diff --git a/doc/pages/Cpp-projects.md b/doc/pages/Cpp-projects.md index 78d8e3b75..adcd8d619 100644 --- a/doc/pages/Cpp-projects.md +++ b/doc/pages/Cpp-projects.md @@ -23,7 +23,7 @@ int main(void) { sim.add(new MinimumEnergy(1*EeV)); ref_ptr obs = new Observer(); - obs->add(new ObserverPoint()); + obs->add(new Observer1D()); obs->onDetection(new TextOutput("events.txt", Output::Event1D)); obs->onDetection(new TextOutput()); sim.add(obs); diff --git a/doc/pages/example_notebooks/basics/basics.v4.ipynb b/doc/pages/example_notebooks/basics/basics.v4.ipynb index ae2f187f8..e64fc8ff6 100644 --- a/doc/pages/example_notebooks/basics/basics.v4.ipynb +++ b/doc/pages/example_notebooks/basics/basics.v4.ipynb @@ -2,6 +2,7 @@ "cells": [ { "cell_type": "markdown", + "metadata": {}, "source": [ "## Introduction to Python Steering\n", "The following is a tour of the basic layout of CRPropa 3, showing how to setup and run a 1D simulation of the extragalactic propagation of UHECR protons from a Python shell.\n", @@ -15,12 +16,13 @@ "In general the order of modules doesn't matter much for sufficiently small propagation steps. For good practice, we recommend the order: Propagator --> Interactions -> Break conditions -> Observer / Output.\n", "\n", "**Please note** that all input, output and internal calculations are done using SI-units to enforce expressive statements such as ```E = 1 * EeV``` or ```D = 100 * Mpc```." - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 4, + "metadata": {}, + "outputs": [], "source": [ "from crpropa import *\n", "\n", @@ -35,38 +37,30 @@ "sim.add(ElectronPairProduction(CMB()))\n", "sim.add(NuclearDecay())\n", "sim.add(MinimumEnergy(1 * EeV))" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Propagating a single particle" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "The simulation can now be used to propagate a cosmic ray, which is called candidate. We create a 100 EeV proton and propagate it using the simulation. The propagation stops when the energy drops below the minimum energy requirement that was specified. The possible propagation distances are rather long since we are neglecting cosmology in this example." - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 5, - "source": [ - "cosmicray = Candidate(nucleusId(1, 1), 200 * EeV, Vector3d(100 * Mpc, 0, 0))\n", - "\n", - "sim.run(cosmicray)\n", - "print(cosmicray)\n", - "print('Propagated distance', cosmicray.getTrajectoryLength() / Mpc, 'Mpc')" - ], + "metadata": {}, "outputs": [ { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "CosmicRay at z = 0\n", " source: Particle 1000010010, E = 200 EeV, x = 100 0 0 Mpc, p = -1 0 0\n", @@ -75,32 +69,32 @@ ] } ], - "metadata": {} + "source": [ + "cosmicray = Candidate(nucleusId(1, 1), 200 * EeV, Vector3d(100 * Mpc, 0, 0))\n", + "\n", + "sim.run(cosmicray)\n", + "print(cosmicray)\n", + "print('Propagated distance', cosmicray.getTrajectoryLength() / Mpc, 'Mpc')" + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Defining an observer\n", "\n", "To define an observer within the simulation we create a ```Observer``` object.\n", "The convention of 1D simulations is that cosmic rays, starting from positive coordinates, propagate in the negative direction until the reach the observer at 0. Only the x-coordinate is used in the three-vectors that represent position and momentum." - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 6, - "source": [ - "# add an observer\n", - "obs = Observer()\n", - "obs.add(ObserverPoint()) # observer at x = 0\n", - "sim.add(obs)\n", - "print(obs)" - ], + "metadata": {}, "outputs": [ { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "Observer\n", " ObserverPoint: observer at x = 0\n", @@ -110,22 +104,30 @@ ] } ], - "metadata": {} + "source": [ + "# add an observer\n", + "obs = Observer()\n", + "obs.add(Observer1D()) # observer at x = 0\n", + "sim.add(obs)\n", + "print(obs)" + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Defining the output file \n", "We want to save the propagated cosmic rays to an output file.\n", "Plain text output is provided by the TextOutput module. \n", "For the type of information being stored we can use one of five presets: Event1D, Event3D, Trajectory1D, Trajectory3D and Everything. \n", "We can also fine tune with ```enable(XXXColumn)``` and ```disable(XXXColumn)```" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 7, + "metadata": {}, + "outputs": [], "source": [ "# trajectory output\n", "output1 = TextOutput('trajectories.txt', Output.Trajectory1D)\n", @@ -136,22 +138,22 @@ "#output1.enable(Output.CurrentEnergyColumn) # current energy\n", "#output1.enable(Output.CurrentIdColumn) # current particle type\n", "# ...