API reference¶
The Python API client is primarily a GraphQL client that interacts with our GraphQL API endpoint. Install the cryoet-data-portal package to use the following classes with methods for searching and downloading datasets, tomograms, annotations and related files and metadata from the portal.
- class cryoet_data_portal.Alignment¶
- Tiltseries Alignment Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - annotation_files- List[AnnotationFile]- The annotation files of this alignment - per_section_alignments- List[PerSectionAlignmentParameters]- The per section alignment parameters of this alignment - deposition- Deposition- The deposition this alignment is a part of - deposition_id- int- None - tiltseries- TiltSeries- The tilt series this alignment is a part of - tiltseries_id- int- None - tomograms- List[Tomogram]- The tomograms of this alignment - run- Run- The run this alignment is a part of - run_id- int- None - alignment_type- str- Whether this a LOCAL or GLOBAL alignment - alignment_method- str- The method used to create this alignment - volume_x_dimension- float- X dimension of the reconstruction volume in angstrom - volume_y_dimension- float- Y dimension of the reconstruction volume in angstrom - volume_z_dimension- float- Z dimension of the reconstruction volume in angstrom - volume_x_offset- float- X shift of the reconstruction volume in angstrom - volume_y_offset- float- Y shift of the reconstruction volume in angstrom - volume_z_offset- float- Z shift of the reconstruction volume in angstrom - x_rotation_offset- float- Additional X rotation of the reconstruction volume in degrees - tilt_offset- float- Additional tilt offset in degrees - affine_transformation_matrix- str- A placeholder for the affine transformation matrix. - s3_alignment_metadata- str- S3 path to the metadata file for this alignment - https_alignment_metadata- str- HTTPS url to the metadata file for this alignment - is_portal_standard- bool- Whether this is the portal standard alignment - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> alignments = Alignment.find(client, query_filters=[Alignment.run.name == "TS_026"])- Get all results for this type: - >>> alignments = Alignment.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an Alignment by ID: - >>> alignment = Alignment.get_by_id(client, 10000) >>> print(alignment.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.Annotation¶
- Metadata for an annotation Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - run- Run- The run this annotation is a part of - run_id- int- None - annotation_shapes- List[AnnotationShape]- The annotation shapes of this annotation - method_links- List[AnnotationMethodLink]- The annotation method links of this annotation - authors- List[AnnotationAuthor]- The annotation authors of this annotation - deposition- Deposition- The deposition this annotation is a part of - deposition_id- int- None - s3_metadata_path- str- S3 path for the metadata json file for this annotation - https_metadata_path- str- HTTPS path for the metadata json file for this annotation - annotation_publication- str- DOIs for publications that describe the dataset. Use a comma to separate multiple DOIs. - annotation_method- str- Describe how the annotation is made (e.g. Manual, crYoLO, Positive Unlabeled Learning, template matching) - ground_truth_status- bool- Whether an annotation is considered ground truth, as determined by the annotator. - object_id- str- Gene Ontology Cellular Component identifier or UniProtKB accession for the annotation object. - object_name- str- Name of the object being annotated (e.g. ribosome, nuclear pore complex, actin filament, membrane) - object_description- str- A textual description of the annotation object, can be a longer description to include additional information not covered by the Annotation object name and state. - object_state- str- Molecule state annotated (e.g. open, closed) - object_count- int- Number of objects identified - confidence_precision- float- Describe the confidence level of the annotation. Precision is defined as the % of annotation objects being true positive - confidence_recall- float- Describe the confidence level of the annotation. Recall is defined as the % of true positives being annotated correctly - ground_truth_used- str- Annotation filename used as ground truth for precision and recall - annotation_software- str- Software used for generating this annotation - is_curator_recommended- bool- Data curator’s subjective choice as the best annotation of the same annotation object ID - method_type- str- The method type for generating the annotation (e.g. manual, hybrid, automated) - deposition_date- date- Date when an annotation set is initially received by the Data Portal. - release_date- date- Date when annotation data is made public by the Data Portal. - last_modified_date- date- Date when an annotation was last modified in the Data Portal - 
download(dest_path=None, format=None, shape=None)¶
- Download annotation files for a given format and/or shape - Parameters:
 
 - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> annotations = Annotation.find(client, query_filters=[Annotation.run.name == "TS_026"])- Get all results for this type: - >>> annotations = Annotation.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an Annotation by ID: - >>> annotation = Annotation.get_by_id(client, 10000) >>> print(annotation.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
