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Add standalone prediction ensemble reporting - #25
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🟡 Changes recommended
The report omits and truncates statistics despite promising a complete standalone research record.
Review effort: Balanced
Findings: 3
Open (4)
What changed in this PR
Adds downloadable standalone HTML reporting for prediction ensembles.
Changes:
- Adds ensemble metrics, provenance, variability rankings, and residue statistics.
- Integrates report download into the Summary workflow.
- Adds regression coverage and documentation.
| File | Description |
|---|---|
shinyRam/R/reports.R |
Generates the standalone ensemble report. |
shinyRam/app.R |
Adds the report download handler and button. |
tests/reports.R |
Tests report generation and content. |
docs/prediction-ensembles.md |
Documents the HTML report. |
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| if(!is.numeric(max_report_rows) || length(max_report_rows)!=1L || | ||
| !is.finite(max_report_rows) || max_report_rows<1L) | ||
| stop("max_report_rows must be a positive finite number.") | ||
| max_report_rows <- as.integer(max_report_rows) |
| "psi_mean","psi_sd","rama8000_models","rama8000_mode", | ||
| "rama8000_consistency","rama8000_changes","plddt_models","plddt_mean", | ||
| "plddt_sd","plddt_min","plddt_max"),names(residues)) | ||
| shown <- utils::head(residues[,all_fields,drop=FALSE],max_report_rows) |
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| all_fields <- intersect(c("chain","resi","insertion_code","resn", | ||
| "models_present","phi_models","psi_models","phi_mean","phi_sd", | ||
| "psi_mean","psi_sd","rama8000_models","rama8000_mode", | ||
| "rama8000_consistency","rama8000_changes","plddt_models","plddt_mean", | ||
| "plddt_sd","plddt_min","plddt_max"),names(residues)) | ||
| shown <- utils::head(residues[,all_fields,drop=FALSE],max_report_rows) | ||
| numeric_fields <- c("phi_mean","phi_sd","psi_mean","psi_sd", | ||
| "rama8000_consistency","plddt_mean","plddt_sd","plddt_min","plddt_max", | ||
| "max_angular_sd") |
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| grepl("aaa",ensemble_contents,fixed=TRUE), | ||
| grepl("bbb",ensemble_contents,fixed=TRUE), |
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Follow-up to merged PR #23.
Adds a self-contained HTML research report for prediction ensembles:
Includes report-generation regression coverage and documentation.
This replaces the automatically closed stacked PR #24 after #23 was merged.