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* The columns the *file itself* carries about its own units, as annotations.
*
* Every container this viewer opens keeps a table beside its pixels, and those
* tables have always held more than the arithmetic the reader needs. A
* metacool's `/genomes` carries completeness and contamination beside the bin
* counts, its `/contigs` carries whatever the assembler and the annotator
* joined on — MGE calls, coverage, a bin id — and every cooler's `/bins`
* carries at least the balancing weight. All of it is already indexed against
* the axis of the map, needs no naming convention to be matched (§8.2 has
* nothing to check: these *are* the map's own names), and until now could only
* be read as a table, one row at a time, in a view that is not the picture.
*
* So it is drawn beside the map, as lanes, through the same {@link
* AnnotationStore} a dropped bigWig goes through — see `ui/MetadataCard.ts` for
* why that is the whole design and not an implementation note.
*
* Two things here are not in any other annotation module, and both come from
* the same fact: **a metadata lane is indexed by the map's own cells, not by
* base pairs.**
*
* - The **level rule** ({@link showsAtLevel}). A genome × genome overview has
* one cell per MAG, and a bin weight has nothing to say about a cell that is
* forty thousand bins; a bin × bin view has one cell per bin, and a genome's
* contamination has something exact to say about every one of them. So a
* column is offered where its own table is *no finer* than the axis, and
* nowhere else. Broadcasting a genome's value down onto its bins invents
* nothing; rolling a bin column up into a genome would have to pick a
* statistic nobody asked for, and would then be drawn as though the file had
* said it.
* - The **cell resolution** ({@link cellsOf}). The reader already sends, with
* every block, the runs its axes are made of and the bin each run's sequence
* starts at, which is exactly enough to say which row of which table each
* cell of the picture is — pooled or dense, on any of the three levels, and
* without going back through a name that a metagenome is entitled to use
* twice.
*
* Everything in this module is free of DOM and of the reader, so the mapping
* can be tested as arithmetic (`test/unit/metadata.test.ts`).
*/
import type { AnnotationEntry, AnnotationKind, MetadataSource } from './types'
import { defaultStyle, placementOn } from './types'
import type { Column, Table } from '../types'
// ---------------------------------------------------------------------------
// What a metadata column is
// ---------------------------------------------------------------------------
/**
* The three tables a value can be keyed on, coarsest first.
*
* The same three the file writes and the same three the tables view lists.
* `bins` is the one no view shows as a table — `/bins` is deliberately never
* read whole at open time (§3.3) — and it is also the only one every container
* has, because a balanced cooler keeps its weights there.
*/
export type MetaTable = 'genomes' | 'contigs' | 'bins'
/** Which of the two pictures a column is drawn as. */
export type MetaKind = 'quantitative' | 'qualitative'
/** What one cell of the axis is; `MatrixResult.level` under another name. */
export type MetaLevel = 'bin' | 'contig' | 'genome'
/** The axis unit each table describes, for the level rule. */
const TABLE_LEVEL: Record<MetaTable, MetaLevel> = {
genomes: 'genome',
contigs: 'contig',
bins: 'bin',
}
/** Coarsest first — the order the drop-down groups its options in. */
export const META_TABLES: readonly MetaTable[] = ['genomes', 'contigs', 'bins']
/**
* Whether a column of one table can be drawn against an axis of one level.
*
* The level rule, and the whole of it: **a table may be no finer than the
* axis**. A genome's value is exact on every contig and every bin inside it, so
* a genomes column draws on all three; a bin's value is a statement about one
* bin and nothing else, so a bins column draws only where a cell is a bin.
*
* The alternative — aggregating upward, a mean weight per contig — is not
* offered anywhere in this module, and the reason is that it would be drawn in
* exactly the same ink as a value the file wrote. A reader cannot see the
* difference between "the file says 0.83" and "we averaged 4,000 numbers the
* file wrote and got 0.83", and a lane that does not distinguish them will
* eventually be read as though it were the first.
*/
export function showsAtLevel(table: MetaTable, level: MetaLevel): boolean {
const ORDER: Record<MetaLevel, number> = { genome: 2, contig: 1, bin: 0 }
return ORDER[TABLE_LEVEL[table]] >= ORDER[level]
}
/** One column the file carries, as the drop-down offers it. */
export interface MetaColumn {
table: MetaTable
column: string
kind: MetaKind
/** Rows in the source table; the number of units the column describes. */
rows: number
/**
* The distinct values, where the column is qualitative and has been read.
