Metadata-Version: 2.4
Name: pynidm
Version: 4.3.2
Summary: PYNIDM: a Python NIDM library and tools
Home-page: https://github.com/incf-nidash/PyNIDM
Author: INCF-NIDASH developers
Author-email: incf-nidash-nidm@googlegroups.com
Maintainer: INCF-NIDASH developers
Maintainer-email: incf-nidash-nidm@googlegroups.com
License: Apache-2.0
Classifier: Development Status :: 3 - Alpha
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.. image:: Logo.png

PyNIDM: Neuroimaging Data Model in Python
##########################################

A Python library to manipulate the `Neuroimaging Data Model <http://nidm.nidash.org>`_.

|PyNIDM Testing| |Docs|

.. |PyNIDM Testing| image:: https://github.com/incf-nidash/PyNIDM/actions/workflows/pythontest.yml/badge.svg
    :target: https://github.com/incf-nidash/PyNIDM/actions/workflows/pythontest.yml
    :alt: Status of PyNIDM Testing

.. |Docs| image:: https://readthedocs.org/projects/pynidm/badge/?version=latest&style=plastic
    :target: https://pynidm.readthedocs.io/en/latest/
    :alt: ReadTheDocs Documentation of master branch

.. contents::
.. section-numbering::

Dependencies
============
* `Git-annex <https://git-annex.branchable.com/install/>`_
* `Graphviz <http://graphviz.org>`_ (native package):

  * Fedora: `dnf install graphviz`
  * OS-X: `brew install graphviz`

Installation
============

.. code:: bash

	$ pip install pynidm

Contributing to the Software
=============================
This software is open source and community developed.  As such, we encourage
anyone and everyone interested in semantic web and neuroimaging to contribute.
To begin contributing code to the repository, please fork the main repo into
your user space and use the pull request GitHub feature to submit code for
review.  Please provide a reasonably detailed description of what was changed
and why in the pull request.

To establish development environment, we recommend to install the
clone of this repository in development mode with development tools
installed via

.. code:: bash

	$ pip install -e .[devel]

We also recommend using
`pre-commit <https://github.com/pre-commit/pre-commit>`_ for ensuring
that your contributions would conform our conventions for code quality
etc. You can enable ``pre-commit`` by running once in your clone

.. code:: bash

	$ pre-commit install

which would then ensure that all commits would be subject to `black
<https://pypi.org/project/black/>`_ code reformatting etc.

Reporting Issues or Problems
============================
If you encounter a bug, you can directly report it in the issues section.
Please describe how to reproduce the issue and include as much information as
possible that can be helpful for fixing it. If you would like to suggest a fix,
please open a new pull request or include your suggested fix in the issue.

Support and Feedback
====================
We would love to hear your thoughts on our Python toolbox. Feedback, questions,
or feature requests can also be submitted as issues. Note, we are a small band
of researchers who mostly volunteer our time to this project.  We will respond
as quickly as possible.

NIDM Model Details
==================

NIDM files (typically ``nidm.ttl``) are `RDF Turtle
<https://www.w3.org/TR/turtle/>`_ documents that represent neuroimaging study
data using the `W3C PROV <https://www.w3.org/TR/prov-overview/>`_ provenance
data model.  Every entity, activity, and agent is identified by a URI and
connected by typed RDF triples, making NIDM data machine-readable, semantically
rich, and interoperable across sites and tools.

The terms and classes used in NIDM documents are formally defined in the
`NIDM-Experiment ontology <https://incf-nidash.github.io/nidm-experiment/>`_.
Community-based management of the controlled vocabulary used to annotate data
elements is described in `Keator et al., Frontiers in Neuroinformatics 2023
<https://doi.org/10.3389/fninf.2023.1174156>`_ and maintained in the
`NIDM-Terms repository <https://github.com/NIDM-Terms/terms>`_.

A formal `LinkML <https://linkml.io>`_ schema documenting the complete graph
structure is provided at
`src/nidm/experiment/schema/nidm_schema.yaml <https://github.com/dbkeator/PyNIDM/blob/master/src/nidm/experiment/schema/nidm_schema.yaml>`_.

Graph Hierarchy
---------------

A NIDM graph is organized as a hierarchy of W3C PROV objects.  Each node
carries one or more ``rdf:type`` assertions — one NIDM-specific type giving
its scientific role, and one PROV type giving its provenance role::

    Project  (nidm:Project + prov:Activity)
    │
    ├── Session  (nidm:Session + prov:Activity)          [dct:isPartOf → Project]
    │    │
    │    └── Acquisition  (nidm:Acquisition + prov:Activity)
    │         │                                          [dct:isPartOf → Session]
    │         └── AcquisitionObject  (nidm:AcquisitionObject + prov:Entity)
    │                                    [prov:wasGeneratedBy → Acquisition]
    │                                    [variable values stored as RDF properties]
    │
    ├── DataElement  (nidm:DataElement / nidm:PersonalDataElement + prov:Entity)
    │
    └── Derivative  (nidm:Derivative + prov:Activity)   [dct:isPartOf → Project]
         │
         └── DerivativeObject  (prov:Entity)            [prov:wasGeneratedBy → Derivative]
                                    [derived values stored as RDF properties]

**Project** is the top-level container for a study or dataset, holding title,
license, funding, and versioning metadata.

**Session** groups the acquisitions for one participant visit.

**Acquisition** represents a single data-collection event — an MRI scan, a
questionnaire, or a demographic entry.  Imaging acquisitions carry
``nidm:hadAcquisitionModality``, ``nidm:hadImageContrastType``, and
``nidm:hadImageUsageType``.

