diff --git a/tools/Jupyter notebooks/example_Ascan_2D.ipynb b/tools/Jupyter notebooks/example_Ascan_2D.ipynb new file mode 100644 index 00000000..996e8e0e --- /dev/null +++ b/tools/Jupyter notebooks/example_Ascan_2D.ipynb @@ -0,0 +1,358 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# A-scan from a metal cylinder (2D)\n", + "\n", + "This example is the GPR modelling equivalent of 'Hello World'! It demonstrates how to simulate a single trace (A-scan) from a metal cylinder buried in a dielectric half-space. The input needed to create the model is:\n", + "\n", + "### my_cylinder_Ascan_2D.in" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overwriting ../../user_models/cylinder_Ascan_2D.in\n" + ] + } + ], + "source": [ + "%%writefile ../../user_models/cylinder_Ascan_2D.in\n", + "#title: A-scan from a metal cylinder buried in a dielectric half-space\n", + "#domain: 0.240 0.210 0.002\n", + "#dx_dy_dz: 0.002 0.002 0.002\n", + "#time_window: 3e-9\n", + "\n", + "#material: 6 0 1 0 half_space\n", + "\n", + "#waveform: ricker 1 1.5e9 my_ricker\n", + "#hertzian_dipole: z 0.100 0.170 0 my_ricker\n", + "#rx: 0.140 0.170 0\n", + "\n", + "#box: 0 0 0 0.240 0.170 0.002 half_space\n", + "#cylinder: 0.120 0.080 0 0.120 0.080 0.002 0.010 pec\n", + "\n", + "#geometry_view: 0 0 0 0.240 0.210 0.002 0.002 0.002 0.002 cylinder_half_space n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Geometry of a metal cylinder buried in a dielectric half-space\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The geometry of the scenario is straightforward - the transparent area around the boundary of the domain represents the PML region. The red cell is the source and the blue cell is the receiver.\n", + "\n", + "For this initial example a detailed description of what each command in the input file does and why each command was used is given. The following steps explain the process of building the input file:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1. Determine the constitutive parameters for the materials\n", + "\n", + "There will be three different materials in the model representing air, the dielectric half-space, and the metal cylinder. Air (free space) already exists as a built-in material in gprMax which can be accessed using the ``free_space`` identifier. The metal cylinder will be modelled as a Perfect Electric Conductor, which again exists as a built-in material in gprMax and can be accessed using the ``pec`` identifier. So the only material which has to be defined is for the dielectric half-space. It is a non-magnetic material, i.e. $\\mu_r=1$ and $\\sigma_*=0$ and with a relative permittivity of six, $\\epsilon_r=6$, and zero conductivity, $\\sigma=0$. The identifier ``half_space`` will be used.\n", + "\n", + " #material: 6 0 1 0 half_space\n", + "\n", + "### 2. Determine the source type and excitation frequency\n", + "\n", + "These should generally be known, often based on the GPR system or scenario being modelled. Low frequencies are used where significant penetration depth is important, whereas high frequencies are used where less penetration and better resolution are required. In this case a theoretical Hertzian dipole source fed with a Ricker waveform with a centre frequency of $f_c=1.5~\\textrm{GHz}$ will be used to simulate the GPR antenna (see the bowtie antenna example model for how to include a model of the actual GPR antenna in the simulation).\n", + "\n", + " #waveform: ricker 1 1.5e9 my_ricker\n", + " #hertzian_dipole: z 0.100 0.170 0 my_ricker\n", + "\n", + "The Ricker waveform is created with the ``#waveform`` command, specifying an amplitude of one, centre frequency of 1.5 GHz and picking an arbitrary identifier of ``my_ricker``. The Hertzian dipole source is created using the ``#hertzian_dipole`` command, specifying a z direction polarisation (perpendicular to the survey direction if a B-scan were being created), location on the surface of the slab, and using the Ricker waveform already created.