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yutannihilation/dev_version_testthat_result.txt

Created July 5, 2020 14:06
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Test result of ggplot2 with the dev version of testthat
Raw
dev_version_testthat_result.txt
==> devtools::test()
Loading ggplot2
Testing ggplot2
✓ | OK F W S | Context
✓ | 1 | Adding plot elements
✓ | 17 | test-aes-calculated.r
✓ | 11 | Aesthetics (grouping) [0.4 s]
✓ | 10 | Aes - setting values [0.6 s]
✓ | 45 | Creating aesthetic mappings [1.3 s]
✓ | 10 | annotate [0.2 s]
✓ | 10 | Plot building [0.2 s]
✓ | 2 | rlang conditions [0.6 s]
✓ | 3 | test-coord-.r
✓ | 7 | coord_cartesian [0.4 s]
✓ | 4 | coord_map [0.5 s]
✓ | 19 | coord_polar [0.8 s]
✓ | 7 | coord_train [0.2 s]
✓ | 13 4 | coord_trans [1.2 s]
─────────────────────────────────────────
test-coord-transform.R:12: warning: warnings are generated when cord_trans() results in new infinite values
Transformation introduced infinite values in y-axis
Backtrace:
1. testthat::expect_warning(ggplot_gtable(ggplot_build(p)), "Transformation introduced infinite values in y-axis") tests/testthat/test-coord-transform.R:12:2
8. ggplot2::ggplot_gtable.ggplot_built(ggplot_build(p)) R/plot-build.r:158:2
9. base::Map(...) R/plot-build.r:168:2
10. base::mapply(FUN = f, ..., SIMPLIFY = FALSE)
12. l$draw_geom(d, layout) R/plot-build.r:168:2
13. ggplot2:::f(..., self = self) R/ggproto.r:176:11
14. self$geom$draw_layer(data, self$geom_params, layout, layout$coord) R/layer.r:377:4
15. ggplot2:::f(..., self = self) R/ggproto.r:176:11
16. base::lapply(...) R/geom-.r:84:4
17. ggplot2:::FUN(X[[i]], ...)
...
21. ggproto_parent(GeomRect, self)$draw_panel(...) R/geom-bar.r:142:4
22. ggplot2:::f(..., self = self) R/ggproto.r:176:11
23. base::lapply(...) R/geom-rect.r:42:6
24. ggplot2:::FUN(X[[i]], ...)
25. GeomPolygon$draw_panel(cbind(poly, aes), panel_params, coord) R/geom-rect.r:46:8
26. ggplot2:::f(...) R/ggproto.r:178:11
27. ggplot2::coord_munch(coord, data, panel_params) R/geom-polygon.r:113:4
28. coord$transform(munched, range) R/coord-munch.r:37:2
29. ggplot2:::f(..., self = self) R/ggproto.r:176:11
30. ggplot2::warn_new_infinites(data$y, new_data$y, "y") R/coord-transform.r:133:4
test-coord-transform.R:12: warning: warnings are generated when cord_trans() results in new infinite values
Transformation introduced infinite values in y-axis
Backtrace:
1. testthat::expect_warning(ggplot_gtable(ggplot_build(p)), "Transformation introduced infinite values in y-axis") tests/testthat/test-coord-transform.R:12:2
8. ggplot2::ggplot_gtable.ggplot_built(ggplot_build(p)) R/plot-build.r:158:2
9. base::Map(...) R/plot-build.r:168:2
10. base::mapply(FUN = f, ..., SIMPLIFY = FALSE)
12. l$draw_geom(d, layout) R/plot-build.r:168:2
13. ggplot2:::f(..., self = self) R/ggproto.r:176:11
14. self$geom$draw_layer(data, self$geom_params, layout, layout$coord) R/layer.r:377:4
15. ggplot2:::f(..., self = self) R/ggproto.r:176:11
16. base::lapply(...) R/geom-.r:84:4
17. ggplot2:::FUN(X[[i]], ...)
