14: TSP command reference 2470 High Voltage SourceMeter Instrument
14-126 2470-901-01 Rev. A / May 2019
smu.measure.filter.type
This attribute sets the type of averaging filter that is used for the selected measure function when the
measurement filter is enabled.
Type TSP-Link accessible Affected by Where saved Default value
Attribute (RW) Yes Restore configuration
Instrument reset
Power cycle
Measure configuration list
Configuration script
Measure configuration list
smu.FILTER_REPEAT_AVG
Usage
filterType = smu.measure.filter.type
smu.measure.filter.type = filterType
The filter type to use when filtering is enabled; set to one of the following values:
 Moving average filter: smu.FILTER_MOVING_AVG
 Repeat filter:
Details
You can select one of two types of averaging filters: repeating average or moving average.
When the repeating average filter is selected, a set of measurements are made. These
measurements are stored in a measurement stack and averaged together to produce the averaged
sample. Once the averaged sample is produced, the stack is flushed and the next set of data is used
to produce the next averaged sample. This type of filter is the slowest, since the stack must be
completely filled before an averaged sample can be produced.
When the moving average filter is selected, the measurements are added to the stack continuously
on a first-in, first-out basis. As each measurement is made, the oldest measurement is removed from
the stack. A new averaged sample is produced using the new measurement and the data that is now
in the stack.
When the moving average filter is first selected, the stack is empty. When the first measurement is
made, it is copied into all the stack locations to fill the stack. A true average is not produced until the
stack is filled with new measurements. The size of the stack is determined by the filter count setting.
The repeating average filter produces slower results, but produces more stable results than the
moving average filter. For either method, the greater the number of measurements that are averaged,
the slower the averaged sample rate, but the lower the noise error. Trade-offs between speed and
noise are normally required to tailor the instrumentation to your measurement application.
Example
smu.measure.func = smu.FUNC_DC_CURRENT
smu.measure.filter.count = 10
smu.measure.filter.type = smu.FILTER_MOVING_AVG
smu.measure.filter.enable = smu.ON
Set the measurement function to
current.
Set the averaging filter type to moving
average, with a filter count of 10.
Enable the averaging filter.
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