stat_connect_samplestat_manual_samplestat_summary_2d_sample /
stat_summary_hex_samplestat_summary_sample/`stat_summary_bin_sample``stat_unique_samplewalktoberstat_ellipse_samplestat_ecdf_samplestat_density_2d_samplestat_count_samplestat_bin_2d_sample/stat_bin_hex_samplegeom_contour_samplegeom_bin_2d_sample/
geom_bin_hex_sampleposition_stack_nestedposition_identity_dodge)
geom_point_samplegeom_sf_sample now accepts random variables to all
aesthetics and the subdivision was moved to the position argumentposition_subdivive had bug fixed and now also works
with sf objectsgeom_abline_sample/ geom_hline_sample /
geom_vline_samplegeom_smooth_samplegeom_spoke_samplegeom_segment_sample/geom_curvegeom_ribbon_sample/geom_areageom_boxplot_samplegeom_freqpolly_sample /
geom_histogram_samplegeom_dotplot_samplegeom_crossbar_sample /
geom_errorbar_sample / geom_linerange_sample /
geom_pointrange_samplegeom_qqline_sample /
geom_quantile_samplegeom_violin_samplegeom_raster_sample / geom_rect_sample /
geom_tile_sampleuncertain_faithfuld an uncertain version of
ggplot2::faithfuldThese functions are all heavily in development, and I cannot (and do not) guarantee their usability beyond the use cases presented in the example code. There are still some kinks to work out with the grouping solution. You are welcome to use them, but I would stick to the example cases for the next few weeks (don’t go crazy with any random fill or group aesthetics is all I will say). New additions to stats and geoms include:
geom_bar_sample, geom_col_sample and
stat_count_samplegeom_count_sample and stat_sum_samplegeom_jitter_samplegeom_density_sample and
stat_density_samplegeom_text_sample and
geom_label_samplegeom_polygon_samplegeom_rug_samplegeom_path_sample, geom_line_sample, and
geom_step_sampleWe also have the addition of a discrete position distribution scale:
scale_x_discrete_distribution &
scale_y_discrete_distributionAs we go through and replicate the ggplot2 examples, we
have been adding random versions of the ggplot2 data sets.
This will make it clear to the users how the package works, and
highlight that the uncertainty visualisation is a function of an
existing graphic.
smaller_diamonds is a subset of
ggplot2::diamondssmaller_uncertain_diamonds is a random variable version
of smaller_diamondsuncertain_mpg is a random variable version of
ggplot2::mpguncertain_mtcars is a random variableuncertain_economics and
uncertain_economics_longer are random variable version of
ggplot2::economicsscale_*_distribution to
scale_*_continuous_distribution
scale_*_discrete_distribution to allow plotting of discrete
random variablesgeom_point_sample and stat_sample
geom_point that allows a
distribution to be passed to any aestheticscale_x_distribution and
scale_y_distribution
n variable in geom_sf_sample has
changed to the times
n is used by some
ggplot2 functions as a parameter.times actually represents the sample size, while
n was the dimension of the grid (so the actual sample used
was \(n^2\))times will be used to
generate the subdivided gridInitial CRAN submission.
geom_sf_sample(): Visualise an sf object with random
variable for filltoy_temp: A toy data set that has the ambient
temperature as measured by a hypothetical citizen scientists in
Iowatoy_temp_dist: A toy data set of Iowa with an example
average temperature for each county