def register_uc_4_8_callbacks(app, plot_service) -> None:
"""
Register UC-4.8 callbacks with Dash app.
Parameters
----------
app : Dash
Dash application instance.
plot_service : PlotService
Singleton PlotService instance (shared across all callbacks).
Notes
-----
- Registers 3 callbacks: panel toggle, dual-dropdown initialization,
and conditional scatter plot rendering
- Refer to official documentation for filtering logic details
"""
@app.callback(
Output("uc-4-8-collapse", "is_open"),
Input("uc-4-8-collapse-button", "n_clicks"),
State("uc-4-8-collapse", "is_open"),
prevent_initial_call=True,
)
def toggle_uc_4_8_info_panel(n_clicks, is_open):
"""Toggle UC-4.8 informative panel collapse."""
logger.info(
f"[UC-4.8] Toggle clicked! n_clicks={n_clicks}, " f"is_open={is_open}"
)
if n_clicks:
new_state = not is_open
logger.info(f"[UC-4.8] [OK] Panel toggled to: {new_state}")
return new_state
logger.info(f"[UC-4.8] No clicks, keeping is_open={is_open}")
return is_open
@app.callback(
[
Output("uc-4-8-sample-dropdown", "options"),
Output("uc-4-8-gene-dropdown", "options"),
],
[
Input("merged-result-store", "data"),
Input("uc-4-8-accordion-group", "active_item"),
],
prevent_initial_call=True,
)
def initialize_uc_4_8_dropdowns(
merged_data: Optional[dict],
active_item: Optional[str],
) -> Tuple[list, list]:
"""Initialize dropdowns with full stable catalogs from BioRemPP data."""
logger.info(
"[UC-4.8] Dropdowns init triggered, data type: %s, active_item=%s",
type(merged_data),
active_item,
)
if not merged_data:
logger.debug("[UC-4.8] No data in store, returning empty options")
return [], []
if isinstance(merged_data, dict) and not merged_data:
logger.debug("[UC-4.8] Empty dict in store, returning empty options")
return [], []
try:
if not isinstance(merged_data, dict) or "biorempp_df" not in merged_data:
logger.error(
"[UC-4.8] Invalid data format: expected dict with 'biorempp_df', got %s",
type(merged_data),
)
raise PreventUpdate
df = pd.DataFrame(merged_data["biorempp_df"])
required_cols = {
"sample": ["sample", "Sample", "sample_id"],
"genesymbol": [
"genesymbol",
"GeneSymbol",
"gene_symbol",
"Gene_Symbol",
],
}
col_mapping = {}
for required, candidates in required_cols.items():
found = False
for candidate in candidates:
if candidate in df.columns:
col_mapping[required] = candidate
found = True
break
if not found:
logger.error(
"[UC-4.8] Required column '%s' not found in BioRemPP data. Available columns: %s",
required,
df.columns.tolist(),
)
raise PreventUpdate
sample_col = col_mapping["sample"]
gene_col = col_mapping["genesymbol"]
base_df = df[[sample_col, gene_col]].dropna()
sample_values = sorted(base_df[sample_col].unique().tolist())
gene_values = sorted(base_df[gene_col].unique().tolist())
sample_options = [{"label": sample, "value": sample} for sample in sample_values]
gene_options = [{"label": gene, "value": gene} for gene in gene_values]
logger.info(
"[UC-4.8] Dropdowns initialized with stable catalogs: %s samples, %s genes",
len(sample_options),
len(gene_options),
)
return sample_options, gene_options
except Exception as e:
logger.error(f"[UC-4.8] Dropdowns error: {e}")
raise PreventUpdate
@app.callback(
Output("uc-4-8-chart-container", "children"),
[
Input("uc-4-8-sample-dropdown", "value"),
Input("uc-4-8-gene-dropdown", "value"),
],
State("merged-result-store", "data"),
prevent_initial_call=True,
)
def render_uc_4_8(
selected_sample: SelectionValue,
selected_gene: SelectionValue,
merged_data: Optional[dict],
) -> Any:
"""Render UC-4.8 scatter plot with multiselect-aware conditional filtering."""
selected_samples = _normalize_selection(selected_sample)
selected_genes = _normalize_selection(selected_gene)
if not selected_samples and not selected_genes:
logger.debug("[UC-4.8] No filter selected, showing informative message")
return html.Div(
[
html.I(className="fas fa-filter me-2"),
"Please select one or more samples and/or genes from the dropdown menus above to explore genetic inventory.",
],
className="alert alert-info mt-3",
)
if not merged_data:
logger.warning("[UC-4.8] No data available")
return _create_error_message("No data available for visualization")
try:
if not isinstance(merged_data, dict) or "biorempp_df" not in merged_data:
logger.error(
"[UC-4.8] Invalid data format: expected dict with 'biorempp_df'"
)
return _create_error_message(
"BioRemPP database data not found. "
"Please ensure BioRemPP data is loaded."
