CRAN Package Check Results for Package cubble

Last updated on 2024-06-29 15:50:36 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.3.0 14.31 164.63 178.94 ERROR
r-devel-linux-x86_64-debian-gcc 0.3.0 9.16 137.48 146.64 ERROR
r-devel-linux-x86_64-fedora-clang 0.3.0 231.29 ERROR
r-devel-linux-x86_64-fedora-gcc 0.3.0 234.84 ERROR
r-devel-windows-x86_64 0.3.0 13.00 145.00 158.00 OK
r-patched-linux-x86_64 0.3.0 13.15 168.39 181.54 OK
r-release-linux-x86_64 0.3.0 10.69 171.20 181.89 OK
r-release-macos-arm64 0.3.0 70.00 OK
r-release-macos-x86_64 0.3.0 127.00 OK
r-release-windows-x86_64 0.3.0 14.00 142.00 156.00 OK
r-oldrel-macos-arm64 0.3.0 67.00 OK
r-oldrel-macos-x86_64 0.3.0 171.00 OK
r-oldrel-windows-x86_64 0.3.0 16.00 185.00 201.00 OK

Additional issues

M1mac

Check Details

Version: 0.3.0
Check: examples
Result: ERROR Running examples in ‘cubble-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: arrange.temporal_cubble_df > ### Title: 'dplyr' methods > ### Aliases: arrange.temporal_cubble_df select.spatial_cubble_df > ### select.temporal_cubble_df group_by.spatial_cubble_df > ### group_by.temporal_cubble_df ungroup.spatial_cubble_df > ### ungroup.temporal_cubble_df summarise.spatial_cubble_df > ### summarise.temporal_cubble_df rename.spatial_cubble_df > ### rename.temporal_cubble_df bind_rows.temporal_cubble_df > ### bind_cols.spatial_cubble_df bind_cols.temporal_cubble_df > ### rowwise.spatial_cubble_df rowwise.temporal_cubble_df > ### dplyr_col_modify.cubble_df dplyr_row_slice.spatial_cubble_df > ### dplyr_row_slice.temporal_cubble_df > ### dplyr_reconstruct.spatial_cubble_df > ### dplyr_reconstruct.temporal_cubble_df mutate.spatial_cubble_df > ### filter.spatial_cubble_df arrange.spatial_cubble_df > > ### ** Examples > > library(dplyr) Attaching package: ‘dplyr’ The following objects are masked from ‘package:stats’: filter, lag The following objects are masked from ‘package:base’: intersect, setdiff, setequal, union > cb_nested <- climate_mel > cb_long <- face_temporal(climate_mel) > > # filter - currently filter.spatial_cubble_df, dply_row_slice > cb_nested %>% filter(elev > 40) # cubble: key: id [2], index: date, nested form # spatial: [144.8321, -37.7276, 144.9066, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% filter(prcp > 0) # cubble: key: id [3], index: date, long form # temporal: 2020-01-05 -- 2020-01-07 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-05 18 16.1 12.5 2 ASN00086038 2020-01-06 104 17.5 11.1 3 ASN00086038 2020-01-07 14 20.7 12.1 4 ASN00086077 2020-01-05 20 17.4 12.7 5 ASN00086077 2020-01-06 122 17.8 11.8 6 ASN00086077 2020-01-07 6 20.3 12.6 7 ASN00086282 2020-01-05 16 15.7 12 8 ASN00086282 2020-01-06 90 17.3 11.5 9 ASN00086282 2020-01-07 6 19.9 11.8 > > # mutate - curerntly mutate.spatial_cubble_df, dply_col_modify > cb_nested %>% mutate(elev2 = elev + 10) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts elev2 <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <dbl> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 88.4 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 22.1 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> 123. > cb_long %>% mutate(prcp2 = prcp + 10) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin prcp2 <chr> <date> <dbl> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 10 2 ASN00086038 2020-01-02 0 26.3 12.2 10 3 ASN00086038 2020-01-03 0 34.5 12.7 10 4 ASN00086038 2020-01-04 0 29.3 18.8 10 5 ASN00086038 2020-01-05 18 16.1 12.5 28 6 ASN00086038 2020-01-06 104 17.5 11.1 114 7 ASN00086038 2020-01-07 14 20.7 12.1 24 8 ASN00086038 2020-01-08 0 26.4 16.4 10 9 ASN00086038 2020-01-09 0 33.1 17.4 10 10 ASN00086038 2020-01-10 0 34 19.6 10 # ℹ 20 more rows > > # arrange - currently arrange.spatial_cubble_df, arrange.temporal_cubble_df > cb_nested %>% arrange(wmo_id) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> > cb_long %>% arrange(prcp) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-08 0 26.4 16.4 6 ASN00086038 2020-01-09 0 33.1 17.4 7 ASN00086038 2020-01-10 0 34 19.6 8 ASN00086077 2020-01-01 0 24.7 10 9 ASN00086077 2020-01-02 0 24.8 11.8 10 ASN00086077 2020-01-03 0 35 12.2 # ℹ 20 more rows > > # summarise - summarise.spatial_cubble_df, summarise.temporal_cubble_df > cb_long %>% + group_by(first_5 = ifelse(lubridate::day(date) <=5, 1, 2 )) %>% + summarise(tmax = mean(tmax)) # cubble: key: id [3], index: first_5, long form, groups: first_5 [2] # temporal: 1 -- 2 [1], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] first_5 id tmax <dbl> <chr> <dbl> 1 1 ASN00086038 26.6 2 1 ASN00086077 25.5 3 1 ASN00086282 27.1 4 2 ASN00086038 26.3 5 2 ASN00086077 25.9 6 2 ASN00086282 26.2 > cb_long %>% + mutate(first_5 = ifelse(lubridate::day(date) <=5, 1, 2)) %>% + summarise(t = mean(tmax), .by = first_5) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date t <chr> <date> <dbl> 1 ASN00086038 2020-01-01 26.8 2 ASN00086038 2020-01-02 26.3 3 ASN00086038 2020-01-03 34.5 4 ASN00086038 2020-01-04 29.3 5 ASN00086038 2020-01-05 16.1 6 ASN00086038 2020-01-06 17.5 7 ASN00086038 2020-01-07 20.7 8 ASN00086038 2020-01-08 26.4 9 ASN00086038 2020-01-09 33.1 10 ASN00086038 2020-01-10 34 # ℹ 20 more rows > > # select - select.spatial_cubble_df, select.temporal_cubble_df > cb_nested %>% select(name) ℹ Missing attribute `id`, `long`, `lat`, and `ts`, add it back. # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat ts name <chr> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 <tibble [10 × 4]> moorabbin airport 3 ASN00086282 145. -37.7 <tibble [10 × 4]> melbourne airport > cb_nested %>% select(-id, -name) ℹ Missing attribute `id`, add it back. # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts <chr> <dbl> <dbl> <dbl> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> > cb_long %>% select(prcp) ℹ Missing attribute `id` and `date`, add it back. # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp <chr> <date> <dbl> 1 ASN00086038 2020-01-01 0 2 ASN00086038 2020-01-02 0 3 ASN00086038 2020-01-03 0 4 ASN00086038 2020-01-04 0 5 ASN00086038 2020-01-05 18 6 ASN00086038 2020-01-06 104 7 ASN00086038 2020-01-07 14 8 ASN00086038 2020-01-08 0 9 ASN00086038 2020-01-09 0 10 ASN00086038 2020-01-10 0 # ℹ 20 more rows > cb_long %>% select(-prcp, -date) ℹ Missing attribute `date`, add it back. # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] date id tmax tmin <date> <chr> <dbl> <dbl> 1 2020-01-01 ASN00086038 26.8 11 2 2020-01-02 ASN00086038 26.3 12.2 3 2020-01-03 ASN00086038 34.5 12.7 4 2020-01-04 ASN00086038 29.3 18.8 5 2020-01-05 ASN00086038 16.1 12.5 6 2020-01-06 ASN00086038 17.5 11.1 7 2020-01-07 ASN00086038 20.7 12.1 8 2020-01-08 ASN00086038 26.4 16.4 9 2020-01-09 ASN00086038 33.1 17.4 10 2020-01-10 ASN00086038 34 19.6 # ℹ 20 more rows > > # rename - rename.spatial_cubble_df, rename.temporal_cubble_df > cb_nested %>% rename(elev2 = elev) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev2 name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% rename(prcp2 = prcp) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp2 tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > # rename on key attributes > cb_nested %>% rename(id2 = id) # cubble: key: id2 [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id2 long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% rename(date2 = date) # cubble: key: id [3], index: date2, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date2 prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > > # join - mutate_join - dplyr_reconstruct() > # join - filter_join - dplyr_row_slice() > df1 <- cb_nested %>% as_tibble() %>% select(id, name) %>% head(2) > nested <- cb_nested %>% select(-name) > nested %>% left_join(df1, by = "id") # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport 3 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> <NA> > nested %>% right_join(df1, by = "id") # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport > nested %>% inner_join(df1, by = "id") # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport > nested %>% full_join(df1, by = "id") # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport 3 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> <NA> > nested %>% anti_join(df1, by = "id") # cubble: key: id [1], index: date, nested form # spatial: [144.8321, -37.6655, 144.8321, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts <chr> <dbl> <dbl> <dbl> <dbl> <list> 1 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> > > # bind_rows - dplyr_reconstruct, bind_rows.temporal_cubble_df > df1 <- cb_nested %>% head(1) > df2 <- cb_nested %>% tail(2) > bind_rows(df1, df2) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > df1 <- cb_long %>% head(10) > df2 <- cb_long %>% tail(20) > bind_rows(df1, df2) # cubble: key: id [1], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > > # relocate - dplyr_col_select, dplyr_col_select > cb_nested %>% relocate(ts, .before = name) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev ts name wmo_id <chr> <dbl> <dbl> <dbl> <list> <chr> <dbl> 1 ASN00086038 145. -37.7 78.4 <tibble [10 × 4]> essendon airport 95866 2 ASN00086077 145. -38.0 12.1 <tibble [10 × 4]> moorabbin airport 94870 3 ASN00086282 145. -37.7 113. <tibble [10 × 4]> melbourne airport 94866 > cb_nested %>% face_temporal() %>% relocate(tmin) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] tmin id date prcp tmax <dbl> <chr> <date> <dbl> <dbl> 1 11 ASN00086038 2020-01-01 0 26.8 2 12.2 ASN00086038 2020-01-02 0 26.3 3 12.7 ASN00086038 2020-01-03 0 34.5 4 18.8 ASN00086038 2020-01-04 0 29.3 5 12.5 ASN00086038 2020-01-05 18 16.1 6 11.1 ASN00086038 2020-01-06 104 17.5 7 12.1 ASN00086038 2020-01-07 14 20.7 8 16.4 ASN00086038 2020-01-08 0 26.4 9 17.4 ASN00086038 2020-01-09 0 33.1 10 19.6 ASN00086038 2020-01-10 0 34 # ℹ 20 more rows > > # slice - all the slice_* uses dplyr::slice(), which uses dplyr_row_slice() > cb_nested %>% slice_head(n = 2) # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> > cb_nested %>% slice_tail(n = 2) # cubble: key: id [2], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 2 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_nested %>% slice_max(elev) # cubble: key: id [1], index: date, nested form # spatial: [144.8321, -37.6655, 144.8321, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_nested %>% slice_min(elev) # cubble: key: id [1], index: date, nested form # spatial: [145.0964, -37.98, 145.0964, -37.98], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> > cb_nested %>% slice_sample(n = 2) # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> > > # rowwise - rowwise.spatial_cubble_df, rowwise.temporal_cuble_df > cb_nested %>% rowwise() # cubble: key: id [3], index: date, nested form, groups: rowwise # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% rowwise() # cubble: key: id [3], index: date, long form, groups: rowwise # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > > # group_by & ungroup - > (res <- cb_nested %>% mutate(group1 = c(1, 1, 2)) %>% group_by(group1)) # cubble: key: id [3], index: date, nested form, groups: group1 [2] # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts group1 <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <dbl> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble> 1 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble> 1 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble> 2 > res %>% ungroup() # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts group1 <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <dbl> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble> 1 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble> 1 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble> 2 > (res2 <- res %>% face_temporal() %>% unfold(group1) %>% group_by(group1)) Adding missing grouping variables: `group1` Error in `group_by()`: ! Must group by variables found in `.data`. ✖ Column `group1` is not found. Backtrace: ▆ 1. ├─res %>% face_temporal() %>% unfold(group1) %>% ... 2. ├─dplyr::group_by(., group1) 3. ├─cubble:::group_by.temporal_cubble_df(., group1) 4. ├─base::NextMethod() 5. └─dplyr:::group_by.data.frame(., group1) 6. └─dplyr::group_by_prepare(.data, ..., .add = .add, error_call = current_env()) 7. └─rlang::abort(bullets, call = error_call) Execution halted Examples with CPU (user + system) or elapsed time > 5s user system elapsed as_cubble 4.644 0.316 5.678 Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.3.0
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘cb1class.Rmd’ using rmarkdown --- finished re-building ‘cb1class.Rmd’ --- re-building ‘cb2create.Rmd’ using rmarkdown --- finished re-building ‘cb2create.Rmd’ --- re-building ‘cb3tsibblesf.Rmd’ using rmarkdown --- finished re-building ‘cb3tsibblesf.Rmd’ --- re-building ‘cb4glyph.Rmd’ using rmarkdown ** Processing: /home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/cubble.Rcheck/vign_test/cubble/vignettes/cb4glyph_files/figure-html/unnamed-chunk-6-1.png 288x288 pixels, 8 bits/pixel, 254 colors in palette Reducing image to 8 bits/pixel, grayscale Input IDAT size = 6023 bytes Input file size = 6875 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 5340 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 5340 Output IDAT size = 5340 bytes (683 bytes decrease) Output file size = 5418 bytes (1457 bytes = 21.19% decrease) --- finished re-building ‘cb4glyph.Rmd’ --- re-building ‘cb5match.Rmd’ using rmarkdown ** Processing: /home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/cubble.Rcheck/vign_test/cubble/vignettes/cb5match_files/figure-html/unnamed-chunk-2-1.png 288x288 pixels, 3x8 bits/pixel, RGB Input IDAT size = 28770 bytes Input file size = 28884 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 20466 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 20466 Output IDAT size = 20466 bytes (8304 bytes decrease) Output file size = 20544 bytes (8340 bytes = 28.87% decrease) Quitting from lines 110-149 [unnamed-chunk-7] (cb5match.Rmd) Error: processing vignette 'cb5match.Rmd' failed with diagnostics: C stack usage 63759928 is too close to the limit --- failed re-building ‘cb5match.Rmd’ --- re-building ‘cb6interactive.Rmd’ using rmarkdown --- finished re-building ‘cb6interactive.Rmd’ SUMMARY: processing the following file failed: ‘cb5match.Rmd’ Error: Vignette re-building failed. Execution halted Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.3.0
Check: examples
Result: ERROR Running examples in ‘cubble-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: arrange.temporal_cubble_df > ### Title: 'dplyr' methods > ### Aliases: arrange.temporal_cubble_df select.spatial_cubble_df > ### select.temporal_cubble_df group_by.spatial_cubble_df > ### group_by.temporal_cubble_df ungroup.spatial_cubble_df > ### ungroup.temporal_cubble_df summarise.spatial_cubble_df > ### summarise.temporal_cubble_df rename.spatial_cubble_df > ### rename.temporal_cubble_df bind_rows.temporal_cubble_df > ### bind_cols.spatial_cubble_df bind_cols.temporal_cubble_df > ### rowwise.spatial_cubble_df rowwise.temporal_cubble_df > ### dplyr_col_modify.cubble_df dplyr_row_slice.spatial_cubble_df > ### dplyr_row_slice.temporal_cubble_df > ### dplyr_reconstruct.spatial_cubble_df > ### dplyr_reconstruct.temporal_cubble_df mutate.spatial_cubble_df > ### filter.spatial_cubble_df arrange.spatial_cubble_df > > ### ** Examples > > library(dplyr) Attaching package: ‘dplyr’ The following objects are masked from ‘package:stats’: filter, lag The following objects are masked from ‘package:base’: intersect, setdiff, setequal, union > cb_nested <- climate_mel > cb_long <- face_temporal(climate_mel) > > # filter - currently filter.spatial_cubble_df, dply_row_slice > cb_nested %>% filter(elev > 40) # cubble: key: id [2], index: date, nested form # spatial: [144.8321, -37.7276, 144.9066, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% filter(prcp > 0) # cubble: key: id [3], index: date, long form # temporal: 2020-01-05 -- 2020-01-07 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-05 18 16.1 12.5 2 ASN00086038 2020-01-06 104 17.5 11.1 3 ASN00086038 2020-01-07 14 20.7 12.1 4 ASN00086077 2020-01-05 20 17.4 12.7 5 ASN00086077 2020-01-06 122 17.8 11.8 6 ASN00086077 2020-01-07 6 20.3 12.6 7 ASN00086282 2020-01-05 16 15.7 12 8 ASN00086282 2020-01-06 90 17.3 11.5 9 ASN00086282 2020-01-07 6 19.9 11.8 > > # mutate - curerntly mutate.spatial_cubble_df, dply_col_modify > cb_nested %>% mutate(elev2 = elev + 10) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts elev2 <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <dbl> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 88.4 