**AcquisitionObject** is the entity produced by an Acquisition.  For imaging
data it stores the filename and checksum; for assessments and demographics it
stores measured values as RDF properties, using DataElement URIs as predicates.

**Derivative / DerivativeObject** represent post-processing pipelines
(FreeSurfer, FSL, ANTs, etc.) and the analysis results they produce.

Participant Linkage
-------------------

Participants are ``prov:Person`` agents linked to Acquisitions through PROV's
qualified-association pattern::

    Acquisition
      └── prov:qualifiedAssociation
            └── prov:Association  (blank node)
                  ├── prov:agent    ──►  Person
                  │                       └── ndar:src_subject_id  "sub-001"
                  └── prov:hadRole  ──►  sio:Subject

``ndar:src_subject_id`` on the ``Person`` node is the primary
human-readable participant identifier across all PyNIDM query operations.

DataElements and Measurement Values
------------------------------------

DataElements define the semantics of every measured variable — its label,
data type, units, valid range, and linkage to a shared ontology concept via
``nidm:isAbout``.  Linking variables to concepts from the
`NIDM-Experiment ontology <https://incf-nidash.github.io/nidm-experiment/>`_
or community registries such as `InterLex <https://scicrunch.org/nidm-terms>`_
enables federated queries across datasets that use different local variable
names for the same underlying concept.

DataElement URIs serve a **dual role** in the graph:

1. **As subjects** — the DataElement URI carries all metadata about the
   variable (label, units, ontology mapping, etc.).
2. **As predicates** — the same URI is used as the RDF predicate on
   AcquisitionObjects and DerivativeObjects to store actual measured values.

A **PersonalDataElement** (demographic or assessment variable) in Turtle::

    niiri:gender_hrg8rh  a nidm:PersonalDataElement, prov:Entity ;
        rdfs:label              "gender" ;
        dct:description         "Gender of participant" ;
        nidm:sourceVariable     "gender" ;
        nidm:isAbout            ilx:ilx_0101292 ;
        nidm:valueType          xsd:complexType ;
        nidm:minValue           "NA" ;
        nidm:maxValue           "NA" ;
        reproschema:choices     [ rdfs:label "male"   ; reproschema:value "1" ],
                                [ rdfs:label "female" ; reproschema:value "2" ] ;
        ilx:ilx_0739289         "NIDM" .

    # Same DataElement URI used as a predicate to store a subject's value:
    niiri:acqobj_abc123  prov:wasGeneratedBy niiri:acq_456 ;
                         niiri:gender_hrg8rh  "1"^^xsd:string .

An **imaging pipeline DataElement** (e.g. from FreeSurfer)::

    fs:fs_000003  a nidm:DataElement ;
        rdfs:label           "Brain Segmentation Volume (mm^3)" ;
        nidm:isAbout         obo:UBERON_0000955 ;
        nidm:measureOf       ilx:ilx_0112559 ;
        nidm:datumType       ilx:ilx_0738276 ;
        nidm:unitCode        "mm^3" ;
        nidm:hasLaterality   "Bilateral" .

DataElement Property Reference
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

+----------------------------------+----------------------------------------------------------+
| RDF Predicate                    | Description                                              |
+==================================+==========================================================+
| ``rdf:type``                     | ``nidm:PersonalDataElement`` (demographic /              |
|                                  | assessment) or ``nidm:DataElement`` (imaging             |
|                                  | pipeline CDE), always combined with ``prov:Entity``      |
+----------------------------------+----------------------------------------------------------+
| ``rdfs:label``                   | Human-readable variable name                             |
+----------------------------------+----------------------------------------------------------+
| ``dct:description``              | Free-text description of the variable                    |
+----------------------------------+----------------------------------------------------------+
| ``rdfs:comment``                 | Longer formal definition (used when importing            |
|                                  | terms from external registries)                          |
+----------------------------------+----------------------------------------------------------+
| ``nidm:sourceVariable``          | Original column / variable name in the source            |
|                                  | dataset                                                  |
+----------------------------------+----------------------------------------------------------+
| ``nidm:isAbout``                 | URI of the ontology concept this variable                |
|                                  | represents (e.g. ``ilx:ilx_0100400`` for age).           |
|                                  | The key property enabling cross-dataset                  |
|                                  | concept-based federated queries.  See the                |
|                                  | `NIDM-Experiment ontology                                |
|                                  | <https://incf-nidash.github.io/nidm-experiment/>`_       |
|                                  | and `InterLex <https://scicrunch.org/nidm-terms>`_       |
+----------------------------------+----------------------------------------------------------+
| ``nidm:valueType``               | XSD datatype URI for the variable's values:              |
|                                  | ``xsd:float``, ``xsd:integer``, ``xsd:string``,          |
|                                  | ``xsd:boolean``, or ``xsd:complexType`` for              |
|                                  | categorical variables                                    |
+----------------------------------+----------------------------------------------------------+
| ``nidm:minValue``                | Minimum allowed value (``"NA"`` if not applicable)       |
+----------------------------------+----------------------------------------------------------+
| ``nidm:maxValue``                | Maximum allowed value (``"NA"`` if not applicable)       |
+----------------------------------+----------------------------------------------------------+
| ``nidm:unitCode``                | Unit of measurement string (e.g. ``"mm^3"``,             |
|                                  | ``"years"``, ``"vertex"``)                               |
+----------------------------------+----------------------------------------------------------+
| ``reproschema:choices``          | Categorical response options.  Each choice is a          |
|                                  | blank node with ``rdfs:label`` (display text) and        |
|                                  | ``reproschema:value`` (stored code), or a plain          |
|                                  | literal string for simple enumerations                   |
+----------------------------------+----------------------------------------------------------+
| ``nidm:measureOf``               | URI of the physical / biological property being          |
|                                  | measured (e.g. ``ilx:ilx_0112559`` for volume,           |
|                                  | ``obo:PATO_0001323`` for surface area).  Used            |
|                                  | primarily in imaging pipeline CDEs                       |
+----------------------------------+----------------------------------------------------------+
| ``nidm:datumType``               | URI of the measurement datum type (e.g.                  |
|                                  | ``ilx:ilx_0738276`` for scalar,                          |
|                                  | ``ilx:ilx_0102597`` for count).  Used primarily          |
|                                  | in imaging pipeline CDEs                                 |
+----------------------------------+----------------------------------------------------------+
| ``nidm:hasLaterality``           | Brain laterality: ``"Left"``, ``"Right"``, or            |
|                                  | ``"Bilateral"``.  Used in imaging pipeline CDEs          |
+----------------------------------+----------------------------------------------------------+
| ``nidm:url``                     | URL linking to this variable's entry in a                |
|                                  | terminology registry (e.g. InterLex / SciCrunch)         |
+----------------------------------+----------------------------------------------------------+
| ``nidm:sameAs``                  | URI of an equivalent term in another vocabulary          |
+----------------------------------+----------------------------------------------------------+
| ``bids:allowableValues``         | Allowable values for BIDS-sourced variables              |
+----------------------------------+----------------------------------------------------------+
| ``ilx:ilx_0739289``              | Terminology provenance tag (e.g. ``"NIDM"``)             |
|                                  | indicating which controlled vocabulary sourced           |
|                                  | this term                                                |
+----------------------------------+----------------------------------------------------------+

