Cleaning up

docs/api/utils.md

@@ -1,9 +1,9 @@
 # Utils
 
 ::: neurotechdevkit.scenarios.create_grid_circular_mask
-options:
-show_root_heading: true
+    options:
+      show_root_heading: true
 
 ::: neurotechdevkit.scenarios.make_grid
-options:
-show_root_heading: true
+    options:
+      show_root_heading: true

docs/examples/plot_scenarios.py

@@ -10,25 +10,27 @@
 import neurotechdevkit as ndk
 
 
-def plot_scenario(scenario_id):
-    print(f"Simulating scenario: {scenario_id}")
-    scenario = ndk.BUILTIN_SCENARIOS[scenario_id].value()
+def plot_scenario(scenario):
+    print(f"Simulating scenario: {scenario.name}")
+    scenario = scenario.value()
     scenario.compile_problem(center_frequency=5e5)
     result = scenario.simulate_steady_state()
     result.render_steady_state_amplitudes(show_material_outlines=False)
 
 
 # %%
-# Simulating scenario: scenario-0
+# Simulating scenario: scenario 0
 # ===================================
-plot_scenario("scenario-0")
+plot_scenario(ndk.BUILTIN_SCENARIOS.SCENARIO_0)
 
 # %%
-# Simulating scenario: scenario-1-2d-v0
+# Simulating scenario: scenario 1 2D
 # ===================================
-plot_scenario("scenario-1-2d-v0")
+plot_scenario(ndk.BUILTIN_SCENARIOS.SCENARIO_1_2D)
 
 # %%
-# Simulating scenario: scenario-2-2d-v0
+# Simulating scenario: scenario 2 2D
 # ===================================
-plot_scenario("scenario-2-2d-v0")
+plot_scenario(ndk.BUILTIN_SCENARIOS.SCENARIO_2_2D)
+
+# %%

docs/index.md

@@ -22,25 +22,23 @@ You can run `neurotechdevkit` inside a docker container with just a couple of st
 
 1. Run the following command:
 
-   ```
-   docker run -p 8888:8888 -it ghcr.io/agencyenterprise/neurotechdevkit:latest
-   ```
+    ```
+    docker run -p 8888:8888 -it ghcr.io/agencyenterprise/neurotechdevkit:latest
+    ```
 
-   The command above will start a [Jupyter notebook](https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html) server with example notebooks you can use to explore `neurotechdevkit`. Use the printed URL to open it in your browser or connect to it using your IDE.
+    The command above will start a [Jupyter notebook](https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html) server with example notebooks you can use to explore `neurotechdevkit`. Use the printed URL to open it in your browser or connect to it using your IDE.
 
-   All changes you make to these files will be lost once you stop the docker container.
+    All changes you make to these files will be lost once you stop the docker container.
 
 > **Note**:
 >
-> You can have persisting [Jupyter notebooks](https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html) by running
+>    You can have persisting [Jupyter notebooks](https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html) by running
+>    ```
+>    docker run -p 8888:8888  -v $(pwd)/notebooks:/ndk/notebooks -it ghcr.io/agencyenterprise/neurotechdevkit:latest
+>    ```
+>    The command above will create a folder `notebooks` in your current directory where you can put your jupyter notebooks.
 >
-> ```
-> docker run -p 8888:8888  -v $(pwd)/notebooks:/ndk/notebooks -it ghcr.io/agencyenterprise/neurotechdevkit:latest
-> ```
->
-> The command above will create a folder `notebooks` in your current directory where you can put your jupyter notebooks.
->
-> We recommend downloading the `.zip` file with example notebooks from this [link](https://agencyenterprise.github.io/neurotechdevkit/generated/gallery/gallery_jupyter.zip), and extracting it into your local `notebooks` folder so you can access them from the docker.
+>    We recommend downloading the `.zip` file with example notebooks from this [link](https://agencyenterprise.github.io/neurotechdevkit/generated/gallery/gallery_jupyter.zip), and extracting it into your local `notebooks` folder so you can access them from the docker.
 
 ### Local installation
 

docs/usage/defining_sources.md

@@ -32,16 +32,16 @@ In the future, we plan to implement constraints to avoid overlapping with solid
 If a source is not specified before the scenario is rendered or simulated, then a default source will be used. So you should add the source to the scenario before doing either of these operations (rendering or simulating).
 
