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Optimize Peak Deconvolution

Source: R/peak-deconv-optimizer.R
optimize_deconvolution.Rd

Finds optimal parameters for a set of peak models by minimizing the sum of squared residuals between the observed and fitted values.

Usage

optimize_deconvolution(
  x,
  y,
  models,
  init_params,
  optimizer = "auto",
  max_iter = 1000L,
  tol = 1e-06,
  constrain_positions = TRUE,
  ...
)

Arguments

x

Numeric vector of x-axis values (e.g., retention time, wavelength).

y

Numeric vector of observed y-axis values.

models

List of peak_model objects, one per peak.

init_params

List of initial parameter lists, one per peak.

optimizer

Optimization method: "auto", "lbfgsb", "multistart", or "nelder_mead".

max_iter

Maximum number of iterations.

tol

Convergence tolerance.

constrain_positions

Logical. If TRUE, enforce that peak centers maintain their relative ordering.

...

Additional arguments passed to specific optimizers.

Value

A list containing:

  • parameters: List of optimized parameter lists

  • fitted_values: Numeric vector of fitted y values

  • residuals: Numeric vector of residuals

  • convergence: Logical indicating convergence

  • n_iterations: Number of iterations used

  • final_value: Final objective function value (SSE)

  • optimizer: Name of optimizer used

  • elapsed_time: Optimization time in seconds

See also

Other peak-deconvolution: add_param_jitter(), assess_deconv_quality(), check_quality_gates(), initialize_peak_params()

Examples

# Create synthetic data with two overlapping Gaussian peaks
x <- seq(0, 20, by = 0.1)
true_y <- 1.5 * exp(-0.5 * ((x - 8) / 1)^2) +
  0.8 * exp(-0.5 * ((x - 12) / 1.5)^2)
y <- true_y + rnorm(length(x), sd = 0.05)

# Set up models and initial guesses
models <- list(gaussian_peak_model(), gaussian_peak_model())
init_params <- list(
  list(height = 1.2, center = 7.5, width = 1.2),
  list(height = 0.6, center = 12.5, width = 1.8)
)

# Optimize
result <- optimize_deconvolution(x, y, models, init_params)
print(result$parameters)
#> [[1]]
#> [[1]]$height
#> [1] 1.501288
#> 
#> [[1]]$center
#> [1] 7.999975
#> 
#> [[1]]$width
#> [1] 0.9969704
#> 
#> 
#> [[2]]
#> [[2]]$height
#> [1] 0.7898916
#> 
#> [[2]]$center
#> [1] 12.01145
#> 
#> [[2]]$width
#> [1] 1.526418
#> 
#>