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UpdatedSpreadsheetDataReader

UpdatedSpreadsheetDataReader

Bases: ConnectomeDataset

Source code in cect/UpdatedSpreadsheetDataReader.py 
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class UpdatedSpreadsheetDataReader(ConnectomeDataset):
    def __init__(self):
        ConnectomeDataset.__init__(self)

        cells, neuron_conns = self.read_data()
        for conn in neuron_conns:
            self.add_connection_info(conn)

        neurons2muscles, muscles, muscle_conns = self.read_muscle_data()
        for conn in muscle_conns:
            self.add_connection_info(conn)

    def read_data(self, include_nonconnected_cells=False):
        """
        Returns:
            Tuple[list, list]: List of cells (str) and list of connections (``ConnectionInfo``) which have been read in
        """

        conns = []
        cells = []

        with open(filename, "r") as f:
            reader = csv.DictReader(f)
            print_("Opened file: " + filename)

            # known_nonconnected_cells = ["CANL", "CANR"]

            for row in reader:
                pre, post, num, syntype, synclass = parse_row(row)

                if not _is_neuron(pre) or not _is_neuron(post):
                    continue  # pre or post is not a neuron

                pre = _remove_leading_index_zero(pre)
                post = _remove_leading_index_zero(post)

                conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
                # print ConnectionInfo(pre, post, num, syntype, synclass)
                if pre not in cells:
                    cells.append(pre)
                if post not in cells:
                    cells.append(post)

            if include_nonconnected_cells:
                from cect.Cells import PREFERRED_HERM_NEURON_NAMES

                for c in PREFERRED_HERM_NEURON_NAMES:
                    if c not in cells:
                        cells.append(c)

        return cells, conns

    def read_muscle_data(self):
        """
        Returns:
            neurons (:obj:`list` of :obj:`str`): List of motor neurons. Each neuron has at least one connection with a post-synaptic muscle cell.
            muscles (:obj:`list` of :obj:`str`): List of muscle cells.
            conns (:obj:`list` of :obj:`ConnectionInfo`): List of neuron-muscle connections.
        """

        neurons = []
        muscles = []
        conns = []

        with open(filename, "r") as f:
            reader = csv.DictReader(f)
            print_("Opened file: " + filename)

            for row in reader:
                pre, post, num, syntype, synclass = parse_row(row)

                if not (
                    _is_neuron(pre) or _is_body_wall_muscle(pre)
                ) or not _is_body_wall_muscle(post):
                    continue

                if _is_neuron(pre):
                    pre = _remove_leading_index_zero(pre)
                else:
                    pre = _get_old_muscle_name(pre)
                post = _get_old_muscle_name(post)

                conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
                if _is_neuron(pre) and pre not in neurons:
                    neurons.append(pre)
                elif _is_body_wall_muscle(pre) and pre not in muscles:
                    muscles.append(pre)
                if post not in muscles:
                    muscles.append(post)

        return neurons, muscles, conns

read_data(include_nonconnected_cells=False)

Returns:

Type Description

Tuple[list, list]: List of cells (str) and list of connections (ConnectionInfo) which have been read in
Source code in cect/UpdatedSpreadsheetDataReader.py 
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def read_data(self, include_nonconnected_cells=False):
    """
    Returns:
        Tuple[list, list]: List of cells (str) and list of connections (``ConnectionInfo``) which have been read in
    """

    conns = []
    cells = []

    with open(filename, "r") as f:
        reader = csv.DictReader(f)
        print_("Opened file: " + filename)

        # known_nonconnected_cells = ["CANL", "CANR"]

        for row in reader:
            pre, post, num, syntype, synclass = parse_row(row)

            if not _is_neuron(pre) or not _is_neuron(post):
                continue  # pre or post is not a neuron

            pre = _remove_leading_index_zero(pre)
            post = _remove_leading_index_zero(post)

            conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
            # print ConnectionInfo(pre, post, num, syntype, synclass)
            if pre not in cells:
                cells.append(pre)
            if post not in cells:
                cells.append(post)

        if include_nonconnected_cells:
            from cect.Cells import PREFERRED_HERM_NEURON_NAMES

            for c in PREFERRED_HERM_NEURON_NAMES:
                if c not in cells:
                    cells.append(c)

    return cells, conns

read_muscle_data()

Returns:

Name Type Description
neurons :obj:`list` of :obj:`str`

List of motor neurons. Each neuron has at least one connection with a post-synaptic muscle cell.
muscles :obj:`list` of :obj:`str`

List of muscle cells.
conns :obj:`list` of :obj:`ConnectionInfo`

List of neuron-muscle connections.
Source code in cect/UpdatedSpreadsheetDataReader.py 
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def read_muscle_data(self):
    """
    Returns:
        neurons (:obj:`list` of :obj:`str`): List of motor neurons. Each neuron has at least one connection with a post-synaptic muscle cell.
        muscles (:obj:`list` of :obj:`str`): List of muscle cells.
        conns (:obj:`list` of :obj:`ConnectionInfo`): List of neuron-muscle connections.
    """

    neurons = []
    muscles = []
    conns = []

    with open(filename, "r") as f:
        reader = csv.DictReader(f)
        print_("Opened file: " + filename)

        for row in reader:
            pre, post, num, syntype, synclass = parse_row(row)

            if not (
                _is_neuron(pre) or _is_body_wall_muscle(pre)
            ) or not _is_body_wall_muscle(post):
                continue

            if _is_neuron(pre):
                pre = _remove_leading_index_zero(pre)
            else:
                pre = _get_old_muscle_name(pre)
            post = _get_old_muscle_name(post)

            conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
            if _is_neuron(pre) and pre not in neurons:
                neurons.append(pre)
            elif _is_body_wall_muscle(pre) and pre not in muscles:
                muscles.append(pre)
            if post not in muscles:
                muscles.append(post)

    return neurons, muscles, conns