Landing kit from go-fileshare: neutral backgrounds, brand from the logo, fileshare's skeleton

.github/workflows/ci.yml

@@ -0,0 +1,29 @@
+name: ci
+
+on:
+  pull_request:
+    branches: [main]
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+jobs:
+  build:
+    name: the site builds
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v5
+      - uses: peaceiris/actions-hugo@v3
+        with:
+          hugo-version: "0.167.0"
+          extended: true
+      - run: hugo --minify
+      # A page that builds and says nothing is a page nobody notices is empty.
+      - name: every repository is on it
+        run: |
+          for repo in ndarray docs brand; do
+            grep -q "go-ndarray/$repo" public/index.html \
+              || { echo "::error::$repo is not on the page"; exit 1; }
+          done
+          echo "the page names every repository this org has"

.github/workflows/links.yml

@@ -0,0 +1,56 @@
+name: links
+
+# Taken from go-fileshare.github.io, where a dead repository link on the
+# landing went unnoticed until a check like this one read the BUILT site.
+#
+# ⛔ THE CHECK READS THE BUILT SITE, NOT THE LAYOUTS: templated links such as
+# the per-repository cards only become real URLs once Hugo has expanded them.
+
+on:
+  pull_request:
+    branches: [main]
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+jobs:
+  links:
+    name: every link and image resolves
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v7
+        with:
+          submodules: recursive
+      - uses: peaceiris/actions-hugo@v3
+        with:
+          hugo-version: "0.167.0"
+          extended: true
+      - run: hugo --minify --destination ./public
+      - name: Check
+        run: |
+          set -uo pipefail
+          # The character class matters: an extractor that stops only at ) and "
+          # carries a closing > or < into the request.
+          urls=$(grep -rhoE 'https?://[^)">< [:space:]]+' public/ | sed 's/[.,]$//' | sort -u)
+          test -n "$urls" || { echo "::error::no links found; did the site build?"; exit 1; }
+          echo "checking $(printf '%s\n' "$urls" | wc -l) distinct URLs"
+          fail=0
+          while read -r u; do
+            # img.shields.io renders anything asked of it and proves nothing.
+            case "$u" in *img.shields.io*) continue ;; esac
+            # Three attempts: one is a flake detector rather than a link
+            # checker, and a lane that fails at random is a lane people learn
+            # to ignore.
+            code=000
+            for attempt in 1 2 3; do
+              code=$(curl -sS -o /dev/null -w '%{http_code}' -L --max-time 25 "$u" || echo 000)
+              case "$code" in 2*|3*) break ;; esac
+              sleep 3
+            done
+            case "$code" in
+              2*|3*) printf '  ok   %s  %s\n' "$code" "$u" ;;
+              *)     printf '  FAIL %s  %s\n' "$code" "$u"; fail=1 ;;
+            esac
+          done <<< "$urls"
+          test "$fail" -eq 0 || { echo "::error::at least one link or image does not resolve"; exit 1; }

hugo.toml

@@ -14,62 +14,6 @@ disableKinds = ['taxonomy', 'term', 'rss', 'sitemap', '404']
 [params]
   description = "go-ndarray is a pure-Go (CGO=0) NumPy-style n-dimensional array library for float64 — slicing/views, broadcasting, ufuncs, reductions and linear algebra, multicore + SIMD on amd64, arm64, ppc64le, loong64 and riscv64, with a Workspace arena for loops."
 
-# The colours are read by partials/styles.html. Emerald, shared with go-fft:
-# the two are one scientific-computing family, told apart by their glyphs.
-# The values are go-fft's, unchanged.
-[params.brand]
-  base   = "#059669"   # emerald-600: accent, primary button, gradient start
-  deep   = "#047857"   # emerald-700: gradient end
-  bright = "#34d399"   # emerald-400: accent in dark mode
-  shadow = "rgba(5,150,105,.7)"
-  chipBg     = "#d1fae5"
-  chipBorder = "#a7f3d0"
-  chipFg     = "#047857"
-  chipBgDark     = "rgba(52,211,153,.14)"
-  chipBorderDark = "rgba(52,211,153,.32)"
-  chipFgDark     = "#6ee7b7"
-  glow        = "rgba(110,231,183,.22)"
-  glow2       = "rgba(5,150,105,.10)"
-  glyphShadow = "rgba(5,150,105,.6)"
-  statsTint   = "#a7f3d0"
-  bandFg      = "#d1fae5"
-  # White on emerald-600 is 3.77:1, under the 4.5:1 body text needs; the band
-  # paragraph and the primary button sit on this gradient, so it runs one step
-  # darker than the accent: 700 -> 800 (white 5.48:1, #d1fae5 4.84:1 at worst).
-  gradFrom    = "#047857"
-  gradTo      = "#065f46"
-  # The hero's accent words: emerald-400 -> 300 on the dark background (the
-  # light theme keeps base -> deep, 600 -> 700).
-  gradTextDark = "linear-gradient(135deg,#34d399,#6ee7b7)"
-  [params.brand.surfaces]
-    ink        = "#052e22"
-    slate      = "#065f46"
-    muted2     = "#047857"
-    line       = "#a7f3d0"
-    bg         = "#f0fdf9"
-    bgSoft     = "#d1fae5"
-    surface    = "#ffffff"
-    navBg      = "rgba(240,253,249,.82)"
-    navBorder  = "#a7f3d0"
-    elevBorder = "#6ee7b7"
-    ghostHover = "#6ee7b7"
-    statsBg    = "#052e22"
-  [params.brand.surfacesDark]
-    ink        = "#d1fae5"
-    slate      = "#a7f3d0"
-    muted2     = "#6ee7b7"
-    line       = "#0a3d2a"
-    bg         = "#04130d"
-    bgSoft     = "#052e22"
-    surface    = "#06291c"
-    navBg      = "rgba(4,19,13,.82)"
-    navBorder  = "#0a3d2a"
-    elevBorder = "#10593d"
-    ghostHover = "#10593d"
-    statsBg    = "#06291c"
-
-# Each repo. Every field is rendered: "name" in the strip under the hero and on
-# its card, "kind" as the card's tag, "href" as both links, "blurb" in full.
 [[params.repos]]
   name  = "ndarray"
   kind  = "library · v0.7.0"
@@ -85,3 +29,46 @@ disableKinds = ['taxonomy', 'term', 'rss', 'sitemap', '404']
   kind  = "assets"
   href  = "https://github.com/go-ndarray/brand"
   blurb = "Logos and icons for the organization, in SVG / PNG / JPG / ICO / ICNS across colour, white and black variants."
+
+[params.brand]
+# Generated by logos/landing-kit/kit.py from static/img/logo.svg: the colours are
+# READ from the logo's gradient, never chosen. Do not add other keys:
+# neutrals (backgrounds, surfaces, greys) belong to the shared sheet.
+# Contrast: base on white 5.48:1, bright on the dark background 10.05:1.
+  base = "#047857"
+  deep = "#024935"
+  bright = "#34d399"
+  shadow = "rgba(4,120,87,.7)"
+  glow = "rgba(4,120,87,.6)"
+  wash = "rgba(4,120,87,.10)"
+  washDeep = "rgba(2,73,53,.06)"
+  chipBg = "#e7faf3"
+  chipBorder = "#c2f2e0"
+  chipFg = "#024935"
+  chipBgDark = "rgba(52,211,153,.14)"
+  chipBorderDark = "rgba(52,211,153,.32)"
+  chipFgDark = "#8fe7c7"
+
+# The API cards (#api) and the count in the hero come from this list, never
+# from a number typed beside it.
+[[params.families]]
+  name = "Creation"
+  what = "`Zeros`, `Ones`, `Full`, `Arange`, `Linspace`, `FromData`, `Eye` and the rest of NumPy's constructors, float64 throughout."
+[[params.families]]
+  name = "Views and indexing"
+  what = "`Reshape`, `Transpose` and NumPy basic indexing with `Slice(All(), A(0), …)`: strided views that share data, no copy."
+[[params.families]]
+  name = "Broadcasting and ufuncs"
+  what = "Elementwise arithmetic with NumPy broadcasting, and the unary functions, including `Exp` and `Log` ported from Arm's optimized-routines (≤ 0.51 ULP)."
+[[params.families]]
+  name = "Reductions"
+  what = "`Sum`, `Mean`, `Max`, `ArgMax`, `CumSum`, `Clip`, `Where`, whole-array or along an axis, multicore on large arrays."
+[[params.families]]
+  name = "Manipulation"
+  what = "`Concatenate`, `Stack` and the shape operations NumPy users reach for."
+[[params.families]]
+  name = "Linear algebra"
+  what = "`MatMul` and `Dot` through a panel-packed, cache-blocked GEMM with a go-asmgen SIMD micro-kernel per architecture."
+[[params.families]]
+  name = "Workspace"
+  what = "An arena for loops: `Use`, `Reset`, `Detach` — results stop costing the garbage collector from one pass to the next."

