Standard curve plots qpcr

app_state.py

@@ -48,7 +48,7 @@ def platewells_by_sample_id(self) -> Dict[str, List[PlateWell]]:
         result = {}
         for plate in self.plate_registry:
             for well in plate.plate_wells:
-                sid = well.sample.sample_id
+                sid = well.get_sample(self).file_sample_identifier
                 if sid:
                     result.setdefault(sid, []).append(well)
         return result

index.py

@@ -32,6 +32,8 @@
     EMPTY_BORDER_PX,
     make_tab,
     get_tab_id,
+    build_standard_curve_figure,
+    build_computed_molarity
 )
 
 pd.set_option('future.no_silent_downcasting', True)
@@ -529,6 +531,54 @@ def plate_mapper(plate_ids, objects):
     raise Exception("ERROR RAISED INTENTIONALLY - Reached end of manipulate_plates without handling trigger... major underlying issue to resolve.")
 
 
+@app.callback(
+        Output({"type": "pcr-curve-graph", "index": MATCH}, "figure"),
+        Output({"type": "pcr-curve-table", "index": MATCH}, "children"),
+        Output({"type": "pcr-curve-store", "index": MATCH}, "data"),
+        Input("app_data_state", "data"),
+        State({"type": "datatable-plate", "index": MATCH}, "rowData"),
+        State({"type": "datatable-plate", "index": MATCH}, "id"),
+        prevent_initial_call=True,
+)
+def update_standard_curve(app_state, row_data, plate_id):
+
+    if not row_data:
+        return no_update, no_update, no_update
+
+    else: 
+        app_state = AppState.from_json(app_state)
+        plate = app_state.plate_by_id.get(plate_id.get("index"))
+        df = plate.dataset(app_state, tidy=True).replace(['None', 'none', 'NaN', 'nan', ''], np.nan).infer_objects(copy=False)
+
+        # grab only samples which are defined as standards 
+        standards_df = df[df['sample_type'] == 'Standard'].copy()
+
+        # ensure numeric and drop rows with missing/invalid Standard or Cq
+        standards_df["Standard"] = pd.to_numeric(standards_df["Standard"], errors="coerce")
+        standards_df = standards_df.loc[standards_df["Standard"].notna() & standards_df["Cq"].notna()]
+
+        pcr_fig, slope, intercept, efficiency, r_squared = build_standard_curve_figure(standards_df)
+        store_data = {
+            "slope": slope,
+            "intercept": intercept,
+            "efficiency": efficiency,
+            "r_squared": r_squared
+        }
+
+        pcr_table_children = [
+            html.Tr([html.Th("PCR Efficiency"), html.Th("R-Squared"), html.Th("Slope"), html.Th("Intercept")]),
+            html.Tr([
+                html.Td(f"{efficiency:.1f}%"),
+                html.Td(f"{r_squared:.3f}"),
+                html.Td(f"{slope:.3f}"),
+                html.Td(f"{intercept:.3f}")
+            ])
+        ]
+        return pcr_fig, pcr_table_children, store_data
+
+
+
+
 @app.callback(
     [
         Output("dynamic-tabs", "children", allow_duplicate=True),
@@ -766,10 +816,14 @@ def sync_plate_style(cell_evt, row_data, virtual_row_data, fig):
     Output({"type": "datatable-plate", "index": MATCH}, "rowData"),
     Input("update-rows-trigger-div", "children"),                     # broadcast trigger
     Input("app_data_state", "data"),                                  # source of truth
+    Input({"type": "pcr-curve-store", "index": MATCH}, "data"),       # for qPCR plates, to show efficiency etc
+    # Input({"type": "phix-control-dropdown", "index": MATCH}, "value"), # to highlight the selected phix control value
     State({"type": "datatable-plate", "index": MATCH}, "id"),         # gives us the plate_id (via id["index"])
     prevent_initial_call=True
 )
-def update_rows_callback(_, app_data_state_json, table_id):
+# def update_rows_callback(_, app_data_state_json, pcr_store, phix_control_value, table_id):
+def update_rows_callback(_, app_data_state_json, pcr_store, table_id):
+
     if not app_data_state_json or not table_id:
         raise PreventUpdate
 
@@ -778,14 +832,23 @@ def update_rows_callback(_, app_data_state_json, table_id):
 
     # find the plate by invariant key
     plate = app_state.plate_by_id.get(plate_id)
+
+    slope, intercept = pcr_store.get("slope"), pcr_store.get("intercept") if pcr_store else (None, None)
+
+    phix_correction_factor = 1.0
+
+    # if phix_control_value is None:
+    #     phix_correction_factor = 1.0
+    # else:
+    #     phix_correction_factor = 10 / float(phix_control_value)
+
     if not plate:
         return None
 
-    print("Processing Plate ID:", plate_id)
-
     is_qpcr = (plate.plate_type == "qPCR")
 
     df = plate.dataset(app_state, tidy=False).replace(['None', 'none', 'NaN', 'nan', ''], np.nan).infer_objects(copy=False)
+    df = build_computed_molarity(app_state, plate, slope, intercept, phix_correction_factor) 
 
     # Keep columns tidy, but do not drop keys AG Grid needs (e.g., well_position_id if you use getRowId)
     if is_qpcr:
@@ -842,7 +905,7 @@ def update_plate_buttons(app_data_state_json, selected_tab):
                 colum_value = row.get(region_molarity_col)
                 plate_type_display = "TS"           
             label = f"{plate_type_display} - PhiX - {well} - {colum_value}"
-            value = f"{plate_type_display} - {well} - {colum_value}"  
+            value = str(colum_value)  
             dropdown_options.append({"label": label, "value": value})
 
     return html.Div(

models.py

@@ -45,9 +45,11 @@ class Sample(BaseModel):
     container: Optional[str] = ""
     file_sample_identifier: Optional[str] = "" # File-specific column for identifying the sample
     sample_type: Optional[SampleType] = SampleType.LIBRARY
+    computed_molarity: Optional[float | str] = " - "  # Computed molarity for qPCR samples
+    computed_standard_error: Optional[float | str] = " - "  # Standard error for qPCR samples
 
     def get_plate_wells(self, app_state):
-        return app_state.platewells_by_sample_id.get(self.sample_id, [])
+        return app_state.platewells_by_sample_id.get(self.file_sample_identifier, [])
 
 
 #####################################################
@@ -157,6 +159,10 @@ def get_well_by_position(self, position: str) -> Optional["PlateWell"]:
 
     def to_json(self) -> str:
         return self.model_dump_json()
+
+    def get_samples(self, app_state) -> List[Sample]:
+        sample_ids = {well.sample_identifier for well in self.plate_wells}
+        return [app_state.sample_by_id[sid] for sid in sample_ids if sid in app_state.sample_by_id]
 
     @classmethod
     def from_json(cls, json_str: str) -> "Plate":
@@ -260,7 +266,7 @@ def from_file(cls, input_file: "File", app_state) -> "Plate":
 
                 app_state.sample_registry.append(sample)
 
-                print("created sample", sample)
+                # print("created sample", sample)
                 for well_position, well_df in df_slice.groupby(input_file.well_position_id):
                     well_kwargs = {}
                     if input_file.plate_specific_columns: