# Analysing data not generated by PYMEAcquire¶

There are two key aspects to analysing data not generated by PYME - getting the data into a format that PYME understands, and filling in the required metadata entries.

There are two principle ways of doing this:

## Directly analysing the data (reccomended method)¶

PYME supports analysing directly from tiff stacks (all time points in one file) and from sequences of individual tiffs (each frame is a seperate file). PYME also makes use of image metadata such as the pixel size and various camera properties. PYME supports a number of ways of specifying the metadata, but the easiest is to create a .md file for each image you want to analyse (or to copy a template and just change the bits which are different).

This file should consist of a number of lines having the syntax:

md['entryname'] = value


The metadata entries are heirachial and use a dot notation (eg Camera.ADOffset)

An absolute minimum set of metadata parameters is outlined below:

Name Description
voxelsize.x x pixel size in μm
voxelsize.y y pixel size in μm
Camera.TrueEMGain The calibrated electron multiplying gain (1 for ordinary CCDs)
Camera.NoiseFactor EM excess noise factor (1.41 for EMCCDs, 1 for standard CCDs / sCMOS)
Camera.ElectronsPerCount Number of photo-electons per AD unit
Camera.ADOffset Analog to digital offset (dark level). Not strictly required as PYME will try and guess this from dark frames at the beginning of the sequence, but unless your acquistion is a very good match to the PYMEAcquire protocols this is unlikely to work well.

### Tiff Stacks¶

For tiff stacks the .md file ought to be in the same directory and have the same name (modulo extension) as the .tif file

Once you’ve created the .md file, just launch:

lmview <filename>.tif


if you want to perform localisation microscopy analysis, or:

dh5view <filename>.tif


for psf extraction, deconvolution, or other general purpose image processing tasks (lmview is just a shortcut for dh5view -m LM and launches dh5view in it’s localisation analysis personality).

### Tiff Sequences¶

For tiff sequences, the metadata file requires an additional entry, SeriesPattern, which identifies the files which comprise the sequence. This is a wildcard string - if for example, your data is in Frame001.tif, Frame002.tif, Frame003.tif etc ... a reasonable pattern could be

md['SeriesPattern'] = 'Frame*.tif'


This means that the .md file doesn’t need to have the same name as the individual data files, and you now load the .md file rather than one of the .tif images. Eg.:

lmview <filename>.md


Once you have loaded the data one can further tweak the metadata (using the Metadata tab) of lmview. Missing entries can to be added in the command window by executing:
image.mdh['entryname'] = value

Unfortunately these changes don’t persist (following the rational that raw data should be immutable) and will need to be re-entered each time you load and analyse the data - change the .md file, or export the data as PYMEs native .h5 format if you want to keep the changes.
## Converting the data to PYMEs native .h5 (old method)¶
There are a number of scripts to convert different data types (currently Raw, Tiff sequences, kdf stacks, and sequences of kdfs) to .h5 in the PYME.io.FileUtils folder. This approach is a little inelegant, because you need to add all the metadata entries manually in dh5view, but can be useful in some circumstances (notably there is not yet support for directly analysing raw of kdf data).