Skip to content

ragraph.io

Graph import/export

Supports multiple formats via its submodules.

archimate

XML format support using The Open Group ArchiMate® Model Exchange File Format.

Reference

from_archimate 

from_archimate(*args, **kwargs)

Archimate XML import is not implemented.

Source code in src/ragraph/io/archimate/__init__.py 
352
353
354
def from_archimate(*args, **kwargs):
    """Archimate XML import is not implemented."""
    raise NotImplementedError("Archimate XML import is not implemented.")

to_archimate 

to_archimate(
    graph: Graph,
    path: Optional[Union[str, Path]] = None,
    elem: Optional[Element] = None,
    tostring_args: Optional[Dict[str, Any]] = None,
    bundle_schemas: bool = False,
) -> str

Encode Graph to an Archimate model XML element.

Parameters:

Name Type Description Default
graph Graph

Graph to convert to XML.

 required
path Optional[Union[str, Path]]

Optional file path to write XML to.

 None
elem Optional[Element]

Optional object to append the Graph to.

 None
tostring_args Optional[Dict[str, Any]]

Optional argument overrides to lxml.etree.tostring.

 None
bundle_schemas bool

When exporting to a file, bundle the .xsd schemas.

 False

Returns:

Type Description
str

XML element.
Note

For both nodes and edges we use the following: The annotations.archimate["type"] determines the type (and therefore layer). The annotations.archimate["documentation"] populates the documentation field. Refer to https://www.opengroup.org/xsd/archimate/ and the XSD scheme for all possible XML element types.

Source code in src/ragraph/io/archimate/__init__.py 
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
def to_archimate(
    graph: Graph,
    path: Optional[Union[str, Path]] = None,
    elem: Optional[etree.Element] = None,
    tostring_args: Optional[Dict[str, Any]] = None,
    bundle_schemas: bool = False,
) -> str:
    """Encode Graph to an Archimate model XML element.

    Arguments:
        graph: Graph to convert to XML.
        path: Optional file path to write XML to.
        elem: Optional object to append the Graph to.
        tostring_args: Optional argument overrides to
            [`lxml.etree.tostring`][lxml.etree.tostring].
        bundle_schemas: When exporting to a file, bundle the .xsd schemas.

    Returns:
        XML element.

    Note:
        For both nodes and edges we use the following:
        The `annotations.archimate["type"]` determines the type (and therefore layer).
        The `annotations.archimate["documentation"]` populates the documentation field.
        Refer to https://www.opengroup.org/xsd/archimate/ and the XSD scheme for all
        possible XML element types.
    """
    if elem is None:
        parser = etree.XMLParser(remove_blank_text=True)
        doc = etree.parse(str(here / "bare.xml"), parser)
        root = doc.getroot()
    else:
        root = elem

    elements = maker.elements()
    elements.extend(_node_to_element(n) for n in graph.nodes)
    if len(elements):
        root.append(elements)

    relationships = maker.relationships()
    relationships.extend(_hierarchy_to_relationships(graph))
    relationships.extend(_edge_to_relationship(e) for e in graph.edges)
    if len(relationships):
        root.append(relationships)

    propdefs = _make_property_definitions(graph)
    if len(propdefs):
        root.append(propdefs)

    for n in graph.nodes:
        _expand_requirements_constraints(n, elements, relationships)

    if path is not None:
        p = Path(path)

        args = dict(encoding="UTF-8", xml_declaration=True, pretty_print=True)
        if tostring_args is not None:
            args.update(tostring_args)

        string = etree.tostring(root, **args)
        p.write_bytes(string)

        if bundle_schemas:
            shutil.copy2(here / "archimate3_Model.xsd", p.parent)

    return root

canopy

Canopy by Ratio CASE format support

from_canopy 

from_canopy(path: Union[str, Path]) -> List[Graph]

Get the graph(s) from a Canopy data file.

Parameters:

Name Type Description Default
path Union[str, Path]

Path of the file to load.

 required

Returns:

Type Description
List[Graph]

Graph objects contained in Canopy data formats being either a graph, tab,
List[Graph]

session, or workspace export of Canopy.

Raises:

Type Description
InconsistencyError

if graph is inconsistent.
Source code in src/ragraph/io/canopy.py 
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
def from_canopy(
    path: Union[str, Path],
) -> List[Graph]:
    """Get the graph(s) from a Canopy data file.

    Arguments:
        path: Path of the file to load.

    Returns:
        Graph objects contained in Canopy data formats being either a graph, tab,
        session, or workspace export of Canopy.

    Raises:
        InconsistencyError: if graph is inconsistent.
    """
    data = json.loads(Path(path).read_text())
    schema = _match_schema(data.get("$schema", ""))
    if schema == "workspace":
        graphs = list(_decode_workspace(data))
    elif schema == "session":
        graphs = list(_decode_session(data))
    elif schema == "tab":
        graphs = list(_decode_tab(data))
    else:
        graphs = [_decode_graph(data)]

    for graph in graphs:
        graph.check_consistency(raise_error=True)

    return graphs

to_canopy 

to_canopy(
    graph: Graph,
    path: Optional[Union[Path, str]] = None,
    fmt: str = "graph",
) -> Optional[str]

Save graph as a Canopy dataset.

Parameters:

Name Type Description Default
graph Graph

Graph to save.

 required
path Optional[Union[Path, str]]

Path to write to.

 None
fmt str

One of 'session' or 'graph'.

 'graph'

Returns:

Type Description
Optional[str]

JSON encoded string if no path was provided to write to.
Source code in src/ragraph/io/canopy.py 
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
def to_canopy(
    graph: Graph,
    path: Optional[Union[Path, str]] = None,
    fmt: str = "graph",
) -> Optional[str]:
    """Save graph as a Canopy dataset.

    Arguments:
        graph: Graph to save.
        path: Path to write to.
        fmt: One of 'session' or 'graph'.

    Returns:
        JSON encoded string if no path was provided to write to.
    """
    if fmt == "session":
        data = _encode_session(graph, schema=True)
    else:
        data = _encode_graph(graph, schema=True)
    if path is not None:
        enc = json.dumps(data)
        Path(path).write_text(enc, encoding="utf-8")
        return None
    else:
        enc = json.dumps(data, indent=2)
        return enc

csv

CSV format support

from_csv 

from_csv(
    nodes_path: Optional[Union[str, Path]] = None,
    edges_path: Optional[Union[str, Path]] = None,
    csv_delimiter: str = ";",
    iter_delimiter: str = ";",
    node_weights: Optional[List[str]] = None,
    edge_weights: Optional[List[str]] = None,
    **graph_kwargs: Any
) -> Graph

Convert CSV files to a graph.

Nodes file (optional) requires at least a name column. Optional special property columns are kind, labels, parent, children and is_bus.

Edges file requires at least a source and target column. Optional special property columns are kind and labels.

Automatically completes one sided parent-child relationships.

Parameters:

Name Type Description Default
nodes_path Optional[Union[str, Path]]

Path of optional nodes CSV file.

 None
edges_path Optional[Union[str, Path]]

Path of edges CSV file.

 None
csv_delimiter str

Delimiter of CSV file.

 ';'
iter_delimiter str

Iterable delimiter (i.e. for children names list).

 ';'
node_weights Optional[List[str]]

Columns to interpret as node weights.