Key Namespaces
--------------

::

    nidm:          http://purl.org/nidash/nidm#
    prov:          http://www.w3.org/ns/prov#
    niiri:         http://iri.nidash.org/              (instance identifiers)
    ndar:          https://ndar.nih.gov/api/datadictionary/v2/dataelement/
    dct:           http://purl.org/dc/terms/
    dctypes:       http://purl.org/dc/dcmitype/
    sio:           http://semanticscience.org/ontology/sio.owl#
    obo:           http://purl.obolibrary.org/obo/
    onli:          http://neurolog.unice.fr/ontoneurolog/v3.0/instrument.owl#
    reproschema:   http://schema.repronim.org/
    ilx:           http://uri.interlex.org/
    freesurfer:    https://surfer.nmr.mgh.harvard.edu/
    fsl:           http://purl.org/nidash/fsl#
    ants:          http://stnava.github.io/ANTs/
    bids:          http://bids.neuroimaging.io/

Example SPARQL Queries
----------------------

List all projects and their titles:

.. code:: sparql

    PREFIX nidm:    <http://purl.org/nidash/nidm#>
    PREFIX dctypes: <http://purl.org/dc/dcmitype/>

    SELECT ?project ?title WHERE {
      ?project a nidm:Project .
      OPTIONAL { ?project dctypes:title ?title }
    }

List all subjects and their source IDs:

.. code:: sparql

    PREFIX prov: <http://www.w3.org/ns/prov#>
    PREFIX ndar: <https://ndar.nih.gov/api/datadictionary/v2/dataelement/>

    SELECT ?person ?subject_id WHERE {
      ?person a prov:Person ;
              ndar:src_subject_id ?subject_id .
    }

Retrieve values for a variable (e.g. ``AGE_AT_SCAN``) across all subjects:

.. code:: sparql

    PREFIX prov:  <http://www.w3.org/ns/prov#>
    PREFIX ndar:  <https://ndar.nih.gov/api/datadictionary/v2/dataelement/>
    PREFIX rdfs:  <http://www.w3.org/2000/01/rdf-schema#>

    SELECT ?subject_id ?value WHERE {
      ?de rdfs:label "AGE_AT_SCAN" .
      ?acq_obj ?de ?value ;
               prov:wasGeneratedBy ?acq .
      ?acq prov:qualifiedAssociation ?assoc .
      ?assoc prov:agent ?person .
      ?person ndar:src_subject_id ?subject_id .
    }

Find all DataElements about a given concept using ``nidm:isAbout``
(enables cross-dataset federated queries):

.. code:: sparql

    PREFIX nidm:  <http://purl.org/nidash/nidm#>
    PREFIX rdfs:  <http://www.w3.org/2000/01/rdf-schema#>

    SELECT DISTINCT ?de ?label ?sourceVar WHERE {
      { ?de a nidm:DataElement } UNION { ?de a nidm:PersonalDataElement }
      ?de nidm:isAbout <http://uri.interlex.org/ilx_0100400> ;
          rdfs:label ?label .
      OPTIONAL { ?de nidm:sourceVariable ?sourceVar }
    }

NIDM-Experiment Tools
=====================

BIDS MRI Conversion to NIDM
---------------------------

This program will convert a BIDS MRI dataset to a NIDM-Experiment RDF document.
It will parse phenotype information and simply store variables/values and link
to the associated json data dictionary file.  To use this tool please set your
INTERLEX_API_KEY environment variable to your unique API key.  To get an
Interlex API key you visit `SciCrunch <http://scicrunch.org/nidm-terms>`_,
register for an account, then click on "MyAccount" and "API Keys" to add a new
API key for your account.


.. code:: bash

   $ bidsmri2nidm -d [ROOT BIDS DIRECT] -bidsignore

   # Write one NIDM file per subject (sub-<id>_nidm.ttl) into the BIDS directory:
   $ bidsmri2nidm -d [ROOT BIDS DIRECT] --per_subject

   # Or direct the per-subject files to a different output directory:
   $ bidsmri2nidm -d [ROOT BIDS DIRECT] --per_subject -o [OUTPUT DIRECTORY]

   usage: bidsmri2nidm [-h] -d DIRECTORY [-jsonld] [-bidsignore] [-no_concepts]
                    [-json_map JSON_MAP] [-log LOGFILE] [-o OUTPUTFILE]
                    [-per_subject]

   This program will represent a BIDS MRI dataset as a NIDM RDF document and provide user with opportunity to annotate
   the dataset (i.e. create sidecar files) and associate selected variables with broader concepts to make datasets more
   FAIR.

