smile

# plot

#### package plot

Data visualization.

Linear Supertypes
Operators, AnyRef, Any
Ordering
1. Alphabetic
2. By Inheritance
Inherited
1. plot
2. Operators
3. AnyRef
4. Any
1. Hide All
2. Show All
Visibility
1. Public
2. All

### Type Members

1. #### trait Operators extends AnyRef

Data visualization operators.

### Value Members

2. #### def boxplot(data: Array[Array[Double]], labels: Array[String]): Window

Box plot.

Box plot.

data

a data matrix of which each row will create a box plot.

labels

the labels for each box plot.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
3. #### def boxplot(data: Array[Double]*): Window

A box plot is a convenient way of graphically depicting groups of numerical data through their five-number summaries (the smallest observation (sample minimum), lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation (sample maximum).

A box plot is a convenient way of graphically depicting groups of numerical data through their five-number summaries (the smallest observation (sample minimum), lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation (sample maximum). A box plot may also indicate which observations, if any, might be considered outliers.

Box plots can be useful to display differences between populations without making any assumptions of the underlying statistical distribution: they are non-parametric. The spacings between the different parts of the box help indicate the degree of dispersion (spread) and skewness in the data, and identify outliers.

For a data set, we construct a boxplot in the following manner:

• Calculate the first q1, the median q2 and third quartile q3. - Calculate the interquartile range (IQR) by subtracting the first quartile from the third quartile. (q3 ? q1)
• Construct a box above the number line bounded on the bottom by the first quartile (q1) and on the top by the third quartile (q3).
• Indicate where the median lies inside of the box with the presence of a line dividing the box at the median value.
• Any data observation which lies more than 1.5*IQR lower than the first quartile or 1.5IQR higher than the third quartile is considered an outlier. Indicate where the smallest value that is not an outlier is by connecting it to the box with a horizontal line or "whisker". Optionally, also mark the position of this value more clearly using a small vertical line. Likewise, connect the largest value that is not an outlier to the box by a "whisker" (and optionally mark it with another small vertical line).
• Indicate outliers by dots.
data

a data matrix of which each row will create a box plot.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
4. #### def contour(x: Array[Double], y: Array[Double], z: Array[Array[Double]], levels: Array[Double], palette: Array[Color]): Window

Contour plot.

Contour plot. A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format. That is, given a value for z, lines are drawn for connecting the (x, y) coordinates where that z value occurs. The contour plot is an alternative to a 3-D surface plot.

x

the x coordinates of the data grid of z. Must be in ascending order.

y

the y coordinates of the data grid of z. Must be in ascending order.

z

the data matrix to create contour plot.

levels

the level values of contours.

palette

the color for each contour level.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
5. #### def contour(x: Array[Double], y: Array[Double], z: Array[Array[Double]]): Window

Contour plot.

Contour plot. A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format. That is, given a value for z, lines are drawn for connecting the (x, y) coordinates where that z value occurs. The contour plot is an alternative to a 3-D surface plot.

x

the x coordinates of the data grid of z. Must be in ascending order.

y

the y coordinates of the data grid of z. Must be in ascending order.

z

the data matrix to create contour plot.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
6. #### def contour(z: Array[Array[Double]], levels: Array[Double], palette: Array[Color]): Window

Contour plot.

Contour plot. A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format. That is, given a value for z, lines are drawn for connecting the (x, y) coordinates where that z value occurs. The contour plot is an alternative to a 3-D surface plot.

z

the data matrix to create contour plot.

levels

the level values of contours.

palette

the color for each contour level.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
7. #### def contour(z: Array[Array[Double]]): Window

Contour plot.

Contour plot. A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format. That is, given a value for z, lines are drawn for connecting the (x, y) coordinates where that z value occurs. The contour plot is an alternative to a 3-D surface plot.

z

the data matrix to create contour plot.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
8. #### def dendrogram(merge: Array[Array[Int]], height: Array[Double]): Window

A dendrogram is a tree diagram to illustrate the arrangement of the clusters produced by hierarchical clustering.

