CellInfo

cds = cds_src.get_connectome_view(view) module-attribute

for cell in ['I3']: print(cds.nodes) print(cds.connections.keys()) index = cds.nodes.index(cell) print('Conns from %s (index: %i): %s'%(cell,index,cds.get_connections_from(cell, syntype))) matrix = cds.connections[syntype] print(matrix[index]) print('Conns to %s (index: %i): %s'%(cell,index,cds.get_connections_to(cell, syntype))) print(matrix.T[index])

cds_src = get_instance() module-attribute

from cect.RipollSanchezMidRangeReader import get_instance cds_src = get_instance()

generate_cell_info_pages(connectomes)

Generates the individual cell pages

Parameters:

Name	Type	Description	Default
connectomes	list	The list of connectome readers to use	required

Source code in cect/CellInfo.py

def generate_cell_info_pages(connectomes):
    """Generates the individual cell pages

    Args:
        connectomes (list): The list of connectome readers to use
    """
    cell_data = load_individual_neuron_info()
    cell_classification = get_primary_classification()

    all_cell_info = [["Cell name", "Type", "Name details", "Lineage", "Classification"]]

    for cell in ALL_PREFERRED_CELL_NAMES:
        print_("Generating individual cell page for: %s" % cell)

        cell_info = '---\ntitle: "Cell: %s"\n---\n\n' % cell

        cell_ref = (
            cell
            if not ((cell.startswith("CA") or cell.startswith("CP")) and cell[2] == "0")
            else "%s%s" % (cell[:2], cell[-1])
        )  # CA04 -> CA4 etc.

        # TODO: investigate  DX1, DX2, DX3, EF1, EF2, EF3
        if is_any_neuron(cell) and "DX" not in cell and "EF" not in cell:
            acronym = cell_data[cell_ref][0]
            lineage = cell_data[cell_ref][1]
            desc = cell_data[cell_ref][2]
            from_ = 0
            for c in cell:
                # print('Replacing %s (from %s) in %s'%(c,from_,acronym))
                if c in acronym:
                    ii = acronym.index(c, from_)
                    acronym = "%s<u>%s</u>%s" % (
                        acronym[:ii],
                        acronym[ii],
                        acronym[ii + 1 :],
                    )
                    from_ = ii + 1

            cell_info += '!!! question "**%s: %s**"\n\n' % (
                cell,
                acronym,
            )
            cell_info += (
                '    <p class="subtext"><b>%s</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;'
                % (desc)
            )
            cell_info += "Lineage: <b>%s</b></p>\n\n" % (lineage)

            all_cell_info.append(
                [
                    cell,
                    get_cell_notes(cell),
                    cell_data[cell_ref][0],
                    lineage,
                    desc,
                ]
            )

        else:
            cell_info += '!!! question "**%s: %s**"\n\n' % (cell, get_cell_notes(cell))
            cc = cell_classification[cell]
            all_cell_info.append(
                [
                    cell,
                    get_cell_notes(cell),
                    cell_data[cell_ref][0]
                    if cell_ref in cell_data
                    else "- To be added... - ",
                    get_cell_notes(cell),
                    "- To be added... - ",
                    cc[0].upper() + cc[1:],
                ]
            )

        cell_info += (
            '    <p class="subtext"><a href="../Cook_2019">Cook 2019</a> classification: <b>%s</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;'
            % (get_cell_notes(cell))
        )
        cc = cell_classification[cell]
        color = get_standard_color(cell)

        cell_info += (
            'All cells of type: <a href="../Cells/#%s"><b><span style="color:%s">%s</span></b></a></p>\n\n'
            % (
                cc.lower().replace(" ", "-").replace("(", "").replace(")", ""),
                color,
                cc[0].upper() + cc[1:],
            )
        )

        cell_info += "    %s " % (
            get_cell_wormatlas_link(cell, text="Info on WormAtlas", button=True)
        )

        cell_info += "%s\n\n" % get_cell_osbv1_link(
            cell, text="View in 3D on Open Source Brain", button=True
        )

        all_synclasses = [
            GENERIC_CHEM_SYN,
            GENERIC_ELEC_SYN,
        ]  # ensure these 2 are at the start...

