Add interface with EnzymeML

nmrpy/data_objects.py

@@ -12,6 +12,7 @@
 import pickle
 from ipywidgets import SelectMultiple
 from sdRDM import DataModel
+from sdRDM.base.importedmodules import ImportedModules
 from nmrpy.datamodel.core import *
 
 
@@ -247,12 +248,11 @@ def __init__(self, *args, **kwargs):
         self._flags = {
             "ft": False,
         }
-        self.fid_object = FID(
+        self.fid_object = FIDObject(
             raw_data=[(str(datum)) for datum in self.data],
             processed_data=[],
             nmr_parameters=Parameters(),
             processing_steps=ProcessingSteps(),
-            peak_identities=[],
         )
 
     def __str__(self):
@@ -1416,9 +1416,11 @@ def assign_identities(self):
         containing species defined in EnzymeML. When satisfied with
         assignment, press Assign button to apply.
         """
-
+        raise NotImplementedError
         widget_title = "Assign identities for {}".format(self.id)
-        self._assigner_widget = IdentityAssigner(fid=self, title=widget_title)
+        self._assigner_widget = IdentityAssigner(
+            fid=self, title=widget_title, available_species=[]
+        )
 
     def clear_identities(self):
         """
@@ -1483,6 +1485,41 @@ def data_model(self):
         del self.__data_model
         print("The current data model has been deleted.")
 
+    @property
+    def enzymeml_document(self):
+        return self.__enzymeml_document
+
+    @enzymeml_document.setter
+    def enzymeml_document(self, enzymeml_document: DataModel):
+        if not isinstance(enzymeml_document, DataModel):
+            raise AttributeError(
+                f"Parameter `enzymeml_document` has to be of type `sdrdm.DataModel`, got {type(enzymeml_document)} instead."
+            )
+        self.__enzymeml_document = enzymeml_document
+        self.__enzymeml_document.modified = datetime.now()
+
+    @enzymeml_document.deleter
+    def enzymeml_document(self):
+        del self.__enzymeml_document
+        print("The current EnzymeML document has been deleted.")
+
+    @property
+    def enzymeml_library(self):
+        return self.__enzymeml_library
+
+    @enzymeml_library.setter
+    def enzymeml_library(self, enzymeml_library: ImportedModules):
+        if not isinstance(enzymeml_library, ImportedModules):
+            raise AttributeError(
+                f"Parameter `enzymeml_library` has to be of type `sdrdm.base.importedmodules.ImportedModules`, got {type(enzymeml_library)} instead."
+            )
+        self.__enzymeml_library = enzymeml_library
+
+    @enzymeml_library.deleter
+    def enzymeml_library(self):
+        del self.__enzymeml_library
+        print("The current EnzymeML library has been deleted.")
+
     def __str__(self):
         return "FidArray of {} FID(s)".format(len(self.data))
 
@@ -1647,6 +1684,17 @@ def add_fids(self, fids):
                 except AttributeError as e:
                     print(e)
 
+    def parse_enzymeml_document(self, path_to_enzymeml_document) -> None:
+        """Parse an EnzymeML document and its library from specified
+        file path.
+
+        Args:
+            path_to_enzymeml_document (str): Path to file containing an EnzymeML document
+        """
+        self.enzymeml_document, self.enzymeml_library = DataModel.parse(
+            path_to_enzymeml_document
+        )
+
     @classmethod
     def from_data(cls, data):
         """

nmrpy/datamodel/core/__init__.py

@@ -1,6 +1,6 @@
 from .nmrpy import NMRpy
 from .experiment import Experiment
-from .fid import FID
+from .fidobject import FIDObject
 from .parameters import Parameters
 from .processingsteps import ProcessingSteps
 from .identity import Identity
@@ -16,11 +16,10 @@
 from .identifiertypes import IdentifierTypes
 