A dendrogram is a tree diagram to illustrate the arrangement of the clusters produced by hierarchical clustering.

merge

an n-1 by 2 matrix of which row i describes the merging of clusters at step i of the clustering. If an element j in the row is less than n, then observation j was merged at this stage. If j ≥ n then the merge was with the cluster formed at the (earlier) stage j-n of the algorithm.

height

a set of n-1 non-decreasing real values, which are the clustering height, i.e., the value of the criterion associated with the clustering method for the particular agglomeration.

Definition Classes
Operators
9. #### def dendrogram(hc: HierarchicalClustering): Window

A dendrogram is a tree diagram to illustrate the arrangement of the clusters produced by hierarchical clustering.

A dendrogram is a tree diagram to illustrate the arrangement of the clusters produced by hierarchical clustering.

hc

hierarchical clustering object.

Definition Classes
Operators
10. #### def grid(data: Array[Array[Array[Double]]]): Window

2D grid plot.

2D grid plot.

data

an m x n x 2 array which are coordinates of m x n grid.

Definition Classes
Operators
11. #### def heatmap(rowLabels: Array[String], columnLabels: Array[String], z: Array[Array[Double]], palette: Array[Color]): Window

Pseudo heat map plot.

Pseudo heat map plot.

rowLabels

the labels for rows of data matrix.

columnLabels

the labels for columns of data matrix.

z

a data matrix to be shown in pseudo heat map.

palette

the color palette.

Definition Classes
Operators
12. #### def heatmap(rowLabels: Array[String], columnLabels: Array[String], z: Array[Array[Double]]): Window

Pseudo heat map plot.

Pseudo heat map plot.

rowLabels

the labels for rows of data matrix.

columnLabels

the labels for columns of data matrix.

z

a data matrix to be shown in pseudo heat map.

Definition Classes
Operators
13. #### def heatmap(x: Array[Double], y: Array[Double], z: Array[Array[Double]], palette: Array[Color]): Window

Pseudo heat map plot.

Pseudo heat map plot.

x

x coordinate of data matrix cells. Must be in ascending order.

y

y coordinate of data matrix cells. Must be in ascending order.

z

a data matrix to be shown in pseudo heat map.

palette

the color palette.

Definition Classes
Operators
14. #### def heatmap(x: Array[Double], y: Array[Double], z: Array[Array[Double]]): Window

Pseudo heat map plot.

Pseudo heat map plot.

x

x coordinate of data matrix cells. Must be in ascending order.

y

y coordinate of data matrix cells. Must be in ascending order.

z

a data matrix to be shown in pseudo heat map.

Definition Classes
Operators
15. #### def heatmap(z: Array[Array[Double]], palette: Array[Color]): Window

Pseudo heat map plot.

Pseudo heat map plot.

z

a data matrix to be shown in pseudo heat map.

palette

the color palette.

Definition Classes
Operators
16. #### def heatmap(z: Array[Array[Double]]): Window

Pseudo heat map plot.

Pseudo heat map plot.

z

a data matrix to be shown in pseudo heat map.

Definition Classes
Operators
17. #### def hexmap(labels: Array[Array[String]], z: Array[Array[Double]], palette: Array[Color]): Window

Heat map with hex shape.

Heat map with hex shape.

labels

the descriptions of each cell in the data matrix.

z

a data matrix to be shown in pseudo heat map.

palette

the color palette.

Definition Classes
Operators
18. #### def hexmap(labels: Array[Array[String]], z: Array[Array[Double]]): Window

Heat map with hex shape.

Heat map with hex shape.

labels

the descriptions of each cell in the data matrix.

z

a data matrix to be shown in pseudo heat map.

Definition Classes
Operators
19. #### def hexmap(z: Array[Array[Double]], palette: Array[Color]): Window

Heat map with hex shape.

Heat map with hex shape.

z

a data matrix to be shown in pseudo heat map.

palette

the color palette.

Definition Classes
Operators
20. #### def hexmap(z: Array[Array[Double]]): Window

Heat map with hex shape.

Heat map with hex shape.

z

a data matrix to be shown in pseudo heat map.

Definition Classes
Operators
21. #### def hist(data: Array[Array[Double]], xbins: Int, ybins: Int): Window

3D histogram plot.