download(dest_path=
- class cryoet_data_portal.AnnotationAuthor¶
- Metadata for an annotation’s authors Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - annotation- Annotation- The annotation this annotation author is a part of - annotation_id- int- None - author_list_order- int- The order in which the author appears in the publication - orcid- str- A unique, persistent identifier for researchers, provided by ORCID. - kaggle_id- str- A unique, persistent identifier for kaggle users at kaggle.com. - name- str- Full name of an annotation author (e.g. Jane Doe). - email- str- Email address for this author - affiliation_name- str- Name of the institution an annotator is affiliated with. Sometimes, one annotator may have multiple affiliations. - affiliation_address- str- Address of the institution an annotator is affiliated with. - affiliation_identifier- str- A unique identifier assigned to the affiliated institution by The Research Organization Registry (ROR). - corresponding_author_status- bool- Indicates whether an annotator is the corresponding author - primary_author_status- bool- Indicates whether an author is the main person executing the annotation, especially on manual annotation - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> annotation_authors = AnnotationAuthor.find(client, query_filters=[AnnotationAuthor.annotation.run.name._in(['TS_026', 'TS_027']), AnnotationAuthor.annotation.object_name.ilike('%membrane%')])- Get all results for this type: - >>> annotation_authors = AnnotationAuthor.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an AnnotationAuthor by ID: - >>> annotation_author = AnnotationAuthor.get_by_id(client, 10000) >>> print(annotation_author.name)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.AnnotationFile¶
- Metadata for files associated with an annotation Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - alignment- Alignment- The alignment this annotation file is a part of - alignment_id- int- None - annotation_shape- AnnotationShape- The annotation shape this annotation file is a part of - annotation_shape_id- int- None - tomogram_voxel_spacing- TomogramVoxelSpacing- The tomogram voxel spacing this annotation file is a part of - tomogram_voxel_spacing_id- int- None - format- str- File format for this file - s3_path- str- s3 path of the annotation file - file_size- float- Size of annotation file in bytes - https_path- str- HTTPS path for this annotation file - is_visualization_default- bool- Data curator’s subjective choice of default annotation to display in visualization for an object - source- str- The source type for the annotation file (dataset_author, community, or portal_standard) - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Get all results for this type: - >>> annotation_files = AnnotationFile.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an AnnotationFile by ID: - >>> annotation_file = AnnotationFile.get_by_id(client, 10000) >>> print(annotation_file.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.AnnotationMethodLink¶
- A set of links to models, source code, documentation, etc referenced by annotation method Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - annotation- Annotation- The annotation this annotation method link is a part of - annotation_id- int- None - link_type- str- Type of link (e.g. model, source code, documentation) - name- str- user readable name of the resource - link- str- URL to the resource - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> annotation_method_links = AnnotationMethodLink.find(client, query_filters=[AnnotationMethodLink.annotation.run.name._in(['TS_026', 'TS_027']), AnnotationMethodLink.annotation.object_name.ilike('%membrane%')])- Get all results for this type: - >>> annotation_method_links = AnnotationMethodLink.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an AnnotationMethodLink by ID: - >>> annotation_method_link = AnnotationMethodLink.get_by_id(client, 10000) >>> print(annotation_method_link.name)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.AnnotationShape¶
- Shapes associated with an annotation Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - annotation- Annotation- The annotation this annotation shape is a part of - annotation_id- int- None - annotation_files- List[AnnotationFile]- The annotation files of this annotation shape - shape_type- str- The shape of the annotation (SegmentationMask, OrientedPoint, Point, InstanceSegmentation, Mesh) - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> annotation_shapes = AnnotationShape.find(client, query_filters=[AnnotationShape.annotation.run.name._in(['TS_026', 'TS_027']), AnnotationShape.annotation.object_name.ilike('%membrane%')])- Get all results for this type: - >>> annotation_shapes = AnnotationShape.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an AnnotationShape by ID: - >>> annotation_shape = AnnotationShape.get_by_id(client, 10000) >>> print(annotation_shape.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.Client¶
- A GraphQL Client library that can traverse all the metadata in the CryoET Data Portal - Parameters:
- url : Optional[str]
- The API URL to connect to, defaults to the latest portal endpoint. 
