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Implementing new API for NDK (#122)
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* Implementing new API for NDK

* Updating gallery examples to use the new API

* Updating 3d scenario result

* Cleaning up scenario __init__

* Updating api docs

* Compiling problem explicitly

* Small fixes to plot full scenario

* Creating NDK's own Problem class

* Removing 'scenario_id' attribute

* Cleaning up

* Fixing docs

* Decoupling render layout from compile problem

* Moving grid creation to its own class

* Moving center_frequency to the scenario root

* Cleaning up

* Cleaning up code. Invalidating grid and compiled problem when center_frequency is changed

* Adapting documentation

* Updating plot full scenario to use the procedural approach

* Updating API docs adding the Grid and Problem pages

* Fixing bug with 3D example

* Improving docs, updating hash of 3d results file

* Improving docs

* Small improvements to notebook

* Addressing review suggestion: replacing enum with subdirectory containing the built in scenarios

* Update src/neurotechdevkit/grid.py

Co-authored-by: charles <[email protected]>

* Addressing review suggestion

* Fixing issue with commited PR suggestion

* Fixing bug

* Removing layer_ids from problem creation. Removing need of creating material_layers, using material_masks keys instead

* Fixing print

* Replacing numpy arrays with plain lists for simple attributes like position, origin and direction

* Refactoring

* Refactoring

* Fixing hash of results file

* Simplifying API

* Setting center_frequency in built_in scenarios

* Adding SliceAxis to spellcheck's whitelist

* Adding unit tests and cleaning up code

* Adding predefined target options

* Fix typo

* Showing how the predefined targt options can be used

* Improving plot full scenario masks creation

* Addressing review suggestions

* Fixing spellchecking error by removing unnecessary types from docstrings

* Updating 3d file hash

* update docstrings

---------

Co-authored-by: charles <[email protected]>
Co-authored-by: d-lucena <[email protected]>
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5 changes: 5 additions & 0 deletions docs/api/grid.md
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# Grid

::: neurotechdevkit.grid
options:
show_root_toc_entry: false
5 changes: 0 additions & 5 deletions docs/api/make.md

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5 changes: 5 additions & 0 deletions docs/api/materials.md
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# Materials

::: neurotechdevkit.materials
options:
show_root_toc_entry: false
5 changes: 5 additions & 0 deletions docs/api/problem.md
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# Problem

::: neurotechdevkit.problem
options:
show_root_toc_entry: false
20 changes: 5 additions & 15 deletions docs/api/scenarios.md
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Expand Up @@ -12,35 +12,25 @@
options:
show_root_heading: true

::: neurotechdevkit.scenarios.Scenario0
::: neurotechdevkit.scenarios.built_in.Scenario0
options:
show_root_heading: true
members:
- _SCENARIO_ID

::: neurotechdevkit.scenarios.Scenario1_2D
::: neurotechdevkit.scenarios.built_in.Scenario1_2D
options:
show_root_heading: true
members:
- _SCENARIO_ID

::: neurotechdevkit.scenarios.Scenario1_3D
::: neurotechdevkit.scenarios.built_in.Scenario1_3D
options:
show_root_heading: true
members:
- _SCENARIO_ID

::: neurotechdevkit.scenarios.Scenario2_2D
::: neurotechdevkit.scenarios.built_in.Scenario2_2D
options:
show_root_heading: true
members:
- _SCENARIO_ID

::: neurotechdevkit.scenarios.Scenario2_3D
::: neurotechdevkit.scenarios.built_in.Scenario2_3D
options:
show_root_heading: true
members:
- _SCENARIO_ID

::: neurotechdevkit.scenarios.Target
options:
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13 changes: 0 additions & 13 deletions docs/api/utils.md

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4 changes: 2 additions & 2 deletions docs/examples/plot_3d.py
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Expand Up @@ -19,8 +19,8 @@

import neurotechdevkit as ndk

URL = "https://neurotechdevkit.s3.us-west-2.amazonaws.com/result-scenario-2-3d.tz"
known_hash = "6a5de26466028c673d253ca014c75c719467ec6c28d7178baf9287b44ad15191"
URL = "https://neurotechdevkit.s3.us-west-2.amazonaws.com/result-scenario-2-3d-v3.tz"
known_hash = "f9c1305fe4be4d348587fdcdfa54bc1a994e6e7dea866bc88ecc7875608c6010"
downloaded_file_path = pooch.retrieve(url=URL, known_hash=known_hash, progressbar=True)
result = ndk.load_result_from_disk(downloaded_file_path)