   Note, you must obtain an API key to Interlex by signing up for an account at scicrunch.org then going to My Account
   and API Keys.  Then set the environment variable INTERLEX_API_KEY with your key.

   optional arguments:
     -h, --help            show this help message and exit
     -d DIRECTORY          Full path to BIDS dataset directory
     -jsonld, --jsonld     If flag set, output is json-ld not TURTLE
     -bidsignore, --bidsignore
                        If flag set, tool will add NIDM-related files to .bidsignore file
     -no_concepts, --no_concepts
                        If flag set, tool will no do concept mapping
     -log LOGFILE, --log LOGFILE
                        Full path to directory to save log file. Log file name is bidsmri2nidm_[basename(args.directory)].log
     -o OUTPUTFILE         Outputs turtle file called nidm.ttl in BIDS directory by default..or whatever path/filename is set here.
                           In ``--per_subject`` mode this argument is interpreted as an output **directory** (created if missing)
                           into which one ``sub-<id>_nidm.ttl`` file is written per subject.
     -per_subject, --per_subject
                        If flag set, a separate NIDM turtle file will be written for each subject in the BIDS directory,
                        named ``sub-<id>_nidm.ttl``.  By default these are placed in the BIDS directory; use ``-o`` to
                        specify a different output directory.  When combined with ``-bidsignore``, each per-subject file
                        is appended to the BIDS dataset's ``.bidsignore`` file (only when the output directory lies
                        inside the BIDS tree).

   map variables to terms arguments:
     -json_map JSON_MAP, --json_map JSON_MAP
                        Optional full path to user-suppled JSON file containing data element definitions.


CSV File to NIDM Conversion
---------------------------
This program will load in a CSV file and iterate over the header variable names
performing an elastic search of https://scicrunch.org/nidm-terms for
NIDM-ReproNim tagged terms that fuzzy match the variable names. The user will
then interactively pick a term to associate with the variable name. The
resulting annotated CSV data will then be written to a NIDM data file.  To use
this tool please set your INTERLEX_API_KEY environment variable to your unique
API key.  To get an Interlex API key you visit `SciCrunch
<http://scicrunch.org/nidm-terms>`_, register for an account, then click on
"MyAccount" and "API Keys" to add a new API key for your account.

.. code:: bash

  usage: csv2nidm [-h] -csv CSV_FILE [-json_map JSON_MAP | -csv_map CSV_MAP | -redcap REDCAP]
                  [-nidm NIDM_FILE] [-no_concepts] [-log LOGFILE]
                  [-dataset_id DATASET_ID] [-derivative DERIVATIVE_METADATA]
                  [-out OUTPUT_FILE]

  This program will load in a CSV file and iterate over the header variable
  names performing an elastic search of https://scicrunch.org/ for NIDM-ReproNim
  tagged terms that fuzzy match the variable names. The user will then
  interactively pick a term to associate with the variable name. The resulting
  annotated CSV data will then be written to a NIDM data file. Note, you must
  obtain an API key to Interlex by signing up for an account at scicrunch.org
  then going to My Account and API Keys. Then set the environment variable
  INTERLEX_API_KEY with your key.  The tool supports import of RedCap data
  dictionaries and will convert relevant information into a json-formatted
  annotation file used to annotate the data elements in the resulting NIDM file.

  optional arguments:
    -h, --help            show this help message and exit
    -csv CSV_FILE         Full path to CSV file to convert
    -json_map JSON_MAP    Full path to user-supplied JSON file containing
                          variable-term mappings.
    -csv_map CSV_MAP      Full path to a user-supplied CSV data dictionary with
                          columns: source_variable, label, description,
                          valueType, measureOf, isAbout, unitCode, minValue,
                          maxValue. Mutually exclusive with -json_map/-redcap.
    -redcap REDCAP        Full path to a user-supplied RedCap formatted data
                          dictionary for csv file.
    -nidm NIDM_FILE       Optional full path of NIDM file to add CSV->NIDM
                          converted graph to
    -no_concepts          If this flag is set then no concept associations will
                          be asked of the user. This is useful if you already
                          have a -json_map specified without concepts and want to
                          simply run this program to get a NIDM file without
                          user interaction to associate concepts.
    -log LOGFILE, --log LOGFILE
                          Full path to directory to save log file. Log file name
                          is csv2nidm_[arg.csv_file].log
    -dataset_id DATASET_ID
                          Optional dataset identifier (e.g. a DOI). When
                          provided, unique data element IDs incorporate this
                          value as part of their hash, ensuring CDE URIs are
                          globally unique across datasets.
    -derivative DERIVATIVE_METADATA
                          If set, indicates the CSV contains derivative data.
                          The value must be the path to a software metadata CSV
                          with columns: title, description, version, url,
                          cmdline, platform, ID. The CSV must also include
                          columns ses, task, run, and source_url.
    -out OUTPUT_FILE      Full path with filename to save NIDM file

convert
-------
This function will convert NIDM files to various RDF-supported formats and name
then / put them in the same place as the input file.