 None
edge_weights Optional[List[str]]

Columns to interpret as edge weights.

 None
**graph_kwargs Any

Optional Graph arguments when instantiating.

 {}

Returns:

Type Description
Graph

Graph object.

Raises:

Type Description
InconsistencyError

if graph is inconsistent.
Source code in src/ragraph/io/csv.py 
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
def from_csv(
    nodes_path: Optional[Union[str, Path]] = None,
    edges_path: Optional[Union[str, Path]] = None,
    csv_delimiter: str = ";",
    iter_delimiter: str = ";",
    node_weights: Optional[List[str]] = None,
    edge_weights: Optional[List[str]] = None,
    **graph_kwargs: Any,
) -> Graph:
    """Convert CSV files to a graph.

    Nodes file (optional) requires at least a `name` column. Optional special
    property columns are `kind`, `labels`, `parent`, `children` and `is_bus`.

    Edges file requires at least a `source` and `target` column. Optional special
    property columns are `kind` and `labels`.

    Automatically completes one sided parent-child relationships.

    Arguments:
        nodes_path: Path of optional nodes CSV file.
        edges_path: Path of edges CSV file.
        csv_delimiter: Delimiter of CSV file.
        iter_delimiter: Iterable delimiter (i.e. for children names list).
        node_weights: Columns to interpret as node weights.
        edge_weights: Columns to interpret as edge weights.
        **graph_kwargs: Optional [`Graph`][ragraph.graph.Graph] arguments when instantiating.

    Returns:
        Graph object.

    Raises:
        InconsistencyError: if graph is inconsistent.
    """
    graph = Graph(**graph_kwargs)

    if not nodes_path and not edges_path:
        return graph

    if not node_weights:
        node_weights = []

    if not edge_weights:
        edge_weights = []

    if nodes_path:
        node_dict = _load_nodes(nodes_path, csv_delimiter, iter_delimiter, node_weights)
    else:
        node_dict = _derive_nodes(edges_path, csv_delimiter)

    if edges_path:
        edges = _load_edges(edges_path, csv_delimiter, iter_delimiter, node_dict, edge_weights)
    else:
        edges = []

    graph.add_parents = True
    graph.add_children = True
    graph.nodes = node_dict
    graph.edges = edges
    graph.check_consistency(raise_error=True)
    return graph

to_csv 

to_csv(
    graph: Graph,
    stem_path: Union[str, Path],
    csv_delimiter: str = ";",
    iter_delimiter: str = ";",
    use_uuid: bool = False,
)

Save graph to nodes and edges CSV files.

Parameters:

Name Type Description Default
graph Graph

Graph to save.

 required
stem_path Union[str, Path]

Stem path for output CSV's. Appended with _nodes.csv and _edges.csv.

 required
csv_delimiter str

CSV delimiter.

 ';'
iter_delimiter str

Iterable delimiter (i.e. for children names list).

 ';'
use_uuid bool

Whether to export UUIDs, too.

 False
Source code in src/ragraph/io/csv.py 
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
def to_csv(
    graph: Graph,
    stem_path: Union[str, Path],
    csv_delimiter: str = ";",
    iter_delimiter: str = ";",
    use_uuid: bool = False,
):
    """Save graph to nodes and edges CSV files.

    Arguments:
        graph: Graph to save.
        stem_path: Stem path for output CSV's. Appended with _nodes.csv and _edges.csv.
        csv_delimiter: CSV delimiter.
        iter_delimiter: Iterable delimiter (i.e. for children names list).
        use_uuid: Whether to export UUIDs, too.
    """
    stem_path = Path(stem_path)

    nodes_fname = stem_path.name + "_nodes.csv"
    nodes_path = stem_path.with_name(nodes_fname)
    _save_nodes(graph, nodes_path, csv_delimiter, iter_delimiter, use_uuid=use_uuid)

    edges_fname = stem_path.name + "_edges.csv"
    edges_path = stem_path.with_name(edges_fname)
    _save_edges(graph, edges_path, csv_delimiter, iter_delimiter, use_uuid=use_uuid)

esl

Elephant Specification Language format support

from_esl 

from_esl(*paths: Union[str, Path]) -> Graph

Convert ESL file(s) into a :obj:ragraph.graph.Graph.

Parameters:

Name Type Description Default
paths Union[str, Path]

Paths to resolve into ESL files. May be any number of files and directories to scan.

 ()

Returns:

Type Description
Graph

Instantiated graph.
Source code in src/ragraph/io/esl.py 
14
15
16
17
18
19
20
21
22
23
24
25
26
def from_esl(
    *paths: Union[str, Path],
) -> Graph:
    """Convert ESL file(s) into a :obj:`ragraph.graph.Graph`.

    Arguments:
        paths: Paths to resolve into ESL files. May be any number of files and
            directories to scan.

    Returns:
        Instantiated graph.
    """
    return to_graph(*paths, output=None, force=False)

grip

GRIP format support

add_SI_Functie 

add_SI_Functie(
    sub: Element,
    func: Dict[str, Any],
    fcount: int,
    node: Node,
)

Add function reference to super element.

Note: This is a bit of a weird quirk of the GRIP data structure.

Parameters:

Name Type Description Default
sub Element

super element to add function element to

 required
func Dict[str, Any]

function reference.

 required
fcount int

Number of referenced function.

 required
node Node

Node to which the reference is added.

 required
Source code in src/ragraph/io/grip.py 
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
def add_SI_Functie(sub: etree.Element, func: Dict[str, Any], fcount: int, node: Node):
    """Add function reference to super element.

    Note: This is a bit of a weird quirk of the GRIP data structure.

    Arguments:
        sub: super element to add function element to
        func: function reference.
        fcount: Number of referenced function.
        node: Node to which the reference is added.
    """
    subsub = etree.SubElement(
        sub,
        "SI_Functie",
        attrib=dict(
            R1Sequence="1",
            R2Sequence=str(fcount),
            Type="RELATION_ELEMENT",
            RootRef=node.annotations["RootRefFunctie"],
        ),
    )

    etree.SubElement(
        subsub,
        func.kind.capitalize(),
        attrib=dict(
            ConfigurationOfRef=func.annotations["ConfigurationOfRef"],
            GUID=func.annotations["GUID"],
        ),
    )

add_labels 

add_labels(g: Graph)

Add labels to edges based on the description of Raakvlakken.

Source code in src/ragraph/io/grip.py 
1723
1724
1725
1726
1727
1728
1729
1730
1731
1732
1733
1734
1735
def add_labels(g: Graph):
    """Add labels to edges based on the description of Raakvlakken."""
    for n in [node for node in g.nodes if node.kind == "raakvlak"]:
        if not n.annotations.get("Description", None):
            # No labels to derive.
            continue
        labels = [label.strip() for label in n.annotations.Description.split(",")]
        variants = [s for s in g.sources_of(n)] + [t for t in g.targets_of(n)]
        for e in g.edges_between_all(variants, variants):
            e.labels = list(set(e.labels + labels))

            if len(e.labels) >= 1 and "default" in e.labels:
                e.labels.remove("default")

add_raakvlak_annotations 

add_raakvlak_annotations(g: Graph)

Adding Raakvlak ID's as a string to edges annotations.

