This section describes the different file format and name conventions used in Picasso.
Picasso accepts three types of raw movie files: TIFF (preferably from μManager), raw binary data (file extension “.raw”) and the Nikon format .nd2.
When loading raw binary files, the user will be prompted for movie metadata such as the number of frames, number of pixels, etc. Alternatively, this metadata can be supplied by an accompanying metadata file with the same filename as the raw binary file, but with the extension .yaml. See
YAML Metadata Files for more details.
HDF5 is a generic and efficient binary file format for storing data. In Picasso, HDF5 files are used for storing tabular data of localization properties with the file extension .hdf5. Furthermore, Picasso saves the statistical properties of groups of localizations in an HDF5 file.
Generally, several datasets can be stored within an HDF5 file. These datasets are accessible by specifying a path within the HDF5 file, similar to a path of an operating system. When saving localizations, Picasso stores tabular data under the path
/locs. When saving statistical properties of groups of localizations, Picasso saves the table under the path
Importing HDF5 files in Pandas, MATLAB and Origin¶
In Pandas, use
In MATLAB, execute the command
locs = h5read(filename, dataset). Replace dataset with
/locs for localization files and with
/groups for pick property files.
In Origin, select
File > Import > HDF5 or drag and drop the file into the main window.
h5py. To load localizations, Picasso uses the function
load_locs(filename)` located in the
io.py package of Picasso.
Localization HDF5 Files¶
Localization HDF5 files must always be accompanied by a YAML metadata file with the same filename, but with the extension .yaml. See
YAML Metadata File for more details. The localization table is stored as a dataset of the HDF5 file in the path
/locs. This table can be visualized by opening the HDF5 file with
Picasso: Filter. The localization table can have an unlimited number of columns. Table 1 describes the meaning of Picasso’s main column names.
|Column Name||Description||C Data Type|
|frame||The frame in which the localization occurred, starting with zero for the first frame.||unsigned long|
|x||The subpixel x coordinate in camera pixels.||float|
|y||The subpixel y coordinate in camera pixels.||float|
|photons||The total number of detected photons from this event, not including background or camera offset.||float|
|sx||The Point Spread Function width in camera pixels.||float|
|sy||The Point Spread Function height in camera pixels.||float|
|bg||The number of background photons per pixel, not including the camera offset.||float|
|lpx||The localization precision in x direction, in camera pixels, as estimated by the Cramer-Rao Lower Bound of the Maximum Likelihood fit (Mortensen et al., Nat Meth, 2010).||float|
|lpy||The localization precision in y direction, in camera pixels, as estimated by the Cramer-Rao Lower Bound of the Maximum Likelihood fit (Mortensen et al., Nat Meth, 2010).||float|
|net_gradient||The net gradient of this spot which is defined by the sum of gradient vector magnitudes within the fitting box, projected to the spot center.||float|
|z||(Optional) The z coordinate fitted in 3D in nm. Please note the units are different for x and y coordinates.||float|
|d_zcalib||(Optional) The value of the D function used for z fitting with astigmatism, see the supplement to Huang et al. 2008.||float|
|likelihood||The log-likelihood of the fit. Only available for MLE fitting.||float|
|iterations||The number of iterations of the fit procedure. Only available for MLE fitting.||long|
|group||(Optional) An identifier to assign multiple localizations to groups, for example by picking regions of interest .||long|
|len||(Optional) The length of the event, if localizations from consecutive frames have been linked.||long|
|n||(Optional) The number of localizations in this event, if localizations from consecutive frames have been linked, potentially diverging from the “len” column due to a transient dark time tolerance.||long|
|photon_rate||(Optional) The mean number of photons per frame, if localizations from consecutive frames have been linked. The total number of photons is set in the “photons” column.||float|
HDF5 Pick Property Files¶
File > Save pick properties in
Picasso: Render, the properties of picked regions are stored in an HDF5 file. Within the HDF5 file, the data table is stored in the path
Each row in the “groups” table corresponds to one picked region. For each localization property (see Table 1), two columns are generated in the
groups table: the mean and standard deviation of the respective column over the localizations in a pick region. For example, if the localization table contains a column
len, the “groups” table will contain a column
Furthermore, the following columns are included:
group (the group identifier),
n_events (the number of localizations in the region) and
n_units (the number of units from a qPAINT measurement).
YAML Metadata Files¶
YAML files are document-oriented text files that can be opened and changed with any text editor. In Picasso, YAML files are used to store metadata of movie or localization files.
Each localization HDF5 file must always be accompanied with a YAML file of the same filename, except for the extension, which is
.yaml. Deleting this YAML metadata file will result in failure of the Picasso software!
Raw binary files (i.e., with extension
.raw) may be accompanied by a YAML metadata file to store data about the movie dimensions, etc. While the metadata file, in this case, is not required, it reduces the effort of typing in this metadata each time the movie is loaded with
Picasso: Localize. To generate such a YAML metadata file, load the raw movie into
Picasso: Localize, then enter all required information in the appearing dialog. Check the checkbox
Save info to yaml file and click ok. The movie will be loaded and the metadata saved in a YAML file. This file will be detected the next time this raw movie is loaded, and the metadata does not need to be entered again.