[{"data":1,"prerenderedAt":18472},["ShallowReactive",2],{"wrun-open-editor-url":3,"indicators:functions/order-flow-kit":4},"https://openmarket.xyz/chart/#wrun-open=v1",{"slug":5,"filePath":6,"frontmatter":7,"rawMarkdown":12,"tree":13},"functions/order-flow-kit","functions/order-flow-kit.md",{"title":8,"description":9,"order":10,"section":11},"Order flow","The chart serves order flow a candle alone cannot show: the bar's aggressive buy and sell volume as two sided inputs, the bar's volume profile as…",55,"functions","---\ntitle: \"Order flow\"\ndescription: \"The chart serves order flow a candle alone cannot show: the bar's aggressive buy and sell volume as two sided inputs, the bar's volume profile as…\"\norder: 55\nsection: \"functions\"\n---\n\n\u003C!-- source: docs/indicators/functions/order-flow-kit.md; generated by packages/cli/scripts/gen-indicator-docs.ts, do not edit -->\n\n# Order flow\n\nThe chart serves order flow a candle alone cannot show: the bar's\naggressive buy and sell volume as two sided inputs, the bar's volume\nprofile as `volume_profile` cells, a book snapshot as `book` cells and the\nbar's forced liquidations per side. This page is the arithmetic on top.\nThe `./sdk/orderflow` module ships `delta` and `deltaPct` for a bar, a\n`Cvd` you restart where you choose, a `VolumeProfile` with its point of\ncontrol and value area, a `BookImbalance`, and the two detectors the\ncookbook recipes use, `Absorption` and `LiquidationBurst`. The same scans\nwritten by hand over the profile and book cells follow each class, with\nthe readers those cells come through; the classes are those scans with\nthe edge rules pinned.\n\n## What the chart serves\n\n| Source | What one bar carries | Notes |\n| --- | --- | --- |\n| `trades.volume` with a `side` | the bar's aggressive buy volume, or its sell volume, as one number | declared twice, `side: \"BUY\"` and `side: \"SELL\"`; `missing: \"zero\"` reads 0 on a bar without prints; `currency: \"USD\"` reads dollars instead of coins |\n| `volume_profile.cells` | one `[low, high, buy, sell]` tuple per price level | real band edges, in ascending price order, a level with a non-finite member skipped; `buy` and `sell` are the aggressor volumes at that level in coins (base-asset units); the count varies with the bar's range |\n| `book.cells` | one `[price, size, side]` tuple per level | `side` is `+1` for a bid and `-1` for an ask, `size` the absolute resting quantity; the bids as the snapshot lists them, then the asks from the highest price down; up to 500 levels a side, so a full book is up to 1,000 tuples |\n| `liquidations.liquidations` with a `side` | the bar's forced liquidations on one side, in USD | the detector sample reads long liquidations from the `SELL` side and short ones from the `BUY` side, both `missing: \"zero\"` |\n\nThe two celled sources share these rules:\n\n- `max_cells` is required and counts tuples. A bar whose block exceeds it\n  refuses the whole run rather than truncating (\"max_cells is 512, so the\n  evaluation is refused (a block is never truncated)\"), except on a\n  profile declared `missing: \"empty\"` (below), where that bar reads an\n  empty block and the run goes on. A profile has one tuple per bucket the\n  bar crossed: BTCUSDT's bucket is $5, so 512 refuses any bar wider than\n  about $2,560, while 8192 covers the majors' profiles at native bucket\n  width; 1000 holds a full book. A low cap refuses wide bars, a high cap\n  reserves memory you never use (8192 profile tuples are 256 KB).\n- A celled input cannot be the primary input (a celled class has no clock\n  of its own), so a scalar input comes first and sets the grid the blocks\n  join row for row. Declaring one derives the sheet on the second runtime\n  contract (`abi_version: \"wrun-2\"`); Run does that for you.\n- Both follow the chart's own market and interval: a `symbol` +\n  `exchange` pin or an `interval` pin is refused (\"the browser lane serves\n  market pins on secondary ohlcv inputs only (typed feeds, cells and time\n  follow the chart's own market)\"). `description` is the only other option\n  the profile takes.\n- The book declaration requires `block_size` and accepts `max_depth`, but\n  the chart reads neither: it serves the same snapshots its own order book\n  lane fetches for the chart's market. Size `max_cells` for the deepest\n  book the market shows, not from `max_depth`.\n- The profile arrives at the market's own bucket width, one tick per\n  bucket, in coins, unless the input says otherwise. `ticks_per_bar`\n  merges that many of the market's own buckets into one, a whole number\n  from 1 to 500 (left out, or 1, the market's own width), and\n  `currency: \"USD\"` quotes bucket volume in dollars instead of coins\n  (`\"Coin\"`, the default, keeps coins):\n  `input(\"profile\", volume_profile.cells, { max_cells: 8192, ticks_per_bar: 5, currency: \"USD\" })`.