Source code in src/ragraph/io/grip.py 
1705
1706
1707
1708
1709
1710
1711
1712
1713
1714
1715
1716
1717
1718
1719
1720
def add_raakvlak_annotations(g: Graph):
    """Adding Raakvlak ID's as a string to edges annotations."""
    for e in g.edges:
        if e.source.kind != "object" or e.target.kind != "object":
            continue

        sr = set([t for t in g.targets_of(e.source) if t.kind == "raakvlak"])
        tr = set([t for t in g.targets_of(e.target) if t.kind == "raakvlak"])

        if not sr.intersection(tr):
            e.annotations.raakvlakken = ""
            continue

        raakvlakken = ",".join([r.name.split(" | ")[-1] for r in sr.intersection(tr)])

        e.annotations.raakvlakken = raakvlakken

from_grip 

from_grip(
    path: Union[str, Path], hierarchy_mode: str = "top-down"
) -> Graph

Decode GRIP XML file, string, or element into a Graph.

Parameters:

Name Type Description Default
path Union[str, Path]

GRIP XML file path.

 required
hierarchy_mode str

One of "bottom-up" or "top-down". Defines how the hierarchy relations are stored.

 'top-down'

Returns:

Type Description
Graph

Graph object.
Source code in src/ragraph/io/grip.py 
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
def from_grip(path: Union[str, Path], hierarchy_mode: str = "top-down") -> Graph:
    """Decode GRIP XML file, string, or element into a Graph.

    Arguments:
        path: GRIP XML file path.
        hierarchy_mode: One of "bottom-up" or "top-down".
            Defines how the hierarchy relations are stored.

    Returns:
        Graph object.
    """

    tree = etree.parse(str(path))
    root = tree.getroot()

    graph = Graph(
        uuid=root.attrib.get("WorkspaceID"),
        name=root.attrib.get("WorkspaceName"),
        annotations=dict(root.attrib),
    )
    parse_params(graph, root)

    parse_collection(graph, root, "Objecten", "Object", OBJECT_KIND)
    parse_objectenboom(graph, root, hierarchy_mode)

    parse_collection(graph, root, "Objecttypen", "Objecttype", OBJECTTYPE_KIND)
    parse_objecttypenboom(graph, root)

    parse_collection(graph, root, "Functies", "Functie", FUNCTIE_KIND)
    parse_collection(graph, root, "Systeemeisen", "Systeemeis", SYSTEEMEIS_KIND)
    parse_collection(graph, root, "Onderhoudsactiviteiten", "Onderhoudsactiviteit", ACTIVITY_KIND)
    parse_collection(graph, root, "Scope", "Scope", SCOPE_KIND)
    parse_collection(graph, root, "Raakvlakken", "Raakvlak", RAAKVLAK_KIND)

    parse_systeemeis_edges(graph, root)
    parse_object_edges(graph, root)
    parse_scope_edges(graph, root)
    parse_raakvlak_edges(graph, root)
    parse_activity_edges(graph, root)

    # Enrich graph.
    add_raakvlak_annotations(graph)
    add_labels(graph)

    return graph

parse_CI_MEEisObjects 

parse_CI_MEEisObjects(el: Element, annotations: Dict)

Parse CI_MEEisObjects and store within annotations.

Parameters:

Name Type Description Default
el Element

Systeemeis to be parsed

 required
annotations Dict

Dictionary in which information must be stored

 required
Source code in src/ragraph/io/grip.py 
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
def parse_CI_MEEisObjects(el: etree.Element, annotations: Dict):
    """Parse CI_MEEisObjects and store within annotations.

    Arguments:
       el: Systeemeis to be parsed
       annotations: Dictionary in which information must be stored
    """
    annotations["CI_MEEisObjects"] = []

    for MObj in el.iterfind("CI_MEEisObject"):
        annotations["CI_MEEisObjects"].append(
            {
                "CI_MEEisObject": {
                    "R1Sequence": MObj.attrib["R1Sequence"],
                    "R2Sequence": MObj.attrib["R2Sequence"],
                    "RootRef": MObj.attrib["RootRef"],
                    "Type": MObj.attrib["Type"],
                    "EisObject": {
                        "Name": MObj.find("EisObject").attrib["Name"],
                        "ConfigurationOfRef": MObj.find("EisObject").attrib["ConfigurationOfRef"],
                        "Type": MObj.find("EisObject").attrib["Type"],
                        "GUID": MObj.find("EisObject").attrib["GUID"],
                        "SI_Object": {
                            "R1Sequence": MObj.find("EisObject")
                            .find("SI_Object")
                            .attrib["R1Sequence"],
                            "R2Sequence": MObj.find("EisObject")
                            .find("SI_Object")
                            .attrib["R2Sequence"],
                            "RootRef": MObj.find("EisObject").find("SI_Object").attrib["RootRef"],
                            "Type": MObj.find("EisObject").find("SI_Object").attrib["Type"],
                            "Object": MObj.find("EisObject")
                            .find("SI_Object")
                            .find("Object")
                            .attrib,
                        },
                    },
                }
            }
        )

parse_CI_MEEisObjecttypen 

parse_CI_MEEisObjecttypen(el: Element, annotations: Dict)

Parse CI_MEEisObjectypen and store within annotations.

Parameters:

Name Type Description Default
el Element

Systeemeis to be parsed

 required
annotations Dict

Dictionary in which information must be stored

 required
Source code in src/ragraph/io/grip.py 
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
def parse_CI_MEEisObjecttypen(el: etree.Element, annotations: Dict):
    """Parse CI_MEEisObjectypen and store within annotations.

    Arguments:
       el: Systeemeis to be parsed
       annotations: Dictionary in which information must be stored
    """
    annotations["CI_MEEisObjecttypen"] = []

    for MObjtype in el.iterfind("CI_MEEisObjecttype"):
        annotations["CI_MEEisObjecttypen"].append(
            {
                "CI_MEEisObjecttype": {
                    "R1Sequence": MObjtype.attrib["R1Sequence"],
                    "R2Sequence": MObjtype.attrib["R2Sequence"],
                    "RootRef": MObjtype.attrib["RootRef"],
                    "Type": MObjtype.attrib["Type"],
                    "EisObjecttype": {
                        "Name": MObjtype.find("EisObjecttype").attrib["Name"],
                        "ConfigurationOfRef": MObjtype.find("EisObjecttype").attrib[
                            "ConfigurationOfRef"
                        ],
                        "Type": MObjtype.find("EisObjecttype").attrib["Type"],
                        "GUID": MObjtype.find("EisObjecttype").attrib["GUID"],
                        "SI_Objecttype": {
                            "R1Sequence": MObjtype.find("EisObjecttype")
                            .find("SI_Objecttype")
                            .attrib["R1Sequence"],
                            "R2Sequence": MObjtype.find("EisObjecttype")
                            .find("SI_Objecttype")
                            .attrib["R2Sequence"],
                            "RootRef": MObjtype.find("EisObjecttype")
                            .find("SI_Objecttype")
                            .attrib["RootRef"],
                            "Type": MObjtype.find("EisObjecttype")
                            .find("SI_Objecttype")
                            .attrib["Type"],
                            "Objecttype": MObjtype.find("EisObjecttype")
                            .find("SI_Objecttype")
                            .find("Objecttype")
                            .attrib,
                        },
                    },
                }
            }
        )

parse_CI_MEOnderhoudsactiviteitObject 

parse_CI_MEOnderhoudsactiviteitObject(
    el: Element, annotations: Dict
)