\n" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "If in the example above ```output1``` is added to the module list, it is called on every propagation step to write out the cosmic ray information. \n", "To save only cosmic rays that reach our observer, we add an output to the observer that we previously defined.\n", "This time we are satisfied with the output type Event1D." - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 8, + "metadata": {}, + "outputs": [], "source": [ "# event output\n", "output2 = TextOutput('events.txt', Output.Event1D)\n", @@ -159,42 +161,33 @@ "\n", "#sim.run(cosmicray)\n", "#output2.close()" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "Similary, the output could be linked to the ```MinimumEnergy``` module to save those cosmic rays that fall below the minimum energy, and so on. \n", "**Note:** If we want to use the CRPropa output file from within the same script that runs the simulation, the output module should be explicitly closed after the simulation run in order to get all events flushed to the file." - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Defining the source\n", "To avoid setting each individual cosmic ray by hand we defince a cosmic ray source.\n", "The source is located at a distance of 100 Mpc and accelerates protons with a power law spectrum and energies between 1 - 200 EeV." - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 9, - "source": [ - "# cosmic ray source\n", - "source = Source()\n", - "source.add(SourcePosition(100 * Mpc))\n", - "source.add(SourceParticleType(nucleusId(1, 1)))\n", - "source.add(SourcePowerLawSpectrum(1 * EeV, 200 * EeV, -1))\n", - "print(source)" - ], + "metadata": {}, "outputs": [ { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "Cosmic ray source\n", " SourcePosition: 100 0 0 Mpc\n", @@ -204,116 +197,114 @@ ] } ], - "metadata": {} + "source": [ + "# cosmic ray source\n", + "source = Source()\n", + "source.add(SourcePosition(100 * Mpc))\n", + "source.add(SourceParticleType(nucleusId(1, 1)))\n", + "source.add(SourcePowerLawSpectrum(1 * EeV, 200 * EeV, -1))\n", + "print(source)" + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Running the simulation\n", "\n", "Finally we run the simulation to inject and propagate 10000 cosmic rays. An optional progress bar can show the progress of the simulation." - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 10, + "metadata": {}, + "outputs": [], "source": [ "sim.setShowProgress(True) # switch on the progress bar\n", "sim.run(source, 10000)" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### (Optional) Plotting\n", "\n", "This is not part of CRPropa, but since we're at it we can plot the energy spectrum of detected particles to observe the GZK suppression.\n", "The plotting is done here using matplotlib, but of course you can use whatever plotting tool you prefer. \n" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 11, - "source": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "\n", - "output2.close() # close output file before loading\n", - "data = np.genfromtxt('events.txt', names=True)\n", - "print('Number of events', len(data))\n", - "\n", - "logE0 = np.log10(data['E0']) + 18\n", - "logE = np.log10(data['E']) + 18\n", - "\n", - "plt.figure(figsize=(10, 7))\n", - "h1 = plt.hist(logE0, bins=25, range=(18, 20.5), histtype='stepfilled', alpha=0.5, label='At source')\n", - "h2 = plt.hist(logE, bins=25, range=(18, 20.5), histtype='stepfilled', alpha=0.5, label='Observed')\n", - "plt.xlabel('log(E/eV)')\n", - "plt.ylabel('N(E)')\n", - "plt.legend(loc = 'upper left', fontsize=20)\n" - ], + "metadata": {}, "outputs": [ { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "Number of events 10000\n" ] }, { - "output_type": "execute_result", "data": { "text/plain": [ "" ] }, + "execution_count": 11, "metadata": {}, - "execution_count": 11 + "output_type": "execute_result" }, { - "output_type": "display_data", "data": { + "image/png": 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" + ] }, "metadata": { "needs_background": "light" - } + }, + "output_type": "display_data" } ], - "metadata": {} + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "output2.close() # close