Density gradient analysis tool

1. A method, comprising:

receiving data points;

calculating a data distribution of the data points, wherein the data distribution has bins, wherein each bin represents an interval; and

rendering a heat map based, at least in part, on the data distribution, wherein the heat map includes regions corresponding to the bins;

receiving a request to illustrate additional data points;

transforming the heat map to form a first ribbon heat map;

calculating an additional data distribution for the additional data points;

generating a second ribbon heat map based, at least in part, on the additional data distribution; and

rendering a combined ribbon heat map by combining the first ribbon heat map and the second ribbon heat map,

wherein the combined ribbon heat map is a sinusoidal wave, and wherein a wavelength of the sinusoidal wave corresponds to data points representing one day.

2. The method of claim 1 , further comprising:

receiving a request to illustrate additional data points;

transforming the heat map to form a first ribbon heat map;

calculating an additional data distribution for the additional data points;

generate a second ribbon heat map based, at least in part, on the additional data distribution; and

rendering a combined ribbon heat map by combining the first ribbon heat map and the second ribbon heat map.

3. The method of claim 1 , further comprising:

assigning a region a color based, at least in part, on a data point density of a region;

wherein rendering the heat map further includes coloring the region with the assigned color.

4. The method of claim 1 , further comprising:

defining thresholds for different values of the data point density;

assigning each bin a threshold based, at least in part, on the data point density of the bin;

assigning a region a color based, at least in part, on the assigned threshold of the bin corresponding to the region; and

coloring the region with the assigned color.

5. The method of claim 4 , further comprising:

smoothing transitions between the colored regions in the heat map.

6. The method of claim 1 , further comprising:

normalizing the data distribution; and

assigning the regions colors based, at least in part, on the normalized distribution, wherein rendering the heat map further includes coloring the regions with the assigned colors.

7. The method of claim 1 , wherein the data points have characteristics, and wherein the characteristics are aggregated in the bins.

8. A system, comprising:

a data distribution logic configured to calculate a first data distribution of the data points, wherein the data distribution logic is further configured to:

receive additional data points; and

calculate a second data distribution based, at least in part, on the first data distribution and the additional data points

wherein each data distribution has bins, wherein each bin corresponds to an interval;

a render logic configured to render a circular heat map based, at least in part, on the first data distribution, wherein the render logic is further configured to render the second data distribution as a ribbon heat map, wherein the ribbon heat map is a sinusoidal wave, and wherein a wavelength of the sinusoidal wave corresponds to data points representing one day; and

a display to display the rendered circular heat map.

9. The system of claim 8 , where the data distribution logic is configured to calculate a value for data point density of each bin, the system further comprising:

a threshold logic is further configured to:

define thresholds corresponding to different values of the data point density; and

assign a bin a color based, at least in part, on the value for the data point density of the bin and corresponding threshold; and

wherein the render logic is further configured to color a region with the color assigned to the bin represented by the region.

10. The system of claim 9 , further comprising

a smoothing logic configured to smooth transitions between colored regions in the circular heat map.

11. The system of claim 9 , further comprising:

a normalization logic configured to normalize the data distribution; and

wherein the threshold logic configured to define the thresholds based, at least in part on the normalized data distribution.

12. The system of claim 8 , wherein the data points are associated with a day of a week, wherein the interval is fifteen minutes, and wherein the data distribution logic is further configured to aggregate data points into an appropriate interval for an appropriate of day of the week for a data point.

13. A non-transitory computer-readable medium storing computer-executable instructions that when executed by a computer cause the computer to perform a method, the method comprising:

receiving a set of data points representing multiple days;

calculating a data distribution for the set of data points;

rendering a ribbon heat map corresponding to the set of data points, where the ribbon heat map comprises periodic regions;

receiving a selection of a region of the periodic regions, wherein the region corresponds to a subset of the set of data points; and

rendering a circular heat map representing the subset of the data points, wherein the ribbon heat map is a sinusoidal wave, and wherein a wavelength of the sinusoidal wave corresponds to data points representing one day.

14. The non-transitory computer-readable medium of claim 13 , wherein the circular heat map comprises bins, and wherein a bin corresponds to an interval of time.

15. The non-transitory computer-readable medium of claim 13 , further comprising:

in response to receiving the selection of a region, displaying an amount of time represented by the region.

16. The non-transitory computer-readable medium of claim 13 , further comprising:

in response to receiving the selection of a region, displaying constituents of the selected region.

17. The non-transitory computer-readable medium of claim 13 , further comprising:

in response to the circular heat map being wound, rendering a circular heat map representing a different subset of the data.