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There is a Calculate Drift Correction button amongst the Tools in the bottom left of the UI.

This approach works best when calculating drift from dense datasets with large numbers of localisations as , since the default minimum number of points to cross-correlate is 400000. For sparser datasets ONI have written a Python script that changes the default number to a user-set value. You can open the Python script in the following way:

  1. In the main menu, click Advanced
  2. Select Python Console
  3. Go to the File/Open... menu of the Python Console and open the following script: drift_ChangeLocs_Region (2).py. The script file is on the desktop of the Nanoimager PC.

    Info

    If you want to use it on your own copy of NimOS then email lmcb-lm-help@ucl.ac.uk and we will send you a copy.

  4. User editable values in the script are highlighted in cyan.
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  5. The most important value to adjust is dc.MinPointsPerSubsample. The default value for this is 400000 (see above). The text in the script recommends setting this to 5000 or less. I have had more luck with around 10000 with my specimens, but it depends on how many localisations you have.
  6. You can also restrict calculation of drift to an ROI (if most of your image has no localisations, for example). This is done by changing the dc.CustomRegionLeft, dc.CustomRegionRight, dc.CustomRegionTop and dc.CustomRegionBottom values. The values have to be typed in, so you will have to hover your cursor over the image to get the coordinates.
  7. I'm not recommending that the dc.MaxSubsampleImageDimension is edited at this time.
  8. Once you've changed the values to the ones you want, click Run code.
  9. If the drift correction hasn't worked well, try decreasing or increasing the dc.MinPointsPerSubsample.
  10. You can use the Apply correction tick-box in the main GUI to toggle the correction on and off.
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Results Filtering

  1. In the Results Filtering area you can choose to apply filters to the localisations. For example, you might want to only look at localisations with a localisation precision of 10 nm or less, or you might want to examine how the localisations change for different ranges of frames using the Frame Index filter.
  2. On the left of the user interface in the Tools area you can use the Trace tool to see how parameters like photon count change over time or use the Line Histogram to measure the distance between spots.
  3. Localisations can be exported using the Export Localizations as .csv button. If you've set filters in the Results Filtering area then the filtered localisations will be exported.