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 22.1 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> 123. > cb_long %>% mutate(prcp2 = prcp + 10) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin prcp2 <chr> <date> <dbl> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 10 2 ASN00086038 2020-01-02 0 26.3 12.2 10 3 ASN00086038 2020-01-03 0 34.5 12.7 10 4 ASN00086038 2020-01-04 0 29.3 18.8 10 5 ASN00086038 2020-01-05 18 16.1 12.5 28 6 ASN00086038 2020-01-06 104 17.5 11.1 114 7 ASN00086038 2020-01-07 14 20.7 12.1 24 8 ASN00086038 2020-01-08 0 26.4 16.4 10 9 ASN00086038 2020-01-09 0 33.1 17.4 10 10 ASN00086038 2020-01-10 0 34 19.6 10 # ℹ 20 more rows > > # arrange - currently arrange.spatial_cubble_df, arrange.temporal_cubble_df > cb_nested %>% arrange(wmo_id) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> > cb_long %>% arrange(prcp) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-08 0 26.4 16.4 6 ASN00086038 2020-01-09 0 33.1 17.4 7 ASN00086038 2020-01-10 0 34 19.6 8 ASN00086077 2020-01-01 0 24.7 10 9 ASN00086077 2020-01-02 0 24.8 11.8 10 ASN00086077 2020-01-03 0 35 12.2 # ℹ 20 more rows > > # summarise - summarise.spatial_cubble_df, summarise.temporal_cubble_df > cb_long %>% + group_by(first_5 = ifelse(lubridate::day(date) <=5, 1, 2 )) %>% + summarise(tmax = mean(tmax)) # cubble: key: id [3], index: first_5, long form, groups: first_5 [2] # temporal: 1 -- 2 [1], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] first_5 id tmax <dbl> <chr> <dbl> 1 1 ASN00086038 26.6 2 1 ASN00086077 25.5 3 1 ASN00086282 27.1 4 2 ASN00086038 26.3 5 2 ASN00086077 25.9 6 2 ASN00086282 26.2 > cb_long %>% + mutate(first_5 = ifelse(lubridate::day(date) <=5, 1, 2)) %>% + summarise(t = mean(tmax), .by = first_5) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date t <chr> <date> <dbl> 1 ASN00086038 2020-01-01 26.8 2 ASN00086038 2020-01-02 26.3 3 ASN00086038 2020-01-03 34.5 4 ASN00086038 2020-01-04 29.3 5 ASN00086038 2020-01-05 16.1 6 ASN00086038 2020-01-06 17.5 7 ASN00086038 2020-01-07 20.7 8 ASN00086038 2020-01-08 26.4 9 ASN00086038 2020-01-09 33.1 10 ASN00086038 2020-01-10 34 # ℹ 20 more rows > > # select - select.spatial_cubble_df, select.temporal_cubble_df > cb_nested %>% select(name) ℹ Missing attribute `id`, `long`, `lat`, and `ts`, add it back. # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat ts name <chr> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 <tibble [10 × 4]> moorabbin airport 3 ASN00086282 145. -37.7 <tibble [10 × 4]> melbourne airport > cb_nested %>% select(-id, -name) ℹ Missing attribute `id`, add it back. # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts <chr> <dbl> <dbl> <dbl> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> > cb_long %>% select(prcp) ℹ Missing attribute `id` and `date`, add it back. # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp <chr> <date> <dbl> 1 ASN00086038 2020-01-01 0 2 ASN00086038 2020-01-02 0 3 ASN00086038 2020-01-03 0 4 ASN00086038 2020-01-04 0 5 ASN00086038 2020-01-05 18 6 ASN00086038 2020-01-06 104 7 ASN00086038 2020-01-07 14 8 ASN00086038 2020-01-08 0 9 ASN00086038 2020-01-09 0 10 ASN00086038 2020-01-10 0 # ℹ 20 more rows > cb_long %>% select(-prcp, -date) ℹ Missing attribute `date`, add it back. # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] date id tmax tmin <date> <chr> <dbl> <dbl> 1 2020-01-01 ASN00086038 26.8 11 2 2020-01-02 ASN00086038 26.3 12.2 3 2020-01-03 ASN00086038 34.5 12.7 4 2020-01-04 ASN00086038 29.3 18.8 5 2020-01-05 ASN00086038 16.1 12.5 6 2020-01-06 ASN00086038 17.5 11.1 7 2020-01-07 ASN00086038 20.7 12.1 8 2020-01-08 ASN00086038 26.4 16.4 9 2020-01-09 ASN00086038 33.1 17.4 10 2020-01-10 ASN00086038 34 19.6 # ℹ 20 more rows > > # rename - rename.spatial_cubble_df, rename.temporal_cubble_df > cb_nested %>% rename(elev2 = elev) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev2 name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% rename(prcp2 = prcp) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp2 tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > # rename on key attributes > cb_nested %>% rename(id2 = id) # cubble: key: id2 [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id2 long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% rename(date2 = date) # cubble: key: id [3], index: date2, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date2 prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > > # join - mutate_join - dplyr_reconstruct() > # join - filter_join - dplyr_row_slice() > df1 <- cb_nested %>% as_tibble() %>% select(id, name) %>% head(2) > nested <- cb_nested %>% select(-name) > nested %>% left_join(df1, by = "id") # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport 3 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> <NA> > nested %>% right_join(df1, by = "id") # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport > nested %>% inner_join(df1, by = "id") # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport > nested %>% full_join(df1, by = "id") # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport 3 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> <NA> > nested %>% anti_join(df1, by = "id") # cubble: key: id [1], index: date, nested form # spatial: [144.8321, -37.6655, 144.8321, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts <chr> <dbl> <dbl> <dbl> <dbl> <list> 1 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> > > # bind_rows - dplyr_reconstruct, bind_rows.temporal_cubble_df > df1 <- cb_nested %>% head(1) > df2 <- cb_nested %>% tail(2) > bind_rows(df1, df2) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > df1 <- cb_long %>% head(10) > df2 <- cb_long %>% tail(20) > bind_rows(df1, df2) # cubble: key: id [1], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > > # relocate - dplyr_col_select, dplyr_col_select > cb_nested %>% relocate(ts, .before = name) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev ts name wmo_id <chr> <dbl> <dbl> <dbl> <list> <chr> <dbl> 1 ASN00086038 145. -37.7 78.4 <tibble [10 × 4]> essendon airport 95866 2 ASN00086077 145. -38.0 12.1 <tibble [10 × 4]> moorabbin airport 94870 3 ASN00086282 145. -37.7 113. <tibble [10 × 4]> melbourne airport 94866 > cb_nested %>% face_temporal() %>% relocate(tmin) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] tmin id date prcp tmax <dbl> <chr> <date> <dbl> <dbl> 1 11 ASN00086038 2020-01-01 0 26.8 2 12.2 ASN00086038 2020-01-02 0 26.3 3 12.7 ASN00086038 2020-01-03 0 34.5 4 18.8 ASN00086038 2020-01-04 0 29.3 5 12.5 ASN00086038 2020-01-05 18 16.1 6 11.1 ASN00086038 2020-01-06 104 17.5 7 12.1 ASN00086038 2020-01-07 14 20.7 8 16.4 ASN00086038 2020-01-08 0 26.4 9 17.4 ASN00086038 2020-01-09 0 33.1 10 19.6 ASN00086038 2020-01-10 0 34 # ℹ 20 more rows > > # slice - all the slice_* uses dplyr::slice(), which uses dplyr_row_slice() > cb_nested %>% slice_head(n = 2) # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> > cb_nested %>% slice_tail(n = 2) # cubble: key: id [2], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 2 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_nested %>% slice_max(elev) # cubble: key: id [1], index: date, nested form # spatial: [144.8321, -37.6655, 144.8321, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_nested %>% slice_min(elev) # cubble: key: id [1], index: date, nested form # spatial: [145.0964, -37.98, 145.0964, -37.98], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> > cb_nested %>% slice_sample(n = 2) # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> > > # rowwise - rowwise.spatial_cubble_df, rowwise.temporal_cuble_df > cb_nested %>% rowwise() # cubble: key: id [3], index: date, nested form, groups: rowwise # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% rowwise() # cubble: key: id [3], index: date, long form, groups: rowwise # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > > # group_by & ungroup - > (res <- cb_nested %>% mutate(group1 = c(1, 1, 2)) %>% group_by(group1)) # cubble: key: id [3], index: date, nested form, groups: group1 [2] # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts group1 <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <dbl> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble> 1 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble> 1 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble> 2 > res %>% ungroup() # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts group1 <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <dbl> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble> 1 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble> 1 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble> 2 > (res2 <- res %>% face_temporal() %>% unfold(group1) %>% group_by(group1)) Adding missing grouping variables: `group1` Error in `group_by()`: ! Must group by variables found in `.data`. ✖ Column `group1` is not found. Backtrace: ▆ 1. ├─res %>% face_temporal() %>% unfold(group1) %>% ... 2. ├─dplyr::group_by(., group1) 3. ├─cubble:::group_by.temporal_cubble_df(., group1) 4. ├─base::NextMethod() 5. └─dplyr:::group_by.data.frame(., group1) 6. └─dplyr::group_by_prepare(.data, ..., .add = .add, error_call = current_env()) 7. └─rlang::abort(bullets, call = error_call) Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.3.0
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘cb1class.Rmd’ using rmarkdown --- finished re-building ‘cb1class.Rmd’ --- re-building ‘cb2create.Rmd’ using rmarkdown --- finished re-building ‘cb2create.Rmd’ --- re-building ‘cb3tsibblesf.Rmd’ using rmarkdown --- finished re-building ‘cb3tsibblesf.Rmd’ --- re-building ‘cb4glyph.Rmd’ using rmarkdown ** Processing: /home/hornik/tmp/R.check/r-devel-gcc/Work/PKGS/cubble.Rcheck/vign_test/cubble/vignettes/cb4glyph_files/figure-html/unnamed-chunk-6-1.png 288x288 pixels, 8 bits/pixel, 254 colors in palette Reducing image to 8 bits/pixel, grayscale Input IDAT size = 6023 bytes Input file size = 6875 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 5340 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 5340 Output IDAT size = 5340 bytes (683 bytes decrease) Output file size = 5418 bytes (1457 bytes = 21.19% decrease) --- finished re-building ‘cb4glyph.Rmd’ --- re-building ‘cb5match.Rmd’ using rmarkdown ** Processing: /home/hornik/tmp/R.check/r-devel-gcc/Work/PKGS/cubble.Rcheck/vign_test/cubble/vignettes/cb5match_files/figure-html/unnamed-chunk-2-1.png 288x288 pixels, 3x8 bits/pixel, RGB Input IDAT size = 28770 bytes Input file size = 28884 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 20466 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 20466 Output IDAT size = 20466 bytes (8304 bytes decrease) Output file size = 20544 bytes (8340 bytes = 28.87% decrease) Quitting from lines 110-149 [unnamed-chunk-7] (cb5match.Rmd) Error: processing vignette 'cb5match.Rmd' failed with diagnostics: protect(): protection stack overflow --- failed re-building ‘cb5match.Rmd’ --- re-building ‘cb6interactive.Rmd’ using rmarkdown --- finished re-building ‘cb6interactive.Rmd’ SUMMARY: processing the following file failed: ‘cb5match.Rmd’ Error: Vignette re-building failed. Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.3.0