layouts/index.html

@@ -11,22 +11,20 @@
 <body class="lm">
   <header class="nav"><div class="wrap">
     <a class="brand" href="/"><img class="glyph" src="/img/logo.svg" width="32" height="32" alt="go-ndarray logo"> go-ndarray</a>
-    <nav><a href="#features">Why</a><a href="#repos">Repos</a><a href="#quality">Quality</a><a href="https://go-ndarray.github.io/docs/">Docs</a></nav>
+    <nav><a href="#features">Why</a><a href="#check">Example</a><a href="#api">API</a><a href="#repos">Repositories</a></nav>
     {{ partial "theme-toggle.html" . }}
-    {{- /* GitHub mark: Octicons "mark-github" (16px), @primer/octicons v19.38.0,
-           build/svg/mark-github-16.svg, MIT License (c) GitHub Inc. Path copied verbatim. */}}
-    <a class="btn btn-ghost" href="https://github.com/go-ndarray"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" width="16" height="16" fill="currentColor" aria-hidden="true" focusable="false"><path d="M6.766 11.328c-2.063-.25-3.516-1.734-3.516-3.656 0-.781.281-1.625.75-2.188-.203-.515-.172-1.609.063-2.062.625-.078 1.468.25 1.968.703.594-.187 1.219-.281 1.985-.281.765 0 1.39.094 1.953.265.484-.437 1.344-.765 1.969-.687.218.422.25 1.515.046 2.047.5.593.766 1.39.766 2.203 0 1.922-1.453 3.375-3.547 3.64.531.344.89 1.094.89 1.954v1.625c0 .468.391.734.86.547C13.781 14.359 16 11.53 16 8.03 16 3.61 12.406 0 7.984 0 3.563 0 0 3.61 0 8.031a7.88 7.88 0 0 0 5.172 7.422c.422.156.828-.125.828-.547v-1.25c-.219.094-.5.156-.75.156-1.031 0-1.64-.562-2.078-1.609-.172-.422-.36-.672-.719-.719-.187-.015-.25-.093-.25-.187 0-.188.313-.328.625-.328.453 0 .844.281 1.25.86.313.452.64.655 1.031.655s.641-.14 1-.5c.266-.265.47-.5.657-.656"/></svg>GitHub</a>
+    <a class="btn btn-ghost" href="https://github.com/go-ndarray">{{ partial "icons/github.html" . }}GitHub</a>
   </div></header>
 
   <div class="hero"><div class="wrap">
     <div>
       <h1 class="head">NumPy-style n-dimensional arrays in pure Go.<br><span class="accent">float64, multicore + SIMD.</span></h1>
       <p class="sub"><b>go-ndarray</b> is the <code>numpy</code> equivalent for Go: a float64 n-dimensional array with creation routines, <b>strided views that share data</b>, broadcasting elementwise ops and ufuncs, reductions (incl. arg / cumulative / clip / where), manipulation, and linear algebra (a panel-packed, cache-blocked GEMM) — all in <b>pure Go, with cgo disabled</b>.</p>
       <div class="cta">
-        <a class="btn btn-primary" href="https://github.com/go-ndarray">Browse the repositories →</a>
-        <a class="btn btn-ghost" href="https://go-ndarray.github.io/docs/">Read the docs</a>
+        <a class="btn btn-primary" href="https://go-ndarray.github.io/docs/">Read the documentation →</a>
+        <a class="btn btn-ghost" href="https://github.com/go-ndarray/ndarray">{{ partial "icons/github.html" . }}Browse the source</a>
       </div>
-      <div class="trust"><span><b>{{ len .Site.Params.repos }}</b> repositories</span><span><b>CGO_ENABLED=0</b>, no BLAS shim</span><span><b>100%</b> test coverage</span></div>
+      <div class="trust"><span><b>{{ len .Site.Params.families }}</b> API families, NumPy's names</span><span><b>5</b> SIMD targets</span><span><b>CGO=0</b> no BLAS shim</span></div>
     </div>
     {{/* Lines taken verbatim from the Example section of go-ndarray/ndarray's README at v0.2.2. */}}
     <div class="term">
@@ -57,23 +55,54 @@ <h1 class="head">NumPy-style n-dimensional arrays in pure Go.<br><span class="ac
     <div class="mods">{{ range .Site.Params.repos }}<a href="{{ .href }}">{{ .name }}</a>{{ end }}</div>
   </div></div>
 
