Calculate matrix of pair-wise travel times between points.

`dodgr_times(graph, from = NULL, to = NULL, shortest = FALSE, heap = "BHeap")`

- graph
A

`dodgr`

network returned from the weight_streetnet function using a network obtained with the osmdata`osmdata_sc`

function, possibly contracted with dodgr_contract_graph.- from
Vector or matrix of points

**from**which route distances are to be calculated (see Notes)- to
Vector or matrix of points

**to**which route distances are to be calculated (see Notes)- shortest
If

`TRUE`

, calculate times along the*shortest*rather than fastest paths.- heap
Type of heap to use in priority queue. Options include Fibonacci Heap (default;

`FHeap`

), Binary Heap (`BHeap`

),`Trinomial Heap (`

TriHeap`), Extended Trinomial Heap (`

TriHeapExt`, and 2-3 Heap (`

Heap23`).

square matrix of distances between nodes

`graph`

must minimally contain three columns of `from`

,
`to`

, `dist`

. If an additional column named `weight`

or
`wt`

is present, shortest paths are calculated according to values
specified in that column; otherwise according to `dist`

values. Either
way, final distances between `from`

and `to`

points are calculated
by default according to values of `dist`

. That is, paths between any pair of
points will be calculated according to the minimal total sum of `weight`

values (if present), while reported distances will be total sums of `dist`

values.

For street networks produced with weight_streetnet, distances may also
be calculated along the *fastest* routes with the `shortest = FALSE`

option. Graphs must in this case have columns of `time`

and `time_weighted`

.
Note that the fastest routes will only be approximate when derived from
sf-format data generated with the osmdata function
`osmdata_sf()`

, and will be much more accurate when derived from `sc`

-format
data generated with `osmdata_sc()`

. See weight_streetnet for details.

The `from`

and `to`

columns of `graph`

may be either single
columns of numeric or character values specifying the numbers or names of
graph vertices, or combinations to two columns specifying geographical
(longitude and latitude) coordinates. In the latter case, almost any sensible
combination of names will be accepted (for example, `fromx, fromy`

,
`from_x, from_y`

, or `fr_lat, fr_lon`

.)

`from`

and `to`

values can be either two-column matrices of
equivalent of longitude and latitude coordinates, or else single columns
precisely matching node numbers or names given in `graph$from`

or
`graph$to`

. If `to`

is `NULL`

, pairwise distances are calculated
between all points specified in `from`

. If both `from`

and `to`

are `NULL`

,
pairwise distances are calculated between all nodes in `graph`

.

Calculations in parallel (`parallel = TRUE`

) ought very generally be
advantageous. For small graphs, calculating distances in parallel is likely
to offer relatively little gain in speed, but increases from parallel
computation will generally markedly increase with increasing graph sizes.
By default, parallel computation uses the maximal number of available cores
or threads. This number can be reduced by specifying a value via
`RcppParallel::setThreadOptions (numThreads = <desired_number>)`

. Parallel
calculations are, however, not able to be interrupted (for example, by
`Ctrl-C`

), and can only be stopped by killing the R process.

Other distances:
`dodgr_distances()`

,
`dodgr_dists_categorical()`

,
`dodgr_dists()`

,
`dodgr_flows_aggregate()`

,
`dodgr_flows_disperse()`

,
`dodgr_flows_si()`

,
`dodgr_isochrones()`

,
`dodgr_isodists()`

,
`dodgr_isoverts()`

,
`dodgr_paths()`

```
# A simple graph
graph <- data.frame (
from = c ("A", "B", "B", "B", "C", "C", "D", "D"),
to = c ("B", "A", "C", "D", "B", "D", "C", "A"),
d = c (1, 2, 1, 3, 2, 1, 2, 1)
)
dodgr_dists (graph)
#> A B C D
#> A 0 1 2 3
#> B 2 0 1 2
#> C 2 2 0 1
#> D 1 2 2 0
# A larger example from the included [hampi()] data.
graph <- weight_streetnet (hampi)
from <- sample (graph$from_id, size = 100)
to <- sample (graph$to_id, size = 50)
d <- dodgr_dists (graph, from = from, to = to)
# d is a 100-by-50 matrix of distances between `from` and `to`
if (FALSE) {
# a more complex street network example, thanks to @chrijo; see
# https://github.com/ATFutures/dodgr/issues/47
xy <- rbind (
c (7.005994, 51.45774), # limbeckerplatz 1 essen germany
c (7.012874, 51.45041)
) # hauptbahnhof essen germany
xy <- data.frame (lon = xy [, 1], lat = xy [, 2])
essen <- dodgr_streetnet (pts = xy, expand = 0.2, quiet = FALSE)
graph <- weight_streetnet (essen, wt_profile = "foot")
d <- dodgr_dists (graph, from = xy, to = xy)
# First reason why this does not work is because the graph has multiple,
# disconnected components.
table (graph$component)
# reduce to largest connected component, which is always number 1
graph <- graph [which (graph$component == 1), ]
d <- dodgr_dists (graph, from = xy, to = xy)
# should work, but even then note that
table (essen$level)
# There are parts of the network on different building levels (because of
# shopping malls and the like). These may or may not be connected, so it may
# be necessary to filter out particular levels
index <- which (!(essen$level == "-1" | essen$level == "1")) # for example
library (sf) # needed for following sub-select operation
essen <- essen [index, ]
graph <- weight_streetnet (essen, wt_profile = "foot")
graph <- graph [which (graph$component == 1), ]
d <- dodgr_dists (graph, from = xy, to = xy)
}
```