# US 10,373,355 B1 · Density gradient analysis tool

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- Number: US 10,373,355 B1
- Document ID: US10373355B1
- Status: Granted
- Kind: B1
- Application number: 16/240,327
- Filed: 2019-01-04
- Granted: 2019-08-06
- Earliest claimed: 2014-08-18
- Assignees: Wells Fargo Bank, N.A.
- Applicants: Wells Fargo Bank, N.A.
- Inventors: Christopher J. Jones
- Web page: https://patentgrep.com/patent/US10373355B1

## CPC

- G06T 11/26: Drawing of charts or graphs
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

## Abstract

Systems, methods, and other embodiments associated with density gradient analysis tool for heat mapping systems. According to one embodiment, a method includes receiving data points. The method further includes calculating a data distribution of the data points. The data distribution has bins, and the bins represent an interval of time. The method further includes rendering a heat map based, at least in part, on the data distribution. The heat map includes regions corresponding to the bins.

## Claims

### Claim 1

A method, comprising:
receiving data points corresponding to a twenty-four hour time period;
calculating a first data distribution of the data points;
organizing the first data distribution into a first set of bins, wherein each bin has a data point density and represents an interval of time; and
rendering a first circular heat map based, at least in part, on the first data distribution, wherein the heat map includes regions corresponding to the first set of bins;
receiving a request to illustrate additional data points for a longer period of time;
calculating an additional data distribution for the additional data points;
organizing the additional data distribution into a second set of bins corresponding to the same interval of time as the first set of bins;
transforming the first circular heat map to a ribbon heat map, wherein the ribbon heat map is based at least in part, on the first data distribution and the additional data distribution; and
displaying the rendered ribbon heat map that includes distinct regions corresponding to the first and second sets of bins, wherein the ribbon heat map is a sinusoidal wave, wherein a wavelength of the sinusoidal wave corresponds to one of either the first or the second sets of bins.

### Claim 2 (depends on 1)

The method of claim 1, further comprising:
selecting a wavelength of the ribbon heat map, wherein the wavelength corresponds to the first or second sets of bins;
rendering a second circular heat map corresponding to the corresponding first or second sets of bins; and
displaying the second circular heat map.

### Claim 3 (depends on 2)

The method of claim 2 wherein both the ribbon heat map and the second circular heat map are displayed together.

### Claim 4 (depends on 1)

The method of claim 1, wherein the ribbon heat map illustrates multiple twenty-four hour time periods.

### Claim 5 (depends on 1)

The method of claim 1, further comprising:
assigning the regions a color based, at least in part, on the density of the bins, wherein rendering the heat map further includes coloring the regions with the assigned colors.

### Claim 6 (depends on 1)

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.

### Claim 7 (depends on 6)

The method of claim 6, further comprising:
smoothing transitions between the colored regions in the heat map.

### Claim 8 (depends on 1)

The method of claim 1, further comprising:
normalizing the first data distribution; and
assigning the regions colors based on a statistical normalization determined using the normalized distribution, wherein rendering the circular heat map further includes coloring the regions with the assigned colors, wherein the determining includes calculating a standard deviation to identify normal ranges of operation in the first data distribution and applying the standard deviation to the color thresholds.

### Claim 9 (depends on 8)

The method of claim 8, wherein the standard deviation is calculated at standard intervals to ensure that the data is still being correctly color coded.

### Claim 10 (depends on 1)

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

### Claim 11

A system, comprising:
a data distribution logic configured to:
receive data points corresponding to a twenty-four hour time period;
calculate a first data distribution of the data points;
organize the first data distribution into a first set of bins, wherein each bin has a data point density and represents an interval of time;
a render logic configured to render a first circular heat map based, at least in part, on the first data distribution, wherein the heat map includes regions corresponding to the first set of bins;
wherein, the data distribution logic is further configured to:
receive additional data points;
calculate a second data distribution based, at least in part, on the additional data points,
organize the second data distribution into a second set of bins corresponding to the same interval of time as the first set of bins,
wherein the render logic is further configured to:
transform the first circular heat map to a ribbon heat map based, at least in part, on the first data distribution and the second data distribution; and
a display to display the rendered ribbon heat map, that includes distinct regions corresponding to the first and second sets of bins, wherein the ribbon heat map is a sinusoidal wave, wherein a wavelength of the sinusoidal wave corresponds to one of either the first or the second sets of bins.

### Claim 12 (depends on 11)

The system of claim 11, 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 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;
wherein the render logic is further configured to color a region with the color assigned to the bin represented by the region.

### Claim 13 (depends on 12)

The system of claim 12, further comprising:
a smoothing logic configured to smooth transitions between colored regions in the first circular heat map.

### Claim 14 (depends on 13)

The system of claim 13, wherein the smoothing logic is configured to determine a number of color values between two different colors.

### Claim 15 (depends on 12)

The system of claim 12, further comprising:
a normalization logic configured to normalize the data distributions and use data from the normalized distributions to determine a statistical normalization for applying color to the bins, wherein the normalization logic calculates standard deviations to identify normal ranges of operation in the data distributions; and
wherein the threshold logic is configured to define the thresholds based, at least in part on the normalized data distributions, wherein the threshold logic applies the standard deviations to the color thresholds.

### Claim 16 (depends on 11)

The system of claim 11, wherein the data distribution logic is further configured to receive a request selecting a wavelength of the ribbon heat map, wherein the wavelength corresponds to the first or second sets of bins; and
the rendering logic is further configured to render a second circular heat map corresponding to the corresponding first or second sets of bins,
wherein the display displays the second circular heat map.

### Claim 17 (depends on 11)

The system of claim 11, 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.

### Claim 18

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 twenty-four hour periods;
calculating a data distribution for the set of data points;
organizing the data distribution into a set of bins, wherein each bin has a data point density and represents a single twenty-four hour period;
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 a single twenty-four hour period.

### Claim 19 (depends on 18)

The non-transitory computer-readable medium of claim 18, further comprising:
assigning the regions a color based, at least in part, on the density of the bins, wherein rendering the heat map further includes coloring the regions with the assigned colors.

### Claim 20 (depends on 18)

The non-transitory computer-readable medium of claim 18, 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.