Parse information for Activity object

Source code in src/ragraph/io/grip.py 
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
def parse_CI_MEOnderhoudsactiviteitObject(el: etree.Element, annotations: Dict):
    """Parse information for Activity object"""
    annotations["CI_MEOnderhoudsactiviteitObjecten"] = []

    for MEOa in el.iterfind("CI_MEOnderhoudsactiviteitObject"):
        annotations["CI_MEOnderhoudsactiviteitObjecten"].append(
            {
                "CI_MEOnderhoudsactiviteitObject": {
                    "R1Sequence": MEOa.attrib["R1Sequence"],
                    "R2Sequence": MEOa.attrib["R2Sequence"],
                    "RootRef": MEOa.attrib["RootRef"],
                    "Type": MEOa.attrib["Type"],
                    "MEOnderhoudsactiviteitObject": {
                        "Name": MEOa.find("MEOnderhoudsactiviteitObject").attrib["Name"],
                        "ConfigurationOfRef": MEOa.find("MEOnderhoudsactiviteitObject").attrib[
                            "ConfigurationOfRef"
                        ],
                        "Type": MEOa.find("MEOnderhoudsactiviteitObject").attrib["Type"],
                        "GUID": MEOa.find("MEOnderhoudsactiviteitObject").attrib["GUID"],
                        "SI_Object": {
                            "R1Sequence": MEOa.find("MEOnderhoudsactiviteitObject")
                            .find("SI_Object")
                            .attrib["R1Sequence"],
                            "R2Sequence": MEOa.find("MEOnderhoudsactiviteitObject")
                            .find("SI_Object")
                            .attrib["R2Sequence"],
                            "RootRef": MEOa.find("MEOnderhoudsactiviteitObject")
                            .find("SI_Object")
                            .attrib["RootRef"],
                            "Type": MEOa.find("MEOnderhoudsactiviteitObject")
                            .find("SI_Object")
                            .attrib["Type"],
                            "Object": MEOa.find("MEOnderhoudsactiviteitObject")
                            .find("SI_Object")
                            .find("Object")
                            .attrib,
                        },
                    },
                }
            }
        )

parse_CI_Toelichting 

parse_CI_Toelichting(el: Element, annotations: Dict)

Parse information attached to an CI_Toelichting.

Source code in src/ragraph/io/grip.py 
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
def parse_CI_Toelichting(el: etree.Element, annotations: Dict):
    """Parse information attached to an CI_Toelichting."""
    st = el.find("CI_Toelichting")

    annotations["CI_Toelichting"] = {
        "R1Sequence": st.attrib["R1Sequence"],
        "R2Sequence": st.attrib["R2Sequence"],
        "RootRef": st.attrib["RootRef"],
        "Type": st.attrib["Type"],
        "Toelichting": {
            "Name": st.find("Toelichting").attrib["Name"],
            "Description": st.find("Toelichting").attrib.get("Description", ""),
            "ConfigurationOfRef": st.find("Toelichting").attrib["ConfigurationOfRef"],
            "GUID": st.find("Toelichting").attrib["GUID"]
        }
    }

parse_CI_Verificatievoorschrift 

parse_CI_Verificatievoorschrift(
    el: Element, annotations: Dict
)

Parse information attached to an CI verificationvoorschrift

Source code in src/ragraph/io/grip.py 
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
def parse_CI_Verificatievoorschrift(el: etree.Element, annotations: Dict):
    """Parse information attached to an CI verificationvoorschrift"""

    annotations["CI_Verificatievoorschrift"] = []

    for cvv in el.iterfind("CI_Verificatievoorschrift"):
        info = {
            "R1Sequence": cvv.attrib["R1Sequence"],
            "R2Sequence": cvv.attrib["R2Sequence"],
            "RootRef": cvv.attrib["RootRef"],
            "Type": cvv.attrib["Type"],
        }

        parse_verificatie(cvv, info)

        annotations["CI_Verificatievoorschrift"].append(info)

parse_SI_Eistype 

parse_SI_Eistype(el: Element, annotations: Dict)

Parse information attached to an SI_Eistype.

Source code in src/ragraph/io/grip.py 
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
def parse_SI_Eistype(el: etree.Element, annotations: Dict):
    """Parse information attached to an SI_Eistype."""
    st = el.find("SI_Eistype")

    annotations["SI_Eistype"] = {
        "R1Sequence": st.attrib["R1Sequence"],
        "R2Sequence": st.attrib["R2Sequence"],
        "RootRef": st.attrib["RootRef"],
        "Type": st.attrib["Type"],
        "Eistype": {
            "Name": st.find("Eistype").attrib["Name"],
            "ConfigurationOfRef": st.find("Eistype").attrib["ConfigurationOfRef"],
            "GUID": st.find("Eistype").attrib["GUID"]
        }
    }

parse_SI_Fase 

parse_SI_Fase(el: Element, annotations: Dict)

Parse information attached to an SI_Fase.

Source code in src/ragraph/io/grip.py 
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
def parse_SI_Fase(el: etree.Element, annotations: Dict):
    """Parse information attached to an SI_Fase."""
    st = el.find("SI_Fase")

    annotations["SI_Fase"] = {
        "R1Sequence": st.attrib["R1Sequence"],
        "R2Sequence": st.attrib["R2Sequence"],
        "RootRef": st.attrib["RootRef"],
        "Type": st.attrib["Type"],
        "Fase": {
            "Name": st.find("Fase").attrib["Name"],
            "ConfigurationOfRef": st.find("Fase").attrib["ConfigurationOfRef"],
            "GUID": st.find("Fase").attrib["GUID"]
        }
    }

parse_SI_Methode 

parse_SI_Methode(el: Element, annotations: Dict)

Parse information attached to an SI_Methode.

Source code in src/ragraph/io/grip.py 
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
def parse_SI_Methode(el: etree.Element, annotations: Dict):
    """Parse information attached to an SI_Methode."""
    st = el.find("SI_Methode")

    annotations["SI_Methode"] = {
        "R1Sequence": st.attrib["R1Sequence"],
        "R2Sequence": st.attrib["R2Sequence"],
        "RootRef": st.attrib["RootRef"],
        "Type": st.attrib["Type"],
        "Methode": {
            "Name": st.find("Methode").attrib["Name"],
            "ConfigurationOfRef": st.find("Methode").attrib["ConfigurationOfRef"],
            "GUID": st.find("Methode").attrib["GUID"]
        }
    }

parse_SI_Periode 

parse_SI_Periode(el: Element, annotations: Dict)

Parse information attached to an SI_Periode.

Source code in src/ragraph/io/grip.py 
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
def parse_SI_Periode(el: etree.Element, annotations: Dict):
    """Parse information attached to an SI_Periode."""
    st = el.find("SI_Periode")

    annotations["SI_Periode"] = {
        "R1Sequence": st.attrib["R1Sequence"],
        "R2Sequence": st.attrib["R2Sequence"],
        "RootRef": st.attrib["RootRef"],
        "Type": st.attrib["Type"],
        "Periode": {
            "Name": st.find("Periode").attrib["Name"],
            "ConfigurationOfRef": st.find("Periode").attrib["ConfigurationOfRef"],
            "GUID": st.find("Periode").attrib["GUID"]
        }
    }

parse_SI_Systeemeisgroepering 

parse_SI_Systeemeisgroepering(
    el: Element, annotations: Dict
)

Parse information attached to an SI_Systeemeisgroepering.

