Modified the SimulationManager to work with the newly implemented Simulator; Added doc comments

This commit is contained in:
Andreas Tsouchlos 2022-11-15 17:26:14 +01:00
parent c24a36db07
commit e9cd215457

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@ -25,105 +25,16 @@ def count_bit_errors(d: np.array, d_hat: np.array) -> int:
return np.sum(d != d_hat)
# def test_decoder(n: int,
# k: int,
# decoder: typing.Any,
# SNRs: typing.Sequence[float] = np.linspace(1, 7, 7),
# target_frame_errors: int = 100) \
# -> typing.Tuple[np.array, np.array]:
# """Calculate the Bit Error Rate (BER) for a given decoder for a number of SNRs.
#
# This function assumes the all-zeros assumption holds. Progress is printed to stdout.
#
# :param n: Length of a codeword of the used code
# :param k: Length of a dataword of the used code
# :param decoder: Instance of the decoder to be tested
# :param SNRs: List of SNRs for which the BER should be calculated
# :param target_frame_errors: Number of frame errors after which to stop the simulation
# :param N_max: Maximum number of iterations to perform for each SNR
# :return: Tuple of numpy arrays of the form (SNRs, BERs)
# """
#
# x = np.zeros(n)
# x_bpsk = 1 - 2 * x # Map x from [0, 1]^n to [-1, 1]^n
#
# BERs = []
# for SNR in tqdm(SNRs,
# desc=f"Calculating BERs for {decoder.__class__.__name__}",
# position=1,
# leave=False,
# bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt}"):
#
# total_bit_errors = 0
# total_bits = 0
# total_frame_errors = 0
#
# pbar = tqdm(total=target_frame_errors,
# desc=f"Simulating for SNR = {SNR} dB",
# position=2,
# leave=False,
# bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}]")
#
# while total_frame_errors < target_frame_errors:
# # Simulate channel
# y = noise.add_awgn(x_bpsk, SNR, n, k)
#
# # Decode received frame
# x_hat = decoder.decode(y)
#
# # Calculate statistics
# bit_errors = count_bit_errors(x, x_hat)
# total_bits += x.size
#
# if bit_errors > 0:
# total_frame_errors += 1
# total_bit_errors += bit_errors
# pbar.update(1)
#
# pbar.close()
#
# BERs.append(total_bit_errors / total_bits)
#
# return np.array(SNRs), np.array(BERs)
#
#
# def test_decoders(n: int,
# k: int,
# decoders: typing.List,
# SNRs: typing.Sequence[float] = np.linspace(1, 7, 7),
# target_frame_errors: int = 100) \
# -> typing.Tuple[np.array, np.array]:
# """Calculate the Bit Error Rate (BER) for a number of given decoders for a number of SNRs.
#
# This function assumes the all-zeros assumption holds. Progress is printed to stdout.
#
# :param n: Length of a codeword of the used code
# :param k: Length of a dataword of the used code
# :param decoders: List of decoder objects to be tested
# :param SNRs: List of SNRs for which the BER should be calculated
# :param target_frame_errors: Number of frame errors after which to stop the simulation
# :return: Tuple of the form (SNRs, [BERs_1, BERs_2, ...]) where SNR and BERs_x are numpy arrays
# """
# result_BERs = []
#
# start_time = default_timer()
#
# for decoder in tqdm(decoders,
# desc="Calculating the answer to life, the universe and everything",
# position=0,
# leave=False,
# bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt}"):
# _, BERs = test_decoder(n, k, decoder, SNRs, target_frame_errors)
# result_BERs.append(BERs)
#
# end_time = default_timer()
# print(f"Elapsed time: {end_time - start_time:.2f}s")
#
# return SNRs, result_BERs
#
# TODO: Write unit tests
class Simulator:
"""Class allowing for saving of simulations state.
Given a list of decoders, this class allows for simulating the Bit-Error-Rates of each decoder for various SNRs.
The functionality implemented by this class could be achieved by a bunch of loops and a function.
However, storing the state of the simulation as member variables allows for pausing and resuming the simulation
at a later state.
"""
def __init__(self, n: int, k: int,
decoders: typing.Sequence[typing.Any],
SNRs: typing.Sequence[float],
@ -159,6 +70,7 @@ class Simulator:
# Results & Miscellaneous
self._sim_running = False
self._sim_done = False
self._BERs = [[]]
def _simulate_transmission(self) -> int:
@ -209,13 +121,15 @@ class Simulator:
self._BERs.append([])
else:
self._sim_running = False
self._sim_done = True
def start(self) -> None:
"""Start the simulation.
