Merge remote-tracking branch 'origin/reader_benchmarks' into energy_c…

…alibration_bias_shift

benchmarks/benchmark_sed.py

@@ -56,9 +56,9 @@ def test_binning_1d() -> None:
     print(result)
     assert min(result) < targets["binning_1d"]
     # update targets if substantial improvement occurs
-    if np.mean(result) < 0.8 * targets["binning_1d"]:
-        print(f"Updating targets for 'binning_1d' to {float(np.mean(result) * 1.2)}")
-        targets["binning_1d"] = float(np.mean(result) * 1.2)
+    if np.mean(result) < 0.75 * targets["binning_1d"]:
+        print(f"Updating targets for 'binning_1d' to {float(np.mean(result) / 0.75)}")
+        targets["binning_1d"] = float(np.mean(result) / 0.75)
         save_config(targets, package_dir + "/../benchmarks/benchmark_targets.yaml")
 
 
@@ -80,9 +80,9 @@ def test_binning_4d() -> None:
     print(result)
     assert min(result) < targets["binning_4d"]
     # update targets if substantial improvement occurs
-    if np.mean(result) < 0.8 * targets["binning_4d"]:
-        print(f"Updating targets for 'binning_4d' to {float(np.mean(result) * 1.2)}")
-        targets["binning_4d"] = float(np.mean(result) * 1.2)
+    if np.mean(result) < 0.75 * targets["binning_4d"]:
+        print(f"Updating targets for 'binning_4d' to {float(np.mean(result) / 0.75)}")
+        targets["binning_4d"] = float(np.mean(result) / 0.75)
         save_config(targets, package_dir + "/../benchmarks/benchmark_targets.yaml")
 
 
@@ -105,9 +105,9 @@ def test_splinewarp() -> None:
     print(result)
     assert min(result) < targets["inv_dfield"]
     # update targets if substantial improvement occurs
-    if np.mean(result) < 0.8 * targets["inv_dfield"]:
-        print(f"Updating targets for 'inv_dfield' to {float(np.mean(result) * 1.2)}")
-        targets["inv_dfield"] = float(np.mean(result) * 1.2)
+    if np.mean(result) < 0.75 * targets["inv_dfield"]:
+        print(f"Updating targets for 'inv_dfield' to {float(np.mean(result) / 0.75)}")
+        targets["inv_dfield"] = float(np.mean(result) / 0.75)
         save_config(targets, package_dir + "/../benchmarks/benchmark_targets.yaml")
 
 
@@ -139,9 +139,9 @@ def test_workflow_1d() -> None:
     print(result)
     assert min(result) < targets["workflow_1d"]
     # update targets if substantial improvement occurs
-    if np.mean(result) < 0.8 * targets["workflow_1d"]:
-        print(f"Updating targets for 'workflow_1d' to {float(np.mean(result) * 1.2)}")
-        targets["workflow_1d"] = float(np.mean(result) * 1.2)
+    if np.mean(result) < 0.75 * targets["workflow_1d"]:
+        print(f"Updating targets for 'workflow_1d' to {float(np.mean(result) / 0.75)}")
+        targets["workflow_1d"] = float(np.mean(result) / 0.75)
         save_config(targets, package_dir + "/../benchmarks/benchmark_targets.yaml")
 
 
@@ -173,9 +173,9 @@ def test_workflow_4d() -> None:
     print(result)
     assert min(result) < targets["workflow_4d"]
     # update targets if substantial improvement occurs
-    if np.mean(result) < 0.8 * targets["workflow_4d"]:
-        print(f"Updating targets for 'workflow_4d' to {float(np.mean(result) * 1.2)}")
-        targets["workflow_4d"] = float(np.mean(result) * 1.2)
+    if np.mean(result) < 0.75 * targets["workflow_4d"]:
+        print(f"Updating targets for 'workflow_4d' to {float(np.mean(result) / 0.75)}")
+        targets["workflow_4d"] = float(np.mean(result) / 0.75)
         save_config(targets, package_dir + "/../benchmarks/benchmark_targets.yaml")
 
 
@@ -199,10 +199,10 @@ def test_loader_compute(loader: BaseLoader) -> None:
         print(result)
         assert min(result) < targets[f"loader_compute_{loader_name}"]
         # update targets if substantial improvement occurs
-        if np.mean(result) < 0.8 * targets[f"loader_compute_{loader_name}"]:
+        if np.mean(result) < 0.75 * targets[f"loader_compute_{loader_name}"]:
             print(
                 f"Updating targets for loader_compute_{loader_name}' "
-                f"to {float(np.mean(result) * 1.2)}",
+                f"to {float(np.mean(result) / 0.75)}",
             )
-            targets[f"loader_compute_{loader_name}"] = float(np.mean(result) * 1.2)
+            targets[f"loader_compute_{loader_name}"] = float(np.mean(result) / 0.75)
             save_config(targets, package_dir + "/../benchmarks/benchmark_targets.yaml")

benchmarks/benchmark_targets.yaml

@@ -1,8 +1,8 @@
-binning_1d: 3.1223518816799785
-binning_4d: 8.959390982640011
-inv_dfield: 5.438782145039997
-loader_compute_flash: 0.21164051592350006
-loader_compute_mpes: 0.07203983277082443
-loader_compute_sxp: 0.024549091011285783
-workflow_1d: 17.297238704399994
-workflow_4d: 20.81487989136001
+binning_1d: 10
+binning_4d: 20
+inv_dfield: 10
+loader_compute_flash: 1
+loader_compute_mpes: 1
+loader_compute_sxp: 1
+workflow_1d: 30
+workflow_4d: 30