        for cds_name in connectomes:
            cds = connectomes[cds_name]
            for synclass in cds.connections:
                if synclass not in all_synclasses:
                    all_synclasses.append(synclass)

        cell_link = get_cell_internal_link(
            cell, html=True, use_color=True, individual_cell_page=True
        )

        reference_cs = "Cook2019Male" if is_male_specific_cell(cell) else "Cook2019Herm"
        # reference_cs = "White_whole"

        reference_gj = reference_cs
        reference_mono = "Bentley2016_MA"
        reference_pep = "RipollSanchezShortRange"
        reference_func = "Randi2023"
        reference_cont = "Brittin2021"
        max_conn_cells = 5
        conns_from_cs = "???"
        conns_to_cs = "???"
        conns_from_mono = "???"
        conns_to_mono = "???"
        conns_from_pep = "???"
        conns_to_pep = "???"
        conns_from_func = "???"
        conns_to_func = "???"
        conns_cont = "???"
        conns_gj = "???"

        tables_md = ""

        for synclass in all_synclasses:
            synclass_info = synclass
            if synclass == GENERIC_CHEM_SYN:
                synclass_info = "Chemical synaptic"
            if synclass == GENERIC_ELEC_SYN:
                synclass_info = "Electrical synaptic"

            header = "### %s connections %s %s  { data-search-exclude }\n\n" % (
                synclass_info,
                "to" if not synclass == GENERIC_ELEC_SYN else "from/to",
                cell_link,
            )

            w = {}
            for cds_name in connectomes:
                r_name = get_dataset_link(cds_name)
                w[r_name] = {}
                cds = connectomes[cds_name]

                connection_symbol = "↔" if synclass == GENERIC_ELEC_SYN else "→"

                if synclass in cds.connections:
                    conns = cds.get_connections_to(cell, synclass)

                    if cds_name == reference_cs and synclass == GENERIC_CHEM_SYN:
                        conns_to_cs = _get_top_list(conns, max_conn_cells)
                    if cds_name == reference_gj and synclass == GENERIC_ELEC_SYN:
                        conns_gj = _get_top_list(conns, max_conn_cells)
                    if cds_name == reference_mono:
                        conns_to_mono = _get_top_list(conns, max_conn_cells)
                    if cds_name == reference_pep:
                        conns_to_pep = _get_top_list(conns, max_conn_cells)
                    if cds_name == reference_func:
                        conns_to_func = _get_top_list(conns, max_conn_cells)
                    if cds_name == reference_cont:
                        conns_cont = _get_top_list(conns, max_conn_cells)

                    for c in conns:
                        cc = get_cell_internal_link(
                            c, html=True, use_color=True, individual_cell_page=True
                        )
                        template = (
                            "<b><i>%s%s%s</i></b>"
                            if cell == c
                            else (
                                "<b>%s%s%s</b>"
                                if are_bilateral_pair(cell, c)
                                else "%s%s%s"
                            )
                        )
                        w[r_name][template % (cc, connection_symbol, cell_link)] = (
                            conns[c]
                        )

            w_md = get_weight_table_markdown(w)

            if "No connections" not in w_md:
                tables_md += "%s\n%s\n\n" % (header, w_md)

            if not synclass == GENERIC_ELEC_SYN:
                header = "### %s connections %s %s  { data-search-exclude }\n\n" % (
                    synclass_info,
                    "from",
                    cell_link,
                )

                w = {}
                for cds_name in connectomes:
                    r_name = get_dataset_link(cds_name)
                    w[r_name] = {}

                    cds = connectomes[cds_name]
                    if synclass in cds.connections:
                        conns = cds.get_connections_from(cell, synclass)

                        if cds_name == reference_cs and synclass == GENERIC_CHEM_SYN:
                            conns_from_cs = _get_top_list(conns, max_conn_cells)
                        if cds_name == reference_mono:
                            conns_from_mono = _get_top_list(conns, max_conn_cells)
                        if cds_name == reference_pep:
                            conns_from_pep = _get_top_list(conns, max_conn_cells)
                        if cds_name == reference_func:
                            conns_from_func = _get_top_list(conns, max_conn_cells)
                        if cds_name == reference_cont:
                            pass  # same as to...