\n", + "\n", + "### 3. Calculate a spatial resolution and domain size\n", + "\n", + "In the guidance section it was stated that a good *rule-of-thumb* was that the spatial resolution should be one tenth of the smallest wavelength present in the model. To determine the smallest wavelength, the highest frequency and lowest velocity present in the model are required. The highest frequency is not the centre frequency of the Ricker waveform! \n", + "\n", + "You can use the following code to plot builtin waveforms and their FFTs." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "from gprMax.waveforms import Waveform\n", + "from tools.plot_builtin_wave import check_timewindow, mpl_plot\n", + "\n", + "w = Waveform()\n", + "w.type = 'ricker'\n", + "w.amp = 1\n", + "w.freq = 1.5e9\n", + "timewindow = 3e-9\n", + "dt = 1.926e-12\n", + "\n", + "timewindow, iterations = check_timewindow(timewindow, dt)\n", + "plt = mpl_plot(w, timewindow, dt, iterations, fft=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "By examining the spectrum of a Ricker waveform it is evident much higher frequencies are present, i.e. at a level -40dB from the centre frequency, frequencies 2-3 times as high are present. In this case the highest significant frequency present in the model is likely to be around 4 GHz. To calculate the wavelength at 4 GHz in the half-space (which has the lowest velocity) use:\n", + "\n", + "$$\\lambda = \\frac{c}{f \\sqrt{\\epsilon_r}}$$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [], + "source": [ + "from math import sqrt\n", + "\n", + "# Speed of light in vacuum (m/s)\n", + "c = 299792458\n", + "\n", + "# Highest relative permittivity present in model\n", + "er = 6\n", + "\n", + "# Maximum frequency present in model\n", + "fmax = 4e9\n", + "\n", + "# Minimum wavelength\n", + "wmin = c / (fmax * sqrt(er))\n", + "\n", + "# Maximum spatial resolution\n", + "dmin = wmin / 10\n", + "\n", + "print('Minimum wavelength = {:g}m'.format(wmin))\n", + "print('Maximum spatial resolution = {:g}m'.format(dmin))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This would give a minimum spatial resolution of 3 mm. However, the diameter of the cylinder is 20 mm so would be resolved to 7 cells. Therefore a better choice would be 2 mm which resolves the diameter of the rebar to 10 cells.\n", + "\n", + " #dx_dy_dz: 0.002 0.002 0.002\n", + "\n", + "The domain size should be enough to enclose the volume of interest, plus allow 10 cells (if using the default value) for the PML absorbing boundary conditions and approximately another 10 cells of between the PML and any objects of interest. In this case the plan is to take a B-scan of the scenario (in the next example) so the domain should be large enough to do that. Although this is a 2D model one cell must be specified in the infinite direction (in this case the z direction) of the domain.\n", + "\n", + " #domain: 0.240 0.210 0.002\n", + "\n", + "### 4. Choose a time window\n", + "\n", + "It is desired to see the reflection from the cylinder, therefore the time window must be long enough to allow the electromagnetic waves to propagate from the source through the half-space to the cylinder and be reflected back to the receiver." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "d = 0.090\n", + "t = (2 * d) / (c / sqrt(6))\n", + "print('Minimum time window: {:g} s'.format(t))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This is the minimum time required, but the source waveform has a width of 1.2 ns, to allow for the entire source waveform to be reflected back to the receiver an initial time window of 3 ns will be tested.\n", + "\n", + " #time_window: 3e-9\n", + "\n", + "The time step required for the model is automatically calculated using the CFL condition (for this case in 2D).