...
21. ggproto_parent(GeomRect, self)$draw_panel(...) R/geom-bar.r:142:4
22. ggplot2:::f(..., self = self) R/ggproto.r:176:11
23. base::lapply(...) R/geom-rect.r:42:6
24. ggplot2:::FUN(X[[i]], ...)
25. GeomPolygon$draw_panel(cbind(poly, aes), panel_params, coord) R/geom-rect.r:46:8
26. ggplot2:::f(...) R/ggproto.r:178:11
27. ggplot2::coord_munch(coord, data, panel_params) R/geom-polygon.r:113:4
28. coord$transform(munched, range) R/coord-munch.r:37:2
29. ggplot2:::f(..., self = self) R/ggproto.r:176:11
30. ggplot2::warn_new_infinites(data$y, new_data$y, "y") R/coord-transform.r:133:4
test-coord-transform.R:12: warning: warnings are generated when cord_trans() results in new infinite values
Transformation introduced infinite values in y-axis
Backtrace:
1. testthat::expect_warning(ggplot_gtable(ggplot_build(p)), "Transformation introduced infinite values in y-axis") tests/testthat/test-coord-transform.R:12:2
8. ggplot2::ggplot_gtable.ggplot_built(ggplot_build(p)) R/plot-build.r:158:2
9. base::Map(...) R/plot-build.r:168:2
10. base::mapply(FUN = f, ..., SIMPLIFY = FALSE)
12. l$draw_geom(d, layout) R/plot-build.r:168:2
13. ggplot2:::f(..., self = self) R/ggproto.r:176:11
14. self$geom$draw_layer(data, self$geom_params, layout, layout$coord) R/layer.r:377:4
15. ggplot2:::f(..., self = self) R/ggproto.r:176:11
16. base::lapply(...) R/geom-.r:84:4
17. ggplot2:::FUN(X[[i]], ...)
...
21. ggproto_parent(GeomRect, self)$draw_panel(...) R/geom-bar.r:142:4
22. ggplot2:::f(..., self = self) R/ggproto.r:176:11
23. base::lapply(...) R/geom-rect.r:42:6
24. ggplot2:::FUN(X[[i]], ...)
25. GeomPolygon$draw_panel(cbind(poly, aes), panel_params, coord) R/geom-rect.r:46:8
26. ggplot2:::f(...) R/ggproto.r:178:11
27. ggplot2::coord_munch(coord, data, panel_params) R/geom-polygon.r:113:4
28. coord$transform(munched, range) R/coord-munch.r:37:2
29. ggplot2:::f(..., self = self) R/ggproto.r:176:11
30. ggplot2::warn_new_infinites(data$y, new_data$y, "y") R/coord-transform.r:133:4
test-coord-transform.R:12: warning: warnings are generated when cord_trans() results in new infinite values
Transformation introduced infinite values in y-axis
Backtrace:
1. testthat::expect_warning(ggplot_gtable(ggplot_build(p)), "Transformation introduced infinite values in y-axis") tests/testthat/test-coord-transform.R:12:2
8. ggplot2::ggplot_gtable.ggplot_built(ggplot_build(p)) R/plot-build.r:158:2
9. base::Map(...) R/plot-build.r:168:2
10. base::mapply(FUN = f, ..., SIMPLIFY = FALSE)
12. l$draw_geom(d, layout) R/plot-build.r:168:2
13. ggplot2:::f(..., self = self) R/ggproto.r:176:11
14. self$geom$draw_layer(data, self$geom_params, layout, layout$coord) R/layer.r:377:4
15. ggplot2:::f(..., self = self) R/ggproto.r:176:11
16. base::lapply(...) R/geom-.r:84:4
17. ggplot2:::FUN(X[[i]], ...)
...
21. ggproto_parent(GeomRect, self)$draw_panel(...) R/geom-bar.r:142:4
22. ggplot2:::f(..., self = self) R/ggproto.r:176:11
23. base::lapply(...) R/geom-rect.r:42:6
24. ggplot2:::FUN(X[[i]], ...)
