Validator

Connection

Bases: Base

A single connection between two cells.

Parameters:

Name	Type	Description	Default
pre		The pre-synaptic cell	required
post		The post-synaptic cell	required
weight		The weight of the connection, which could be the number of synapses or a normalized value.	required

Source code in cect/validation/Validator.py

@modelspec.define
class Connection(Base):
    """
    A single connection between two cells.

    Args:
        pre: The pre-synaptic cell
        post: The post-synaptic cell
        weight: The weight of the connection, which could be the number of synapses or a normalized value.
    """

    pre: str = field(validator=instance_of(str))
    post: str = field(validator=instance_of(str))
    weight: float = field(validator=instance_of(float))

ConnectionList

Bases: Base

A model of a list of connections of a specific synapse type.

Parameters:

Name	Type	Description	Default
synapse		The type of synapse	required
total_nonzero_conns		Total nonzero connections	required
total_weight		Total weight of connections (optional)	required
num_cells		Number of cells (optional)	required
view		An optional string specifying a ConnectomeView to use, e.g. Neurons, Pharynx, etc. Numbers of conns will be checked inside that view	required
comment		A comment about how the data was found, e.g. taken from a spreadsheet	required
connections		The list of connections of this type	required

Source code in cect/validation/Validator.py

@modelspec.define
class ConnectionList(Base):
    """
    A model of a list of connections of a specific synapse type.

    Args:
        synapse: The type of synapse
        total_nonzero_conns: Total nonzero connections
        total_weight: Total weight of connections (optional)
        num_cells: Number of cells (optional)
        view: An optional string specifying a ConnectomeView to use, e.g. Neurons, Pharynx, etc. Numbers of conns will be checked inside that view
        comment: A comment about how the data was found, e.g. taken from a spreadsheet
        connections: The list of connections of this type
    """

    synapse: str = field(validator=instance_of(str))
    total_nonzero_conns: int = field(validator=instance_of(int))
    total_weight: float = field(validator=instance_of(float))
    num_cells: int = field(validator=instance_of(int))
    view: str = field(validator=instance_of(str))
    comment: str = field(validator=instance_of(str))
    connections: List[Connection] = field(factory=list)

ReaderExpectedData

Bases: Base

A model of expected data for a specific reader.

Parameters:

Name	Type	Description	Default
reader		The name of the reader	required
connection_lists		The list of connection lists for this reader	required

Source code in cect/validation/Validator.py

@modelspec.define
class ReaderExpectedData(Base):
    """
    A model of expected data for a specific reader.

    Args:
        reader: The name of the reader
        connection_lists: The list of connection lists for this reader
    """

    reader: str = field(validator=instance_of(str))
    connection_lists: List[ConnectionList] = field(factory=list)

    def get_connection_list_by_synapse(self, synapse_type):
        """
        Get the connection list for a specific synapse type.

        Args:
            synapse_type: The type of synapse to get the connection list for


        Returns:            The connection list for the specified synapse type, or None if not found.
        """
        for conn_list in self.connection_lists:
            if (
                isinstance(conn_list, dict)
                and "synapse" in conn_list
                and conn_list["synapse"] == synapse_type
            ):
                return conn_list
            if conn_list.synapse == synapse_type:
                return conn_list
        return None

get_connection_list_by_synapse(synapse_type)

Get the connection list for a specific synapse type.

Parameters:

Name	Type	Description	Default
synapse_type		The type of synapse to get the connection list for	required

Returns: The connection list for the specified synapse type, or None if not found.

Source code in cect/validation/Validator.py

def get_connection_list_by_synapse(self, synapse_type):
    """
    Get the connection list for a specific synapse type.

    Args:
        synapse_type: The type of synapse to get the connection list for


    Returns:            The connection list for the specified synapse type, or None if not found.
    """
    for conn_list in self.connection_lists:
        if (
            isinstance(conn_list, dict)
            and "synapse" in conn_list
            and conn_list["synapse"] == synapse_type
        ):
            return conn_list
        if conn_list.synapse == synapse_type:
            return conn_list
    return None

generate_reader_exp_data_obj(reader_name, source_files, additional_comment='')

A function to generate a ReaderExpectedData object which will list expected data as visually extracted from a source file, e.g. an Excel spreadsheet.

Parameters:

Name	Type	Description	Default
reader_name		The name of the reader	required
source_files		A dict of syn types vs paths to the source files	required

Returns:

Type	Description
	A ReaderExpectedData object with the expected data for the reader.

Source code in cect/validation/Validator.py

def generate_reader_exp_data_obj(reader_name, source_files, additional_comment=""):
    """
    A function to generate a ReaderExpectedData object which will list expected data as visually extracted from a source file, e.g. an Excel spreadsheet.

    Args:
        reader_name: The name of the reader
        source_files: A dict of syn types vs paths to the source files

    Returns:
        A ReaderExpectedData object with the expected data for the reader.
    """
    # This is a placeholder implementation. In a real implementation, you would read the source files and extract the expected data.
    expected_data = ReaderExpectedData(reader=reader_name)

    for syn_class, source_file in source_files.items():
        chem_conns = ConnectionList(
            synapse=syn_class,
            comment=f"Data visually read in from {source_file}. {additional_comment}",
            total_nonzero_conns=-1,
        )

    expected_data.connection_lists.append(chem_conns)

    return expected_data