Source code for hermespy.simulation.antennas

# -*- coding: utf-8 -*-

from __future__ import annotations
from typing import Dict, List, overload, Sequence, Type, Literal

import matplotlib.colors as colors
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
from mpl_toolkits.mplot3d import Axes3D  # type: ignore
from scipy.constants import pi

from hermespy.beamforming import TransmitBeamformer, ReceiveBeamformer
from hermespy.core import (
    Antenna,
    AntennaArray,
    AntennaArrayState,
    AntennaMode,
    AntennaPort,
    CustomAntennaArray,
    Dipole,
    Executable,
    IdealAntenna,
    LinearAntenna,
    PatchAntenna,
    ReceiveState,
    Signal,
    Transformation,
    TransmitState,
    UniformArray,
)
from .coupling import Coupling
from .isolation import Isolation
from .rf_chain import RfChain

__author__ = "Jan Adler"
__copyright__ = "Copyright 2024, Barkhausen Institut gGmbH"
__credits__ = ["Jan Adler"]
__license__ = "AGPLv3"
__version__ = "1.4.0"
__maintainer__ = "Jan Adler"
__email__ = "jan.adler@barkhauseninstitut.org"
__status__ = "Prototype"


[docs] class SimulatedAntennaPort(AntennaPort["SimulatedAntenna", "SimulatedAntennaArray"]): """Port within a simulated antenna array.""" yaml_tag = "SimulatedAntennaPort" __rf_chain: RfChain | None # radio frequency chain connected to this antenna port def __init__( self, antennas: Sequence[SimulatedAntenna] = None, pose: Transformation | None = None, rf_chain: RfChain | None = None, ) -> None: """ Args: antennas (Sequence[SimulatedAntenna], optional): Sequence of antennas connected to this antenna port. If not specified, an empty sequence is assumed. pose (Transformation, optional): The antenna's position and orientation with respect to its array. rf_chain (RfChain, optional): The antenna's RF chain. If not specified, the connected device's default RF chain is assumed. """ # Initialize base class AntennaPort.__init__(self, antennas, pose) # Initialize attributes self.__rf_chain = None self.rf_chain = rf_chain @property def rf_chain(self) -> RfChain | None: """The antenna's RF chain.""" return self.__rf_chain @rf_chain.setter def rf_chain(self, value: RfChain | None) -> None: # Abort if the RF chain configuration didn't change if value == self.__rf_chain: return # Update the RF chain configuration self.__rf_chain = value # Notify the antenna array about the change in its RF chain configuration if self.array is not None: self.array.rf_chain_modified()
[docs] class SimulatedAntenna(Antenna[SimulatedAntennaPort]): """Model of single antenna within an antenna array.""" __weight: complex # Phase and amplitude shift of signals transmitted / received by this antenna def __init__( self, mode: AntennaMode = AntennaMode.DUPLEX, pose: Transformation | None = None, weight: complex = 1.0 + 0.0j, ) -> None: """ Args: mode (AntennaMode, optional): Antenna's mode of operation. By default, a full duplex antenna is assumed. pose (Transformation, optional): The antenna's position and orientation with respect to its array. weight (complex, optional): Phase and amplitude shift of signals transmitted and received by this antenna. By default, no phase and amplitude shift is applied. """ # Initialize base class Antenna.__init__(self, mode, pose) # Initialize attributes self.weight = weight @property def weight(self) -> complex: """Phase and amplitude shift of signals transmitted and received by this antenna.""" return self.__weight @weight.setter def weight(self, value: complex) -> None: self.__weight = value
[docs] def transmit(self, signal: Signal) -> Signal: """Transmit a signal over this antenna. The transmission may be distorted by the antennas impulse response / frequency characteristics. Args: signal (Signal): The signal model to be transmitted. Returns: The actually transmitted (distorted) signal model. Raises: ValueError: If the signal has more than one stream. """ if signal.num_streams != 1: raise ValueError("Only single-streamed signal can be transmitted over a single antenna") if self.weight != 1.0: signal = signal.copy() for block in signal: block *= self.weight return signal
