{ "cells": [ { "cell_type": "markdown", "id": "a3e92e8e-7c4e-41ae-9fea-040dada717b2", "metadata": {}, "source": [ "# Full detector response" ] }, { "cell_type": "markdown", "id": "693f2144-561f-4699-9624-1122b9f730e3", "metadata": {}, "source": [ "The detector response provides us with the the following information:\n", "- The effective area at given energy for given direction. This allows us to convert from counts to physical quantities like flux\n", "- The expected distribution of measured energy and other reconstructed quantities. This allows us to account for all sorts of detector effects when we do our analysis.\n", "\n", "This tutorial will show you how to handle detector response and extrat useful information from it." ] }, { "cell_type": "markdown", "id": "9ec5eb17-f83d-4a9c-b45c-42c7d71bd6a8", "metadata": {}, "source": [ "## Dependencies" ] }, { "cell_type": "code", "execution_count": 1, "id": "366b09f0-aff2-47cd-93ee-2dcff45185e5", "metadata": {}, "outputs": [], "source": [ "%%capture\n", "import numpy as np\n", "import astropy.units as u\n", "from astropy.units import Quantity\n", "from astropy.coordinates import SkyCoord\n", "from astropy.io import fits\n", "from astropy.time import Time\n", "\n", "import matplotlib.pyplot as plt\n", "import matplotlib.pyplot as ply\n", "\n", "from mhealpy import HealpixMap, HealpixBase\n", "import pandas as pd\n", "from pathlib import Path\n", "\n", "from scoords import Attitude, SpacecraftFrame\n", "from cosipy.response import FullDetectorResponse\n", "from cosipy.spacecraftfile import SpacecraftFile\n", "from cosipy import test_data\n", "from cosipy.util import fetch_wasabi_file\n", "from histpy import Histogram\n", "import gc\n", "\n", "from threeML import Model, Powerlaw\n", "\n", "from cosipy.response import FullDetectorResponse\n", "\n", "import shutil\n", "import os" ] }, { "cell_type": "markdown", "id": "ba883bb8-fa61-4f9c-a551-25e8c4649bad", "metadata": {}, "source": [ "## File downloads" ] }, { "cell_type": "markdown", "id": "2d7fca99-a643-4a09-b60e-f09bf0145049", "metadata": {}, "source": [ "You can skip this step if you already downloaded the files. Make sure that paths point to the right files" ] }, { "cell_type": "code", "execution_count": 2, "id": "89945d9d-7d38-4871-bf20-4000ca93c06b", "metadata": {}, "outputs": [], "source": [ "data_dir = Path(\"\") # Current directory by default. Modify if you can want a different path\n", "\n", "ori_path = data_dir/\"20280301_3_month_with_orbital_info.ori\"\n", "response_path = data_dir/\"SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5\"\n", "\n", "# download orientation file ~684.38 MB\n", "if not ori_path.exists():\n", " fetch_wasabi_file(\"COSI-SMEX/DC2/Data/Orientation/20280301_3_month_with_orbital_info.ori\", ori_path)\n", "\n", "# download response file ~839.62 MB\n", "if not response_path.exists():\n", " \n", " response_path_zip = str(response_path) + '.zip'\n", " fetch_wasabi_file(\"COSI-SMEX/DC2/Responses/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5.zip\",response_path_zip)\n", " \n", " # unzip the response file\n", " shutil.unpack_archive(response_path_zip)\n", " \n", " # delete the zipped response to save space\n", " os.remove(response_path_zip)" ] }, { "cell_type": "markdown", "id": "d2a3629d-b7a0-4c2e-bfc5-786b17ed06f8", "metadata": {}, "source": [ "## Opening a full detector response" ] }, { "cell_type": "markdown", "id": "a571dd15-b4f7-4f3e-9ab1-ac399afb6c3c", "metadata": {}, "source": [ "The response of the instrument in encoded in a series of matrices cointained in a file. you can open the file like this:" ] }, { "cell_type": "code", "execution_count": 3, "id": "a7c37c72-a197-4e87-849a-93bf491eac88", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5\n" ] } ], "source": [ "response = FullDetectorResponse.open(response_path)\n", "\n", "print(response.filename)\n", "\n", "response.close()" ] }, { "cell_type": "markdown", "id": "02ab5663-6255-47f6-938a-be52dbb1ba2e", "metadata": {}, "source": [ "Or