def __init__(self, position, center_frequency, bandwidth, resistance,
orientation=(0,0,1), effective_height=None, noisy=True,
unique_noise_waveforms=10):
if effective_height is None:
# Calculate length of half-wave dipole
self.effective_height = 3e8 / center_frequency / 2
else:
self.effective_height = effective_height
# Get the critical frequencies in Hz
f_low = center_frequency - bandwidth/2
f_high = center_frequency + bandwidth/2
# Get arbitrary x-axis orthogonal to orientation
tmp_vector = np.zeros(3)
while np.array_equal(np.cross(orientation, tmp_vector), (0,0,0)):
tmp_vector = np.random.rand(3)
ortho = np.cross(orientation, tmp_vector)
# Note: ortho is not normalized, but will be normalized by Antenna init
super().__init__(position=position, z_axis=orientation, x_axis=ortho,
antenna_factor=1/self.effective_height,
temperature=ice.temperature(position[2]),
freq_range=(f_low, f_high), resistance=resistance,
unique_noise_waveforms=unique_noise_waveforms,
noisy=noisy)
# Build scipy butterworth filter to speed up response function
b, a = scipy.signal.butter(1, 2*np.pi*np.array(self.freq_range),
btype='bandpass', analog=True)
self.filter_coeffs = (b, a)
def __init__(self,
response_data,
position,
center_frequency,
bandwidth,
resistance,
z_axis=(0, 0, 1),
x_axis=(1, 0, 0),
efficiency=1,
noisy=True,
unique_noise_waveforms=10):
# Parse the response data
self._theta_response = response_data[0]
self._phi_response = response_data[1]
self._response_freqs = response_data[2]
self._response_zens = response_data[3]
self._response_azis = response_data[4]
# Get the critical frequencies in Hz
f_low = center_frequency - bandwidth / 2
f_high = center_frequency + bandwidth / 2
super().__init__(position=position,
z_axis=z_axis,
x_axis=x_axis,
efficiency=efficiency,
freq_range=(f_low, f_high),
temperature=ice.temperature(position[2]),
resistance=resistance,
noisy=noisy,
unique_noise_waveforms=unique_noise_waveforms)
def test_creation(self, dipole):
"""Test that the antenna's creation goes as expected"""
assert dipole.name == "ant"
assert np.array_equal(dipole.position, [0, 0, -250])
assert np.array_equal(dipole.z_axis, [0, 0, 1])
assert dipole.x_axis[2] == 0
assert dipole.antenna_factor == 2 * 250e6 / 3e8
assert dipole.efficiency == 1
assert np.array_equal(dipole.freq_range, [100e6, 400e6])
assert dipole.temperature == pytest.approx(ice.temperature(-250))
assert dipole.resistance == 100
assert dipole.threshold == 75e-6
assert dipole.noisy
def __init__(self,
response_data,
position,
center_frequency,
bandwidth,
resistance,
orientation=(0, 0, 1),
efficiency=1,
noisy=True,
unique_noise_waveforms=10):
# Parse the response data
self._theta_response = response_data[0]
self._phi_response = response_data[1]
self._response_freqs = response_data[2]
self._response_zens = response_data[3]
self._response_azis = response_data[4]
# Get the critical frequencies in Hz
f_low = center_frequency - bandwidth / 2
f_high = center_frequency + bandwidth / 2
# Get arbitrary x-axis orthogonal to orientation
tmp_vector = np.zeros(3)
while np.array_equal(np.cross(orientation, tmp_vector), (0, 0, 0)):
tmp_vector = np.random.rand(3)
ortho = np.cross(orientation, tmp_vector)
# Note: ortho is not normalized, but will be normalized by Antenna's init
super().__init__(position=position,
z_axis=orientation,
x_axis=ortho,
efficiency=efficiency,
freq_range=(f_low, f_high),
temperature=ice.temperature(position[2]),
resistance=resistance,
noisy=noisy,
unique_noise_waveforms=unique_noise_waveforms)