### Install kglab

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/practical_examples/knowledge_graph.html

Install the kglab package using pip. This is the first step before using kglab in the knowledge graph example.

```python
#!pip install kglab

```

--------------------------------

### Create an example HDF5 file with coordinates

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/wrapper/DatasetSlicing.ipynb

Creates an example HDF5 file using h5rdmtoolbox. The make_scale and attach_scale arguments set up coordinates and associate them with the dataset 'data'.

```python
with h5tbx.File('example.h5', 'w') as h5:
    h5.create_dataset('data', data=np.random.rand(10, 10))
    h5['data'].make_scale('x')
    h5['data'].attach_scale('x', 'x')
```

--------------------------------

### Start the linked-data web viewer with h5tbx serve

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/ld/web_viewer.rst

Use h5tbx serve to start the web viewer. Provide a file or directory, optionally filter by extensions, and set a file URI and local IRI pattern for DOI resolution.

```bash
h5tbx serve example.h5
h5tbx serve data/ --h5ext=.h5 --h5ext=.hdf5
h5tbx serve example.h5 --file-uri https://doi.org/10.5281/zenodo.17572275# --local-iri-pattern "https://doi.org/10.5281/zenodo.*"
```

--------------------------------

### Example convention YAML file

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/convention/creating_a_new_convention.ipynb

A complete example of a convention file named example_convention.yaml, including header metadata, standard attribute definitions, and custom type validators.

```yaml
# filename: example_convention.yaml
# 1. General information at the header
#-------------------------------------
__name__: h5rdmtoolbox-tuturial-convention
__institution__: https://orcid.org/members/001G000001e5aUTIAY
__contact__: https://orcid.org/0000-0001-8729-0482


# 2. Definition of standard attributes
#-------------------------------------
units:
  target_method: create_dataset
  validator: $units
  description: The physical unit of the dataset. If dimensionless, the unit is ''.
  default_value: $EMPTY

contact_id:
  description: ID of a person to contact for questions.
  target_method: __init__
  validator: $str
  default_value: $EMPTY

comment:
  description: Comment to a dataset
  target_method: create_dataset
  validator: $regex(^[A-Z].*)
  default_value: $NONE
  
data_type:
  description: 'Type of data in file. Can be numerical or experimental'
  target_method: __init__
  validator: $dataSourceTypes

# 3. Special type definitions
#----------------------------
$dataSourceTypes:
  - numerical
  - experimental
```

--------------------------------

### Download example Photon-HDF5 file

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/practical_examples/photon_hdf5.ipynb

Downloads the example Photon-HDF5 file from figshare if it is not already present locally. The file is saved as 'test_photon_file.hdf5' in the current directory.

```python
import requests
import pathlib

if not pathlib.Path('test_photon_file.hdf5').exists():
    r = requests.get('https://figshare.com/ndownloader/files/2182602')

    with open('test_photon_file.hdf5', 'wb') as f:
        f.write(r.content)
```

--------------------------------

### Create example data with h5rdmtoolbox

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/layout/getting_started.html

Creates example data for layout validation: two datasets with different compression types and a group with an attribute. The output includes a deprecation warning about creating a dataset without data or dtype.

```python
import h5rdmtoolbox as h5tbx
with h5tbx.File() as h5:
    h5.create_dataset('u', shape=(3, 5), compression='lzf')
    h5.create_dataset('v', shape=(3, 5), compression='gzip')
    h5.create_group('instruments', attrs={'description': 'Instrument data'})
    h5.dump()

```

--------------------------------

### Download NeXus example file

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/practical_examples/nexus.ipynb

Downloads a sample NeXus file from the nexusformat exampledata repository if it does not already exist locally.

```python
import requests
import pathlib

if not pathlib.Path('file.nxs').exists():
    r = requests.get('https://github.com/nexusformat/exampledata/raw/master/Soleil/hdf5/file_1.nxs')
    with open('file.nxs', 'wb') as f:
        f.write(r.content)
```

--------------------------------

### Install kglab

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/practical_examples/knowledge_graph.ipynb

Install the kglab package, which is required for building and visualizing knowledge graphs from HDF5 data.

```python
#!pip install kglab
```

--------------------------------

### Install h5RDMtoolbox optional dependencies

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/gettingstarted/installation.rst

Installs optional dependencies for h5RDMtoolbox. The database extra requires a separately installed MongoDB server. The complete extra installs all the above dependencies.

```sh
# install dependencies to use the database (MongoDB)
pip install h5RDMtoolbox[database]
# Note: MongoDB server must be installed separately

# install dependencies for testing
pip install h5RDMtoolbox[test]

# install dependencies needed to build this documentation
pip install h5RDMtoolbox[docs]

# install all above dependencies
pip install h5RDMtoolbox[complete]

# install dependencies for CSV support
pip install h5RDMtoolbox[csv]

# install dependencies for standard name tables
pip install h5RDMtoolbox[snt]

# install dependencies for catalog/SPARQL queries
pip install h5RDMtoolbox[catalog]
```

--------------------------------

### Create database and collection

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/database/mongoDB.ipynb

Creates a database named 'h5database_notebook_tutorial' and a collection named 'digits', then drops all content to start fresh.

```python
db = client['h5database_notebook_tutorial']
collection = db['digits']

# drop all content in order to start from scratch:
collection.drop()
```

--------------------------------

### Import h5rdmtoolbox and tutorial modules

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/faq/faq004.ipynb

Imports the h5rdmtoolbox library and its tutorial module, which provides access to example convention files.

```python
import h5rdmtoolbox as h5tbx
from h5rdmtoolbox import tutorial
```

--------------------------------

### Import Zenodo and h5rdmtoolbox

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/repository/zenodo.ipynb

Imports the Zenodo repository module and the h5rdmtoolbox package for the example workflow.

```python
from h5rdmtoolbox.repository import zenodo
import h5rdmtoolbox as h5tbx
```

--------------------------------

### Set h5rdmtoolbox backend to h5py

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/wrapper/GroupCreation.ipynb

Initializes the h5rdmtoolbox library and sets the backend to h5py. This is a prerequisite for the subsequent examples.

```python
import h5rdmtoolbox as h5tbx

h5tbx.use(None)
```

--------------------------------

### Import download_file and pprint

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/wrapper/FAIRAttributes.ipynb

Imports `download_file` from h5rdmtoolbox.utils and `pprint` for pretty printing. Used in the example to download a file.

```python
from h5rdmtoolbox.utils import download_file
from pprint import pprint
```

--------------------------------

### Import required libraries

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/ld/getting_started.ipynb

Imports numpy, rdflib, h5rdmtoolbox, and Path for the linked data example.

```python
import numpy as np
import rdflib
import h5rdmtoolbox as h5tbx
from pathlib import Path
```

--------------------------------

### Import h5rdmtoolbox and select h5py backend

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/wrapper/CreateFile.html

Sets up the h5rdmtoolbox environment by importing the package and selecting the h5py backend. The first block initializes the toolbox, and the second block activates the h5py backend for subsequent file operations.

```python
import h5rdmtoolbox as h5tbx
h5tbx.use(None)

```

```python
using("h5py")

```

--------------------------------

### Configure h5rdmtoolbox to disable auto version

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/practical_examples/metadata4ing.html

Configures h5rdmtoolbox to disable automatic creation of the h5tbx version attribute. This setup is required before using the library in the examples.

```python
import h5rdmtoolbox as h5tbx
_ = h5tbx.set_config(auto_create_h5tbx_version=False)

```

--------------------------------

### Get first match with h5.find_one

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/database/hdfDB.html

Use h5.find_one to retrieve only the first matching dataset. The example searches for standard_name 'velocity' and units 'm', returning a single lazy dataset object.

```python
with h5tbx.File(filename) as h5:
    res = h5.find_one(flt={'standard_name': 'velocity', 'units': 'm'})

res

```

```text
<LDataset "/velocity" in "/home/docs/.local/share/h5rdmtoolbox/2.8.1/tmp/tmp_1006_0/tmp0.hdf" attrs=(units=m/s, standard_name=velocity, check_value=14.2)>

```

--------------------------------

### Get call and failure counts for compression specification

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/layout/getting_started.ipynb

Returns a tuple with the number of calls and the number of failures for the compression specification. In this example, it returns (2, 1), indicating two calls and one failure.

```python
spec_compression.n_calls, spec_compression.n_fails
```

--------------------------------

### Using a database interface

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/database/firstSteps.ipynb

Example showing how to use a database interface to insert datasets and groups into a database and perform find operations.

```python
import h5rdmtoolbox as h5tbx

mydb = MyDBInterface()

with h5tbx.File() as h5:
    h5.create_group('a group')
    h5.create_dataset('my_dataset', shape=(4, 2))
    # ... 
    mydb.insert_dataset(h5['my_dataset'])
    mydb.insert_group(h5['a group'])

many_res = mydb.find(...)
single_res = mydb.find_one(...)
```

--------------------------------

### Layout.__init__

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/generated/h5rdmtoolbox.layout.Layout.rst

Initializes a new Layout instance.

```APIDOC
## Layout.__init__

### Description
Initializes a new Layout instance.

### Method
__init__

### Signature
`__init__(self, ...)`

### Parameters
No parameters documented.

### Returns
None

```

--------------------------------

### Pint-xarray unit conversion example

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/wrapper/DatasetSlicing.html

Example of using pint-xarray to quantify and convert units, which is what to_units does under the hood.

```python
# note, that we need to call the "pint"-accessory every time to make the xarray object
quantified_data = data.pint.quantify(unit_registry=h5tbx.get_ureg())

u_mm_s = quantified_data.pint.to('mm/s').pint.dequantify()
u_mm_s.units

```

--------------------------------

### Initialize ZenodoRecord with sandbox

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/repository/zenodo.ipynb

Initializes a ZenodoRecord instance with sandbox=True to use the testing environment.

```python
repo = zenodo.ZenodoRecord(None, sandbox=True)
```

--------------------------------

### ModuleNotFoundError for kglab

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/practical_examples/knowledge_graph.html

Error output showing that the kglab module is not installed. This occurs when running the import without installing kglab first.

```text
---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
Cell In[2], line 1
----> 1 import kglab
      2 import rdflib
      3 import numpy as np

ModuleNotFoundError: No module named 'kglab'

```

--------------------------------

### Install h5RDMtoolbox with pip

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/gettingstarted/installation.rst

Installs the h5RDMtoolbox package. Requires Python 3.9 or higher; automatic testing is performed for Python 3.9-3.13.

```sh
pip install h5RDMtoolbox
```

--------------------------------

### Get shape of inserted dataset

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/database/mongoDB.html

Get the shape of the lazy dataset from the found document. Expected output: (1797, 8, 8).

```python
res[()].shape

```

--------------------------------

### Initialize h5rdmtoolbox with h5tbx.use(None)

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/database/hdfDB.ipynb

Initializes the h5rdmtoolbox environment by disabling any default backend. Required before using tutorial data in this chapter.

```python
import h5rdmtoolbox as h5tbx
from h5rdmtoolbox import tutorial

h5tbx.use(None)
```

--------------------------------

### DownloadFileManager.__init__()

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/generated/h5rdmtoolbox.utils.DownloadFileManager.html

Initializes the DownloadFileManager instance. This class is a singleton, so only one instance can be created.

```APIDOC
## DownloadFileManager.__init__()

### Description
Initializes the DownloadFileManager instance. This constructor is part of the DownloadFileManager class, which manages downloading files by registering checksums and filenames. The class is a singleton, so only one instance can be created.

### Signatures
- `__init__()`
- `__init__(*args, **kwargs)`

### Usage
Used to create or access the singleton instance of the DownloadFileManager.

