This is the in-memory workflow function that orchestrates the complete SQI calculation pipeline using data frames. It performs standardization, PCA-based MDS selection, AHP weighting, indicator scoring, and calculates the final Soil Quality Index.
Usage
compute_sqi_df(
df,
id_column = NULL,
pairwise_df = NULL,
directions = NULL,
var_threshold = 0.05,
loading_threshold = 0.5,
...
)Arguments
- df
Data frame containing soil property data with samples in rows and properties in columns.
- id_column
Optional character string specifying the name of the ID column to preserve in the output. If NULL, no ID column is preserved.
- pairwise_df
Optional pairwise comparison matrix (as matrix or data frame). If NULL, equal weights are used for all indicators.
- directions
Optional named list specifying scoring functions for each indicator. If NULL, all indicators use higher-is-better scoring.
- var_threshold
Numeric value for PCA variance threshold (default 0.05).
- loading_threshold
Numeric value for PCA loading threshold (default 0.5).
- ...
Additional arguments (currently unused).
Value
An object of class "sqi_result" containing:
- mds
Character vector of selected MDS indicators
- weights
Named numeric vector of AHP weights
- CR
Consistency Ratio from AHP
- results
Data frame with original data, scored indicators, and SQI
- pca
PCA object from stats::prcomp
- loadings
Matrix of variable loadings
- var_exp
Numeric vector of variance explained by each PC
Details
The function performs the following steps:
Preserve ID column if specified
Standardize numeric columns (z-score)
Perform PCA and select MDS indicators
Calculate AHP weights (from pairwise matrix or equal weights)
Score each MDS indicator
Calculate weighted SQI as sum of (weight * score)
Examples
# Create example data
soil_data <- data.frame(
SampleID = paste0("S", 1:20),
Sand = rnorm(20, 45, 10),
Silt = rnorm(20, 30, 5),
Clay = rnorm(20, 25, 5),
pH = rnorm(20, 6.5, 0.5),
OM = rnorm(20, 3, 0.5)
)
# Compute SQI
result <- compute_sqi_df(soil_data, id_column = "SampleID")
# View results
head(result$results)
#> SampleID Sand Silt Clay pH OM OM_scored Sand_scored
#> 1 S1 44.94429 33.68888 23.74258 6.377052 3.278112 0.7394162 0.47286736
#> 2 S2 51.21553 39.44252 27.22399 5.911218 2.725871 0.4816739 0.63252067
#> 3 S3 56.48412 29.51277 38.77709 6.012075 3.555267 0.8687703 0.76664847
#> 4 S4 26.78182 25.32076 25.23266 7.032529 1.693833 0.0000000 0.01048713
#> 5 S5 42.52675 29.92025 27.88855 6.565835 2.922153 0.5732827 0.41132159
#> 6 S6 42.55800 25.86606 25.59097 6.744314 3.216945 0.7108681 0.41211733
#> pH_scored Silt_scored SQI
#> 1 0.4011139 0.6970645 0.5776155
#> 2 0.1440168 1.0000000 0.5645528
#> 3 0.1996802 0.4771879 0.5780717
#> 4 0.7628767 0.2564740 0.2574594
#> 5 0.5053050 0.4986419 0.4971378
#> 6 0.6038090 0.2851842 0.5029947
print(result$mds)
#> [1] "OM" "Sand" "pH" "Silt"
print(result$weights)
#> OM Sand pH Silt
#> 0.25 0.25 0.25 0.25