 !!! note
-The visualization of the source in 2D plots currently has some scaling limitations, and transducers with short focal lengths can appear very small. This only affects the visualization and not the simulation, and will be improved in future versions.
+    The visualization of the source in 2D plots currently has some scaling limitations, and transducers with short focal lengths can appear very small. This only affects the visualization and not the simulation, and will be improved in future versions.
 
 The implemented source options are:
 
-- `FocusedSource2D`
-- `FocusedSource3D`
-- `PlanarSource2D`
-- `PlanarSource3D`
-- `PhasedArraySource2D`
-- `PhasedArraySource3D`
+* `FocusedSource2D`
+* `FocusedSource3D`
+* `PlanarSource2D`
+* `PlanarSource3D`
+* `PhasedArraySource2D`
+* `PhasedArraySource3D`
 
 The 2D sources are for 2D scenarios and the 3D sources for 3D scenarios. The parameters to configure the sources are identical between focused and planar sources, except that planar sources have a pre-defined focal length of `np.inf`.
 

src/neurotechdevkit/rendering/napari.py

@@ -123,7 +123,6 @@ def _create_napari_3d(
     add_material_layers(viewer, scenario, viewer_config)
     add_target(viewer, scenario)
 
-    assert hasattr(scenario, "sources")
     for source in scenario.sources:
         add_source(viewer, scenario, source)
 

src/neurotechdevkit/results/_results.py

@@ -10,7 +10,7 @@
 import tarfile
 from dataclasses import dataclass
 from io import BytesIO
-from typing import Any
+from typing import Any, Union
 
 import numpy as np
 import numpy.typing as npt
@@ -57,7 +57,7 @@ class Result(abc.ABC):
             pde.
     """
 
-    scenario: scenarios.Scenario
+    scenario: Union[scenarios.Scenario2D, scenarios.Scenario3D]
     center_frequency: float
     effective_dt: float
     pde: stride.Operator
@@ -1085,7 +1085,7 @@ def _build_animation(
 
 
 def create_steady_state_result(
-    scenario: scenarios.Scenario,
+    scenario: Union[scenarios.Scenario2D, scenarios.Scenario3D],
     center_frequency: float,
     effective_dt: float,
     pde: stride.Operator,
@@ -1148,7 +1148,7 @@ def create_steady_state_result(
 
 
 def create_pulsed_result(
-    scenario: scenarios.Scenario,
+    scenario: Union[scenarios.Scenario2D, scenarios.Scenario3D],
     center_frequency: float,
     effective_dt: float,
     pde: stride.Operator,

src/neurotechdevkit/scenarios/_base.py

@@ -79,24 +79,6 @@ class Scenario(abc.ABC):
     slice_position: float
     material_outline_upsample_factor: int = 16
 
-    def render_layout(
-        self,
-        show_sources: bool = True,
-        show_target: bool = True,
-        show_material_outlines: bool = False,
-    ) -> None:
-        """Render the layout of the scenario. Is implemented by subclasses."""
-        raise NotImplementedError()
-
-    @abc.abstractmethod
-    def get_target_mask(self) -> npt.NDArray[np.bool_]:
-        """Return the mask for the target region.
-
-        Returns:
-            A boolean array indicating which gridpoints correspond to the target region.
-        """
-        pass
-
     @property
     def extent(self) -> npt.NDArray[np.float_]:
         """The extent of the spatial grid (in meters)."""
@@ -349,7 +331,7 @@ def simulate_steady_state(
         wavefield = np.moveaxis(pde.wavefield.data[:-1], 0, -1)
 
         return results.create_steady_state_result(
-            scenario=self,
+            scenario=self,  # type: ignore
             center_frequency=center_frequency,
             effective_dt=self.dt * recording_time_undersampling,
             pde=pde,
@@ -482,7 +464,7 @@ def _simulate_pulse(
         wavefield = np.moveaxis(pde.wavefield.data[:-1], 0, -1)
 
         return results.create_pulsed_result(
-            scenario=self,
+            scenario=self,  # type: ignore
             center_frequency=center_frequency,
             effective_dt=self.dt * recording_time_undersampling,
             pde=pde,