```

--------------------------------

### Import h5rdmtoolbox and use None

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/wrapper/NaturalNaming.html

Initializes the h5rdmtoolbox library and sets the backend to None (default).

```python
import h5rdmtoolbox as h5tbx
h5tbx.use(None)

```

--------------------------------

### YAML example for create_from_yaml

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_modules/h5rdmtoolbox/wrapper/core.html

Example YAML content for create_from_yaml. Defines groups, datasets, and attributes relative to the current group level. Supports overwrite and num_dtype options.

```yaml
>>> title: 'Title of the file'
>>> contact: '0000-1234-1234-1234'
>>> grp:
>>>   attrs:
>>>     comment: test
>>> grp/subgrp/y:
>>>   data: 2
>>>   overwrite: True
>>>   attrs:
>>>     units: 'm/s'
>>> grp/subgrp:
>>>   attrs:
>>>     comment: This is a group comment
>>>   velocity:
>>>     data: [3.4, 1.1]
>>>     overwrite: True
>>>     attrs:
>>>       units: 'm/s'
```

--------------------------------

### Find slice by digit and get shape

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/database/mongoDB.html

Find one document where the 'digit' field equals 3 and get the shape of its dataset. Expected output: (1, 8, 8).

```python
one_res = mdb.find_one({'digit': {'$eq': 3}})
one_res[()].shape

```

--------------------------------

### Turtle RDF example of structural and semantic HDF5 metadata

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/ld/getting_started.html

Shows a Turtle RDF example contrasting structural HDF5 metadata with semantic annotations. It defines an HDF5 file with a dataset for mean temperature, including attributes for description and units, and links to semantic terms like m4i:NumericalVariable and schema:description. The snippet is truncated at the end, so the full example is not shown.

```turtle
@prefix hdf: <http://purl.allotrope.org/ontologies/hdf5/1.8#> .
@prefix m4i: <http://w3id.org/nfdi4ing/metadata4ing#> .
@prefix schema: <https://schema.org/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

hdf:H5T_IEEE_F64LE a hdf:Datatype .

[] a hdf:File ;
    hdf:rootGroup [ a hdf:Group ;
            hdf:member [ a hdf:Dataset,
                        m4i:NumericalVariable ;
                    hdf:attribute [ a hdf:StringAttribute ;
                            hdf:data "Mean room temperature" ;
                            hdf:name "description" ],
                        [ a hdf:StringAttribute ;
                            hdf:data "degree_Celsius" ;
                            hdf:name "units" ] ;
                    hdf:dataspace [ a hdf:ScalarDataspace ] ;
                    hdf:datatype hdf:H5T_FLOAT,
                        hdf:H5T_IEEE_F64LE ;
                    hdf:layout hdf:H5D_CONTIGUOUS ;
                    hdf:maximumSize -1 ;
                    hdf:name "/mean_temperature" ;
                    hdf:rank 0 ;
                    hdf:size 1 ;
                    hdf:value 2.05e+01 ;
                    m4i:hasNumericalValue "20.5"^^xsd:float ;
                    m4i:hasUnit <http://qudt.org/vocab/unit/DEG_C> ;
                    schema:description "Mean room temperature" ],
                [ a hdf:Dataset ;
                    hdf:attribute [ a hdf:StringAttribute ;
                            hdf:data "Room temperature measurements" ;
                            hdf:name "description" ],
                        [ a hdf:StringAttribute ;
                            hdf:data "degree_Celsius" ;
                            hdf:name "units" ] ;
                    hdf:dataspace [ a hdf:SimpleDataspace ;
                            hdf:dimension [ a hdf:DataspaceDimension ;
                                    hdf:dimensionIndex 0 ;
                                    hdf:size 4 ] ] ;
                    hdf:datatype hdf:H5T_FLOAT,
             
```

--------------------------------

### Enable convention with h5tbx.use

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/gettingstarted/quickoverview.html

Enables the loaded convention. The output confirms the convention is in use.

```python
h5tbx.use(cv)

```

```text
using("h5rdmtoolbox-tutorial-convention")

```

--------------------------------

### Import dependencies and select h5py backend

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/database/mongoDB.html

Sets up the environment for the MongoDB tutorial: imports pymongo, mongomock (for docs/testing), h5rdmtoolbox, numpy, and pprint, then disables the default HDF5 backend with h5tbx.use(None). The second block selects the h5py backend via using("h5py").

```python
import pymongo
# from pymongo import MongoClient
from mongomock import MongoClient  # for docs or testing only

from h5rdmtoolbox import tutorial
import h5rdmtoolbox as h5tbx

import numpy as np
from pprint import pprint

h5tbx.use(None)