 
- Returns:
- A GraphQL API Client library 
 - Examples - Generate a client that connects to the default GraphQL API: - >>> client = cryoet_data_portal.Client()
- class cryoet_data_portal.Dataset¶
- A collection of imaging experiments on the same organism Attributes:- Name - Type - Description - id- int- An identifier for a CryoET dataset, assigned by the Data Portal. Used to identify the dataset as the directory name in data tree - deposition- Deposition- The deposition this dataset is a part of - deposition_id- int- None - funding_sources- List[DatasetFunding]- The dataset fundings of this dataset - authors- List[DatasetAuthor]- The dataset authors of this dataset - runs- List[Run]- The runs of this dataset - title- str- Title of a CryoET dataset - description- str- A short description of a CryoET dataset, similar to an abstract for a journal article or dataset. - assay_label- str- Label for the type of assay performed in a CryoET dataset, e.g. cryo-electron tomography - assay_ontology_id- str- Ontology identifier for the type of assay performed in a CryoET dataset - development_stage_name- str- Development stage of the organism from which a biological sample used the study is derived. - development_stage_ontology_id- str- Ontology identifier for the development stage - disease_name- str- Name of the disease associated with the biological sample used in a CryoET study, e.g. Alzheimer’s disease - disease_ontology_id- str- Ontology identifier for the disease associated with the biological sample used in a CryoET study - organism_name- str- Name of the organism from which a biological sample used in a CryoET study is derived from, e.g. homo sapiens - organism_taxid- int- NCBI taxonomy identifier for the organism, e.g. 9606 - tissue_name- str- Name of the tissue from which a biological sample used in a CryoET study is derived from. - tissue_id- str- UBERON identifier for the tissue - cell_name- str- Name of the cell from which a biological sample used in a CryoET study is derived from. - cell_type_id- str- Cell Ontology identifier for the cell type - cell_strain_name- str- Cell line or strain for the sample. - cell_strain_id- str- Link to more information about the cell strain - sample_type- str- Type of samples used in a CryoET study. (cell, tissue, organism, intact organelle, in-vitro mixture, in-silico synthetic data, other) - sample_preparation- str- Describe how the sample was prepared. - grid_preparation- str- Describe Cryo-ET grid preparation. - other_setup- str- Describe other setup not covered by sample preparation or grid preparation that may make this dataset unique in the same publication - key_photo_url- str- URL for the dataset preview image. - key_photo_thumbnail_url- str- URL for the thumbnail of preview image. - cell_component_name- str- Name of the cellular component - cell_component_id- str- If the dataset focuses on a specific part of a cell, the subset is included here - deposition_date- date- Date when a dataset is initially received by the Data Portal. - release_date- date- Date when a dataset is made available on the Data Portal. - last_modified_date- date- Date when a released dataset is last modified. - dataset_publications- str- Comma-separated list of DOIs for publications associated with the dataset. - related_database_entries- str- If a CryoET dataset is also deposited into another database, enter the database identifier here (e.g. EMPIAR-11445). Use a comma to separate multiple identifiers. - s3_prefix- str- The S3 public bucket path where this dataset is contained - https_prefix- str- The https directory path where this dataset is contained - file_size- float- Size of the dataset in bytes - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Get all results for this type: - >>> datasets = Dataset.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an Dataset by ID: - >>> dataset = Dataset.get_by_id(client, 10000) >>> print(dataset.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.DatasetAuthor¶
