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Simulator class now returns pandas dataframe instead of raw data

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This commit is contained in:
Andreas Tsouchlos 2022-11-22 17:05:58 +01:00
parent 8599ea9662
commit 3c27a0cc18
1 changed files with 9 additions and 18 deletions
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27
sw/utility/simulation.py
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@ -199,30 +199,27 @@ class Simulator:
"""Stop the simulation.""" """Stop the simulation."""
self._sim_running = False self._sim_running = False
@property def get_current_results(self) -> pd.DataFrame:
def SNRs_and_BERs(self) -> typing.Tuple[np.array, np.array]:
"""Get the current results. """Get the current results.
If the simulation has not yet completed, the BERs which have not yet been calculated are set to 0. If the simulation has not yet completed, the BERs which have not yet been calculated are set to 0.
:return: Tuple of numpy arrays of the form (SNRs, BERs), where BERs is a list of the form :return: pandas Dataframe with the columns ["SNR", "BER_1", "BER_2", ...]
[BER_decoder_1, BER_decoder_2, ...]
""" """
SNRs = np.array(self._SNRs) data = {"SNR": np.array(self._SNRs)}
# If the BERs of a decoder have not been calculated for all SNRs, # If the BERs of a decoder have not been calculated for all SNRs,
# fill the rest up with zeros to match the length of the 'SNRs' array # fill the rest up with zeros to match the length of the 'SNRs' array
BERs = [] for i, decoder_BER_list in enumerate(self._BERs):
for decoder_BER_list in self._BERs:
padded = np.pad(decoder_BER_list, (0, len(self._SNRs) - len(decoder_BER_list))) padded = np.pad(decoder_BER_list, (0, len(self._SNRs) - len(decoder_BER_list)))
BERs.append(padded) data[f"BER_{i}"] = padded
# If the BERs have not been calculated for all decoders, fill up the BERs list # If the BERs have not been calculated for all decoders, fill up the BERs list
# with zero-vectors to match the length of the 'decoders' list # with zero-vectors to match the length of the 'decoders' list
for i in range(len(self._decoders) - len(BERs)): for i in range(len(self._decoders), len(self._BERs)):
BERs.append(np.zeros(len(self._SNRs))) data[f"BER_{i}"] = np.zeros(len(self._SNRs))
return SNRs, BERs return pd.DataFrame(data)
# TODO: Fix typing.Any or Simulator # TODO: Fix typing.Any or Simulator
@ -310,13 +307,7 @@ class SimulationDeSerializer:
json.dump(metadata, f, ensure_ascii=False, indent=4) json.dump(metadata, f, ensure_ascii=False, indent=4)
# Save results # Save results
SNRs, BERs = simulator.SNRs_and_BERs df = simulator.get_current_results()
data_dict = {"SNR": SNRs}
for i, BER in enumerate(BERs):
data_dict[f"BER_{i}"] = BER
df = pd.DataFrame(data_dict)
df.to_csv(self._get_results_path(sim_name)) df.to_csv(self._get_results_path(sim_name))
def read_results(self, sim_name: str) -> typing.Tuple[pd.DataFrame, typing.Dict]: def read_results(self, sim_name: str) -> typing.Tuple[pd.DataFrame, typing.Dict]: