add latex rst rendering, fix #12775

Author: carnaval

base/error.jl

@@ -38,7 +38,7 @@ systemerror(p, b::Bool) = b ? throw(Main.Base.SystemError(string(p))) : nothing
 assert(x) = x ? nothing : throw(Main.Base.AssertionError())
 macro assert(ex, msgs...)
     msg = isempty(msgs) ? ex : msgs[1]
-    if !isempty(msgs) && isa(msg, Expr)
+    if !isempty(msgs) && (isa(msg, Expr) || isa(msg, Symbol))
         # message is an expression needing evaluating
         msg = :(Main.Base.string($(esc(msg))))
     elseif isdefined(Main, :Base) && isdefined(Main.Base, :string)

base/markdown/render/rst.jl

@@ -52,6 +52,13 @@ function rst(io::IO, md::HorizontalRule)
     println(io, "–" ^ 5)
 end
 
+function rst(io::IO, l::LaTeX)
+    println(io, ".. math::\n")
+    for l in lines(l.formula)
+        println(io, "    ", l)
+    end
+end
+
 rst(io::IO, md) = writemime(io, "text/rst", md)
 
 # Inline elements

doc/genstdlib.jl

@@ -37,7 +37,7 @@ end
 torst(md) = isrst(md) ? flatten(md).content[1].code : tryrst(md)
 
 function translate(file)
-    @assert isfile(file)
+    @assert(isfile(file))
     ls = split(readall(file), "\n")[1:end-1]
     doccing = false
     func = nothing

doc/stdlib/math.rst

@@ -2858,28 +2858,26 @@ multi-threading. Use `FFTW.set_num_threads(np)` to use `np` threads.
 
 .. function:: fft(A [, dims])
 
-   Performs a multidimensional FFT of the array ``A``.  The optional ``dims``
-   argument specifies an iterable subset of dimensions (e.g. an integer,
-   range, tuple, or array) to transform along.  Most efficient if the
-   size of ``A`` along the transformed dimensions is a product of small
-   primes; see :func:`nextprod`.  See also :func:`plan_fft` for even
-   greater efficiency.
+   .. Docstring generated from Julia source
+
+   .. code-block:: julia
+
+       fft(A[, dims])
+
+   Performs a multidimensional FFT of the array ``A``\ .  The optional ``dims`` argument specifies an iterable subset of dimensions (e.g. an integer, range, tuple, or array) to transform along.  Most efficient if the size of ``A`` along the transformed dimensions is a product of small primes; see ``nextprod()``\ .  See also ``plan_fft()`` for even greater efficiency.
 
-   A one-dimensional FFT computes the one-dimensional discrete Fourier
-   transform (DFT) as defined by
+   A one-dimensional FFT computes the one-dimensional discrete Fourier transform (DFT) as defined by
 
    .. math::
 
-      \operatorname{DFT}(A)[k] = \sum_{n=1}^{\operatorname{length}(A)}
-      \exp\left(-i\frac{2\pi (n-1)(k-1)}{\operatorname{length}(A)} \right)
-      A[n].
+       \operatorname{DFT}(A)[k] =
+         \sum_{n=1}^{\operatorname{length}(A)}
+         \exp\left(-i\frac{2\pi
+         (n-1)(k-1)}{\operatorname{length}(A)} \right) A[n].
 
-   A multidimensional FFT simply performs this operation along each transformed
-   dimension of ``A``.
+   A multidimensional FFT simply performs this operation along each transformed dimension of ``A``\ .
 
-   Higher performance is usually possible with multi-threading. Use
-   `FFTW.set_num_threads(np)` to use `np` threads, if you have `np`
-   processors.
+   Higher performance is usually possible with multi-threading. Use ``FFTW.set_num_threads(np)`` to use ``np`` threads, if you have ``np`` processors.
 
 .. function:: fft!(A [, dims])