DIAdem Idea Exchange

We are very happy about the support of Python as additional language in DIAdem script.

It would be a really nice feature if the DIAdem Python module would also be available in Python scripts that are running not within DIAdem script but on a machine with valid DIAdem license.
This would allow to create Python applications that use DIAdem commands but do not require the user to explicitly open DIAdem and load a Python script and thus improve usability.
Another use case would be an improved communication between Matlab and DIAdem by calling Python code including DIAdem commands from Matlab as executing Python code from Matlab is possible.

I would like a tool that would help identify noise spikes in my data, so that they may be set to NO VALUE or carefully interpolated. In the attached example, I have two torque spikes in my data that are significantly higher than the mean. If I were only looking at one file, I would simply "Set Flags" in VIEW, then "Flags: Remove Data Points". However, I am reviewing dozens of files with several channels of interest.

Peak data points are the most damaging to the components under test, so it is important that we keep the real events and reject the noise.

Concerns with other peak / spike removal options:

Manual Set Flags -> Flags: Remove Data Points; time required
ANALYSIS -> Event Search -> Event = Window -> Upper Limit: In other data files, I have real events with values higher than the noise in this data file.
ANALYSIS -> Digital Filters or Smoothing: This will change all of the data - it will likely narrow the peak-to-peak of my other data and interpolate my noise spikes, adding damage that is not actually real. I only want to remove a few data points in the channel data.

nCode Glyphworks has a nice Spike Detection Tool that uses 6 available algorithms to detect spikes. Once it identifies them, it allows the user to see them, prior to performing any actions - this is important, because it allows the user to identify if they are real or noise, prior to taking action.