{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"\n",
"\n",
"**This is a fixed-text formatted version of a Jupyter notebook.**\n",
"\n",
" You can contribute with your own notebooks in this\n",
" [GitHub repository](https://github.com/gammapy/gammapy-extra/tree/master/notebooks).\n",
"\n",
"**Source files:**\n",
"[cta_simulation.ipynb](../_static/notebooks/cta_simulation.ipynb) |\n",
"[cta_simulation.py](../_static/notebooks/cta_simulation.py)\n",
"
\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# CTA simulation tools\n",
"\n",
"## Introduction\n",
"\n",
"In this tutorial we will simulate the expected counts of a Fermi/LAT source in the CTA energy range.\n",
"\n",
"We will go through the following topics: \n",
"\n",
"- handling of Fermi/LAT 3FHL catalogue with [gammapy.catalog.SourceCatalog3FHL](http://docs.gammapy.org/dev/catalog/)\n",
"- handling of EBL tables with [gammapy.spectrum.TableModel](http://docs.gammapy.org/dev/api/gammapy.spectrum.models.TableModel.html#gammapy.spectrum.models.TableModel)\n",
"- handling of CTA responses with [gammapy.scripts.CTAPerf](http://docs.gammapy.org/dev/api/gammapy.scripts.CTAPerf.html?highlight=ctaperf)\n",
"- simulation of an observation for a given set of parameters with [gammapy.scripts.CTAObservationSimulation](http://docs.gammapy.org/dev/api/gammapy.scripts.CTAObservationSimulation.html#gammapy.scripts.CTAObservationSimulation)\n",
"- Illustration of Sherpa power to fit an observation with a user model (coming soon)\n",
" \n",
"## Setup\n",
"\n",
"In order to deal with plots we will begin with matplotlib import: "
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## PKS 2155-304 selection from the 3FHL Fermi/LAT catalogue\n",
"We will start by selecting the source PKS 2155-304 in the 3FHL Fermi/LAT catalogue for further use."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from gammapy.catalog import SourceCatalog3FHL\n",
"\n",
"# load catalogs\n",
"fermi_3fhl = SourceCatalog3FHL()\n",
"name = 'PKS 2155-304'\n",
"source = fermi_3fhl[name]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can then access the caracteristics of the source via the `data` attribut and select its spectral model for further use. "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"redshift = source.data['Redshift']\n",
"src_spectral_model = source.spectral_model"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here is an example on how to plot the source spectra"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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ghburrSkicde71dFMvLU7R1erwKCX5uhWVwIqbCGZTaiQdAS6AwPNbFzcUomI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\nEhERiYoKiYiIREWFREREovL/+3xNqZPdnUgAAAAASUVORK5CYII=\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot the Fermi/LAT model\n",
"import astropy.units as u\n",
"src_spectral_model.plot(energy_range=[10 * u.GeV, 2 *u.TeV])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Select a model for EBL absorption\n",
"We will need to modelise EBL (extragalactic background light) attenuation to have get a 'realistic' simulation. Different models are available in GammaPy. Here is an example on how to deal with the absorption coefficients. "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"from gammapy.spectrum.models import Absorption\n",
"\n",
"# Load models for PKS 2155-304 redshift \n",
"dominguez = Absorption.read_builtin('dominguez').table_model(redshift)\n",
"franceschini = Absorption.read_builtin('franceschini').table_model(redshift)\n",
"finke = Absorption.read_builtin('finke').table_model(redshift)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"From here you can have access to the absorption coefficient for a given energy."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"absorption(1.0 TeV) = 0.2877190694779645\n"
]
}
],
"source": [
"energy = 1 * u.TeV\n",
"abs_value = dominguez.evaluate(energy=energy, scale=1)\n",
"print('absorption({} {}) = {}'.format(energy.value, energy.unit, abs_value))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Below is an example to plot EBL absorption for different models "
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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SIUSYlHL5Yx313jrnAc2BEkKISOAjKeWvQogRwBpAD8yQUp7Iy+Nahd4WnEto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\nQmCC\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# start customised plot\n",