if you don't want to worry about closing the file, use a context manager statement:" ] }, { "cell_type": "code", "execution_count": 4, "id": "f5921a20-9560-4bfd-be91-29490aac144a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "FILENAME: '/Users/imartin5/software/cosipy/docs/tutorials/response/SMEXv12.Continuum.HEALPixO3_10bins_log_flat.binnedimaging.imagingresponse.nonsparse_nside8.area.good_chunks_unzip.h5'\n", "AXES:\n", " NuLambda:\n", " DESCRIPTION: 'Location of the simulated source in the spacecraft coordinates'\n", " TYPE: 'healpix'\n", " NPIX: 768\n", " NSIDE: 8\n", " SCHEME: 'RING'\n", " Ei:\n", " DESCRIPTION: 'Initial simulated energy'\n", " TYPE: 'log'\n", " UNIT: 'keV'\n", " NBINS: 10\n", " EDGES: [100.0 keV, 158.489 keV, 251.189 keV, 398.107 keV, 630.957 keV, 1000.0 keV, 1584.89 keV, 2511.89 keV, 3981.07 keV, 6309.57 keV, 10000.0 keV]\n", " Em:\n", " DESCRIPTION: 'Measured energy'\n", " TYPE: 'log'\n", " UNIT: 'keV'\n", " NBINS: 10\n", " EDGES: [100.0 keV, 158.489 keV, 251.189 keV, 398.107 keV, 630.957 keV, 1000.0 keV, 1584.89 keV, 2511.89 keV, 3981.07 keV, 6309.57 keV, 10000.0 keV]\n", " Phi:\n", " DESCRIPTION: 'Compton angle'\n", " TYPE: 'linear'\n", " UNIT: 'deg'\n", " NBINS: 36\n", " EDGES: [0.0 deg, 5.0 deg, 10.0 deg, 15.0 deg, 20.0 deg, 25.0 deg, 30.0 deg, 35.0 deg, 40.0 deg, 45.0 deg, 50.0 deg, 55.0 deg, 60.0 deg, 65.0 deg, 70.0 deg, 75.0 deg, 80.0 deg, 85.0 deg, 90.0 deg, 95.0 deg, 100.0 deg, 105.0 deg, 110.0 deg, 115.0 deg, 120.0 deg, 125.0 deg, 130.0 deg, 135.0 deg, 140.0 deg, 145.0 deg, 150.0 deg, 155.0 deg, 160.0 deg, 165.0 deg, 170.0 deg, 175.0 deg, 180.0 deg]\n", " PsiChi:\n", " DESCRIPTION: 'Location in the Compton Data Space'\n", " TYPE: 'healpix'\n", " NPIX: 768\n", " NSIDE: 8\n", " SCHEME: 'RING'\n", "\n" ] } ], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", "\n", " print(repr(response))" ] }, { "cell_type": "markdown", "id": "f6750d71-cc53-4aef-b023-835a646a2ff2", "metadata": {}, "source": [ "Although opening a detector response does not load the matrices, it loads all the header information above. This allows us to pass it around for various analysis at a very low cost." ] }, { "cell_type": "markdown", "id": "b7b4c8fa-4565-4a51-932f-3feecafa42d4", "metadata": {}, "source": [ "## Detector response matrix" ] }, { "cell_type": "markdown", "id": "c69e16d8-4822-43ec-bc4e-135abe25d6fd", "metadata": {}, "source": [ "The full --i.e. all-sky-- detector response is encoded in a HEALPix grid. For each pixel there is a multidimensional matrix describing the response of the instrument for that particular direction in the spacefraft coordinates. For this response has the following grid:" ] }, { "cell_type": "code", "execution_count": 5, "id": "cad81d6b-7c7b-41d5-9868-da58d25d4a3d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "NSIDE = 8\n", "SCHEME = RING\n", "NPIX = 768\n", "Pixel size = 7.33 deg\n" ] } ], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", " \n", " print(f\"NSIDE = {response.nside}\")\n", " print(f\"SCHEME = {response.scheme}\")\n", " print(f\"NPIX = {response.npix}\")\n", " print(f\"Pixel size = {np.sqrt(response.pixarea()).to(u.deg):.2f}\")" ] }, { "cell_type": "markdown", "id": "5c18a7b2-0190-4027-afe7-2f631fc245e1", "metadata": {}, "source": [ "To retrieve the detector response matrix for a given pixel simply use the `[]` operator" ] }, { "cell_type": "code", "execution_count": 6, "id": "d4972c53-f653-4694-8190-8524362b6ef7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pixel 0 centered at \n" ] } ], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", " \n", " print(f\"Pixel 0 centered at {response.pix2skycoord(0)}\")\n", " drm = response[0]" ] }, { "cell_type": "markdown", "id": "9bf2f221-0300-4dd1-8dc7-eb4e0e694997", "metadata": {}, "source": [ "Or better, get the interpolated matrix for a given direction. In this case, for the on-axis response:" ] }, { "cell_type": "code", "execution_count": 