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+       "                  performances in 3ML                                                                              \n",
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+       "                  performances in 3ML                                                                              \n",
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+       "                  performances in 3ML                                                                              \n",
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These object (or a derivative) will be passed around by \n", + "# the different modules.\n", + "from histpy import Histogram, Axis\n", + "from mhealpy import HealpixMap\n", + "\n", + "# Needed for coordinate conversion.\n", + "# cosipy uses astropy coordinates, with a custom\n", + "# SpacecraftFrame (coordinate frame attached to COSI)\n", + "from astropy.coordinates import SkyCoord\n", + "from cosipy.coordinates import SpacecraftFrame, Attitude\n", + "\n", + "# cosipy uses astropy units\n", + "import astropy.units as u\n", + "from astropy.time import Time\n", + "\n", + "# Other cosipy modules. Eventually the data classes and \n", + "# SC pos/attitude modules will be needed too.\n", + "from cosipy.response import FullDetectorResponse\n", + "\n", + "#Other standard libraries\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy.special import factorial\n", + "from scipy import stats\n", + "import collections\n", + "\n", + "# To deal with deep copy\n", + "import copy\n", + "\n", + "# To load the saved 3ML fitting results\n", + "import astropy.io.fits as fits" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "1e40fa5b", + "metadata": {}, + "outputs": [], + "source": [ + "class COSILike(PluginPrototype):\n", + " def __init__(self, name, dr, data, bkg, sc_orientation, **kwargs):\n", + " \"\"\"\n", + " COSI 3ML plugin\n", + " \n", + " Parameters\n", + " ----------\n", + " name : str\n", + " Plugin name e.g. \"cosi\". Needs to have a distinct name with respect to other plugins in the same analysis\n", + " dr : Path\n", + " Path to full detector response\n", + " data: histpy.Histogram\n", + " Binned data. Note: Eventually this should be a cosipy data class\n", + " bkg: histpy.Histogram\n", + " Binned background model. Note: Eventually this should be a cosipy data class\n", + " sc_orientation: array\n", + " Pair of timestamps (astropy.Time) and attitudes (scoord.Attitude) that describe\n", + " the orientation of the spacecraft for the duration of the data included in\n", + " the analysis. Note: this will eventually be handled by the SC location and\n", + " orientation module\n", + " \"\"\"\n", + " \n", + " # create the hash for the nuisance parameters. We have none for now.\n", + " nuisance_parameters = collections.OrderedDict()\n", + "\n", + " # call the prototype constructor. Boilerplate.\n", + " super(COSILike, self).__init__(name, nuisance_parameters)\n", + "\n", + " # User inputs needed to compute the likelihood\n", + " self._dr = FullDetectorResponse.open(dr)\n", + " self._data = data\n", + " self._bkg = bkg\n", + " self._sc_orientation = sc_orientation\n", + " \n", + " # Place-holder for cached data.\n", + " self._model = None\n", + " self._source = None\n", + " self._psr = None\n", + " self._signal = None\n", + " \n", + " def set_model(self, model):\n", + " \"\"\"\n", + " Set the model to be used in the joint minimization.\n", + " \n", + " Parameters:\n", + " model: LikelihoodModel\n", + " Any model supported by astromodel. However, this simple plugin only support single \n", + " point-sources with a power law spectrum\n", + " \"\"\"\n", + " \n", + " # Check for limitations\n", + " if len(model.extended_sources) != 0 or len(model.particle_sources):\n", + " raise RuntimeError(\"Only point source models are supported\")\n", + " \n", + " sources = model.point_sources\n", + " \n", + " if len(sources) != 1:\n", + " raise RuntimeError(\"Only one for now\")\n", + " \n", + " # Get expectation\n", + " for name, source in sources.items():\n", + "\n", + " if self._source is None:\n", + " self._source = copy.deepcopy(source) # to avoid same memory issue\n", + " \n", + " # Compute point source response for source position\n", + " # See also the Detector Response and Source Injector tutorials\n", + " if self._psr is None:\n", + " \n", + " coord = self._source.position.sky_coord\n", + " \n", + " dwell_time_map = self._get_dwell_time_map(coord)\n", + " \n", + " self._psr = self._dr.get_point_source_response(dwell_time_map)\n", + " \n", + " elif (source.position.ra._internal_value != self._source.position.ra._internal_value) or\\\n", + " (source.position.dec._internal_value != self._source.position.dec._internal_value):\n", + " \n", + " print('position change!')\n", + " \n", + " coord = source.position.sky_coord\n", + " \n", + " dwell_time_map = self._get_dwell_time_map(coord)\n", + " \n", + " self._psr = self._dr.get_point_source_response(dwell_time_map)\n", + " \n", + " # Caching source to self._source after position judgment\n", + " if self._source is not None:\n", + " self._source = copy.deepcopy(source)\n", + "\n", + " # Convolve with spectrum\n", + " # See also the Detector Response and Source Injector tutorials\n", + " spectrum = source.spectrum.main.shape\n", + " \n", + " # Here we translate to gammapy. We will make the detector response\n", + " # accept 3ML models and there will be no need for this\n", + " if not isinstance(spectrum, Powerlaw):\n", + " raise RuntimeError(\"Only PowerLaw supported for now\")\n", + "\n", + " spectrum = PowerLawSpectralModel(\n", + " index = -spectrum.index.value,\n", + " amplitude = spectrum.K.value * spectrum.K.unit,\n", + " reference = spectrum.piv.value * spectrum.piv.unit)\n", + " \n", + " self._signal = self._psr.get_expectation(spectrum).project(['Em', 'Phi', 'PsiChi'])\n", + " \n", + " # Cache\n", + " self._model = model # They share the same memory!