This is a blocking call. A call to the stop() function
from another thread will stop this function
from another thread will stop this function.
"""
if not self._sim_done:
self._sim_running = True
while self._sim_running:
@ -227,57 +141,50 @@ class Simulator:
"""Stop the simulation."""
self._sim_running = False
@property
def simulation_done(self) -> bool:
"""Check whether the simulation is still ongoing or completed.
:return: True if the simulation is completed
"""
return self._sim_done
# TODO: Make sure the length of each BER_array is the same as the number of SNRs
@property
def SNRs_and_BERs(self) -> typing.Tuple[np.array, np.array]:
"""Get the current results.
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)
:return: Tuple of numpy arrays of the form (SNRs, BERs), where BERs is a list of the form
[BER_decoder_1, BER_decoder_2, ...]
"""
SNRs = np.array(self._SNRs)
# TODO: Make sure the length of each BER_array is the same as the number of SNRs
BERs = [np.array(BER_array) for BER_array in self._BERs]
return SNRs, BERs
@dataclass
class SimulationParameters:
n: int
k: int
decoders: typing.Sequence[typing.Any]
SNRs: typing.Sequence[float]
target_frame_errors: int
@dataclass
class SimulationState:
"""Data structure storing the state of the simulation."""
num_frame_errors: int = 0
num_bit_errors: int = 0
num_total_bits: int = 0
# simulation_time: float = 0
current_decoder_index = 0
current_SNRs_index: int = 0
# TODO: Make more generic
# TODO: Remove save data after successful execution
# TODO: Write currently calculated BERs to file when simulation is stopped
class SimulationManager:
"""This class only contains functions relating to stopping and restarting of simulations
(and storing of the simulation state in a file, to be resumed at a later date).
All actual work is outsourced to a provided simulator class.
"""
def __init__(self, save_dir: str, results_dir: str):
"""Construct a SimulationManager object.
:param save_dir: Directory in which the simulation state of a paused simulation should be stored
:param results_dir: Directory in which the results of the simulation should be stored
"""
self._save_dir = save_dir
self._sim_parameters_filepath = f"{self._save_dir}/sim_parameters.pickle"
self._sim_state_filepath = f"{self._save_dir}/sim_state.pickle"
self._logs_filepath = f"{self._save_dir}/logs.txt"
self._results_dir = results_dir
# TODO: Should the be none or SimulationParameters() and SimulationState() respectively?
self._sim_params = None
self._sim_state = None
self._sim_running = False
self._simulator = None
Path(self._save_dir).mkdir(parents=True, exist_ok=True)
@ -292,142 +199,64 @@ class SimulationManager:
#
def unfinished_simulation_present(self) -> bool:
return os.path.isfile(self._sim_parameters_filepath) \
and os.path.isfile(self._sim_state_filepath)
"""Check whether the savefile of a previously unfinished simulation is present."""
return os.path.isfile(self._sim_state_filepath)
def continue_unfinished(self):
def load_unfinished(self):
"""Load the state of an unfinished simulation its savefile."""
assert self.unfinished_simulation_present()
with open(self._sim_parameters_filepath, "rb") as file:
self._sim_params = pickle.load(file)
self._logger.info("Loading saved simulation state")
with open(self._sim_state_filepath, "rb") as file:
self._sim_state = pickle.load(file)
self._logger.info("Loaded saved simulation state")
self.start()
self._simulator = pickle.load(file)
# TODO: Make sure old state is overwritten
def _save_state(self):
with open(self._sim_parameters_filepath, "wb") as file:
pickle.dump(self._sim_params, file)
def _save_state(self) -> None:
"""Write the state of the currently configured simulation to a savefile."""
if self._simulator is not None:
with open(self._sim_state_filepath, "wb") as file:
pickle.dump(self._sim_state, file)
pickle.dump(self._simulator, file)
self._logger.info("Saved simulation state")
else:
self._logger.info("No simulation state to save: simulator object is 'None'")
def _exit_gracefully(self, *args):
def _exit_gracefully(self, *args) -> None:
"""Handler called when the program is interrupted.
