![[Experimental]](figures/lifecycle-experimental.svg)
Collection function spaces. Nested collections are allowed.
The interface and object storage model is experimental and may change.
Arguments
- x
list of function space objects, such as
fm_mesh_2d(), all of the same type.- ...
Currently unused
Value
A fm_collect or fm_collect_list object.
Elements of fm_collect:
- fun_spaces
fm_listof function space objects- fun_spaces_lengths
integerwith the length of thefun_spaceslist. For nested collections, a list with elements of the same type, including potentially nested lists for multiple nesting layers.- manifold
character; manifold type summary, obtained from the function spaces.
Details
Coordinate input is of the form of a list or tibble with columns
loc and index. The loc column contains the coordinates of the
evaluation points in the format of the contained spaces, and the index
column is a vector or matrix (for nested collections) that contains the
index of the function space in the collection to which each point belongs.
For nested collections, the index column is a matrix with one column per
nesting level.
See also
Other object creation and conversion:
fm_as_collect(),
fm_as_fm(),
fm_as_lattice_2d(),
fm_as_lattice_Nd(),
fm_as_mesh_1d(),
fm_as_mesh_2d(),
fm_as_mesh_3d(),
fm_as_segm(),
fm_as_sfc(),
fm_as_tensor(),
fm_lattice_2d(),
fm_lattice_Nd(),
fm_mesh_1d(),
fm_mesh_2d(),
fm_segm(),
fm_simplify(),
fm_tensor()
Examples
m <- fm_collect(list(
A = fmexample$mesh,
B = fmexample$mesh
))
m2 <- fm_as_collect(m)
m3 <- fm_as_collect_list(list(m, m))
c(fm_dof(m$fun_spaces[[1]]) + fm_dof(m$fun_spaces[[2]]), fm_dof(m))
#> [1] 584 584
fm_basis(m, loc = tibble::tibble(
loc = fmexample$loc_sf,
index = c(1, 1, 2, 2, 1, 2, 2, 1, 1, 2)
), full = TRUE)
#> fm_basis object
#> Projection matrix (A): 10-by-584
#> Valid evaluations (ok): 10 out of 10
#> Additional information:
fm_basis(m, loc = tibble::tibble(
loc = rbind(c(0, 0), c(0.1, 0.1)),
index = c("B", "A")
), full = TRUE)
#> fm_basis object
#> Projection matrix (A): 2-by-584
#> Valid evaluations (ok): 2 out of 2
#> Additional information:
fm_evaluator(m, loc = tibble::tibble(loc = cbind(0, 0), index = 2))
#> fm_evaluator object
#> proj:
#> fm_basis object
#> Projection matrix (A): 1-by-584
#> Valid evaluations (ok): 1 out of 1
#> Additional information:
#> Additional evaluator information:
names(fm_fem(m))
#> [1] "cc" "c0" "c1" "va" "ta" "g1" "g2"
fm_diameter(m)
#> [1] 10.51699
m_nested <- fm_collect(list(
A = fm_collect(list(
A1 = fmexample$mesh,
A2 = fmexample$mesh
)),
B = fm_collect(list(
B1 = fmexample$mesh,
B2 = fmexample$mesh,
B3 = fmexample$mesh
))
))
fm_evaluator(
m_nested,
loc = tibble::tibble(loc = cbind(0, 0), index = cbind(3,2))
)
#> fm_evaluator object
#> proj:
#> fm_basis object
#> Projection matrix (A): 1-by-1460
#> Valid evaluations (ok): 0 out of 1
#> Additional information:
#> Additional evaluator information:
names(fm_fem(m))
#> [1] "cc" "c0" "c1" "va" "ta" "g1" "g2"
fm_diameter(m)
#> [1] 10.51699
fm_bbox(m)
#> Bounding box: (-5.345477, 4.083580) x (-3.997839, 5.415519)
fm_diameter(m, multi = TRUE)
#> A B
#> 10.51699 10.51699
fm_bbox(m, multi = TRUE)
#> (-5.345477, 4.083580) x (-3.997839, 5.415519)
#> (-5.345477, 4.083580) x (-3.997839, 5.415519)
fm_int(m_nested, name = "geometry")
#> # A tibble: 1,460 × 5
#> weight .block geometry geometry.index[,1] [,2]
#> <dbl> <int> <POINT> <int> <int>
#> 1 0.349 1 Z (-5.180541 -0.8956538 0) 1 1
#> 2 0.254 1 Z (-4.924679 -1.465076 0) 1 1
#> 3 0.144 1 Z (-4.644074 -1.860313 0) 1 1
#> 4 0.361 1 Z (-4.242024 -2.255549 0) 1 1
#> 5 0.143 1 Z (-3.620028 -2.650785 0) 1 1
#> 6 0.449 1 Z (-3.202318 -2.82668 0) 1 1
#> 7 0.868 1 Z (-1.61974 -3.713512 0) 1 1
#> 8 0.742 1 Z (-0.8284506 -3.89906 0) 1 1
#> 9 0.198 1 Z (0.3584832 -3.997839 0) 1 1
#> 10 0.202 1 Z (0.7541278 -3.960901 0) 1 1
#> # ℹ 1,450 more rows
#> # ℹ 1 more variable: .block_origin <int[,1]>