\n  Any other value stops the build with the option's name.\n- The bucket size can be a setting: `ticks_per_bar: \"@node_ticks\"` names\n  a `param.int` whose `min..max` lies inside 1..500, the chart asks for\n  the profile at the setting's value and fetches again when the user\n  changes it:\n  `param.int(\"node_ticks\", 10, { min: 1, max: 50 }); input(\"profile\", volume_profile.cells, { max_cells: 8192, ticks_per_bar: \"@node_ticks\" })`.\n- The profile is required: a market without one stops the run with a\n  message naming it. `missing: \"empty\"` makes it optional, so on a\n  market that serves no profile, or a stretch without one, every bar\n  reads an empty block (`in_profile_cells()` is `0`) and the rest of the\n  indicator draws as usual:\n  `input(\"profile\", volume_profile.cells, { max_cells: 8192, missing: \"empty\" })`.\n  A bar whose profile has more buckets than `max_cells` reads the same\n  empty block on an optional profile, never a truncated one, so a wide\n  bar blanks that bar's profile parts instead of stopping the run.\n  Scans over an empty block find no level, so code that reads the profile\n  blanks those outputs by itself. Only `\"empty\"`, and only on\n  `volume_profile.cells`.\n- Neither block carries the bar's timestamp: the `time` source does when a\n  scan needs one.\n\n## Reading the cells\n\nDeclare a celled input behind a scalar one, with its cap:\n\n```typescript\ninput(\"close\", ohlcv.close);\ninput(\"profile\", volume_profile.cells, { max_cells: 8192 });\ninput(\"book\", book.cells, { max_cells: 1000, block_size: 10 });\n```\n\nA celled input has no scalar reader (`in_profile()` does not exist). It\nreaches `onBar()` through a generated pair, four cells per profile tuple\nand three per book tuple:\n\n| Accessor | Returns |\n| --- | --- |\n| `in_profile_cells(): i32`, `in_book_cells(): i32` | the number of `f64` cells this bar (tuples times the tuple width); `0` for a present, empty block; `-1` when the bar carries no block |\n| `in_profile_view(): StaticArray\u003Cf64>`, `in_book_view(): StaticArray\u003Cf64>` | the bar's cells in place: one buffer the build owns, filled before `onBar()` runs and never copied; only the first `in_\u003Cname>_cells()` values belong to this bar |\n\nRead the count, then the block, where you use them. The view is not\ncleared between bars: an absent or empty bar leaves the previous block in\nit, so bound every scan by the count. Profile tuple `i` is `cells[4 * i]`\nthrough `cells[4 * i + 3]` and `n / 4` is the count; a loop guarded by\n`i + 3 \u003C n` (`i + 2 \u003C n` over the book) walks whole tuples only, so a\nblock that is not a multiple of the tuple width (it never is, but the\nguard costs nothing) cannot read past the last cell. The copying reader\nand the capacity constants are on\n[Data sources](../core-concepts/data-sources.md#reading-a-block).\n\n## Every export\n\n| Export | Signature | What it gives |\n| --- | --- | --- |\n| `delta` | `delta(buy: f64, sell: f64): f64` | `buy - sell`; NaN when a side is not finite |\n| `deltaPct` | `deltaPct(buy: f64, sell: f64): f64` | `(buy - sell) / (buy + sell) * 100`, -100..100; NaN when the sum is 0 |\n| `Cvd` | `update(buy, sell): f64`, `value(): f64`, `delta(): f64`, `reset()` | the running sum of `buy - sell` since construction or the last `reset()`; a non-finite side counts as 0 on its bar |\n| `VolumeProfile` | `constructor(rows: i32)`, `begin(low, high)`, `add(low, high, buy, sell)`, `end(valueAreaPct: f64 = 70.0): bool`, `poc()`, `vah()`, `val()`, `total()`, `rowCount()`, `rowLow(i)`, `rowVolume(i)`, `rowBuy(i)`, `rowSell(i)`, `pocRow()`, `vahRow()`, `valRow()`, `reset()` | bands spread over `rows` equal-width rows across `[low, high)`, buy and sell kept per row; the POC row, its centre, and the value area's edges |\n| `BookImbalance` | `constructor(levels: i32)`, `begin()`, `add(price, size, side: i32)`, `end()`, `bidSize()`, `askSize()`, `ratio()`, `imbalance()`, `bestBid()`, `bestAsk()`, `spread()`, `reset()` | the `levels` highest bids and lowest asks kept whatever order the cells arrive in; their sizes summed, `bid / (bid + ask)`, `(bid - ask) / (bid + ask)`, the touch and the spread |\n| `Absorption` | `constructor(deltaWindow: i32, atrLength: i32, deltaSpike: f64, maxRange: f64)`, `update(high, low, close, buy, sell): i32`, `delta()`, `norm()`, `range()`, `reset()` | +1 buying absorbed, -1 selling absorbed, 0 otherwise: the absorption recipe's test |\n| `LiquidationBurst` | `constructor(window: i32, burstZ: f64)`, `update(longLiq, shortLiq): i32`, `longZ()`, `shortZ()`, `reset()` | -1 a long burst, +1 a short burst, 0 neither: the liquidation-bursts recipe's test |\n\nEvery class allocates in its constructor and never per bar, `NaN` means\n\"nothing\" (not warm yet, no such row, no level on that side), and\n`reset()` restores the freshly constructed state. Counts below 1 (rows,\nlevels, windows) are clamped to 1. Construct the objects in `onStart()`\n(a settings change rebuilds them there); an abort at module start loses\nits message.\n\n## Delta and CVD\n\n`delta(buy, sell)` is the bar's `buy - sell` and `deltaPct` the same as a\npercent of the bar's sided volume. `Cvd` keeps the running sum: every\n`update(buy, sell)` adds the bar's delta and returns the sum, `value()`\nreads it again, `delta()` reads the last bar's own delta. The sum has no\nanchor of its own: you decide where it restarts by calling `reset()`. The\nsample below restarts it on the first bar of each UTC day, gated by a\ndata-only `new_day` flag computed from `bar.time()` (the bar's open in\nUTC seconds), so the flag is on the chart too and an alert can read it.\n\n```typescript sample=fn-orderflow-cvd\ninput(\"close\", ohlcv.close);\ninput(\"buy\", trades.volume, { side: \"BUY\", missing: \"zero\" });\ninput(\"sell\", trades.volume, { side: \"SELL\", missing: \"zero\" });\noutput(\"cvd\", line, lower, { color: \"#2563eb\", width: 2, description: \"Cumulative volume delta, restarted each UTC day\" });\noutput(\"bar_delta\", line, lower, { color: \"#94a3b8\", description: \"This bar's buy minus sell volume\" });\noutput(\"new_day\", none, lower, { description: \"1 on the first bar of a UTC day (the reset gate)\" });\n\nlet cvd = new Cvd();\nlet prevDay: f64 = NaN;\n\nfunction onStart(): void {\n  cvd = new Cvd();\n}\n\nfunction onBar(): void {\n  const day = Math.floor(bar.time() / 86400.0);\n  const newDay = !isNaN(prevDay) && day != prevDay ? 1.0 : 0.0;\n  prevDay = day;\n  if (newDay == 1.0) cvd.reset();\n  const buy = in_buy();\n  const sell = in_sell();\n  const barDelta = delta(buy, sell);\n  const sum = cvd.update(buy, sell);\n  out_cvd(sum);\n  out_bar_delta(barDelta);\n  out_new_day(newDay);\n}\n```\n\nThe first bar of the history is not a \"new day\" (there is no previous\nday to compare), so the sum starts there and restarts at every day\nboundary after it. Read `new_day` in the Console to check the gate before\nyou alert on the line.\n\n## Volume profile\n\nA `VolumeProfile` is built from bands. `begin(low, high)` opens a profile\nover `[low, high)` split into the constructor's `rows` equal-width rows and\nclears them; `add(low, high, buy, sell)` folds one band; `end(valueAreaPct)`\ncloses the profile and answers `false` when nothing landed. Call `add()`\nper cell across as many bars as the profile should cover: a bar profile is\n`begin`, the bar's cells, `end`; a rolling profile is one `begin`, cells\nfrom every bar, `end` when you read it.\n\nThe frozen rules, the ones the\n[Volume profile and value area](../cookbook/volume-profile-value-area.md)\nrecipe uses:\n\n- A band is spread over the rows it overlaps in proportion to the overlap.\n  A band whose two edges fall in the same row, a band thinner than a row\n  and a point band with `low == high` land whole in that row.\n- A band entirely outside the span lands whole in the nearest edge row; a\n  band crossing the span's edge keeps the part inside.\n- The POC is the heaviest row; the lower row wins a tie. `poc()` is that\n  row's centre.\n- The value area starts at the POC and grows toward the heavier neighbour\n  (up wins a tie) until it holds `valueAreaPct` percent of the total.\n  `vah()` is the area's top row's upper edge and `val()` its bottom row's\n  lower edge, both row EDGES.\n- Buy and sell are kept per row: `rowBuy(i)`, `rowSell(i)` and their sum\n  `rowVolume(i)`; `rowLow(i)` is the row's lower edge and `total()` what\n  every row holds.\n\nThe sample reads the bar's `volume_profile` cells with the generated\n`in_profile_cells()` / `in_profile_view()` pair, loops the four-cell\ntuples into `add()`, and draws the three levels as lines on price.\n\n```typescript sample=fn-orderflow-profile\nparam(\"rows\", 24, { min: 2, max: 128, description: \"Price rows across the bar's range\" });\nparam(\"value_area\", 70, { min: 50, max: 95, description: \"Value area as a percent of the bar's volume\" });\ninput(\"close\", ohlcv.close);\ninput(\"profile\", volume_profile.cells, { max_cells: 4096, description: \"This bar's volume by price level\" });\noutput(\"poc\", line, overlay, { color: \"#f59e0b\", width: 2, description: \"Point of control: the heaviest row's centre\" });\noutput(\"vah\", line, overlay, { color: \"#38bdf8\", description: \"Value area high: the area's upper edge\" });\noutput(\"val\", line, overlay, { color: \"#38bdf8\", description: \"Value area low: the area's lower edge\" });\n\nlet profile = new VolumeProfile(24);\nlet valueArea: f64 = 70.0;\n\nfunction onStart(): void {\n  profile = new VolumeProfile(i32(p_rows()));\n  valueArea = p_value_area();\n}\n\nfunction onBar(): void {\n  profile.begin(bar.low(), bar.high()); // the bar's own range; a flat bar keeps the profile closed\n  const n = in_profile_cells();\n  if (n >= 4) {\n    const cells = in_profile_view();\n    for (let i = 0; i + 3 \u003C n; i += 4) {\n      profile.add(cells[i], cells[i + 1], cells[i + 2], cells[i + 3]);\n    }\n  }\n  const ok = profile.end(valueArea);\n  out_poc(ok ? profile.poc() : NaN);\n  out_vah(ok ? profile.vah() : NaN);\n  out_val(ok ? profile.val() : NaN);\n}\n```\n\n`end()` answers `false` on a bar with no bands or a flat range and the\nthree outputs are written `NaN` there, so the lines simply skip it. A\nclamp such bands into the edge rows on purpose, or skip them before\n`add()` when you want the recipe's stray-print rule.\n\n### Profile scans by hand\n\nThe class re-bins the bar's bands into rows you choose. When the native\nbuckets are what you want (the heaviest level as the chart serves it, the\nbar's sided totals, the range the profile spans), read the tuples\ndirectly. Each read is a function over the block, `cells` being the view\nand `n` the cell count for the bar. All nine take the same two arguments,\nso a module scans once and reads as many as it likes.\n\n| Function | Returns |\n| --- | --- |\n| `vpBuy(cells, n)` | total buy volume across the bar's buckets |\n| `vpSell(cells, n)` | total sell volume |\n| `vpDelta(cells, n)` | `vpBuy - vpSell`; positive is buy dominant |\n| `vpTotal(cells, n)` | combined buy + sell volume |\n| `vpPoc(cells, n)` | the point of control: the midprice of the highest-volume bucket, `NaN` if no buckets |\n| `vpPocVolume(cells, n)` | combined volume at the point-of-control bucket |\n| `vpBucketCount(n)` | the number of buckets this bar |\n| `vpPriceHigh(cells, n)` | the highest `high` across buckets, `NaN` if empty |\n| `vpPriceLow(cells, n)` | the lowest `low` across buckets, `NaN` if empty |\n\nHow the two readings differ:\n\n| | `VolumeProfile` | Hand scan |\n| --- | --- | --- |\n| Rows | `rows` equal-width rows across the span you pass to `begin()` | the chart's native buckets, one tick each |\n| Point of control | the heaviest row's centre, the lower row on a tie | the heaviest bucket's midprice, the lower bucket on a tie |\n| Value area | `vah()` and `val()` at `valueAreaPct` | none |\n| Totals | `total()`, buy and sell per row | `vpBuy`, `vpSell`, `vpDelta`, `vpTotal` |\n| Range | the span you passed | `vpPriceLow` and `vpPriceHigh` from the buckets |\n\nThe module below writes nine outputs from one scan per bar. The delta\ndraws as a histogram tinted by sign, the point of control as a line on\nthe price pane, and the rest in a lower pane. A bar with no block\n(`n \u003C 0`) abstains; a bar with an empty block (`n == 0`) is a real\nobservation of zero volume and writes zeros and `NaN` prices.\n\n```typescript sample=fn-vp-accessors\ninput(\"close\", ohlcv.close);\ninput(\"profile\", volume_profile.cells, { max_cells: 8192 });\noutput(\"poc\", line, overlay, { color: \"#ff9800\", width: 2, description: \"Point of control\" });\noutput(\"price_high\", line, overlay, { color: \"#94a3b8\", width: 1, description: \"Top of the profile\" });\noutput(\"price_low\", line, overlay, { color: \"#94a3b8\", width: 1, description: \"Bottom of the profile\" });\noutput(\"total_buy\", line, lower, { color: \"#26a69a\", width: 2, description: \"Buy volume summed over the profile\" });\noutput(\"total_sell\", line, lower, { color: \"#ef5350\", width: 2, description: \"Sell volume summed over the profile\" });\noutput(\"delta\", histogram, lower, { color_by: \"delta_sign\", colors: [\"#ef5350\", \"#26a69a\"], description: \"Net buy minus sell volume\" });\noutput(\"delta_sign\", none, lower, { description: \"0 sell dominant, 1 buy dominant: the delta palette index\" });\noutput(\"total_volume\", line, lower, { color: \"#9e9e9e\", width: 1, description: \"Combined volume\" });\noutput(\"poc_volume\", line, lower, { color: \"#ff9800\", width: 1, description: \"Volume at the point of control\" });\noutput(\"bucket_count\", line, lower, { color: \"#64748b\", width: 1, description: \"Price levels this bar\" });\n\nfunction vpBuy(cells: StaticArray\u003Cf64>, n: i32): f64 {\n  let total = 0.0;\n  for (let i = 0; i + 3 \u003C n; i += 4) total += cells[i + 2];\n  return total;\n}\n\nfunction vpSell(cells: StaticArray\u003Cf64>, n: i32): f64 {\n  let total = 0.0;\n  for (let i = 0; i + 3 \u003C n; i += 4) total += cells[i + 3];\n  return total;\n}\n\nfunction vpDelta(cells: StaticArray\u003Cf64>, n: i32): f64 {\n  return vpBuy(cells, n) - vpSell(cells, n);\n}\n\nfunction vpTotal(cells: StaticArray\u003Cf64>, n: i32): f64 {\n  return vpBuy(cells, n) + vpSell(cells, n);\n}\n\n// The index of the bucket with the most combined volume, or -1 for an empty block.\nfunction vpPocIndex(cells: StaticArray\u003Cf64>, n: i32): i32 {\n  let best = -1;\n  let bestVolume = -1.0;\n  for (let i = 0; i + 3 \u003C n; i += 4) {\n    const volume = cells[i + 2] + cells[i + 3];\n    if (volume > bestVolume) {\n      bestVolume = volume;\n      best = i;\n    }\n  }\n  return best;\n}\n\nfunction vpPoc(cells: StaticArray\u003Cf64>, n: i32): f64 {\n  const i = vpPocIndex(cells, n);\n  return i \u003C 0 ? NaN : (cells[i] + cells[i + 1]) / 2.0;\n}\n\nfunction vpPocVolume(cells: StaticArray\u003Cf64>, n: i32): f64 {\n  const i = vpPocIndex(cells, n);\n  return i \u003C 0 ? NaN : cells[i + 2] + cells[i + 3];\n}\n\nfunction vpBucketCount(n: i32): f64 {\n  return n \u003C 0 ? 0.0 : f64(n / 4);\n}\n\nfunction vpPriceHigh(cells: StaticArray\u003Cf64>, n: i32): f64 {\n  let top = NaN;\n  for (let i = 0; i + 3 \u003C n; i += 4) {\n    if (isNaN(top) || cells[i + 1] > top) top = cells[i + 1];\n  }\n  return top;\n}\n\nfunction vpPriceLow(cells: StaticArray\u003Cf64>, n: i32): f64 {\n  let bottom = NaN;\n  for (let i = 0; i + 3 \u003C n; i += 4) {\n    if (isNaN(bottom) || cells[i] \u003C bottom) bottom = cells[i];\n  }\n  return bottom;\n}\n\nfunction onBar(): void {\n  const n = in_profile_cells();\n  if (n \u003C 0) return; // no block on this bar: abstain\n  const cells = in_profile_view();\n  const delta = vpDelta(cells, n);\n  out_poc(vpPoc(cells, n));\n  out_price_high(vpPriceHigh(cells, n));\n  out_price_low(vpPriceLow(cells, n));\n  out_total_buy(vpBuy(cells, n));\n  out_total_sell(vpSell(cells, n));\n  out_delta(delta);\n  out_delta_sign(delta >= 0.0 ? 1.0 : 0.0);\n  out_total_volume(vpTotal(cells, n));\n  out_poc_volume(vpPocVolume(cells, n));\n  out_bucket_count(vpBucketCount(n));\n}\n```\n\nThe scans run in `onBar()` over the view the build filled before it: a\nmodule that reads the count once and computes many things from one block\npays for the block once.\n\n### One mark per price level\n\nEvery output is one number per bar and every renderer draws one thing\nper bar, so the per-level picture is not a loop of marks. It is a\ndeclaration over the same cells: `plot.footprint({ name, cells:\n\"profile\" })` draws one footprint column per bar from the buckets,\n`plot.heatmap({ name, cells: \"profile\", value: \"delta\" })` paints them as\na time by price heatmap, and `plot.profile({ name, cells: \"profile\",\nspan: \"session\" })` sums them into a volume profile per session, range or\nvisible window ([Price canvases](../presentation/price-canvases.md)). A\nprofile the module computes itself (a scan that weights or filters the\nbuckets) goes to a `plot.levels` frame docked on the price axis\n([Docked profiles](../presentation/cards-frames-panels.md#docked-profiles));\na fixed set of outputs (the point of control as a line, the top and\nbottom of the profile as two more, a `render.shape` at the level you care\nabout) draws the levels you name. The\n[Volume profile and value area](../cookbook/volume-profile-value-area.md)\nrecipe draws its levels that way.\n\n### The worked footprint\n\nThe `vp-buy-share-codefirst` starter is the footprint loop end to end: a\ncelled input, the buy share of each bar's profile as a numeric output,\nand a text renderer fed from a string slot on the newest bar. The whole\nfile and how to run it are on\n[Data sources](../core-concepts/data-sources.md#the-worked-footprint-example);\nin the editor it is the **VP Buy Share** card under\n**Order flow** in the template picker (the **Templates** icon beside\n**New indicator**). After a run on a market with profile data, type\n`last 5 buy_share` at the Console prompt to read the newest values.\n\n## Book imbalance\n\nA `BookImbalance` reads one snapshot per bar: `begin()`, one `add(price,\nsize, side)` per level with `side` exactly as the cell encodes it (`+1`\nbid, `-1` ask; any other value is ignored, so is a non-finite price or\nsize), then `end()`. It keeps the `levels` highest bids and the `levels`\nlowest asks, each side in a small array sorted best price first, so the\nresult is the same whatever order the levels arrive in. That matters: the\nchart hands the asks over from the highest price down, so the first ask\ntuple is the worst ask, never the best; `bestAsk()` is the lowest ask\nprice whatever the order. After `end()`, `bidSize()` and `askSize()` are\nthe kept sizes summed, `ratio()` is `bid / (bid + ask)` and `imbalance()`\n`(bid - ask) / (bid + ask)` (both NaN when both sums are 0), `bestBid()`,\n`bestAsk()` and `spread()` read the touch (NaN when a side is empty).