7, "id": "5a621225-5619-4d43-9670-b4bd03b1d801", "metadata": {}, "outputs": [], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", " \n", " drm = response.get_interp_response(SkyCoord(lon = 0*u.deg, lat = 0*u.deg, frame = SpacecraftFrame()))" ] }, { "cell_type": "markdown", "id": "05e40223-2d93-4a82-95b3-c30d00499742", "metadata": {}, "source": [ "The matrix has multiple dimensions, including real photon initial energy, the measured energy, the Compton data space, and possibly other:" ] }, { "cell_type": "code", "execution_count": 8, "id": "6680c76c-3483-462e-bb40-5a00b282cdba", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['Ei', 'Em', 'Phi', 'PsiChi'], dtype='" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "drm.get_spectral_response().plot();" ] }, { "cell_type": "markdown", "id": "f37ad594-0be7-41f0-b7ec-16e2251a78b8", "metadata": {}, "source": [ "You can further project it into the initial energy to get the effective area:" ] }, { "cell_type": "code", "execution_count": 10, "id": "a20f628e-b891-4dcb-b305-8a94c01f2d4a", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax,plot = drm.get_effective_area().plot();\n", "\n", "ax.set_ylabel(f'Aeff [{drm.unit}]');" ] }, { "cell_type": "markdown", "id": "64edb047-2d80-4011-9fa3-665a1bdd282e", "metadata": {}, "source": [ "Get the interpolated effective area" ] }, { "cell_type": "code", "execution_count": 11, "id": "6ad17044-46a6-4646-b5d2-1cec399228f2", "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$6.3406481 \\; \\mathrm{cm^{2}}$" ], "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "drm.get_effective_area(511*u.keV)" ] }, { "cell_type": "markdown", "id": "983b731f-1dad-434a-8430-544c76b0e862", "metadata": {}, "source": [ "Or the energy dispersion matrix" ] }, { "cell_type": "code", "execution_count": 12, "id": "2003abb9-c2a5-487f-b869-f0e4b46bc053", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "drm.get_dispersion_matrix().plot();" ] }, { "cell_type": "markdown", "id": "aac9aaff-8b5b-4ce6-a84e-5552ea0ac5ad", "metadata": {}, "source": [ "## Point source response and expected counts" ] }, { "cell_type": "markdown", "id": "efb6da4d-1c70-473a-8137-05a9bb2ba063", "metadata": {}, "source": [ "Once we have the response, the next step is usually to get the expected counts for a specific source. However, it is not trivial for the case of a spacecraft because the response we have here is the detector response. This response records the detector effects to given points viewed from the reference frame attached to the spacecraft (SC).\n", "\n", "A source with a fixed position on the sky is moving from the perspective of the spacecraft (detector). Therefore, we need to convert the coordinate of a source to the reference frame, which results in a moving point viewed the spacecraft. By convolving the trajectory of the source in the spacecraft frame with the detector response, we will get the so-called point source response.\n", "\n", "See the spacecraft file tutorial for a discussion of the SC attitude history, transformations to/from galactic coordinates, and the dwell time map." ] }, { "cell_type": "code", "execution_count": 13, "id": "cd6dd9bd-02c3-4116-b291-b8eaba8a05cc", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Now converting to the Spacecraft frame...\n", "Conversion completed!\n" ] } ], "source": [ "# read the full oritation\n", "ori = SpacecraftFile.parse_from_file(ori_path)\n", "\n", "# define the target coordinates (Crab)\n", "target_coord = SkyCoord(184.5551, -05.7877, unit = \"deg\", frame = \"galactic\")\n", "\n", "# get the target movement in the reference frame attached to the detector\n", "target_in_sc_frame = ori.get_target_in_sc_frame(target_name = \"Crab\", target_coord = target_coord)\n", "\n", "# Get the dwell time map\n", "dwell_time_map = ori.get_dwell_map(response = response_path, src_path = target_in_sc_frame)" ] }, { "cell_type": "markdown", "id": "17277018-0380-4daf-bf41-fe1fac44d0ab", "metadata": {}, "source": [ "We can now convolve the exposure map with the full detector response, and get a