"energy_range = [0.08, 3] * u.TeV\n",
"ax = plt.gca()\n",
"opts = dict(energy_range=energy_range, energy_unit='TeV', ax=ax)\n",
"franceschini.plot(label='Franceschini 2008', **opts)\n",
"finke.plot(label='Finke 2010', **opts)\n",
"dominguez.plot(label='Dominguez 2011', **opts)\n",
"\n",
"# tune plot\n",
"ax.set_ylabel(r'Absorption coefficient [$\\exp{(- au(E))}$]')\n",
"ax.set_xlim(energy_range.value) # we get ride of units\n",
"ax.set_ylim([1.e-1, 2.])\n",
"ax.set_yscale('log')\n",
"ax.set_title('EBL models (z=' + str(redshift) + ')')\n",
"plt.grid(which='both')\n",
"plt.legend(loc='best') # legend\n",
"\n",
"# show plot\n",
"plt.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## CTA instrument response functions\n",
"Here we are going to deal with CTA point-like instrument response functions (public version, production 2). Data format for point-like IRF is still missing. For now, a lot of efforts is made to define full-containment IRFs (https://gamma-astro-data-formats.readthedocs.io/en/latest/irfs/index.html). In the meantime a temporary format is used in gammapy. It will evolved.\n",
"\n",
"To simulate one observation we need the following IRFs: \n",
" - effective area as a function of true energy (energy-dependent theta square cute)\n",
" - background rate as a function of reconstructed energy (energy-dependent theta square cute)\n",
" - migration matrix, e_reco/e_true as a function of true energy\n",
" \n",
"To handle CTA's responses we will use the `CTAPerf` class"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "'numpy.ndarray' object has no attribute '_set_unit'",
"output_type": "error",
"traceback": [
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"\u001b[0;32m/opt/local/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/colors.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, value, clip)\u001b[0m\n\u001b[1;32m 1198\u001b[0m \u001b[0mresdat\u001b[0m \u001b[0;34m-=\u001b[0m \u001b[0mvmin\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1199\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpower\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresdat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgamma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresdat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1200\u001b[0;31m \u001b[0mresdat\u001b[0m \u001b[0;34m/=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mvmax\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mvmin\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m**\u001b[0m \u001b[0mgamma\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1201\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1202\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresdat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/Library/Python/3.6/lib/python/site-packages/astropy/units/quantity.py\u001b[0m in \u001b[0;36m__array_ufunc__\u001b[0;34m(self, function, method, *inputs, **kwargs)\u001b[0m\n\u001b[1;32m 641\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 642\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 643\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_result_as_quantity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 644\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 645\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_result_as_quantity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/Library/Python/3.6/lib/python/site-packages/astropy/units/quantity.py\u001b[0m in \u001b[0;36m_result_as_quantity\u001b[0;34m(self, result, unit, out)\u001b[0m\n\u001b[1;32m 680\u001b[0m \u001b[0;31m# the output is of the correct Quantity subclass, as it was passed\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 681\u001b[0m \u001b[0;31m# through check_output.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 682\u001b[0;31m \u001b[0mout\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_set_unit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0munit\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 683\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 684\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mAttributeError\u001b[0m: 'numpy.ndarray' object has no attribute '_set_unit'"
]
},
{
"data": {
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from gammapy.scripts import CTAPerf\n",
"# South array optimisation for faint source \n",