\n", + "\n", + " def get_log_like(self):\n", + "\n", + " # Recompute the expectation if any parameter in the model changed\n", + " if self._model is None:\n", + " log.error(\"You need to set the model first\")\n", + " \n", + " self.set_model(self._model)\n", + " \n", + " # Compute \"lambda\" in the equations above\n", + " expectation = self._signal.contents + self._bkg.contents\n", + " \n", + " data = self._data.contents # Into an array\n", + " \n", + " # Compute the log-likelihood from the equations above\n", + " log_like = np.sum(np.log(np.power(expectation, data) * \n", + " np.exp(-expectation) / \n", + " factorial(data)))\n", + " \n", + " return log_like\n", + "\n", + " def inner_fit(self):\n", + " \"\"\"\n", + " This fits nuisance parameters, but we have none for now.\n", + " \"\"\"\n", + " \n", + " return self.get_log_like()\n", + " \n", + " def _get_dwell_time_map(self, coord):\n", + " \"\"\"\n", + " This will be eventually be provided by another module\n", + " \"\"\"\n", + " \n", + " # The dwell time map has the same pixelation (base) as the detector response.\n", + " # We start with an empty map\n", + " dwell_time_map = HealpixMap(base = self._dr, \n", + " unit = u.s, \n", + " coordsys = SpacecraftFrame())\n", + "\n", + " # Get timestamps and attitude values\n", + " timestamps, attitudes = zip(*self._sc_orientation)\n", + " \n", + " for attitude,duration in zip(attitudes[:-1], np.diff(timestamps)):\n", + "\n", + " local_coord = coord.transform_to(SpacecraftFrame(attitude = attitude))\n", + "\n", + " # Here we add duration in between timestamps using interpolations\n", + " pixels, weights = dwell_time_map.get_interp_weights(local_coord)\n", + "\n", + " for p,w in zip(pixels, weights):\n", + " dwell_time_map[p] += w*duration.to(u.s)\n", + " \n", + " return dwell_time_map" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "c106e9df", + "metadata": {}, + "outputs": [], + "source": [ + "# Inputs needed by the COSI plugin\n", + "# We'll use fake data from the \"Source injector\" tutorial\n", + "dr = \"/Users/jasonpbu/Desktop/COSIpy/tutorial/FlatContinuumIsotropic.LowRes.binnedimaging.imagingresponse.area.nside8.cosipy.h5\"\n", + "data = Histogram.open(\"/Users/jasonpbu/Desktop/COSIpy/tutorial/data.h5\")\n", + "bkg = Histogram.open(\"/Users/jasonpbu/Desktop/COSIpy/tutorial/bkg.h5\")\n", + "signal = Histogram.open(\"/Users/jasonpbu/Desktop/COSIpy/tutorial/signal.h5\")\n", + "\n", + "# 1s duration. Spacecraft aligned with the ICRS ([0,0,0,1] = Identity)\n", + "sc_orientation = [(Time('2025-01-01T13:02:01.00'), Attitude.from_quat([0,0,0,1])), \n", + " (Time('2025-01-01T13:02:02.00'), Attitude.from_quat([0,0,0,1]))]\n", + "\n", + "# Instantiate the plugin\n", + "# Note that we'll use 3x the signal we injected before. \n", + "cosi = COSILike(\"cosi\",\n", + " dr = dr,\n", + " data = bkg + 3*signal, \n", + " bkg = bkg, \n", + " sc_orientation = sc_orientation)\n", + "\n", + "# Corresponding parameters, for reference\n", + "ra_inj = 20 # deg\n", + "dec_inj = 40 # deg\n", + "norm_inj = 3e-1 # 1/keV/cm2/s (3x the injected signal)\n", + "piv_inj = 1 # keV\n", + "index_inj = -1.7 " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "82d3f4fe", + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "# Our model will contain a single source with a power law spectrum\n", + "spectrum = Powerlaw()\n", + "\n", + "# Setting the parameter to something reasonable helps the \n", + "# fitting to converge\n", + "spectrum.K.value = 1 # 1/keV/cm2/s\n", + "spectrum.piv.value = piv_inj # will be fixed \n", + "spectrum.index.value = index_inj # will be fixed \n", + "\n", + "# Optional: change pivot energy\n", + "# The pivot value is arbitrary, ideally nothing should depend on it\n", + "# However, it is recommended to choose a value near the energy\n", + "# for which the detector is most sensitive ir onder to minimize\n", + "# the correlation between the normalization and spectral index.\n", + "# Try setting it to 500 keV and see how the results change\n", + "# piv = 500 #keV\n", + "# spectrum.K.value = spectrum(piv) # 1/keV/cm2/s\n", + "# spectrum.piv.value = piv # keV\n", + "\n", + "# Point source instance, at the know location (from the \"Source Injectior\" tutorial)\n", + "source = PointSource(\"source\", # The name of the source is arbitrary, but needs to be unique\n", + " ra = ra_inj, \n", + " dec = dec_inj,\n", + " spectral_shape = spectrum)\n", + "\n", + "# Adding the source to the model\n", + "# If we had multiple sources, we would do Model(source1, source2, ...)\n", + "model = Model(source)\n", + "\n", + "# Optional: if you want to call get_log_like manually, then you\n", + "# also need to set the model manually. 3ML does this internanlly during the fit though\n", + "cosi.set_model(model)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "0411bdc0", + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "Model summary:

