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grass_db
and scale_fill_grass_c()
family.
This is an implementation of terra::map.pal()
, that is the
default palette for terra::plot()
(> 1.7.78
).autoplot.SpatRaster()
now uses also
grass_db
as the default palette.scale_fill_princess_c()
scale family.SpatVector
objects:
pivot_longer.SpatVector()
and
pivot_wider.SpatVector()
.fill.SpatVector()
.geom_spatraster_contour_text()
implemented on
top of isoband::isolines_grob()
.glimpse.SpatRaster()
and
glimpse.SpatVector()
now displays information using
?tibble::print.tbl_df
approach for the header and the
footer. The body is still displayed transposed as of
dplyr::glimpse()
. See
pillar::tbl_format_header()
and
pillar::tbl_format_footer()
for examples.as_sf()
converts a SpatVector
to a
sf
object with an additional tbl_df
class for
pretty printing.fortify.SpatRaster()
gains a new argument
pivot
that allows better integration with other
ggplot2 geoms when pivoting. This is a wrapper of
tidyr::pivot_longer()
.asia.tif
.as_sf()
(#124).tidyterra has been accepted on JOSS. Please use the
result of citation("tidyterra")
or the following
string:
Hernangómez, D. (2023). “Using the tidyverse with terra objects: the tidyterra package.” Journal of Open Source Software, 8(91), 5751. ISSN 2475-9066, https://doi.org/10.21105/joss.05751
Other changes on this version:
SpatRaster
objects with a color table
autoplot.SpatRaster()
can detect now
SpatRaster
objects with color tables.geom_spatraster()
can detect now
SpatRaster
objects with color tables.SpatRaster
objects with color
tables: scale_fill_coltab()
and rest of family scales
(colour
).coltab
of a
SpatRaster
.na.translate = FALSE
.na.value = "transparent"
(#120).glimpse.Spat()
with meta-information on type
of geometry, crs, etc.SpatVector
objects. The
improvements have been:
SpatVector
:
glimpse.SpatVector()
arrange.SpatVector()
distinct.SpatVector()
inner_join.SpatVector()
,
left_join.SpatVector()
,
right_join.SpatVector()
and
full_join.SpatVector()
semi_join.SpatVector()
and
anti_join.SpatVector()
summarise.SpatVector()
rowwise.SpatVector()
group_by.SpatVector()
,ungroup.SpatVector()
count.SpatVector()
,
tally.SpatVector()
bind_spat_cols()
, bind_spat_rows()
dplyr::group_by()
.sf::st_as_sf()
coercion. In fact coercion between object
classes is avoided as much as possible.glimpse.SpatRaster()
method for
SpatRaster
.as_spatvector()
as_sf()
is_grouped_spatvector()
pull_crs()
that returned "NA"
on sf
objects with any field equal to NA
(#74).scales_*
(#73) .autoplot.SpatVector()
,
autoplot.SpatRaster()
.
autoplot.SpatRaster()
now is smarter on identifying the
type of plot to produce. Can still be overridden with parameters.SpatRaster
and
SpatVector
objects: fortify.SpatRaster()
,
fortify.SpatVector()
.hypso.colors()
: "artic"
, "meyers"
and "nordisk-familjebok"
.scale_colour_*
.ggplot2::aes_string()
.geom_spatraster_contour()
and
geom_spatraster_contour_filled()
to the changes introduced
in ggplot2 (3.4.0), most notably the adoption of
linewidth = .2
, by default.geom_spatraster()
:
geom_spatraster()
is possible to avoid the
default fill
of the layer using
geom_spatraster(fill = NA)
or
geom_spatraster(aes(fill = NULL))
.aes(fill = ggplot2::after_stat())
now works on
geom_spatraster()
.aes()
and layersstat_spatraster()
.library
or require
is called. Messages on load
can be suppressed with
suppressPackageStartupMessages(library(tidyterra))
.geom_spatraster_rgb()
works with
facet_wrap()
(#35)extdata/volcano2.tif
using official DEM
information from New Zealand. Source: Auckland
LiDAR 1m DEM (2013).volcano2
dataset.slice_min()
and slice_max()
for SpatRaster
objects (#20). Also add a new parameter
na.rm
.scale_fill_hypso_c()
scale_fill_whitebox_c()
scale_fill_wiki_c()
scale_fill_cross_blended_c()
asia.tif
file on extdata
.data.tables
instead of
tibbles
.as_spatraster()
handles tibbles with characters and
factors.geom_spatraster()
and
geom_spatraster_rgb()
.pull()
transmute()
rename()
geom_spatraster_contour()
family.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.