NanoLocz

NanoLocz User Guide 1.3

Installation - - Getting Started - - Saving Data
Level - - Detect - - FineAlign - - Localize
Area Analysis - - Keyboard Shortcuts
Simulation AFM - - YouTube Video Tutorials

Saving Data

This section explains how to save data in NanoLocz. Data can either be saved/processed in bulk and for later use or by exporting the current views in the plots for figures/presentations.
1. Save or Batch Process Data
2. Export Images, Videos and Data
3. h5 and mat File Structure for NanoLocz

1. Save or Batch Process Data

The following describes saving and batch processing options so that raw and processed data can be quickly reopened in NanoLocz or other software. See section 2 for export of images / movies for publication quality figures or presentations.

Single or Batch Save

• To save one or multiple files open the Save Options using save
• Select the format, to retain all image and analysis data use combined file format options. To access the images and data analysis in other software use separate Image/video and Analysis tables formats.
• Select Files to save using the Save dropdown box:
  Current File: Selects the currently open image
  All Files: Selects all files in the open folder
  All Processed: Selects and displays only files that have been processed (levelled, filtered or analysed)
  Session: Saves all processed data in a single .mat file which can be reopened in NanoLocz
• Use the checkboxes next to each file name to select which files to Save.
• To level unprocessed data select the ‘Level unprocessed data’ option and images will be levelled using the current level settings in the main NanoLocz window.
• Select the Output folder you want NanoLocz to save to.
• Select subfolder preferences:
  Create a new subfolder: Generates 1 subfolder in the Output folder with the name: ‘xxxxxxx NanoLocz Output’ where xxxxxx is the name of the current open folder. Recommended for general use.
  Create multiple subfolder(s): Generates 1 subfolder per image/movie in the Output folder with the name: ‘Image Name’. Recommended if saving many separate tables and images.
• Press Save to run the save

Filename Generation Options

Controlled by Output Filename:

• Auto save (same name): Saves using the same name as the filename (will overwrite files)
• Prompt for name: Asks to choose filename/location
• Add suffix _copy: Adds _copy to the filename
• Add suffix _channel: Adds _’channel’ to the filename where channel is replaced by the source channel eg ‘_Height-retrace’
• Save to new location: Asks the user to choose a folder

Note

• File extensions are stripped if they match known types (csv, png, mat, etc.).
• Auto save and add suffix will save to the output folder and overwrite files with matching filenames

Format Options

AutoSave

By turning on AutoSave - files will automatically be saved to the output folder according to the settings in Preferences. To change these setting - open the preferences window using the Cog icon or Settings option.

2. Exporting Images, Videos and Data

This section describes how to export data based on the current view - useful for publication quality figures, presentations, or exporting raw data in manual way. See section 1 for batch export options.

2.1 Image and Video export

Option 1:

• Select ‘Plot 1’ (left image panel) or ‘Plot 2’ (right Image panel) from the dropdown box
• Select the desired format from the dropdown box (.tiff, .csv, .txt, .xls, gif, .avi, .png, .jpeg or .pdf)
• Press the Export button, then select file name and save location.
• Don’t close the image window that pops up until after the file has saved

Note: Exporting as .tiff, .csv, .txt, or .xls enables export without loss of image information whereas export as .gif, .avi, .png, .jpeg or .pdf gives movies/images at presentation or publication quality with automatic scale bars and timestamps.

Option 2 (good for creating publication quality figures or grabbing images quickly):

• Press the Pop Out button
• Resize the image
• Go to the top right hand side of the image and select the far left button from the toolbar
• For making figures choose ‘Copy as vector graphic’ Or for quickly copying an image choose ‘Copy as image’, the image can then be pasted into another program.
• Once pasted vector files can be ungrouped to enable movement and formatting of any labels (eg. scale bars, timestamps…)
• Only works for single images
  

2.2 Analysis data export

• Open the data Viewer
• With Plot type table selected, choose the table of data required for export
• Select format (.txt, .csv, .xls) and press export
• Alternatively, manually select entries from the table and copy (ctrl+c)

2.3 MATLAB data export (MATLAB app only)

• From the ‘Plot 1’ dropdown select ‘data’
• From the desired format dropdown box select ‘MATLAB Workspace’
• Press the Export button
• Data will appear in the MATLAB workspace

3. h5 and mat File Structure for NanoLocz

When data is saved in the .h5 or ‘.mat’ format, NanoLocz organizes it into a hierarchical structure. This format allows for easy access to all data components used in analysis and visualization.

Structure Overview

Each top-level field in the data struct (Data) becomes a group in the HDF5 file. Nested structures create subgroups, and each individual variable (numeric arrays, tables, strings) becomes a dataset.

📁 Typical HDF5 Layout

/Imagedata → Primary image data
/ImageInfo → Metadata about the image (e.g., pixel size, channel info)
/ref/ROIimage → Region of interest image used as a reference
/ref/simImage → Simulated reference image (if available)
/ref/LAFM → LAFM reference image (if used)
/ref/av → Averaged reference
/ImageLocs → Struct or array containing localized particle data
/LAFMLocs → Struct with LAFM localization results\

📁 Typical MATLAB Data Layout

Image Data

• Data.Imagedata
  → The primary image data array.

• Data.ImageInfo
  → Metadata about the image, including:

  • Pixel size
  • Scan size
  • Channel information

---

Particle Detection (ImageLocs)

• Data.ImageLocs
  → A struct containing detected particle data.

• Data.ImageLocs.Locs
  → A table where each row corresponds to a detected particle. Columns:

  1. x — x-coordinate
  2. y — y-coordinate
  3. z — height
  4. ccr — cross-correlation value
  5. Frame — frame number
  6. id — unique particle ID
  7. Track id — tracking ID (for tracked particles)
  8. Angle — orientation angle

---

LAFM Localizations (LAFMLocs)

• Data.LAFMLocs
  → A struct containing LAFM localization results.

• Data.LAFMLocs.Locs
  → A table where each row corresponds to a localization event. Columns:

  1. x — x-coordinate
  2. y — y-coordinate
  3. z — height
  4. Peak Prominence — peak prominence
  5. Particle — particle ID
  6. Frame — frame number
  7. Time — time point
  8. ccr — cross-correlation value
  9. PT Cloud RMSE — point cloud root-mean-square error
  10. Error — localization error estimate

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