Documentation for asciidoctor-html asciidoctor-html

Part 3

Numbered Blocks

asciidoctor-html automatically adds a number of the form $chapnum.$blocknum to the block contexts example, image, and table. Each of these has a unique counter. You have already seen numbered example blocks used to typeset Part 2. There, you may have noticed that the list of figures Figure 2.1 is also numbered.

An ordered list with the figlist style shares a counter with the image counter.

The block contexts stem and listing get numbered only when the numbered option is set. They each have a unique counter.

Reference Table

For each numbered block, automatic reference text gets generated. The details are in Table 3.1.

Table 3.1Numbered block contexts, counters and reference text
Context Numbered Counter Reference Text
example automatic thm E.g., “Example 3.1” (default)
Depends on block style if set
(see Example Blocks)
image automatic fig E.g., “Figure 3.1”
table automatic tbl E.g., “Table 3.1”
olist when style is figlist fig E.g., “Figure 3.2”
stem with numbered option eqn E.g., “(3.1)”
listing with numbered option ltg E.g., “Listing 3.1”

Example Blocks

Example blocks play the role of amsthm LaTeX environments.

Theorems and other mathematical blocks

You can set a custom name and reference text on an example block by setting the block’s style to the desired text (in lowercase). In Definition 3.1 we used [definition].

Definition 3.1UMP test[2, Definition 6.1]

A test $T_\ast$ of size $\alpha$ is a uniformly most powerful (UMP) test if and only if $\beta_{T_\ast}(P)\geq\beta_T(P)$ for all $P\in\mathcal{P}_1$ and $T$ of level $\alpha$.

You can add a bracketed title suffix by setting the title-suffix attribute. This is perfect for including citations.

The styles theorem, proposition, lemma, and corollary on example blocks get a blue colour, and the algorithm style gets an orange colour as in Algorithm 2.6.

Lemma 3.2[2, Lemma 6.3]

Suppose that the distribution of $X$ is in a parametric family $\mathcal{P}$ indexed by a real-valued $\theta$ and that $\mathcal{P}$ has monotone likelihood ratio in $Y(X)$. If $\psi$ is a nondecreasing function of $Y$, then $g(\theta) = E\left[\psi(Y)\right]$ is a nondecreasing function of $\theta$.

You can typeset a proof using an open block with the proof style.

Proof

See [2, p.398].

You can make any open block collapsible with the collapsible option. This may be useful for hiding solutions to exercises for instance.

Example Listings

You may find it useful for your listings to share the same counter as examples. To achieve this, nest a listing inside an example block with style listing, and put the listing title on the example as we have done in Listing 3.3.

Listing 3.3Hello World program
def say_hi():
  """Says hello to the world"""
  print("Hello World!")

Unnumbered Example Blocks

Finally, you may wish to have a block styled like an example, but without a number.

There is almost never a good reason to have an unnumbered example, theorem, algorithm, listing, etc. The numbering helps the reader understand where your block is situated on the page. For example, if you are at Proposition 2.1, and you see a reference to Lemma 2.5, you know that is further ahead of where you are, and not something you should already have come across.

To typeset a block that looks like an unnumbered example, use an open block with the example role. And if you want one of the example variant styles, additionally add a role of the form example-$variant, such as example-algorithm as we have used below.

General descent method[1, Algorithm 9.1]
  • given a starting point $x\in\dom f$.

  • repeat

    1. 1.

      Determine a descent direction $\Delta x$.

    2. 2.

      Line search. Choose a step size $t > 0$.

    3. 3.

      Update. $x\gets x + t\Delta x$.

  • until stopping criterion is satisfied.

Above, we added the unmarked option to the top-level list. Use this option if you want to hide the markers in an unordered list.

References

  1. [1]

    Boyd, S. and Vandenberghe, L. (2004) Convex Optimization. Cambridge: Cambridge University Press.

  2. [2]

    Shao, J. (2007) Mathematical Statistics. 2nd ed. New York, NY: Springer.