Handle Bitfields to Record Meta Data.

bitfield

Overview

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.

Installation

Install the official version from CRAN:

install.packages("bitfield")

Install the latest development version from GitHub:

devtools::install_github("bitfloat/bitfield")

Getting Started

Tabular Data

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 2021

Create 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 yield

Encode 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   18561

Decode 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    9.01

Raster Data

The 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

Getting Help

• Browse the function reference for detailed documentation
• Report bugs at github.com/bitfloat/bitfield/issues.