\n", + "\n", + "### 5. Create the objects\n", + "\n", + "Now physical objects can be created for the half-space and the cylinder. First the ``#box`` command will be used to create the half-space and then the ``#cylinder`` command will be given which will overwrite the properties of the half-space with those of the cylinder at the location of the cylinder.\n", + "\n", + " #box: 0 0 0 0.240 0.170 0.002 half_space\n", + " #cylinder: 0.120 0.080 0 0.120 0.080 0.002 0.010 pec" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Run the model\n", + "\n", + "You can now run the model using:\n", + " \n", + " python -m gprMax user_models/cylinder_Ascan_2D.in\n", + "\n", + "**Tip**: You can use the ``--geometry-only`` command line argument to build a model and produce any geometry views but not run the simulation. This option is useful for checking the geometry of the model is correct." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "********************************************************************\n", + "\n", + "Model input file: /Users/cwarren/Documents/Git-projects/gprMax/user_models/cylinder_Ascan_2D.in\n", + "\n", + "Constants/variables available for Python scripting: {'input_directory': '/Users/cwarren/Documents/Git-projects/gprMax/user_models', 'e0': 8.854187817620389e-12, 'z0': 376.73031346177066, 'm0': 1.2566370614359173e-06, 'number_model_runs': 1, 'c': 299792458.0, 'current_model_run': 1}\n", + "\n", + "Model title: A-scan from a metal cylinder buried in a dielectric half-space\n", + "Number of threads: 4\n", + "Spatial discretisation: 0.002 x 0.002 x 0.002m\n", + "Domain size: 0.24 x 0.21 x 0.002m (120 x 105 x 1 = 12600 cells)\n", + "Memory (RAM) usage: ~30.5MiB required, 32.0GiB available\n", + "Time step (at 2D CFL limit): 4.71731e-12 secs\n", + "Time window: 3e-09 secs (637 iterations)\n", + "Waveform my_ricker of type ricker with amplitude 1, frequency 1.5e+09Hz created.\n", + "Hertzian dipole with polarity z at 0.1m, 0.17m, 0m, using waveform my_ricker created.\n", + "Receiver at 0.14m, 0.17m, 0m with output(s) Ex, Ey, Ez, Hx, Hy, Hz, Ix, Iy, Iz created.\n", + "Material half_space with epsr=6, sig=0 S/m; mur=1, sig*=0 S/m created.\n", + "Geometry view from 0m, 0m, 0m, to 0.24m, 0.21m, 0.002m, discretisation 0.002m, 0.002m, 0.002m, filename cylinder_half_space created.\n", + "Box from 0m, 0m, 0m, to 0.24m, 0.17m, 0.002m of material(s) half_space created, dielectric smoothing is on.\n", + "Cylinder with face centres 0.12m, 0.08m, 0m and 0.12m, 0.08m, 0.002m, with radius 0.01m, of material(s) pec created, dielectric smoothing is off.\n", + "\n", + "Input file processed in [HH:MM:SS]: 0:00:00\n", + "\n", + "PML slab (xminus direction) with 10 cells created.\n", + "PML slab (yminus direction) with 10 cells created.\n", + "PML slab (xplus direction) with 10 cells created.\n", + "PML slab (yplus direction) with 10 cells created.\n", + "\n", + "Model built in [HH:MM:SS]: 0:00:00\n", + "\n", + "Materials:\n", + "\n", + "ID\tName\t\tProperties\n", + "--------------------------------------------------\n", + " 0\tpec \tepsr=1, sig=0 S/m; mur=1, sig*=0 S/m; dielectric smoothing not permitted.\n", + " 1\tfree_space \tepsr=1, sig=0 S/m; mur=1, sig*=0 S/m; dielectric smoothing permitted.\n", + " 2\thalf_space \tepsr=6, sig=0 S/m; mur=1, sig*=0 S/m; dielectric smoothing permitted.\n", + " 3\tfree_space+free_space+half_space+half_space\tepsr=3.5, sig=0 S/m; mur=1, sig*=0 S/m; dielectric smoothing permitted.\n", + "\n", + "Geometry file(s) written in [HH:MM:SS]: 0:00:00\n", + "\n", + "Output to file: /Users/cwarren/Documents/Git-projects/gprMax/user_models/cylinder_Ascan_2D.out\n", + "Estimated runtime [HH:MM:SS]: 0:00:03\n", + "Solving for model run 1 of 1...\n", + "|##################################################| 100.0%\n", + "\n", + "Solving took [HH:MM:SS]: 0:00:04\n", + "Peak memory (approx) used: 58.4MiB\n", + "\n", + "Total simulation time [HH:MM:SS]: 0:00:04\n", + "\n", + "Simulation completed.