def register_uc_3_7_callbacks(app, plot_service) -> None:
"""
Register all UC-3.7 callbacks with Dash app.
Parameters
----------
app : Dash
Dash application instance.
plot_service : PlotService
Singleton PlotService instance (shared across all callbacks).
Notes
-----
- Registers panel toggle and correlogram rendering callbacks
- Refer to official documentation for processing logic details
"""
logger.info("[UC-3.7] Registering callbacks")
# ========================================
# Callback 1: Toggle Informative Panel
# ========================================
@app.callback(
Output("uc-3-7-collapse", "is_open"),
Input("uc-3-7-collapse-button", "n_clicks"),
State("uc-3-7-collapse", "is_open"),
prevent_initial_call=True,
)
def toggle_uc_3_7_info_panel(n_clicks: Optional[int], is_open: bool) -> bool:
"""
Toggle UC-3.7 informative panel collapse state.
Parameters
----------
n_clicks : int
Number of times button was clicked.
is_open : bool
Current collapse state.
Returns
-------
bool
New collapse state (toggled).
Notes
-----
Simple toggle: open -> close, close -> open.
"""
if n_clicks:
logger.debug(f"[UC-3.7] Toggling info panel: {is_open} -> {not is_open}")
return not is_open
return is_open
# ========================================
# Callback 2: Render Correlogram
# ========================================
@app.callback(
Output("uc-3-7-chart", "children"),
Input("uc-3-7-accordion-group", "active_item"),
State("merged-result-store", "data"),
prevent_initial_call=True,
)
def render_uc_3_7(
active_item: Optional[str], merged_data: Optional[Dict[str, Any]]
) -> html.Div:
"""
Render UC-3.7 correlogram when accordion is activated.
Parameters
----------
active_item : str, optional
ID of the currently active accordion item.
merged_data : dict, optional
Dictionary containing merged result data with 'biorempp_df' key.
Returns
-------
html.Div
Container with chart or error message.
Raises
------
PreventUpdate
If accordion is not active or data is not ready.
Notes
-----
- Validates merged_data structure and extracts BioRemPP DataFrame
- Maps column names flexibly (Sample/Compound_Name with multiple aliases)
- Cleans data by stripping whitespace and removing nulls
- Passes prepared data to CorrelogramStrategy via PlotService
- Generates compound-compound correlation matrix heatmap
"""
logger.debug(f"[UC-3.7] Render callback triggered. Active item: {active_item}")
# Check if UC-3.7 accordion is active
if not active_item or active_item != "uc-3-7-accordion":
logger.debug("[UC-3.7] Accordion not active. Preventing update.")
raise PreventUpdate
try:
# ========================================
# Step 1: Validate merged_data structure
# ========================================
if not merged_data:
logger.warning("[UC-3.7] merged_data is None or empty")
return _create_error_message(
"No data available. Please upload and process data first.",
"bi bi-exclamation-triangle",
)
if not isinstance(merged_data, dict):
logger.error("[UC-3.7] merged_data is not a dictionary")
return _create_error_message(
"Invalid data structure. Please reload the application.",
"bi bi-x-circle",
)
if "biorempp_df" not in merged_data:
logger.error("[UC-3.7] merged_data does not contain 'biorempp_df' key")
return _create_error_message(
"BioRemPP data not found. This use case requires "
"BioRemPP database.",
"bi bi-database-x",
)
# ========================================
# Step 2: Extract DataFrame
# ========================================
logger.debug("[UC-3.7] Extracting DataFrame from merged_data")
biorempp_data = merged_data["biorempp_df"]
if not biorempp_data:
logger.warning("[UC-3.7] biorempp_df is empty")
return _create_error_message(
"BioRemPP dataset is empty. Please check your input data.",
"bi bi-inbox",
)
df = pd.DataFrame(biorempp_data)
if df.empty:
logger.warning("[UC-3.7] DataFrame is empty after conversion")
return _create_error_message(
"No data available after processing.", "bi bi-inbox"
)
logger.info(
f"[UC-3.7] Processing DataFrame: {len(df)} rows, "
f"{len(df.columns)} columns"
)
logger.debug(f"[UC-3.7] Available columns: {df.columns.tolist()}")
# ========================================
# Step 3: Map column names flexibly
# ========================================
col_map = {}
# Try to find Sample column
sample_candidates = [
"Sample",
"sample",
"sample_id",
"Sample_ID",
"sampleID",
"genome",