[docs] def receive(self, signal: Signal) -> Signal: """Receive a signal over this antenna. The reception may be distorted by the antennas impulse response / frequency characteristics. Args: signal (Signal): The signal model to be received. Returns: Signal: The actually received (distorted) signal model. """ if signal.num_streams != 1: raise ValueError("Only single-streamed signal can be received over a single antenna") if self.weight != 1.0: signal = signal.copy() for block in signal: block *= self.weight return signal
class SimulatedDipole(SimulatedAntenna, Dipole[SimulatedAntennaPort]): """Model of single dipole antenna within an antenna array.""" yaml_tag = "SimulatedDipole" def __init__( self, mode: AntennaMode = AntennaMode.DUPLEX, pose: Transformation | None = None, weight: complex = 1.0 + 0j, ) -> None: """ Args: mode (AntennaMode, optional): Antenna's mode of operation. By default, a full duplex antenna is assumed. pose (Transformation, optional): The antenna's position and orientation with respect to its array. weight (complex, optional): Phase and amplitude shift of signals transmitted and received by this antenna. By default, no phase and amplitude shift is applied. """ # Initialize base classes Dipole.__init__(self, mode, pose) SimulatedAntenna.__init__(self, mode, pose, weight)
[docs] class SimulatedIdealAntenna(SimulatedAntenna, IdealAntenna[SimulatedAntennaPort]): """Model of single ideal antenna within an antenna array.""" yaml_tag = "SimulatedIdealAntenna" def __init__( self, mode: AntennaMode = AntennaMode.DUPLEX, pose: Transformation | None = None, weight: complex = 1.0 + 0j, ) -> None: """ Args: mode (AntennaMode, optional): Antenna's mode of operation. By default, a full duplex antenna is assumed. pose (Transformation, optional): The antenna's position and orientation with respect to its array. weight (complex, optional): Phase and amplitude shift of signals transmitted and received by this antenna. By default, no phase and amplitude shift is applied. """ # Initialize base classes IdealAntenna.__init__(self, mode, pose) SimulatedAntenna.__init__(self, mode, pose, weight)
[docs] class SimulatedLinearAntenna(SimulatedAntenna, LinearAntenna[SimulatedAntennaPort]): """Model of single linear antenna within an antenna array.""" yaml_tag = "SimulatedLinearAntenna" def __init__( self, mode: AntennaMode = AntennaMode.DUPLEX, slant: float = 0.0, pose: Transformation | None = None, weight: complex = 1.0 + 0j, ) -> None: """ Args: mode (AntennaMode, optional): Antenna's mode of operation. By default, a full duplex antenna is assumed. slant (float, optional): The antenna's slant angle in radians. pose (Transformation, optional): The antenna's position and orientation with respect to its array. weight (complex, optional): Phase and amplitude shift of signals transmitted and received by this antenna. By default, no phase and amplitude shift is applied. """ # Initialize base classes LinearAntenna.__init__(self, mode, slant, pose) SimulatedAntenna.__init__(self, mode, pose, weight)
[docs] class SimulatedPatchAntenna(SimulatedAntenna, PatchAntenna[SimulatedAntennaPort]): """Model of single patch antenna within an antenna array.""" yaml_tag = "SimulatedPatchAntenna" def __init__( self, mode: AntennaMode = AntennaMode.DUPLEX, pose: Transformation | None = None, weight: complex = 1.0 + 0j, ) -> None: """ Args: mode (AntennaMode, optional): Antenna's mode of operation. By default, a full duplex antenna is assumed. pose (Transformation, optional): The antenna's position and orientation with respect to its array. weight (complex, optional): Phase and amplitude shift of signals transmitted and received by this antenna. By default, no phase and amplitude shift is applied. """ # Initialize base classes SimulatedAntenna.__init__(self, mode, pose, weight) PatchAntenna.__init__(self, mode, pose)