\n", + "********************************************************************\n", + "\n" + ] + } + ], + "source": [ + "import os\n", + "from gprMax.gprMax import api\n", + "\n", + "filename = os.path.join(os.pardir, os.pardir, 'user_models', 'cylinder_Ascan_2D.in')\n", + "api(filename, n=1, geometry_only=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## View the results\n", + "\n", + "### Plot the A-scan\n", + "\n", + "You should have produced an output file ``cylinder_Ascan_2D.out``. You can view the results using:\n", + "\n", + " python -m tools.plot_Ascan user_models/cylinder_Ascan_2D.out\n", + " \n", + "You can use the following code to experiment with plotting different field/current components." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAABKYAAAJcCAYAAADDx6yjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "import os\n", + "from gprMax.receivers import Rx\n", + "from tools.plot_Ascan import mpl_plot\n", + "\n", + "filename = os.path.join(os.pardir, os.pardir, 'user_models', 'cylinder_Ascan_2D.out')\n", + "outputs = Rx.availableoutputs\n", + "#outputs = ['Ez']\n", + "plt = mpl_plot(filename, outputs, fft=False)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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", + "version": "3.5.1" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/tools/Jupyter notebooks/example_Bscan_2D.ipynb b/tools/Jupyter notebooks/example_Bscan_2D.ipynb new file mode 100644 index 00000000..366fd6ba --- /dev/null +++ b/tools/Jupyter notebooks/example_Bscan_2D.ipynb @@ -0,0 +1,181 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# B-scan from a metal cylinder (2D)\n", + "\n", + "This example uses the same geometry as the previous (A-scan) example but this time a B-scan is created. A B-scan is composed of multiple traces (A-scans) recorded as the source and receiver are moved over the target, in this case the metal cylinder. The input needed to create the model is:\n", + "\n", + "### my_cylinder_Bscan_2D.in" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%%writefile ../../user_models/cylinder_Bscan_2D.in\n", + "#title: B-scan from a metal cylinder buried in a dielectric half-space\n", + "#domain: 0.240 0.210 0.002\n", + "#dx_dy_dz: 0.002 0.002 0.002\n", + "#time_window: 3e-9\n", + "\n", + "#material: 6 0 1 0 half_space\n", + "\n", + "#waveform: ricker 1 1.5e9 my_ricker\n", + "#hertzian_dipole: z 0.040 0.170 0 my_ricker\n", + "#rx: 0.080 0.170 0\n", + "#src_steps: 0.002 0 0\n", + "#rx_steps: 0.002 0 0\n", + "\n", + "#box: 0 0 0 0.240 0.170 0.002 half_space\n", + "#cylinder: 0.120 0.080 0 0.120 0.080 0.002 0.010 pec" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The differences between this input file and the one from the A-scan are the x coordinates of the source and receiver, and the commands needed to move the source and receiver. As before, the source and receiver are offset by 40mm from each other as before but they are now shifted to a starting position for the scan. The ``#src_steps`` command is used to move every source in the model by specified steps each time the model is run. Similarly, the ``#rx_steps`` command is used to move every receiver in the model by specified steps each time the model is run. Note, the same functionality can be achieved by using a block of Python code in the input file to move the source and receiver individually (for further details see the Python section of the User Guide)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Run the model\n", + "\n", + "To run the model to create a B-scan you must pass an optional argument to specify the number of times the model should be run. In this case this is the number of A-scans (traces) that will comprise the B-scan. For a B-scan over a distance of 120mm with a step of 2mm that is 60 A-scans. You can now run the model