 __doc__ = ""
-
 __all__ = [
     "NMRpy",
     "Experiment",
-    "FID",
+    "FIDObject",
     "Parameters",
     "ProcessingSteps",
     "Identity",

nmrpy/datamodel/core/citation.py

@@ -1,19 +1,15 @@
 import sdRDM
 
-from typing import List, Optional
-from pydantic import Field
+from typing import Any, List, Optional
+from pydantic import AnyUrl, Field
 from sdRDM.base.listplus import ListPlus
 from sdRDM.base.utils import forge_signature, IDGenerator
-
-from pydantic import AnyUrl
-from typing import Any
-
-from .term import Term
+from .publicationtypes import PublicationTypes
+from .person import Person
 from .identifiertypes import IdentifierTypes
+from .term import Term
 from .publication import Publication
 from .subjects import Subjects
-from .publicationtypes import PublicationTypes
-from .person import Person
 
 
 @forge_signature
@@ -111,7 +107,6 @@ def add_to_authors(
             identifier_type (): Recognized identifier for the person.. Defaults to None
             identifier_value (): Value of the identifier for the person.. Defaults to None
         """
-
         params = {
             "last_name": last_name,
             "first_name": first_name,
@@ -121,12 +116,9 @@ def add_to_authors(
             "identifier_type": identifier_type,
             "identifier_value": identifier_value,
         }
-
         if id is not None:
             params["id"] = id
-
         self.authors.append(Person(**params))
-
         return self.authors[-1]
 
     def add_to_keywords(
@@ -147,19 +139,15 @@ def add_to_keywords(
             term_cv_reference (): Reference to the `CV.id` of a controlled vocabulary that has been defined for this dataset.. Defaults to None
             value (): Value of the term, if applicable.. Defaults to None
         """
-
         params = {
             "name": name,
             "accession": accession,
             "term_cv_reference": term_cv_reference,
             "value": value,
         }
-
         if id is not None:
             params["id"] = id
-
         self.keywords.append(Term(**params))
-
         return self.keywords[-1]
 
     def add_to_topics(
@@ -180,19 +168,15 @@ def add_to_topics(
             term_cv_reference (): Reference to the `CV.id` of a controlled vocabulary that has been defined for this dataset.. Defaults to None
             value (): Value of the term, if applicable.. Defaults to None
         """
-
         params = {
             "name": name,
             "accession": accession,
             "term_cv_reference": term_cv_reference,
             "value": value,
         }
-
         if id is not None:
             params["id"] = id
-
         self.topics.append(Term(**params))
-
         return self.topics[-1]
 
     def add_to_related_publications(
@@ -215,18 +199,14 @@ def add_to_related_publications(
             year (): Year of publication.. Defaults to None
             doi (): The DOI pointing to the publication.. Defaults to None
         """
-
         params = {
             "type": type,
             "title": title,
             "authors": authors,
             "year": year,
             "doi": doi,
         }
-
         if id is not None:
             params["id"] = id
-
         self.related_publications.append(Publication(**params))
-
         return self.related_publications[-1]

nmrpy/datamodel/core/cv.py

@@ -1,11 +1,9 @@
 import sdRDM
 
 from typing import Optional
-from pydantic import Field
+from pydantic import AnyUrl, Field
 from sdRDM.base.utils import forge_signature, IDGenerator
 
-from pydantic import AnyUrl
-
 
 @forge_signature
 class CV(sdRDM.DataModel):

nmrpy/datamodel/core/experiment.py

@@ -4,13 +4,11 @@
 from pydantic import Field
 from sdRDM.base.listplus import ListPlus
 from sdRDM.base.utils import forge_signature, IDGenerator
-
-
-from .fidarray import FIDArray
-from .fid import FID
 from .parameters import Parameters
+from .fidarray import FIDArray
 from .processingsteps import ProcessingSteps
 from .identity import Identity
+from .fidobject import FIDObject
 
 
 @forge_signature
@@ -36,7 +34,7 @@ class Experiment(sdRDM.DataModel):
         multiple=True,
     )
 
-    fid: List[FID] = Field(
+    fid: List[FIDObject] = Field(
         description="A single NMR spectrum.",
         default_factory=ListPlus,
         multiple=True,
@@ -57,28 +55,24 @@ def add_to_fid(
         id: Optional[str] = None,
     ) -> None:
         """
-        This method adds an object of type 'FID' to attribute fid
+        This method adds an object of type 'FIDObject' to attribute fid
 