output file before loading\n", + "data = np.genfromtxt('events.txt', names=True)\n", + "print('Number of events', len(data))\n", + "\n", + "logE0 = np.log10(data['E0']) + 18\n", + "logE = np.log10(data['E']) + 18\n", + "\n", + "plt.figure(figsize=(10, 7))\n", + "h1 = plt.hist(logE0, bins=25, range=(18, 20.5), histtype='stepfilled', alpha=0.5, label='At source')\n", + "h2 = plt.hist(logE, bins=25, range=(18, 20.5), histtype='stepfilled', alpha=0.5, label='Observed')\n", + "plt.xlabel('log(E/eV)')\n", + "plt.ylabel('N(E)')\n", + "plt.legend(loc = 'upper left', fontsize=20)\n" + ] } ], "metadata": { + "interpreter": { + "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac" + }, "kernelspec": { - "name": "python3", - "display_name": "Python 3.8.3 64-bit" + "display_name": "Python 3.9.5 64-bit", + "name": "python3" }, "language_info": { "name": "python", - "version": "3.8.3", - "mimetype": "text/x-python", - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "pygments_lexer": "ipython3", - "nbconvert_exporter": "python", - "file_extension": ".py" - }, - "interpreter": { - "hash": "d7f94b8b1e41b02170d45ac71ce2d6b011e7cd56207b4c480f5292088bcfab93" + "version": "" } }, "nbformat": 4, "nbformat_minor": 1 -} - +} \ No newline at end of file diff --git a/doc/pages/example_notebooks/photon_propagation/cascade_1d.ipynb b/doc/pages/example_notebooks/photon_propagation/cascade_1d.ipynb index aaabcbd5f..53df6bc70 100644 --- a/doc/pages/example_notebooks/photon_propagation/cascade_1d.ipynb +++ b/doc/pages/example_notebooks/photon_propagation/cascade_1d.ipynb @@ -2,18 +2,20 @@ "cells": [ { "cell_type": "markdown", + "metadata": {}, "source": [ "# Electromagnetic cascade example\n", "\n", "This is a simple 1D example of gamma-ray propagation over cosmological distances.\n", "Note that only pair production and inverse Compton scattering are relevant for the energy range of this example.\n", "Moreover, the radio background is negligible for the energy range below PeV.\n" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 34, + "metadata": {}, + "outputs": [], "source": [ "from crpropa import *\n", "\n", @@ -46,7 +48,7 @@ "sim.add(MinimumEnergy(10 * GeV))\n", "\n", "obs = Observer()\n", - "obs.add(ObserverPoint())\n", + "obs.add(Observer1D())\n", "obs.add(ObserverElectronVeto()) # we are only interested in photons\n", "output = TextOutput('cascade_1d.txt', Output.Event1D)\n", "output.setEnergyScale(eV)\n", @@ -64,23 +66,36 @@ "sim.run(source, 10000, True)\n", "\n", "output.close()\n" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Plotting\n", "\n", "We will now plot the spectrum of photons arriving at Earth.\n", "Note that whenever thinning is used, the weight column has to be enabled and the weights must be accounted for in the analysis." - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "metadata": {} + ] } ], "metadata": { - "orig_nbformat": 4, - "language_info": { - "name": "python", - "version": "3.8.3", - "mimetype": "text/x-python", - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "pygments_lexer": "ipython3", - "nbconvert_exporter": "python", - "file_extension": ".py" + "interpreter": { + "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac" }, "kernelspec": { - "name": "python3", - "display_name": "Python 3.8.3 64-bit" + "display_name": "Python 3.9.5 64-bit", + "name": "python3" }, - "interpreter": { - "hash": "d7f94b8b1e41b02170d45ac71ce2d6b011e7cd56207b4c480f5292088bcfab93" - } + "language_info": { + "name": "python", + "version": "" + }, + "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 diff --git a/doc/pages/example_notebooks/secondaries/neutrinos.v4.ipynb b/doc/pages/example_notebooks/secondaries/neutrinos.v4.ipynb index 692cc0c16..5d2b570d5 100644 --- a/doc/pages/example_notebooks/secondaries/neutrinos.v4.ipynb +++ b/doc/pages/example_notebooks/secondaries/neutrinos.v4.ipynb @@ -2,6 +2,7 @@ "cells": [ { "cell_type": "markdown", + "metadata": {}, "source": [ "## Example with secondary neutrinos\n", "\n", @@ -9,12 +10,15 @@ "Hadrons and Neutrinos are stored separately using two observers.