Implemented proper titles and line labels in visualization.show_BER_curves()

sw/plot_results.py

@@ -0,0 +1,46 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+import pandas as pd
+import os
+from utility import visualization
+
+
+# TODO: Fix spacing between axes and margins
+def plot_results():
+    graph_names = {"96.3.965": "n=96, k=48 - 965",
+                   "204.3.486": "n=204, k=102 - 486",
+                   "204.55.187": "n=204, k=102 - 187",
+                   "408.33.844": "n=408, k=204 - 844",
+                   "816.1A4.845": "n=816, k=272 - 843",
+                   "999.111.3.5543": "n=999, k=888 - 5543",
+                   "999.111.3.5565": "n=999, k=888 - 5565",
+                   "PEGReg252x504": "n=504, k=252 - PEGReg"}
+
+    line_labels = {"BER_ML": "ML",
+                   "BER_prox_0_15": "$\gamma = 0.15$",
+                   "BER_prox_0_05": "$\gamma = 0.05$",
+                   "BER_prox_0_01": "$\gamma = 0.01$"}
+
+    # Read data from files
+    results_dir = "sim_results"
+
+    data = {}
+    for file in os.listdir(results_dir):
+        if file.endswith(".csv"):
+            filename = os.path.splitext(file)[0]
+
+            df = pd.read_csv(os.path.join(results_dir, file))
+            df = df.loc[:, ~df.columns.str.contains('^Unnamed')]
+            data[graph_names[filename]] = df
+
+    # Create and show graphs
+
+    sns.set_theme()
+    fig = visualization.show_BER_curves("Bit-Error-Rates of proximal decoder for different codes",
+                                        data, num_cols=4, line_labels=line_labels)
+    plt.show()
+
+
+if __name__ == "__main__":
+    plot_results()

sw/utility/visualization.py

@@ -18,15 +18,18 @@ def _get_num_rows(num_graphs: int, num_cols: int) -> int:
 
 
 # TODO: Calculate fig size in relation to the number of rows and columns
-# TODO: Set proper line labels
-# TODO: Set proper axis titles
-# TODO: Should unnamed columns be dropped by this function or by the caller?
 # TODO: Handle number of graphs not nicely fitting into rows and columns
-def show_BER_curves(data: typing.List[pd.DataFrame], num_cols: int = 3) -> plt.figure:
+def show_BER_curves(title: str,
+                    data: typing.Dict[str, pd.DataFrame],
+                    line_labels: typing.Dict[str, str],
+                    num_cols: int = 3) -> plt.figure:
     """This function creates a matplotlib figure containing a number of BER curves.
 
-    :param data: List of pandas DataFrames containing the data to be plotted. Each dataframe in the list is plotted
+    :param title: Title of the figure
-        in a new graph. Each dataframe is assumed to contain a column named "SNR" which is used as the x-axis
+    :param data: Dictionary where each key corresponds to the name of a new graph and the value is a pandas Dataframe
+        containing the data to be plotted. Each dataframe is assumed to contain a column named "SNR" which is used
+        as the x-axis
+    :param line_labels: Dictionary mapping column names to proper labels
     :param num_cols: Number of columns in which the graphs should be arranged in the resulting figure
     :return: Matplotlib figure
     """
@@ -34,17 +37,18 @@ def show_BER_curves(data: typing.List[pd.DataFrame], num_cols: int = 3) -> plt.f
     num_rows = _get_num_rows(num_graphs, num_cols)
 
     fig, axes = plt.subplots(num_rows, num_cols, squeeze=False)
-    fig.suptitle("Bit-Error-Rates of various decoders for different codes")
+    fig.suptitle(title)
 
     axes = list(chain.from_iterable(axes))[:num_graphs]  # Flatten the 2d axes array
 
-    for axis, df in zip(axes, data):
+    for axis, name_data_pair in zip(axes, sorted(data.items())):
+        graph_name, df = name_data_pair
         column_names = [column for column in df.columns.values.tolist() if not column == "SNR"]
 
         for column in column_names:
-            sns.lineplot(ax=axis, data=df, x="SNR", y=column, label=column)
+            sns.lineplot(ax=axis, data=df, x="SNR", y=column, label=line_labels[column])
 
-        #axis.set_title(code)
+        axis.set_title(graph_name)
         axis.set(yscale="log")
         axis.set_xlabel("SNR")
         axis.set_ylabel("BER")