Classes of histogram plots
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|Mandatory||List of arithmetical expressions|
|Objects||Cells Default Values|
Cells determines the number and position
of the classes used in a histogram.
Cells accepts either a single positive integer
(or, equivalently, a list of one positive integer) or a list of cells
given as ranges or lists of two elements.
A single integer n in
Cells = n or
[n] is interpreted as “subdivide the range of data
into n cells
of equal size.”
The number n can be animated. In this case, n may be a symbolic expression of the animation parameter.
The cells may be specified directly as in
Cells = [[a1,
b1], [a2, b2],
Cells = [a_1..b_1, a_2..b_2, Symbol::dots].
The i-th cell is the semi-open interval , i.e., a datum x is tallied into the i-th cell if ai < x ≤ bi is satisfied.
The cell boundaries must satisfy a1 < b1 ≤ a2 < b2 ≤ a3 < …. In most applications, b1 = a2, b2 = a3 etc. is appropriate.
If giving cells directly, the leftmost border may be
infinity and the rightmost border may be
infinity. These rectangles
will then be adjusted according to the average widths of the other
rectangles for display purposes.
With the attribute
[a_1..b_1, a_2..b_2, Symbol::dots] are
interpreted as the semi-open intervals .
We create a sample of 1000 data points and plot a histogram of them:
X := stats::fRandom(100, 10): data := [X() $ i = 1..1000]: plot(plot::Histogram2d(data))
The shape of the distribution becomes much better visible when we increase the number of cells:
plot(plot::Histogram2d(data, Cells = 40))
plot(plot::Histogram2d(data, Cells = , Area = 1), plot::Function2d(stats::fPDF(100,10)(x), x = 0 .. 5, Color = RGB::Black))
With cells of different widths, setting
Area to a positive value
is highly recommended, to still have the histogram follow the probability
cells := stats::equiprobableCells(50, stats::fQuantile(100, 10))
plot(plot::Histogram2d(data, Cells = cells)):
plot(plot::Histogram2d(data, Cells = cells, Area = 1), plot::Function2d(stats::fPDF(100, 10)(x), x = 0 .. 5, Color = RGB::Black))