\n", "\n", "**Note: the simulation might take a minute**" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 5, + "metadata": { + "collapsed": true + }, + "outputs": [], "source": [ "from crpropa import *\n", "\n", @@ -40,7 +44,7 @@ "\n", "# observer for hadrons\n", "obs1 = Observer()\n", - "obs1.add(ObserverPoint())\n", + "obs1.add(Observer1D())\n", "obs1.add(ObserverNeutrinoVeto()) # we don't want neutrinos here\n", "output1 = TextOutput('out-nucleons.txt', Output.Event1D)\n", "output1.setEnergyScale(eV)\n", @@ -48,7 +52,7 @@ "m.add(obs1)\n", "# observer for neutrinos\n", "obs2 = Observer()\n", - "obs2.add(ObserverPoint())\n", + "obs2.add(Observer1D())\n", "obs2.add(ObserverNucleusVeto()) # we don't want hadrons here\n", "output2 = TextOutput('out-neutrinos.txt', Output.Event1D)\n", "output2.setEnergyScale(eV)\n", @@ -68,22 +72,33 @@ "\n", "output1.close()\n", "output2.close()" - ], - "outputs": [], - "metadata": { - "collapsed": true - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Plotting the neutrino energy distribution" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" - ], - "image/png": 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" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "metadata": {} + ] } ], "metadata": { + "interpreter": { + "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac" + }, "kernelspec": { - "name": "python3", - "display_name": "Python 3.8.3 64-bit" + "display_name": "Python 3.9.5 64-bit", + "name": "python3" }, "language_info": { "name": "python", - "version": "3.8.3", - "mimetype": "text/x-python", - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "pygments_lexer": "ipython3", - "nbconvert_exporter": "python", - "file_extension": ".py" - }, - "interpreter": { - "hash": "d7f94b8b1e41b02170d45ac71ce2d6b011e7cd56207b4c480f5292088bcfab93" + "version": "" } }, "nbformat": 4, "nbformat_minor": 1 -} +} \ No newline at end of file diff --git a/doc/pages/example_notebooks/secondaries/photons.v4.ipynb b/doc/pages/example_notebooks/secondaries/photons.v4.ipynb index e49ea5812..2ab01c312 100644 --- a/doc/pages/example_notebooks/secondaries/photons.v4.ipynb +++ b/doc/pages/example_notebooks/secondaries/photons.v4.ipynb @@ -2,19 +2,26 @@ "cells": [ { "cell_type": "markdown", + "metadata": {}, "source": [ "# Photon Propagation\n" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 1, + "metadata": { + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [], "source": [ "from crpropa import *\n", "\n", "obs = Observer()\n", - "obs.add(ObserverPoint())\n", + "obs.add(Observer1D())\n", "obs.add(ObserverInactiveVeto())\n", "t = TextOutput(\"photon_electron_output.txt\", Output.Event1D)\n", "obs.onDetection(t)\n", @@ -45,25 +52,37 @@ "sim.add(obs)\n", "sim.run(source,1000,True)\n", "t.close()" - ], - "outputs": [], - "metadata": { - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### (Optional) plotting of the results" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 2, + "metadata": { + "jupyter": { + "outputs_hidden": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
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" - ], - "image/png": 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" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "metadata": { - "jupyter": { - "outputs_hidden": false - } - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "# Photon Propagation outside of CRPropa with EleCa and DINT\n", "\n", @@ -133,21 +134,22 @@ "\n", "Note that the differing results in EleCa (and correspondingly the high energy part of the combined option) are due to an incorrect sampling of the background photon energies in EleCa. The EleCa support will be removed in the near future.\n", "\n" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Photons from Proton Propagation\n", "\n", "The generation of photons has to be enabled for the individual energy-loss processes in the module chain. Also, separate photon output can be added:" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 3, + "metadata": {}, + "outputs": [], "source": [ "from crpropa import *\n", "\n", @@ -164,7 +166,7 @@ "\n", "# observer\n", "obs1 = Observer() # proton output\n", - "obs1.add( ObserverPoint() )\n", + "obs1.add( Observer1D() )\n", "obs1.add( ObserverPhotonVeto() ) # we don't want photons here\n", "obs1.onDetection( TextOutput('proton_output.txt', Output.Event1D) )\n", "m.add(obs1)\n", @@ -185,96 +187,113 @@ "\n", "# run simulation\n", "m.run(source, 10000, True)" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "The file 'photon_output.txt' will contain approximately 300 photons and can be processed as the photon