```

```python
using("h5py")

```

--------------------------------

### h5rdmtoolbox package initialization and logging setup

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_modules/h5rdmtoolbox.html

Initializes the h5rdmtoolbox package: configures logging with a stream handler and a rotating file handler, sets up the unit registry, registers the h5py convention, and imports core modules. The logger writes to USER_LOG_DIR/h5rdmtoolbox.log with DEBUG level for file and WARNING for console.

```python
"""h5rdmtoolbox repository"""

import logging
import pathlib
from logging.handlers import RotatingFileHandler
from typing import Optional, Dict

import rdflib

from ._version import __version__
from .user import USER_LOG_DIR, USER_DATA_DIR

DEFAULT_LOGGING_LEVEL = logging.WARNING
_formatter = logging.Formatter(
    '%(asctime)s,%(msecs)d %(levelname)-8s [%(filename)s:%(lineno)d] %(message)s',
    datefmt='%Y-%m-%d_%H:%M:%S')

_stream_handler = logging.StreamHandler()
_stream_handler.setLevel(DEFAULT_LOGGING_LEVEL)
_stream_handler.setFormatter(_formatter)

_file_handler = RotatingFileHandler(USER_LOG_DIR / 'h5rdmtoolbox.log', delay=True)
_file_handler.setLevel(logging.DEBUG)  # log everything to file!
_file_handler.setFormatter(_formatter)

logger = logging.getLogger(__package__)
logger.addHandler(_stream_handler)
logger.addHandler(_file_handler)

import atexit
# noinspection PyUnresolvedReferences
import pint_xarray
import shutil
import xarray as xr
from typing import Union, Callable
from pydantic import HttpUrl

from h5rdmtoolbox._cfg import set_config, get_config, get_ureg

pint_xarray.unit_registry = get_ureg()

from . import convention
from .convention.core import Convention
from . import wrapper
from .user import UserDir
from ._version import __version__
from . import utils
from .wrapper.core import lower, Lower, File, Group, Dataset
from . import errors
from .wrapper import jsonld
from .database.lazy import lazy
from .wrapper.h5attr import Attribute
import json
from .wrapper.accessor import register_accessor

from .ld.shacl import validate_hdf, ValidationResult
from .ld._types import RDFMappingEntry
# noinspection PyUnresolvedReferences
from .utils import DownloadFileManager

name = 'h5rdmtoolbox'
__this_dir__ = pathlib.Path(__file__).parent
__author__ = 'Matthias Probst'
__author_orcid__ = 'https://orcid.org/0000-0001-8729-0482'


def get_package_meta() -> Dict:
    """Reads codemeta.json and returns it as dict"""
    with open(__this_dir__ / '../codemeta.json', 'r') as f:
        codemeta = json.loads(f.read())
    return codemeta


cv_h5py = convention.Convention(name='h5py',
                                contact=__author_orcid__)
cv_h5py.register()

use = convention.core.use
use(None)
```

--------------------------------

### Vector example output: xarray.Dataset, data arrays, and coordinate indexes

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/misc/Extensions.html

Output of the Vector example: the xarray.Dataset representation, the data arrays for xvel and yvel, and the PandasIndex objects for the y and x coordinates. These are the printed results from the preceding Vector code block.

```text
<xarray.Dataset> Size: 136B
Dimensions:  (y: 2, x: 3)
Coordinates:
  * y        (y) int64 16B 2 3
  * x        (x) int64 24B 1 2 3
Data variables:
    xvel     (y, x) float64 48B 0.9919 0.7565 0.3806 0.6557 0.6515 0.01967
    yvel     (y, x) float64 48B 0.2993 0.8466 0.04372 0.88 0.8598 0.2207
Attributes:
    long_name:  x vel
    units:      m/s

```

```text
array([[0.99190512, 0.75645821, 0.38064616],
       [0.65569809, 0.65153778, 0.01966631]])

```

```text
array([[0.29928468, 0.84656168, 0.04372209],
       [0.88003235, 0.85982443, 0.22072619]])

```

```text
PandasIndex(Index([2, 3], dtype='int64', name='y'))

```

```text
PandasIndex(Index([1, 2, 3], dtype='int64', name='x'))

```

--------------------------------

### FileDB.__init__

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/generated/h5rdmtoolbox.database.FileDB.rst

Initializes a new FileDB instance. The constructor is automatically documented and likely accepts parameters for database configuration.

```APIDOC
## FileDB.__init__

### Description
Initializes a new FileDB instance. The constructor is automatically documented and likely accepts parameters for database configuration.

### Method
Constructor

### Signature
`FileDB.__init__(...)`

### Parameters
No explicit parameters are documented in the source.

### Returns
A new FileDB instance.

