Add additional percentile metrics (#8)

* Add additional percentile metrics

* Version updated from v0.2.1 to v0.3.0

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "v0.2.1"
+current_version = "v0.3.0"
 commit = true
 commit_args = "--no-verify"
 tag = true

README.md

@@ -1,5 +1,5 @@
 # invrs-utils - Miscellaneous utilities
-`v0.2.1`
+`v0.3.0`
 
 This package is a collection of utilities that may be useful, but do not have fundamental roles in the invrs-io ecosystem. These currently include,
 

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 
 name = "invrs_utils"
-version = "v0.2.1"
+version = "v0.3.0"
 description = "Miscellaneous utilities for the invrs-io ecosystem"
 keywords = ["topology", "optimization", "jax", "inverse design"]
 readme = "README.md"

src/invrs_utils/__init__.py

@@ -3,5 +3,5 @@
 Copyright (c) 2023 The INVRS-IO authors.
 """
 
-__version__ = "v0.2.1"
+__version__ = "v0.3.0"
 __author__ = "Martin F. Schubert <[email protected]>"

src/invrs_utils/experiment/data.py

@@ -23,14 +23,20 @@
 LOSS = "loss"
 LOSS_MIN = "loss_min"
 LOSS_MEAN = "loss_mean"
-LOSS_PERCENTILE_10 = "loss_percentile_10"
+LOSS_P05 = "loss_p05"
+LOSS_P10 = "loss_p10"
+LOSS_P25 = "loss_p25"
+LOSS_P50 = "loss_p50"
 
 DISTANCE = "distance"
 DISTANCE_MIN = "distance_min"
 DISTANCE_MEAN = "distance_mean"
 DISTANCE_ZERO_STEP = "distance_zero_step"
 DISTANCE_ZERO_COUNT = "distance_zero_count"
-DISTANCE_PERCENTILE_10 = "distance_percentile_10"
+DISTANCE_P05 = "distance_p05"
+DISTANCE_P10 = "distance_p10"
+DISTANCE_P25 = "distance_p25"
+DISTANCE_P50 = "distance_p50"
 
 SUMMARY_INTERVAL = "summary_interval"
 
@@ -109,10 +115,16 @@ def summarize_work_unit(
         SUMMARY_INTERVAL,
         LOSS_MIN,
         LOSS_MEAN,
-        LOSS_PERCENTILE_10,
+        LOSS_P05,
+        LOSS_P10,
+        LOSS_P25,
+        LOSS_P50,
         DISTANCE_MIN,
         DISTANCE_MEAN,
-        DISTANCE_PERCENTILE_10,
+        DISTANCE_P05,
+        DISTANCE_P10,
+        DISTANCE_P25,
+        DISTANCE_P50,
         DISTANCE_ZERO_COUNT,
         DISTANCE_ZERO_STEP,
     ):
@@ -126,10 +138,16 @@ def summarize_work_unit(
 
         data[LOSS_MIN].append(onp.amin(interval_loss))
         data[LOSS_MEAN].append(onp.mean(interval_loss))
-        data[LOSS_PERCENTILE_10].append(onp.percentile(interval_loss, 10))
+        data[LOSS_P05].append(onp.percentile(interval_loss, 5))
+        data[LOSS_P10].append(onp.percentile(interval_loss, 10))
+        data[LOSS_P25].append(onp.percentile(interval_loss, 25))
+        data[LOSS_P50].append(onp.percentile(interval_loss, 50))
         data[DISTANCE_MIN].append(onp.amin(interval_distance))
         data[DISTANCE_MEAN].append(onp.mean(interval_distance))
-        data[DISTANCE_PERCENTILE_10].append(onp.percentile(interval_distance, 10))
+        data[DISTANCE_P05].append(onp.percentile(interval_distance, 5))
+        data[DISTANCE_P10].append(onp.percentile(interval_distance, 10))
+        data[DISTANCE_P25].append(onp.percentile(interval_distance, 25))
+        data[DISTANCE_P50].append(onp.percentile(interval_distance, 50))
         data[DISTANCE_ZERO_COUNT].append(onp.sum(interval_distance <= 0))
 
         (zero_distance_steps,) = onp.where(interval_distance <= 0)

tests/experiment/test_data.py

@@ -91,10 +91,16 @@ def test_summarize_experiment(self):
             data.SUMMARY_INTERVAL,
             data.LOSS_MIN,
             data.LOSS_MEAN,
-            data.LOSS_PERCENTILE_10,
+            data.LOSS_P05,
+            data.LOSS_P10,
+            data.LOSS_P25,
+            data.LOSS_P50,
             data.DISTANCE_MIN,
             data.DISTANCE_MEAN,
-            data.DISTANCE_PERCENTILE_10,
+            data.DISTANCE_P05,
+            data.DISTANCE_P10,
+            data.DISTANCE_P25,
+            data.DISTANCE_P50,
             data.DISTANCE_ZERO_STEP,
             data.DISTANCE_ZERO_COUNT,
         ]
@@ -109,7 +115,7 @@ def test_summarize_experiment(self):
             onp.mean(_loss(onp.arange(0, 10))),
         )
         onp.testing.assert_allclose(
-            df[df["summary_interval"] == "000-010"][data.LOSS_PERCENTILE_10],
+            df[df["summary_interval"] == "000-010"][data.LOSS_P10],
             onp.percentile(_loss(onp.arange(0, 10)), 10),
         )
 
@@ -122,7 +128,7 @@ def test_summarize_experiment(self):
             onp.mean(_distance(onp.arange(0, 10))),
         )
         onp.testing.assert_allclose(
-            df[df["summary_interval"] == "000-010"][data.DISTANCE_PERCENTILE_10],
+            df[df["summary_interval"] == "000-010"][data.DISTANCE_P10],
             onp.percentile(_distance(onp.arange(0, 10)), 10),
         )