eSDIva¶
Efficient Sparse Delta Integration for Vectorized Acoustics.
Ultrasound pressure-field simulation for arbitrary transducer geometries — fast and exact. Built on the Tupholme–Stepanishen Spatial Impulse Response formulation and accelerated by the SDI method.
Install¶
[all] switches on every optional feature. See
Installation to install a slimmer subset.
Quickstart¶
import esdiva as diva
# 64-element linear array focused at 30 mm depth
tx = diva.transducers.LinearArrayTransducer(
n_elements=64,
element_width_mm=0.25,
element_height_mm=12.0,
kerf_mm=0.05,
no_sub_x=2,
no_sub_y=4,
frequency_Hz=5e6,
)
tx.compute_delays(focus_mm=[0, 0, 30])
tx.compute_apodization(focus_mm=[0, 0, 30], FoverD=2.0)
# Field grid (all distances in mm)
field_points = {
"x_extent": [-5, 5],
"y_extent": [-0.5, 0.5],
"z_extent": [5, 55],
"dx": 0.1,
"dy": 1.0,
"dz": 0.2,
}
# Run monochromatic simulation and visualize
sim = diva.Emission(tx, monochromatic=True)
p, coords = sim(field_points, method="auto")
diva.plot2D_pressure_slices(p, coords=coords, db_scale=True, vmin=-40)
Why eSDIva¶
Sparse Delta Integration — the core of eSDIva
The SDI method reformulates the spatial impulse response as a sparse train of Dirac deltas integrated in time or frequency, evaluated with Numba-parallel CPU kernels (no GPU required). For large apertures this delivers >100× faster emission and >20× faster reception (RF) than sample-by-sample evaluation — with negligible difference from Field II — making full RF and phantom simulations practical on a laptop.
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SDI — very fast SIR
Sparse Delta Integration in time and frequency domain. >100× emission and
20× reception speedup on large apertures, Field II-accurate.
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Numba-parallel, CPU-only
Parallel JIT kernels run on any multi-core CPU. No CUDA, no GPU dependency — fast RF simulation anywhere.
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Emission & Reception
CW / transient / attenuated emission fields, and full pulse-echo RF for PSF, phantom, FMC, and sequence (PW/DW) studies.
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Rich transducer library
Linear, convex, matrix arrays; flat, concave, convex, focused circular mono-elements; fully custom geometries. Import Field II probes.
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3-D visualization
Interactive PyVista scenes: transducer geometry, pressure volumes, STL meshes, and brain anatomy composed in one renderer.
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Brain atlas integration
Map acoustic fields onto anatomy via BrainGlobe. Rat and mouse atlases out of the box.
Background theory
The SIR/SDI derivations are covered in the accompanying eSDIva paper — see Citing eSDIva.