update AR and add coverage

reduction/test/test_scaling_factors.py

@@ -138,3 +138,29 @@ def test_compute_sf_with_deadtime_tof_200(nexus_dir):
     assert output is True
 
     check_results(output_cfg, 'data/sf_197912_Si_dt_par_46_200.cfg')
+
+
+def test_compute_sf_with_deadtime_tof_200_sort(nexus_dir):
+    """
+        Test the computation of scaling factors
+    """
+    with amend_config(data_dir=nexus_dir):
+        ws = mtd_api.Load("REF_L_197912")
+
+    output_dir = '/tmp'
+
+    output_cfg = os.path.join(output_dir, "sf_197912_Si_test_dt.cfg")
+    if os.path.isfile(output_cfg):
+        os.remove(output_cfg)
+
+    output = sf_workflow.process_scaling_factors(ws, output_dir,
+                                                 order_by_runs=False,
+                                                 use_deadtime=True,
+                                                 deadtime=4.6,
+                                                 deadtime_tof_step=200,
+                                                 paralyzable=False,
+                                                 wait=False, postfix='_test_dt')
+    assert output is True
+
+    check_results(output_cfg, 'data/sf_197912_Si_dt_par_46_200.cfg')
+

scripts/autoreduce/reduce_REF_L.py

@@ -71,12 +71,6 @@
 # Check the measurement geometry. This will be useful later
 #if ws.getRun().getProperty('BL4B:CS:ExpPl:OperatingMode').value[0] == 'Free Liquid':
 
-# Determine whether we have to go through the legacy reduction to
-# process direct beams
-if not old_version and ws.getRun().hasProperty("data_type"):
-    data_type = ws.getRun().getProperty("data_type").value[0]
-    old_version = not data_type == 0
-
 if old_version:
     SetInstrumentParameter(ws, ParameterName="dq-constant", Value="0.0", ParameterType="Number")
     output = LRAutoReduction(#Filename=event_file_path,
@@ -90,17 +84,27 @@
                              TemplateFile=template_file)
     first_run_of_set=int(output[1])
 else:
-    print("Average overlap: %s" % avg_overlap)
-    print("Constant-Q binning: %s" % const_q)
-    from lr_reduction import workflow
-    if True:
+    data_type = ws.getRun().getProperty("data_type").value[0]
+    # Direct beam data
+    if data_type == 1:
+        from lr_reduction.scaling_factors import workflow as sf_workflow
+        sf_workflow.process_scaling_factors(ws, output_dir,
+                                            tof_step=200,
+                                            order_by_runs=True,
+                                            use_deadtime=True,
+                                            deadtime=4.2,
+                                            deadtime_tof_step=200,
+                                            paralyzable=True,
+                                            wait=True,
+                                            slit_tolerance=0.07)
+    else:
+        # Scattering data
+        print("Average overlap: %s" % avg_overlap)
+        print("Constant-Q binning: %s" % const_q)
+        from lr_reduction import workflow
         first_run_of_set = workflow.reduce(ws, template_file, output_dir,
                                            average_overlap=avg_overlap,
                                            q_summing=const_q, bck_in_q=False)
-    else:
-        first_run_of_set = workflow.reduce_fixed_two_theta(ws, template_file, output_dir,
-                                                           average_overlap=avg_overlap,
-                                                           q_summing=const_q, bck_in_q=False)
 
 #-------------------------------------------------------------------------
 # Produce plot for the web monitor