*
* Carried on the descriptor so the card can say "6 categories" before
* anything is drawn, and so the palette a lane uses is decided once, over the
* whole column, rather than per block — a category that changes colour when
* you zoom is a legend that lies.
*/
levels?: readonly string[]
}
/**
* A whole column, decoded, indexed by row of its own table.
*
* `from` is the first row the arrays cover, which is `0` for the two tables
* that are read whole and the block's first bin for a `/bins` column, where
* reading the whole thing would mean reading a column the same length as the
* file's bin count for a picture of four thousand cells.
*/
export type MetaValues =
| { kind: 'quantitative'; from: number; values: Float64Array }
| { kind: 'qualitative'; from: number; codes: Int32Array; levels: readonly string[] }
/**
* What one axis of one block resolves to, per cell.
*
* The output of this module and the input to `render/meta.ts`. `NaN` and `-1`
* both mean *this cell has no value*, which is a different thing from zero and
* from the first category — a cell of `__unbinned__`, a run the axis carries
* that the table does not, a bin past the end of its contig.
*/
export type MetaCells =
| {
kind: 'quantitative'
values: Float64Array
/** Over the cells in hand, skipping the gaps; `null` where every cell is one. */
extent: { min: number; max: number } | null
}
| { kind: 'qualitative'; codes: Int32Array; levels: readonly string[] }
// ---------------------------------------------------------------------------
// Discovery
// ---------------------------------------------------------------------------
/**
* The columns that are the table's *skeleton* rather than an annotation of it.
*
* A name is what the axis is already labelled with and a `genome_id` is a join
* key; drawn as a lane, the first is a thousand distinct categories and the
* second is a staircase. Everything else the creator wrote is offered,
* including the ones this app happens to use: a contig's `length` as a barplot
* beside a metagenome is a genuine picture of an assembly, and hiding it
* because the reader also uses it for arithmetic would be an odd rule to have
* to explain.
*
* `/bins` has `chrom`, `start` and `end` cut for the same reason — they are the
* bin's address, and the address is the axis.
*/
const SKELETON: Record<MetaTable, readonly string[]> = {
genomes: ['name'],
contigs: ['name', 'genome_id'],
bins: ['chrom', 'start', 'end'],
}
/**
* Past this many distinct values a numeric column is a measurement rather than
* a set of labels.
*
* Twelve, which is where a discrete palette stops being readable anyway. The
* columns this rescues are the ones a binner writes — a cluster id, a
* `is_circular` flag, a three-way quality call — which are integers in the file
* and categories to every reader of it, and which as a barplot are a picture of
* the numbering rather than of the data.
*/
export const MAX_NUMERIC_CATEGORIES = 12
/**
* How many distinct values it takes for a text column to be an identifier.
*
* A column with a different string on nearly every row is an accession, a path
* or a description; drawn as colours it is confetti with a legend as long as
* the axis. Nine tenths rather than all of them, because a real annotation
* column has ties and a real accession column has a handful of blanks.
*/
const IDENTIFIER_SHARE = 0.9
/**
* What kind of picture a column is, from the values themselves.
*
* Text is qualitative and numbers are quantitative, with the one exception
* {@link MAX_NUMERIC_CATEGORIES} describes. `null` means *not an annotation*:
* an identifier column, or one with nothing in it.
*/
export function classify(column: Column): MetaKind | null {
if (column.length === 0) return null
if (isText(column)) {
const distinct = new Set<string>()
for (const value of column) {
if (value !== '') distinct.add(value)
// An identifier is recognisable long before the whole column has been
// walked, and these columns are as long as the file's contig count.
if (distinct.size > MAX_NUMERIC_CATEGORIES && distinct.size > column.length * IDENTIFIER_SHARE) {
return null
}
}
if (distinct.size === 0) return null
return distinct.size > column.length * IDENTIFIER_SHARE && column.length > 4
? null
: 'qualitative'
}
const distinct = new Set<number>()
let integral = true
let any = false
for (let i = 0; i < column.length; i++) {
const value = Number(column[i])
if (!Number.isFinite(value)) continue
any = true
if (!Number.isInteger(value)) integral = false
if (distinct.size <= MAX_NUMERIC_CATEGORIES) distinct.add(value)
if (!integral && distinct.size > MAX_NUMERIC_CATEGORIES) break
}
if (!any) return null
// Small integers repeated over many rows are labels; anything else is a
// measurement. The row-count clause is what stops a four-genome file's
// completeness column — four distinct floats, or four distinct integers —
// from being read as four categories.
return integral && distinct.size <= MAX_NUMERIC_CATEGORIES && column.length > distinct.size * 2
? 'qualitative'
: 'quantitative'
}
/** `true` when a decoded column holds strings. */
function isText(column: Column): column is string[] {
return Array.isArray(column) && (column.length === 0 || typeof column[0] === 'string')
}
/**
* Every column of one table worth offering, in the file's own column order.