25. GeomPolygon$draw_panel(cbind(poly, aes), panel_params, coord) R/geom-rect.r:46:8
26. ggplot2:::f(...) R/ggproto.r:178:11
27. ggplot2::coord_munch(coord, data, panel_params) R/geom-polygon.r:113:4
28. coord$transform(munched, range) R/coord-munch.r:37:2
29. ggplot2:::f(..., self = self) R/ggproto.r:176:11
30. ggplot2::warn_new_infinites(data$y, new_data$y, "y") R/coord-transform.r:133:4
─────────────────────────────────────────
✓ | 29 | coord_sf [2.3 s]
✓ | 4 1 | Data
─────────────────────────────────────────
test-data.r:13: warning: stringsAsFactors doesn't affect results
'options(stringsAsFactors = TRUE)' is deprecated and will be disabled
Backtrace:
1. base::options(stringsAsFactors = TRUE) tests/testthat/test-data.r:13:4
─────────────────────────────────────────
✓ | 2 | Legend key glyphs [0.6 s]
✓ | 23 | Empty data [0.6 s]
✓ | 2 | error
✓ | 86 | Facetting [1.2 s]
✓ | 21 | Facet Labels [0.8 s]
✓ | 38 | Facetting (layout) [0.2 s]
✓ | 39 | Facetting (mapping) [0.5 s]
✓ | 10 | Facet Strips [1.2 s]
✓ | 2 | Fortify [0.1 s]
✓ | 79 | function-args [0.2 s]
✓ | 4 | geom_bar [0.1 s]
✓ | 18 | geom_boxplot [0.8 s]
✓ | 5 | geom_col [0.1 s]
✓ | 43 | geom_dotplot [5.7 s]
✓ | 3 | geom_freqpoly
✓ | 5 | geom_hex [0.1 s]
✓ | 18 | geom-hline-vline-abline [0.7 s]
✓ | 15 | geom-path [0.7 s]
✓ | 6 | geom-point
✓ | 1 | geom-polygon [0.1 s]
✓ | 3 | geom-quantile [0.2 s]
✓ | 10 | geom-raster [1.7 s]
✓ | 17 | geom_ribbon [0.2 s]
✓ | 13 | geom_rug [0.1 s]
✓ | 10 | geom_rule [0.2 s]
✓ | 29 | geom-sf [1.3 s]
✓ | 12 | geom_smooth [0.6 s]
✓ | 4 | geom_text
✓ | 7 | geom_tile
✓ | 21 | geom_violin [2.5 s]
✓ | 1 | ggproto
✓ | 26 | ggsave [0.3 s]
✓ | 2 | Grid utilites
✓ | 81 1 | Guides [8.6 s]
─────────────────────────────────────────
test-guides.R:84: warning: a warning is generated when more than one position guide is drawn at a location
guide_axis(): Discarding guide on merge. Do you have more than one guide with the same position?
Backtrace:
1. testthat::expect_warning(ggplot_gtable(built), "Discarding guide") tests/testthat/test-guides.R:84:2
8. ggplot2::ggplot_gtable.ggplot_built(built) R/plot-build.r:158:2
9. layout$render(geom_grobs, data, theme, plot$labels) R/plot-build.r:170:2
10. ggplot2:::f(..., self = self) R/ggproto.r:176:11
11. self$coord$labels(...) R/layout.R:107:4
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. base::lapply(...) R/coord-cartesian-.r:158:4
14. ggplot2:::FUN(X[[i]], ...)
