Style guide
One page that exercises every element the template can set.
Block elements
Level three
Level four
Level five
Level six
Bold, italic, and bold italic in one run. Struck through stays quiet. The morph target is resampled on every page load, which is the bug.
An inline link, a https://example.com/autolink, and a reference — Bishop.
Everything should be built top-down, except the first time.
Second paragraph inside the same quote.
- Unordered item
- Item with nesting
- Nested one level
- Nested two levels
- Nested one level
- Last item
- Ordered item
- Item with nesting
- Nested ordered
- Sibling
- Last item
- Point sprite
- A single
gl.POINTSvertex, discarded outside a unit disc. - Arcball
- Quaternion drag mapping screen delta to an axis-angle rotation.
Press Ctrl+C to abort; the program prints built 3 posts, 5 projects → _site/. H2O, and E = mc2. The GPU is saturated.
Show the derivation
A paragraph with code, then a list:
- one
- two
const q = qnorm(qmul(qaxis(0, 1, 0, 0.0022), q));
Code
Read the palette with getComputedStyle(document.documentElement).
def morph(a, b, t):
return a * (1 - t) + b * t # a $ in here is not math
docker run --rm -p 8000:8000 -e PORT=8000 --entrypoint granian olivares.cl --interface wsgi --host 0.0.0.0 --port 8000 server:app
Table
| Shape | Points | Morph target |
|---|---|---|
| Sphere | 4200 | Torus |
| Torus | 4200 | none |
| Helix | 4200 | none |
Media

Math
Inline: $\mathcal{L} = -\sum_k y_k \log \hat{y}_k$ with $w_i \in \mathbb{R}^{d}$.
$$ \hat{y} = \sigma\!\left(\sum_{i=1}^{n} w_i x_i + b\right) $$
A Push 3 costs \$2,000 — escaped, so KaTeX leaves it alone.
Footnotes and citations
Point sprites are cheaper than instanced quads.1
Smarty typography: straight quotes “become curly”, an em dash — like so, a numeric range 30–40, an ellipsis… and it’s got apostrophes.
Bishop remains the reference for the classical view 2, and the deep-learning successor updates it 3.
Dates
Shipped — hover for age.
-
Bishop, C. M. & Nasrabadi, N. M. Pattern recognition and machine learning. Springer. (2006) ↩
-
Goodfellow, I., Bengio, Y. & Courville, A. Deep learning. MIT press. (2016) ↩
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