Skip to content

Fix apply apodization #552

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Draft
waltsims wants to merge 1 commit into
base: master
Choose a base branch
from
Draft

Fix apply apodization #552

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
49 changes: 26 additions & 23 deletions kwave/kWaveSimulation.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -826,7 +826,7 @@ def check_source(self, k_dim, k_Nt) -> None:
Check the source properties for correctness and validity

Args:
kgrid_dim: kWaveGrid dimension
k_dim: kWaveGrid dimension
k_Nt: Number of time steps in kWaveGrid

Returns:
Expand Down Expand Up @@ -961,47 +961,50 @@ def check_source(self, k_dim, k_Nt) -> None:
# get the input signal - this is appended with zeros if required to
# account for the beamforming delays (this will throw an error if the
# input signal is not defined)
self.transducer_input_signal = self.source.input_signal
transducer_input_signal = self.source.input_signal

# get the delay mask that accounts for the beamforming delays and
# elevation focussing; this is used so that a single time series can be
# applied to the complete transducer mask with different delays
# Ensure input signal has shape (L, 1)
if transducer_input_signal.ndim == 1:
transducer_input_signal = transducer_input_signal.reshape(-1, 1)

# get the delay mask that accounts for the beamforming delays and elevation focussing
delay_mask = self.source.delay_mask()

# set source flag - this should be the length of signal minus the
# maximum delay
self.transducer_source = self.transducer_input_signal.size - delay_mask.max()
# set source flag - this should be the length of signal minus the maximum delay
self.transducer_source = transducer_input_signal.size - delay_mask.max()

# get the active elements mask
active_elements_mask = self.source.active_elements_mask

# get the apodization mask if not set to 'Rectangular' and convert to a
# linear array
# Process transmit apodization
if self.source.transmit_apodization == "Rectangular":
self.transducer_transmit_apodization = 1
# No apodization applied; leave input signal as is
else:
self.transducer_transmit_apodization = self.source.transmit_apodization_mask
self.transducer_transmit_apodization = self.transducer_transmit_apodization[active_elements_mask != 0]
# Use the get_transmit_apodization() method to get the correctly sized apodization
self.transducer_transmit_apodization = self.source.get_transmit_apodization()
# Apply apodization: multiply the reshaped input signal (L x 1) by the transpose of the apodization vector (1 x N_active)
transducer_input_signal = transducer_input_signal * self.transducer_transmit_apodization.T

# create indexing variable corresponding to the active elements
# and convert the data type depending on the number of indices
self.u_source_pos_index = matlab_find(active_elements_mask).astype(self.index_data_type)
# Ensure the final transducer input signal has a leading singleton dimension for compatibility
transducer_input_signal = np.expand_dims(transducer_input_signal, axis=0)
# Transpose the last two axes to swap time and active element dimensions
transducer_input_signal = np.transpose(transducer_input_signal, (0, 2, 1))

# convert the delay mask to an indexing variable (this doesn't need to
# be modified if the grid is expanded) which tells each point in the
# source mask which point in the input_signal should be used
delay_mask = matlab_mask(delay_mask, active_elements_mask != 0) # compatibility
# Store the apodized input signal for later use
self.transducer_input_signal = transducer_input_signal

# create indexing variable corresponding to the active elements and convert the data type depending on the number of indices
self.u_source_pos_index = matlab_find(active_elements_mask).astype(self.index_data_type)

# convert the data type depending on the maximum value of the delay
# mask and the length of the source
# convert the delay mask to an indexing variable
delay_mask = matlab_mask(delay_mask, active_elements_mask != 0)
smallest_type = get_smallest_possible_type(delay_mask.max(), "uint")
if smallest_type is not None:
delay_mask = delay_mask.astype(smallest_type)

# move forward by 1 as a delay of 0 corresponds to the first point in the input signal
self.delay_mask = delay_mask + 1

# clean up unused variables
del active_elements_mask

def check_kgrid_time(self) -> None:
Expand Down
Loading