Plots can be embedded in Baysig documents generated on BayesHive. To generate a plot, put a value of a
Plot type in a question block, for instance:
Here is my plot ?> distPlot (normal 0 1) Thanks for watching!
In the following sections, we describe the different ways to create and manipulate Plot values.
There are a number of functions that take data of different types and turn them into plots
distPlot takes a distribution over real numbers and returns a histogram plot.
The hitogram plots give you a small input control to set the number of bins. This can be dynamically changed by the user.
distPlot (normal 0 1)
histogram takes a list of numbers (real or integers) as its argument and returns a histogram plot
fromTo 1 10 ⇒ [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
histogram (fromTo 1 10)
scatterPlot takes a list of pairs of numbers (either of which can be real or integers) and creates a scatter plot using the pairs as coordinates (as is conventional, the first pair component is plotted on the x-axis and the second on the y-axis).
xyData = zipWithNats (linspace 0 10 8) 1
xyData ⇒ [(1,0.0000), (2,1.2500), (3,2.5000), (4,3.7500), (5,5.0000), (6,6.2500), (7,7.5000), (8,8.7500)]
sigPlot plots a timeseries from a value of type
We Solve a simple differential equation to generate data for this example, but you can also use uploaded timeseries.
dt = 0.1 tmax = 10 s_0 = 1.0 D s t = - s t
psigPlot is the probabilistic equivalent of
sigPlot which takes a probability distribution over timeseries instead of a single value. Let's plot the
wiener distribution over Wiener processes:
As you can see, it draws a number of samples from the probability distribution. You ca change the number of samples drawn by using
psigNPlot 10 wiener
If you plot a lot of signals this way, your browser will feel very slow.
ppoints is the probabilistic equivalent of
scatterPlot. It takes a probability distribution over list of pairs.
ppoints does the same thing, but draws lines between the points. We will a suitable value here to illustrate:
myRandomPoints = prob xs = linspace 0 1 10 ys ~ mapM (\x -> normal x 0.1) xs return (zip xs ys)
PlotRow  [ppoints myRandomPoints, plines myRandomPoints]
This is pur first example of multi-panel plots, which will be described below.
There are a number of function that modify fundamental plots.
over superimposes a list of plots on a single plot with a single set of axes.
over [scatterPlot xyData, sigPlot s]
axisLabels sets the plot x axis label (first argument) and y axis label (second argument) on the plot which is its third argument
axisLabels "cheese" "potato" (scatterPlot xyData)
style allows you to specify the styles that correspond to Radian style properties. These are specified as a list of string-string pairs.
style [("marker", "square"), ("fill", "red")] (scatterPlot xyData)
PlotColumn can be used to nest plots. Both take an initial argument with is a list of style properties for that whole sub-plot.
PlotRow  [ppoints myRandomPoints, PlotColumn  [scatterPlot xyData, distPlot (normal 0 1)]]