115 lines
5.8 KiB
Markdown
115 lines
5.8 KiB
Markdown
# CRDS Scan Analyzer
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<img src="screenshots/fit_demo.png" width=800/>
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## Basics
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- Designed for usage with **Mid-IR laser comb** scan output (time scale, not frequency)
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- Expected data column format: `<time>, <signal voltage in>, <piezo crystal voltage out (optional)>`
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## Building (Python 3.8+)
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1. `pip3 <or python3 -m pip> install -r requirements.txt`
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2. `build.cmd -compileUI -build`
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3. Find build output in `/dist/`
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## General Usage
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1. Import data (CSV - default Zurich output format)
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- Comment - %
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- Delimiter - ;
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2. Cut out & overlay peak groups using either piezo-voltage-threshold or group-spacing algorithm
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3. Set peak isolation parameters + guesses for ringdown function coefficients
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4. Admire glorious tau distributions for each comb tooth - **Note that the timescale used during correlation, adding & fitting (including the initial guess for tau) is in SENSOR TICKS. The resulting tau values are converted back to the original timescale at the end.**
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## Instructions
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##### GENERAL CONFIG
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| Input | Purpose |
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| -------- | ------------------------------------------------------ |
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| Timestep | Time interval of each sensor tick (e.g. 0.0000000178s) |
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##### GROUPING CONFIG (SpacedGroups)
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The SpacedGroups algorithm uses the length of each group (looking *length* in each direction from the first peak in the group) to determine which peaks fit into which group.
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| Input | Purpose |
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| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Group length | How long in time the peak group is (e.g. 0.0006s) |
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| Min peak height | The lowest acceptable height for a peak to be detected |
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| Min peak prominence | Prominence of detectable peaks - read about prominence [here](https://en.wikipedia.org/wiki/Topographic_prominence). Is finnicky, might have to play around a bit |
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| Moving average size | Peak detection uses a moving average (of which this is the denominator) to smooth out the data **(FOR GROUPING ONLY)**. |
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**Notes**
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- You can set custom start and end cutoffs for grouping in case there's only part of a group at the beginning or end
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- You can choose to exclude mirrored groups (which occur every other group). Or don't. Depends on how you configured the lab setup.
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##### GROUPING CONFIG (VThreshold)
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This algorithm *should* look at the min and max voltages provided to separate out groups. It's not implemented yet, though.
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##### PEAK ISOLATION CONFIG
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This is where the overlayed peak groups are added together, and the added peaks are cut out.
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**Note that the timescale here is in ticks, NOT seconds/milliseconds/etc.**
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| Input | Purpose |
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| ----------------------- | ------------------------------------------------------------------------------------------------------------------- |
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| Added peak length | The length of the (added) peaks that you want cut out. Centers around tip of peak. |
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| Min added peak height | The lowest acceptable height for a peak to be detected |
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| Added peak prominence | Prominence of detectable peaks - read about prominence [here](https://en.wikipedia.org/wiki/Topographic_prominence) |
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| Shift over cut-out zone | How many ticks to shift the center of the cut-out zone from the peak tip |
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##### INITIAL FIT CONFIG
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`y = y0 + a*e^(-t/tau)`
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| Input | Purpose |
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| -------------------- |:------------------------------------------------------- |
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| *a* value | Variable in equation |
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| *tau* value | Variable in equation |
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| *y0* value | Variable in equation |
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| Shift over fit start | How many ticks to shift over the start of the curve fit |
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## Feature Set
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| Feature | Status |
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| ---------------------------------------------- |:------:|
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| Import CSV Data | ✅ |
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| Group peaks (peak spacing) | ✅ |
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| Group peaks (piezo crystal voltage thresholds) | ❌ |
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| Custom start & end times for peak grouping | ✅ |
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| Correlate grouped peaks | ✅ |
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| Add & cut out overlayed peaks | ✅ |
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| Batch fit peaks | ✅ |
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| Display average tau data | ✅ |
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| Export data as CSV | ✅ |
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| Residuals on fits | ✅ |
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| Standard deviations | ✅ |
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| Persistent data storage | ❌ |
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## Ideas if anyone has the time to add anything
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- Speedier iteration & number crunching ([Numba](https://numba.pydata.org/))
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- Support for different file formats (e.g. [LabView]([npTDMS · PyPI](https://pypi.org/project/npTDMS/)))
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## Screenshots
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<img src="screenshots/time_constant_demo.png" width=800/>
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<img src="screenshots/correlation_demo.png" width=800/>
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<img src="screenshots/voltage_demo.png" width=800/>
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