Pauses and saves the currently running simulation
"""
self._logger.debug("Intercepted signal SIGINT/SIGTERM")
self._sim_running = False
if (self._sim_params is not None) and (self._sim_state is not None):
if self._simulator is not None:
self._simulator.stop()
self._save_state()
#
# Functions responsible for the actual simulation
#
# def test_decoders(self,
# n: int,
# k: int,
# decoders: typing.Sequence[typing.Any],
# SNRs: typing.Sequence[float] = np.linspace(1, 7, 7),
# target_frame_errors: int = 100):
# """Calculate the Bit Error Rate (BER) for a number of given decoders for a number of SNRs.
#
# This function assumes the all-zeros assumption holds. Progress is printed to stdout.
#
# :param n: Length of a codeword of the used code
# :param k: Length of a dataword of the used code
# :param decoders: List of decoder objects to be tested
# :param SNRs: List of SNRs for which the BER should be calculated
# :param target_frame_errors: Number of frame errors after which to stop the simulation
# :return: Tuple of the form (SNRs, [BERs_1, BERs_2, ...]) where SNR and BERs_x are numpy arrays
# """
# # TODO
#
# # Save simulation
# self._sim_parameters = SimulationMetaData(n, k, decoders, SNRs, target_frame_errors)
# self._sim_state = SimulationState()
#
# self._logger.info("Initialized new simulation state")
#
# # Simulation
#
# result_BERs = []
#
# start_time = default_timer()
#
# for decoder in tqdm(decoders,
# desc="Calculating the answer to life, the universe and everything",
# position=0,
# leave=False,
# bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt}"):
# _, BERs = self.test_decoder(n, k, decoder, SNRs, target_frame_errors)
# result_BERs.append(BERs)
#
# end_time = default_timer()
# print(f"Elapsed time: {end_time - start_time:.2f}s")
#
# return SNRs, result_BERs
def set_simulator(self, simulator: typing.Any) -> None:
"""Select a simulator to do the actual work."""
self._simulator = simulator
# def test_decoder(self,
# n: int,
# k: int,
# decoder: typing.Any,
# SNRs: typing.Sequence[float] = np.linspace(1, 7, 7),
# target_frame_errors: int = 100) \
# -> typing.Tuple[np.array, np.array]:
def start(self):
self._sim_running = True # TODO: Move this somewhere else
"""Start the simulation.
decoder = self._sim_params.decoders[self._sim_state.current_decoder_index]
This is a blocking call. A call to the stop() function
from another thread will stop this function.
"""
assert self._simulator is not None
x = np.zeros(self._sim_params.n)
x_bpsk = 1 - 2 * x # Map x from [0, 1]^n to [-1, 1]^n
self._logger.info("Starting simulation")
self._simulator.start()
BERs = []
for SNR in tqdm(self._sim_params.SNRs[self._sim_state.current_SNRs_index:],
desc=f"Calculating BERs for {decoder.__class__.__name__}",
position=1,
leave=False,
bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt}"):
@property
def simulation_done(self):
"""Check whether the configured simulation has been completed."""
return self._simulator.simulation_done
pbar = tqdm(total=self._sim_params.target_frame_errors,
desc=f"Simulating for SNR = {SNR} dB",
position=2,
leave=False,
bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}]")
pbar.update(self._sim_state.num_frame_errors)
while self._sim_state.num_frame_errors < self._sim_params.target_frame_errors:
if not self._sim_running:
return
# Simulate channel
y = noise.add_awgn(x_bpsk, SNR, self._sim_params.n, self._sim_params.k)
# Decode received frame
x_hat = decoder.decode(y)
# Calculate statistics
bit_errors = count_bit_errors(x, x_hat)
self._sim_state.num_total_bits += x.size
if bit_errors > 0:
self._sim_state.num_frame_errors += 1
self._sim_state.num_bit_errors += bit_errors
pbar.update(1)
# TODO: Load BERs from file as well
BERs.append(self._sim_state.num_bit_errors / self._sim_state.num_total_bits)
pbar.close()
self._sim_state.current_SNRs_index += 1
self._sim_state.num_frame_errors = 0
self._sim_state.num_bit_errors = 0
self._sim_state.num_total_bits = 0
# return np.array(self._sim_params.SNRs), np.array(BERs)
def get_current_results(self) -> typing.Any:
"""Get the current results of the configured simulation."""
return self._simulator.SNRs_and_BERs