grayleafspotr Workflow

1. Load the package

Open grayleafspotr/grayleafspotr.Rproj in RStudio for the source workflow, or install the package and load it with library(grayleafspotr).

2. Confirm the example data

example_dir <- system.file("extdata", "example", package = "grayleafspotr")
list.files(example_dir)

## [1] "analysis.csv"  "analysis.json" "manifest.json"

3. Load saved example results

example_run <- example_grayleafspot_results()
example_run$run

## $id
## [1] "example-run"
## 
## $engine
## [1] "python-local"
## 
## $engineModel
## [1] "packaged-python-pipeline"
## 
## $createdAt
## [1] "2026-04-14T12:00:00Z"
## 
## $outputDir
## [1] "inst/extdata/example"
## 
## $analysisJson
## [1] "inst/extdata/example/analysis.json"
## 
## $analysisCsv
## [1] "inst/extdata/example/analysis.csv"

example_run$results

## # A tibble: 2 × 34
##   id     filename    day area_mm2 radius_mm diameter_mm perimeter_mm circularity
##   <chr>  <chr>     <dbl>    <dbl>     <dbl>       <dbl>        <dbl>       <dbl>
## 1 demo-1 demo_day…     1       12      1.95        3.9           8          0.8 
## 2 demo-2 demo_day…     2       18      2.39        4.78          9.1        0.77
## # ℹ 26 more variables: eccentricity <dbl>, edge_roughness <dbl>,
## #   contrast <dbl>, correlation <dbl>, energy <dbl>, homogeneity <dbl>,
## #   entropy <dbl>, center_edge_delta <dbl>, density_index <dbl>, core <dbl>,
## #   middle <dbl>, outer <dbl>, crack_count <dbl>, crack_length_mm <dbl>,
## #   crack_coverage_pct <dbl>, proportional_crack_coverage_pct <dbl>,
## #   radial_velocity_mm_per_day <dbl>, area_growth_rate_mm2_per_day <dbl>,
## #   relative_growth_rate_per_day <dbl>, radial_acceleration <dbl>, …

4. Generate template plots

plot_colony_expansion(example_run)

plot_growth_roughness(example_run)

plot_stress_remodeling(example_run)

plot_texture_organization(example_run)

plot_shape_vs_stress(example_run)

plot_feature_heatmap(example_run)

plot_radial_profile(example_run)

5. Run the Python analysis pipeline on real images

One-time Python setup

Add the interpreter path to ~/.Rprofile so it loads automatically every time R starts:

file.edit("~/.Rprofile")
# Add this line (adjust path to your rvenv_arm_311 location):
# Sys.setenv(GRAYLEAFSPOTR_PYTHON = "/path/to/rvenv_arm_311/bin/python")

Or set it for the current session only:

Sys.setenv(GRAYLEAFSPOTR_PYTHON = "/path/to/rvenv_arm_311/bin/python")

Run with grayleafspot_run() — the primary entry point

grayleafspot_run() finds the installed package Python directory automatically, creates the output folder if needed, and returns parsed JSON results directly.

res <- grayleafspot_run(
  input_dir  = system.file("extdata", "testdata", "06FEB", package = "grayleafspotr"),
  output_dir = file.path(tempdir(), "gls_run"),
  run_name   = "trial_01"
)

# Access results
res$run       # manifest metadata
res$results   # per-image data frame

Full-featured alternative: grayleafspot_analyze()

For tidy S3 objects with built-in plotting helpers, use grayleafspot_analyze():

real_run <- grayleafspot_analyze(
  input_dir  = system.file("extdata", "testdata", "06FEB", package = "grayleafspotr"),
  output_dir = tempdir(),
  save_outputs = FALSE,
  verbose      = FALSE,
  engine_model = "localunet"
)
plot_colony_expansion(real_run)

6. Convert to tidy data

growth_data <- as_grayleafspot_growth_data(example_run)
growth_data

## # A tibble: 2 × 34
##   id     filename    day area_mm2 radius_mm diameter_mm perimeter_mm circularity
##   <chr>  <chr>     <dbl>    <dbl>     <dbl>       <dbl>        <dbl>       <dbl>
## 1 demo-1 demo_day…     1       12      1.95        3.9           8          0.8 
## 2 demo-2 demo_day…     2       18      2.39        4.78          9.1        0.77
## # ℹ 26 more variables: eccentricity <dbl>, edge_roughness <dbl>,
## #   contrast <dbl>, correlation <dbl>, energy <dbl>, homogeneity <dbl>,
## #   entropy <dbl>, center_edge_delta <dbl>, density_index <dbl>, core <dbl>,
## #   middle <dbl>, outer <dbl>, crack_count <dbl>, crack_length_mm <dbl>,
## #   crack_coverage_pct <dbl>, proportional_crack_coverage_pct <dbl>,
## #   radial_velocity_mm_per_day <dbl>, area_growth_rate_mm2_per_day <dbl>,
## #   relative_growth_rate_per_day <dbl>, radial_acceleration <dbl>, …

7. Custom plotting

plot_colony_expansion(example_run) +
  ggplot2::labs(title = "Custom colony expansion view")