3D histogram plot.

data

a sample set.

xbins

the number of bins on x-axis.

ybins

the number of bins on y-axis.

Definition Classes
Operators
22. #### def hist(data: Array[Array[Double]], k: Int): Window

3D histogram plot.

3D histogram plot.

data

a sample set.

k

the number of bins.

Definition Classes
Operators
23. #### def hist(data: Array[Array[Double]]): Window

3D histogram plot.

3D histogram plot.

data

a sample set.

Definition Classes
Operators
24. #### def hist(data: Array[Double], breaks: Array[Double]): Window

Histogram plot.

Histogram plot.

data

a sample set.

breaks

an array of size k+1 giving the breakpoints between histogram cells. Must be in ascending order.

Definition Classes
Operators
25. #### def hist(data: Array[Double], k: Int): Window

Histogram plot.

Histogram plot.

data

a sample set.

k

the number of bins.

Definition Classes
Operators
26. #### def hist(data: Array[Double]): Window

Histogram plot.

Histogram plot.

data

a sample set.

Definition Classes
Operators
27. #### def line(data: Array[Array[Double]], style: Style = Line.Style.SOLID, color: Color = Color.BLACK, legend: Char = ' '): Window

Line plot.

Line plot.

data

a n-by-2 or n-by-3 matrix that describes coordinates of points.

style

the stroke style of line.

color

the color of line.

legend

the legend used to draw data points. The default value ' ' makes the point indistinguishable from the line on purpose.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
28. #### def plot(x: Array[Array[Double]], y: Array[Double], model: Regression[Array[Double]]): Window

Plots the regression surface.

Plots the regression surface.

x

training data.

y

response variable.

model

regression model.

Definition Classes
Operators
29. #### def plot(x: Array[Array[Double]], y: Array[Int], model: Classifier[Array[Double]]): Window

Plots the classification boundary.

Plots the classification boundary.

x

training data.

y

training label.

model

classification model.

Definition Classes
Operators
30. #### def plot(data: AttributeDataset, legend: Array[Char], palette: Array[Color]): JFrame

Plot a grid of scatter plots of for all attribute pairs in the attribute data of which the response variable is integer.

Plot a grid of scatter plots of for all attribute pairs in the attribute data of which the response variable is integer.

data

an attribute frame.

legend

the legend for each class.

palette

the color for each class.

returns

the window frame.

Definition Classes
Operators
31. #### def plot(data: AttributeDataset, legend: Char, palette: Array[Color]): JFrame

Plot a grid of scatter plots of for all attribute pairs in the attribute data of which the response variable is integer.

Plot a grid of scatter plots of for all attribute pairs in the attribute data of which the response variable is integer.

data

an attribute frame.

legend

the legend for all classes.

palette

the color for each class.

returns

the window frame.

Definition Classes
Operators
32. #### def plot(data: AttributeDataset, legend: Char): JFrame

Plot a grid of scatter plots of for all attribute pairs in the attribute data.

Plot a grid of scatter plots of for all attribute pairs in the attribute data.

data

an attribute frame.

legend

the legend for all classes.

returns

the window frame.

Definition Classes
Operators
33. #### def plot(data: Array[Array[Double]], label: Array[Int], legend: Array[Char], palette: Array[Color]): Window

Scatter plot.

Scatter plot.

data

a n-by-2 or n-by-3 matrix that describes coordinates of points.

label

the class labels of data.

legend

the legend for each class.

palette

the color for each class.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
34. #### def plot(data: Array[Array[Double]], label: Array[Int], legend: Char, palette: Array[Color]): Window

Scatter plot.

Scatter plot.

data

a n-by-2 or n-by-3 matrix that describes coordinates of points.

label

the class labels of data.

legend

the legend for all classes.

palette

the color for each class.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
35. #### def plot(data: Array[Array[Double]], labels: Array[String]): Window

Scatter plot.

Scatter plot.

data

a n-by-2 or n-by-3 matrix that describes coordinates of points.

labels

labels of points.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
36. #### def plot(data: Array[Array[Double]], legend: Char = '*', color: Color = Color.BLACK): Window

Scatter plot.