\n\n```typescript sample=fn-orderflow-book\nparam(\"levels\", 10, { min: 1, max: 500, description: \"Levels kept per side, counted from the touch\" });\nparam(\"smooth\", 21, { min: 1, max: 200, description: \"EMA window over the imbalance\" });\ninput(\"close\", ohlcv.close);\ninput(\"book\", book.cells, { max_cells: 1000, block_size: 10 });\noutput(\"imbalance\", line, lower, { color: \"#94a3b8\", description: \"(bids - asks) / (bids + asks) over the kept levels, -1..1\" });\noutput(\"smoothed\", line, lower, { color: \"#2563eb\", width: 2, description: \"The imbalance smoothed\" });\noutput(\"spread\", none, lower, { description: \"Best ask minus best bid\" });\n\nlet imbalanceOf = new BookImbalance(10);\nlet ema = new Ema(21);\n\nfunction onStart(): void {\n  imbalanceOf = new BookImbalance(i32(p_levels()));\n  ema = new Ema(i32(p_smooth()));\n}\n\nfunction onBar(): void {\n  const n = in_book_cells();\n  if (n \u003C= 0) return; // no snapshot this bar, or an empty one: nothing to measure\n  const cells = in_book_view();\n  imbalanceOf.begin();\n  for (let i = 0; i + 2 \u003C n; i += 3) {\n    imbalanceOf.add(cells[i], cells[i + 1], i32(cells[i + 2]));\n  }\n  imbalanceOf.end();\n  const imbalance = imbalanceOf.imbalance();\n  const spread = imbalanceOf.spread();\n  const smoothed = isNaN(imbalance) ? NaN : ema.update(imbalance);\n  out_imbalance(imbalance);\n  out_smoothed(smoothed);\n  out_spread(spread);\n}\n```\n\nThe `Ema` from `./sdk/ta` is fed once per bar, in order; on a bar without\na snapshot `onBar()` returns early, so the average is left untouched and\nthe three outputs stay `NaN`. Size `max_cells` for the deepest book the\nmarket shows (a snapshot over the cap refuses the run); the cap is in\ntuples.\n\n### Depth window scans by hand\n\nThe class keeps a count of levels from the touch. A depth window keeps a\nprice band instead: every scan takes a `depthPct` (`10` in the module\nbelow) and only levels within that percentage of the mid price count. The\nmid is the average of the best bid (the highest bid price) and the best\nask (the lowest ask price), read from prices rather than positions so any\nlevel order works, and a level is inside the window when\n`abs(price - mid) \u003C= mid * depthPct / 100`. Smaller percentages (1 to 5)\nfocus on top-of-book activity; larger ones (10 to 20) read overall depth.\n\n| | `BookImbalance` | Depth window scan |\n| --- | --- | --- |\n| Levels kept | the `levels` best on each side | every level within `depthPct` of the mid |\n| Window | a count, the same whatever the price | a price band that scales with the mid |\n| Reads | sizes, ratio, imbalance, touch, spread | sums, the largest and smallest order, imbalance |\n\nThree scans parameterized by side cover six measures. The sums answer `0`\non an empty window, `maxSide` and `minSide` answer `NaN` when no level of\nthat side sits inside it, and all three answer `NaN` when a side of the\nbook is missing (no mid):\n\n| Scan | Returns |\n| --- | --- |\n| `sumSide(cells, n, 1.0, depthPct)` | total bid size within the window |\n| `sumSide(cells, n, -1.0, depthPct)` | total ask size within the window |\n| `maxSide(cells, n, 1.0, depthPct)` | the largest single bid within the window |\n| `maxSide(cells, n, -1.0, depthPct)` | the largest single ask |\n| `minSide(cells, n, 1.0, depthPct)` | the smallest bid within the window |\n| `minSide(cells, n, -1.0, depthPct)` | the smallest ask |\n\nWhat the six measures serve:\n\n| Category | What the scans give you |\n| --- | --- |\n| Volume analysis | bid and ask size summed within the depth window, and their imbalance |\n| Order size analysis | the largest and smallest resting orders on each side, to spot size |\n| Market depth | how far liquidity reaches and where it clusters, for support and resistance reads |\n\nThe module adds the imbalance the sums are usually combined into,\n`(bids - asks) / (bids + asks)`, smoothed with the shipped `Ema` so the\nper-snapshot noise reads as pressure. `depth_pct` is a param, so the\nwindow is a setting the chart user can change.\n\n```typescript sample=fn-orderbook-depth\nparam(\"depth_pct\", 10, { min: 0.1, max: 50, description: \"Depth window as a percent of the mid price\" });\nparam(\"smooth\", 21, { min: 1, max: 200, description: \"EMA window over the imbalance\" });\ninput(\"close\", ohlcv.close);\ninput(\"book\", book.cells, { max_cells: 1000, block_size: 10 });\noutput(\"bid_volume\", line, lower, { color: \"#26a69a\", width: 2, description: \"Bid size within the window\" });\noutput(\"ask_volume\", line, lower, { color: \"#ef5350\", width: 2, description: \"Ask size within the window\" });\noutput(\"max_bid\", line, lower, { color: \"#0f766e\", width: 1, description: \"Largest resting bid within the window\" });\noutput(\"max_ask\", line, lower, { color: \"#be123c\", width: 1, description: \"Largest resting ask within the window\" });\noutput(\"min_bid\", line, lower, { color: \"#5eead4\", width: 1, description: \"Smallest resting bid within the window\" });\noutput(\"min_ask\", line, lower, { color: \"#fda4af\", width: 1, description: \"Smallest resting ask within the window\" });\noutput(\"imbalance\", line, lower, { color: \"#94a3b8\", width: 1, description: \"(bids - asks) / (bids + asks), -1..1\" });\noutput(\"imbalance_ema\", line, lower, { color: \"#2563eb\", width: 2, description: \"Smoothed imbalance\" });\n\n// The average of the best bid (the highest bid price) and the best ask (the lowest ask price),\n// or NaN when either side is missing. Reads prices, not positions, so any level order works.