.. code:: bash

  Usage: pynidm convert [OPTIONS]

  Options:
    -nl, --nidm_file_list TEXT      A comma separated list of NIDM files with
                                    full path  [required]
    -t, --type [turtle|jsonld|xml-rdf|n3|trig]
                                    Output RDF serialization format  [required]
    -out, --outdir TEXT             Optional directory to save converted file.
                                    Defaults to the same directory as the input.
    --help                          Show this message and exit.

concatenate
-----------
This function will concatenate NIDM files.  Warning, no merging will be done so
you may end up with multiple prov:agents with the same subject id if you're
concatenating NIDM files from multiple visits of the same study.  If you want
to merge NIDM files on subject ID see pynidm merge

.. code:: bash

  Usage: pynidm concat [OPTIONS]

  Options:
    -nl, --nidm_file_list TEXT  A comma separated list of NIDM files with full
                              path  [required]
    -o, --out_file TEXT         File to write concatenated NIDM files
                              [required]
    --help                      Show this message and exit.

visualize
---------
This command produces a visualization of the supplied NIDM files as a directed
provenance graph, written to the same directory as each input file.

.. code:: bash

  Usage: pynidm visualize [OPTIONS]

  Options:
    -nl, --nidm_file_list TEXT    A comma-separated list of NIDM files with
                                  full path  [required]
    -fmt, --format [svg|png|pdf]  Output format (default: svg). SVG opens in
                                  any web browser with unlimited scroll and
                                  zoom. PNG produces a high-resolution raster.
                                  PDF is vector but may clip very large graphs.
    --help                        Show this message and exit.

merge
-----
This function will merge NIDM files.  See command line parameters for supported
merge operations.

.. code:: bash

   Usage: pynidm merge [OPTIONS]

   Options:
     -nl, --nidm_file_list TEXT  A comma separated list of NIDM files with full
                              path  [required]
     -s, --s                     If parameter set then files will be merged by
                              ndar:src_subjec_id of prov:agents
	 -o, --out_file TEXT         File to write concatenated NIDM files
                              [required]
	 --help                      Show this message and exit.

Query
-----
This function provides query support for NIDM graphs.  Exactly one query-type
option is required (the group is mutually exclusive).

.. code:: bash

    Usage: pynidm query [OPTIONS]

    Options:
      -nl, --nidm_file_list TEXT      A comma separated list of NIDM files with
                                      full path  [required]
      -nc, --cde_file_list TEXT       A comma separated list of NIDM CDE files
                                      with full path. Can also be set in the
                                      CDE_DIR environment variable

      Query Type (pick exactly one):
      -q, --query_file FILENAME       Text file containing a SPARQL query to
                                      execute
      -p, --get_participants          Return participant IDs and prov:agent
                                      entity IDs
      -i, --get_instruments           Return list of
                                      onli:assessment-instrument entries
      -iv, --get_instrument_vars      Return variables for all
                                      onli:assessment-instrument entries
      -de, --get_dataelements         Return all DataElements in NIDM file
      -debv, --get_dataelements_brainvols
                                      Return all brain volume DataElements with
                                      details
      -bv, --get_brainvols            Return all brain volume data elements and
                                      values with participant IDs
      -gf, --get_fields TEXT          Return data for a comma-separated list of
                                      field names across all NIDM files
                                      (e.g. -gf age,fs_000003)
      -u, --uri TEXT                  A REST API URI query

      -o, --output_file TEXT          Optional output file (CSV) to store
                                      results of query
      -j / -no_j                      Return result of a uri query as JSON
      -bg, --blaze TEXT               Base URL of a Blazegraph SPARQL endpoint
                                      (e.g. http://localhost:9999/blazegraph/sparql)
      -v, --verbosity TEXT            Verbosity level 0-5, 0 is default
      --help                          Show this message and exit.

Details on the REST API URI format and usage can be found below.

queryai — AI-Assisted Natural Language Query
--------------------------------------------
This tool translates natural-language questions about your NIDM data into
SPARQL queries using an LLM (Anthropic Claude or OpenAI GPT).  It uses a
two-phase approach:

1. **Phase 1 — Concept Resolution:** The AI extracts variable concepts
   (e.g. "age", "left hippocampus volume") from your question.  The tool
   then resolves each concept to the exact DataElement URI in your NIDM
   files by matching on ``nidm:isAbout`` (preferred) or
   ``nidm:sourceVariable``.  If multiple DataElements match, you are
   prompted to select the correct one(s).

2. **Phase 2 — SPARQL Generation:** The resolved URIs, together with the
   NIDM graph structure from the bundled ``nidm_schema.json``, are sent to
   the LLM which generates a SPARQL query.  The query is executed locally
   against your NIDM files via rdflib — **no subject data leaves your
   machine**.

.. code:: bash

   Usage: pynidm queryai [OPTIONS]

   Options:
     -nl, --nidm_file_list TEXT  A comma separated list of NIDM files with
                                 full path  [required]
     -q, --question TEXT         Natural-language question to ask about the
                                 NIDM data. If not provided, enters
                                 interactive mode.
     -o, --output_file PATH      Optional output file for results (TSV format)
     -s, --show_query            Show the generated SPARQL query before
                                 executing it
     --help                      Show this message and exit.

**Prerequisites** — an API key for either Anthropic or OpenAI:

.. code:: bash

   export ANTHROPIC_API_KEY=sk-ant-...   # or
   export OPENAI_API_KEY=sk-...

Or create a config file at ``~/.pynidm/config.json``::

   {"provider": "anthropic", "api_key": "sk-ant-..."}

**Example — count subjects:**

.. code:: bash

   pynidm queryai -nl data/nidm.ttl -q "How many subjects are there?" -s

**Example — average age:**

.. code:: bash

   pynidm queryai -nl data/nidm.ttl -q "What is the average age of all subjects?" -s

**Example — interactive mode:**

.. code:: bash

   pynidm queryai -nl data/nidm.ttl

A demo script that downloads sample NIDM data and runs several example
queries is available at
``src/nidm/experiment/tools/examples/queryai_demo.sh``.

linear_regression
-----------------
This function provides linear regression support for NIDM graphs.