Source code in src/ragraph/io/grip.py 
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
def parse_SI_Systeemeisgroepering(el: etree.Element, annotations: Dict):
    """Parse information attached to an SI_Systeemeisgroepering."""
    annotations["SI_Systeemeisgroepering"] = []

    for st in el.iterfind("SI_Systeemeisgroepering"):

        annotations["SI_Systeemeisgroepering"].append({
            "R1Sequence": st.attrib["R1Sequence"],
            "R2Sequence": st.attrib["R2Sequence"],
            "RootRef": st.attrib["RootRef"],
            "Type": st.attrib["Type"],
            "Systeemeisgroepering": {
                "Name": st.find("Systeemeisgroepering").attrib["Name"],
                "ConfigurationOfRef": st.find("Systeemeisgroepering").attrib["ConfigurationOfRef"],
                "GUID": st.find("Systeemeisgroepering").attrib["GUID"]
            }
        })

parse_collection 

parse_collection(
    graph: Graph,
    root: Element,
    collection: str,
    item: str,
    kind: str,
)

Decode contents of XML file.

Parameters:

Name Type Description Default
graph Graph

Graph object to add nodes to

 required
root Element

Root of XML file

 required
collection str

Sub-collection to parse (e.g. objecten or Objecttypen)

 required
item str

item kind to parse.

 required
kind str

kind to assign to created nodes.

 required
Source code in src/ragraph/io/grip.py 
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
def parse_collection(graph: Graph, root: etree.Element, collection: str, item: str, kind: str):
    """Decode contents of XML file.

    Arguments:
       graph: Graph object to add nodes to
       root: Root of XML file
       collection: Sub-collection to parse (e.g. objecten or Objecttypen)
       item: item kind to parse.
       kind: kind to assign to created nodes.
    """
    coll = root.find(collection)

    if coll is None:
        "No collection found, return."
        return 

    for el in coll.iterfind(item):
        name, annotations = parse_element(el=el, item=item)
        graph.add_node(
            Node(
                uuid=el.attrib.get("GUID"),
                name=name,
                kind=kind,
                annotations=annotations,
            )
        )

parse_eisteksten 

parse_eisteksten(el: Element, annotations: Dict)

Parse eisteksten and store within annotations.

Parameters:

Name Type Description Default
el Element

Systeemeis to be parsed

 required
annotations Dict

Dictionary in which information must be stored

 required
Source code in src/ragraph/io/grip.py 
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
def parse_eisteksten(el: etree.Element, annotations: Dict):
    """Parse eisteksten and store within annotations.

    Arguments:
       el: Systeemeis to be parsed
       annotations: Dictionary in which information must be stored
    """
    if el.find("CI_EistekstDefinitief") is not None:
        annotations.update(
            {
                "CI_EistekstDefinitief": {
                    "R1Sequence": el.find("CI_EistekstDefinitief").attrib["R1Sequence"],
                    "R2Sequence": el.find("CI_EistekstDefinitief").attrib["R2Sequence"],
                    "RootRef": el.find("CI_EistekstDefinitief").attrib["RootRef"],
                    "Type": el.find("CI_EistekstDefinitief").attrib["Type"],
                    "Eistekst": el.find("CI_EistekstDefinitief").find("Eistekst").attrib,
                }
            }
        )

    if el.find("CI_EistekstOrigineel") is not None:
        annotations.update(
            {
                "CI_EistekstOrigineel": {
                    "R1Sequence": el.find("CI_EistekstOrigineel").attrib["R1Sequence"],
                    "R2Sequence": el.find("CI_EistekstOrigineel").attrib["R2Sequence"],
                    "RootRef": el.find("CI_EistekstOrigineel").attrib["RootRef"],
                    "Type": el.find("CI_EistekstOrigineel").attrib["Type"],
                    "EistekstOrigineel": el.find("CI_EistekstOrigineel")
                    .find("EistekstOrigineel")
                    .attrib,
                }
            }
        )

parse_element 

parse_element(el: Element, item: str) -> Dict

Parsing element and store relevant information within Node annotations

Parameters:

Name Type Description Default
el Element

Element to parse.

 required
item str

item kind being parsed.

 required

Returns:

Type Description
Dict

Name string and Annotations dictionary.
Source code in src/ragraph/io/grip.py 
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
def parse_element(el: etree.Element, item: str) -> Dict:
    """Parsing element and store relevant information within Node annotations

    Arguments:
      el: Element to parse.
      item: item kind being parsed.

    Returns:
      Name string and Annotations dictionary.
    """
    annotations = dict(el.attrib)

    if el.find("ID") is not None:
        annotations.update(dict(ID=el.find("ID").attrib))
        if item == "Onderhoudsactiviteit":
            id1 = el.find("ID").attrib.get("IDOA")
        else:
            id1 = el.find("ID").attrib.get("ID1")
        name = el.attrib.get("Name")
        if name and id1 not in name:
            name = f"{name} | {id1}"
        elif not name:
            name = id1
    else:
        name = el.attrib.get("Name")

    for key in ["Code", "BronID", "Eiscodering", "ExterneCode"]:
        if el.find(key) is None:
            continue
        annotations.update({key: el.find(key).attrib})

    if item == "Systeemeis":
        parse_eisteksten(el, annotations)

        if el.find("CI_MEEisObject") is not None:
            parse_CI_MEEisObjects(el=el, annotations=annotations)

        if el.find("CI_MEEisObjecttype") is not None:
            parse_CI_MEEisObjecttypen(el=el, annotations=annotations)

        if el.find("SI_Eistype") is not None:
            parse_SI_Eistype(el=el, annotations=annotations)

        if el.find("SI_Periode") is not None:
            parse_SI_Periode(el=el, annotations=annotations)

        if el.find("SI_Systeemeisgroepering") is not None:
            parse_SI_Systeemeisgroepering(el=el, annotations=annotations)

        if el.find("CI_Verificatievoorschrift") is not None:
            parse_CI_Verificatievoorschrift(el=el, annotations=annotations)

        if el.find("CI_Toelichting") is not None:
            parse_CI_Toelichting(el=el, annotations=annotations)


    # Store information for activities
    if item == "Onderhoudsactiviteit":
        if el.find("CI_MEOnderhoudsactiviteitObject") is not None:
            parse_CI_MEOnderhoudsactiviteitObject(el=el, annotations=annotations)
        if el.find("Aard") is not None:
            annotations["Aard"] = el.find("Aard").attrib
        if el.find("Onderhoudsactiviteittype") is not None:
            annotations["Onderhoudsactiviteittype"] = el.find("Onderhoudsactiviteittype").attrib

    # Parse hierarchy relations for objects
    if el.find("SI_Onderliggend") is not None:
        annotations.update({"RootRefOnderliggend": el.find("SI_Onderliggend").attrib["RootRef"]})

    if el.find("SI_Bovenliggend") is not None:
        annotations.update({"RootRefBovenliggend": el.find("SI_Bovenliggend").attrib["RootRef"]})

    # Parse hiearchy relations for objecttypes.
    if el.find("SI_Onderliggende") is not None:
        annotations.update({"RootRefOnderliggende": el.find("SI_Onderliggende").attrib["RootRef"]})

    # Parse relations to functions.
    if el.find("SI_Functie") is not None:
        annotations.update({"RootRefFunctie": el.find("SI_Functie").attrib["RootRef"]})

    # Parse assignment relations to objectttpes.
    if el.find("SI_Objecttype") is not None:
        annotations.update({"RootRefObjecttype": el.find("SI_Objecttype").attrib["RootRef"]})

    return name, annotations

parse_params 

parse_params(graph: Graph, root: Element)

Decode parameter section of GRIP XML file.