example below." - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Propagation with EleCa\n" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 4, + "metadata": { + "jupyter": { + "outputs_hidden": true + } + }, + "outputs": [], "source": [ "import crpropa\n", "\n", "# Signature: ElecaPropagation(inputfile, outputfile, showProgress=True, lowerEnergyThreshold=5*EeV, magneticFieldStrength=1*nG, background=\"ALL\")\n", "crpropa.ElecaPropagation(\"photon_output.txt\", \"photons_eleca.dat\", True, 0.1*crpropa.EeV, 0.1*crpropa.nG)" - ], - "outputs": [], - "metadata": { - "jupyter": { - "outputs_hidden": true - } - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Propagation with DINT\n" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 5, + "metadata": { + "jupyter": { + "outputs_hidden": true + } + }, + "outputs": [], "source": [ "import crpropa\n", "\n", "# Signature: DintPropagation(inputfile, outputfile, IRFlag=4, RadioFlag=4, magneticFieldStrength=1*nG, aCutcascade_Magfield=0)\n", "crpropa.DintPropagation(\"photon_output.txt\", \"spectrum_dint.dat\", 4, 4, 0.1*crpropa.nG)" - ], - "outputs": [], - "metadata": { - "jupyter": { - "outputs_hidden": true - } - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### Combined Propagation" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 6, + "metadata": { + "jupyter": { + "outputs_hidden": true + } + }, + "outputs": [], "source": [ "import crpropa\n", "\n", "# Signature: DintElecaPropagation(inputfile, outputfile, showProgress=True, crossOverEnergy=0.5*EeV, magneticFieldStrength=1*nG, aCutcascade_Magfield=0)\n", "crpropa.DintElecaPropagation(\"photon_output.txt\", \"spectrum_dint_eleca.dat\", True, 0.5*crpropa.EeV, 0.1*crpropa.nG)" - ], - "outputs": [], - "metadata": { - "jupyter": { - "outputs_hidden": true - } - } + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### (Optional) Plotting of Results" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 7, + "metadata": { + "jupyter": { + "outputs_hidden": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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s5+w+Y4H5jlwlGhFBizOjUreJZsmYDpaM6dh3K++e1Y2IiJRNs85ERCRWdVvRiEi6FK6XKaT1Msmr60ST6TEXYH4me45E/5uFi0i1ya+X6ZlUtF4meXWbaIL+4uXP+VaiEalN+fUyUl3qNtF0dPSeXJYZkUwsIiJppskAIiISKyUaERGJVaoTjZnNMbPO7du3Jx2KiEjdSnWicffF7t7R2NiYdCgiInUr1YlGRESSp0QjIiKxUqIREZFYKdGIiEislGhERCRWdbszgIjUudwunM2Z3N5TbQ3agTMmqmhEpD7ld+EspB04Y6GKRkRqTtCRAAMqRlpa2MB3AXSSZoxU0YhIzVExUltU0YhITUrLkQA9z8WC9J2NpUQjIpKQYhVY2s7GUqIREUlI0LlYkL6zsTRGIyIisUp1otExASIiyUt1otExASIiyUt1ohERkeRpMoCIVK2ghZmgnWJqjSoaEalaQQszQYsza40qGhGpamlZmFnPVNGIiEislGhERCRWSjQiIhKrUGM0ZnZgiLe97u7/U2Y8IlKnItv6X6pO2MkAz+e+rI/3DAbGlR1Rwpq7A7ZShewUl6BNiUQkEvkZZoWJpaTZZcXmQoP+/SYsbKJZ5+59ngpkZo9FEE+iljZl/0b3+g9Ufn6l/qKKxKqsGWZBmQr077cKhE00MyN6T1VbMqaDJWM6ev9FD6pwRKT6BGUq/ftNXKjJAO6+s9hrZnZwf+8REZH6FcWssx9GcA8REUmpshONu38wikBERCSdStqCxsz+b9B1d/9qNOGIiEjalLrX2csFj4cBs4F10YUjImmnHZnrT0mJxt2/XfjczL4F/DLSiEQk1YrNQtaOzOlV7u7N+wNjowhEROqHdmSuL6WO0TwBeO7pYGAUoPEZEREpqtSKZnbB493AZnffHWE8IiKSMqWO0fyp5zUzO9jd/xJdSMnKBGx1Nj8DTaNhTCIRiYjUtihO2PwhkIq1NMUGIru7s78q0YiEp9llkld2ool7waaZTQC+BDS6+2m5a5OAK4FtwG/cfVEUn9XREbzvXmZEFHcXqS+aXSZ5UVQ0JTOzW8iO92xx98kF108BriM70eBmd7/G3TcC55lZYTJ5P3CDu//OzO4FIkk0IhItzS4TGMAWNGb2VjObYWbvyX8N4HMXAKf0uO9g4CaySWQScFaucgnyU+BMM/smMHIAny8iIhVS6vTmTwKXkl07kwGOB34PvLeU+7j7g2Y2vsflGcCGXAWDmd0BnAqsDfj+LcCnc8np7lI+W0REKqvUiuZS4FjgT+5+AjANiOr45kOA5wqedwGHmNlIM/s+MM3MLgcws/Fm1gn8BPhm0M3MrMPMVpnZqq1bt0YUooiIlKrUMZqd7r7TzDCzoe6+3swmxhJZjrtvAy7ocW0T0Odxee7eCXQCtLa2el/vFRGR+JSaaLrMbARwD/BrM/sr0GttzQD9GXh7wfOxuWsiIlLDSl2w+eHcwyvNbBnQCPwiolhWAoeb2aFkE8yZgCZBiojUuFCJxsz+4O7TC6+5+wP9vaeP+90OtAEHmVkXcIW7/9DMLia7G/Rg4BZ3fyrM/fr4nDnAnObm5nJuIyL9CFqcqYWZkhe2onmnma3p43UjW92E4u5nFbl+H3Bf2PuE+JzFwOLW1tbzo7qniPQWtDhTCzMlL2yiOTLEe/aUE4iI1DYtzpRiQiWaoM00RUREwih5Z4BaYmZzzKxz+/btSYciIlK3Up1o3H2xu3c0NoYePhIRkYilOtGIiEjyEtm9WURqk86YkYFQRSMioeWnMfekqczSl7ALNo8qd/GkiKSDpjFLqcJWND/NP8gdFUDB8/0jjShCmnUmIpK8sInGCh5f1OO130UUS+Q060xEJHlhE03hNvvW4zWN84iISFFhZ50dbGZzgcfpnWh01ouIiBQVNtFcCRwDnAOMNbO1wDpgPXBQPKGJiEgahE00XcASd38ewMzGAlOAo4EHY4pNRBKkrf8lKmHHVz4M3Gtmz5nZr4HLgJFkt/Q/O67gyqVZZyIDF7RmRutlZCDC7t58PoCZ/TNwCLAROAHoBF4ie+xy1dF5NCLl0ZoZiUKpW9Cc4e5T80/M7N+AL0QbUnVq7s5AW1vvF9rboaOj4vGIiNSKUqcm7zCzY/JP3H01cES0IVWfpU3tbGgI6JjOZII3fhIRkb1KrWjOA+42s5XAarITAnZFHlWVWTKmgyVjOnp3IQRVOCIiso+SKhp3fxqYDtwPjCY7xfkDMcQlIiIpEXZTzZnAw571GnBn7ktEapy2/pe4ha1o/glYbWZ3mNlcMzs4zqCiounNIv3T1v8St7DTmy8EMLMjgfcDC8ysEVgG/AJY4e57YotygDS9WSQcTWOWOIWqaMzsHQDuvt7dv+vupwDvBR4CPgY8El+IIiJSy8LOOrvfzJrI7m22Bngi9+tD7n5fXMGJiEjtC9t1NsnMhgKTeGOPs1OBo83sVXc/NMYYRSQJxWYJaJGylCj09GZ3f9XdHwN+Trar7C/ATrJHB4hI2gTNEtAiZRmAsNObJwIfBGYDo4BfA7cCHbnpziJSA0rekbnnLAEtUpYBCDtGsw54DLgW+A93fzW+kEQkLvkipTCxaBqzxC1sorkQmAx8GrjRzLaRnRDwBPCEu98TU3xlMbM5wJzm5uakQxGpGprKLJUWaozG3f/d3T/j7rPcvQk4CfgR8Brw0TgDLIe7L3b3jsbGxqRDERGpW2HHaD4AZPInbLp7F9lTN++PMTYRqQTtQSMxC9t19mHgq2Y2muxamseBTO7XtdW4K0DUMgHH0czPQNNoGJNIRCIRCRq4AQ3eSGRSfcJmVIr9W+vuzv6qRCM1TwM3EiOdsBlCR0fw+rTMiMrHIiJSa0pNNDvM7JjcyZq4+2ozS/0JmyK1RsMuUk10wqZICmnYRapJSYnG3Z82s+nAh8gmmXXAP8cRmIiUR8MuUi36TTRmdhJwOnCTu2eAue7eiU7YFBGREMJUNOeS3RngX8zsQEA9vCIiElqYnQH+5u7/4+6fB04Gjo05JhERSZEwieb/5R+4+zzgJ/GFEy0zm2Nmndu3b086FBGRutVv15m7/4eZHeXuT+We3xB/WNFw98XA4tbW1vOTjkUkDprGLLUg7MFnP80/MLNPFr5gZvtHGpGIhBZ0NhloGrNUl7DTm63g8UXAzQXPfwccE1lEIlKSkqYxl3zymUj5wlY0XvDYerwW+jhoEUlYUAmk8kdiFraiOdjM5pLdrblnovHebxeRqqWVnFJhYRPNlWS7x84BxprZWrK7AqwHDoonNBERSYOwxwR0Fj43s7Fkt6A5GngwhrhERCQlSt1UE9AJmyJJ0Di+1CoN5IvUCI3jS60aUEUjIsnQOL7UIiWaMjV3Z6Ctbd+L7e3BR3KKiNQhJZoyLG3K9lns00We79tQohERAZRoyrJkTAdLxnTs25XRs7oREalzmgwgIiKxUqIREZFYpbrrzMzmAHOam5uTDkUkNG39L2mT6orG3Re7e0djY2PSoYiEpq3/JW1SXdGI1Kqy18uoLJIqkuqKRqRuqSySKqKKRiSttI2AVAlVNCIiEislGhERiZW6zkQSpK3/pR6oohFJkLb+l3qgikYkYXGP2T/f+Tybb9vc6/ro9tGM6RgT3weL5KiiEUm5zbdtpjvTvc+17kx3YPIRiYMqGpE60NDSwLTl0/Y+f6ztsQSjkXqjRFOmTI9zz+ZnoGk0qENCRCRLiaYMQQO23bkeCiUaEZEsJZoydHT0PkgzMyKZWKROaU8zqQFKNCIVEFs+yM+P7nkTzZGWKqJEI1IBseYD7WkmVU6JRqRClA+kXmkdjYiIxEqJRkREYqWuM5EkFZsl0N7ee0qjSI1SRSOSpKBdNTOZ4OQjUqNU0YhEaEDTmHvOEijcakIkBao+0ZjZBOBLQKO7n5a7Ng64HngJeNrdr0kwRJG9IpvG3HNvo77ep4WZUuUSSTRmdgswG9ji7pMLrp8CXAcMBm5292vcfSNwnpktKrjFFGCRu//MzBZWMvYwmruL/JBQv3tdKHsacykZSQszpQYkVdEsAG4EfpK/YGaDgZuAk4AuYKWZ3evuawO+/2FgkZmdC/w0/nDDW9qU/Uff6/+Y+X54JZr6VEqfWtDeRiI1LJFE4+4Pmtn4HpdnABtyFQxmdgdwKhCUaM4BrsjdZxHwoxjDLcmSMR0sGdPR+3+06nevb9oqRupYNY3RHAI8V/C8CzjOzEYCVwPTzOxyd/868AvgSjNrBzYF3czMOoAOgHHjxsUZt0g42hpA6lQ1JZpA7r4NuKDHtSeB0/r5vk6gE6C1tdVjC1DSr1i3V4D5+ZnKbT1e0KC91LFqSjR/Bt5e8Hxs7ppIsop0ez3/AmzpcRpydzc0NATcQ11kUseqKdGsBA43s0PJJpgzAf3LlOoQ0O3V3gaZzb0LlfZ2aNFYvsheSU1vvp1s58JBZtZFdmD/h2Z2MfBLstObb3H3p8r8nDnAnObm5nJDFgmkYReR/iU16+ysItfvA+6L8HMWA4tbW1vPj+qeIiJSmmrqOhNJXtDAvwbyRcqiTTVFCgVtcqmBfJGyqKIR6UkDLyKRSnWi0WQAEalV3d37bigyPwNNo2FMYhENXKoTjSYDSBQGtPW/SBmaRve+1t2d/VWJRqRWlJA9tE2ZVNqYt2W/CntwMyMSC6dsSjRSn0rMHhq2ERk4JRqpX8oeIhWR6kST1GSAoMMRa3kgT0SkHKlONElMBijWZ1/LA3k1T4swRRKV6kSThGKHI9byQF7NCxqP0Ui+SMUo0Uh9CDkeo+JHJHragkakgHagEYmeKpoKau4OmCXQ3h7c1yali2hlpSajiUQr1RWNmc0xs87t27cnHQpLm9rZ0NDjh10mE/qIYAkhqBwBlSQiCUt1RVNNW9AsGdPBkjEd+/5PuWd1I+VTOSJSdVJd0YiISPKUaEREJFap7joTKUY7MotUjioaqUuaNyBSOapopPZoGrNITUl1RVNN05slQipHRGpKqiuaapreLBFTOSJSM1Jd0YiISPKUaEREJFap7jqTFIhgO2XtyCySLFU0Ut0i2E5ZOzKLJEsVjVS/CAb+NXdAJDmqaEREJFaqaJKWCTijBnROjYikRqoTjZnNAeY0NzcnHUqwYoME+QEFJRoRSYFUJ5pqW7DZu3jpoL29o3c+qcdzarTLpUhqpTrRVJOg4kWFS4H81LCeSaWE6WHKVSLVSYmmQjo6eieUeixc+lTm1LAIcpWIxECJRlJF05hFqo+mN4uISKyUaEREJFbqOpPK0+ZjInVFFY1UnjYfE6krqmgkGWWM2msas0htUUUjNUcnOYvUllRXNFW/BY0MmKYxi9SOVCeaatuCpiRBm21qo00RqUGpTjQ1Ky371WgwRURQoqlOadmvRnvCiAhKNBI3DaaI1D0lGqlqWtspUvuUaBKmAzb7FtT7pp43kdqiRJOgVB2wGWPpod43kdqmRJOgoDF/qM1xf5UeIlKMEk0tqfZ+NpUeIhJAiaZWpKqfTUTqiRJNrUhVP1tvWtspkl5KNFKamDKC1naKpJcSjZQmxoygIR6RdFKikdIpI4hICZRo0qDc2WjFusOKfZYGTUSkBKk++MzM5phZ5/bt25MOJT7t7cE/+DOZ8Mmj2EliQTRoIiIlSnVFU9Pn0YQV1Wy0CnaHaf8ykfqS6kRT94p1qQW9r4I/5bWJgEh9UaKpUmUfsFnKT+0EfsprPoFI/VCiqUKRHLBZrEtNRKTClGiqUFoO2BQRASUaiZG2lRERSPn0ZklWsVnTGvgXqS+qaCRWGvQXEVU0IiISKyUaERGJlbrOakg1H7Cp1f4iUowqmhoRxZZmcQoa+Negv4iAKpqaUQsHbGrgX0SCqKIREZFYqaKRkmgRpoiUShWNlESLMEWkVKpoUqDSs9E0FiMipVCiqXHFqoiSd3vuQV1kIhIVJZoaF9dstKDDyUBdZCJSOiWaFAt7eFpfiy3VRSYi5VKiSamgquOBB7JfPZPKAw9kf501641rqlxEJCpKNCkV1KVWbNxl1qzq2MZGRNKp6hONmU0AvgQ0uvtpuWv/AHycbPyT3P1/JRhizdDpziKShETW0ZjZLWa2xcye7HH9FDP7o5ltMOQJtiAAAAfESURBVLN5AO6+0d3PK3yfu//O3S8AlgA/rlzkIiJSqqQWbC4ATim8YGaDgZuA9wOTgLPMbFI/92kHqmBLSRERKSaRROPuDwIv9bg8A9iQq2BeA+4ATi12DzMbB2x397/FF6mIiJSrmsZoDgGeK3jeBRxnZiOBq4FpZna5u3899/p5wI+K3czMOoD8iMSrPbvpBqAR2F7m+4Je6+9amMcHAS+GiK0v5bYv7PW+nsfVvrj+7IKul9q+yv3ZWcD7rM97FL9mFvSeZNvXO7Z9XzN74x5WeN/pAdcK7xcYR//tC46j4PXA+/Z1j77bF8/PlonBwZfI3RP5AsYDTxY8Pw24ueD5J4AbI/qsVRHco7Pc9wW91t+1kI8Tb1/Y6309j6t9cf3ZRdG+avizK/ZamGtpbl+YtqalfXH+bHH3qtpU88/A2wuej81dqxaLI3hf0Gv9XQvzOArlti/s9b6ex9W+uP7sgq6nqX1hrqW5fWHbWq5qaF+cP1uwXNaqODMbDyxx98m55/sBTwMnkk0wK4F2d38qgs9a5e6t5d6nWql9tSvNbQO1r9ZF1b6kpjffDvwemGhmXWZ2nrvvBi4GfgmsA+6MIsnkdEZ0n2ql9tWuNLcN1L5aF0n7EqtoRESkPlTTGI2IiKSQEo2IiMRKiUZERGJVN4nGzCaY2Q/NbFGP68PNbJWZzU4qtigEtc/M2szsd2b2fTNrSzC8shVp3yAzu9rMbjCzs5OMr1xF2vcPuT+7m83sP5OMr1xF2jfOzO7J7X04L8n4ylGkbZPM7E4z+56ZnZZkfOUysw+Z2Q/MbKGZnZy7NtzMfpy7/vH+7lHTiabczTlz/g9wZyXiLVUE7XOgGxhGdqeFqhJB+04lu95qFylsn1f55rER/PlNARa5+7nAtAqFHUoEbXs/cIO7Xwj8U4XCDq3E9t3j7ucDFwBn5N76EbJ/ducD/9jvB0ax6jOpL+A9ZPePKNxhYDDwDDABeBPwONmjBPKvLyp4fBJwJjAXmJ10e2Jo36Dcr6OBW5NuTwztmwd8quf1avkqt30F1+4E3pJ0e2L48xsJLAN+C5yTdHsiblsT2U2CvwmsSLo9EbXv28D03OPLgZbc49v6+7yarmi8/M0524Djye4Cfb6ZVdXvR7ntc/fXcw//CgyNLdABiuDPr4ts2wD2xBPlwEXQvqrePDaC9p0DXOHu7wU+GF+kpYvg394Wd/802f8MlbvXW+RKaZ9lXQvc7+5/yL23i2xvAoToGauqH6wRCdqc8xAzG2lm3ye3OSeAu3/J3S8je9TADwp+MFez0O0zs4+Y2b8DPwVurHyoAxK6fcDdwP82sxuABysc50CV0j7oZ/PYKlRK+34BXJK7vqmyYQ5IKf/2xptZJ/ATslVNLQhsH/AZ4H3AaWZ2Qe61u4GPmtn3CLFlTTXt3hwrd99Gto8x6LUFlY0mekHtc/e7yf6FqHlF2vcK2R/ENa/Y3093vyKBcCJX5M/vSbKb6da0Im3bxBu7x9c0d78euL7HtZfJVqShpLGiqfbNOcul9tU2ta92pbltEGP70phoVgKHm9mhZvYmsoP99yYcU5TUvtqm9tWuNLcN4mxf0rMfypw5cTvwAm9Mbz0vd/0DZHeCfgb4UtJxqn1qn9pXW19pblsS7dOmmiIiEqs0dp2JiEgVUaIREZFYKdGIiEislGhERCRWSjQiIhIrJRoREYmVEo1IATPbY2aZgq+qOCelIK4xfbznCjP7eo9rLWa2Lvd4mZl1m1lr3PGKFNI6GpECZtbt7g0R33M/d99d5j36jcvMjgB+4e4TCq5dA7zi7l/NPV8OfN7dV5UTj0gpVNGIhGBmm8zsK2b2BzN7wsyOzF0fnjtE6lEze8zMTs1dn2tm95rZb4HfmNn+lj1xca2Z/dzMHjGzVjM718zmF3zO+Wb23RDxnGxmv8/Fc5eZNbj708Bfzey4greeTnYVuEhilGhE9vXmHl1nZxS89qK7Twe+B3w+d+1LwG/dfQZwAvBNMxuee206cJq7zwIuAv7q7pOALwPH5N5zJzDHzIbknp8D3NJXgGZ2EPAvwPty8awCPpt7+Xaye1RhZscDL7n7f5X+2yASnbo5JkAkpL+7e0uR1/JHLqwme5QtwMnAP5pZPvEMA8blHv/a3fOHS70buA6y2+Ob2Zrc4+5c1TM7N5YyxN2f6CfG44FJwAozg+xpiL/PvbYQ+E8z+xzZhKNqRhKnRCMS3qu5X/fwxr8dAz7q7n8sfGOu++rlkPe9GfhnYD3hDjkzsknsrJ4vuPtzZvYsMAv4KDAzZAwisVHXmUh5fgl8xnKlhZlNK/K+FWTHSzCzScCU/Avu/gjZc0DaCVeBPAy8y8yac/cbnpsIkHc78F1go7t3ldYckegp0Yjsq+cYzTX9vP9fgSHAGjN7Kvc8yL8Bo8xsLXAV8BSwveD1O4EV7v7X/gJ0963AXOD2XBfc74EjC95yF3AU6jaTKqHpzSIVYGaDyY6/7DSzw4ClwER3fy33+hLgu+7+myLfH8m0a01vliSoohGpjP2Bh8zsceDnwEXu/pqZjTCzp8lOQghMMjk7+luw2R8zWwZMIHvYlUjFqKIREZFYqaIREZFYKdGIiEislGhERCRWSjQiIhIrJRoREYmVEo2IiMTq/wMOzyt/JaEwQAAAAABJRU5ErkJggg==", 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" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "metadata": { - "jupyter": { - "outputs_hidden": false - } - } + ] } ], "metadata": { + "interpreter": { + "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac" + }, "kernelspec": { - "display_name": "Python 3", - "language": "python", + "display_name": "Python 3.9.5 64-bit", "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": "3.6.9" + "version": "" } }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/doc/pages/example_notebooks/secondaries/secondary_photons.ipynb b/doc/pages/example_notebooks/secondaries/secondary_photons.ipynb index 5e2d24d93..034e84ae2 100644 --- a/doc/pages/example_notebooks/secondaries/secondary_photons.ipynb +++ b/doc/pages/example_notebooks/secondaries/secondary_photons.ipynb @@ -2,16 +2,17 @@ "cells": [ { "cell_type": "markdown", - "source": [ - "# Photon Propagation" - ], "metadata": { "deletable": true, "editable": true - } + }, + "source": [ + "# Photon Propagation" + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "This examples shows how to propagate electromagnetic cascades at ultra-high energies.\n", "Note that the `EM*` modules act on photons and electrons only, such that these modules can be used concomitantly with the modules to propagate cosmic-ray nuclei to treat secondary photons produced by cosmic rays.\n", @@ -19,19 +20,25 @@ "These simulations can be very time consuming. This particular example shown below can take several minutes to run.\n", "\n", "Here we simulate the propagation of UHE protons. We track the electromagnetic cascades initiated by the photons and electrons produced via photopion production. We ignore the electrons produce via Bether-Heitler pair production to make it possible to run the example within a reasonable time." - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Setting up the simulation" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": 18, + "metadata": { + "collapsed": true, + "deletable": true, + "editable": true, + "scrolled": true + }, + "outputs": [], "source": [ "from crpropa import *\n", "\n", @@ -63,7 +70,7 @@ "\n", "# observer\n", "obs1 = Observer() # proton output\n", - "obs1.add(ObserverPoint())\n", + "obs1.add(Observer1D())\n", "obs1.add(ObserverPhotonVeto()) # we