the whole point will be zeroed out with nulls. Beyond these you can also specify "defaultValue", a value to use if the coordinate is null. This is for instance handy for bars where one can omit the third coordinate (the bottom of the bar) which then defaults to 0.

### processDatapoints [phase 3]

    function(plot, series, datapoints)

Called after normalization of the given series but before finding min/max of the data points. This hook is useful for implementing data transformations. "datapoints" contains the normalized data points in a flat array as datapoints.points with the size of a single point given in datapoints.pointsize. Here's a simple transform that multiplies all y coordinates by 2:

    function multiply(plot, series, datapoints) {
        var points = datapoints.points, ps = datapoints.pointsize;
        for (var i = 0; i < points.length; i += ps)
        points[i + 1] *= 2;
    }

Note that you must leave datapoints in a good condition as Flot doesn't check it or do any normalization on it afterwards.

### drawSeries [phase 5]

    function(plot, canvascontext, series)

Hook for custom drawing of a single series. Called just before the standard drawing routine has been called in the loop that draws each series.

### draw [phase 5]

    function(plot, canvascontext)

Hook for drawing on the canvas. Called after the grid is drawn (unless it's disabled or grid.aboveData is set) and the series have been plotted (in case any points, lines or bars have been turned on). For examples of how to draw things, look at the source code.

### bindEvents [phase 6]

    function(plot, eventHolder)

Called after Flot has setup its event handlers. Should set any necessary event handlers on eventHolder, a jQuery object with the canvas, e.g.

    function (plot, eventHolder) {
        eventHolder.mousedown(function (e) {
            alert("You pressed the mouse at " + e.pageX + " " + e.pageY);
        });
    }

Interesting events include click, mousemove, mouseup/down. You can use all jQuery events. Usually, the event handlers will update the state by drawing something (add a drawOverlay hook and call triggerRedrawOverlay) or firing an externally visible event for user code. See the crosshair plugin for an example.

Currently, eventHolder actually contains both the static canvas used for the plot itself and the overlay canvas used for interactive features because some versions of IE get the stacking order wrong. The hook only gets one event, though (either for the overlay or for the static canvas).

Note that custom plot events generated by Flot are not generated on eventHolder, but on the div placeholder supplied as the first argument to the plot call. You can get that with plot.getPlaceholder() - that's probably also the one you should use if you need to fire a custom event.

### drawOverlay [phase 7]

    function (plot, canvascontext)

The drawOverlay hook is used for interactive things that need a canvas to draw on. The model currently used by Flot works the way that an extra overlay canvas is positioned on top of the static canvas. This overlay is cleared and then completely redrawn whenever something interesting happens. This hook is called when the overlay canvas is to be redrawn.

"canvascontext" is the 2D context of the overlay canvas. You can use this to draw things. You'll most likely need some of the metrics computed by Flot, e.g. plot.width()/plot.height(). See the crosshair plugin for an example.

### shutdown [phase 8]

    function (plot, eventHolder)

Run when plot.shutdown() is called, which usually only happens in case a plot is overwritten by a new plot. If you're writing a plugin that adds extra DOM elements or event handlers, you should add a callback to clean up after you. Take a look at the section in PLUGINS.txt for more info.

## Plugins

Plugins extend the functionality of Flot. To use a plugin, simply include its Javascript file after Flot in the HTML page.

If you're worried about download size/latency, you can concatenate all the plugins you use, and Flot itself for that matter, into one big file (make sure you get the order right), then optionally run it through a Javascript minifier such as YUI Compressor.

Here's a brief explanation of how the plugin plumbings work:

Each plugin registers itself in the global array $.plot.plugins. When you make a new plot object with $.plot, Flot goes through this array calling the "init" function of each plugin and merging default options from the "option" attribute of the plugin. The init function gets a reference to the plot object created and uses this to register hooks and add new public methods if needed.

See the PLUGINS.txt file for details on how to write a plugin. As the above description hints, it's actually pretty easy.

## Version number

The version number of Flot is available in $.plot.version.