[docs] class SimulatedAntennaArray(AntennaArray[SimulatedAntennaPort, SimulatedAntenna]): """Array of simulated antennas.""" __cached_default_rf_chain: RfChain | None __cached_rf_transmit_map: Dict[RfChain | None, List[int]] | None __cached_rf_receive_map: Dict[RfChain | None, List[int]] | None def __init__(self, pose: Transformation | None = None) -> None: """ Args: pose (Transformation, optional): The antenna array's position and orientation with respect to its device. If not specified, the same orientation and position as the device is assumed. """ # Initialize base class AntennaArray.__init__(self, pose) # Initialize class attributes self.__cached_default_rf_chain = None self.__cached_rf_transmit_map = None self.__cached_rf_receive_map = None def _new_port(self) -> SimulatedAntennaPort: return SimulatedAntennaPort()
[docs] def rf_chain_modified(self) -> None: """Notify the antenna array that the RF chain configuration of one of its antennas has changed. Automatically called when the :attr:`rf_chain<SimulatedAntennaPort.rf_chain>` attribute of a :class:`SimulatedAntennaPort` a is modified. """ self.__cached_rf_transmit_map = None self.__cached_rf_receive_map = None
def _rf_transmit_chains(self, default_chain: RfChain) -> Dict[RfChain, List[int]]: """Compute a map of all unique RF chains used for transmission. Args: default_chain (RfChain): The default RF chain to be used if no RF chain is specified for a port. Returns: A dictionary mapping each unique RF chain to the indices of the ports using it. """ # If the RF chain map has already been computed and the array hasn't changed since then, # return the cached map immediately if ( self.__cached_rf_transmit_map is not None and self.__cached_default_rf_chain == default_chain ): return self.__cached_rf_transmit_map.copy() unique_rf_chains: Dict[RfChain, List[int]] = dict() port_idx = 0 for port in self.transmit_ports: port_rf_chain = port.rf_chain if port.rf_chain is not None else default_chain if port_rf_chain not in unique_rf_chains: unique_rf_chains[port_rf_chain] = [port_idx] else: unique_rf_chains[port_rf_chain].append(port_idx) port_idx += 1 # Update the cached RF chain map to save computation time in the future self.__cached_default_rf_chain = default_chain self.__cached_rf_transmit_map = unique_rf_chains # Return the computed RF chain map return unique_rf_chains.copy() def _rf_receive_chains(self, default_chain: RfChain) -> Dict[RfChain, List[int]]: """Compute a map of all unique RF chains used for reception. Args: default_chain (RfChain): The default RF chain to be used if no RF chain is specified for a port. Returns: A dictionary mapping each unique RF chain to the indices of the ports using it. """ # If the RF chain map has already been computed and the array hasn't changed since then, # return the cached map immediately if ( self.__cached_rf_receive_map is not None and self.__cached_default_rf_chain == default_chain ): return self.__cached_rf_receive_map.copy() unique_rf_chains: Dict[RfChain, List[int]] = dict() port_idx = 0 for port in self.receive_ports: port_rf_chain = port.rf_chain if port.rf_chain is not None else default_chain if port_rf_chain not in unique_rf_chains: unique_rf_chains[port_rf_chain] = [port_idx] else: unique_rf_chains[port_rf_chain].append(port_idx) port_idx += 1 # Update the cached RF chain map to save computation time in the future self.__cached_rf_receive_map = unique_rf_chains # Return the computed RF chain map return unique_rf_chains.copy() @staticmethod def __combine_rf_propagations( num_streams: int, sampling_rate: float, carrier_frequency: float, propagations: Sequence[Signal], stream_indices, ) -> Signal: """Combine multiple RF chain propagations into a single signal model. Args: num_streams (int): The number of signal streams to be combined. sampling_rate (float): The sampling rate of the signal model to be generated in Hz. carrier_frequency (float): The carrier frequency of the signal model to be generated in Hz. propagations (Sequence[Signal]): The RF chain propagations to be combined. stream_indices (Sequence[Sequence[int]]): The indices of the signal streams to be combined for each RF chain propagation. Returns: The combined signal model. """ # Infer the maximum number of generated samples max_num_samples = ( max(propagations, key=lambda s: s.num_samples).num_samples if len(propagations) > 0 else 0 ) # Recombine the propagated signals into a single signal model combined_signal = Signal.Create( np.zeros((num_streams, max_num_samples), dtype=np.complex128), sampling_rate, carrier_frequency, ) for propagation, stream_indices in zip(propagations, stream_indices): combined_signal[stream_indices, : propagation.num_samples] = propagation.getitem() return combined_signal
[docs] def transmit( self, signal: Signal, default_rf_chain: RfChain, isolation_model: Isolation | None = None ) -> tuple[Signal, Signal]: """Transmit a signal over the antenna array. The transmission may be distorted by the antennas impulse response / frequency characteristics, as well as by the RF chains connected to the array's ports. Args: signal (Signal): The signal model to be transmitted. default_rf_chain (RfChain): The default RF chain to be used if no RF chain is specified for a port. isolation_model (Isolation, optional): Model of the signal leaking from the transmit chains to the receive chains. If not specified, no leakage is assumed. Returns: Tuple of the actually transmitted (distorted) signal model and the leakage signal model. Raises: ValueError: If the number of signal streams does not match the number of transmit ports. """ if signal.num_streams != self.num_transmit_ports: raise ValueError( f"Number of signal streams does not match number of transmit ports ({signal.num_streams} != {self.num_transmit_ports})" ) # Collect all RF chains used by the array rf_chains = self._rf_transmit_chains(default_rf_chain) # Simulate RF chain transmission for all specified RF chains rf_signals: List[Signal] = [] for rf_chain, stream_indices in rf_chains.items(): stream_signal = signal.getstreams(stream_indices) rf_signals.append(rf_chain.transmit(stream_signal)) # Recombine the RF chain transmissions into a single signal model combined_rf_signal = self.__combine_rf_propagations( signal.num_streams, signal.sampling_rate, signal.carrier_frequency, rf_signals, rf_chains.values(), ) # Simulate the transmit-receive leakage if isolation_model is not None: leaking_signal = isolation_model.leak(combined_rf_signal) else: leaking_signal = combined_rf_signal.from_ndarray( np.empty((combined_rf_signal.num_streams, 0), dtype=np.complex128) ) # Simulate antenna transmission for all antennas antenna_signals = signal.Empty( **signal.kwargs, num_streams=self.num_transmit_antennas, num_samples=combined_rf_signal.num_samples, ) antenna_idx = 0 for port, stream_idx in zip(self.transmit_ports, range(combined_rf_signal.num_streams)): antenna_input = combined_rf_signal.getstreams(stream_idx) for antenna in port.antennas: antenna_signals[antenna_idx, :] = antenna.transmit(antenna_input).getitem() antenna_idx += 1 return antenna_signals, leaking_signal
[docs] def receive( self, impinging_signal: Signal, default_rf_chain: RfChain, leaking_signal: Signal | None = None, coupling_model: Coupling | None = None, ) -> Signal: """Receive a signal over the antenna array. Args: impinging_signal (Signal): The signal model iminging onto the antenna array over the air. default_rf_chain (RfChain): The default RF chain to be used if no RF chain is specified for a port. leaking_signal (Signal, optional): The signal model leaking from the antenna array's transmit chains. If not specified, no leakage is assumed. coupling_model (Coupling, optional): The coupling model to be used to simulate mutual coupling between the antenna elements. If not specified, no mutual coupling is assumed. Returns: The base-band digital signal model after analog-digital conversion. """ if impinging_signal.num_streams != self.num_receive_antennas: raise ValueError( f"Number of signal streams does not match number of receiving antennas ({impinging_signal.num_streams} != {self.num_receive_antennas})" ) # Simulate antenna reception for all antennas antenna_outputs = impinging_signal.Empty( num_streams=self.num_receive_antennas, num_samples=impinging_signal.num_samples, **impinging_signal.kwargs, ) for antenna_idx, (stream_idx, antenna) in enumerate( zip(range(impinging_signal.num_streams), self.receive_antennas) ): antenna_input_signal = impinging_signal.getstreams(stream_idx) antenna_outputs[antenna_idx, :] = antenna.receive(antenna_input_signal).getitem() # Simulate mutual coupling between receiving antennas if coupling_model is not None: antenna_outputs = coupling_model.receive(antenna_outputs) # Simulate transmit receive leakage if leaking_signal is not None: if leaking_signal.num_streams != self.num_receive_antennas: raise ValueError( f"Number of signal streams does not match number of receiving antennas ({impinging_signal.num_streams} != {self.num_receive_antennas})" ) antenna_outputs.superimpose(leaking_signal) # Simulate RF chain reception for all specified RF chains rf_chains = self._rf_receive_chains(default_rf_chain) rf_signals: List[Signal] = [] for rf_chain, stream_indices in rf_chains.items(): stream_signal = antenna_outputs.getstreams(stream_indices) rf_signals.append(rf_chain.receive(stream_signal)) rf_receptions = self.__combine_rf_propagations( self.num_receive_ports, antenna_outputs.sampling_rate, antenna_outputs.carrier_frequency, rf_signals, rf_chains.values(), ) return rf_receptions
[docs] def analog_digital_conversion( self, rf_signal: Signal, default_rf_chain: RfChain, frame_duration: float ) -> Signal: """Model analog-digital conversion during reception. Args: rf_signal (Signal): The signal model received by the antenna array's RF chains. default_rf_chain (RfChain): The default RF chain to be used if no RF chain is specified for a port. frame_duration (float): The duration of the frame to be modeled in seconds. Returns: The base-band digital signal model after analog-digital conversion. """ # Recall RF chain map rf_chains = self._rf_receive_chains(default_rf_chain) # Model ADC conversion during reception quantized_signals: List[Signal] = [] for rf_chain, stream_indices in rf_chains.items(): quantized_signal = rf_chain.adc.convert( rf_signal.getstreams(stream_indices), frame_duration ) quantized_signals.append(quantized_signal) # Recombine the quantized signals into a single signal model combined_quantized_signal = self.__combine_rf_propagations( quantized_signal.num_streams, quantized_signal.sampling_rate, quantized_signal.carrier_frequency, quantized_signals, rf_chains.values(), ) return combined_quantized_signal
[docs] def visualize_far_field_pattern( self, signal: Signal, *, title: str | None = None ) -> plt.Figure: """Visualize a signal radiated by the antenna array in its far-field. Returns: The Figure of the visualization. """ # Collect angle candidates zenith_angles = np.linspace(0, 0.5 * pi, 31) azimuth_angles = np.linspace(-pi, pi, 31) zenith_samples, azimuth_samples = np.meshgrid(zenith_angles[1:], azimuth_angles) aoi = np.append( np.array([azimuth_samples.flatten(), zenith_samples.flatten()]).T, np.zeros((1, 2)), axis=0, ) far_field_power = np.empty(aoi.shape[0], dtype=np.float64) for idx, (azimuth, zenith) in enumerate(aoi): phase_response = self.spherical_phase_response( signal.carrier_frequency, azimuth, zenith, AntennaMode.TX ) for block in signal: far_field_power[idx] += np.linalg.norm(phase_response @ block, 2) ** 2 axes: Axes3D with Executable.style_context(): figure, axes = plt.subplots(subplot_kw={"projection": "3d"}) figure.suptitle( "Antenna Array Transmitted Signal Spatial Characteristics" if title is None else title ) self.__visualize_pattern(axes, far_field_power, aoi) return figure
@overload def plot_pattern( self, carrier_frequency: float, mode: Literal[AntennaMode.TX] | Literal[AntennaMode.RX], beamforming_weights: np.ndarray | None = None, *, title: str | None = None, ) -> plt.Figure: """Plot the antenna array's radiation pattern. Args: carrier_frequency (float): The carrier frequency of the signal to be transmitted / received in Hz. mode (AntennaMode.TX | AntennaMode.RX): The antenna mode to be plotted. beamforming_weights (numpy.ndarray, optional): The beamforming weights to be used for beamforming. If not specified, the weights are assumed to be :math:`1+0\\mathrm{j}`. title (str, optional): The title of the plot. If not specified, a default title is assumed. """ ... # pragma: no cover @overload def plot_pattern( self, carrier_frequency: float, beamformer: TransmitBeamformer | ReceiveBeamformer, *, title: str | None = None, ) -> plt.Figure: """Plot the antenna array's radiation pattern. Args: carrier_frequency (float): The carrier frequency of the signal to be transmitted / received in Hz. beamformer (TransmitBeamformer | ReceiveBeamformer): The beamformer to be used for beamforming. title (str, optional): The title of the plot. If not specified, a default title is assumed. """ ... # pragma: no cover
[docs] def plot_pattern( # type: ignore[misc] self, carrier_frequency: float, arg_0: ( Literal[AntennaMode.TX] | Literal[AntennaMode.RX] | TransmitBeamformer | ReceiveBeamformer ), arg_1: np.ndarray | None = None, *, title: str | None = None, ) -> plt.Figure: num_ports: int ports: Sequence[AntennaPort] antennas: Sequence[SimulatedAntenna] num_antenna_attr: str mode_str: str antenna_mode: AntennaMode if arg_0 == AntennaMode.TX or isinstance(arg_0, TransmitBeamformer): num_ports = self.num_transmit_ports ports = self.transmit_ports antennas = self.transmit_antennas num_antenna_attr = "num_transmit_antennas" mode_str = "Transmit" antenna_mode = AntennaMode.TX elif arg_0 == AntennaMode.RX or isinstance(arg_0, ReceiveBeamformer): num_ports = self.num_receive_ports ports = self.receive_ports antennas = self.receive_antennas num_antenna_attr = "num_receive_antennas" mode_str = "Receive" antenna_mode = AntennaMode.RX else: raise ValueError("Unknown antenna mode encountered") # Collect angle candidates zenith_angles = np.linspace(0, 0.5 * pi, 31) azimuth_angles = np.linspace(-pi, pi, 31) zenith_samples, azimuth_samples = np.meshgrid(zenith_angles[1:], azimuth_angles) aoi = np.append( np.array([azimuth_samples.flatten(), zenith_samples.flatten()]).T, np.zeros((1, 2)), axis=0, ) # Collect sensor array response for each angle candidate antenna_responses = np.array( [ self.spherical_phase_response(carrier_frequency, angles[0], angles[1], antenna_mode) for angles in aoi ], dtype=np.complex128, ) antenna_responses *= np.array([[a.weight for a in antennas]], dtype=np.complex128) # Collect port responses for each angle candidate port_responses = np.zeros((antenna_responses.shape[0], num_ports), dtype=np.complex128) antenna_idx = 0 for port_idx, port in enumerate(ports): num_antennas = getattr(port, num_antenna_attr) port_responses[:, port_idx] = ( np.sum( antenna_responses[:, antenna_idx : antenna_idx + num_antennas], axis=1, keepdims=False, ) / num_antennas ) antenna_idx += num_antennas if arg_0 == AntennaMode.TX or arg_0 == AntennaMode.RX: beamforming_weights = np.ones(num_ports, dtype=np.complex128) if arg_1 is None else arg_1 if beamforming_weights.shape != (num_ports,): raise ValueError( f"Beamforming weights must have shape ({num_ports},) but have shape {beamforming_weights.shape}" ) power = ( np.abs(np.sum(port_responses * beamforming_weights, axis=1, keepdims=False)) ** 2 ) elif isinstance(arg_0, TransmitBeamformer): base_transform = Transformation.From_Translation(np.zeros(3)) port_responses = arg_0.encode_streams( Signal.Create( np.ones( (arg_0._num_transmit_input_streams(self.num_transmit_ports), 1), dtype=np.complex128, ), 1.0, carrier_frequency, ), self.num_transmit_ports, TransmitState( 0.0, base_transform, np.zeros(3), carrier_frequency, 1.0, self.state(base_transform), self.num_transmit_ports, ), ).getitem() antenna_weights = np.empty(self.num_transmit_antennas, dtype=np.complex128) antenna_idx = 0 for response, port in zip(port_responses, self.transmit_ports): antenna_weights[antenna_idx : antenna_idx + port.num_transmit_antennas] = response antenna_idx += port.num_transmit_antennas power = np.abs(antenna_responses @ antenna_weights) ** 