don't want photons here\n", "obs1.add(ObserverElectronVeto()) # we don't want electrons\n", "out1 = TextOutput(filename1, Output.Event1D)\n", @@ -72,7 +79,7 @@ "obs1.onDetection(out1)\n", "\n", "obs2 = Observer() # photon output\n", - "obs2.add(ObserverPoint())\n", + "obs2.add(Observer1D())\n", "# obs2.add(ObserverDetectAll()) # stores the photons at creation without propagating them\n", "obs2.add(ObserverElectronVeto())\n", "obs2.add(ObserverNucleusVeto()) # we don't want nuclei here\n", @@ -86,7 +93,7 @@ "obs2.onDetection(out2)\n", "\n", "obs3 = Observer() # electron output\n", - "obs3.add(ObserverPoint())\n", + "obs3.add(Observer1D())\n", "# obs3.add(ObserverDetectAll()) # stores the photons at creation without propagating them\n", "obs3.add(ObserverPhotonVeto()) # we don't want photons\n", "obs3.add(ObserverNucleusVeto()) # we don't want nuclei here\n", @@ -123,28 +130,41 @@ "out1.close()\n", "out2.close()\n", "out3.close()" - ], - "outputs": [], - "metadata": { - "collapsed": true, - "deletable": true, - "editable": true, - "scrolled": true - } + ] }, { "cell_type": "markdown", - "source": [ - "## Plotting results (optional)" - ], "metadata": { "deletable": true, "editable": true - } + }, + "source": [ + "## Plotting results (optional)" + ] }, { "cell_type": "code", "execution_count": 21, + "metadata": { + "collapsed": false, + "deletable": true, + "editable": true, + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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", 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" - ], - "image/png": 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" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "scrolled": true - } + ] }, { "cell_type": "code", "execution_count": null, - "source": [], + "metadata": {}, "outputs": [], - "metadata": {} + "source": [] } ], "metadata": { + "interpreter": { + "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac" + }, "kernelspec": { - "name": "python3", - "display_name": "Python 3.8.3 64-bit" + "display_name": "Python 3.9.5 64-bit", + "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": "3.8.3" - }, - "interpreter": { - "hash": "d7f94b8b1e41b02170d45ac71ce2d6b011e7cd56207b4c480f5292088bcfab93" + "version": "" } }, "nbformat": 4, diff --git a/doc/pages/example_notebooks/sim1D/sim1D.v4.ipynb b/doc/pages/example_notebooks/sim1D/sim1D.v4.ipynb index 7534b4c93..412741de0 100644 --- a/doc/pages/example_notebooks/sim1D/sim1D.v4.ipynb +++ b/doc/pages/example_notebooks/sim1D/sim1D.v4.ipynb @@ -48,7 +48,7 @@ "\n", "# observer and output\n", "obs = Observer()\n", - "obs.add( ObserverPoint() )\n", + "obs.add( Observer1D() )\n", "output = TextOutput('events.txt', Output.Event1D)\n", "obs.onDetection( output )\n", "sim.add( obs )\n", @@ -87,7 +87,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", 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" ] @@ -151,22 +151,16 @@ } ], "metadata": { + "interpreter": { + "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac" + }, "kernelspec": { - "display_name": "Python 3", - "language": "python", + "display_name": "Python 3.9.5 64-bit", "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": "3.6.9" + "version": "" }, "widgets": { "application/vnd.jupyter.widget-state+json": { @@ -178,4 +172,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/test/testBreakCondition.cpp b/test/testBreakCondition.cpp index 499d083e0..468a08387 100644 --- a/test/testBreakCondition.cpp +++ b/test/testBreakCondition.cpp @@ -205,7 +205,7 @@ TEST(ObserverFeature, LargeSphere) { TEST(ObserverFeature, Point) { Observer obs; - obs.add(new ObserverPoint()); + obs.add(new Observer1D()); Candidate c; c.setNextStep(10); diff --git a/test/testOutput.cpp b/test/testOutput.cpp index 3c56c2d00..da104d697 100644 --- a/test/testOutput.cpp +++ b/test/testOutput.cpp @@ -229,7 +229,7 @@ TEST(ParticleCollector, getTrajectory) { sim->add(new SimplePropagation(1, 1)); ref_ptr obs = new Observer(); - obs->add(new ObserverPoint()); + obs->add(new Observer1D()); obs->onDetection(output); sim->add(obs); diff --git a/test/testSimulationExecution.py b/test/testSimulationExecution.py index 4b4d37723..1db919033 100644 --- a/test/testSimulationExecution.py +++ b/test/testSimulationExecution.py @@ -42,7 +42,7 @@ def runTest(self): # observer obs = crp.Observer() - obs.add(crp.ObserverPoint()) + obs.add(crp.Observer1D()) sim.add(obs) # output