+  <section id="check" style="padding-top:10px"><div class="wrap">
+    <span class="eyebrow">Ask it, do not take our word</span>
+    <h2>The example above, <i>actually run</i>.</h2>
+    <p class="lead">The lines in the hero, built into a program against the published module and run. Views share data, broadcasting stretches <code>row</code> over both rows, and <code>MatMul</code> goes through the same cache-blocked SIMD kernel as a 4096² product. The output below is a real run, with nothing edited.</p>
+    <div class="term" style="margin-top:22px">
+      <div class="bar"><i style="background:#ff5f57"></i><i style="background:#febc2e"></i><i style="background:#28c840"></i><span class="t">go run ./ndcheck — zsh</span></div>
+{{/* Verbatim: go run of the hero's lines against
+     github.com/go-ndarray/ndarray v0.7.0, on an Apple M4 (arm64),
+     2026-10-08. Re-run it and paste its output when the API changes; never
+     retype a value here. */}}
+<pre style="white-space:pre;overflow-x:auto"><span class="c-com"># go-ndarray v0.7.0 — each step of the example, printed</span>
+<span class="c-cmd">$ go run</span> ./ndcheck
+<span class="c-out">m         Array(shape=[2 3], data=[0 1 2 3 4 5])
+m + row   Array(shape=[2 3], data=[10 21 32 13 24 35])
+m.T       Array(shape=[3 2], data=[0 3 1 4 2 5])
+sum(m,0)  Array(shape=[3], data=[3 5 7])
+m[:,0]    Array(shape=[2], data=[0 3])
+m @ b     Array(shape=[2 2], data=[10 13 28 40])</span></pre>
+    </div>
+  </div></section>
+
   <section id="features"><div class="wrap">
     <span class="eyebrow">Why go-ndarray</span>
     <h2>The n-dimensional array, <i>without</i> cgo.</h2>
-    <p class="lead">NumPy is the lingua franca of numerical computing, but in Go the choices are <code>gonum</code> (matrix-centric, amd64-only assembly) or a C extension. go-ndarray brings the <b>n-dimensional array</b> vocabulary — shapes, strided views, broadcasting, ufuncs, reductions and linear algebra — to Go with <b>no cgo</b>, cross-compiling to a static binary everywhere. The hot paths are multicore, and SIMD on amd64, arm64, ppc64le and loong64.</p>
+    <p class="lead">NumPy is the lingua franca of numerical computing, but in Go the choices are <code>gonum</code> (matrix-centric, amd64-only assembly) or a C extension. go-ndarray brings the <b>n-dimensional array</b> vocabulary — shapes, strided views, broadcasting, ufuncs, reductions and linear algebra — to Go with <b>no cgo</b>, cross-compiling to a static binary everywhere. The hot paths are multicore, and SIMD on amd64, arm64, ppc64le, loong64 and riscv64.</p>
     <div class="grid" id="quality">
       <div class="card"><div class="ico">🐹</div><h3>Pure Go</h3><p><code>CGO_ENABLED=0</code> across the org. No cgo, no BLAS shim.</p></div>
       <div class="card"><div class="ico">✅</div><h3>100% test coverage</h3><p>Gated in CI, differentially checked against <code>numpy</code>.</p></div>
       <div class="card"><div class="ico">🔢</div><h3>NumPy semantics</h3><p>Row-major strided arrays, <b>NumPy broadcasting</b>, and NumPy basic-indexing <code>Slice</code> returning strided views that share data.</p></div>
       <div class="card"><div class="ico">♻️</div><h3><code>Workspace</code> arena for loops</h3><p>Bind the inputs with <code>ws.Use</code>, compute as usual, <code>ws.Reset()</code> at the end of each pass: results stop costing the garbage collector anything. On a Zen 3, <code>x + y</code> on 1&nbsp;024 elements drops from 2.6 to 0.38&nbsp;µs (2.1× NumPy).</p></div>
-      <div class="card"><div class="ico">⚡</div><h3>SIMD on amd64, arm64, ppc64le &amp; loong64</h3><p>go-asmgen SIMD kernels on amd64 (SSE2, AVX2/FMA picked at run time), arm64 (NEON), ppc64le (VSX) and loong64 (LASX, when the CPU has it); riscv64, s390x and the 32-bit targets run the same pure-Go code those kernels are tested against.</p></div>
+      <div class="card"><div class="ico">⚡</div><h3>SIMD on amd64, arm64, ppc64le, loong64 &amp; riscv64</h3><p>go-asmgen SIMD kernels on amd64 (SSE2, AVX2/FMA picked at run time), arm64 (NEON), ppc64le (VSX) and loong64 (LASX, when the CPU has it) and riscv64 (RVV, when the CPU has it); riscv64, s390x and the 32-bit targets run the same pure-Go code those kernels are tested against.</p></div>
       <div class="card"><div class="ico">🎯</div><h3>Accurate <code>Exp</code>/<code>Log</code></h3><p>Ports of Arm's optimized-routines: worst 0.504 / 0.508 ULP against a 300-bit reference, and correct where Go's amd64 <code>math.Exp</code> returns +Inf (<a href="https://github.com/golang/go/issues/81995"><u>golang/go#81995</u></a>) and <code>math.Log</code> is wrong on subnormals (<a href="https://github.com/golang/go/issues/56600"><u>golang/go#56600</u></a>).</p></div>
       <div class="card"><div class="ico">🧪</div><h3>Multi-arch CI</h3><p>The suite runs on amd64, arm64 and 386 natively and on riscv64/loong64/ppc64le/s390x/arm under qemu, on Linux, macOS and Windows, and compiles for every <code>GOOS/GOARCH</code> pair Go supports; v0.2.0 was also run on real amd64, arm64, ppc64le, riscv64 and loong64 hardware.</p></div>
       <div class="card"><div class="ico">💎</div><h3>The cgo-free ndarray that was missing</h3><p>Ruby has no cgo-free ndarray (<code>Numo::NArray</code> and <code>NMatrix</code> are C extensions) and <code>gonum</code>'s optimized assembly is amd64-only. go-ndarray pairs a portable pure-Go core with multicore fan-out and SIMD kernels.</p></div>
       <div class="card"><div class="ico">⚖️</div><h3>BSD-3-Clause</h3><p><code>Exp</code> and <code>Log</code> are MIT-licensed ports of Arm's optimized-routines.</p></div>
     </div>
   </div></section>
 
