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

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Andreas Tsouchlos 2022-11-15 16:09:57 +01:00
parent 524b57f41c
commit d9009970ad
2 changed files with 60 additions and 10 deletions
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46
sw/plot_results.py Normal file
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@ -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()

24
sw/utility/visualization.py
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@ -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
in a new graph. Each dataframe is assumed to contain a column named "SNR" which is used as the x-axis
:param title: Title of the figure
: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")