"Genome",
"organism",
]
for col_name in sample_candidates:
if col_name in df.columns:
col_map["Sample"] = col_name
logger.debug(f"[UC-3.7] Mapped Sample to '{col_name}'")
break
# Try to find Compound_Name column
compound_candidates = [
"Compound_Name",
"compound_name",
"compoundname",
"CompoundName",
"compound",
"Compound",
"chemical",
"Chemical",
"chemical_name",
]
for col_name in compound_candidates:
if col_name in df.columns:
col_map["Compound_Name"] = col_name
logger.debug(f"[UC-3.7] Mapped Compound_Name to '{col_name}'")
break
# ========================================
# Step 4: Validate required columns found
# ========================================
missing_cols = []
if "Sample" not in col_map:
missing_cols.append("Sample")
logger.error(
f"[UC-3.7] Sample column not found. "
f"Available: {df.columns.tolist()}"
)
if "Compound_Name" not in col_map:
missing_cols.append("Compound_Name")
logger.error(
f"[UC-3.7] Compound_Name column not found. "
f"Available: {df.columns.tolist()}"
)
if missing_cols:
return _create_error_message(
f"Required columns not found: {', '.join(missing_cols)}. "
f"Available columns: {', '.join(df.columns[:5])}...",
"bi bi-exclamation-octagon",
)
# Extract mapped column names
sample_col = col_map["Sample"]
compound_col = col_map["Compound_Name"]
logger.debug(
f"[UC-3.7] Using columns - "
f"Sample: '{sample_col}', Compound_Name: '{compound_col}'"
)
# ========================================
# Step 5: Prepare data for strategy
# ========================================
# Select and rename columns to standard names
df_for_plot = df[[sample_col, compound_col]].rename(
columns={sample_col: "Sample", compound_col: "Compound_Name"}
)
# Clean data: remove nulls
initial_count = len(df_for_plot)
df_for_plot = df_for_plot.dropna()
# Strip whitespace from string columns
df_for_plot["Sample"] = df_for_plot["Sample"].astype(str).str.strip()
df_for_plot["Compound_Name"] = (
df_for_plot["Compound_Name"].astype(str).str.strip()
)
# Remove empty strings
df_for_plot = df_for_plot[
(df_for_plot["Sample"] != "") & (df_for_plot["Compound_Name"] != "")
]
cleaned_count = len(df_for_plot)
logger.info(
f"[UC-3.7] Data cleaned: {initial_count} -> {cleaned_count} "
f"rows ({initial_count - cleaned_count} removed)"
)
if df_for_plot.empty:
logger.warning("[UC-3.7] No valid data after cleaning")
return _create_error_message(
"No valid Sample-Compound combinations found after cleaning.",
"bi bi-funnel",
)
# Log statistics
n_samples = df_for_plot["Sample"].nunique()
n_compounds = df_for_plot["Compound_Name"].nunique()
logger.info(
f"[UC-3.7] Data statistics: "
f"{n_samples} samples, {n_compounds} unique compounds"
)
# Check minimum compounds for correlation
if n_compounds < 2:
return _create_error_message(
f"Need at least 2 compounds for correlation. "
f"Found: {n_compounds}",
"bi bi-exclamation-triangle",
)
# ========================================
# Step 6: Generate plot using PlotService
# ========================================
logger.debug("[UC-3.7] Calling PlotService to generate correlogram")
fig = plot_service.generate_plot(
use_case_id="UC-3.7", data=df_for_plot, filters={}, force_refresh=False
)
logger.info("[UC-3.7] Correlogram generation successful")
# ========================================
# Step 7: Prepare download filename and return chart component
# ========================================
try:
suggested = sanitize_filename(
"UC-3.7", "compound_cooccurrence_correlogram", "png"
)
except Exception:
suggested = "uc_3_7_compound_cooccurrence_correlogram.png"
base_filename = os.path.splitext(suggested)[0]
return dcc.Graph(
id="uc-3-7-graph",
figure=fig,
config={
"displayModeBar": True,
"displaylogo": False,
"modeBarButtonsToRemove": ["pan2d", "lasso2d", "select2d"],
"toImageButtonOptions": {
"format": "svg",
"filename": base_filename,
"height": 600,
"width": 600,
"scale": 6,
},
},
style={"height": "600px"},
className="mt-3",
)
except ValueError as ve:
logger.error(
f"[UC-3.7] ValueError during processing: {str(ve)}", exc_info=True
)
return _create_error_message(
f"Data validation error: {str(ve)}", "bi bi-exclamation-triangle"
)
except Exception as e:
logger.error(f"[UC-3.7] Unexpected error: {str(e)}", exc_info=True)
return _create_error_message(
f"An unexpected error occurred: {str(e)}", "bi bi-bug"
)
logger.info("[UC-3.7] All callbacks registered successfully")