torchsig.signals.builders.ofdm.OFDMSignalGenerator¶

class torchsig.signals.builders.ofdm.OFDMSignalGenerator(**kwargs: dict[str, str | float | int])[source]¶

Bases: BaseSignalGenerator

OFDM Signal Generator.

Implements OFDM waveforms with configurable parameters.

Methods

`add_parent`	Add parent Seedable object and set up RNGs accordingly.
`copy`	Creates a deep copy of the SignalGenerator with copied transforms.
`generate`	Generates an OFDM signal based on the configured parameters.
`get_distribution`	Create distribution function with proper seeding.
`get_full_metadata`	Function for modifying and returning a new metadata with all the fields in parent or child, with child overriding parent in conflicts.
`get_second_seed`	Gets second seed, usually used to seed both torch and numpy generators with slightly different seeds.
`key_lookup`	Lookup a metadata key with enhanced error reporting.
`keys`	Get all metadata keys.
`seed`	Seed number generators with given seed.
`set_default_class_name`	Sets the class_name to name if there wasn't already a class name set.
`setup_rngs`	Initialize torch and numpy number generators, and update its children.
`update_from_parent`	Update numpy and torch number generators with parent seed.
`validate_metadata_fields`	Validates that all required metadata fields are present.

__init__(**kwargs: dict[str, str | float | int]) → None[source]¶

Initializes OFDM Signal Generator.

Parameters:: **kwargs – Metadata parameters including: - sample_rate: Sampling rate (Hz) - bandwidth_min: Minimum bandwidth (Hz) - bandwidth_max: Maximum bandwidth (Hz) - num_subcarriers: Number of subcarriers - signal_duration_in_samples_min: Minimum signal duration (samples) - signal_duration_in_samples_max: Maximum signal duration (samples)
Raises:: ValueError – If required metadata fields are missing or invalid.

generate() → Signal[source]¶

Generates an OFDM signal based on the configured parameters.

Returns:: Generated OFDM signal with metadata.
Return type:: Signal
Raises:: ValueError – If required metadata fields are missing or invalid.

__call__() → Signal¶

Generates a new signal and applies all transforms.

Returns:: The generated signal after applying all transforms.

__repr__() → str¶

Returns a string representation of the SignalGenerator.

Returns:: A string representation showing the class name, metadata, and transforms.

add_parent(parent: Seedable, register: bool = True) → None¶

Add parent Seedable object and set up RNGs accordingly.

Parameters:

parent – Parent Seedable object to add.
register – If True (default), add self to parent.children so that future seed propagation reaches this object. Pass False for transient objects (e.g. per-sample Signal instances) that only need the parent link for metadata/RNG access during their lifetime but must not accumulate in the parent’s child list, which would otherwise cause unbounded memory growth.

copy() → BaseSignalGenerator¶

Creates a deep copy of the SignalGenerator with copied transforms.

Returns:: A new instance of the SignalGenerator with copied metadata and transforms.

get_distribution(params: list | tuple | float, scaling: str = 'linear') → Distribution¶

Create distribution function with proper seeding.

Parameters:

params – Parameters for distribution.
scaling – Scaling param for distribution. Defaults to ‘linear’.

Returns:

Distribution function, seeded.

Return type:

Distribution

get_full_metadata() → dict[str, Any]¶

Function for modifying and returning a new metadata with all the fields in parent or child, with child overriding parent in conflicts.

Returns:: Dictionary containing all metadata from parent and child, with child values overriding parent values in case of conflicts.

Example

>>> parent = HierarchicalMetadataObject(metadata={"field_1": 4, "field_2": 5})
>>> child = HierarchicalMetadataObject(parent=parent, metadata={"field_2": 6})
>>> child.get_full_metadata()
{'field_1': 4, 'field_2': 6}

get_second_seed(seed: int) → int¶

Gets second seed, usually used to seed both torch and numpy generators with slightly different seeds.

Parameters:: seed – Seed to use.
Returns:: New seed.

key_lookup(key: str) → Any¶

Lookup a metadata key with enhanced error reporting.

Parameters:: key – The metadata key to lookup.
Returns:: The value associated with the key.
Raises:: MetadataAttributeError – If the key is not found in the metadata or parent metadata.

Example

>>> obj = HierarchicalMetadataObject(metadata={"key": "value"})
>>> obj.key_lookup("key")
'value'

keys() → list[str]¶

Get all metadata keys.

Returns:: List of all metadata keys.

Example

>>> obj = HierarchicalMetadataObject(metadata={"key1": 1, "key2": 2})
>>> list(obj.keys())
['key1', 'key2']

seed(seed: int) → None¶

Seed number generators with given seed.

Parameters:: seed – Seed to use.

set_default_class_name(name: str) → None¶

Sets the class_name to name if there wasn’t already a class name set.

Parameters:: name – The class name to set if no class name exists.

setup_rngs() → None¶: Initialize torch and numpy number generators, and update its children.

update_from_parent() → None¶: Update numpy and torch number generators with parent seed.

validate_metadata_fields() → None¶

Validates that all required metadata fields are present.

Throws an exception if required_metadata_fields are not filled. Does nothing if required_metadata_fields is not set.

Raises:

TypeError – If any required metadata field names are not strings.
ValueError – If any required metadata fields are missing.