EPSIAE » eneraptor

Flot Reference

--------------

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 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 bars, you can specify a

third coordinate which is the bottom of the 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: 1 or 2

    yaxis: 1 or 2

    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, specify 2

to get the secondary axis (x axis at top or y axis to the right).

E.g., you can use this to make a dual axis plot by specifying

{ yaxis: 2 } for one data series.

"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, x2axis, y2axis: {

    mode: null or "time"

    min: null or number

    max: null or number

    autoscaleMargin: null or number

    labelWidth: null or number

    labelHeight: 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

  }

All axes have the same kind of options. 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 next section.

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.

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 axis and

0.02 for the y axis which seems appropriate for most cases.

"labelWidth" and "labelHeight" specifies a fixed size of the tick

labels in pixels. They're useful in case you need to align several

plots.

"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); }

  }

Note that for finding extrema, Flot assumes that the transform

function does not reorder values (monotonicity is assumed).

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 look like 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";

  }

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)

  %m: month (1-12)

  %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)

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

    }

    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.

"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

    tickColor: color

    labelMargin: number

    markings: array of markings or (fn: axes -> array of markings)

    borderWidth: number

    borderColor: color or null

    clickable: boolean

    hoverable: boolean

    autoHighlight: boolean

    mouseActiveRadius: number

  }

The grid is the thing with the axes and a number of ticks. "color" is

the color of the grid itself whereas "backgroundColor" specifies the

background color inside the grid area. The default value of 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 on

above the data or below (below is default).

"tickColor" is the color of the ticks and "labelMargin" is the spacing

between tick labels and the grid. 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.

"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 } } (secondary axis

coordinates with x2axis/y2axis) 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 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);

        // secondary axis coordinates if present are in pos.x2, pos.y2,

        // 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).

  - 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 dual axes, you

    can specify the x and y axis references, e.g. 

      o = pointOffset({ x: xpos, y: ypos, xaxis: 2, yaxis: 2 })

      // o.left and o.top now contains the offset within the div

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 settings as { xaxis, yaxis, x2axis,

    y2axis }.

    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.

  - 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, in a normalized format with default

    values filled in.

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

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.

 - draw  [phase 5]

   function(plot, canvascontext)

   Hook for drawing on the canvas. Called after the grid is drawn

   (unless it's disabled) 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).

 - 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.

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 its "option" attribute. 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.