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" + ], + "text/plain": [ + "Model summary:\n", + "==============\n", + "\n", + " N\n", + "Point sources 1\n", + "Extended sources 0\n", + "Particle sources 0\n", + "\n", + "Free parameters (1):\n", + "--------------------\n", + "\n", + " value min_value max_value unit\n", + "source.spectrum.main.Powerlaw.K 1.0 0.0 1000.0 keV-1 s-1 cm-2\n", + "\n", + "Fixed parameters (4):\n", + "---------------------\n", + "\n", + " value min_value max_value unit\n", + "source.position.ra 20.0 0.0 360.0 deg\n", + "source.position.dec 40.0 -90.0 90.0 deg\n", + "source.spectrum.main.Powerlaw.piv 1.0 None None keV\n", + "source.spectrum.main.Powerlaw.index -1.7 -10.0 10.0 \n", + "\n", + "Properties (0):\n", + "--------------------\n", + "\n", + "(none)\n", + "\n", + "\n", + "Linked parameters (0):\n", + "----------------------\n", + "\n", + "(none)\n", + "\n", + "Independent variables:\n", + "----------------------\n", + "\n", + "(none)\n", + "\n", + "Linked functions (0):\n", + "----------------------\n", + "\n", + "(none)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Checking new fix and free parameters\n", + "model.display(complete=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "e1165c4f", + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
11:11:10 INFO      set the minimizer to minuit                                             joint_likelihood.py:1042\n",
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11:11:14 WARNING   get_number_of_data_points not implemented, values for statistical        plugin_prototype.py:128\n",
+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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total4540.459283
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+       "Values of statistical measures:\n",
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statistical measures
AIC9078.918565
BIC9080.918565
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11:11:16 WARNING   get_number_of_data_points not implemented, values for statistical        plugin_prototype.py:128\n",
+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
+       "
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+       "\n",
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resultunit
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source.spectrum.main.Powerlaw.K(2.77 -0.33 +0.4) x 10^-11 / (cm2 keV s)
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+       "Correlation matrix:\n",
+       "\n",
+       "
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+       "Values of -log(likelihood) at the minimum:\n",
+       "\n",
+       "
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-log(likelihood)
cosi4548.361879
total4548.361879
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+       "Values of statistical measures:\n",
+       "\n",
+       "
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statistical measures
AIC9094.723757
BIC9096.723757
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11:11:19 WARNING   get_number_of_data_points not implemented, values for statistical        plugin_prototype.py:128\n",
+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
N
Point sources1
Extended sources0
Particle sources0
\n", + "


