Find Pagination Indices From Pagination Info Dataframe

Usage

pag_indices_inner(
  pagdf,
  rlpp,
  min_siblings,
  nosplitin = character(),
  verbose = FALSE,
  row = TRUE,
  have_col_fnotes = FALSE,
  div_height = 1L
)

Arguments

pagdf

data.frame. A pagination info data.frame as created by either make_rows_df or make_cols_df.

rlpp

numeric. Maximum number of row lines per page (not including header materials), including (re)printed header and context rows

min_siblings

numeric. Minimum sibling rows which must appear on either side of pagination row for a mid-subtable split to be valid. Defaults to 2.

nosplitin

character. List of names of sub-tables where page-breaks are not allowed, regardless of other considerations. Defaults to none.

verbose

logical(1). Should additional informative messages about the search for pagination breaks be shown. Defaults to FALSE.

row

logical(1). Is pagination happening in row space (TRUE, the default) or column space (FALSE)

have_col_fnotes

logical(1). Does the table-like object being rendered have column-associated referential footnotes.

div_height

numeric(1). The height of the divider line when the associated object is rendered. Defaults to 1.

Value

A list containing the vector of row numbers, broken up by page

Details

pab_indices_inner implements the Core Pagination Algorithm for a single direction (vertical if row = TRUE, the default, horizontal otherwise) based on the pagination dataframe and (already adjusted for non-body rows/columns) lines (or characters) per page.

Pagination Algorithm

Pagination is performed independently in the vertical and horizontal directions based solely on a pagination data.frame, which includes the following information for each row/column:

• number of lines/characters rendering the row will take after word-wrapping (self_extent)

• the indices (reprint_inds) and number of lines (par_extent) of the rows which act as context for the row

• the row's number of siblings and position within its siblings

Given lpp (cpp) already adjusted for rendered elements which are not rows/columns and a dataframe of pagination information, pagination is performed via the following algorithm, and with a start = 1:

Core Pagination Algorithm:

1. Initial guess for pagination point is start + lpp (start + cpp)

2. While the guess is not a valid pagination position, and guess > start, decrement guess and repeat

• an error is thrown if all possible pagination positions between start and start + lpp (start + cpp) would ever be < start after decrementing

1. Retain pagination index

2. if pagination point was less than NROW(tt) (ncol(tt)), set start to pos + 1, and repeat steps (1) - (4).

Validating pagination position:

Given an (already adjusted) lpp or cpp value, a pagination is invalid if:

• The rows/columns on the page would take more than (adjusted) lpp lines/cpp characters to render including

  • word-wrapping

  • (vertical only) context repetition

• (vertical only) footnote messages and or section divider lines take up too many lines after rendering rows

• (vertical only) row is a label or content (row-group summary) row

• (vertical only) row at the pagination point has siblings, and it has less than min_siblings preceding or following siblings

• pagination would occur within a sub-table listed in nosplitin

Examples

mypgdf <- basic_pagdf(row.names(mtcars))

paginds <- pag_indices_inner(mypgdf, rlpp = 15, min_siblings = 0)
lapply(paginds, function(x) mtcars[x, ])
#> [[1]]
#>                     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#> Mazda RX4          21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#> Mazda RX4 Wag      21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
#> Datsun 710         22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
#> Hornet 4 Drive     21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
#> Hornet Sportabout  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
#> Valiant            18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
#> Duster 360         14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
#> Merc 240D          24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
#> Merc 230           22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
#> Merc 280           19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
#> Merc 280C          17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
#> Merc 450SE         16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
#> Merc 450SL         17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
#> Merc 450SLC        15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
#> Cadillac Fleetwood 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
#> 
#> [[2]]
#>                      mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
#> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
#> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
#> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
#> Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
#> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
#> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
#> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
#> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
#> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
#> Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
#> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
#> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
#> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
#> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
#> 
#> [[3]]
#>                mpg cyl disp  hp drat   wt qsec vs am gear carb
#> Maserati Bora 15.0   8  301 335 3.54 3.57 14.6  0  1    5    8
#> Volvo 142E    21.4   4  121 109 4.11 2.78 18.6  1  1    4    2
#>