Fix #143

src/shortestpaths/astar.jl

@@ -66,15 +66,15 @@ Compute a shortest path using the [A* search algorithm](http://en.wikipedia.org/
 - `s::Integer`: the source vertex
 - `t::Integer`: the target vertex
 - `distmx::AbstractMatrix`: an optional (possibly sparse) `n × n` matrix of edge weights. It is set to `weights(g)` by default (which itself falls back on [`Graphs.DefaultDistance`](@ref)).
-- `heuristic::Function`: an optional function mapping each vertex to a lower estimate of the remaining distance from `v` to `t`. It is set to `v -> 0` by default (which corresponds to Dijkstra's algorithm)
+- `heuristic`: an optional function mapping each vertex to a lower estimate of the remaining distance from `v` to `t`. It is set to `v -> 0` by default (which corresponds to Dijkstra's algorithm). Note that the heuristic values should have the same type as the edge weights!
 - `edgetype_to_return::Type{E}`: the eltype `E<:AbstractEdge` of the vector of edges returned. It is set to `edgetype(g)` by default. Note that the two-argument constructor `E(u, v)` must be defined, even for weighted edges: if it isn't, consider using `E = Graphs.SimpleEdge`.
 """
 function a_star(
     g::AbstractGraph{U},  # the g
     s::Integer,                       # the start vertex
     t::Integer,                       # the end vertex
     distmx::AbstractMatrix{T}=weights(g),
-    heuristic::Function=n -> zero(T),
+    heuristic=n -> zero(T),
     edgetype_to_return::Type{E}=edgetype(g),
 ) where {T,U,E<:AbstractEdge}
     # if we do checkbounds here, we can use @inbounds in a_star_impl!