Check: examples
Result: ERROR Running examples in ‘cubble-Ex.R’ failed The error most likely occurred in: > ### Name: arrange.temporal_cubble_df > ### Title: 'dplyr' methods > ### Aliases: arrange.temporal_cubble_df select.spatial_cubble_df > ### select.temporal_cubble_df group_by.spatial_cubble_df > ### group_by.temporal_cubble_df ungroup.spatial_cubble_df > ### ungroup.temporal_cubble_df summarise.spatial_cubble_df > ### summarise.temporal_cubble_df rename.spatial_cubble_df > ### rename.temporal_cubble_df bind_rows.temporal_cubble_df > ### bind_cols.spatial_cubble_df bind_cols.temporal_cubble_df > ### rowwise.spatial_cubble_df rowwise.temporal_cubble_df > ### dplyr_col_modify.cubble_df dplyr_row_slice.spatial_cubble_df > ### dplyr_row_slice.temporal_cubble_df > ### dplyr_reconstruct.spatial_cubble_df > ### dplyr_reconstruct.temporal_cubble_df mutate.spatial_cubble_df > ### filter.spatial_cubble_df arrange.spatial_cubble_df > > ### ** Examples > > library(dplyr) Attaching package: ‘dplyr’ The following objects are masked from ‘package:stats’: filter, lag The following objects are masked from ‘package:base’: intersect, setdiff, setequal, union > cb_nested <- climate_mel > cb_long <- face_temporal(climate_mel) > > # filter - currently filter.spatial_cubble_df, dply_row_slice > cb_nested %>% filter(elev > 40) # cubble: key: id [2], index: date, nested form # spatial: [144.8321, -37.7276, 144.9066, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% filter(prcp > 0) # cubble: key: id [3], index: date, long form # temporal: 2020-01-05 -- 2020-01-07 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-05 18 16.1 12.5 2 ASN00086038 2020-01-06 104 17.5 11.1 3 ASN00086038 2020-01-07 14 20.7 12.1 4 ASN00086077 2020-01-05 20 17.4 12.7 5 ASN00086077 2020-01-06 122 17.8 11.8 6 ASN00086077 2020-01-07 6 20.3 12.6 7 ASN00086282 2020-01-05 16 15.7 12 8 ASN00086282 2020-01-06 90 17.3 11.5 9 ASN00086282 2020-01-07 6 19.9 11.8 > > # mutate - curerntly mutate.spatial_cubble_df, dply_col_modify > cb_nested %>% mutate(elev2 = elev + 10) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts elev2 <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <dbl> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 88.4 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 22.1 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> 123. > cb_long %>% mutate(prcp2 = prcp + 10) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin prcp2 <chr> <date> <dbl> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 10 2 ASN00086038 2020-01-02 0 26.3 12.2 10 3 ASN00086038 2020-01-03 0 34.5 12.7 10 4 ASN00086038 2020-01-04 0 29.3 18.8 10 5 ASN00086038 2020-01-05 18 16.1 12.5 28 6 ASN00086038 2020-01-06 104 17.5 11.1 114 7 ASN00086038 2020-01-07 14 20.7 12.1 24 8 ASN00086038 2020-01-08 0 26.4 16.4 10 9 ASN00086038 2020-01-09 0 33.1 17.4 10 10 ASN00086038 2020-01-10 0 34 19.6 10 # ℹ 20 more rows > > # arrange - currently arrange.spatial_cubble_df, arrange.temporal_cubble_df > cb_nested %>% arrange(wmo_id) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> > cb_long %>% arrange(prcp) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-08 0 26.4 16.4 6 ASN00086038 2020-01-09 0 33.1 17.4 7 ASN00086038 2020-01-10 0 34 19.6 8 ASN00086077 2020-01-01 0 24.7 10 9 ASN00086077 2020-01-02 0 24.8 11.8 10 ASN00086077 2020-01-03 0 35 12.2 # ℹ 20 more rows > > # summarise - summarise.spatial_cubble_df, summarise.temporal_cubble_df > cb_long %>% + group_by(first_5 = ifelse(lubridate::day(date) <=5, 1, 2 )) %>% + summarise(tmax = mean(tmax)) # cubble: key: id [3], index: first_5, long form, groups: first_5 [2] # temporal: 1 -- 2 [1], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] first_5 id tmax <dbl> <chr> <dbl> 1 1 ASN00086038 26.6 2 1 ASN00086077 25.5 3 1 ASN00086282 27.1 4 2 ASN00086038 26.3 5 2 ASN00086077 25.9 6 2 ASN00086282 26.2 > cb_long %>% + mutate(first_5 = ifelse(lubridate::day(date) <=5, 1, 2)) %>% + summarise(t = mean(tmax), .by = first_5) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date t <chr> <date> <dbl> 1 ASN00086038 2020-01-01 26.8 2 ASN00086038 2020-01-02 26.3 3 ASN00086038 2020-01-03 34.5 4 ASN00086038 2020-01-04 29.3 5 ASN00086038 2020-01-05 16.1 6 ASN00086038 2020-01-06 17.5 7 ASN00086038 2020-01-07 20.7 8 ASN00086038 2020-01-08 26.4 9 ASN00086038 2020-01-09 33.1 10 ASN00086038 2020-01-10 34 # ℹ 20 more rows > > # select - select.spatial_cubble_df, select.temporal_cubble_df > cb_nested %>% select(name) ℹ Missing attribute `id`, `long`, `lat`, and `ts`, add it back. # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat ts name <chr> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 <tibble [10 × 4]> moorabbin airport 3 ASN00086282 145. -37.7 <tibble [10 × 4]> melbourne airport > cb_nested %>% select(-id, -name) ℹ Missing attribute `id`, add it back. # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts <chr> <dbl> <dbl> <dbl> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> > cb_long %>% select(prcp) ℹ Missing attribute `id` and `date`, add it back. # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp <chr> <date> <dbl> 1 ASN00086038 2020-01-01 0 2 ASN00086038 2020-01-02 0 3 ASN00086038 2020-01-03 0 4 ASN00086038 2020-01-04 0 5 ASN00086038 2020-01-05 18 6 ASN00086038 2020-01-06 104 7 ASN00086038 2020-01-07 14 8 ASN00086038 2020-01-08 0 9 ASN00086038 2020-01-09 0 10 ASN00086038 2020-01-10 0 # ℹ 20 more rows > cb_long %>% select(-prcp, -date) ℹ Missing attribute `date`, add