- An author of a dataset Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - dataset- Dataset- The dataset this dataset author is a part of - dataset_id- int- None - author_list_order- int- The order in which the author appears in the publication - orcid- str- A unique, persistent identifier for researchers, provided by ORCID. - kaggle_id- str- A unique, persistent identifier for kaggle users at kaggle.com. - name- str- Full name of a dataset author (e.g. Jane Doe). - email- str- Email address for this author - affiliation_name- str- Name of the institutions an author is affiliated with. Comma separated - affiliation_address- str- Address of the institution an author is affiliated with. - affiliation_identifier- str- A unique identifier assigned to the affiliated institution by The Research Organization Registry (ROR). - corresponding_author_status- bool- Indicates whether an author is the corresponding author - primary_author_status- bool- Indicates whether an author is the main person associated with the corresponding dataset - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Filter dataset authors by attributes, including attributes in related models: - >>> dataset_authors = DatasetAuthor.find(client, query_filters=[DatasetAuthor.name == "TS_026", DatasetAuthor.dataset.id == 10000])- Get all results for this type: - >>> dataset_authors = DatasetAuthor.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an DatasetAuthor by ID: - >>> dataset_author = DatasetAuthor.get_by_id(client, 10000) >>> print(dataset_author.name)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.DatasetFunding¶
- Metadata for a dataset’s funding sources Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - dataset- Dataset- The dataset this dataset funding is a part of - dataset_id- int- None - funding_agency_name- str- Name of the funding agency. - grant_id- str- Grant identifier provided by the funding agency. - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Filter dataset fundings by attributes, including attributes in related models: - >>> dataset_fundings = DatasetFunding.find(client, query_filters=[DatasetFunding.dataset.id == 10000])- Get all results for this type: - >>> dataset_fundings = DatasetFunding.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an DatasetFunding by ID: - >>> dataset_funding = DatasetFunding.get_by_id(client, 10000) >>> print(dataset_funding.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.Deposition¶
- Deposition metadata Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - authors- List[DepositionAuthor]- The deposition authors of this deposition - alignments- List[Alignment]- The alignments of this deposition - annotations- List[Annotation]- The annotations of this deposition - datasets- List[Dataset]- The datasets of this deposition - frames- List[Frame]- The frames of this deposition - tiltseries- List[TiltSeries]- The tilt series of this deposition - tomograms- List[Tomogram]- The tomograms of this deposition - title- str- Title for the deposition - description- str- Description for the deposition - tag- str- Tag for the deposition - like ml competition - deposition_types- List[DepositionType]- The deposition types of this deposition - deposition_publications- str- The publications related to this deposition - related_database_entries- str- The related database entries to this deposition - deposition_date- date- The date the deposition was deposited - release_date- date- The date the deposition was released - last_modified_date- date- The date the deposition was last modified - key_photo_url- str- URL for the deposition preview image. - key_photo_thumbnail_url- str- URL for the deposition thumbnail image. - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Get all results for this type: - >>> depositions = Deposition.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an Deposition by ID: - >>> deposition = Deposition.get_by_id(client, 10000) >>> print(deposition.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.DepositionAuthor¶
- Authors for a deposition Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - deposition- Deposition- The deposition this deposition author is a part of - deposition_id- int- None - author_list_order- int- The order in which the author appears in the publication - orcid- str- A unique, persistent identifier for researchers, provided by ORCID. - kaggle_id- str- A unique, persistent identifier for kaggle users at kaggle.com. - name- str- Full name of a deposition author (e.g. Jane Doe). - email- str- Email address for this author - affiliation_name- str- Name of the institutions an author is affiliated with. Comma separated - affiliation_address- str- Address of the institution an author is affiliated with. - affiliation_identifier- str- A unique identifier assigned to the affiliated institution by The Research Organization Registry (ROR). - corresponding_author_status- bool- Indicates whether an author is the corresponding author - primary_author_status- bool- Indicates whether an author is the main person creating the deposition - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Get all results for this type: - >>> deposition_authors = DepositionAuthor.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an DepositionAuthor by ID: - >>> deposition_author = DepositionAuthor.get_by_id(client, 10000) >>> print(deposition_author.name)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.DepositionType¶
