Merge branch 'master' into Senegal-updates

nasaharvest · Mar 19, 2024 · 155be36 · 155be36
2 parents cf5667a + 4c04f2a
commit 155be36
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Showing 4 changed files with 16 additions and 14 deletions.
diff --git a/evaluate.py b/evaluate.py
@@ -1,6 +1,7 @@
 """
 Script to evaluate an individual model
 """
+
 from openmapflow.config import PROJECT_ROOT, DataPaths
 
 from src.pipeline_funcs import run_evaluation  # noqa: E402

diff --git a/src/consensus_utils.py b/src/consensus_utils.py
@@ -174,10 +174,10 @@ def create_consensus_features(consensus_dataframe: pd.DataFrame) -> pd.DataFrame
     """Creates and adds features to consensus dataframe."""
 
     # Convert analysis duration to float
-    consensus_dataframe[
-        ["set_1_analysis_duration", "set_2_analysis_duration"]
-    ] = consensus_dataframe[["set_1_analysis_duration", "set_2_analysis_duration"]].applymap(
-        tofloat
+    consensus_dataframe[["set_1_analysis_duration", "set_2_analysis_duration"]] = (
+        consensus_dataframe[["set_1_analysis_duration", "set_2_analysis_duration"]].applymap(
+            tofloat
+        )
     )
 
     # (1)
@@ -302,10 +302,10 @@ def renaming_func(s):
         consensus_dataframe = df1.merge(
             df2, left_on=["plotid", "sampleid"], right_on=["plotid", "sampleid"]
         )
-        consensus_dataframe[
-            ["set_1_analysis_duration", "set_2_analysis_duration"]
-        ] = consensus_dataframe[["set_1_analysis_duration", "set_2_analysis_duration"]].applymap(
-            tofloat
+        consensus_dataframe[["set_1_analysis_duration", "set_2_analysis_duration"]] = (
+            consensus_dataframe[["set_1_analysis_duration", "set_2_analysis_duration"]].applymap(
+                tofloat
+            )
         )
 
         rcolumns = [

diff --git a/src/models/classifier.py b/src/models/classifier.py
@@ -61,9 +61,9 @@ def __init__(
             global_classification_layers.append(
                 nn.Linear(
                     in_features=hparams.classifier_vector_size,
-                    out_features=1
-                    if i == (num_global_layers - 1)
-                    else hparams.classifier_vector_size,
+                    out_features=(
+                        1 if i == (num_global_layers - 1) else hparams.classifier_vector_size
+                    ),
                     bias=True if i == 0 else False,
                 )
             )
@@ -82,9 +82,9 @@ def __init__(
                 local_classification_layers.append(
                     nn.Linear(
                         in_features=hparams.classifier_vector_size,
-                        out_features=1
-                        if i == (num_local_layers - 1)
-                        else hparams.classifier_vector_size,
+                        out_features=(
+                            1 if i == (num_local_layers - 1) else hparams.classifier_vector_size
+                        ),
                         bias=True if i == 0 else False,
                     )
                 )

diff --git a/train.py b/train.py
@@ -1,6 +1,7 @@
 """
 Script that uses argument parameters to train an individual model
 """
+
 from argparse import ArgumentParser
 
 from datasets import datasets