AnnotationEngine¶

The AnnotationClient is used to interact with the AnnotationEngine service to create tables from existing schema, upload new data, and download existing annotations. Note that annotations in the AnnotationEngine are not linked to any particular segmentation, and thus do not include any root ids. An annotation client is accessed with client.annotation.

Getting existing tables¶

A list of the existing tables for the dataset can be found at with get_tables.

all_tables = client.annotation.get_tables()
all_tables[0]

Each table has three main properties that can be useful to know:

table_name : The table name, used to refer to it when uploading or downloading annotations. This is also passed through to the table in the Materialized database.
schema_name : The name of the table’s schema from EMAnnotationSchemas (see below).
max_annotation_id : An upper limit on the number of annotations already contained in the table.

Downloading annotations¶

You can download the JSON representation of a data point through the get_annotation method. This can be useful if you need to look up information on unmaterialized data, or to see what a properly templated annotation looks like.

table_name = all_tables[0]['table_name']      # 'ais_analysis_soma'
annotation_id = 100
client.annotation.get_annotation(annotation_id=annotation_id, table_name=table_name)

Create a new table¶

One can create a new table with a specified schema with the create_table method:

client.annotation.create_table(table_name='test_table',
                               schema_name='microns_func_coreg')

New data can be generated as a dict or list of dicts following the schema and uploaded with post_annotation. For example, a microns_func_coreg point needs to have: * type set to microns_func_coreg * pt set to a dict with position as a key and the xyz location as a value. * func_id set to an integer.

The following could would create a new annotation and then upload it to the service. Note that you get back the annotation id(s) of what you uploaded.

new_data = {'type': 'microns_func_coreg',
            'pt': {'position': [1,2,3]},
            'func_id': 0}
client.annotation.post_annotation(table_name='test_table', data=[new_data])