Enable pawly refinement batch processing for GSASII GUI

qt/python/mantidqtinterfaces/mantidqtinterfaces/Engineering/gui/engineering_diffraction/tabs/gsas2/model.py

@@ -12,7 +12,7 @@
 import subprocess
 from dataclasses import dataclass, field
 from pathlib import Path
-from typing import List, Optional, Union, Tuple, TypeAlias
+from typing import List, Optional, Union, Tuple, TypeAlias, Dict
 
 import matplotlib.pyplot as plt
 from matplotlib.axes import Axes
@@ -194,13 +194,91 @@ def clear_input_components(self) -> None:
         for attr, default in refinement_defaults.items():
             setattr(self, attr, default)
 
+    # def run_model(
+    #     self,
+    #     load_parameters: list,
+    #     refinement_parameters: list,
+    #     project_name: str,
+    #     rb_num: Optional[str] = None,
+    #     user_x_limits: Optional[List[List[float]]] = None,
+    # ) -> Optional[int]:
+    #     self.clear_input_components()
+    #     if not self.initial_validation(project_name, load_parameters):
+    #         return None
+    #     self.set_components_from_inputs(load_parameters, refinement_parameters, project_name, rb_num)
+    #     self.read_phase_files()
+    #     self.generate_reflections_from_space_group()
+
+    #     formatted_limits: Optional[List[List[float]]] = None
+    #     # Ensure both elements are lists of floats and pass formatted limits to validate_x_limits
+    #     if isinstance(user_x_limits, list) and len(user_x_limits) == 2:
+    #         formatted_limits = [
+    #             user_x_limits[0] if isinstance(user_x_limits[0], list) else [user_x_limits[0]],
+    #             user_x_limits[1] if isinstance(user_x_limits[1], list) else [user_x_limits[1]],
+    #         ]
+
+    #     self.validate_x_limits(formatted_limits)
+    #     if not self.further_validation():
+    #         return None
+
+    #     runtime = self.call_gsas2()
+    #     if not runtime:
+    #         return None
+    #     runtime_str = runtime[1]  # Extract the string part of the runtime tuple
+    #     report_result = self.report_on_outputs(runtime_str)
+    #     if report_result is not None:
+    #         gsas_result_filepath, _ = report_result  # Unpack the tuple
+    #     else:
+    #         logger.error("Failed to unpack the result from report_on_outputs.")
+    #         return None
+    #     gsas_result = gsas_result_filepath
+    #     if not gsas_result:
+    #         return None
+    #     self.load_basic_outputs(gsas_result)
+
+    #     if self.state.number_of_regions > self.state.number_histograms:
+    #         return self.state.number_of_regions
+    #     return self.state.number_histograms
+
     def run_model(
         self,
         load_parameters: list,
         refinement_parameters: list,
         project_name: str,
         rb_num: Optional[str] = None,
         user_x_limits: Optional[List[List[float]]] = None,
+    ) -> Optional[Dict[str, int]]:
+        """
+        Returns a dictionary mapping data file names to their result counts
+        """
+        data_files = load_parameters[2]  # Extract data files list
+        num_hist = None
+
+        for data_file in data_files:
+            # Create unique project name for each file
+            file_basename = os.path.splitext(os.path.basename(data_file))[0]
+            individual_project_name = f"{project_name}_{file_basename}"
+
+            # Create modified load_parameters for single file
+            single_file_load_params = [
+                load_parameters[0],  # instrument_files (reuse same)
+                load_parameters[1],  # phase_filepaths (reuse same)
+                [data_file],  # single data file
+            ]
+
+            num_hist = self._run_single_refinement(
+                single_file_load_params, refinement_parameters, individual_project_name, rb_num, user_x_limits
+            )
+
+        return num_hist
+
+    def _run_single_refinement(
+        self,
+        load_parameters: list,
+        refinement_parameters: list,
+        project_name: str,
+        rb_num: Optional[str] = None,
+        user_x_limits: Optional[List[List[float]]] = None,
     ) -> Optional[int]:
         self.clear_input_components()
         if not self.initial_validation(project_name, load_parameters):
@@ -240,6 +318,9 @@ def run_model(
             return self.state.number_of_regions
         return self.state.number_histograms
 
+    # C:/MantidInstall/scripts/Engineering/ENGINX/phase_info/
+    # C:/Users/joy22959/Engineering_Mantid/User/test/Focus/
+
     # ===============
     # Prepare Inputs
     # ===============
@@ -912,9 +993,13 @@ def create_lattice_parameter_table(self, test: bool = False) -> Optional[Union[N
     # ===========
 
     def load_focused_nxs_for_logs(self, filenames: List[str]) -> None:
-        if len(filenames) == 1 and "all_banks" in filenames[0]:
-            filenames = [filenames[0].replace("all_banks", "bank_1"), filenames[0].replace("all_banks", "bank_2")]
+        banks_filenames = []
         for filename in filenames:
+            if "all_banks" in filename:
+                banks_filenames.extend([filename.replace("all_banks", "bank_1"), filename.replace("all_banks", "bank_2")])
+            else:
+                banks_filenames.append(filename)
+        for filename in banks_filenames:
             filename = filename.replace(".gss", ".nxs")
             ws_name = _generate_workspace_name(filename, self._suffix)
             if ws_name not in self._data_workspaces.get_loaded_workpace_names():