"filename = '$GAMMAPY_EXTRA/datasets/cta/perf_prod2/point_like_non_smoothed/South_50h.fits.gz'\n",
"cta_perf = CTAPerf.read(filename)\n",
"cta_perf.peek()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Different optimisations are available for different type of source (bright, 0.5h; medium, 5h; faint, 50h). Here is an example to have a quick look to the different optimisation"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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sIgtQ4atrQNcBfUFRaDUwjFVf/Mjho0coVNIAC6rtvkW2JZyIWM/dNUeRevAI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PHHH/n888/ZunWrcYfc3NzcUk2x2LhxI3Xr1qVbN/Ocf3t30rN37LJly7jvvvuMVSwCAgLYvn17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\nOoaFhXH58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EWLFjF+/HgAunXrxieffMLo0aNZsWIFvXr1sntsUFAQKSkpbp0vODiY/Px8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\nYsjEJF1jGqwfKFKPaH3waA8r6je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M5s3SN/W600nTP7eLvu3E2X5VFnYNnW7yk+2qGI1H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\nIHcGKkXkAyC8P6OqnpVmu4ZhtCA9Dr6RdvonHtyzjLXFrdinto5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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"prod_dir = '$GAMMAPY_EXTRA/datasets/cta/perf_prod2/point_like_non_smoothed/'\n",
"opti = ['0.5h', '5h', '50h']\n",
"site = ['South', 'North']\n",
"cta_perf_list = [] # will be filled with different performance\n",
"labels = [] # will be filled with different performance labels for the legend\n",
"for isite in site: \n",
" for iopti in opti:\n",
" filename = prod_dir + '/' + isite + '_' + iopti + '.fits.gz'\n",
" cta_perf = CTAPerf.read(filename)\n",
" cta_perf_list.append(cta_perf)\n",
" labels.append(isite + ' (' + iopti + ')')\n",
"\n",
"CTAPerf.superpose_perf(cta_perf_list, labels)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## CTA simulation of an observation\n",
"Now we are going to simulate the expected counts in the CTA energy range. To do so we will need to specify a target (caracteristics of the source) and the parameters of the observation (such as time, ON/OFF normalisation, etc.)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Target definition"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"*** Target parameters ***\n",
"Name=3FHL J2158.8-3013 \n",
"amplitude=7.707001703494143e-11 1 / (cm2 GeV s)\n",
"reference=18.31732177734375 GeV\n",
"alpha=1.8807274103164673 \n",
"beta=0.14969758689403534 \n",
"\n"
]
}
],
"source": [
"# define target spectral model absorbed by EBL\n",
"from gammapy.spectrum.models import Absorption, AbsorbedSpectralModel\n",
"\n",
"absorption = Absorption.read_builtin('dominguez')\n",
"spectral_model = AbsorbedSpectralModel(\n",
" spectral_model=src_spectral_model,\n",
" absorption=absorption,\n",
" parameter=redshift,\n",
")\n",
"# define target\n",
"from gammapy.scripts.cta_utils import Target\n",
"target = Target(\n",
" name=source.data['Source_Name'], # from the 3FGL catalogue source class\n",
" model=source.spectral_model, # defined above\n",
")\n",
"print(target)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Observation definition"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"*** Observation parameters summary ***\n",
"alpha=0.2 []\n",
"livetime=5.0 [h]\n",
"emin=0.05 [TeV]\n",
"emax=5.0 [TeV]\n",
"\n"
]
}
],
"source": [
"from gammapy.scripts.cta_utils import ObservationParameters\n",
"alpha = 0.2 * u.Unit('') # normalisation between ON and OFF regions\n",
"livetime = 5. * u.h\n",
"# energy range used for statistics (excess, significance, etc.)\n",
"emin, emax = 0.05 * u.TeV, 5 * u.TeV\n",
"params = ObservationParameters(\n",
" alpha=alpha, livetime=livetime,\n",
" emin=emin, emax=emax,\n",
")\n",
"print(params)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Performance"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"from gammapy.scripts import CTAPerf\n",
"# PKS 2155-304 is 10 % of Crab at 1 TeV ==> intermediate source\n",
"filename = '$GAMMAPY_EXTRA/datasets/cta/perf_prod2/point_like_non_smoothed/South_5h.fits.gz'\n",
"perf = CTAPerf.read(filename)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Simulation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we are going to simulate what we expect to see with CTA and measure the duration of the simulation"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"*** Observation summary report ***\n",
"Observation Id: 0\n",
"Livetime: 5.000 h\n",