Parameters:

Name Type Description Default
graph Graph

Graph object to add nodes to.

 required
root Element

Root of XML file.

 required
Source code in src/ragraph/io/grip.py 
133
134
135
136
137
138
139
140
141
142
def parse_params(graph: Graph, root: etree.Element):
    """Decode parameter section of GRIP XML file.

    Arguments:
       graph: Graph object to add nodes to.
       root: Root of XML file.
    """
    scope = root.find("Scope")
    for param in scope.find("RelaticsParameters").iterfind("RelaticsParameter"):
        graph.add_node(Node(kind=PARAMETER_KIND, annotations=param.attrib))

parse_verificatie 

parse_verificatie(el: Element, annotations: Dict)

Parse information attached to Verificatie.

Source code in src/ragraph/io/grip.py 
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
def parse_verificatie(el: etree.Element, annotations: Dict):
    """Parse information attached to Verificatie."""
    v = el.find("Verificatie")

    annotations["Verificatie"] = {
        "Name": v.attrib["Name"],
        "ConfigurationOfRef": v.attrib["ConfigurationOfRef"],
        "GUID": v.attrib["GUID"],
        "Criterium": {
            "RootRef": v.find("Criterium").attrib["RootRef"],
            "Type": v.find("Criterium").attrib["Type"]
        }
    }

    parse_SI_Methode(v, annotations["Verificatie"])
    parse_SI_Fase(v, annotations["Verificatie"])
    parse_CI_Toelichting(v, annotations["Verificatie"])

to_grip 

to_grip(
    graph: Graph,
    path: Optional[Union[str, Path]] = None,
    hierarchy_mode: str = "top-down",
) -> Optional[str]

Convert a graph with GRIP content structure to a GRIP XML.

Parameters:

Name Type Description Default
graph Graph

Graph to convert.

 required
path Optional[Union[str, Path]]

Optional path to write converted XML text to.

 None

Returns:

Type Description
Optional[str]

String contents when no path was given.
Source code in src/ragraph/io/grip.py 
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
def to_grip(
    graph: Graph, path: Optional[Union[str, Path]] = None, hierarchy_mode: str = "top-down"
) -> Optional[str]:
    """Convert a graph with GRIP content structure to a GRIP XML.

    Arguments:
        graph: Graph to convert.
        path: Optional path to write converted XML text to.

    Returns:
        String contents when no path was given.
    """
    report = _build_report(graph, hierarchy_mode)
    byte = etree.tostring(
        report,
        encoding="UTF-8",
        xml_declaration=True,
        pretty_print=True,
    )
    if path:
        Path(path).write_bytes(byte)
    else:
        return byte.decode()

json

JSON format support

from_json 

from_json(
    path: Optional[Union[str, Path]] = None,
    enc: Optional[str] = None,
    use_uuid: bool = True,
) -> Graph

Decode JSON file or string into a Graph.

Parameters:

Name Type Description Default
path Optional[Union[str, Path]]

JSON file path.

 None
enc Optional[str]

JSON encoded string.

 None

Returns:

Type Description
Graph

Graph object.
Source code in src/ragraph/io/json.py 
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
def from_json(
    path: Optional[Union[str, Path]] = None,
    enc: Optional[str] = None,
    use_uuid: bool = True,
) -> Graph:
    """Decode JSON file or string into a Graph.

    Arguments:
        path: JSON file path.
        enc: JSON encoded string.

    Returns:
        Graph object.
    """
    if path is None and enc is None:
        raise ValueError("`path` and `enc` arguments cannot both be `None`.")
    if path is not None and enc is not None:
        raise ValueError("`path` and `enc` arguments cannot both be set.")

    if path:
        enc = Path(path).read_text(encoding="utf-8")

    json_dict = json.loads(enc)

    return graph_from_json_dict(json_dict, use_uuid=use_uuid)

graph_from_json_dict 

graph_from_json_dict(
    graph_dict: Dict[str, Any], use_uuid: bool = True
) -> Graph

Recreate Graph object from JSON dictionary.

Source code in src/ragraph/io/json.py 
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
def graph_from_json_dict(graph_dict: Dict[str, Any], use_uuid: bool = True) -> Graph:
    """Recreate Graph object from JSON dictionary."""
    nodes = graph_dict.get("nodes", dict())
    edges = graph_dict.get("edges", dict())
    g = Graph(
        name=graph_dict.get("name"),
        kind=graph_dict.get("kind"),
        labels=graph_dict.get("labels"),
        weights=graph_dict.get("weights"),
        annotations=graph_dict.get("annotations"),
        uuid=graph_dict.get("uuid"),
    )

    # Get node dictionaries.
    if isinstance(nodes, dict):
        node_dicts = list(nodes.values())
    elif isinstance(nodes, list):
        node_dicts = nodes
    else:
        raise ValueError("Unrecognizable nodes property.")

    # Get edge dictionaries.
    if isinstance(edges, dict):
        edge_dicts = list(edges.values())
    elif isinstance(edges, list):
        edge_dicts = edges
    else:
        raise ValueError("Unrecognizable edges property.")

    # Add initial nodes.
    for nd in node_dicts:
        g.add_node(
            Node(
                name=nd.get("name"),
                kind=nd.get("kind"),
                labels=nd.get("labels"),
                parent=None,
                children=[],
                weights=nd.get("weights"),
                annotations=nd.get("annotations"),
                uuid=nd.get("uuid"),
            )
        )

    node_ref = {str(node.uuid): node for node in g.nodes} if use_uuid else g.node_dict
    ref_key = "uuid" if use_uuid else "name"

    # Resolve references.
    for nd in node_dicts:
        if nd.get("parent", False):
            node_ref[nd[ref_key]].parent = node_ref[nd["parent"]]
        if nd.get("children", False):
            node_ref[nd[ref_key]].children = [node_ref[c] for c in nd["children"]]
        if nd.get("is_bus", False):
            node_ref[nd[ref_key]].is_bus = True

    # Add edges.
    for ed in edge_dicts:
        g.add_edge(
            Edge(
                node_ref[ed["source"]],
                node_ref[ed["target"]],
                name=ed.get("name"),
                kind=ed.get("kind"),
                labels=ed.get("labels"),
                weights=ed.get("weights"),
                annotations=ed.get("annotations"),
                uuid=ed.get("uuid"),
            ),
        )

    return g

to_json 

to_json(
    graph: Graph, path: Optional[Union[str, Path]] = None
) -> Optional[str]

Encode Graph to JSON file or string.

Parameters:

Name Type Description Default
path Optional[Union[str, Path]]

Optional file path to write JSON to.