```

--------------------------------

### Metadata4Ing example in Turtle RDF

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/practical_examples/metadata4ing.html

Turtle RDF describing a Metadata4Ing example with processing steps, tools, and a numerical variable. It defines a FileSet, a Person with ORCID, a Method, and a ProcessingStep for XRCT scanning, including a voltage variable with unit KiloV.

```turtle
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix m4i: <http://w3id.org/nfdi4ing/metadata4ing#> .
@prefix ns1: <http://purl.obolibrary.org/obo/> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix schema: <https://schema.org/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://local-domain.org/tmp1.hdf/metadata/FileSet> schema:about <https://local-domain.org/output/xrct-data> .

<https://local-domain.org/tmp1.hdf/metadata/FineTec%20FORE%20180.01C%20TT> schema:about <https://local-domain.org/xray_source_finetec_180.01ctt_0001> .

<https://local-domain.org/tmp1.hdf/metadata/Image%20Processing%20and%20Reconstruction> schema:about <https://local-domain.org/reconstruction_0001> .

<https://local-domain.org/tmp1.hdf/metadata/Person> schema:about <https://local-domain.org/alex> .

<https://local-domain.org/tmp1.hdf/metadata/Post%20Processing> schema:about <https://local-domain.org/postprocessing_0001> .

<https://local-domain.org/tmp1.hdf/metadata/Sample%20preparation%20and%20parameter%20definition> schema:about <https://local-domain.org/preparation_0001> .

<https://local-domain.org/tmp1.hdf/metadata/Standard%20cone%20beam%20scanning> schema:about <https://local-domain.org/cone_beam_scanning> .

<https://local-domain.org/tmp1.hdf/metadata/Standard%20cone%20beam%20scanning/parameter> schema:about <https://local-domain.org/xray_tube_voltage> .

<https://local-domain.org/tmp1.hdf/metadata/XRCT-Scan> schema:about <https://local-domain.org/xrctscan_0001> .

<https://local-domain.org/alex> a foaf:Person ;
    m4i:orcidId "0000-0000-0123-4567" ;
    foaf:lastName "Test" .

<https://local-domain.org/cone_beam_scanning> a m4i:Method ;
    rdfs:label "scanning" ;
    dcterms:description "sample" ;
    m4i:hasParameter <https://local-domain.org/xray_tube_voltage> .

<https://local-domain.org/output/xrct-data> a m4i:FileSet ;
    dcterms:description "image-files" ;
    m4i:includes "tiff" .

<https://local-domain.org/postprocessing_0001> a m4i:ProcessingStep ;
    rdfs:label "Processing" .

<https://local-domain.org/preparation_0001> a m4i:ProcessingStep ;
    rdfs:label "definition" ;
    m4i:hasParticipant "alex" ;
    m4i:startTime "2026-06-22T00:00:00"^^xsd:dateTime .

<https://local-domain.org/reconstruction_0001> a m4i:ProcessingStep ;
    rdfs:label "Reconstruction" ;
    ns1:RO_0002233 "xrct_data_0001" .

<https://local-domain.org/xray_source_finetec_180.01ctt_0001> a m4i:Tool ;
    rdfs:label "TT" .

<https://local-domain.org/xrctscan_0001> a m4i:ProcessingStep ;
    rdfs:label "XRCT-Scan" ;
    ns1:RO_0002234 "xrct-data" ;
    m4i:hasEmployedTool "xray_source_finetec_180.01ctt_0001" ;
    m4i:investigates <https://www.wikidata.org/wiki/Q189259> ;
    m4i:investigatesProperty <https://www.wikidata.org/wiki/Q256699> ;
    m4i:realizesMethod "cone_beam_scanning" .

<https://local-domain.org/xray_tube_voltage> a m4i:NumericalVariable ;
    rdfs:label "Voltage" ;
    m4i:hasKindOfQuantity <http://qudt.org/vocab/quantitykind/ElectricPotential> ;
    m4i:hasNumericalValue "140" ;
    m4i:hasUnit <http://qudt.org/vocab/unit/KiloV> .

