Update codegreen version and add

export_summary_to_csv function

README.md

@@ -11,6 +11,11 @@ Codegreen requires the following hardware:
 
 The Intel processor is needed for accessing the RAPL power sensors. An NVIDIA GPU is required for profiling GPU usage via `nvidia-smi`.
 
+Make sure to add your respective local paths to the following files after installation:
+
+- `codegreen/fecom/patching/patching_config.py`
+- `codegreen/fecom/measurement/measurement_config.py`
+
 ## Installation
 
 ```

codegreen/__init__.py

@@ -1,3 +1,3 @@
 """Codegreen package!"""
 
-__version__ = "0.1.30"
+__version__ = "0.1.31"

codegreen/fecom/experiment/analysis.py

@@ -254,6 +254,23 @@ def export_summary_to_latex(output_dir: Path, summary_dfs: Dict[str, pd.DataFram
     for name, df in summary_dfs.items():
         df.style.format(precision=2).to_latex(buf = output_dir/f"{name}.tex")
 
+def export_summary_to_csv(output_dir: Path, summary_dfs: Dict[str, pd.DataFrame]):
+    """
+    Write a given set of summary dfs returned by create_summary() to csv files.
+    """
+
+    for name, df in summary_dfs.items():
+        csv_path = output_dir / f"{name}.csv"
+
+        with open(csv_path, 'w') as csv_file:
+            writer = csv.writer(csv_file)
+
+            # Write column headers 
+            writer.writerow(df.columns)
+
+            # Write each row to the csv
+            for index, row in df.iterrows():
+                writer.writerow(row)
 
 def create_summary(project_energy_data: ProjectEnergyData) -> Dict[str, pd.DataFrame]:
     cpu_summary_mean = build_summary_df_mean(project_energy_data.cpu_data)

pyproject.toml

@@ -6,7 +6,7 @@ build-backend = "flit_core.buildapi"
 name = "codegreen"
 authors = [{name = "Saurabhsingh Rajput", email = "[email protected]"}]
 license = {file = "LICENSE"}
-classifiers = ["License :: OSI Approved :: Apache 2.0"]
+classifiers = ["License :: OSI Approved :: Apache Software License"]
 dynamic = ["version", "description"]
 dependencies = [
 "typer>=0.9",