)
df = pd.DataFrame(merged_data["biorempp_df"])
required_cols = {
"sample": ["sample", "Sample", "sample_id"],
"compoundname": [
"compoundname",
"Compound_Name",
"CompoundName",
"compound",
],
"genesymbol": [
"genesymbol",
"GeneSymbol",
"gene_symbol",
"Gene_Symbol",
],
"ko": ["ko", "KO", "ko_id"],
}
col_mapping = {}
for required, candidates in required_cols.items():
found = False
for candidate in candidates:
if candidate in df.columns:
col_mapping[required] = candidate
found = True
break
if not found:
logger.error(
"[UC-4.8] Required column '%s' not found. Available: %s",
required,
df.columns.tolist(),
)
return _create_error_message(f"Missing required column: {required}")
if col_mapping["sample"] != "sample":
df = df.rename(columns={col_mapping["sample"]: "sample"})
if col_mapping["compoundname"] != "compoundname":
df = df.rename(columns={col_mapping["compoundname"]: "compoundname"})
if col_mapping["genesymbol"] != "genesymbol":
df = df.rename(columns={col_mapping["genesymbol"]: "genesymbol"})
if col_mapping["ko"] != "ko":
df = df.rename(columns={col_mapping["ko"]: "ko"})
filtered_df = _apply_dual_filter(
df,
"sample",
selected_samples,
"genesymbol",
selected_genes,
)
title_parts = []
sample_label = _format_selection_label("Sample", selected_samples)
gene_label = _format_selection_label("Gene", selected_genes)
if sample_label:
title_parts.append(sample_label)
if gene_label:
title_parts.append(gene_label)
plot_title = (
"Gene Inventory for " + " & ".join(title_parts)
if title_parts
else "Gene Inventory"
)
if filtered_df.empty:
filter_desc = []
if selected_samples:
filter_desc.append(f"{len(selected_samples)} sample(s)")
if selected_genes:
filter_desc.append(f"{len(selected_genes)} gene(s)")
logger.warning("[UC-4.8] No data found for selected filters")
return _create_error_message(
"No gene presence found for the selected filters "
f"({', '.join(filter_desc)}). Try a different combination."
)
logger.info(
"[UC-4.8] Filtered data: %s rows (samples=%s, genes=%s)",
len(filtered_df),
len(selected_samples),
len(selected_genes),
)
filtered_df = filtered_df.dropna(
subset=["sample", "compoundname", "genesymbol", "ko"]
)
if filtered_df.empty:
logger.warning("[UC-4.8] No valid data after removing NaNs")
return _create_error_message(
"No valid gene inventory found after data cleaning."
)
use_case_id = "UC-4.8"
logger.info(
"[UC-4.8] Calling PlotService for %s with %s rows",
use_case_id,
len(filtered_df),
)
fig = plot_service.generate_plot(use_case_id=use_case_id, data=filtered_df)
fig.update_layout(title=plot_title, title_x=0.5)
logger.info("[UC-4.8] [OK] Plot generated successfully")
try:
suggested = sanitize_filename("UC-4.8", "compound_network", "png")
except Exception:
suggested = "compound_network.png"
base_filename = os.path.splitext(suggested)[0]
return dcc.Graph(
figure=fig,
config={
"displayModeBar": True,
"toImageButtonOptions": {
"format": "svg",
"filename": base_filename,
},
},
style={"height": "600px"},
)
except ValueError as ve:
logger.error(f"[UC-4.8] Value error: {ve}")
return _create_error_message(str(ve))
except Exception as e:
logger.error(f"[UC-4.8] Rendering error: {e}", exc_info=True)
return _create_error_message(f"Error generating chart: {str(e)}")