```

--------------------------------

### Compare method signatures with and without convention

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/convention/creating_a_new_convention.ipynb

Defines a helper to print method parameters and compares the signature of h5tbx.File.__init__ with no convention versus with the tutorial convention. The output shows that standard attributes like data_type and standard_name_table are added as bold parameters when the convention is active.

```python
import inspect

def print_method_parameters(method):
    print(f'\nParameters for "{method.__name__}":')
    for param in inspect.signature(method).parameters.values():
        if not param.name == 'self':
            if param.name in h5tbx.convention.get_current_convention().methods[h5tbx.File].get('__init__', {}).keys():
                print(f'  - {h5tbx._repr.make_bold(param.name)}')
            else:
                print(f'  - {param.name}')

methods = (h5tbx.File.__init__, h5tbx.Group.create_group, h5tbx.Group.create_dataset)

print('no convention: ')
h5tbx.use(None)
print_method_parameters(h5tbx.File.__init__)

print(f'\n------------\nwith convention {cv.name}: (standard attributes are made bold)')
h5tbx.use(cv)
print_method_parameters(h5tbx.File.__init__)
```

--------------------------------

### Output of get_checksum

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/misc/FileProperties.html

Example output showing the checksum returned by the get_checksum function.

```text
'6781e0baec8d65b9a95a3e879a5098d1'

```

--------------------------------

### Create HDF5 file with datasets and scales

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/userguide/misc/Visualization.ipynb

Creates an HDF5 file with datasets and scales, then dumps the structure. Use to set up data for visualization examples.

```python
with h5tb.File() as h5:
    dsx = h5.create_dataset('x', data=np.linspace(0, 10, 20), attrs=dict(units='mm', long_name='x'), make_scale=True)
    dsy = h5.create_dataset('y', data=np.linspace(0, 5, 10), attrs=dict(units='mm', long_name='y'), make_scale=True)
    dsz = h5.create_dataset('z', data=np.linspace(0, 3, 4), attrs=dict(units='mm', long_name='z'), make_scale=True)
    h5.create_dataset('data', data=np.random.random((10, 20)), attrs=dict(units='m/s', long_name='velocity'), attach_scales=(dsy, dsx))
    
    xx, yy, zz = np.meshgrid(dsy.values[:], dsz.values[:], dsx.values[:])
    
    h5.create_dataset('u', data=np.sin(xx), attrs=dict(units='m/s', long_name='x_velocity'), attach_scales=(dsz, dsy, dsx))
    h5.create_dataset('v', data=yy, attrs=dict(units='m/s', long_name='y_velocity'), attach_scales=(dsz, dsy, dsx))
    h5.create_dataset('w', data=np.ones((4, 10, 20)), attrs=dict(units='m/s', long_name='z_velocity'), attach_scales=(dsz, dsy, dsx))
    h5.dump()
```

--------------------------------

### Get current convention property

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_modules/h5rdmtoolbox/wrapper/core.html

Property that returns the currently enabled convention.

```python
@property
    def convention(self):
        """Return the convention currently enabled."""
        return self._convention
```

--------------------------------

### FileDB.__init__()

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/generated/h5rdmtoolbox.database.FileDB.html

Initializes a FileDB instance for a single HDF5 file, specifying the filename of the HDF5 file to interface with.

```APIDOC
## FileDB.__init__()

### Description
Initializes a FileDB instance, creating a database interface for a single HDF5 file.

### Parameters
- **filename** (string) - Required - The path to the HDF5 file for which the database interface is created.

### Method Signature
```python
class h5rdmtoolbox.database.FileDB(filename)
```
```

--------------------------------

### File.get_groups

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/generated/h5rdmtoolbox.wrapper.core.File.rst

Gets all groups in the file. This method is part of the File class API.

```APIDOC
## File.get_groups

### Description
Gets all groups in the file.

### Method
Method

### Signature
`File.get_groups(...)`

### Parameters
No parameters are explicitly documented in the source.

### Returns
No return value is explicitly documented.

