def register_uc_4_5_callbacks(app, plot_service) -> None:
"""
Register UC-4.5 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, pathway dropdown initialization,
and scatter plot rendering
- Refer to official documentation for processing logic details
"""
@app.callback(
Output("uc-4-5-collapse", "is_open"),
Input("uc-4-5-collapse-button", "n_clicks"),
State("uc-4-5-collapse", "is_open"),
prevent_initial_call=True,
)
def toggle_uc_4_5_info_panel(n_clicks, is_open):
"""
Toggle UC-4.5 informative panel collapse.
Parameters
----------
n_clicks : int
Number of clicks on collapse button.
is_open : bool
Current collapse state.
Returns
-------
bool
New collapse state (toggled).
"""
logger.info(
f"[UC-4.5] 🔘 Toggle clicked! n_clicks={n_clicks}, is_open={is_open}"
)
if n_clicks:
new_state = not is_open
logger.info(f"[UC-4.5] [OK] Panel toggled to: {new_state}")
return new_state
logger.info(f"[UC-4.5] ⊘ No clicks, keeping is_open={is_open}")
return is_open
@app.callback(
[
Output("uc-4-5-pathway-dropdown", "options"),
Output("uc-4-5-pathway-dropdown", "value"),
],
[
Input("merged-result-store", "data"),
Input("uc-4-5-accordion-group", "active_item"),
],
prevent_initial_call=True,
)
def initialize_pathway_dropdown_uc_4_5(
merged_data: Optional[dict], active_item: Optional[str]
) -> Tuple[list, None]:
"""
Initialize pathway dropdown with KEGG data.
This callback populates the dropdown menu with available pathways
extracted from processed KEGG data, enabling users to select
specific pathways for gene presence mapping.
Data Processing (inline):
1. Extract KEGG data from store
2. Validate 'Pathway' column exists
3. Extract unique pathways
4. Sort alphabetically
5. Create dropdown options
Parameters
----------
merged_data : Optional[dict]
Pre-processed merged data stored in merged-result-store.
Expected structure: dict with 'kegg_df' key.
active_item : Optional[str]
Currently active accordion item (triggers re-initialization).
Returns
-------
Tuple[list, None]
- First element: List of dropdown option dictionaries with
label/value pairs for pathway selection. Empty list
if no data available.
- Second element: Default selection value (None for no
initial selection).
Raises
------
PreventUpdate
If no data available or 'Pathway' column not found.
"""
logger.info(
f"[UC-4.5] 🔄 Dropdown init triggered, data type: {type(merged_data)}"
)
if not merged_data:
logger.debug("[UC-4.5] No data in store, preventing dropdown init")
return [], None
# Check if this is initial call with empty/invalid data
if isinstance(merged_data, dict) and not merged_data:
logger.debug("[UC-4.5] Empty dict in store, preventing dropdown init")
return [], None
try:
# Extract KEGG DataFrame from store
if not isinstance(merged_data, dict) or "kegg_df" not in merged_data:
logger.error(
f"[UC-4.5] Invalid data format: expected dict with 'kegg_df', "
f"got {type(merged_data)}"
)
raise PreventUpdate
df = pd.DataFrame(merged_data["kegg_df"])
# Validate 'Pathway' column exists
pathway_col = None
for col_name in ["Pathway", "pathway", "pathname", "pathway_name"]:
if col_name in df.columns:
pathway_col = col_name
break
if pathway_col is None:
logger.error(
f"[UC-4.5] 'Pathway' column not found in KEGG data. "
f"Available columns: {df.columns.tolist()}"
)
raise PreventUpdate
# DATA PROCESSING: Extract unique pathways (inline)
pathways = sorted(df[pathway_col].dropna().unique())
# Create dropdown options
options = [{"label": pathway, "value": pathway} for pathway in pathways]
logger.info(f"[UC-4.5] Dropdown initialized with {len(options)} pathways")
return options, None
except Exception as e:
logger.error(f"[UC-4.5] Dropdown error: {e}")
raise PreventUpdate
@app.callback(
Output("uc-4-5-chart-container", "children"),
Input("uc-4-5-pathway-dropdown", "value"),
State("merged-result-store", "data"),
prevent_initial_call=True,
)
def render_uc_4_5(
selected_pathway: Optional[str], merged_data: Optional[dict]
) -> Any:
"""
Render UC-4.5 scatter plot based on selected pathway.