*
* The order matters more than it looks: a creator writes the columns of a
* `/genomes` table in the order they think about them, and a list re-sorted
* alphabetically here would present a reader's own file back to them
* rearranged.
*/
export function discoverTable(table: MetaTable, data: Table | null): MetaColumn[] {
if (data === null) return []
const out: MetaColumn[] = []
for (const name of data.columns) {
if (SKELETON[table].includes(name)) continue
const column = data.data[name]
if (column === undefined) continue
const kind = classify(column)
if (kind === null) continue
out.push({
table,
column: name,
kind,
rows: data.length,
...(kind === 'qualitative' ? { levels: levelsOf(column) } : {}),
})
}
return out
}
/**
* The distinct values of a qualitative column, in the order they first appear.
*
* First-appearance rather than alphabetical, for the same reason the column
* order is kept: a file usually writes its rows in a meaningful order, so the
* first category to appear is the first one the reader will meet. Blanks are
* not a category — an empty cell is a missing value, and giving it a colour and
* a legend entry would draw the gaps as a finding.
*/
export function levelsOf(column: Column): string[] {
const seen = new Set<string>()
const out: string[] = []
for (let i = 0; i < column.length; i++) {
const text = textOf(column[i])
if (text === '' || seen.has(text)) continue
seen.add(text)
out.push(text)
}
return out
}
/** One cell as the category name it stands for. */
function textOf(value: string | number | bigint | undefined): string {
if (value === undefined) return ''
if (typeof value === 'string') return value.trim()
const number = Number(value)
return Number.isFinite(number) ? String(number) : ''
}
/**
* A whole column, as the values a lane reads.
*
* Encoded once, against the levels the descriptor already fixed, so that the
* same category is the same colour in every view and in every export. A value
* the descriptor has never seen — impossible for a column read whole, possible
* for a `/bins` slice read after the descriptor was made — is a gap rather than
* a new level, because a legend that grows as you scroll is not a legend.
*/
export function valuesOf(column: Column, kind: MetaKind, levels: readonly string[], from = 0): MetaValues {
if (kind === 'quantitative') {
const values = new Float64Array(column.length)
for (let i = 0; i < column.length; i++) {
const value = Number(column[i])
values[i] = Number.isFinite(value) ? value : Number.NaN
}
return { kind: 'quantitative', from, values }
}
const index = new Map(levels.map((level, code) => [level, code]))
const codes = new Int32Array(column.length).fill(-1)
for (let i = 0; i < column.length; i++) {
codes[i] = index.get(textOf(column[i])) ?? -1
}
return { kind: 'qualitative', from, codes, levels }
}
// ---------------------------------------------------------------------------
// The block's axis
// ---------------------------------------------------------------------------
/**
* One run of an axis, exactly as the reader reports it (`AxisGroup`).
*
* Structural rather than imported, like `render/locus.ts`'s `AxisRun` and for
* the same reason: this module describes annotations and has no business
* depending on the wire format the reader answers in.
*/
export interface MetaAxisRun {
label: string
start: number
end: number
/** The arithmetic origin of the run's sequence; see `AxisGroup.unitStart`. */
unitStart?: number
/** The absolute bin the run's sequence begins at; bin level only. */
unitBin?: number
}
/**
* Where a cell of the *table* lands on the axis the picture is drawn in.
*
* The identity almost always, and the exception is the turn. A turned map is
* drawn on a lattice of **half-bin** columns (`render/rotate.ts`), so the cell
* a metadata column is indexed by is two of the columns the lane is drawn
* against, and the block may not begin where the rotation's origin does. Two
* numbers carry both facts, and they are applied at the one place a cell
* becomes a position — which is what keeps the renderers free of any knowledge
* that a turn exists.
*/
export interface CellScale {
/** The drawn unit that cell `0` begins at. */
origin: number
/** Drawn units per cell. */
per: number
}
/** A picture whose cells are the axis's own units — every view but the turn. */
export const IDENTITY_CELLS: CellScale = { origin: 0, per: 1 }
/** The drawn unit a cell begins at. */
export function unitOfCell(scale: CellScale, cell: number): number {
return scale.origin + cell * scale.per
}
/** The cell a drawn unit falls in; the inverse, for the readout. */
export function cellOfUnit(scale: CellScale, unit: number): number {
return scale.per === 0 ? -1 : Math.floor((unit - scale.origin) / scale.per)
}
/** One axis of one rendered block, as this module needs it. */
export interface MetaBlock {
level: MetaLevel
runs: readonly MetaAxisRun[]
/** Cells on this axis — `nrows` or `ncols`. */
cells: number
/** The bin the block opens at (`rowExtent[0]`/`colExtent[0]`). */
blockStart: number
/** Bins summed into one cell; `1` for a dense read. */
binsPerCell: number
/** How the cells land on the drawn axis; the identity unless turned. */
scale?: CellScale
}
/**
* The lookups a cell → row mapping needs, which only the open file can answer.
*
* An interface rather than the tables themselves, so the arithmetic below can
* be tested against four lines of fixture and so this module never learns what
* a `Table` is shaped like. `ui/MetadataIndex.ts` is the implementation.
*/
export interface MetaRowIndex {
/** Row of `/genomes` for a genome name, or `-1`. */
genomeRow(name: string): number
/** Row of `/contigs` for a contig name, or `-1`. */
contigRow(name: string): number
/** Row of `/contigs` whose sequence covers an absolute bin, or `-1`. */
contigRowOfBin(bin: number): number
/** The genome a contig row belongs to, or `-1` on a file with no genomes. */
genomeOfContig(row: number): number
/** How many bins a contig row has; `0` for a row that is not there. */
binsInContig(row: number): number
}
/**
* Which row of one table each cell of one axis is, and `-1` where none.
*
* The three levels, each resolved by the least ambiguous thing available:
*
* - **bin.** The run carries `unitBin`, the absolute bin its sequence begins
* at, so the contig is found by *position* and not by name. That matters on a
* metagenome, where two MAGs are perfectly entitled to have assembled a
* `contig_1` each, and a name lookup would draw one MAG's annotation on the
* other's bins.
* - **contig.** A cell is a whole sequence and there is no bin to ask, so the
* name is all there is. Ambiguity resolves to the first match, which is what
* the reader's own `contigIds` does with a repeated name.
* - **genome.** Genome names are unique by construction — they are the keys the
* file's genome layer is built on.
*
* A cell claimed by two runs — which happens above bin level, where several
* short sequences share one cell — keeps the **first**, because the first is
* what the axis is labelled with and a lane that disagrees with its own axis
* label is worse than one that is coarse.
*/
export function rowsForCells(block: MetaBlock, table: MetaTable, index: MetaRowIndex): Int32Array {
const rows = new Int32Array(Math.max(0, block.cells)).fill(-1)
for (const run of block.runs) {
const from = Math.max(0, Math.trunc(run.start))
const to = Math.min(rows.length, Math.trunc(run.end))
if (to <= from) continue
const contig =
block.level === 'genome'
? -1
: run.unitBin === undefined
? index.contigRow(run.label)
: index.contigRowOfBin(run.unitBin)
const row =
table === 'genomes'
? block.level === 'genome'
? index.genomeRow(run.label)
: index.genomeOfContig(contig)
: contig
if (row < 0) continue
for (let cell = from; cell < to; cell++) if (rows[cell] < 0) rows[cell] = row
}
return rows
}
/** The bins one cell of a bin-level axis covers. */
export interface BinSpan {
/** First absolute bin, or `-1` where the cell is not on a sequence. */
start: number
/** How many bins, clamped to the end of the sequence; `0` where there are none. */
count: number
}
/**
* The bin range of every cell of a bin-level axis.
*
* One formula, and it is the reader's own (`AxisGroup.unitStart`): the cells of
* a sequence are counted from that sequence's own start, so
*
* ```
* cells into the sequence = blockStart + cell − unitStart
* first bin of the cell = unitBin + that × binsPerCell
* ```
*
* and it is exact in all four cases the reader produces. A dense block sends
* `unitStart` as the sequence's own first bin and `binsPerCell` of 1, so the
* expression collapses to `blockStart + cell`. A pooled block anchors each
* sequence's grid to that sequence's start, sends `unitStart` only on the first
* run — the only one that can open partway along — and the default for every
* later run, its own block-local `start`, is right by construction.
*
* The count is clamped to what the sequence has left, because the last cell of
* a contig is partial in general and a mean taken over bins that do not exist
* would be a mean over zeros.
*/
export function binSpansForCells(block: MetaBlock, index: MetaRowIndex): BinSpan[] {
const spans: BinSpan[] = Array.from({ length: Math.max(0, block.cells) }, () => ({
start: -1,
count: 0,
}))
if (block.level !== 'bin') return spans
const stride = Math.max(1, Math.trunc(block.binsPerCell))
for (const run of block.runs) {
const from = Math.max(0, Math.trunc(run.start))
const to = Math.min(spans.length, Math.trunc(run.end))
if (to <= from) continue
const first = run.unitBin
if (first === undefined) continue
const origin = run.unitStart ?? block.blockStart + run.start
const bins = index.binsInContig(index.contigRowOfBin(first))
for (let cell = from; cell < to; cell++) {
if (spans[cell].start >= 0) continue
const into = (block.blockStart + cell - origin) * stride
if (into < 0) continue
const left = bins > 0 ? bins - into : stride
if (left <= 0) continue
spans[cell] = { start: first + into, count: Math.min(stride, left) }
}
}
return spans
}
// ---------------------------------------------------------------------------
// Cells → values
// ---------------------------------------------------------------------------
/**
* One column, resolved onto the cells of one axis of one block.
*
* The only place the two halves meet, and the only thing `render/meta.ts` is
* given. Where a cell covers several bins — a pooled block, which is every
* whole-genome picture — a quantitative column is **averaged** over them and a
* qualitative one takes the **most common** of them. Both are aggregations, and
* the difference from the roll-up {@link showsAtLevel} refuses is that these
* stay inside the unit the axis is drawn in: the cell *is* those bins, and
* every one of them is on screen at that position. Rolling a bin column up to a
* genome would put a number where the file has none.
*/
export function cellsOf(options: {
block: MetaBlock
table: MetaTable
values: MetaValues
index: MetaRowIndex
}): MetaCells {
const { block, table, values, index } = options
const cells = Math.max(0, block.cells)
if (table === 'bins') return binCells(binSpansForCells(block, index), values, cells)
const rows = rowsForCells(block, table, index)
if (values.kind === 'quantitative') {
const out = new Float64Array(cells).fill(Number.NaN)
for (let cell = 0; cell < cells; cell++) {
const row = rows[cell] - values.from
if (rows[cell] < 0 || row < 0 || row >= values.values.length) continue
out[cell] = values.values[row]
}
return { kind: 'quantitative', values: out, extent: extentOf(out) }
}
const codes = new Int32Array(cells).fill(-1)
for (let cell = 0; cell < cells; cell++) {
const row = rows[cell] - values.from
if (rows[cell] < 0 || row < 0 || row >= values.codes.length) continue
codes[cell] = values.codes[row]
}
return { kind: 'qualitative', codes, levels: values.levels }
}
/** The bins path: a span per cell, averaged or voted on. */
function binCells(spans: readonly BinSpan[], values: MetaValues, cells: number): MetaCells {
if (values.kind === 'quantitative') {
const out = new Float64Array(cells).fill(Number.NaN)
for (let cell = 0; cell < cells && cell < spans.length; cell++) {
const { start, count } = spans[cell]
if (start < 0 || count <= 0) continue
let sum = 0
let seen = 0
for (let i = 0; i < count; i++) {
const at = start + i - values.from
if (at < 0 || at >= values.values.length) continue
const value = values.values[at]
// A filtered bin's weight is `NaN` in the file and means *no value
// here*, exactly as it does in a bigWig. Averaged in as a zero it would
// draw a filtered region as a low one rather than as an empty one.
if (!Number.isFinite(value)) continue
sum += value
seen++
}
if (seen > 0) out[cell] = sum / seen
}
return { kind: 'quantitative', values: out, extent: extentOf(out) }
}
const codes = new Int32Array(cells).fill(-1)
const tally = new Map<number, number>()
for (let cell = 0; cell < cells && cell < spans.length; cell++) {
const { start, count } = spans[cell]
if (start < 0 || count <= 0) continue
if (count === 1) {
const at = start - values.from
codes[cell] = at >= 0 && at < values.codes.length ? values.codes[at] : -1
continue
}
tally.clear()
for (let i = 0; i < count; i++) {
const at = start + i - values.from
if (at < 0 || at >= values.codes.length) continue
const code = values.codes[at]
if (code < 0) continue
tally.set(code, (tally.get(code) ?? 0) + 1)
}
let best = -1
let bestCount = 0
for (const [code, seen] of tally) {
// Ties go to the lower code, which is the level that appears earlier in
// the file: an arbitrary rule, but a *stable* one, so a cell does not
// change colour between two draws of the same picture.