.. code:: bash

    Usage: pynidm linear-regression [OPTIONS]

    Options:
      -nl, --nidm_file_list TEXT      A comma-separated list of NIDM files with
                                      full path  [required]
      -model, --ml TEXT               An equation representing the linear
                                      regression. The dependent variable comes
                                      first, followed by "=" or "~", followed by
                                      the independent variables separated by "+"
                                      (Ex: -model "fs_003343 = age*sex + sex +
                                      age + group + age*group + bmi") [required]
      -contrast, --ctr TEXT           Parameter, if set, will return differences
                                      in variable relationships by group. One or
                                      multiple parameters can be used (separate
                                      with commas) (Ex: -contrast group,age)
      -r, --regularization TEXT       If set, applies L1 or L2 regularization
                                      and returns the maximum likelihood weight.
                                      Prevents overfitting. (Ex: -r L1)
      -o, --output_file TEXT          Optional output file (TXT) to store results
      --help                          Show this message and exit.

To use the linear regression algorithm successfully, structure, syntax, and
querying is important. Here is how to maximize the usefulness of the tool:

First, use pynidm query to discover the variables to use. PyNIDM allows for the
use of either data elements (PIQ_tca9ck), specific URLs
(http://uri.interlex.org/ilx_0100400), or source variables (DX_GROUP).

An example of a potential query is::

    pynidm query -nl /simple2_NIDM_examples/datasets.datalad.org/abide/RawDataBIDS/CMU_a/nidm.ttl,/simple2_NIDM_examples/datasets.datalad.org/abide/RawDataBIDS/CMU_b/nidm.ttl -u /projects?fields=fs_000008,DX_GROUP,PIQ_tca9ck,http://uri.interlex.org/ilx_0100400

You can also do::

    pynidm query -nl /simple2_NIDM_examples/datasets.datalad.org/abide/RawDataBIDS/CMU_a/nidm.ttl,/Users/Ashu/Downloads/simple2_NIDM_examples/datasets.datalad.org/abide/RawDataBIDS/CMU_b/nidm.ttl -gf fs_000008,DX_GROUP,PIQ_tca9ck,http://uri.interlex.org/ilx_0100400

The query looks in the two files specified in the -nl parameter for the
variables specified. In this case, we use fs_000008 and DX_GROUP (source
variables), a URL (http://uri.interlex.org/ilx_0100400), and a data element
(PIQ_tca9ck). The output of the file is slightly different depending on whether
you use -gf or -u. With -gf, it will return the variables from both files
separately, while -u combines them.

Now that we have selected the variables, we can perform a linear regression. In
this example, we will look at the effect of DX_GROUP, age at scan, and PIQ on
supratentorial brain volume.

The command to use for this particular data is::

    pynidm linear-regression -nl /simple2_NIDM_examples/datasets.datalad.org/abide/RawDataBIDS/CMU_a/nidm.ttl,/simple2_NIDM_examples/datasets.datalad.org/abide/RawDataBIDS/CMU_b/nidm.ttl -model "fs_000008 = DX_GROUP + PIQ_tca9ck + http://uri.interlex.org/ilx_0100400" -contrast "DX_GROUP" -r L1

-nl specifies the file(s) to pull data from, while -model is the model to
perform a linear regression model on. In this case, the variables are fs_000008
(the dependent variable, supratentorial brain volume), DX_GROUP (diagnostic
group), PIQ_tca9ck (PIQ), and http://uri.interlex.org/ilx_0100400 (age at
scan). The -contrast parameter says to contrast the data using DX_GROUP, and
then do a L1 regularization to prevent overfitting.

Details on the REST API URI format and usage can be found below.

PyNIDM: REST API and Command Line Usage
##########################################

Introduction
============

There are two main ways to interact with NIDM data using the PyNIDM REST API.
First, the pynidm query command line utility will accept queries formatted as
REST API URIs. Second, the rest-server.py script can be used to run a HTTP
server to accept and process requests. This script can either be run directly
or using a docker container defined in the docker directory of the project.

Example usage:

.. code:: bash

   $ pynidm query -nl "cmu_a.ttl,cmu_b.ttl" -u /projects

   dc1bf9be-10a3-11ea-8779-003ee1ce9545
   ebe112da-10a3-11ea-af83-003ee1ce9545

Installation
============

To use the REST API query syntax on the command line, follow the PyNIDM
`installation instructions <https://github.com/incf-nidash/PyNIDM/>`_.

The simplest way to deploy a HTTP REST API server would be with the provided
docker container. You can find instructions for that process in the `README.md
<https://github.com/incf-nidash/PyNIDM/tree/master/docker>`_ file in the docker
directory of the Github repository.


URI formats
===========

You can find details on the REST API at the `SwaggerHub API Documentation
<https://app.swaggerhub.com/apis-docs/albertcrowley/PyNIDM>`_.  The OpenAPI
specification file is part of the Github repository in
'docs/REST_API_definition.openapi.yaml'

.. note::

   The SwaggerHub API documentation may not always reflect the latest REST API.
   The canonical OpenAPI specification is the ``docs/REST_API_definition.openapi.yaml``
   file in this repository.

Here is a list of the current operations. See the SwaggerHub page for more
details and return formats.

