Add Focussed Detector In 2D Example

examples/README.md

@@ -26,9 +26,10 @@ Every example has a short readme.md file which briefly describes the purpose of
 
 - [Focused bowl transducer (axisymmetric)](at_focused_bowl_AS/) ([original example](http://www.k-wave.org/documentation/example_at_piston_and_bowl_transducers.php#heading6), [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/waltsims/k-wave-python/blob/master/examples/at_focused_bowl_AS/at_focused_bowl_AS.ipynb))
 
-
 - [Focused annular array](at_focused_annular_array_3D/) ([original example](http://www.k-wave.org/documentation/example_at_piston_and_bowl_transducers.php#heading7), [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/waltsims/k-wave-python/blob/master/examples/at_focused_annular_array_3D/at_focused_annular_array_3D.ipynb))
 
+- [Focussed Detector In 2D Example](at_focused_annular_array_3D/) ([original example](http://www.k-wave.org/documentation/example_sd_focussed_detector_2D.php), [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/waltsims/k-wave-python/blob/master/examples/sd_focussed_detector_2D/sd_focussed_detector_2D.ipynb))
+
 
 ## Contributing new examples
 

examples/sd_focussed_detector_2D/README.md

@@ -0,0 +1,7 @@
+# Focussed Detector In 2D Example
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/waltsims/k-wave-python/blob/master/examples/sd_focussed_detector_2D/sd_focussed_detector_2D.ipynb)
+
+This example shows how k-Wave-python can be used to model the output of a focussed semicircular detector where the directionality arises from spatially averaging across the detector surface.
+
+To read more, visit the [original example page](http://www.k-wave.org/documentation/example_sd_focussed_detector_2D.php).

examples/sd_focussed_detector_2D/sd_focussed_detector_2D.ipynb

@@ -0,0 +1,199 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install git+https://github.com/waltsims/k-wave-python "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Focussed Detector In 2D Example\n",
+    "\n",
+    "This example shows how k-Wave-python can be used to model the output of a focussed semicircular detector where the directionality arises from spatially averaging across the detector surface."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "\n",
+    "import os\n",
+    "from copy import deepcopy\n",
+    "from tempfile import gettempdir\n",
+    "\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from kwave.data import Vector\n",
+    "from kwave.kgrid import kWaveGrid\n",
+    "from kwave.kmedium import kWaveMedium\n",
+    "from kwave.ksource import kSource\n",
+    "from kwave.kspaceFirstOrder2D import kspaceFirstOrder2DC\n",
+    "from kwave.ktransducer import kSensor\n",
+    "from kwave.options.simulation_execution_options import SimulationExecutionOptions\n",
+    "from kwave.options.simulation_options import SimulationOptions\n",
+    "from kwave.utils.mapgen import make_disc, make_circle\n",
+    "from kwave.utils.data import scale_SI\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# create the computational grid\n",
+    "grid_size = Vector([180, 180])  # [grid points]\n",
+    "grid_spacing = Vector([0.1e-3, 0.1e-3])  # [m]\n",
+    "kgrid = kWaveGrid(grid_size, grid_spacing)\n",
+    "\n",
+    "# define the properties of the propagation medium\n",
+    "medium = kWaveMedium(sound_speed=1500)\n",
+    "\n",
+    "# define a sensor as part of a circle centred on the grid\n",
+    "sensor_radius = 65  # [grid points]\n",
+    "arc_angle = np.pi  # [rad]\n",
+    "sensor_mask = make_circle(grid_size, grid_size // 2 + 1, sensor_radius, arc_angle)\n",
+    "sensor = kSensor(sensor_mask)\n",
+    "\n",
+    "# define the array of temporal points\n",
+    "t_end = 11e-6  # [s]\n",
+    "_ = kgrid.makeTime(medium.sound_speed, t_end=t_end)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Define simulation parameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "input_filename = \"example_sd_focused_2d_input.h5\"\n",
+    "pathname = gettempdir()\n",
+    "input_file_full_path = os.path.join(pathname, input_filename)\n",
+    "simulation_options = SimulationOptions(save_to_disk=True, input_filename=input_filename, data_path=pathname)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Run simulation with first source"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# place a disc-shaped source near the focus of the detector\n",
+    "source = kSource()\n",
+    "source.p0 = 2 * make_disc(grid_size, grid_size / 2, 4)\n",
+    "\n",
+    "# run the simulation\n",
+    "sensor_data1 = kspaceFirstOrder2DC(\n",
+    "    medium=medium,\n",
+    "    kgrid=kgrid,\n",
+    "    source=deepcopy(source),\n",
+    "    sensor=sensor,\n",
+    "    simulation_options=simulation_options,\n",
+    "    execution_options=SimulationExecutionOptions(),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Run simulation with second source"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# place a disc-shaped source horizontally shifted from the focus of the detector\n",
+    "source.p0 = 2 * make_disc(grid_size, grid_size / 2 + [0, 20], 4)\n",
+    "\n",
+    "sensor_data2 = kspaceFirstOrder2DC(\n",
+    "    medium=medium,\n",
+    "    kgrid=kgrid,\n",
+    "    source=deepcopy(source),\n",
+    "    sensor=sensor,\n",
+    "    simulation_options=simulation_options,\n",
+    "    execution_options=SimulationExecutionOptions(),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Visualize recorded data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sensor_output1 = np.sum(sensor_data1['p'], axis=1) / np.sum(sensor.mask)\n",
+    "sensor_output2 = np.sum(sensor_data2['p'], axis=1) / np.sum(sensor.mask)\n",
+    "\n",
+    "t_sc, t_scale, t_prefix, _ = scale_SI(t_end)\n",
+    "t_array = kgrid.t_array.squeeze() * t_scale\n",
+    "\n",
+    "plt.plot(t_array, sensor_output1, 'k')\n",
+    "plt.plot(t_array, sensor_output2, 'r')\n",
+    "\n",
+    "plt.xlabel('Time [' + t_prefix + 's]')\n",
+    "plt.ylabel('Average Pressure Measured Over Detector [au]')\n",
+    "plt.legend([\n",
+    "    f\"Source on focus, sum(output^2) = {round(np.sum(sensor_output1**2) * 100) / 100}\",\n",
+    "    f\"Source off focus, sum(output^2) = {round(np.sum(sensor_output2**2) * 100) / 100}\"\n",
+    "])\n",
+    "\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env_kwave",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}