15. ggplot2::panel_guide_label(...) R/coord-cartesian-.r:167:8
17. ggplot2::guide_for_position(guides, position) R/utilities.r:11:2
18. base::Reduce(guide_merge, guides[order(guides_order)]) R/coord-cartesian-.r:236:2
20. ggplot2::guide_merge.axis(init, x[[i]]) R/guides-.r:339:15
─────────────────────────────────────────
✓ | 23 | Labels [0.4 s]
✓ | 15 | Layer [0.1 s]
✓ | 53 | Munch [0.1 s]
✓ | 13 | Performance related alternatives
✓ | 60 | plot summary API [0.4 s]
✓ | 9 | position_dodge2 [0.2 s]
✓ | 24 | position_nudge [0.1 s]
✓ | 11 | position_stack [0.3 s]
✓ | 2 | position_dodge
✓ | 7 | qplot
✓ | 5 | range
✓ | 1 | data.frame binding
✓ | 15 4 | sanitise_dim
─────────────────────────────────────────
test-sanitise-dim.r:16: warning: sanitise_dim returns the first element or NULL for non-positive integer inputs, with appropriate warnings
`n2` is missing or less than 1 and will be treated as NULL.
Backtrace:
1. testthat::expect_warning(sanitise_dim(n2), "Only the first value of `n2` will be used.") tests/testthat/test-sanitise-dim.r:16:2
7. ggplot2::sanitise_dim(n2)
test-sanitise-dim.r:17: warning: sanitise_dim returns the first element or NULL for non-positive integer inputs, with appropriate warnings
Only the first value of `n2` will be used.
Backtrace:
1. testthat::expect_warning(sanitise_dim(n2), "`n2` is missing or less than 1 and will be treated as NULL.") tests/testthat/test-sanitise-dim.r:17:2
7. ggplot2::sanitise_dim(n2)
test-sanitise-dim.r:32: warning: sanitise_dim returns a positive integer or NULL for non-integer inputs, with appropriate warnings
`n2` is missing or less than 1 and will be treated as NULL.
Backtrace:
1. testthat::expect_warning(sanitise_dim(n2), "Coercing `n2` to be an integer.") tests/testthat/test-sanitise-dim.r:32:2
7. ggplot2::sanitise_dim(n2)
test-sanitise-dim.r:33: warning: sanitise_dim returns a positive integer or NULL for non-integer inputs, with appropriate warnings
Coercing `n2` to be an integer.
Backtrace:
1. testthat::expect_warning(sanitise_dim(n2), "`n2` is missing or less than 1 and will be treated as NULL.") tests/testthat/test-sanitise-dim.r:33:2
7. ggplot2::sanitise_dim(n2)
─────────────────────────────────────────
✓ | 2 | scale_brewer
✓ | 10 | scale_date [0.2 s]
✓ | 33 | scale_discrete [0.4 s]
✓ | 23 | scale-expansion
✓ | 1 | scale_gradient
✓ | 15 | scale_manual [0.3 s]
✓ | 4 | test-scale-type.R
✓ | 8 | scale_date [1.0 s]
✓ | 108 | Scales: breaks and labels [1.7 s]
✓ | 74 | Scales [0.7 s]
✓ | 39 | sec-axis [1.4 s]
✓ | 43 | stat_bin/stat_count [1.2 s]
✓ | 7 | stat_bin2d [0.1 s]
✓ | 3 | stat_boxplot
✓ | 17 4 | stat-contour [0.4 s]
─────────────────────────────────────────
test-stat-contour.R:7: warning: a warning is issued when there is more than one z per x+y
no non-missing arguments to min; returning Inf
Backtrace:
1. testthat::expect_warning(ggplot_build(p), "Zero contours were generated") tests/testthat/test-stat-contour.R:7:2
8. ggplot2::ggplot_build.ggplot(p) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
29. scales::rescale_max(path_df$level) R/stat-contour.r:101:4
30. base::range(x, na.rm = TRUE)
test-stat-contour.R:7: warning: a warning is issued when there is more than one z per x+y
no non-missing arguments to max; returning -Inf
Backtrace:
1. testthat::expect_warning(ggplot_build(p), "Zero contours were generated") tests/testthat/test-stat-contour.R:7:2
8. ggplot2::ggplot_build.ggplot(p) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
29. scales::rescale_max(path_df$level) R/stat-contour.r:101:4
30. base::range(x, na.rm = TRUE)
test-stat-contour.R:13: warning: contouring sparse data results in a warning
