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base repository: TorchDSP/torchsig
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head repository: Gradiant/COM-SIGINT-Spectrum-Awareness-torchsig
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TorchDSP:main and Gradiant:main are entirely different commit histories.

Showing with 12 additions and 12 deletions.
  1. +9 −9 generate_signals.py
  2. +3 −3 test_generate_signals.py
18 changes: 9 additions & 9 deletions generate_signals.py
Original file line number Diff line number Diff line change
@@ -53,10 +53,10 @@ def _create_dataset(self):

def generate(self):
for idx in range(self.num_samples):
data, label = self.dataset[idx]
data = data.astype(np.complex64)
sample, label = self.dataset[idx]
sample = sample.astype(np.complex64)
signal_info = {
"data": data,
"sample": sample,
"label_index": label,
"label_class": self.idx_to_class[label],
}
@@ -88,10 +88,10 @@ def save_iq_file(self):

def retrieve_signal(self, idx):
signal_info = self.signals[idx]
data, label = self.dataset[idx]
data = data.astype(np.complex64)
sample, label = self.dataset[idx]
sample = sample.astype(np.complex64)
return {
"data": data,
"sample": sample,
"class_index": label,
"class_name": self.idx_to_class[label],
"signal_info": signal_info
@@ -104,8 +104,8 @@ def __init__(self, dataset):
super().__init__(dataset)

def __getitem__(self, idx):
data = self.dataset[idx]
return data
sample = self.dataset[idx]
return sample

def __len__(self) -> int:
return len(self.dataset)
@@ -164,7 +164,7 @@ def main():
random_number = random.randrange(num_samples)

sample_signal = signal_generator.retrieve_signal(random_number)
print("Sample Signal Info:", {k: sample_signal[k] for k in sample_signal if k != 'data'})
print("Sample Signal Info:", {k: sample_signal[k] for k in sample_signal if k != 'sample'})

if args.save_plot:
signal_generator.save_plot()
6 changes: 3 additions & 3 deletions test_generate_signals.py
Original file line number Diff line number Diff line change
@@ -47,7 +47,7 @@ def test_generate_signals(signal_generator_instance):
assert len(signal_generator_instance.signals) == signal_generator_instance.num_samples

# Check if all generated signals are unique
signals_data = [signal["data"] for signal in signal_generator_instance.signals]
signals_data = [signal["sample"] for signal in signal_generator_instance.signals]
# Convert each signal data array to a tuple for hashing and compare lengths
unique_signals_data = set(map(lambda x: tuple(x), signals_data))
assert len(unique_signals_data) == len(signals_data), "Generated signals are not unique"
@@ -74,13 +74,13 @@ def test_saved_file_format(signal_generator_instance):
signals = pickle.load(f)
assert isinstance(signals, list)
for signal in signals:
assert "data" in signal
assert "sample" in signal
assert "label_index" in signal
assert "label_class" in signal
assert "additional_info" in signal

# Check data types
assert signal["data"].dtype == np.complex64
assert signal["sample"].dtype == np.complex64
assert isinstance(signal["label_index"], int)
assert isinstance(signal["label_class"], str)
assert isinstance(signal["additional_info"], str)