- None Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - deposition- Deposition- The deposition this deposition type is a part of - deposition_id- int- None - type- str- The type of data submitted as a part of this deposition (annotation, dataset, tomogram) - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Get all results for this type: - >>> deposition_types = DepositionType.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an DepositionType by ID: - >>> deposition_type = DepositionType.get_by_id(client, 10000) >>> print(deposition_type.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.Frame¶
- None Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - deposition- Deposition- The deposition this frame is a part of - deposition_id- int- None - run- Run- The run this frame is a part of - run_id- int- None - acquisition_order- int- Frame’s acquistion order within a tilt experiment - accumulated_dose- float- The total accumulated dose exposure frame - exposure_dose- float- The dose exposure of this frame - is_gain_corrected- bool- Whether this frame has been gain corrected - per_section_parameters- List[PerSectionParameters]- The per section parameters of this frame - s3_frame_path- str- S3 path to the frame file - https_frame_path- str- HTTPS path to the frame file - file_size- float- Size of the frame file in bytes - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> frames = Frame.find(client, query_filters=[Frame.run.name == "TS_026"])- Get all results for this type: - >>> frames = Frame.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an Frame by ID: - >>> frame = Frame.get_by_id(client, 10000) >>> print(frame.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.FrameAcquisitionFile¶
- References to files containing more information about frame acquisition Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - run- Run- The run this frame acquisition file is a part of - run_id- int- None - s3_mdoc_path- str- Path to the frame acquisition mdoc file in s3 - https_mdoc_path- str- Path to the frame acquisition mdoc file as an https url - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> frame_acquisition_files = FrameAcquisitionFile.find(client, query_filters=[FrameAcquisitionFile.run.name == "TS_026"])- Get all results for this type: - >>> frame_acquisition_files = FrameAcquisitionFile.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an FrameAcquisitionFile by ID: - >>> frame_acquisition_file = FrameAcquisitionFile.get_by_id(client, 10000) >>> print(frame_acquisition_file.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.GainFile¶
- Gain values for frames in this run Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - run- Run- The run this gain file is a part of - run_id- int- None - s3_file_path- str- Path to the file in s3 - https_file_path- str- Path to the file as an https url - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> gain_files = GainFile.find(client, query_filters=[GainFile.run.name == "TS_026"])- Get all results for this type: - >>> gain_files = GainFile.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an GainFile by ID: - >>> gain_file = GainFile.get_by_id(client, 10000) >>> print(gain_file.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.PerSectionAlignmentParameters¶
- Map alignment parameters to tilt series frames Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - alignment- Alignment- The alignment this per section alignment parameters is a part of - alignment_id- int- None - z_index- int- z-index of the frame in the tiltseries - x_offset- float- In-plane X-shift of the projection in angstrom - y_offset- float- In-plane Y-shift of the projection in angstrom - volume_x_rotation- float- X-axis rotation in degrees - in_plane_rotation- List[List[float]]- In-plane rotation of the projection in degrees - tilt_angle- float- Tilt angle of the projection in degrees - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Get all results for this type: - >>> per_section_alignment_parameters = PerSectionAlignmentParameters.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an PerSectionAlignmentParameters by ID: - >>> per_section_alignment_parameters = PerSectionAlignmentParameters.get_by_id(client, 10000) >>> print(per_section_alignment_parameters.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.PerSectionParameters¶
- Map individual Frames to a Tiltseries Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - astigmatic_angle- float- Angle (in degrees) from reciprocal space X axis to the major axis of defocus. - frame- Frame- The frame this per section parameters is a part of - frame_id- int- None - major_defocus- float- Defocus (major axis) estimated for this tilt image in Angstrom (underfocus has positive sign). - max_resolution- float- Maximum resolution of the frame - minor_defocus- float- Defocus (minor axis) estimated for this tilt image in Angstrom (underfocus has positive sign). - phase_shift- float- Phase shift estimated for this tilt image in degrees. - raw_angle- float- Nominal tilt angle for this tilt image reported by the microscope. - run- Run- The run this per section parameters is a part of - run_id- int- None - tiltseries- TiltSeries- The tilt series this per section parameters is a part of - tiltseries_id- int- None - z_index- int- Index (0-based) of this tilt image in the tilt series stack. - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> per_section_parameters = PerSectionParameters.find(client, query_filters=[PerSectionParameters.run.name == "TS_026"])- Get all results for this type: - >>> per_section_parameters = PerSectionParameters.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an PerSectionParameters by ID: - >>> per_section_parameters = PerSectionParameters.get_by_id(client, 10000) >>> print(per_section_parameters.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.Run¶
- None Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - alignments- List[Alignment]- The alignments of this run - annotations- List[Annotation]- The annotations of this run - dataset- Dataset- The dataset this run is a part of - dataset_id- int- None - frames- List[Frame]- The frames of this run - gain_files- List[GainFile]- The gain files of this run - frame_acquisition_files- List[FrameAcquisitionFile]- The frame acquisition files of this run - per_section_parameters- List[PerSectionParameters]- The per section parameters of this run - tiltseries- List[TiltSeries]- The tilt series of this run - tomogram_voxel_spacings- List[TomogramVoxelSpacing]- The tomogram voxel spacings of this run - tomograms- List[Tomogram]- The tomograms of this run - name- str- Short name for this experiment run - s3_prefix- str- The S3 public bucket path where this run is contained - https_prefix- str- The HTTPS directory path where this run is contained url - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Filter runs by attributes, including attributes in related models: - >>> runs = Run.find(client, query_filters=[Run.name == "TS_026", Run.dataset.id == 10000]) >>> runs = Run.find(client, query_filters=[Run.name._in(['TS_026', 'TS_027']), Run.annotations.object_name.ilike('%membrane%')])- Get all results for this type: - >>> runs = Run.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an Run by ID: - >>> run = Run.get_by_id(client, 10000) >>> print(run.name)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.TiltSeries¶
- None Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - alignments- List[Alignment]- The alignments of this tilt series - run- Run- The run this tilt series is a part of - run_id- int- None - deposition- Deposition- The deposition this tilt series is a part of - deposition_id- int- None - s3_omezarr_dir- str- S3 path to this tiltseries in multiscale OME-Zarr format - file_size_omezarr- float- Size of the tiltseries in OME-Zarr format in bytes - s3_mrc_file- str- S3 path to this tiltseries in MRC format (no scaling) - file_size_mrc- float- Size of the tiltseries in MRC format in bytes - https_omezarr_dir- str- HTTPS path to this tiltseries in multiscale OME-Zarr format - https_mrc_file- str- HTTPS path to this tiltseries in MRC format (no scaling) - s3_angle_list- str- S3 path to the angle list file for this tiltseries - https_angle_list- str- HTTPS path to the angle list file for this tiltseries - acceleration_voltage- int- Electron Microscope Accelerator voltage in volts - spherical_aberration_constant- float- Spherical Aberration Constant of the objective lens in millimeters - microscope_manufacturer- str- Name of the microscope manufacturer (FEI, TFS, JEOL) - microscope_model- str- Microscope model name - microscope_energy_filter- str- Energy filter setup used - microscope_phase_plate- str- Phase plate configuration - microscope_image_corrector- str- Image corrector setup - microscope_additional_info- str- Other microscope optical setup information, in addition to energy filter, phase plate and image corrector - per_section_parameters- List[PerSectionParameters]- The per section parameters of this tilt series - camera_manufacturer- str- Name of the camera manufacturer - camera_model- str- Camera model name - tilt_min- float- Minimal tilt angle in degrees - tilt_max- float- Maximal tilt angle in degrees - tilt_range- float- Total tilt range in degrees - tilt_step- float- Tilt step in degrees - tilting_scheme- str- The order of stage tilting during acquisition of the data - tilt_axis- float- Rotation angle in degrees - total_flux- float- Number of Electrons reaching the specimen in a square Angstrom area for the entire tilt series - data_acquisition_software- str- Software used to collect data - related_empiar_entry- str- If a tilt series is deposited into EMPIAR, enter the EMPIAR dataset identifier - binning_from_frames- float- Describes the binning factor from frames to tilt series file - tilt_series_quality- int- Author assessment of tilt series quality within the dataset (1-5, 5 is best) - is_aligned- bool- Whether this tilt series is aligned - pixel_spacing- float- Pixel spacing equal in both axes in angstroms - aligned_tiltseries_binning- int- Binning factor of the aligned tilt series - size_x- int- Number of pixels in the 3D data fast axis - size_y- int- Number of pixels in the 3D data medium axis - size_z- int- Number of pixels in the 3D data slow axis - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> tilt_series = TiltSeries.find(client, query_filters=[TiltSeries.run.name == "TS_026"])- Get all results for this type: - >>> tilt_series = TiltSeries.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an TiltSeries by ID: - >>> tilt_series = TiltSeries.get_by_id(client, 10000) >>> print(tilt_series.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.Tomogram¶
- Metadata describing a tomogram. Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - alignment- Alignment- The alignment this tomogram is a part of - alignment_id- int- None - authors- List[TomogramAuthor]- The tomogram authors of this tomogram - deposition- Deposition- The deposition this tomogram is a part of - deposition_id- int- None - run- Run- The run this tomogram is a part of - run_id- int- None - tomogram_voxel_spacing- TomogramVoxelSpacing- The tomogram voxel spacing this tomogram is a part of - tomogram_voxel_spacing_id- int- None - name- str- Short name for this tomogram - size_x- int- Number of pixels in the 3D data fast axis - size_y- int- Number of pixels in the 3D data medium axis - size_z- int- Number of pixels in the 3D data slow axis. This is the image projection direction at zero stage tilt - voxel_spacing- float- Voxel spacing equal in all three axes in angstroms - fiducial_alignment_status- str- Fiducial Alignment status: True = aligned with fiducial False = aligned without fiducial - reconstruction_method- str- Describe reconstruction method (WBP, SART, SIRT) - processing- str- Describe additional processing used to derive the tomogram - tomogram_version- float- Version of tomogram - processing_software- str- Processing software used to derive the tomogram - reconstruction_software- str- Name of software used for reconstruction - is_portal_standard- bool- whether this tomogram adheres to portal standards - is_author_submitted- bool- Whether this tomogram was submitted by the author of the dataset it belongs to. - is_visualization_default- bool- Data curator’s subjective choice of default tomogram to display in visualization for a run - s3_omezarr_dir- str- S3 path to this tomogram in multiscale OME-Zarr format - https_omezarr_dir- str- HTTPS path to this tomogram in multiscale OME-Zarr format - file_size_omezarr- float- Size of the tomogram in OME-Zarr format in bytes - s3_mrc_file- str- S3 path to this tomogram in MRC format (no scaling) - https_mrc_file- str- HTTPS path to this tomogram in MRC format (no scaling) - file_size_mrc- float- Size of the tomogram in MRC format in bytes - scale_0_dimensions- str- comma separated x,y,z dimensions of the unscaled tomogram - scale_1_dimensions- str- comma separated x,y,z dimensions of the scale1 tomogram - scale_2_dimensions- str- comma separated x,y,z dimensions of the scale2 tomogram - ctf_corrected- bool- Whether this tomogram is CTF corrected - offset_x- int- x offset data relative to the canonical tomogram in pixels - offset_y- int- y offset data relative to the canonical tomogram in pixels - offset_z- int- z offset data relative to the canonical tomogram in pixels - key_photo_url- str- URL for the key photo - key_photo_thumbnail_url- str- URL for the thumbnail of key photo - neuroglancer_config- str- the compact json of neuroglancer config - publications- str- Comma-separated list of DOIs for publications associated with the tomogram. - related_database_entries- str- If a CryoET tomogram is also deposited into another database, enter the database identifier here (e.g. EMPIAR-11445). Use a comma to separate multiple identifiers. - deposition_date- date- The date a data item was received by the cryoET data portal. - release_date- date- The date a data item was received by the cryoET data portal. - last_modified_date- date- The date a piece of data was last modified on the cryoET data portal. - 