it back. # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] date id tmax tmin <date> <chr> <dbl> <dbl> 1 2020-01-01 ASN00086038 26.8 11 2 2020-01-02 ASN00086038 26.3 12.2 3 2020-01-03 ASN00086038 34.5 12.7 4 2020-01-04 ASN00086038 29.3 18.8 5 2020-01-05 ASN00086038 16.1 12.5 6 2020-01-06 ASN00086038 17.5 11.1 7 2020-01-07 ASN00086038 20.7 12.1 8 2020-01-08 ASN00086038 26.4 16.4 9 2020-01-09 ASN00086038 33.1 17.4 10 2020-01-10 ASN00086038 34 19.6 # ℹ 20 more rows > > # rename - rename.spatial_cubble_df, rename.temporal_cubble_df > cb_nested %>% rename(elev2 = elev) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev2 name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% rename(prcp2 = prcp) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp2 tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > # rename on key attributes > cb_nested %>% rename(id2 = id) # cubble: key: id2 [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id2 long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% rename(date2 = date) # cubble: key: id [3], index: date2, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date2 prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > > # join - mutate_join - dplyr_reconstruct() > # join - filter_join - dplyr_row_slice() > df1 <- cb_nested %>% as_tibble() %>% select(id, name) %>% head(2) > nested <- cb_nested %>% select(-name) > nested %>% left_join(df1, by = "id") # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport 3 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> <NA> > nested %>% right_join(df1, by = "id") # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport > nested %>% inner_join(df1, by = "id") # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport > nested %>% full_join(df1, by = "id") # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts name <chr> <dbl> <dbl> <dbl> <dbl> <list> <chr> 1 ASN00086038 145. -37.7 78.4 95866 <tibble [10 × 4]> essendon airport 2 ASN00086077 145. -38.0 12.1 94870 <tibble [10 × 4]> moorabbin airport 3 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> <NA> > nested %>% anti_join(df1, by = "id") # cubble: key: id [1], index: date, nested form # spatial: [144.8321, -37.6655, 144.8321, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev wmo_id ts <chr> <dbl> <dbl> <dbl> <dbl> <list> 1 ASN00086282 145. -37.7 113. 94866 <tibble [10 × 4]> > > # bind_rows - dplyr_reconstruct, bind_rows.temporal_cubble_df > df1 <- cb_nested %>% head(1) > df2 <- cb_nested %>% tail(2) > bind_rows(df1, df2) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > df1 <- cb_long %>% head(10) > df2 <- cb_long %>% tail(20) > bind_rows(df1, df2) # cubble: key: id [1], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > > # relocate - dplyr_col_select, dplyr_col_select > cb_nested %>% relocate(ts, .before = name) # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev ts name wmo_id <chr> <dbl> <dbl> <dbl> <list> <chr> <dbl> 1 ASN00086038 145. -37.7 78.4 <tibble [10 × 4]> essendon airport 95866 2 ASN00086077 145. -38.0 12.1 <tibble [10 × 4]> moorabbin airport 94870 3 ASN00086282 145. -37.7 113. <tibble [10 × 4]> melbourne airport 94866 > cb_nested %>% face_temporal() %>% relocate(tmin) # cubble: key: id [3], index: date, long form # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] tmin id date prcp tmax <dbl> <chr> <date> <dbl> <dbl> 1 11 ASN00086038 2020-01-01 0 26.8 2 12.2 ASN00086038 2020-01-02 0 26.3 3 12.7 ASN00086038 2020-01-03 0 34.5 4 18.8 ASN00086038 2020-01-04 0 29.3 5 12.5 ASN00086038 2020-01-05 18 16.1 6 11.1 ASN00086038 2020-01-06 104 17.5 7 12.1 ASN00086038 2020-01-07 14 20.7 8 16.4 ASN00086038 2020-01-08 0 26.4 9 17.4 ASN00086038 2020-01-09 0 33.1 10 19.6 ASN00086038 2020-01-10 0 34 # ℹ 20 more rows > > # slice - all the slice_* uses dplyr::slice(), which uses dplyr_row_slice() > cb_nested %>% slice_head(n = 2) # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> > cb_nested %>% slice_tail(n = 2) # cubble: key: id [2], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 2 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_nested %>% slice_max(elev) # cubble: key: id [1], index: date, nested form # spatial: [144.8321, -37.6655, 144.8321, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_nested %>% slice_min(elev) # cubble: key: id [1], index: date, nested form # spatial: [145.0964, -37.98, 145.0964, -37.98], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> > cb_nested %>% slice_sample(n = 2) # cubble: key: id [2], index: date, nested form # spatial: [144.9066, -37.98, 145.0964, -37.7276], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> > > # rowwise - rowwise.spatial_cubble_df, rowwise.temporal_cuble_df > cb_nested %>% rowwise() # cubble: key: id [3], index: date, nested form, groups: rowwise # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble [10 × 4]> 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble [10 × 4]> 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble [10 × 4]> > cb_long %>% rowwise() # cubble: key: id [3], index: date, long form, groups: rowwise # temporal: 2020-01-01 -- 2020-01-10 [1D], no gaps # spatial: long [dbl], lat [dbl], elev [dbl], name [chr], wmo_id [dbl] id date prcp tmax tmin <chr> <date> <dbl> <dbl> <dbl> 1 ASN00086038 2020-01-01 0 26.8 11 2 ASN00086038 2020-01-02 0 26.3 12.2 3 ASN00086038 2020-01-03 0 34.5 12.7 4 ASN00086038 2020-01-04 0 29.3 18.8 5 ASN00086038 2020-01-05 18 16.1 12.5 6 ASN00086038 2020-01-06 104 17.5 11.1 7 ASN00086038 2020-01-07 14 20.7 12.1 8 ASN00086038 2020-01-08 0 26.4 