if (seen > bestCount || (seen === bestCount && best >= 0 && code < best)) {
best = code
bestCount = seen
}
}
codes[cell] = best
}
return { kind: 'qualitative', codes, levels: values.levels }
}
/** The range over the cells in hand, skipping the gaps; `null` where all are. */
export function extentOf(values: Float64Array): { min: number; max: number } | null {
let min = Number.POSITIVE_INFINITY
let max = Number.NEGATIVE_INFINITY
for (let i = 0; i < values.length; i++) {
const value = values[i]
if (!Number.isFinite(value)) continue
if (value < min) min = value
if (value > max) max = value
}
return min > max ? null : { min, max }
}
// ---------------------------------------------------------------------------
// The rows on the card
// ---------------------------------------------------------------------------
/**
* What every metadata entry's id begins with.
*
* The same argument `SYNTHETIC_PREFIX` makes: `mintAnnotationId` produces `a`
* followed by a decimal number and `reserveAnnotationId` reads one back by
* taking `Number` of everything after the first character, so an id of that
* shape minted here could later be handed to a loaded track — and two rows
* under one id is one row listed twice, where removing either removes both.
* This shape begins with neither `a` nor a digit, and the colons mean no suffix
* of a column name can rescue it either.
*/
export const METADATA_PREFIX = 'metadata:'
/**
* The id a column always has, derived rather than minted.
*
* So that adding `contamination` twice lands on the row that is already there
* instead of stacking a second identical lane beside it — `AnnotationStore.begin`
* replaces an id it already holds and keeps its slot — and so that a row
* restored from session storage is recognisably the same row.
*/
export function metadataId(table: MetaTable, column: string): string {
return `${METADATA_PREFIX}${table}:${column}`
}
/** The table and column a metadata id names, or `null` for any other id. */
export function metadataSpec(id: string): { table: MetaTable; column: string } | null {
if (!id.startsWith(METADATA_PREFIX)) return null
const rest = id.slice(METADATA_PREFIX.length)
const cut = rest.indexOf(':')
if (cut <= 0) return null
const table = rest.slice(0, cut) as MetaTable
return META_TABLES.includes(table) ? { table, column: rest.slice(cut + 1) } : null
}
/** Which of the two lane kinds a column is drawn as. */
export function kindFor(kind: MetaKind): AnnotationKind {
return kind === 'quantitative' ? 'metadata' : 'classes'
}
/**
* The edge a metadata lane opens on.
*
* The **top**, and by elimination: a loaded track lands at the bottom, a
* computed one on the left (`SYNTHETIC_EDGE`), and a metadata lane arriving on
* either would be a new row in the middle of a stack somebody has arranged. It
* is also the right edge on the merits — metadata is what a reader wants
* *above* the map while they read the columns of it, in the position a genome
* browser puts its ideogram — and it is an ordinary lane, so the location row
* moves it anywhere.
*/
export const METADATA_EDGE = 'top' as const
/**
* A discovered column, as a row on the card.
*
* `status: 'ready'` at birth, like a synthetic track and for a stronger reason:
* there is nothing to fetch that the open file is not already holding. The
* caller puts it in the store with `begin` and the lane draws on the next
* frame.
*/
export function metadataEntry(
column: MetaColumn,
colour: string,
): AnnotationEntry & { source: MetadataSource } {
const kind = kindFor(column.kind)
return {
id: metadataId(column.table, column.column),
card: 'metadata',
kind,
label: column.column,
source: {
kind: 'metadata',
name: `${column.table}/${column.column}`,
table: column.table,
column: column.column,
},
status: 'ready',
visible: true,
placement: placementOn(METADATA_EDGE),
style: defaultStyle(kind, colour),
}
}
/** `where it comes from`, as the row writes it under the name. */
export function originOf(table: MetaTable, column: string): string {
return `${table === 'bins' ? '/bins' : `/${table}`} · ${column}`
}
/** `48 genomes · 6 categories` — the row's summary line. */
export function summaryOf(column: MetaColumn): string {
const unit = column.table === 'bins' ? 'bins' : column.table
const rows = `${column.rows.toLocaleString('en-US')} ${unit}`
return column.kind === 'quantitative'
? rows
: `${rows} · ${(column.levels?.length ?? 0).toLocaleString('en-US')} categories`
}
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