Metadata structure#

The BaseSignal class stores metadata in the metadata attribute, which has a tree structure. By convention, the node labels are capitalized and the leaves are not capitalized.

When a leaf contains a quantity that is not dimensionless, the units can be given in an extra leaf with the same label followed by the “_units” suffix. For example, an “energy” leaf should be accompanied by an “energy_units” leaf.

The metadata structure is represented in the following tree diagram. The default units are given in parentheses. Details about the leaves can be found in the following sections of this chapter.

metadata
├── General
|   |── FileIO
|   |   ├── 0
|   |   |   ├── operation
|   |   |   ├── hyperspy_version
|   |   |   ├── io_plugin
|   │   |   └── timestamp
|   |   ├── 1
|   |   |   ├── operation
|   |   |   ├── hyperspy_version
|   |   |   ├── io_plugin
|   │   |   └── timestamp
|   |   └── ...
│   ├── authors
│   ├── date
│   ├── doi
│   ├── original_filename
│   ├── notes
│   ├── time
│   ├── time_zone
│   └── title
├── Sample
│   ├── credits
│   ├── description
│   └── thickness
└── Signal
    ├── FFT
    │   └── shifted
    ├── Noise_properties
    │   ├── Variance_linear_model
    │   │   ├── correlation_factor
    │   │   ├── gain_factor
    │   │   ├── gain_offset
    │   │   └── parameters_estimation_method
    │   └── variance
    ├── quantity
    ├── signal_type
    └── signal_origin

General#

title

type: Str

A title for the signal, e.g. “Sample overview”

original_filename

type: Str

If the signal was loaded from a file this key stores the name of the original file.

time_zone

type: Str

The time zone as supported by the python-dateutil library, e.g. “UTC”, “Europe/London”, etc. It can also be a time offset, e.g. “+03:00” or “-05:00”.

time

type: Str

The acquisition or creation time in ISO 8601 time format, e.g. ‘13:29:10’.

date

type: Str

The acquisition or creation date in ISO 8601 date format, e.g. ‘2018-01-28’.

authors

type: Str

The authors of the data, in Latex format: Surname1, Name1 and Surname2, Name2, etc.

doi

type: Str

Digital object identifier of the data, e. g. doi:10.5281/zenodo.58841.

notes

type: Str

Notes about the data.

FileIO#

Contains information about the software packages and versions used any time the Signal was created by reading the original data format (added in HyperSpy v1.7) or saved by one of HyperSpy’s IO tools. If the signal is saved to one of the hspy, zspy or nxs formats, the metadata within the FileIO node will represent a history of the software configurations used when the conversion was made from the proprietary/original format to HyperSpy’s format, as well as any time the signal was subsequently loaded from and saved to disk. Under the FileIO node will be one or more nodes named 0, 1, 2, etc., each with the following structure:

operation

type: Str

This value will be either "load" or "save" to indicate whether this node represents a load from, or save to disk operation, respectively.

hyperspy_version

type: Str

The version number of the HyperSpy software used to extract a Signal from this data file or save this Signal to disk

io_plugin

type: Str

The specific input/output plugin used to originally extract this data file into a HyperSpy Signal or save it to disk – will be of the form rsciio.<plugin_name>.

timestamp

type: Str

The timestamp of the computer running the data loading/saving process (in a timezone-aware format). The timestamp will be in ISO 8601 format, as produced by the datetime.date.isoformat().

Sample#

credits

type: Str

Acknowledgment of sample supplier, e.g. Prepared by Putin, Vladimir V.

description

type: Str

A brief description of the sample

thickness

type: Float

The thickness of the sample in m.

Signal#

signal_type

type: Str

A term that describes the signal type, e.g. EDS, PES… This information can be used by HyperSpy to load the file as a specific signal class and therefore the naming should be standardised. Currently, HyperSpy provides special signal class for photoemission spectroscopy, electron energy loss spectroscopy and energy dispersive spectroscopy. The signal_type in these cases should be respectively PES, EELS and EDS_TEM (EDS_SEM).

signal_origin

type: Str

Describes the origin of the signal e.g. ‘simulation’ or ‘experiment’.

record_by

Deprecated since version 1.2.

type: Str

One of ‘spectrum’ or ‘image’. It describes how the data is stored in memory. If ‘spectrum’, the spectral data is stored in the faster index.

quantity

type: Str

The name of the quantity of the “intensity axis” with the units in round brackets if required, for example Temperature (K).

FFT#

shifted

type: bool.

Specify if the FFT has the zero-frequency component shifted to the center of the signal.

Noise_properties#

variance

type: float or BaseSignal instance.

The variance of the data. It can be a float when the noise is Gaussian or a BaseSignal instance if the noise is heteroscedastic, in which case it must have the same dimensions as data.

Variance_linear_model#

In some cases the variance can be calculated from the data using a simple linear model: variance = (gain_factor * data + gain_offset) * correlation_factor.

gain_factor: type: Float
gain_offset: type: Float
correlation_factor: type: Float
parameters_estimation_method: type: Str

_Internal_parameters#

This node is “private” and therefore is not displayed when printing the metadata attribute.

Stacking_history#

Generated when using stack(). Used by split(), to retrieve the former list of signal.

step_sizes

type: list of int

Step sizes used that can be used in split.

axis

type: int

The axis index in axes manager on which the dataset were stacked.

Folding#

Constains parameters that related to the folding/unfolding of signals.

Functions to handle the metadata#

Existing nodes can be directly read out or set by adding the path in the metadata tree:

s.metadata.General.title = 'FlyingCircus'
s.metadata.General.title

The following functions can operate on the metadata tree. An example with the same functionality as the above would be:

s.metadata.set_item('General.title', 'FlyingCircus')
s.metadata.get_item('General.title')

Adding items#

set_item(): Given a path and value, easily set metadata items, creating any necessary nodes on the way.
add_dictionary(): Add new items from a given dictionary.

Output metadata#

get_item(): Given an item_path, return the value of the metadata item.
as_dictionary(): Returns a dictionary representation of the metadata tree.
export(): Saves the metadata tree in pretty tree printing format in a text file. Takes filename as parameter.

Searching for keys#

has_item(): Given an item_path, returns True if the item exists anywhere in the metadata tree.

Using the option full_path=False, the functions has_item() and get_item() can also find items by their key in the metadata when the exact path is not known. By default, only an exact match of the search string with the item key counts. The additional setting wild=True allows to search for a case-insensitive substring of the item key. The search functionality also accepts item keys preceded by one or several nodes of the path (separated by the usual full stop).

has_item(): For full_path=False, given a item_key, returns True if the item exists anywhere in the metadata tree.
has_item(): For full_path=False, return_path=True, returns the path or list of paths to any matching item(s).
get_item(): For full_path=False, returns the value or list of values for any matching item(s). Setting return_path=True, a tuple (value, path) is returned – or lists of tuples for multiple occurences.