 None

Returns:

Type Description
Optional[str]

JSON string.
Source code in src/ragraph/io/json.py 
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
def to_json(graph: Graph, path: Optional[Union[str, Path]] = None) -> Optional[str]:
    """Encode Graph to JSON file or string.

    Arguments:
        path: Optional file path to write JSON to.

    Returns:
        JSON string.
    """

    enc = json.dumps(graph, cls=GraphEncoder, sort_keys=True, indent=4)
    if path is not None:
        path = Path(path)
        path.write_text(enc, encoding="utf-8")
        return None
    else:
        return enc

matrix

Adjacency and mapping matrices support

from_matrix 

from_matrix(
    matrix: Union[
        ndarray, List[List[int]], List[List[float]]
    ],
    rows: Optional[Union[List[Node], List[str]]] = None,
    cols: Optional[Union[List[Node], List[str]]] = None,
    weight_label: str = "default",
    empty: Optional[Union[int, float]] = 0.0,
    convention: Convention = IR_FAD,
    **graph_args: Dict[str, Any]
) -> Graph

Create a graph from an adjacency or mapping matrix.

Parameters:

Name Type Description Default
matrix Union[ndarray, List[List[int]], List[List[float]]]

Matrix to convert into a graph.

 required
rows Optional[Union[List[Node], List[str]]]

Nodes or node labels corresponding to the rows of the matrix.

 None
cols Optional[Union[List[Node], List[str]]]

Nodes or node labels corresponding to the columns of the matrix. If none are provided, the row labels are re-used.

 None
weight_label str

Weight label to use for matrix values.

 'default'
empty Optional[Union[int, float]]

Cell value to be considered "empty", e.g. no edge should be created.

 0.0
**graph_args Dict[str, Any]

Additional arguments to Graph constructor.

 {}

Returns:

Type Description
Graph

Graph object.
Note

If no row labels are provided, they are generated in a "node#" format. If no column labels are provided, they are assumed to be equal to the rows. For non-square matrices, you should provide node labels!

Source code in src/ragraph/io/matrix.py 
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
def from_matrix(
    matrix: Union["np.ndarray", List[List[int]], List[List[float]]],
    rows: Optional[Union[List[Node], List[str]]] = None,
    cols: Optional[Union[List[Node], List[str]]] = None,
    weight_label: str = "default",
    empty: Optional[Union[int, float]] = 0.0,
    convention: Convention = Convention.IR_FAD,
    **graph_args: Dict[str, Any],
) -> Graph:
    """Create a graph from an adjacency or mapping matrix.

    Arguments:
        matrix: Matrix to convert into a graph.
        rows: Nodes or node labels corresponding to the rows of the matrix.
        cols: Nodes or node labels corresponding to the columns of the matrix. If none
            are provided, the row labels are re-used.
        weight_label: Weight label to use for matrix values.
        empty: Cell value to be considered "empty", e.g. no edge should be created.
        **graph_args: Additional arguments to [`Graph`][ragraph.graph.Graph] constructor.

    Returns:
        Graph object.

    Note:
        If no row labels are provided, they are generated in a "node#" format.
        If no column labels are provided, they are assumed to be equal to the rows.
        For non-square matrices, you should provide node labels!
    """

    rows = [Node(f"node{i}") for i in range(len(matrix))] if rows is None else rows

    # init empty graph
    graph = Graph(**graph_args)  # type: ignore

    # Parse row labels and create new nodes.
    node_rows = _parse_labels(graph, rows)

    # Init nodes from provided labels.
    if cols is None:
        node_cols = node_rows
    else:
        node_cols = _parse_labels(graph, cols)

    # Dimension check of matrix and labels.
    dim = (len(matrix), len(matrix[0]))
    labdim = (len(node_rows), len(node_cols))
    if dim != labdim:
        raise ValueError(f"Matrix dimensions {dim} do not agree with label dimensions {labdim}.")

    # Generate edges and return.
    if convention == Convention.IR_FAD:
        edges = [
            Edge(
                source,
                target,
                name=f"{source.name}->{target.name}",
                weights={weight_label: matrix[row][col]},
            )
            for row, target in enumerate(node_rows)
            for col, source in enumerate(node_cols)
            if matrix[row][col] != empty
        ]
    elif convention == Convention.IC_FBD:
        edges = [
            Edge(
                source,
                target,
                name=f"{source.name}->{target.name}",
                weights={weight_label: matrix[row][col]},
            )
            for row, source in enumerate(node_rows)
            for col, target in enumerate(node_cols)
            if matrix[row][col] != empty
        ]
    else:
        raise ValueError("Unknown convention for matrix conversion.")

    graph.edges = edges
    return graph

to_matrix 

to_matrix(
    graph: Graph,
    rows: Optional[Union[List[Node], List[str]]] = None,
    cols: Optional[Union[List[Node], List[str]]] = None,
    inherit: bool = False,
    loops: bool = False,
    only: Optional[List[str]] = None,
    convention: Convention = IR_FAD,
) -> Union[ndarray, List[List[float]]]

Convert graph data into a directed numerical adjacency or mapping matrix.

Parameters:

Name Type Description Default
graph Graph

Graph to fetch data from.

 required
rows Optional[Union[List[Node], List[str]]]

Nodes representing the matrix rows.

 None
cols Optional[Union[List[Node], List[str]]]

Nodes representing the matrix columns if different from the rows.

 None
inherit bool

Whether to count weights between children of the given nodes.

 False
loops bool

Whether to calculate self-loops from a node to itself.

 False
only Optional[List[str]]

Optional subset of edge weights to consider. See ragraph.edge.Edge for default edge weight implementation.

 None

Returns:

Type Description
Union[ndarray, List[List[float]]]

Adjacency matrix as a 2D numpy array if numpy is present. Otherwise it will return a 2D
Union[ndarray, List[List[float]]]

nested list.
Note

Note that the matrix is directed! Columns are inputs to rows.

Source code in src/ragraph/io/matrix.py 
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
def to_matrix(
    graph: Graph,
    rows: Optional[Union[List[Node], List[str]]] = None,
    cols: Optional[Union[List[Node], List[str]]] = None,
    inherit: bool = False,
    loops: bool = False,
    only: Optional[List[str]] = None,
    convention: Convention = Convention.IR_FAD,
) -> Union["np.ndarray", List[List[float]]]:
    """Convert graph data into a directed numerical adjacency or mapping matrix.

    Arguments:
        graph: Graph to fetch data from.
        rows: Nodes representing the matrix rows.
        cols: Nodes representing the matrix columns if different from the rows.
        inherit: Whether to count weights between children of the given nodes.
        loops: Whether to calculate self-loops from a node to itself.
        only: Optional subset of edge weights to consider. See
            [`ragraph.edge.Edge`][ragraph.edge.Edge] for default edge weight implementation.

    Returns:
        Adjacency matrix as a 2D numpy array if numpy is present. Otherwise it will return a 2D
        nested list.