Scatter plot.

data

a n-by-2 or n-by-3 matrix that describes coordinates of points.

legend

the legend used to draw points.

• . : dot
• + : +
• - : -
• | : |
• * : star
• x : x
• o : circle
• O : large circle
• @ : solid circle
• # : large solid circle
• s : square
• S : large square
• q : solid square
• Q : large solid square
• others : dot
color

the color used to draw points.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
37. #### def qqplot(x: Array[Int], y: Array[Int]): Window

QQ plot of two sample sets.

QQ plot of two sample sets. The x-axis is the quantiles of x and the y-axis is the quantiles of y.

x

a sample set.

y

a sample set.

Definition Classes
Operators
38. #### def qqplot(x: Array[Int], d: DiscreteDistribution): Window

QQ plot of samples to given distribution.

QQ plot of samples to given distribution. The x-axis is the quantiles of x and the y-axis is the quantiles of given distribution.

x

a sample set.

d

a distribution.

Definition Classes
Operators
39. #### def qqplot(x: Array[Double], y: Array[Double]): Window

QQ plot of two sample sets.

QQ plot of two sample sets. The x-axis is the quantiles of x and the y-axis is the quantiles of y.

x

a sample set.

y

a sample set.

Definition Classes
Operators
40. #### def qqplot(x: Array[Double], d: Distribution): Window

QQ plot of samples to given distribution.

QQ plot of samples to given distribution. The x-axis is the quantiles of x and the y-axis is the quantiles of given distribution.

x

a sample set.

d

a distribution.

Definition Classes
Operators
41. #### def qqplot(x: Array[Double]): Window

QQ plot of samples to standard normal distribution.

QQ plot of samples to standard normal distribution. The x-axis is the quantiles of x and the y-axis is the quantiles of normal distribution.

x

a sample set.

Definition Classes
Operators
42. #### def screeplot(pca: PCA): Window

The scree plot is a useful visual aid for determining an appropriate number of principal components.

The scree plot is a useful visual aid for determining an appropriate number of principal components. The scree plot graphs the eigenvalue against the component number. To determine the appropriate number of components, we look for an "elbow" in the scree plot. The component number is taken to be the point at which the remaining eigenvalues are relatively small and all about the same size.

pca

principal component analysis object.

Definition Classes
Operators
43. #### def spy(matrix: SparseMatrix): Window

Visualize sparsity pattern.

Visualize sparsity pattern.

matrix

a sparse matrix.

Definition Classes
Operators
44. #### def staircase(data: Array[Double]*): Window

Create a plot canvas with the staircase line plot.

Create a plot canvas with the staircase line plot.

data

a n x 2 or n x 3 matrix that describes coordinates of points.

Definition Classes
Operators
45. #### def surface(x: Array[Double], y: Array[Double], z: Array[Array[Double]], palette: Array[Color]): Window

3D surface plot.

3D surface plot.

x

the x-axis values of surface.

y

the y-axis values of surface.

z

the z-axis values of surface.

palette

the color palette.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
46. #### def surface(x: Array[Double], y: Array[Double], z: Array[Array[Double]]): Window

3D surface plot.

3D surface plot.

x

the x-axis values of surface.

y

the y-axis values of surface.

z

the z-axis values of surface.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
47. #### def surface(z: Array[Array[Double]], palette: Array[Color]): Window

3D surface plot.

3D surface plot.

z

the z-axis values of surface.

palette

the color palette.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
48. #### def surface(z: Array[Array[Double]]): Window

3D surface plot.

3D surface plot.

z

the z-axis values of surface.

returns

a tuple of window frame and plot canvas which can be added other shapes.

Definition Classes
Operators
49. #### def wireframe(vertices: Array[Array[Double]], edges: Array[Array[Int]]): Window

Wire frame plot.

Wire frame plot. A wire frame model specifies each edge of the physical object where two mathematically continuous smooth surfaces meet, or by connecting an object's constituent vertices using straight lines or curves.

vertices

a n-by-2 or n-by-3 array which are coordinates of n vertices.

edges

an m-by-2 array of which each row is the vertex indices of two end points of each edge.

Definition Classes
Operators