The bitfield package enables efficient storage and transmission of metadata and intermediate results across scientific workflows by encoding computational decisions into sequences of bits that transform to integer values. This approach allows storing rich contextual information - including quality assessments, uncertainty metrics, model parameters, and processing thresholds - in a single column of a table or raster layer.
Think of a bit as a switch representing off and on states. A sequence of n bits can accommodate 2^n states, enabling the encoding of boolean responses, categorical cases, integers, or even floating-point values with limited precision. The resulting bitfield creates a ‘computational footprint’ that preserves the context needed for cross-workflow integration and downstream reuse.
Install the official version from CRAN:
install.packages("bitfield")Install the latest development version from GitHub:
devtools::install_github("bitfloat/bitfield")
library(bitfield)
# Example data with quality issues
bf_tbl
#> # A tibble: 9 × 5
#> x y commodity yield year
#> <dbl> <dbl> <fct> <dbl> <chr>
#> 1 25.3 59.5 soybean 11.2 2021
#> 2 27.9 58.1 maize 12.0 <NA>
#> 3 27.8 57.8 soybean 13.2 2021r
#> 4 27 59.2 <NA> 4.43 2021
#> 5 259 Inf honey 13.0 2021
#> 6 27.3 59.1 maize 8.55 2021
#> 7 26.1 58.4 soybean 11.3 2021
#> 8 26.5 NaN maize 10.6 2021
#> 9 0 0 soybean 9.01 2021Create a registry to capture metadata about your workflow:
reg <- bf_registry(name = "data_quality",
description = "Quality assessment for agricultural data",
template = bf_tbl)
# Test for missing values (1 bit)
reg <- bf_map(protocol = "na", data = bf_tbl, x = commodity, registry = reg)
# Encode yield values with half precision (16 bits)
reg <- bf_map(protocol = "numeric", data = bf_tbl, x = yield,
format = "half", registry = reg)
# View the registry structure
reg
#> type data.frame
#> width 17
#> flags 2 -|----------------
#>
#> pos encoding name col
#> 1 0.0.1/0 na commodity
#> 2 1.5.10/15 numeric yieldEncode the flags into integer representation:
field <- bf_encode(registry = reg)
field
#> # A tibble: 9 × 1
#> bf_int1
#> <int>
#> 1 18840
#> 2 18942
#> 3 19101
#> 4 83054
#> 5 19071
#> 6 18502
#> 7 18851
#> 8 18770
#> 9 18561Decode the bitfield in a downstream application:
decoded <- bf_decode(x = field, registry = reg, verbose = FALSE)
# Returns a named list with decoded values
names(decoded)
#> [1] "na_commodity" "numeric_yield"
# Access individual flags
decoded$na_commodity
#> [1] 0 0 0 1 0 0 0 0 0
library(tibble)
tibble(original = bf_tbl$yield, decoded = decoded$numeric_yield)
#> # A tibble: 9 × 2
#> original decoded
#> <dbl> <dbl>
#> 1 11.2 11.2
#> 2 12.0 12.0
#> 3 13.2 13.2
#> 4 4.43 4.43
#> 5 13.0 13.0
#> 6 8.55 8.55
#> 7 11.3 11.3
#> 8 10.6 10.6
#> 9 9.01 9.01The same workflow applies to raster data - just use a SpatRaster as the template:
library(terra)
# Create example raster
bf_rst <- rast(nrows = 3, ncols = 3, vals = bf_tbl$commodity, names = "commodity")
bf_rst$yield <- rast(nrows = 3, ncols = 3, vals = bf_tbl$yield)
# Create registry with raster template
reg_rst <- bf_registry(name = "raster_quality",
description = "Quality flags for raster data",
template = bf_rst)
reg_rst <- bf_map(protocol = "na", data = bf_rst, x = commodity, registry = reg_rst)
reg_rst <- bf_map(protocol = "numeric", data = bf_rst, x = yield,
format = "half", registry = reg_rst)
# Encode returns a SpatRaster
field_rst <- bf_encode(registry = reg_rst)
field_rst
#> class : SpatRaster
#> size : 3, 3, 1 (nrow, ncol, nlyr)
#> resolution : 120, 60 (x, y)
#> extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax)
#> coord. ref. : lon/lat WGS 84 (CRS84) (OGC:CRS84)
#> source(s) : memory
#> name : bf_int1
#> min value : 18502
#> max value : 83054
# Decode returns a multi-layer SpatRaster
decoded_rst <- bf_decode(x = field_rst, registry = reg_rst, verbose = FALSE)
decoded_rst
#> class : SpatRaster
#> size : 3, 3, 2 (nrow, ncol, nlyr)
#> resolution : 120, 60 (x, y)
#> extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax)
#> coord. ref. : lon/lat WGS 84 (CRS84) (OGC:CRS84)
#> source(s) : memory
#> names : na_commodity, numeric_yield
#> min values : 0, 4.429688
#> max values : 1, 13.226562