style(PLRsearch): format according to black

[csit.git] / resources / libraries / python / PLRsearch / stat_trackers.py

diff --git a/resources/libraries/python/PLRsearch/stat_trackers.py b/resources/libraries/python/PLRsearch/stat_trackers.py
index e0b21dc..d19eebe 100644 (file)
--- a/resources/libraries/python/PLRsearch/stat_trackers.py
+++ b/resources/libraries/python/PLRsearch/stat_trackers.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2021 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:
 # 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:


@@ -64,8 +64,10 @@ class ScalarStatTracker:
         :returns: Expression constructing an equivalent instance.
         :rtype: str
         """
         :returns: Expression constructing an equivalent instance.
         :rtype: str
         """

-        return f"ScalarStatTracker(log_sum_weight={self.log_sum_weight!r}," \
+        return (
+            f"ScalarStatTracker(log_sum_weight={self.log_sum_weight!r},"

             f"average={self.average!r},log_variance={self.log_variance!r})"
             f"average={self.average!r},log_variance={self.log_variance!r})"

+        )

 
     def copy(self):
         """Return new ScalarStatTracker instance with the same state as self.
 
     def copy(self):
         """Return new ScalarStatTracker instance with the same state as self.


@@ -110,7 +112,8 @@ class ScalarStatTracker:
         if absolute_shift > 0.0:
             log_square_shift = 2 * math.log(absolute_shift)
             log_variance = log_plus(
         if absolute_shift > 0.0:
             log_square_shift = 2 * math.log(absolute_shift)
             log_variance = log_plus(

-                log_variance, log_square_shift + log_sample_ratio)
+                log_variance, log_square_shift + log_sample_ratio
+            )

         if log_variance is not None:
             log_variance += old_log_sum_weight - new_log_sum_weight
         self.log_sum_weight = new_log_sum_weight
         if log_variance is not None:
             log_variance += old_log_sum_weight - new_log_sum_weight
         self.log_sum_weight = new_log_sum_weight


@@ -133,10 +136,17 @@ class ScalarDualStatTracker(ScalarStatTracker):
     One typical use is for Monte Carlo integrator to decide whether
     the partial sums so far are reliable enough.
     """
     One typical use is for Monte Carlo integrator to decide whether
     the partial sums so far are reliable enough.
     """

+

     def __init__(
     def __init__(

-            self, log_sum_weight=None, average=0.0, log_variance=None,
-            log_sum_secondary_weight=None, secondary_average=0.0,
-            log_secondary_variance=None, max_log_weight=None):
+        self,
+        log_sum_weight=None,
+        average=0.0,
+        log_variance=None,
+        log_sum_secondary_weight=None,
+        secondary_average=0.0,
+        log_secondary_variance=None,
+        max_log_weight=None,
+    ):

         """Initialize new tracker instance, empty by default.
 
         :param log_sum_weight: Natural logarithm of sum of weights
         """Initialize new tracker instance, empty by default.
 
         :param log_sum_weight: Natural logarithm of sum of weights


@@ -177,12 +187,14 @@ class ScalarDualStatTracker(ScalarStatTracker):
         :rtype: str
         """
         sec = self.secondary
         :rtype: str
         """
         sec = self.secondary

-        return f"ScalarDualStatTracker(log_sum_weight={self.log_sum_weight!r},"\
-            f"average={self.average!r},log_variance={self.log_variance!r}," \
-            f"log_sum_secondary_weight={sec.log_sum_weight!r}," \
-            f"secondary_average={sec.average!r}," \
-            f"log_secondary_variance={sec.log_variance!r}," \
+        return (
+            f"ScalarDualStatTracker(log_sum_weight={self.log_sum_weight!r},"
+            f"average={self.average!r},log_variance={self.log_variance!r},"
+            f"log_sum_secondary_weight={sec.log_sum_weight!r},"
+            f"secondary_average={sec.average!r},"
+            f"log_secondary_variance={sec.log_variance!r},"

             f"max_log_weight={self.max_log_weight!r})"
             f"max_log_weight={self.max_log_weight!r})"

+        )

 
     def add(self, scalar_value, log_weight=0.0):
         """Return updated both stats after addition of another sample.
 
     def add(self, scalar_value, log_weight=0.0):
         """Return updated both stats after addition of another sample.


@@ -242,8 +254,12 @@ class VectorStatTracker:
     """
 
     def __init__(
     """
 
     def __init__(

-            self, dimension=2, log_sum_weight=None, averages=None,
-            covariance_matrix=None):
+        self,
+        dimension=2,
+        log_sum_weight=None,
+        averages=None,
+        covariance_matrix=None,
+    ):

         """Initialize new tracker instance, two-dimensional empty by default.
 
         If any of latter two arguments is None, it means
         """Initialize new tracker instance, two-dimensional empty by default.
 
         If any of latter two arguments is None, it means


@@ -272,10 +288,12 @@ class VectorStatTracker:
         :returns: Expression constructing an equivalent instance.
         :rtype: str
         """
         :returns: Expression constructing an equivalent instance.
         :rtype: str
         """

-        return f"VectorStatTracker(dimension={self.dimension!r}," \
-            f"log_sum_weight={self.log_sum_weight!r}," \
-            f"averages={self.averages!r}," \
+        return (
+            f"VectorStatTracker(dimension={self.dimension!r},"
+            f"log_sum_weight={self.log_sum_weight!r},"
+            f"averages={self.averages!r},"

             f"covariance_matrix={self.covariance_matrix!r})"
             f"covariance_matrix={self.covariance_matrix!r})"

+        )

 
     def copy(self):
         """Return new instance with the same state as self.
 
     def copy(self):
         """Return new instance with the same state as self.


@@ -287,8 +305,10 @@ class VectorStatTracker:
         :rtype: VectorStatTracker
         """
         return VectorStatTracker(
         :rtype: VectorStatTracker
         """
         return VectorStatTracker(

-            self.dimension, self.log_sum_weight, self.averages[:],
-            copy.deepcopy(self.covariance_matrix)
+            self.dimension,
+            self.log_sum_weight,
+            self.averages[:],
+            copy.deepcopy(self.covariance_matrix),

         )
 
     def reset(self):
         )
 
     def reset(self):