16.4 9 ASN00086038 2020-01-09 0 33.1 17.4 10 ASN00086038 2020-01-10 0 34 19.6 # ℹ 20 more rows > > # group_by & ungroup - > (res <- cb_nested %>% mutate(group1 = c(1, 1, 2)) %>% group_by(group1)) # cubble: key: id [3], index: date, nested form, groups: group1 [2] # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts group1 <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <dbl> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble> 1 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble> 1 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble> 2 > res %>% ungroup() # cubble: key: id [3], index: date, nested form # spatial: [144.8321, -37.98, 145.0964, -37.6655], Missing CRS! # temporal: date [date], prcp [dbl], tmax [dbl], tmin [dbl] id long lat elev name wmo_id ts group1 <chr> <dbl> <dbl> <dbl> <chr> <dbl> <list> <dbl> 1 ASN00086038 145. -37.7 78.4 essendon airport 95866 <tibble> 1 2 ASN00086077 145. -38.0 12.1 moorabbin airport 94870 <tibble> 1 3 ASN00086282 145. -37.7 113. melbourne airport 94866 <tibble> 2 > (res2 <- res %>% face_temporal() %>% unfold(group1) %>% group_by(group1)) Adding missing grouping variables: `group1` Error in `group_by()`: ! Must group by variables found in `.data`. ✖ Column `group1` is not found. Backtrace: ▆ 1. ├─res %>% face_temporal() %>% unfold(group1) %>% ... 2. ├─dplyr::group_by(., group1) 3. ├─cubble:::group_by.temporal_cubble_df(., group1) 4. ├─base::NextMethod() 5. └─dplyr:::group_by.data.frame(., group1) 6. └─dplyr::group_by_prepare(.data, ..., .add = .add, error_call = current_env()) 7. └─rlang::abort(bullets, call = error_call) Execution halted Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 0.3.0
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: --- re-building ‘cb1class.Rmd’ using rmarkdown --- finished re-building ‘cb1class.Rmd’ --- re-building ‘cb2create.Rmd’ using rmarkdown --- finished re-building ‘cb2create.Rmd’ --- re-building ‘cb3tsibblesf.Rmd’ using rmarkdown --- finished re-building ‘cb3tsibblesf.Rmd’ --- re-building ‘cb4glyph.Rmd’ using rmarkdown ** Processing: /data/gannet/ripley/R/packages/tests-clang/cubble.Rcheck/vign_test/cubble/vignettes/cb4glyph_files/figure-html/unnamed-chunk-6-1.png 288x288 pixels, 8 bits/pixel, 255 colors in palette Reducing image to 8 bits/pixel, grayscale Input IDAT size = 6042 bytes Input file size = 6897 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 5338 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 5338 Output IDAT size = 5338 bytes (704 bytes decrease) Output file size = 5416 bytes (1481 bytes = 21.47% decrease) --- finished re-building ‘cb4glyph.Rmd’ --- re-building ‘cb5match.Rmd’ using rmarkdown ** Processing: /data/gannet/ripley/R/packages/tests-clang/cubble.Rcheck/vign_test/cubble/vignettes/cb5match_files/figure-html/unnamed-chunk-2-1.png 288x288 pixels, 3x8 bits/pixel, RGB Input IDAT size = 28812 bytes Input file size = 28926 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 20562 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 20562 Output IDAT size = 20562 bytes (8250 bytes decrease) Output file size = 20640 bytes (8286 bytes = 28.65% decrease) Quitting from lines 110-149 [unnamed-chunk-7] (cb5match.Rmd) Error: processing vignette 'cb5match.Rmd' failed with diagnostics: C stack usage 49815048 is too close to the limit --- failed re-building ‘cb5match.Rmd’ --- re-building ‘cb6interactive.Rmd’ using rmarkdown --- finished re-building ‘cb6interactive.Rmd’ SUMMARY: processing the following file failed: ‘cb5match.Rmd’ Error: Vignette re-building failed. Execution halted Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.3.0
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: --- re-building ‘cb1class.Rmd’ using rmarkdown --- finished re-building ‘cb1class.Rmd’ --- re-building ‘cb2create.Rmd’ using rmarkdown --- finished re-building ‘cb2create.Rmd’ --- re-building ‘cb3tsibblesf.Rmd’ using rmarkdown --- finished re-building ‘cb3tsibblesf.Rmd’ --- re-building ‘cb4glyph.Rmd’ using rmarkdown ** Processing: /data/gannet/ripley/R/packages/tests-devel/cubble.Rcheck/vign_test/cubble/vignettes/cb4glyph_files/figure-html/unnamed-chunk-6-1.png 288x288 pixels, 8 bits/pixel, 255 colors in palette Reducing image to 8 bits/pixel, grayscale Input IDAT size = 6042 bytes Input file size = 6897 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 5338 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 5338 Output IDAT size = 5338 bytes (704 bytes decrease) Output file size = 5416 bytes (1481 bytes = 21.47% decrease) --- finished re-building ‘cb4glyph.Rmd’ --- re-building ‘cb5match.Rmd’ using rmarkdown ** Processing: /data/gannet/ripley/R/packages/tests-devel/cubble.Rcheck/vign_test/cubble/vignettes/cb5match_files/figure-html/unnamed-chunk-2-1.png 288x288 pixels, 3x8 bits/pixel, RGB Input IDAT size = 28812 bytes Input file size = 28926 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 20562 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 20562 Output IDAT size = 20562 bytes (8250 bytes decrease) Output file size = 20640 bytes (8286 bytes = 28.65% decrease) Quitting from lines 110-149 [unnamed-chunk-7] (cb5match.Rmd) Error: processing vignette 'cb5match.Rmd' failed with diagnostics: C stack usage 19927636 is too close to the limit --- failed re-building ‘cb5match.Rmd’ --- re-building ‘cb6interactive.Rmd’ using rmarkdown --- finished re-building ‘cb6interactive.Rmd’ SUMMARY: processing the following file failed: ‘cb5match.Rmd’ Error: Vignette re-building failed. Execution halted Flavor: r-devel-linux-x86_64-fedora-gcc