no non-missing arguments to min; returning Inf
Backtrace:
1. testthat::expect_warning(ggplot_build(p), "Zero contours were generated") tests/testthat/test-stat-contour.R:13:2
8. ggplot2::ggplot_build.ggplot(p) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
29. scales::rescale_max(path_df$level) R/stat-contour.r:101:4
30. base::range(x, na.rm = TRUE)
test-stat-contour.R:13: warning: contouring sparse data results in a warning
no non-missing arguments to max; returning -Inf
Backtrace:
1. testthat::expect_warning(ggplot_build(p), "Zero contours were generated") tests/testthat/test-stat-contour.R:13:2
8. ggplot2::ggplot_build.ggplot(p) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
29. scales::rescale_max(path_df$level) R/stat-contour.r:101:4
30. base::range(x, na.rm = TRUE)
─────────────────────────────────────────
✓ | 8 | stat_density [0.5 s]
✓ | 43 | stat_density_2d [0.9 s]
✓ | 2 | stat_ellipsis
✓ | 52 | stat_function [0.4 s]
✓ | 1 | stat_hex
✓ | 5 | stat_sf_coordinates
✓ | 24 | stat_sum [0.5 s]
✓ | 4 | stat_summary [0.2 s]
✓ | 4 13 | Stats [0.1 s]
─────────────────────────────────────────
test-stats.r:11: warning: plot succeeds even if some computation fails
span too small. fewer data values than degrees of freedom.
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
at 0.995
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
radius 2.5e-05
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
all data on boundary of neighborhood. make span bigger
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
pseudoinverse used at 0.995
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
neighborhood radius 0.005
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
reciprocal condition number 1
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
at 2.005
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
radius 2.5e-05
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
all data on boundary of neighborhood. make span bigger
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
There are other near singularities as well. 2.5e-05
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
zero-width neighborhood. make span bigger
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
test-stats.r:11: warning: plot succeeds even if some computation fails
zero-width neighborhood. make span bigger
Backtrace:
1. testthat::expect_warning(b2 <- ggplot_build(p2), "Computation failed") tests/testthat/test-stats.r:11:2
8. ggplot2::ggplot_build.ggplot(p2) R/plot-build.r:24:2
9. ggplot2:::by_layer(function(l, d) l$compute_statistic(d, layout)) R/plot-build.r:72:2
10. ggplot2:::f(l = layers[[i]], d = data[[i]]) R/plot-build.r:42:6
11. l$compute_statistic(d, layout) R/plot-build.r:72:2
12. ggplot2:::f(..., self = self) R/ggproto.r:176:11
13. self$stat$compute_layer(data, params, layout) R/layer.r:279:4
14. ggplot2:::f(..., self = self) R/ggproto.r:176:11
15. ggplot2::dapply(...) R/stat-.r:98:4
16. ggplot2:::apply_fun(df) R/compat-plyr.R:377:4
17. ggplot2:::fun(x, ...) R/compat-plyr.R:364:4
24. ggplot2:::f(..., self = self) R/ggproto.r:176:11
25. base::lapply(...) R/stat-.r:111:4
26. ggplot2:::FUN(X[[i]], ...)
27. self$compute_group(data = group, scales = scales, ...) R/stat-.r:112:6
28. ggplot2:::f(...) R/ggproto.r:178:11
31. stats:::simpleLoess(...)
─────────────────────────────────────────
✓ | 153 | Themes [4.9 s]
✓ | 28 | Utilities
✓ | 3 | Viridis
✓ | 1 | zzz
══ Results ═══════════════════════════════════════════════════════════════════════
Duration: 56.5 s
OK: 1801
Failed: 0
Warnings: 27
Skipped: 0
#> 0 1
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