Rendering Logic:
- Dropdown selection: Render scatter plot for selected pathway
- No auto-update (single trigger)
Data Processing (inline):
1. Extract KEGG data from store
2. Validate required columns: 'Sample', 'Pathway', 'KO', 'GeneSymbol'
3. Filter by selected pathway
4. Pass filtered data to PlotService
5. PlotService applies YAML config processing:
- GroupBy ['Sample', 'GeneSymbol']
- Count unique KO (nunique)
- Create scatter plot (X=Sample, Y=GeneSymbol)
Parameters
----------
selected_pathway : Optional[str]
Selected pathway from dropdown.
merged_data : Optional[dict]
Merged data from store with 'kegg_df' key.
Returns
-------
dcc.Graph or html.Div
Scatter plot component or error message.
Raises
------
PreventUpdate
If no pathway selected or no data available.
"""
# Check dropdown selection
if not selected_pathway:
logger.debug("[UC-4.5] No pathway selected")
raise PreventUpdate
# Check data availability
if not merged_data:
logger.warning("[UC-4.5] No data available")
return _create_error_message("No data available for visualization")
try:
# Extract KEGG DataFrame from store
logger.debug(f"[UC-4.5] Received data type: {type(merged_data)}")
if not isinstance(merged_data, dict) or "kegg_df" not in merged_data:
logger.error(
f"[UC-4.5] Invalid data format: expected dict with 'kegg_df'"
)
return _create_error_message(
"KEGG database data not found. "
"Please ensure KEGG data is loaded."
)
df = pd.DataFrame(merged_data["kegg_df"])
# Validate required columns
required_cols = {
"Sample": ["Sample", "sample", "sample_id"],
"Pathway": ["Pathway", "pathname", "pathway_name"],
"KO": ["KO", "ko", "ko_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(
f"[UC-4.5] Required column '{required}' not found. "
f"Available: {df.columns.tolist()}"
)
return _create_error_message(f"Missing required column: {required}")
# Normalize column names if needed
if col_mapping["Sample"] != "Sample":
df = df.rename(columns={col_mapping["Sample"]: "Sample"})
if col_mapping["Pathway"] != "Pathway":
df = df.rename(columns={col_mapping["Pathway"]: "Pathway"})
if col_mapping["KO"] != "KO":
df = df.rename(columns={col_mapping["KO"]: "KO"})
if col_mapping["GeneSymbol"] != "GeneSymbol":
df = df.rename(columns={col_mapping["GeneSymbol"]: "GeneSymbol"})
# DATA PROCESSING: Filter by selected pathway
pathway_data = df[df["Pathway"] == selected_pathway].copy()
if pathway_data.empty:
logger.warning(
f"[UC-4.5] No data found for pathway '{selected_pathway}'"
)
return _create_error_message(
f"No gene data found for pathway: {selected_pathway}"
)
logger.info(
f"[UC-4.5] Filtered data for pathway '{selected_pathway}': "
f"{len(pathway_data)} rows"
)
# Remove rows with missing GeneSymbol
pathway_data = pathway_data.dropna(subset=["GeneSymbol"])
if pathway_data.empty:
logger.warning(
f"[UC-4.5] No gene symbols found for pathway '{selected_pathway}'"
)
return _create_error_message(
f"No gene symbols found for pathway: {selected_pathway}"
)
# Generate plot using PlotService
# (Further processing defined in uc_4_5_config.yaml)
use_case_id = "UC-4.5"
logger.info(
f"[UC-4.5] Calling PlotService for {use_case_id} "
f"with {len(pathway_data)} rows"
)
fig = plot_service.generate_plot(use_case_id=use_case_id, data=pathway_data)
logger.info(f"[UC-4.5] [OK] Plot generated successfully")
try:
suggested = sanitize_filename("UC-4.5", "gene_presence_absence", "png")
except Exception:
suggested = "gene_presence_absence.png"
base_filename = os.path.splitext(suggested)[0]
return dcc.Graph(
figure=fig,
config={
"displayModeBar": True,
"toImageButtonOptions": {
"format": "svg",
"filename": base_filename,
},
},
style={"height": "750px"},
)
except ValueError as ve:
logger.error(f"[UC-4.5] Value error: {ve}")
return _create_error_message(str(ve))
except Exception as e:
logger.error(f"[UC-4.5] Rendering error: {e}", exc_info=True)
return _create_error_message(f"Error generating chart: {str(e)}")