    Note:
        Note that the matrix is directed! Columns are inputs to rows.
    """
    if rows is None:
        rows = graph.leafs
    else:
        rows = [n if isinstance(n, Node) else graph.node_dict[n] for n in rows]

    if cols is None:
        cols = rows
    else:
        cols = [n if isinstance(n, Node) else graph.node_dict[n] for n in cols]

    dim = (len(rows), len(cols))
    if np:
        matrix = np.zeros(dim, dtype=float)
    else:
        matrix = [[0.0 for j in range(dim[1])] for i in range(dim[0])]

    for col, col_node in enumerate(cols):
        for row, row_node in enumerate(rows):
            if col_node == row_node and not loops:
                continue

            if convention == Convention.IR_FAD:
                source = col_node
                target = row_node
            elif convention == Convention.IC_FBD:
                source = row_node
                target = col_node
            else:
                raise ValueError("Unknown convention for matrix conversion.")

            sources = [source]
            targets = [target]

            if inherit:
                sources.extend(source.descendants)
                targets.extend(target.descendants)

            weight = sum(
                [_get_weight(e, only=only) for e in graph.edges_between_all(sources, targets)]
            )
            matrix[row][col] = float(weight)

    return matrix

xml

XML format support using the XML Metadata Interchange (XMI) standard.

from_xml 

from_xml(
    path: Optional[Union[str, Path]] = None,
    enc: Optional[str] = None,
    elem: Optional[Element] = None,
    validate: bool = True,
) -> Graph

Decode XML file, string, or element into a Graph.

Parameters:

Name Type Description Default
path Optional[Union[str, Path]]

XML file path.

 None
enc Optional[str]

XML encoded string.

 None
elem Optional[Element]

XML Element.

 None
validate bool

Whether to validate the XML input.

 True

Returns:

Type Description
Graph

Graph object.
Note

You should only provide one of path, enc, or elem, which are handled in that order of precedence.

Source code in src/ragraph/io/xml/__init__.py 
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
def from_xml(
    path: Optional[Union[str, Path]] = None,
    enc: Optional[str] = None,
    elem: Optional[etree.Element] = None,
    validate: bool = True,
) -> Graph:
    """Decode XML file, string, or element into a Graph.

    Arguments:
        path: XML file path.
        enc: XML encoded string.
        elem: XML Element.
        validate: Whether to validate the XML input.

    Returns:
        Graph object.

    Note:
        You should only provide one of `path`, `enc`, or `elem`, which are handled in that order of
        precedence.
    """
    # Parse input XML.
    if path is not None:
        elem = etree.parse(str(Path(path))).getroot()
    elif enc is not None:
        elem = etree.fromstring(enc)
    elif elem is not None:
        assert isinstance(elem, etree._Element)
    else:
        raise ValueError("At least one of the 'path', 'enc', or 'elem' arguments should be set.")

    # Validate if required.
    if validate and not schema.validate(elem):
        raise ValueError(f"Schema validation failed: \n\n{schema.error_log}")

    # Find the Graph XML element.
    g = elem.find(f".//{q_graph}")

    # Parse nodes.
    node_dict = dict()
    for elem in g.findall(f".//{q_node}"):
        node = _element_to_node(elem)
        node_dict[elem.attrib[q_id]] = node
    _resolve_node_references(node_dict)

    # Parse edges.
    edges = [_element_to_edge(e, node_dict) for e in g.findall(f".//{q_edge}")]

    # Build graph and return.
    graph = Graph(nodes=node_dict.values(), edges=edges)
    _element_to_metadata(g, graph)
    return graph

to_xml 

to_xml(
    graph: Graph,
    path: Optional[Union[str, Path]] = None,
    elem: Optional[Element] = None,
    tostring_args: Optional[Dict[str, Any]] = None,
    bundle_schemas: bool = False,
) -> str

Encode Graph to an XML element.

Parameters:

Name Type Description Default
graph Graph

Graph to convert to XML.

 required
path Optional[Union[str, Path]]

Optional file path to write XML to.

 None
elem Optional[Element]

Optional object to append the Graph to.

 None
tostring_args Optional[Dict[str, Any]]

Optional argument overrides to lxml.etree.tostring.

 None
bundle_schemas bool

When exporting to a file, bundle the .xsd schemas.

 False

Returns:

Type Description
str

XML element.
Source code in src/ragraph/io/xml/__init__.py 
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
def to_xml(
    graph: Graph,
    path: Optional[Union[str, Path]] = None,
    elem: Optional[etree.Element] = None,
    tostring_args: Optional[Dict[str, Any]] = None,
    bundle_schemas: bool = False,
) -> str:
    """Encode Graph to an XML element.

    Arguments:
        graph: Graph to convert to XML.
        path: Optional file path to write XML to.
        elem: Optional object to append the Graph to.
        tostring_args: Optional argument overrides to
            [`lxml.etree.tostring`][lxml.etree.tostring].
        bundle_schemas: When exporting to a file, bundle the .xsd schemas.

    Returns:
        XML element.
    """

    if elem is None:
        parser = etree.XMLParser(remove_blank_text=True)
        doc = etree.parse(str(here / "bare.xml"), parser)
        elem = doc.getroot()

    graph_elem = etree.SubElement(elem, q_graph, nsmap=nsmap)
    _metadata_to_subelements(graph_elem, graph)
    graph_elem.extend(_node_to_element(n) for n in graph.nodes)
    graph_elem.extend(_edge_to_element(e) for e in graph.edges)

    if path is not None:
        p = Path(path)

        args = dict(encoding="UTF-8", xml_declaration=True, pretty_print=True)
        if tostring_args is not None:
            args.update(tostring_args)

        string = etree.tostring(elem, **args)
        p.write_bytes(string)

        if bundle_schemas:
            shutil.copy2(here / "ragraph.xsd", p.parent)
            shutil.copy2(here / "XMI-Canonical.xsd", p.parent)

    return elem

yaml

YAML format support

from_yaml 

from_yaml(
    path: Optional[Union[str, Path]] = None,
    enc: Optional[str] = None,
) -> Graph

Decode YAML file or string into a Graph.

Parameters:

Name Type Description Default
path Optional[Union[str, Path]]

YAML file path.

 None
enc Optional[str]

YAML encoded string.

 None

Returns:

Type Description
Graph

Graph object.
Source code in src/ragraph/io/yaml.py 
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
def from_yaml(path: Optional[Union[str, Path]] = None, enc: Optional[str] = None) -> Graph:
    """Decode YAML file or string into a Graph.

    Arguments:
        path: YAML file path.
        enc: YAML encoded string.

    Returns:
        Graph object.
    """
    if path is None and enc is None:
        raise ValueError("`path` and `enc` arguments cannot both be `None`.")
    if path is not None and enc is not None:
        raise ValueError("`path` and `enc` arguments cannot both be set.")

    if path:
        json_dict = yaml.load(Path(path))
    else:
        json_dict = yaml.load(enc)

    return graph_from_json_dict(json_dict)

to_yaml 

to_yaml(
    graph: Graph, path: Optional[Union[str, Path]] = None
) -> Optional[str]

Encode Graph to YAML file or string.

Parameters:

Name Type Description Default
path Optional[Union[str, Path]]

Optional file path to write YAML to.

 None

Returns:

Type Description
Optional[str]

YAML string.
Source code in src/ragraph/io/yaml.py 
40
41
42
43
44
45
46
47
48
49
50
def to_yaml(graph: Graph, path: Optional[Union[str, Path]] = None) -> Optional[str]:
    """Encode Graph to YAML file or string.

    Arguments:
        path: Optional file path to write YAML to.

    Returns:
        YAML string.
    """
    stream = Path(path) if path else None
    return yaml.dump(graph.json_dict, stream=stream)