Global

Members

attributes

Name of attributes and name of associated values of attribute. Used for parsing
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barChartError

Svg for the bar chart of the error-axis
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barChartX

Svg for the bar chart of the x-axis
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barChartY

Svg for the bar chart of the y-axis
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colors

Array of used colors
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data

Raw data
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datastructure

The data structure, which is defined in datastructure.js
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gRowProj

svg for the row projections (observations)
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gVoronoi

svg of the voronoi diagram
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gVoronoiCircle

svg for the circles in the voronoi diagram
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Header data
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headerCopy

Copy of header data datastructure. Filter and merging operations are applied to this before swapping it with the header data for recalculation
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headerData

Datastructure used to store the attributes.
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indicatorMatrix

Indicator matrix for the MCA
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indicatorSize

Number of columns in the indicatormatrix (columns)
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merge

List for elements to merge
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mergeParent

Store current attribute name for merging
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nameToIndexMap

Stores the mapping for an Attributes values name to an index in the indicator matrix
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newIndicatorSize

Number of columns in the indicatormatrix after applying the filtering/merging
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numAttributes

Number of Attributes
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relevanceScale

Scale for scaling the relevance bar
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rowCoordinates

Array of observations calculated 2D coordinates
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showObservation

Show the observations as overlay
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svg

svg of the projection view
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tip

Overlay for hovering a voronoi cell
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tipPoint

Overlay for hovering a observation
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ul

The list for the dimensions view
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xScale

Scale for the x-axis projection
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yScale

Scale for the y-axis projection
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Methods

calcIndicatorMatrix()

Calculate the indicator matrix from the raw data
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calculateProjection()

The core of the program. Here the background calculation is initiated. Multiple web workers are used, which rely on calculations of previous web workers. This is necessary because of the garbage collector
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copyHeader()

Function to make a deep copy of the headerData datastructure
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createNameToIndexMap()

Helper function to create an index map for values of the attributes. This is needed to create the indicator matrix
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drawColumnProjection()

Draw the voronoi diagram of the projection of the attributes of the values
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drawDimensionsView()

Draw the dimensions view
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drawErrorBarChart()

Draw the bar chart for the error-axis of the projection. This is the same as for the y-bar chart
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drawFilterView()

Populate the selector element with attributes
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drawRowProjection()

Draw the overlay of observations
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drawXBarChart()

Draw the bar chart for the x-axis of the projection. This is the same as for the y-bar chart
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drawYBarChart()

Draw the bar chart for the y-axis of the projection
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getColor()

Helper function to return a color by index from a color mapping. A modulo is used for cyclic color return
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getColorByObservation()

Get an array of names, colors and coordinates for an Observation. The color is calculated by the value of the observation of the attribute specified with its name in the function head.
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getFlatJSON()

Get a flat array for the visualization with d3. Also merge two values of an attribute if the distance is less than delta
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isWithinDelta()

Helper function to calculate if the distance from (x1,y1) to (x2,y2) is less than delta
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loadCSV()

Function which initiates the datastructure after a csv file is selected
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merge(mergeList, mergeParent)

Function to merge the values of an attribute.
Parameters:
Name Type Description
mergeList Array List of indices of values to merge.
mergeParent string The name of the attribute which contains the values to merge.
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mergeValues()

Apply value merging on datastructure
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openView()

open a certain view by button click
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redraw()

Redraw all parts of the interface
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selectChange()

Draw the filter view when a attribute is selected
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setArea()

Set the size of the area of a voronoi region
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setColSum()

Set the column sum of the values. This uses the callback from the background calculation param{array} Array of column sum
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setColumnCoordinate()

Set the column coordinates of a value of an attribute
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setCopyHeaderActive()

Swap the headerCopy with the headerData
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setErrorBarChart()

Set the error-weights of the values. This uses the callback from the background calculation param{array} Array of column error-weights
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setFilteredAttribute()

Set the state of an attribute to filtered. This omits it from MCA calculations and visualization
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setRelevance()

Set the relevance of the values. This uses the callback from the background calculation param{array} Array of relevance values
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setRowCoordinates()

Set the coordinates of Observations. This is no longer needed
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setXBarChart()

Set the x-weights of the values. This uses the callback from the background calculation param{array} Array of column x-weights
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setXCoord()

Set the coordinates of the observations. This uses the callback from the background calculation param{array} Array of row coordinates (x AND y)
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setYBarChart()

Set the y-weights of the values. This uses the callback from the background calculation param{array} Array of column y-weights
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setYCoord()

Set the coordinates of the values. This uses the callback from the background calculation param{array} Array of column coordinates (x AND y)
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showObservations()

If the show Observations button is clicked, show the observations and set the color of the voronoi cells to a grayscale. If clicked again, reverse it
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split(splitList, splitParent)

Function to split merged values of an attribute.
Parameters:
Name Type Description
splitList Array List of indices of values to split.
splitParent string The name of the attribute which contains the values to split.
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splitValues()

Apply value splitting on datastructure
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stringCompare()

Helper for string comparison
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updateSlider()

Update delta if the slider is moved
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