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compile-widget.md

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Locate channels, create channel stacks, and return metadata (Compile widget).

fov_inspect1

The Compile widget attempts to automatically identify and crop out individual growth channels. Images corresponding to a specific channel are then stacked in time, and these "channel stacks" are the basis of further analysis. If there are multiple colors, a channel stack is made for each color for each channel.

It is also at this time that metadata is drawn from the images and saved.

Parameters

  • TIFF_source needs to be specified to indicate how the script should look for TIFF metadata. Choices are nd2, BioFormats. elements. nd2 indicates that TIFF files were exported by nd2reader within the TIFFconverter script. BioFormats indicates that the TIFFs were extracted via Bio-Formats in the TIFFconverter widget and subsequent scripts should read in information from the TIFF names. Lastly, elements indicates that the TIFFs came from Nikon Elements.
  • channel_width, channel_separation, and channel_detection_snr, which are used to help find the channels.
  • channel_length_pad and channel_width_pad will increase the size of your channel slices.
  • phase_plane is the postfix of the channel which contains the phase images
  • start time, end time : Will only analyze images up to this time point. Useful for debugging.

Outputs

  • Stacked TIFFs through time for each channel (colors saved in separate stacks). These are saved to the channels/ subfolder in the analysis directory.
  • Metadata for each TIFF in a Python dictionary. These are saved as TIFF_metadata.pkl and .txt. The pickle file is read by subsequent scripts, the text file is simply for the user (true of all metadata files).
  • Channel masks for each FOV. These are saved as channel_masks.pkl and .txt. A Python dictionary that records the location of the channels in each FOV. Is a nested dictionaries of FOVs and then channel peaks. The final values are 4 pixel coordinates, ((y1, y2), (x1, x2)).
  • Time table for all time points and FOVs. These are saved as time_table.pkl and .txt. A Python dictionary by FOV which maps the actual time (elapsed seconds since the start of the experiment) each nominal time point was taken.
  • crosscorrs.pkl and .txt : Python dictionary that contains image correlation value for channels over time. Used to guess if a channel is full or empty. Same structure as channel_masks.

The working directory now contains:

.
├── 20170720_SJ388_mopsgluc12aa.nd2
├── TIFF
├── analysis
│   ├── time_table.pkl
│   ├── time_table.txt
│   ├── TIFF_metadata.pkl
│   ├── TIFF_metadata.txt
│   ├── channel_masks.pkl
│   ├── channel_masks.txt
│   └── channels