fixed bug due to removing outlier detection

mtor/workflows.py

@@ -12,8 +12,7 @@ from .dataproc import (
     construct_data_frame,
     find_guard_threshold,
     check_guards,
-    find_outliers,
-    select_on_guards_and_outliers,
+    select_on_guards,
     smooth_rolling_min,
     smooth_savgol_filter,
     find_extremas,
@@ -23,15 +22,14 @@ from .dataproc import (
 from .postproc import (
     stem_file_list,
     annotate_color_coded_images,
-    sort_cut_images,
-    remove_cuts_dir,
+    rename_cut_images,
 )
 
 
 def prescan_workflow(folder, top, right, bottom, left, **kargs):
     print("1/5: scanning tifs for common autocontrast values")
 
-    parameters = Parameters(folder, top, right, bottom, left)
+    parameters = Parameters(folder, top, right, bottom, left, **kargs)
     parameters = scan_tifs(parameters)
 
     parameters.offset = parameters.intensity_min
@@ -64,9 +62,8 @@ def data_workflow(stats_results, parameters):
 
     find_guard_threshold(data_frame, parameters)
     data_frame = check_guards(data_frame, parameters)
-    data_frame = find_outliers(data_frame, parameters)
 
-    selected_df = select_on_guards_and_outliers(data_frame, parameters)
+    selected_df = select_on_guards(data_frame, parameters)
     selected_df = smooth_rolling_min(selected_df, parameters)
     selected_df = smooth_savgol_filter(selected_df, parameters)
 
@@ -79,10 +76,9 @@ def data_workflow(stats_results, parameters):
 
 
 def postprocessing_workflow(selected_files, parameters):
-    print("4/5: Post processing, sorting cut images")
+    print("4/5: Post processing, renaming cut images")
     file_stems = stem_file_list(selected_files)
-    sort_cut_images(file_stems, parameters)
-    remove_cuts_dir(parameters)
+    rename_cut_images(file_stems, parameters)
     print("5/5: Post processing, annotating color coded images")
     annotate_color_coded_images(file_stems, parameters)
     return WorkflowResult(None, parameters)
@@ -96,9 +92,8 @@ def cached_data_workflow(folder):
     data_frame, parameters = load_temp(folder)
     find_guard_threshold(data_frame, parameters)
     data_frame = check_guards(data_frame, parameters)
-    data_frame = find_outliers(data_frame, parameters)
 
-    selected_df = select_on_guards_and_outliers(data_frame, parameters)
+    selected_df = select_on_guards(data_frame, parameters)
     selected_df = smooth_rolling_min(selected_df, parameters)
     selected_df = smooth_savgol_filter(selected_df, parameters)