Gradient
apama.analyticskit.blocks.core.Gradient
Calculates the weighted linear regression gradient for the values.
A gradient measures the rate of change of a value over time. A positive gradient indicates an increase of the input values, and a negative gradient indicates a decrease of the input values. The magnitude of the gradient signifies the scale of change.
The block can operate over a time-bounded window that is specified with the Window Duration parameter. If this parameter is not specified, it uses an unbounded window and the block re-evaluates for every 1 second, and will use 1-second buckets. If a window is configured, the block will use a set of 20 buckets, so the time of expired values is an approximation to the nearest bucket interval. The first gradient output is generated only when a minimum of two buckets is available for computation.
The Reset input clears the content of the window. Sample input can be used to force re-evaluation and generate the latest value.
Parameters
Name | Description | Type | Notes |
Window Duration (secs) | If present, the amount of time (in seconds) for which values are to be kept in the window. This must be a finite and positive number. | float | Optional |
Input Port Details
Name | Description | Type |
Value | The input value for which the gradient is to be calculated. | float |
Reset | Clears the content of the window. | pulse |
Sample | Forces re-evaluation of the current value and sends the output. | pulse |
Output Port Details
Name | Description | Type |
Gradient | The gradient of the input values. | float |