using:\n", + " \n", + " python -m gprMax user_models/cylinder_Bscan_2D.in -n 60" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import os\n", + "from gprMax.gprMax import api\n", + "\n", + "filename = os.path.join(os.pardir, os.pardir, 'user_models', 'cylinder_Bscan_2D.in')\n", + "api(filename, n=60, geometry_only=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## View the results\n", + "\n", + "### Merge A-scans into B-scan\n", + "\n", + "You should have produced 60 output files, one for each A-scan, with names ``my_cylinder_Bscan_2D1.out``, ``my_cylinder_Bscan_2D2.out`` etc... These can be combined into a single file using the command:\n", + "\n", + " python -m tools.outputfiles_merge user_models/cylinder_Bscan_2D" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 60 files to merge\n", + "Do you want to remove the multiple individual output files? [y] or n:\n" + ] + } + ], + "source": [ + "%run -m tools.outputfiles_merge user_models/cylinder_Bscan_2D" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You should see a combined output file ``cylinder_Bscan_2D_merged.out``. The tool will ask you if you want to delete the original single A-scan output files or keep them.\n", + "\n", + "### Plot the B-scan\n", + "\n", + "You can plot the B-scan using:\n", + "\n", + " python -m tools.plot_Bscan user_models/cylinder_Bscan_2D_merged.out Ez" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAABDYAAAJkCAYAAADqRaGKAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhBBCCCGEECIs/z8lUrXo0uRCOwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "import os\n", + "from tools.plot_Bscan import get_output_data, mpl_plot\n", + "\n", + "filename = os.path.join(os.pardir, os.pardir, 'user_models', 'cylinder_Bscan_2D_merged.out')\n", + "rxnumber = 1\n", + "rxcomponent = 'Ez'\n", + "outputdata, dt = get_output_data(filename, rxnumber, rxcomponent)\n", + "plt = mpl_plot(outputdata, dt, rxnumber, rxcomponent)\n", + "\n", + "# Change from the default 'seismic' colormap\n", + "#plt.set_cmap('gray')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The B-scan (of the $E_z$ field component) shows the initial part of the signal (~0.5-1.5 ns) which represents the direct wave from transmitter to receiver. Then comes the refelected wave (~2-3 ns) from the metal cylinder which creates the hyperbolic shape." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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", + "version": "3.5.1" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/tools/Jupyter notebooks/plot_Ascan.ipynb b/tools/Jupyter notebooks/plot_Ascan.ipynb index 18b9e7ba..55987376 100644 --- a/tools/Jupyter notebooks/plot_Ascan.ipynb +++ b/tools/Jupyter notebooks/plot_Ascan.ipynb @@ -45,9 +45,7 @@ ], "source": [ "%matplotlib inline\n", - "\n", "import os\n", - "\n", "from gprMax.receivers import Rx\n", "from tools.plot_Ascan import mpl_plot\n", "\n", diff --git a/tools/Jupyter notebooks/plot_Bscan.ipynb b/tools/Jupyter notebooks/plot_Bscan.ipynb index 03c13eac..368c11a3 100644 --- a/tools/Jupyter notebooks/plot_Bscan.ipynb +++ b/tools/Jupyter notebooks/plot_Bscan.ipynb @@ -40,9 +40,7 @@ ], "source": [ "%matplotlib inline\n", - "\n", "import os\n", - "\n", "from tools.plot_Bscan import get_output_data, mpl_plot\n", "\n", "filename = os.path.join(os.pardir, os.pardir, 'user_models', 'cylinder_Bscan_2D_merged.out')\n", diff --git a/tools/Jupyter notebooks/plot_antenna_params.ipynb b/tools/Jupyter notebooks/plot_antenna_params.ipynb index 5526e2b8..b40a8f80 100644 --- a/tools/Jupyter notebooks/plot_antenna_params.ipynb +++ b/tools/Jupyter notebooks/plot_antenna_params.ipynb @@ -69,7 +69,6 @@ "source": [ "%matplotlib inline\n", "import os\n", - "\n", "from tools.plot_antenna_params import calculate_antenna_params, mpl_plot\n", "\n", "filename = os.path.join(os.pardir, os.pardir, 'user_models', 'antenna_wire_dipole_fs.out')\n",