download_all_annotations(dest_path=None, format=None, shape=None)¶
- Download all annotation files for this tomogram - Parameters:
 
 - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> tomograms = Tomogram.find(client, query_filters=[Tomogram.run.name == "TS_026"])- Get all results for this type: - >>> tomograms = Tomogram.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an Tomogram by ID: - >>> tomogram = Tomogram.get_by_id(client, 10000) >>> print(tomogram.name)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
download_all_annotations(dest_path=
- class cryoet_data_portal.TomogramAuthor¶
- Author of a tomogram Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - tomogram- Tomogram- The tomogram this tomogram author is a part of - tomogram_id- int- None - author_list_order- int- The order in which the author appears in the publication - orcid- str- A unique, persistent identifier for researchers, provided by ORCID. - kaggle_id- str- A unique, persistent identifier for kaggle users at kaggle.com. - name- str- Full name of an author (e.g. Jane Doe). - email- str- Email address for this author - affiliation_name- str- Name of the institutions an author is affiliated with. Comma separated - affiliation_address- str- Address of the institution an author is affiliated with. - affiliation_identifier- str- A unique identifier assigned to the affiliated institution by The Research Organization Registry (ROR). - corresponding_author_status- bool- Indicates whether an author is the corresponding author - primary_author_status- bool- Indicates whether an author is the main person creating the tomogram - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - Get all results for this type: - >>> tomogram_authors = TomogramAuthor.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an TomogramAuthor by ID: - >>> tomogram_author = TomogramAuthor.get_by_id(client, 10000) >>> print(tomogram_author.name)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=
- class cryoet_data_portal.TomogramVoxelSpacing¶
- Voxel spacings for a run Attributes:- Name - Type - Description - id- int- Numeric identifier (May change!) - annotation_files- List[AnnotationFile]- The annotation files of this tomogram voxel spacing - run- Run- The run this tomogram voxel spacing is a part of - run_id- int- None - tomograms- List[Tomogram]- The tomograms of this tomogram voxel spacing - voxel_spacing- float- The voxel spacing for the tomograms in this set in angstroms - s3_prefix- str- The S3 public bucket path where this tomogram voxel spacing is contained - https_prefix- str- The HTTPS directory path where this tomogram voxel spacing is contained - 
classmethod find(client, query_filters=None)¶
- Find objects based on a set of search filters. - Search filters are combined with and so all results will match all filters. - Expressions with python-native operators ( - ==,- !=,- >,- >=,- <,- <=) must be in the format:- ModelSubclass.field- {operator}- {value}- Example: - Tomogram.voxel_spacing.run.name == "RUN1"
 - Expressions with method operators ( - like,- ilike,- _in) must be in the format:- ModelSubclass.field.{operator}({value})- Examples: - Tomogram.voxel_spacing.run.name.like("%RUN1%")
- Tomogram.voxel_spacing.run.name._in(["RUN1", "RUN2"])
 - Supported operators are: - ==,- !=,- >,- >=,- <,- <=,- like,- ilike,- _in- likeis a partial match, with the % character being a wildcard
- ilikeis similar to- likebut case-insensitive
- _inaccepts a list of values that are acceptable matches.
 - Values may be strings or numbers depending on the type of the field being matched, and _in supports a list of values of the field’s corresponding type. - ModelSubclass.fieldmay be an arbitrarily nested path to any field on any related model, such as:- ModelSubclass.related_class_field.related_field.second_related_class_field.second_field- Parameters:
- Yields:
- Matching Model objects. 
 - Examples - >>> tomogram_voxel_spacings = TomogramVoxelSpacing.find(client, query_filters=[TomogramVoxelSpacing.run.name == "TS_026"])- Get all results for this type: - >>> tomogram_voxel_spacings = TomogramVoxelSpacing.find(client)
 - classmethod get_by_id(client, id)¶
- Find objects by primary key - Parameters:
- Returns:
- A matching Model object if found, None otherwise. 
 - Examples - Get an TomogramVoxelSpacing by ID: - >>> tomogram_voxel_spacing = TomogramVoxelSpacing.get_by_id(client, 10000) >>> print(tomogram_voxel_spacing.id)
 - to_dict()¶
- Return a dictionary representation of this object’s attributes 
 
- 
classmethod find(client, query_filters=