Data plot processing

• US 10,825,235 B2
• Filed: 06/26/2019
• Issued: 11/03/2020
• Est. Priority Date: 08/15/2012
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Baudel, Thomas, Broeksema, Albertus H. J.
• Primary Examiner(s): Le, Sarah
• Application Number:
  US16/453,307
• Publication Number:
  US 20190318531A1
• Time in Patent Office: 496 Days
• Field of Search: None
• CPC Class Codes: G06F 18/213 Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
• CPC Class Codes: G06F 18/2413 based on distances to training or reference patterns
• CPC Class Codes: G06T 11/00 2D [Two Dimensional] image generation
• CPC Class Codes: G06T 15/10 Geometric effects
• CPC Class Codes: G06T 19/00 Manipulating 3D models or images for computer graphics
• CPC Class Codes: G06T 2219/004 Annotating, labelling

Abstract

A method, system, and/or computer program product processes a data plot comprising a plurality of data points for inclusion of additional information content. A space of the data plot is divided into subspaces, where each subspace contains at least one data point of the data plot. A compressed information representation for each subspace is computed based on information about said at least one data point contained in said each subspace. The data plot is displayed with the compressed information representation for said each subspace, where each unit of compressed information is displayed, on a display, adjacent to a corresponding group of data points from the data plot.

Claims

1. A method comprising:

dividing, by one or more processors, a space of a data plot into subspaces, wherein each subspace contains at least one data point of the data plot;

computing, by one or more processors, a compressed information representation for each subspace of the data plot based on information about said at least one data point contained in said each subspace;

displaying, by one or more processors, the data plot with the compressed information representation for said each subspace, wherein each unit of compressed information is displayed, on a display, adjacent to a corresponding group of data points from the data plot;

generating, by one or more processors, a compressed information representation from the information about said at least one data point contained in said each subspace;

determining, by one or more processors, if a size of the compressed information representation fits within a computed available area for said each subspace; and

in response to the compressed information representation failing to fit within the computed available area for said each subspace, further compressing, by one or more processors, the compressed information representation to generate a new compressed information representation.

2. The method of claim 1, wherein the compressed information representation is a label that describes multiple data points within a particular Voronoi cell, and wherein the method further comprises:

determining, by one or more processors, a maximum size of the label that can be fitted within a circle that is bound by the particular Voronoi cell on the display; and

in response to determining that the label for the multiple data points in the particular Voronoi cell cannot be fitted within the circle, compressing, by one or more processors, the label to create a lossy label that does not describe all information found in the compressed information representation.

3. The method of claim 1, further comprising:

in response to a size of a smaller subspace from said subspaces being smaller than a predetermined value, merging, by one or more processors, said smaller subspace with a neighboring subspace.

4. The method of claim 3, further comprising:

identifying, by one or more processors, subspaces that have a size smaller than the predetermined value; and

merging, by one or more processors, the subspaces determined to have the size smaller than the predetermined value with neighboring subspaces, wherein an order of merging subspaces is based on a size of the subspaces to be merged.

5. The method of claim 4, wherein the subspaces are merged in order of ascending size.

6. The method of claim 1, further comprising:

in response to a separation of two data points in the data plot being less than a predetermined value, merging, by one or more processors, the two data points into a new merged data point; and

defining and displaying, by one or more processors, a merged data point subspace in the space, wherein the merged data point subspace contains the new merged data point.

7. The method of claim 1, further comprising:

determining, by one or more processors, if repetition exists within the information about the multiple data points contained in said each subspace and, if repetition is determined to exist, representing the repeated information with a single object in the compressed information representation, the single object indicating a number of repetitions of the repeated information.

8. The method of claim 1, further comprising:

determining, by one or more processors, if information within the information about said at least one data point contained in said each subspace shares a common attribute; and

in response to determining that information within the information about said at least one data point contained in said each subspace shares the common attribute, representing, by one or more processors, the information that shares the common attribute in the compressed information representation.

9. The method of claim 1, further comprising:

editing, by one or more processors, the compressed information representation to be smaller in size by reducing an amount of information displayed by the compressed information representation.

10. The method of claim 1, further comprising:

determining, by one or more processors, a quantity of data points contained in said each subspace; and

editing, by one or more processors, the compressed information representation so that said compressed information representation represents a determined number of data points contained in said each subspace.

11. A computer program product for processing a data plot comprising a plurality of data points for inclusion of additional information content, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a processor to perform a method comprising:

dividing a space of a data plot into subspaces, wherein each subspace contains at least one data point of the data plot;

computing a compressed information representation for each subspace of the data plot based on information about said at least one data point contained in said each subspace, wherein the compressed information representation is a label that describes multiple data points within a particular Voronoi cell;

displaying the data plot with the compressed information representation for said each subspace, wherein each unit of compressed information is displayed, on a display, adjacent to a corresponding group of data points from the data plot;

determining a maximum size of the label that can be fitted within a circle that is bound by the particular Voronoi cell on the display; and

in response to determining that the label for the multiple data points in the particular Voronoi cell cannot be fitted within the circle, compressing the label to create a lossy label that does not describe all information found in the compressed information representation.

12. The computer program product of claim 11, wherein the method further comprises:

in response to a size of a smaller subspace from said subspaces being smaller than a predetermined value, merging said smaller subspace with a neighboring subspace.

13. The computer program product of claim 11, wherein the method further comprises:

in response to a separation of two data points in the data plot being less than a predetermined value, merging the two data points into a new merged data point.

14. The computer program product of claim 11, wherein the method further comprises:

generating the compressed information representation from the information about said at least one data point contained said each subspace;

determining if a size of the compressed information representation fits within a computed available area for said each subspace; and

in response to the compressed information representation failing to fit within the computed available area for said each subspace, further compressing the compressed information representation to generate a new compressed information representation.

15. A computer system comprising one or more processors, one or more computer readable memories, and one or more computer readable non-transitory storage mediums, and program instructions stored on at least one of the one or more computer readable non-transitory storage mediums for execution by at least one of the one or more processors via at least one of the one or more computer readable memories, the stored program instructions executed to perform a method comprising:

dividing a space of a data plot into subspaces, wherein each subspace contains at least one data point of the data plot;

computing a compressed information representation for each subspace of the data plot based on information about said at least one data point contained in said each subspace, wherein the compressed information representation is a label that describes multiple data points within a particular Voronoi cell;

displaying the data plot with the compressed information representation for said each subspace, wherein each unit of compressed information is displayed, on a display, adjacent to a corresponding group of data points from the data plot;

determining a maximum size of the label that can be fitted within a circle that is bound by the particular Voronoi cell on the display; and

in response to determining that the label for the multiple data points in the particular Voronoi cell cannot be fitted within the circle, compressing the label to create a lossy label that does not describe all information found in the compressed information representation.

16. The computer system of claim 15, wherein the method further comprises:

in response to a size of a smaller subspace from said subspaces being smaller than a predetermined value, merging said smaller subspace with a neighboring subspace.

17. The computer system of claim 16, wherein the method further comprises:

identifying subspaces that have a size smaller than the predetermined value; and

merging the subspaces determined to have the size smaller than the predetermined value with neighboring subspaces, wherein an order of merging subspaces is based on a size of the subspaces to be merged.