::

    - /projects
    - /projects/{project_id}
    - /projects/{project_id}/subjects
    - /projects/{project_id}/subjects?filter=[filter expression]
    - /projects/{project_id}/subjects/{subject_id}
    - /projects/{project_id}/subjects/{subject_id}/instruments/{instrument_id}
    - /projects/{project_id}/subjects/{subject_id}/derivatives/{derivative_id}
    - /statistics/projects/{project_id}

You can append the following query parameters to many of the operations::

    - filter
    - field

Operations
-----------

``/projects``
    Get a list of all project IDs available.

    Supported query parameters: none

``/projects/{project_id}``
    See some details for a project. This will include the list of subject IDs
    and data elements used in the project

    Supported query parameters: filter

``/projects/{project_id}/subjects``
    Get the list of subjects in a project

    Supported query parameters: filter

``/projects/{project_id}/subjects/{subject_id}``
    Get the details for a particular subject. This will include the results of
    any instrumnts or derivatives associated with the subject, as well as a
    list of the related activities.

    Supported query parameters: none

``/projects/{project_id}/subjects/{subject_id}/instruments/{instrument_id}``
    Get the values for a particular instrument

    Supported query parameters: none

``/projects/{project_id}/subjects/{subject_id}/derivatives/{derivative_id}``
    Get the values for a particular derivative

    Supported query parameters: none

``/statistics/projects/{project_id}``
    See project statistics. You can also use this operation to get statsitcs on
    a particular instrument or derivative entry by use a *field* query option.

    Supported query parameters: filter, field

``/statistics/projects/{project_id}/subjects/{subject_id}``
    See some details for a project. This will include the list of subject IDs
    and data elements used in the project

    Supported query parameters: none

Query Parameters
-----------------

``filter``
    The filter query parameter is used when you want to receive data only on
    subjects that match some criteria.  The format for the filter value should
    be of the form::

        identifier op value [ and identifier op value and ... ]

    Identifiers should be formatted as "instrument.ID" or "derivatives.ID"  You
    can use any value for the instrument ID that is shown for an instrument or
    in the data_elements section of the project details. For the derivative ID,
    you can use the last component of a derivative field URI (ex. for the URI
    http://purl.org/nidash/fsl#fsl_000007, the ID would be "fsl_000007") or the
    exact label shown when viewing derivative data (ex. "Left-Caudate (mm^3)").

    The ``op`` can be one of "eq", "gt", "lt".

    Example filters:
        ``?filter=instruments.AGE_AT_SCAN gt 30``
        ``?filter=instrument.AGE_AT_SCAN eq 21 and derivative.fsl_000007 lt 3500``

``fields``
    The fields query parameter is used to specify what fields should be
    detailed in a statistics operation. For each field specified the result
    will show minimum, maximum, average, median, and standard deviation for the
    values of that field across all subjects matching the operation and filter.
    Multiple fields can be specified by separating each field with a comma.

    Fields should be formatted in the same way as identifiers are specified in
    the filter parameter.

    Example field query:
        ``http://localhost:5000/statistics/projects/abc123?field=instruments.AGE_AT_SCAN,derivatives.fsl_000020``


Return Formatting
==================

By default the HTTP REST API server will return JSON formatted objects or
arrays.  When using the pynidm query command line utility the default return
format is text (when possible) or you can use the -j option to have the output
formatted as JSON.

Examples
--------

Get the UUID for all the projects at this location
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: bash

   curl http://localhost:5000/projects

Example response:

.. code:: JSON

   [
       "dc1bf9be-10a3-11ea-8779-003ee1ce9545"
   ]

Get the project summary details
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: bash

   curl http://localhost:5000/projects/dc1bf9be-10a3-11ea-8779-003ee1ce9545

Example response:

.. code:: JSON

   {
    "http://www.w3.org/1999/02/22-rdf-syntax-ns#type": "http://purl.org/nidash/nidm#Project",
    "dctypes:title": "ABIDE CMU_a Site",
    "http://www.w3.org/ns/prov#Location": "/datasets.datalad.org/abide/RawDataBIDS/CMU_a",
    "sio:Identifier": "1.0.1",
    "nidm:NIDM_0000171": 14,
    "age_max": 33.0,
    "age_min": 21.0,
    "ndar:gender": [
        "1",
        "2"
    ],
    "obo:handedness": [
        "R",
        "L",
        "Ambi"
    ]
   }

Get the subjects in a project
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: bash

   pynidm query -nl "cmu_a.nidm.ttl" -u http://localhost:5000/projects/dc1bf9be-10a3-11ea-8779-003ee1ce9545/subjects

Example response::

   deef8eb2-10a3-11ea-8779-003ee1ce9545
   df533e6c-10a3-11ea-8779-003ee1ce9545
   ddbfb454-10a3-11ea-8779-003ee1ce9545
   df21cada-10a3-11ea-8779-003ee1ce9545
   dcfa35b2-10a3-11ea-8779-003ee1ce9545
   de89ce4c-10a3-11ea-8779-003ee1ce9545
   dd2ce75a-10a3-11ea-8779-003ee1ce9545
   ddf21020-10a3-11ea-8779-003ee1ce9545
   debc0f74-10a3-11ea-8779-003ee1ce9545
   de245134-10a3-11ea-8779-003ee1ce9545
   dd5f2f30-10a3-11ea-8779-003ee1ce9545
   dd8d4faa-10a3-11ea-8779-003ee1ce9545
   df87cbaa-10a3-11ea-8779-003ee1ce9545
   de55285e-10a3-11ea-8779-003ee1ce9545


Use the command line to get statistics on a project for the AGE_AT_SCAN and a FSL data element
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: bash

   pynidm query -nl ttl/cmu_a.nidm.ttl -u /statistics/projects/dc1bf9be-10a3-11ea-8779-003ee1ce9545?fields=instruments.AGE_AT_SCAN,derivatives.fsl_000001

Example response::

