Data visualization methods

1. A method of creating a graphical representation of data points in the form of a heatmap wherein the heatmap represents a plurality of multi-directional flow values between the data points, the method including the steps of:

positioning data points at respective data point locations on a heatmap for graphical representation;

calculating bi-directional flow values between data points, at least two data points having bi-directional flow values to at least two other data points;

determining the intensity and direction of a predominant flow from the bi-directional flow values;

calculating weighted heat values for an area on the heatmap based on the bi-directional flow values near the area, the distance the bi-directional flow values are from the area and flow start values for the data points;

for each data point, representing flow start values at the respective data point by calculating respective conical data distribution values around the respective data point based on the flow start value associated with the respective data point, wherein each conical distribution comprises a set of locations and a unique distribution value corresponding to each location in a respective region centered on the respective data point location;

for each data point, determining whether the calculated respective conical data distribution values of other data points at the respective data point location are greater than the flow start value associated with the respective data point;

upon a positive determination, calculating inverse conic data distribution values around the respective data point based on the flow start value associated with the respective data point; and

graphically representing the predominant flow, the bi-directional flows between the data points, the calculated weighted heat values, the calculated conical data distribution values and the calculated inverse conic data distribution values in the heatmap.

2. The method of claim 1 , further including the step of calculating the weighted heat values by calculating a weighted distance function.

3. The method of claim 2 , wherein the weighted distance function is an inverse distance weighted (IDW) function.

4. The method of claim 1 , further including the step of:

calculating a trapezoid distribution between the first and second data point, where the length of the parallel surfaces of the trapezoid distribution at the data points is based on the value of the calculated flow emanating from each represented data point.

5. The method of claim 1 , further including the step of:

calculating a triangular prism distribution between the first and second data point, where the height of the triangular prism at each data point is based on the value of the calculated flow emanating from each represented data point.

6. The method of claim 5 , wherein the prism height corresponds to one or more of a range of colors or shadings.

7. The method of claim 1 , wherein the conical data distribution values are calculated by applying one of a frustoconical distribution, an exact conical distribution or a skewed conical distribution to the data value.

8. The method of claim 7 , wherein the inverse conical data distribution values are calculated by applying one of an inverse frustoconical distribution, an exact inverse conical distribution or a skewed inverse conical distribution to the data value.

9. The method of claim 1 , wherein the inverse conical data distribution values are calculated by applying one of an inverse frustoconical distribution, an exact inverse conical distribution or a skewed inverse conical distribution to the data value.

10. A graphical computing system for creating a graphical representation of data points in the form of a heatmap wherein the heatmap represents a plurality of multi-directional flow values between the data points, the system including:

a processor;

a memory device;

a node determination module executable by the processor arranged to position data points at respective data point locations on a heatmap for graphical representation;

a flow determination module executable by the processor arranged to calculate bi-directional flow values between data points, at least two data points having bi-directional flow values to at least two other data points;

a heat determination module executable by the processor arranged to calculate the intensity and direction of a predominant flow from the bi-directional flow values and further arranged to calculate weighted heat values for an area on the heatmap based on the bi-directional flow values near the area, the distance the bi-directional flow values are from the area and flow start values for the data points;

a cone generation module executable by the processor arranged for each data point to represent flow start values at each respective data point by calculating respective conical data distribution values around the respective data point based on the flow start value associated with the respective data point, wherein each conical distribution comprises a set of locations and a unique distribution value corresponding to each location in a respective region centered on the respective data point location, wherein the cone generation module executable by the processor is further arranged to for each data point determine whether the calculated respective conical data distribution values of other data points at the respective data point location are greater than the flow start value associated with the respective data point, and upon a positive determination, calculate inverse conic data distribution values around the respective data point based on the flow start value associated with the respective data point; and

a rendering module executable by the processor arranged to graphically represent the predominant flow, bi-directional flows between the data points, the calculated weighted heat values, the calculated conical data distribution values and the calculated inverse conic data distribution values in the heatmap.

11. The system of claim 10 , wherein the heat determination module executable by the processor is further arranged to calculate the weighted heat values by calculating a weighted distance function.

12. The system of claim 11 , wherein the weighted distance function is an inverse distance weighted (IDW) function.

13. The system of claim 10 , wherein the heat determination module executable by the processor is further arranged to calculate a trapezoid distribution between the first and second data point, where the length of the parallel surfaces of the trapezoid distribution at the data points is based on the value of the calculated flow emanating from each represented data point.

14. The system of claim 10 , wherein the heat determination module executable by the processor is further arranged to calculate a triangular prism distribution between the first and second data point, where the height of the triangular prism at each data point is based on the value of the calculated flow emanating from each represented data point.

15. The system of claim 14 , wherein the prism height corresponds to one or more of a range of colors or shadings.

16. The system of claim 10 , wherein the conical data distribution values are calculated by applying one of a frustoconical distribution, an exact conical distribution or a skewed conical distribution to the data value.

17. The system of claim 16 , wherein the inverse conical data distribution values are calculated by applying one of an inverse frustoconical distribution, an exact inverse conical distribution or a skewed inverse conical distribution to the data value.

18. The system of claim 10 , wherein the inverse conical data distribution values are calculated by applying one of an inverse frustoconical distribution, an exact inverse conical distribution or a skewed inverse conical distribution to the data value.

19. A non-transitory computer readable storage medium storing one or more programs configured for execution by an electronic computing device, the one or more programs comprising instructions for:

positioning data points at respective data point locations on a heatmap for graphical representation;

calculating bi-directional flow values between data points, at least two data points having bi-directional flow values to at least two other data points;

determining the intensity and direction of a predominant flow from the bi-directional flow values;

calculating weighted heat values for an area on the heatmap based on the bi-directional flow values near the area, the distance the bi-directional flow values are from the area and flow start values for the data points;

for each data point, representing flow start values at each respective data point by calculating respective conical data distribution values around the respective data point based on the flow start value associated with the respective data point, wherein each conical distribution comprises a set of locations and a unique distribution value corresponding to each location in a respective region centered on the respective data point location;

for each data point, determining whether the calculated respective conical data distribution values of other data points at the respective data point location are greater than the flow start value associated with the respective data point; and

upon a positive determination, calculating inverse conic data distribution values around the respective data point based on the flow start value associated with the respective data point; and

graphically representing the predominant flow, the bi-directional flows between the data points, the calculated weighted heat values, the calculated conical data distribution values and the calculated inverse conic data distribution values in the heatmap.

20. The non-transitory computer readable storage medium of claim 19 , wherein the conical data distribution values are calculated by applying one of a frustoconical distribution, an exact conical distribution or a skewed conical distribution to the data value and wherein the inverse conical data distribution values are calculated by applying one of an inverse frustoconical distribution, an exact inverse conical distribution or a skewed inverse conical distribution to the data value.