import {Plot} from "@mkfreeman/plot-tooltip"
import {map} from "@martien/ramda"

papers_r = FileAttachment("../data/all_papers.json").json()
n_columns = Object.entries(papers_r["doi"]).length
index_array = Array.from({length: n_columns}, (_, i) => i)
papers = map(i => map(x => x[i], papers_r), index_array)

my_papers = papers.filter(function(p) {
    return p.authors.map(a => a.full_name).includes("Roberto Menichetti")
})

  import {Plot as Plot} from "@mkfreeman/plot-tooltip"

  import {map as map} from "@martien/ramda"

papers_r = Object {doi: Object, title: Object, publication_date: Object, authors: Object, citation_count: Object, bib_entry: Object, abstract: Object, tldr: Object, year: Object, embedding: Object, journal.name: Object, journal.url: Object, journal.issue: Object, journal.abbreviation: Object, journal.pages: Object, journal.volume: Object, open_access.is_open_access: Object, open_access.open_access_status: Object, open_access.landing_page_url: Object, open_access.pdf_url: Object}

n_columns = 79

index_array = Array(79) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, …]

papers = Array(79) [Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, …]

my_papers = Array(6) [Object, Object, Object, Object, Object, Object]

Roberto Menichetti

Group publications

Inputs.table(my_papers, {
    columns: [
    "doi",
    "title",
    "journal.name",
    "journal.volume",
    "journal.issue",
    "journal.pages",
    "year",
    "embedding.topic_name"
  ],
  header: {
    "journal.name": "journal",
    "journal.volume": "volume",
    "journal.issue": "issue",
    "journal.pages": "pages",
    "embedding.topic_name": "topic",
  },
  format: {
    doi: doi => htl.html`<a href=https://doi.org/${doi} target=_blank>${doi}</a>`,
    title: title => htl.html`${title}`,
    "journal.volume": volume => htl.html`<b>${volume}</b>`,
    year: year => htl.html`${year}`,
  },
  width: {
    "title": 10
  },
  layout: "auto",
})

	doi	title	journal	volume	issue	pages	year	topic
	10.1038/s41597-020-0391-0	Molecular dynamics trajectories for 630 coarse-grained drug-membrane permeations	Scientific Data	7	1		2020
	10.1103/PhysRevE.100.033302	Controlled exploration of chemical space by machine learning of coarse-grained representations	Physical Review E	100	3		2019
	10.1080/00268976.2019.1601787	Revisiting the Meyer-Overton rule for drug-membrane permeabilities	Molecular Physics	117	20	2900-2909	2019
	10.1021/acscentsci.8b00718	Drug–Membrane Permeability across Chemical Space	ACS Central Science	5	2	290-298	2019
	10.1063/1.4987012	<i>In silico</i> screening of drug-membrane thermodynamics reveals linear relations between bulk partitioning and the potential of mean force	The Journal of Chemical Physics	147	12		2017
	10.1016/j.bbrc.2017.08.095	Efficient potential of mean force calculation from multiscale simulations: Solute insertion in a lipid membrane	Biochemical and Biophysical Research Communications	498	2	282-287	2017

Group collaborators

collaborators = Array.from(
    new Set(
        my_papers.flatMap(p => p.authors)
        .filter(function(a) {
            return a.full_name != "Roberto Menichetti"
            }
        )
    )
)

list_of_collaborators = (
    Array.from(d3.group(collaborators, a => a.full_name).keys())
)
dict_of_collaborators = (
    collaborators.reduce(
        (acc, x) => (
            {...acc, [x.full_name]:
                {
                    "given": x.given,
                    "family": x.family,
                    "affiliation_city": x.affiliation.city,
                    "affiliation_name": x.affiliation.name,
                    "affiliation_country": x.affiliation.country,
                    "orcid": x.orcid,
                }
            }
        ),
        {}
    )
)

Inputs.table(
    list_of_collaborators.map(c => dict_of_collaborators[c]),
    {
        columns: [
            "given",
            "family",
            "orcid",
            "affiliation_country",
            "affiliation_city",
            "affiliation_name",
        ],
        header: {
            "affiliation_country": "country",
            "affiliation_city": "city",
            "affiliation_name": "affiliation",
        },
        multiple: false,
        sort: "family",
        layout: "fixed",
        format: {
            orcid: orcid =>
            htl.html`<a href=https://orcid.org/${orcid} target=_blank>${orcid}</a>`
        },
    }
)

collaborators = Array(14) [Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object, Object]

list_of_collaborators = Array(5) ["Christian Hoffmann", "Alessia Centi", "Tristan Bereau", "Kiran Kanekal", "Kurt Kremer"]

dict_of_collaborators = Object {Christian Hoffmann: Object, Alessia Centi: Object, Tristan Bereau: Object, Kiran Kanekal: Object, Kurt Kremer: Object}

	given	▴family	orcid	country	city	affiliation
	Tristan	Bereau	0000-0001-9945-1271	DE	Heidelberg	Heidelberg University
	Alessia	Centi	0000-0002-1883-9416
	Christian	Hoffmann
	Kiran	Kanekal	0000-0003-1785-5219
	Kurt	Kremer	0000-0003-1842-9369