\nfunction bookMid(cells: StaticArray\u003Cf64>, n: i32): f64 {\n  let bestBid = NaN;\n  let bestAsk = NaN;\n  for (let i = 0; i + 2 \u003C n; i += 3) {\n    const price = cells[i];\n    if (cells[i + 2] > 0.0) {\n      if (isNaN(bestBid) || price > bestBid) bestBid = price;\n    } else if (isNaN(bestAsk) || price \u003C bestAsk) bestAsk = price;\n  }\n  return isNaN(bestBid) || isNaN(bestAsk) ? NaN : (bestBid + bestAsk) / 2.0;\n}\n\n// True when a level sits within depthPct percent of the mid.\nfunction inWindow(price: f64, mid: f64, depthPct: f64): bool {\n  return Math.abs(price - mid) \u003C= (mid * depthPct) / 100.0;\n}\n\nfunction sumSide(cells: StaticArray\u003Cf64>, n: i32, side: f64, depthPct: f64): f64 {\n  const mid = bookMid(cells, n);\n  if (isNaN(mid)) return NaN;\n  let total = 0.0;\n  for (let i = 0; i + 2 \u003C n; i += 3) {\n    if (cells[i + 2] == side && inWindow(cells[i], mid, depthPct)) total += cells[i + 1];\n  }\n  return total;\n}\n\nfunction maxSide(cells: StaticArray\u003Cf64>, n: i32, side: f64, depthPct: f64): f64 {\n  const mid = bookMid(cells, n);\n  if (isNaN(mid)) return NaN;\n  let best = NaN;\n  for (let i = 0; i + 2 \u003C n; i += 3) {\n    if (cells[i + 2] == side && inWindow(cells[i], mid, depthPct)) {\n      if (isNaN(best) || cells[i + 1] > best) best = cells[i + 1];\n    }\n  }\n  return best;\n}\n\nfunction minSide(cells: StaticArray\u003Cf64>, n: i32, side: f64, depthPct: f64): f64 {\n  const mid = bookMid(cells, n);\n  if (isNaN(mid)) return NaN;\n  let best = NaN;\n  for (let i = 0; i + 2 \u003C n; i += 3) {\n    if (cells[i + 2] == side && inWindow(cells[i], mid, depthPct)) {\n      if (isNaN(best) || cells[i + 1] \u003C best) best = cells[i + 1];\n    }\n  }\n  return best;\n}\n\nlet depthPct: f64 = 10.0;\nlet ema = new Ema(21);\n\nfunction onStart(): void {\n  depthPct = p_depth_pct();\n  ema = new Ema(i32(p_smooth()));\n}\n\nfunction onBar(): void {\n  const n = in_book_cells();\n  if (n \u003C= 0) return; // no snapshot, or an empty one: nothing to measure\n  const cells = in_book_view();\n  const bids = sumSide(cells, n, 1.0, depthPct);\n  const asks = sumSide(cells, n, -1.0, depthPct);\n  const imbalance = bids + asks > 0.0 ? (bids - asks) / (bids + asks) : NaN;\n  const smoothed = isNaN(imbalance) ? NaN : ema.update(imbalance);\n  out_bid_volume(sumSide(cells, n, 1.0, depthPct));\n  out_ask_volume(sumSide(cells, n, -1.0, depthPct));\n  out_max_bid(maxSide(cells, n, 1.0, depthPct));\n  out_max_ask(maxSide(cells, n, -1.0, depthPct));\n  out_min_bid(minSide(cells, n, 1.0, depthPct));\n  out_min_ask(minSide(cells, n, -1.0, depthPct));\n  out_imbalance(imbalance);\n  out_imbalance_ema(smoothed);\n}\n```\n\nThe `Ema` is fed in `onBar()` once per bar, in order, after the early\nreturn, so a bar without a snapshot never touches it.\n\n## Absorption and liquidation bursts\n\nBoth detectors are the cookbook recipes' tests, verbatim, so an indicator\nbuilt on them flags exactly the bars\n[Absorption](../cookbook/absorption.md) and\n[Liquidation bursts](../cookbook/liquidation-bursts.md) flag.\n\n`Absorption(deltaWindow, atrLength, deltaSpike, maxRange)` answers, per\n`update(high, low, close, buy, sell)`: delta = `buy - sell`; norm = the\n`Sma(deltaWindow)` of `abs(delta)`; range = the `Atr(atrLength)`; heavy =\nnorm > 0 and `abs(delta) >= deltaSpike * norm`; stuck = range > 0 and\n`high - low \u003C= maxRange * range`; heavy and stuck give `+1` when delta >= 0\n(buying absorbed) and `-1` otherwise (selling absorbed), else `0`.\n`delta()`, `norm()` and `range()` read the bar's three numbers. The answer\nis `0` while the average or the ATR is warming up.\n\n`LiquidationBurst(window, burstZ)` answers, per `update(longLiq,\nshortLiq)`, side by side: mean = `Sma(window)`, dev = `Stdev(window)`;\nburst = value > 0 and dev > 0 and `value >= mean + burstZ * dev`. A long\nburst answers `-1`, a short burst `+1`; when both sides burst the larger\nvalue wins, long on a tie; else `0`. `longZ()` and `shortZ()` read\n`(value - mean) / dev`, NaN while not warm or when dev is 0.\n\nThe sample draws absorbed bars as dots (above the candle when buying was\nabsorbed, below it when selling was) and writes both answers as data-only\noutputs an alert can read.\n\n```typescript sample=fn-orderflow-detectors\nparam(\"delta_spike\", 2.0, { min: 1.0, max: 6.0, description: \"Heavy when abs(delta) is this many times its rolling mean\" });\nparam(\"delta_window\", 48, { min: 10, max: 400, description: \"Bars the mean of abs(delta) is taken over\" });\nparam(\"max_range\", 0.8, { min: 0.2, max: 2.0, description: \"Stuck when the bar's range is under this many ATRs\" });\nparam(\"atr_length\", 14, { min: 2, max: 100, description: \"The ATR's Wilder length\" });\nparam(\"burst_z\", 3.0, { min: 1.0, max: 8.0, description: \"A burst sits this many deviations above the window's mean\" });\nparam(\"window\", 96, { min: 10, max: 500, description: \"Bars the liquidation mean and deviation are taken over\" });\ninput(\"close\", ohlcv.close);\ninput(\"buy\", trades.volume, { side: \"BUY\", missing: \"zero\" });\ninput(\"sell\", trades.volume, { side: \"SELL\", missing: \"zero\" });\ninput(\"long_liq\", liquidations.liquidations, { side: \"SELL\", missing: \"zero\" });\ninput(\"short_liq\", liquidations.liquidations, { side: \"BUY\", missing: \"zero\" });\noutput(\"absorbed_buying\", shape, overlay, { color: \"#f86800\", description: \"A dot above a candle where heavy buying went nowhere\" });\noutput(\"absorbed_selling\", shape, overlay, { color: \"#f8c000\", description: \"A dot below a candle where heavy selling went nowhere\" });\noutput(\"absorption\", none, overlay, { description: \"+1 buying absorbed, -1 selling absorbed, 0 none\" });\noutput(\"burst\", none, overlay, { description: \"-1 a long burst, +1 a short burst, 0 none\" });\n\nlet absorption = new Absorption(48, 14, 2.0, 0.8);\nlet bursts = new LiquidationBurst(96, 3.0);\n\nfunction onStart(): void {\n  absorption = new Absorption(i32(p_delta_window()), i32(p_atr_length()), p_delta_spike(), p_max_range());\n  bursts = new LiquidationBurst(i32(p_window()), p_burst_z());\n}\n\nfunction onBar(): void {\n  const close = bar.close();\n  const high = bar.high();\n  const low = bar.low();\n  const absorbed = absorption.update(high, low, close, in_buy(), in_sell());\n  const burst = bursts.update(in_long_liq(), in_short_liq());\n  const range = absorption.range();\n  const dotAbove = absorbed == 1 ? high + range * 0.4 : NaN;\n  const dotBelow = absorbed == -1 ? low - range * 0.4 : NaN;\n  out_absorbed_buying(dotAbove);\n  out_absorbed_selling(dotBelow);\n  out_absorption(f64(absorbed));\n  out_burst(f64(burst));\n}\n```\n\nA `shape` output written `NaN` draws nothing on that bar, so the dots\nappear only where the detector fired. The recipes add a box around the\ncandle, a money tag on a burst and a notice when the market serves no\nsided prints or no liquidations; those are drawing objects on top of the\nsame two answers.\n\n## Where it runs\n\nThe chart serves `volume_profile` and `book` over the loaded history and\npushes the forming bar's profile and book live; a book module refreshes\nits newest bar at most about once a second. Cell alignment is an exact\njoin: a primary bar with no observation gets a present empty block\n(`n == 0`), never a carried-forward one, so volume is never counted twice\nand a stale book never masquerades as a fresh read\n([Data sources](../core-concepts/data-sources.md#celled-sources)). When\nthe market has no profile data, the run stops with a toast instead of\ndrawing zeros: \"Volume profile data is unavailable for '\u003Ctitle>' (the\nvolume_profile source lane answered empty or was declined), so the\nindicator cannot compute.\" An alert on the indicator runs in OpenMarket's\ncloud; when it cannot evaluate a data source, saving the alert says so\n(\"This Indicator reads a data source alerts cannot evaluate yet.\",\n[Alerts](alerts.md)).\n\n## Practices\n\n- **Scan once.** Read the count and the view once per bar and compute\n  every measure from them. Nine scans over a bar's few hundred tuples is\n  still cheap, but one is cheaper.\n- **Track the point of control.** The price with the most traded volume\n  often acts as a magnet; `vpPoc` with `vpPocVolume` says how dominant the\n  level is.\n- **Read delta for pressure.** `vpDelta` summarizes net aggressor flow per\n  bar. Sustained positive delta is buy-side control; feed it to `Cvd` or\n  `Cum` for cumulative delta, or to `Rsi` for delta-RSI\n  ([TA library](ta-library.md)).\n- **Smooth the imbalance.** A large bid-over-ask imbalance often precedes\n  an upward move and the reverse a downward one; a single snapshot is\n  noisy, so smooth it before alerting on it.\n- **Watch large orders.** `max_bid` and `max_ask` jumping is size\n  arriving; pair them with `min_bid` / `min_ask` to tell a thin book from\n  a deep one.\n\n## From Pine\n\nNothing on this page maps one to one. Pine has no sided trades, volume\nprofile bands, book levels or liquidations as script inputs, so there is\nno `ta.*` call to translate: the delta, the profile and the imbalance are\ncomputed from cells the chart serves to the indicator, and the detectors\nare recipes of this chart. 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