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12 changes: 6 additions & 6 deletions docs/examples/plot_adding_custom_source.py
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Expand Up @@ -27,20 +27,20 @@
# - delay `(float, optional)`: the delay (in seconds) that the source will wait before
# emitting. Defaults to 0.0.

import numpy as np

import neurotechdevkit as ndk

source = ndk.sources.FocusedSource2D(
position=np.array([0.00, 0.0]),
direction=np.array([0.9, 0.0]),
position=[0.00, 0.0],
direction=[0.9, 0.0],
aperture=0.01,
focal_length=0.01,
num_points=1000,
)

scenario = ndk.make("scenario-0-v0")
scenario.add_source(source)
scenario = ndk.built_in.Scenario0()
scenario.sources = [source]
scenario.make_grid()
scenario.compile_problem()
result = scenario.simulate_steady_state()
assert isinstance(result, ndk.results.SteadyStateResult2D)
result.render_steady_state_amplitudes()
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11 changes: 5 additions & 6 deletions docs/examples/plot_customized_center_frequency.py
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Expand Up @@ -11,19 +11,18 @@

CENTER_FREQUENCY = 6e5

scenario = ndk.make("scenario-0-v0")

# using default material layers
scenario.material_layers = ["water", "cortical_bone", "brain", "tumor"]
scenario = ndk.scenarios.built_in.Scenario0()

# Customizing material properties
scenario.material_properties = {
"tumor": ndk.materials.Material(
vp=1850.0, rho=1250.0, alpha=0.8, render_color="#94332F"
),
}

result = scenario.simulate_steady_state(center_frequency=CENTER_FREQUENCY)
scenario.center_frequency = CENTER_FREQUENCY
scenario.make_grid()
scenario.compile_problem()
result = scenario.simulate_steady_state()
assert isinstance(result, ndk.results.SteadyStateResult2D)
result.render_steady_state_amplitudes(show_material_outlines=False)

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210 changes: 73 additions & 137 deletions docs/examples/plot_full_scenario.py
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Expand Up @@ -10,114 +10,62 @@
The following code is a simplified implementation of NDK's Scenario 1.
"""
# %%
# ## Implementing a Scenario
# Implementing a Scenario
import numpy as np
import stride

from neurotechdevkit import sources
from neurotechdevkit.grid import Grid
from neurotechdevkit.problem import Problem
from neurotechdevkit.results import SteadyStateResult2D
from neurotechdevkit.scenarios import (
Scenario2D,
Target,
add_material_fields_to_problem,
make_grid,
from neurotechdevkit.scenarios import Scenario2D, Target

# %%
# Creating the scenario
scenario = Scenario2D()
scenario.center_frequency = 5e5 # Hz
scenario.target = Target(
target_id="target_1", center=[0.064, 0.0], radius=0.004, description=""
)
scenario.material_properties = {}
scenario.origin = [0.0, -0.035]
scenario.sources = [
sources.FocusedSource2D(
position=[0.0, 0.0],
direction=[1.0, 0.0],
aperture=0.064,
focal_length=0.064,
num_points=1000,
)
]
scenario.material_outline_upsample_factor = 8

# %%
# Creating grid
grid = Grid.make_grid(
extent=(0.12, 0.07), # m
speed_water=1500,
center_frequency=scenario.center_frequency,
ppw=6,
)

scenario.grid = grid

# %%
# Creating masks


def fill_mask(mask, start, end, dx):
# fill linearly along the x axis
if end is None:
n = int(start / dx)
mask[n:] = True
else:
n = int(start / dx)
m = int(end / dx)
mask[n:m] = True

class FullScenario(Scenario2D):
"""This Scenario is based on benchmark 4 of the following paper:
Jean-Francois Aubry, Oscar Bates, Christian Boehm, et al., "Benchmark problems for
transcranial ultrasound simulation: Intercomparison of compressional wave models",
The Journal of the Acoustical Society of America 152, 1003 (2022);
doi: 10.1121/10.0013426
https://asa.scitation.org/doi/pdf/10.1121/10.0013426
"""

_SCENARIO_ID = "the_id_for_this_scenario"

"""
Target attributes:
target_id: the string id of the target.
center: the location of the center of the target (in meters).
radius: the radius of the target (in meters).
description: a text describing the target.
"""
_TARGET_OPTIONS = {
"target_1": Target("target_1", np.array([0.064, 0.0]), 0.004, ""),
}

"""
The order of returned materials defines the layering of the scenario.
"""
material_layers = [
"water",
"skin",
"cortical_bone",
"trabecular_bone",
"brain",
]

def __init__(self, complexity="fast"):
"""
Instantiate a new scenario.
The origin defines the spatial coordinates of grid position (0, 0, 0).
"""
self._target_id = "target_1"

super().__init__(
origin=np.array([0.0, -0.035]),
complexity=complexity,
)

@property
def _material_outline_upsample_factor(self) -> int:
"""
The factor to use when upsampling the material field before
detecting transitions between materials. If the factor is N, then each pixel
will be split into N^2 pixels. Defaults to 1 (no resampling).
"""
return 8

def _compile_problem(self, center_frequency) -> stride.Problem:
"""The problem definition for the scenario."""
extent = np.array([0.12, 0.07]) # m
# scenario constants
speed_water = 1500 # m/s

# desired resolution for complexity=fast
ppw = 6

# compute resolution
dx = speed_water / center_frequency / ppw # m

grid = make_grid(extent=extent, dx=dx)
problem = stride.Problem(
name=f"{self.scenario_id}-{self.complexity}", grid=grid
)
problem = add_material_fields_to_problem(
problem=problem,
materials=self.get_materials(center_frequency),
layer_ids=self.layer_ids,
masks={
name: _create_scenario_1_mask(name, problem.grid)
for name in self.material_layers
},
)
return problem

def get_default_source(self) -> sources.Source:
"""The transducer source for the scenario."""
return sources.FocusedSource2D(
position=np.array([0.0, 0.0]),
direction=np.array([1.0, 0.0]),
aperture=0.064,
focal_length=0.064,
num_points=1000,
)


def _create_scenario_1_mask(material, grid):

def create_masks(grid):
# layers are defined by X position
dx = grid.space.spacing[0]

Expand All @@ -131,56 +79,44 @@ def _create_scenario_1_mask(material, grid):
0.0835, # brain
]
)
layers = np.array(
["water", "skin", "cortical_bone", "trabecular_bone", "cortical_bone", "brain"]
)
interfaces = np.cumsum(layers_m)

mask = np.zeros(grid.space.shape, dtype=bool)
mask_materials = {}

if material == "water":
_fill_mask(mask, start=0, end=interfaces[0], dx=dx)
for material in np.unique(layers):
mask = np.zeros(grid.space.shape, dtype=bool)
for index in np.where(layers == material)[0]:
start = interfaces[index - 1] if material != "water" else 0
end = interfaces[index] if material != "brain" else None
fill_mask(mask, start=start, end=end, dx=dx)
mask_materials[material] = mask
return mask_materials

elif material == "skin":
_fill_mask(mask, start=interfaces[0], end=interfaces[1], dx=dx)

elif material == "cortical_bone":
_fill_mask(mask, start=interfaces[1], end=interfaces[2], dx=dx)
_fill_mask(mask, start=interfaces[3], end=interfaces[4], dx=dx)

elif material == "trabecular_bone":
_fill_mask(mask, start=interfaces[2], end=interfaces[3], dx=dx)

elif material == "brain":
_fill_mask(mask, start=interfaces[4], end=None, dx=dx)

else:
raise ValueError(material)

return mask


def _fill_mask(mask, start, end, dx):
# fill linearly along the x axis
if end is None:
n = int(start / dx)
mask[n:] = True
else:
n = int(start / dx)
m = int(end / dx)
mask[n:m] = True
scenario.material_masks = create_masks(grid)


# %%
# ## Creating the scenario
scenario = FullScenario()
# Rendering the layout
scenario.render_layout()

# %%
# ## Rendering the scenario layout
scenario.render_layout()
# Creating problem

problem = Problem(grid=grid)
problem.add_material_fields(
materials=scenario.materials,
masks=scenario.material_masks,
)
scenario.problem = problem

# %%
# ## Running the scenario
# Rendering the simulation
result = scenario.simulate_steady_state()
assert isinstance(result, SteadyStateResult2D)
result.render_steady_state_amplitudes(show_material_outlines=False)


# %%
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