Free parameters (1):

\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
valuemin_valuemax_valueunit
source.spectrum.main.Powerlaw.K0.10.01000.0keV-1 s-1 cm-2
\n", + "


Fixed parameters (4):

\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
valuemin_valuemax_valueunit
source.position.ra22.0408160.0360.0deg
source.position.dec41.25-90.090.0deg
source.spectrum.main.Powerlaw.piv1.0NoneNonekeV
source.spectrum.main.Powerlaw.index-1.7-10.010.0
\n", + "


Properties (0):

(none)


Linked parameters (0):

(none)

Independent variables:

(none)

Linked functions (0):

(none)
" + ], + "text/plain": [ + "Model summary:\n", + "==============\n", + "\n", + " N\n", + "Point sources 1\n", + "Extended sources 0\n", + "Particle sources 0\n", + "\n", + "Free parameters (1):\n", + "--------------------\n", + "\n", + " value min_value max_value unit\n", + "source.spectrum.main.Powerlaw.K 0.1 0.0 1000.0 keV-1 s-1 cm-2\n", + "\n", + "Fixed parameters (4):\n", + "---------------------\n", + "\n", + " value min_value max_value unit\n", + "source.position.ra 22.040816 0.0 360.0 deg\n", + "source.position.dec 41.25 -90.0 90.0 deg\n", + "source.spectrum.main.Powerlaw.piv 1.0 None None keV\n", + "source.spectrum.main.Powerlaw.index -1.7 -10.0 10.0 \n", + "\n", + "Properties (0):\n", + "--------------------\n", + "\n", + "(none)\n", + "\n", + "\n", + "Linked parameters (0):\n", + "----------------------\n", + "\n", + "(none)\n", + "\n", + "Independent variables:\n", + "----------------------\n", + "\n", + "(none)\n", + "\n", + "Linked functions (0):\n", + "----------------------\n", + "\n", + "(none)" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "spectrum.K.value = 1e-1\n", + "model.display(complete=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "844c6363", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "                  measurements such as AIC or BIC are unreliable                                                   \n",
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+       "Values of statistical measures:\n",
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" + ], + "text/plain": [ + " statistical measures\n", + "AIC 9080.754414\n", + "BIC 9082.754414" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filename: RA_Dec_freeNorm_3ML.fits\n", + "No. Name Ver Type Cards Dimensions Format\n", + " 0 PRIMARY 1 PrimaryHDU 6 () \n", + " 1 ANALYSIS_RESULTS 1 BinTableHDU 38 1R x 9C [31A, D, D, D, D, 15A, 1D, D, D] \n" + ] + } + ], + "source": [ + "# Refitting the best fitting case\n", + "# Changing the position parameters\n", + "# Converting rad to deg due to RA and Dec in 3ML PointSource\n", + "if ts.axes['ra'].centers[argmax[0]] < 0:\n", + " source.position.ra = (ts.axes['ra'].centers[argmax[0]] + 2*np.pi) * (180/np.pi) # deg\n", + "else:\n", + " source.position.ra = (ts.axes['ra'].centers[argmax[0]]) * (180/np.pi) # deg\n", + "source.position.dec = ts.axes['dec'].centers[argmax[1]] * (180/np.pi) # deg\n", + "\n", + "# Maximum likelihood\n", + "like.fit()\n", + "\n", + "# Displaying the best fit result \n", + "ar = like.results\n", + "ar.display()\n", + "\n", + "# Saving ar as .fits file\n", + "ar.write_to(\"RA_Dec_freeNorm_3ML.fits\", overwrite=True)\n", + "\n", + "# Loading .fits file and checking\n", + "ar_fits = fits.open(\"RA_Dec_freeNorm_3ML.fits\")\n", + "ar_fits.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "4ed33c18", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plotting\n", + "fig, ax = plt.subplots(figsize=(16, 8), subplot_kw={'projection': 'mollweide'}, dpi=120)\n", + "\n", + "_,plot = ts.plot(ax, vmin = 0, colorbar = False, zorder=0)\n", + "\n", + "ax.scatter([ts.axes['ra'].centers[argmax[0]]],[ts.axes['dec'].centers[argmax[1]]], label = \"Max TS\", zorder=3)\n", + "\n", + "ax.scatter([20/180*np.pi],[40/180*np.pi], marker = \"x\", label = \"Injected\", zorder=2)\n", + "\n", + "# Here we also use Wilk's theorem to find the DeltaTS that corresponse to a 90% containment confidence\n", + "ts_thresh = ts_max - stats.chi2.isf(1-.9, df = 2)\n", + "contours = ax.contour(ts.axes['ra'].centers, \n", + " ts.axes['dec'].centers, \n", + " ts.contents.transpose(), \n", + " [ts_thresh], colors = 'red', zorder=1)\n", + "contours.collections[0].set_label(\"90% cont.\")\n", + "\n", + "cbar = fig.colorbar(plot)\n", + "cbar.ax.set_ylabel(\"TS\")\n", + "\n", + "ax.set_xlabel('R.A.', fontsize=15);\n", + "ax.set_ylabel('Dec.', fontsize=15);\n", + "ax.tick_params(axis='x', colors='White')\n", + "ax.legend(fontsize=10)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "da80df7b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:env_cosipy]", + "language": "python", + "name": "conda-env-env_cosipy-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}