         Args:
-            id (str): Unique identifier of the 'FID' object. Defaults to 'None'.
+            id (str): Unique identifier of the 'FIDObject' object. Defaults to 'None'.
             raw_data (): Complex spectral data from numpy array as string of format `{array.real}+{array.imag}j`.. Defaults to ListPlus()
             processed_data (): Processed data array.. Defaults to ListPlus()
             nmr_parameters (): Contains commonly-used NMR parameters.. Defaults to None
             processing_steps (): Contains the processing steps performed, as well as the parameters used for them.. Defaults to None
             peak_identities (): Container holding and mapping integrals resulting from peaks and their ranges to EnzymeML species.. Defaults to ListPlus()
         """
-
         params = {
             "raw_data": raw_data,
             "processed_data": processed_data,
             "nmr_parameters": nmr_parameters,
             "processing_steps": processing_steps,
             "peak_identities": peak_identities,
         }
-
         if id is not None:
             params["id"] = id
-
-        self.fid.append(FID(**params))
-
+        self.fid.append(FIDObject(**params))
         return self.fid[-1]

nmrpy/datamodel/core/fidarray.py

@@ -8,7 +8,7 @@
 
 @forge_signature
 class FIDArray(sdRDM.DataModel):
-    """Container for processing of multiple spectra. Must reference the respective `FID` objects by `id`. {Add reference back. Setup time for experiment, Default 0.5}"""
+    """Container for processing of multiple spectra. Must reference the respective `FIDObject` by `id`. {Add reference back. Setup time for experiment, Default 0.5}"""
 
     id: Optional[str] = Field(
         description="Unique identifier of the given object.",
@@ -17,7 +17,7 @@ class FIDArray(sdRDM.DataModel):
     )
 
     fids: List[str] = Field(
-        description="List of `FID.id` belonging to this array.",
+        description="List of `FIDObject.id` belonging to this array.",
         multiple=True,
         default_factory=ListPlus,
     )

nmrpy/datamodel/core/fid.py → nmrpy/datamodel/core/fidobject.py

@@ -4,21 +4,18 @@
 from pydantic import Field
 from sdRDM.base.listplus import ListPlus
 from sdRDM.base.utils import forge_signature, IDGenerator
-
-from pydantic.types import FrozenSet
-
 from .parameters import Parameters
 from .processingsteps import ProcessingSteps
-from .identity import Identity
+from .identity import Identity, AssociatedRanges
 
 
 @forge_signature
-class FID(sdRDM.DataModel):
+class FIDObject(sdRDM.DataModel):
     """Container for a single NMR spectrum."""
 
     id: Optional[str] = Field(
         description="Unique identifier of the given object.",
-        default_factory=IDGenerator("fidINDEX"),
+        default_factory=IDGenerator("fidobjectINDEX"),
         xml="@id",
     )
 
@@ -64,7 +61,7 @@ def add_to_peak_identities(
         name: Optional[str] = None,
         species_id: Optional[str] = None,
         associated_peaks: List[float] = ListPlus(),
-        associated_ranges: List[FrozenSet] = ListPlus(),
+        associated_ranges: List[AssociatedRanges] = ListPlus(),
         associated_integrals: List[float] = ListPlus(),
         id: Optional[str] = None,
     ) -> None:
@@ -79,18 +76,14 @@ def add_to_peak_identities(
             associated_ranges (): Sets of ranges belonging to the given peaks. Defaults to ListPlus()
             associated_integrals (): Integrals resulting from the given peaks and ranges of a species. Defaults to ListPlus()
         """
-
         params = {
             "name": name,
             "species_id": species_id,
             "associated_peaks": associated_peaks,
             "associated_ranges": associated_ranges,
             "associated_integrals": associated_integrals,
         }
-
         if id is not None:
             params["id"] = id
-
         self.peak_identities.append(Identity(**params))
-
         return self.peak_identities[-1]