style(PLRsearch): format according to black

Change-Id: I26e0ce172740f7f440469578294f8c13fec5850b
Signed-off-by: Vratko Polak <vrpolak@cisco.com>

1 files changed, 32 insertions, 21 deletions

diff --git a/resources/libraries/python/PLRsearch/Integrator.py b/resources/libraries/python/PLRsearch/Integrator.py
index 7f118db00d..f80110ce29 100644
--- a/resources/libraries/python/PLRsearch/Integrator.py
+++ b/resources/libraries/python/PLRsearch/Integrator.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2022 Cisco and/or its affiliates.
+# Copyright (c) 2024 Cisco and/or its affiliates.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at:
@@ -192,9 +192,12 @@ def estimate_nd(communication_pipe, scale_coeff=8.0, trace_enabled=False):
     debug_list = list()
     trace_list = list()
     # Block until input object appears.
-    dimension, dilled_function, param_focus_tracker, max_samples = (
-        communication_pipe.recv()
-    )
+    (
+        dimension,
+        dilled_function,
+        param_focus_tracker,
+        max_samples,
+    ) = communication_pipe.recv()
     debug_list.append(
         f"Called with param_focus_tracker {param_focus_tracker!r}"
     )
@@ -237,16 +240,18 @@ def estimate_nd(communication_pipe, scale_coeff=8.0, trace_enabled=False):
         if max_samples and samples >= max_samples:
             break
         sample_point = generate_sample(
-            param_focus_tracker.averages, param_focus_tracker.covariance_matrix,
-            dimension, scale_coeff
+            param_focus_tracker.averages,
+            param_focus_tracker.covariance_matrix,
+            dimension,
+            scale_coeff,
         )
-        trace(u"sample_point", sample_point)
+        trace("sample_point", sample_point)
         samples += 1
-        trace(u"samples", samples)
+        trace("samples", samples)
         value, log_weight = value_logweight_function(trace, *sample_point)
-        trace(u"value", value)
-        trace(u"log_weight", log_weight)
-        trace(u"focus tracker before adding", param_focus_tracker)
+        trace("value", value)
+        trace("log_weight", log_weight)
+        trace("focus tracker before adding", param_focus_tracker)
         # Update focus related statistics.
         param_distance = param_focus_tracker.add_without_dominance_get_distance(
             sample_point, log_weight
@@ -254,22 +259,28 @@ def estimate_nd(communication_pipe, scale_coeff=8.0, trace_enabled=False):
         # The code above looked at weight (not importance).
         # The code below looks at importance (not weight).
         log_rarity = param_distance / 2.0 / scale_coeff
-        trace(u"log_rarity", log_rarity)
+        trace("log_rarity", log_rarity)
         log_importance = log_weight + log_rarity
-        trace(u"log_importance", log_importance)
+        trace("log_importance", log_importance)
         value_tracker.add(value, log_importance)
         # Update sampled statistics.
         param_sampled_tracker.add_get_shift(sample_point, log_importance)
     debug_list.append(f"integrator used {samples!s} samples")
     debug_list.append(
-        u" ".join([
-            u"value_avg", str(value_tracker.average),
-            u"param_sampled_avg", repr(param_sampled_tracker.averages),
-            u"param_sampled_cov", repr(param_sampled_tracker.covariance_matrix),
-            u"value_log_variance", str(value_tracker.log_variance),
-            u"value_log_secondary_variance",
-            str(value_tracker.secondary.log_variance)
-        ])
+        " ".join(
+            [
+                "value_avg",
+                str(value_tracker.average),
+                "param_sampled_avg",
+                repr(param_sampled_tracker.averages),
+                "param_sampled_cov",
+                repr(param_sampled_tracker.covariance_matrix),
+                "value_log_variance",
+                str(value_tracker.log_variance),
+                "value_log_secondary_variance",
+                str(value_tracker.secondary.log_variance),
+            ]
+        )
     )
     communication_pipe.send(
         (value_tracker, param_focus_tracker, debug_list, trace_list, samples)