                        for c in conns:
                            cc = get_cell_internal_link(
                                c, html=True, use_color=True, individual_cell_page=True
                            )
                            template = (
                                "<b><i>%s→%s</i></b>"
                                if cell == c
                                else (
                                    "<b>%s→%s</b>"
                                    if are_bilateral_pair(cell, c)
                                    else "%s→%s"
                                )
                            )
                            w[r_name][template % (cell_link, cc)] = conns[c]

                w_md = get_weight_table_markdown(w)

                if "No connections" not in w_md:
                    tables_md += "%s\n%s\n\n" % (header, w_md)

        cell_info += f"""

### Summary of connections

<p class="subtext">Top {max_conn_cells} connections of specified types to/from this cell (based on {get_dataset_link(reference_cs)}, {get_dataset_link(reference_mono)}, {get_dataset_link(reference_pep)}, {get_dataset_link(reference_func)} & {get_dataset_link(reference_cont)})</p>

<table style="width:700px">
<tr>
    <td><b><a href="#electrical-synaptic-connections-fromto-{cell.lower()}" title="Electrical connectivity from {reference_cs}">Electrical</a></b></td> <td colspan="5" align="middle">{conns_gj}</td> 
</tr><tr>
    <td>&nbsp;</td> <td colspan="5" align="middle">\u2195</td> 
</tr><tr>
    <td><b><a href="#chemical-synaptic-connections-to-{cell.lower()}" title="Chemical synaptic connectivity from {reference_cs}">Chemical</a></b></td>
    <td style="width:40%">{conns_to_cs}</td>
    <td style="width:5%" style="vertical-align:bottom;text-align:center;">\u2198</td>
    <td rowspan="5" style="vertical-align:middle;text-align:center;"><b>{cell_link}</b></td>
    <td style="width:5%" style="vertical-align:bottom;text-align:center;">\u2197</td>
    <td style="width:40%">{conns_from_cs}</td>
</tr><tr>
    <td><b><a href="#monoaminergic-connections-to-{cell.lower()}" title="Monoaminergic connectivity from {reference_mono}">Monoaminergic</a></b></td><td>{conns_to_mono}</td><td align="middle">→</td><td align="middle">→</td><td>{conns_from_mono}</td>
</tr><tr>
    <td><b><a href="#peptidergic-connections-to-{cell.lower()}" title="Peptidergic connectivity from {reference_pep}">Peptidergic</a></b></td>  <td>{conns_to_pep}</td><td align="middle">→</td><td align="middle">→</td><td>{conns_from_pep}</td>
</tr><tr>
    <td><b><a href="#functional-connections-to-{cell.lower()}" title="Functional connectivity from {reference_func}">Functional</a></b></td>   <td>{conns_to_func}</td><td align="middle">→</td><td align="middle">→</td><td>{conns_from_func}</td>
</tr><tr>
    <td>&nbsp;</td> <td colspan="5" align="middle">\u2195</td> 
</tr><tr>
    <td><b><a href="#membrane-contacts-to-{cell.lower()}" title="Contactome from {reference_cont}">Contactomic</a></b></td>  <td colspan="5" align="middle">{conns_cont}</td>
</tr>
</table>

"""
        cell_info += tables_md

        cell_filename = "docs/%s.md" % cell
        with open(cell_filename, "w") as cell_file:
            print_(f"Writing info on cell {cell} to {cell_filename}")
            cell_file.write(cell_info)

    cell_info_filename = "cect/data/all_cell_info.csv"
    with open(cell_info_filename, "w") as csv_file:
        print_(f"Writing info on all cells to {cell_info_filename}")
        csv_writer = csv.writer(csv_file, delimiter=",", quotechar='"')
        for line in all_cell_info:
            csv_writer.writerow(line)

get_dataset_link(dataset)

Helper method to generate an internal link to the page for a dataset

Parameters:

Name	Type	Description	Default
dataset	str	The dataset to link to	required

Returns:

Name	Type	Description
str		A hyperlink to the dataset

Source code in cect/CellInfo.py

def get_dataset_link(dataset):
    """Helper method to generate an internal link to the page for a dataset

    Args:
        dataset (str): The dataset to link to

    Returns:
        str: A hyperlink to the dataset
    """
    # return dataset+'--'
    dataset_text = dataset.replace("Herm", " Herm").replace("Male", " Male")
    return f'<a href="../{dataset}_data">{dataset_text}</a>'