  -------------------------------------------------  ---------------------------------------------
  "http://www.w3.org/1999/02/22-rdf-syntax-ns#type"  http://www.w3.org/ns/prov#Activity
  "title"                                            ABIDE CMU_a Site
  "Identifier"                                       1.0.1
  "prov:Location"                                    /datasets.datalad.org/abide/RawDataBIDS/CMU_a
  "NIDM_0000171"                                     14
  "age_max"                                          33.0
  "age_min"                                          21.0

    gender
  --------
         1
         2

  handedness
  ------------
  R
  L
  Ambi

  subjects
  ------------------------------------
  de89ce4c-10a3-11ea-8779-003ee1ce9545
  deef8eb2-10a3-11ea-8779-003ee1ce9545
  dd8d4faa-10a3-11ea-8779-003ee1ce9545
  ddbfb454-10a3-11ea-8779-003ee1ce9545
  de245134-10a3-11ea-8779-003ee1ce9545
  debc0f74-10a3-11ea-8779-003ee1ce9545
  dd5f2f30-10a3-11ea-8779-003ee1ce9545
  ddf21020-10a3-11ea-8779-003ee1ce9545
  dcfa35b2-10a3-11ea-8779-003ee1ce9545
  df21cada-10a3-11ea-8779-003ee1ce9545
  df533e6c-10a3-11ea-8779-003ee1ce9545
  de55285e-10a3-11ea-8779-003ee1ce9545
  df87cbaa-10a3-11ea-8779-003ee1ce9545
  dd2ce75a-10a3-11ea-8779-003ee1ce9545

  -----------  ------------------  --------
  AGE_AT_SCAN  max                 33
  AGE_AT_SCAN  min                 21
  AGE_AT_SCAN  median              26
  AGE_AT_SCAN  mean                26.2857
  AGE_AT_SCAN  standard_deviation   4.14778
  -----------  ------------------  --------

  ----------  ------------------  -----------
  fsl_000001  max                 1.14899e+07
  fsl_000001  min                 5.5193e+06
  fsl_000001  median              7.66115e+06
  fsl_000001  mean                8.97177e+06
  fsl_000001  standard_deviation  2.22465e+06
  ----------  ------------------  -----------

Get details on a subject
~~~~~~~~~~~~~~~~~~~~~~~~

Use ``-j`` for a JSON-formatted response

.. code:: bash

   pynidm query -j -nl "cmu_a.nidm.ttl" -u http://localhost:5000/projects/dc1bf9be-10a3-11ea-8779-003ee1ce9545/subjects/df21cada-10a3-11ea-8779-003ee1ce9545

Example response:

.. code:: JSON

   {
  "uuid": "df21cada-10a3-11ea-8779-003ee1ce9545",
  "id": "0050665",
  "activity": [
    "e28dc764-10a3-11ea-a7d3-003ee1ce9545",
    "df28e95a-10a3-11ea-8779-003ee1ce9545",
    "df21c76a-10a3-11ea-8779-003ee1ce9545"
  ],
  "instruments": {
    "e28dd218-10a3-11ea-a7d3-003ee1ce9545": {
      "SRS_VERSION": "nan",
      "ADOS_MODULE": "nan",
      "WISC_IV_VCI": "nan",
      "WISC_IV_PSI": "nan",
      "ADOS_GOTHAM_SOCAFFECT": "nan",
      "VINELAND_PLAY_V_SCALED": "nan",
      "null": "http://www.w3.org/ns/prov#Entity",
      "VINELAND_EXPRESSIVE_V_SCALED": "nan",
      "SCQ_TOTAL": "nan",
      "SRS_MOTIVATION": "nan",
      "PIQ": "104.0",
      "FIQ": "109.0",
      "WISC_IV_PRI": "nan",
      "FILE_ID": "CMU_a_0050665",
      "VIQ": "111.0",
      "WISC_IV_VOCAB_SCALED": "nan",
      "VINELAND_DAILYLVNG_STANDARD": "nan",
      "WISC_IV_SIM_SCALED": "nan",
      "WISC_IV_DIGIT_SPAN_SCALED": "nan",
      "AGE_AT_SCAN": "33.0"
      }
   },
  "derivatives": {
      "b9fe0398-16cc-11ea-8729-003ee1ce9545": {
         "URI": "http://iri.nidash.org/b9fe0398-16cc-11ea-8729-003ee1ce9545",
         "values": {
           "http://purl.org/nidash/fsl#fsl_000005": {
             "datumType": "ilx_0102597",
             "label": "Left-Amygdala (voxels)",
             "value": "1573",
             "units": "voxel"
           },
           "http://purl.org/nidash/fsl#fsl_000004": {
             "datumType": "ilx_0738276",
             "label": "Left-Accumbens-area (mm^3)",
             "value": "466.0",
             "units": "mm^3"
           },
           "http://purl.org/nidash/fsl#fsl_000003": {
             "datumType": "ilx_0102597",
             "label": "Left-Accumbens-area (voxels)",
             "value": "466",
             "units": "voxel"
           }
         },
         "StatCollectionType": "FSLStatsCollection"
      }
   }

version
-------
Print the installed PyNIDM version.

.. code:: bash

   Usage: pynidm version

Additional NIDM-related Tools
=============================

* NIDM-Terms <https://github.com/NIDM-Terms/terms>
* NIDM-Terms Scicrunch Interface <https://scicrunch.org/nidm-terms>
* Freesurfer stats -> NIDM <https://github.com/repronim/segstats_jsonld>
* FSL structural segmentation -> NIDM <https://github.com/ReproNim/fsl_seg_to_nidm>
* ANTS structural segmentation -> NIDM <https://github.com/ReproNim/ants_seg_to_nidm>
