55 lines
2.0 KiB
Python
55 lines
2.0 KiB
Python
import seaborn as sns
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import matplotlib.pyplot as plt
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import pandas as pd
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import typing
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from itertools import chain
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import math
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def _get_num_rows(num_graphs: int, num_cols: int) -> int:
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"""Get the minimum number of rows needed to show a certain number of graphs,
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given a certain number of columns.
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:param num_graphs: Number of graphs
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:param num_cols: Number of columns
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:return: Number of rows
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"""
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return math.ceil(num_graphs / num_cols)
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# TODO: Calculate fig size in relation to the number of rows and columns
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# TODO: Set proper line labels
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# TODO: Set proper axis titles
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# TODO: Should unnamed columns be dropped by this function or by the caller?
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# TODO: Handle number of graphs not nicely fitting into rows and columns
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def show_BER_curves(data: typing.List[pd.DataFrame], num_cols: int = 3) -> plt.figure:
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"""This function creates a matplotlib figure containing a number of BER curves.
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:param data: List of pandas DataFrames containing the data to be plotted. Each dataframe in the list is plotted
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in a new graph. Each dataframe is assumed to contain a column named "SNR" which is used as the x-axis
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:param num_cols: Number of columns in which the graphs should be arranged in the resulting figure
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:return: Matplotlib figure
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"""
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num_graphs = len(data)
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num_rows = _get_num_rows(num_graphs, num_cols)
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fig, axes = plt.subplots(num_rows, num_cols, squeeze=False)
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fig.suptitle("Bit-Error-Rates of various decoders for different codes")
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axes = list(chain.from_iterable(axes))[:num_graphs] # Flatten the 2d axes array
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for axis, df in zip(axes, data):
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column_names = [column for column in df.columns.values.tolist() if not column == "SNR"]
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for column in column_names:
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sns.lineplot(ax=axis, data=df, x="SNR", y=column, label=column)
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#axis.set_title(code)
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axis.set(yscale="log")
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axis.set_xlabel("SNR")
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axis.set_ylabel("BER")
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axis.set_yticks([10e-5, 10e-4, 10e-3, 10e-2, 10e-1, 10e0])
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axis.legend()
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return fig
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