2 elif isinstance(arg_0, ReceiveBeamformer): base_transform = Transformation.From_Translation(np.zeros(3)) power = np.empty(port_responses.shape[0], dtype=np.float64) for p, port_response in enumerate(port_responses): s = Signal.Create(port_response[:, None], 1.0, carrier_frequency) s = arg_0.decode_streams( s, arg_0.num_receive_output_streams(self.num_receive_ports), ReceiveState( 0.0, base_transform, np.zeros(3), carrier_frequency, 1.0, self.state(base_transform), self.num_receive_ports, ), ) power[p] = np.abs(s.getitem()) ** 2 axes: Axes3D with Executable.style_context(): figure, axes = plt.subplots(subplot_kw={"projection": "3d"}) figure.suptitle(f"Antenna Array {mode_str} Characteristics" if title is None else title) self.__visualize_pattern(axes, power, aoi) return figure
@staticmethod def __visualize_pattern(axes: Axes3D, power: np.ndarray, aoi: np.ndarray) -> None: power /= power.max() # Normalize for visualization purposes # Threshold the lower values for better visualization power[power < 0.01] = 0.01 # Compute surface surface = np.array( [ power * np.cos(aoi[:, 0]) * np.sin(aoi[:, 1]), power * np.sin(aoi[:, 0]) * np.sin(aoi[:, 1]), power * np.cos(aoi[:, 1]), ], dtype=np.float64, ) triangles = tri.Triangulation(aoi[:, 0], aoi[:, 1]) cmap = plt.cm.ScalarMappable(norm=colors.Normalize(power.min(), power.max()), cmap="jet") axes.plot_trisurf( surface[0, :], surface[1, :], surface[2, :], triangles=triangles.triangles, cmap=cmap.cmap, norm=cmap.norm, linewidth=0.0, ) axes.set_xlim((-1, 1)) axes.set_ylim((-1, 1)) axes.set_zlim((0, 1)) axes.set_xlabel("X") axes.set_ylabel("Y")
[docs] def antenna_state(self, base_pose: Transformation) -> AntennaArrayState: """Return the antenna array's state with respect to a base pose. Args: base_pose (Transformation): The base pose to be used as reference. Returns: The antenna array's state with respect to the base pose. """
[docs] class SimulatedUniformArray( SimulatedAntennaArray, UniformArray[SimulatedAntennaPort, SimulatedAntenna] ): """A uniform array of simulated antennas.""" yaml_tag = "SimulatedUniformArray" def __init__( self, element: Type[SimulatedAntenna] | SimulatedAntenna, spacing: float, dimensions: Sequence[int], pose: Transformation | None = None, ) -> None: """ Args: element (Type[SimulatedAntenna] | SimulatedAntenna): The anntenna model this uniform array assumes. spacing (float): Spacing between the antenna elements in m. dimensions (Sequence[int]): The number of antennas in x-, y-, and z-dimension. pose (Transformation, optional): The anntena array's transformation with respect to its device. """ # Initialize base classes # Not that the order of the base class initialization is important here to presrve the kinematic chain! SimulatedAntennaArray.__init__(self, pose) UniformArray.__init__(self, element, spacing, dimensions, pose)
[docs] class SimulatedCustomArray( SimulatedAntennaArray, CustomAntennaArray[SimulatedAntennaPort, SimulatedAntenna] ): """A custom array of simulated antennas.""" yaml_tag = "SimulatedCustomArray" def __init__( self, ports: Sequence[SimulatedAntennaPort | SimulatedAntenna] = None, pose: Transformation | None = None, ) -> None: """ Args: ports (Sequence[SimulatedAntennaPort | SimulatedAntenna], optional): Sequence of antenna ports available within this array. If antennas are passed instead of ports, the ports are automatically created. If not specified, an empty array is assumed. pose (Transformation, optional): The anntena array's transformation with respect to its device. """ # Initialize base classes CustomAntennaArray.__init__(self, ports, pose) SimulatedAntennaArray.__init__(self, pose)
[docs] def add_port(self, port: SimulatedAntennaPort) -> None: CustomAntennaArray.add_port(self, port) self.rf_chain_modified()
[docs] def remove_port(self, port: SimulatedAntennaPort) -> None: CustomAntennaArray.remove_port(self, port) self.rf_chain_modified()
[docs] def add_antenna(self, antenna: SimulatedAntenna) -> None: CustomAntennaArray.add_antenna(self, antenna) self.rf_chain_modified()