+  <section id="api" style="padding-top:10px"><div class="wrap">
+    <span class="eyebrow">What the module offers</span>
+    <h2>{{ len .Site.Params.families }} families, <i>NumPy's names</i>.</h2>
+    <div class="grid">
+      {{ range .Site.Params.families }}
+      <div class="card"><h3>{{ .name }}</h3><p>{{ .what | markdownify }}</p></div>
+      {{ end }}
+    </div>
+  </div></section>
+
   <section id="perf" style="padding-top:10px"><div class="wrap">
     <div class="stats">
       <div><div class="n">100%</div><div class="l">test coverage, differentially checked against numpy</div></div>
@@ -100,8 +129,8 @@ <h2>What is here.</h2>
   <section id="eco" style="padding-top:6px"><div class="wrap">
     <div class="band">
       <h2>The cgo-free ndarray the Go and Ruby ecosystems lacked.</h2>
-      <p>No cgo, no BLAS shim. A portable pure-Go core, multicore, with SIMD kernels on amd64, arm64, ppc64le and loong64 and a <code>Workspace</code> arena that takes the garbage collector out of loops. Faster than NumPy on whole-array and row reductions, on large <code>Exp</code> and on <code>MatMul</code> against single-threaded BLAS, slower against 16-thread BLAS — the numbers are on the <a href="https://go-ndarray.github.io/docs/latest/performance/"><u>performance page</u></a>.</p>
-      <a class="btn btn-ghost" href="https://github.com/go-ndarray/ndarray">Read the source on GitHub →</a>
+      <p>No cgo, no BLAS shim. A portable pure-Go core, multicore, with SIMD kernels on amd64, arm64, ppc64le, loong64 and riscv64 and a <code>Workspace</code> arena that takes the garbage collector out of loops. Faster than NumPy on whole-array and row reductions, on large <code>Exp</code> and on <code>MatMul</code> against single-threaded BLAS, slower against 16-thread BLAS — the numbers are on the <a href="https://go-ndarray.github.io/docs/latest/performance/"><u>performance page</u></a>.</p>
+      <a class="btn btn-ghost" href="https://github.com/go-ndarray/ndarray">{{ partial "icons/github.html" . }}Read the source on GitHub →</a>
     </div>
   </div></section>
 

layouts/partials/icons/OCTICONS-LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 GitHub Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.