"On events: 9533\n",
"Off events: 10394\n",
"Alpha: 0.200\n",
"Bkg events in On region: 2078.80\n",
"Excess: 7454.20\n",
"Excess / Background: 3.59\n",
"Gamma rate: 2.48 1 / min\n",
"Bkg rate: 0.69 1 / min\n",
"Sigma: 101.81\n",
"energy range: 0.05 TeV - 5.01 TeV\n"
]
}
],
"source": [
"from gammapy.scripts.cta_utils import CTAObservationSimulation\n",
"\n",
"simu = CTAObservationSimulation.simulate_obs(\n",
" perf=perf,\n",
" target=target,\n",
" obs_param=params,\n",
")\n",
"\n",
"# print simulation results\n",
"print(simu)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can take a look at the excess, ON and OFF distributions"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
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vNkM/Kse2s/dpPucQfrclHdzbzN7enj179gDQoUOHV06blpL9+/fj6elJ8+bN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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"CTAObservationSimulation.plot_simu(simu, target)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can access simulation parameters via the [gammapy.spectrum.SpectrumStats](http://docs.gammapy.org/dev/api/gammapy.spectrum.SpectrumStats.html#gammapy.spectrum.SpectrumStats) attribute of the [gammapy.spectrum.SpectrumObservation](http://docs.gammapy.org/dev/api/gammapy.spectrum.SpectrumObservation.html#gammapy.spectrum.SpectrumObservation) class:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"excess: 7454.2\n",
"sigma: 101.8\n"
]
}
],
"source": [
"stats = simu.total_stats_safe_range\n",
"stats_dict = stats.to_dict()\n",
"print('excess: {}'.format(stats_dict['excess']))\n",
"print('sigma: {:.1f}'.format(stats_dict['sigma']))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Finally, you can get statistics for every reconstructed energy bin with: "
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"QTable length=10\n",
"\n",
"| energy_min | energy_max | excess | background | sigma |
|---|
\n",
"| TeV | TeV | | | |
|---|
\n",
"| float64 | float64 | float64 | float64 | float64 |
|---|
\n",
"| 0.012589254416525364 | 0.019952623173594475 | 80.2 | 3698.8 | 1.19876696834 |
\n",
"| 0.019952623173594475 | 0.03162277862429619 | 523.2 | 3101.8 | 8.31247160578 |
\n",
"| 0.03162277862429619 | 0.05011872574687004 | 1179.8 | 6852.2 | 12.6036218473 |
\n",
"| 0.05011872574687004 | 0.07943282276391983 | 1486.4 | 827.6 | 37.1420674171 |
\n",
"| 0.07943282276391983 | 0.1258925497531891 | 1845.2 | 884.8 | 43.4004197611 |
\n",
"| 0.1258925497531891 | 0.19952623546123505 | 1510.6 | 235.4 | 52.3960324108 |
\n",
"| 0.19952623546123505 | 0.3162277638912201 | 1004.0 | 73.0 | 48.5896826006 |
\n",
"| 0.3162277638912201 | 0.5011872053146362 | 644.4 | 32.6 | 40.7290245347 |
\n",
"| 0.5011872053146362 | 0.7943282127380371 | 421.8 | 12.2 | 34.7549641246 |
\n",
"| 0.7943282127380371 | 1.258925437927246 | 273.2 | 4.8 | 28.9374446728 |
\n",
"
"
],
"text/plain": [
"\n",
" energy_min energy_max excess background sigma \n",
" TeV TeV \n",
" float64 float64 float64 float64 float64 \n",
"-------------------- -------------------- ------- ---------- -------------\n",
"0.012589254416525364 0.019952623173594475 80.2 3698.8 1.19876696834\n",
"0.019952623173594475 0.03162277862429619 523.2 3101.8 8.31247160578\n",
" 0.03162277862429619 0.05011872574687004 1179.8 6852.2 12.6036218473\n",
" 0.05011872574687004 0.07943282276391983 1486.4 827.6 37.1420674171\n",
" 0.07943282276391983 0.1258925497531891 1845.2 884.8 43.4004197611\n",
" 0.1258925497531891 0.19952623546123505 1510.6 235.4 52.3960324108\n",
" 0.19952623546123505 0.3162277638912201 1004.0 73.0 48.5896826006\n",
" 0.3162277638912201 0.5011872053146362 644.4 32.6 40.7290245347\n",
" 0.5011872053146362 0.7943282127380371 421.8 12.2 34.7549641246\n",
" 0.7943282127380371 1.258925437927246 273.2 4.8 28.9374446728"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"table = simu.stats_table()\n",
"# Here we only print part of the data from the table\n",
"table[['energy_min', 'energy_max', 'excess', 'background', 'sigma']][:10]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Exercises\n",
"\n",
"- do the same thing for the source 1ES 2322-40.9 (faint BL Lac object)\n",
"- repeat the procedure 10 times and average detection results (excess and significance)\n",
"- estimate the time needed to have a 5-sigma detection for Cen A (core)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
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