```

--------------------------------

### Load and activate convention from YAML file

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/faq/faq004.ipynb

Retrieves the filename of a tutorial convention YAML file, creates a Convention object from it using Convention.from_yaml(), and activates it with h5tbx.use(). The output shows the activated convention name.

```python
yaml_filename = tutorial.get_convention_yaml_filename()

cv = h5tbx.convention.Convention.from_yaml(yaml_filename)
h5tbx.use(cv)
```

--------------------------------

### File.get_datasets

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/generated/h5rdmtoolbox.wrapper.core.File.rst

Gets all datasets in the file. This method is part of the File class API.

```APIDOC
## File.get_datasets

### Description
Gets all datasets in the file.

### Method
Method

### Signature
`File.get_datasets(...)`

### Parameters
No parameters are explicitly documented in the source.

### Returns
No return value is explicitly documented.

```

--------------------------------

### File.get

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/generated/h5rdmtoolbox.wrapper.core.File.rst

Gets an item from the file. This method is part of the File class API.

```APIDOC
## File.get

### Description
Gets an item from the file.

### Method
Method

### Signature
`File.get(...)`

### Parameters
No parameters are explicitly documented in the source.

### Returns
No return value is explicitly documented.

```

--------------------------------

### Create layout and add specifications

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/gettingstarted/quickoverview.html

Create a Layout instance and add specifications using FileDB.find queries. The first specification matches all datasets, and the second is added to the first, requiring the 'units' attribute to exist. The layout's specifications are then displayed.

```python
lay = Layout()

spec_all_dataset = lay.add(
    FileDB.find,  # query function
    flt={},
    objfilter='dataset',
    n=None
)

# The following specification is added to the previous.
# This will apply the query only on results found by the previous query
spec_compression = spec_all_dataset.add(
    FileDB.find,
    flt={'units': {'$exists': True}}, # attribute "units" exists
    n=1
)

# we added one specification to the layout. let's check:
lay.specifications  # note, that the second specification is not shown, because it is part of the first one

```

--------------------------------

### Pint-xarray output units

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/wrapper/DatasetSlicing.html

Output of the pint-xarray example showing the resulting units string.

```text
'mm/s'

```

--------------------------------

### Import rdflib

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/gettingstarted/quickoverview.ipynb

Imports the rdflib library, which is used for RDF-related operations in the subsequent examples.

```python
import rdflib
```

--------------------------------

### Create dataset using __setitem__ with attributes and compression

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/wrapper/DatasetCreation.html

Creates a dataset using the __setitem__ syntax, specifying data, attributes, and gzip compression. The dump() output shows the resulting dataset.

```python
with h5tbx.File() as h5:
    h5['x'] = ([1,2,3], dict(attrs={'hello': 'world'}, compression='gzip'))
    h5.dump()

```

```text
  * /(1) x (3) [int64]
      * hello: world

```

--------------------------------

### File.get_tree_structure

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/generated/h5rdmtoolbox.wrapper.core.File.rst

Gets the tree structure of the file. This method is part of the File class API.

```APIDOC
## File.get_tree_structure

### Description
Gets the tree structure of the file.

### Method
Method

### Signature
`File.get_tree_structure(...)`

### Parameters
No parameters are explicitly documented in the source.

### Returns
No return value is explicitly documented.

```

--------------------------------

### File.get_group_names

Source: https://h5rdmtoolbox.readthedocs.io/en/latest/_sources/generated/h5rdmtoolbox.wrapper.core.File.rst

Gets the names of all groups in the file. This method is part of the File class API.

```APIDOC
## File.get_group_names

### Description
Gets the names of all groups in the file.

### Method
Method

### Signature
`File.get_group_names(...)`

### Parameters
No parameters are explicitly documented in the source.

### Returns
No return value is explicitly documented.

```