PointSourceResponse" ] }, { "cell_type": "code", "execution_count": 14, "id": "f6edcf60-c017-40d9-92b5-e85f612d7eeb", "metadata": {}, "outputs": [], "source": [ "with FullDetectorResponse.open(response_path) as response:\n", " psr = response.get_point_source_response(exposure_map = dwell_time_map, coord = target_coord)" ] }, { "cell_type": "markdown", "id": "e7ce6363-066e-4a2b-9fdc-bf2ca03d0d89", "metadata": {}, "source": [ "Note that a PointSourceResponse only depends on the path of the source, not on the spectrum of the source. It has units of area*time" ] }, { "cell_type": "code", "execution_count": 15, "id": "62b557b0-c988-4859-b5c7-f3709e47a9ae", "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\mathrm{cm^{2}\\,s}$" ], "text/plain": [ "Unit(\"cm2 s\")" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "psr.unit" ] }, { "cell_type": "markdown", "id": "5b014e8e-21ca-4d97-8436-2292b2a5c132", "metadata": {}, "source": [ "Finally, we convolve a spectrum to get the spected excess for each *measured* energy bin:" ] }, { "cell_type": "code", "execution_count": 16, "id": "9976cfa6-fec0-4ef5-b448-20aee8678946", "metadata": {}, "outputs": [], "source": [ "index = -2.2\n", "K = 10**-3 / u.cm / u.cm / u.s / u.keV\n", "piv = 100 * u.keV\n", "\n", "spectrum = Powerlaw()\n", "spectrum.index.value = index\n", "spectrum.K.value = K.value\n", "spectrum.piv.value = piv.value \n", "spectrum.K.unit = K.unit\n", "spectrum.piv.unit = piv.unit\n", " \n", "expectation = psr.get_expectation(spectrum)" ] }, { "cell_type": "code", "execution_count": 17, "id": "0c929b25-4b09-475f-bcdd-ac7dfba10e84", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Expected counts')" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax, plot = expectation.project('Em').plot()\n", "\n", "ax.set_ylabel('Expected counts')" ] }, { "cell_type": "markdown", "id": "c8f64def-a29b-4277-aa6c-9d9561117acb", "metadata": {}, "source": [ "Try changing the spectrum and se how the expected excess changes." ] }, { "cell_type": "code", "execution_count": 18, "id": "766ea3af-1282-4c0d-a22f-2192a7dcb938", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Expected counts')" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "spectrum.index.value = -1\n", "\n", "expectation = psr.get_expectation(spectrum)\n", "\n", "ax, plot = expectation.project('Em').plot()\n", "\n", "ax.set_ylabel('Expected counts')" ] }, { "cell_type": "markdown", "id": "86bac761-903c-4c72-8138-130c2194e876", "metadata": {}, "source": [ "## Point source response in inertial coordinates" ] }, { "cell_type": "markdown", "id": "ad7b53cf-f02c-4e29-9079-d96f73f929b3", "metadata": {}, "source": [ "In the previous example we obtained the response for a point source as seen in the reference frame attached to the spacecraft (SC) frame. As the spacecraft rotates, a fixed source in the sky is seen by the detector from multiple direction, so binnind the data on the spacecraft coordinate, without binning it simultenously in time, can wash out the signal. As shown in this section, we can instead rotate the response and convolve it the attitude history of the spacecraft, resulting in a point source response with a Compton data space binned in inertial coordinates.\n", "\n", "We use a scatt map, which tracks the amount of time the spacecraft spent in a given orientation. See spacecraft file tutorial for more details." ] }, { "cell_type": "code", "execution_count": 19, "id": "cb7f52de-e3fb-4568-adaf-ccca8e55d215", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\n", "WARNING ErfaWarning: ERFA function \"utctai\" yielded 7979956 of \"dubious year (Note 3)\"\n", "\n" ] } ], "source": [ "coord = SkyCoord.from_name('Crab').galactic\n", "\n", "scatt_map = ori.get_scatt_map(coord, nside = 16, coordsys = 'galactic')" ] }, { "cell_type": "markdown", "id": "dfac4b7b-227f-4c4b-977b-5cc4cebc9ee5", "metadata": {}, "source": [ "Now we can let cosipy perform the convolution with the scatt map and get the point source response:" ] }, { "cell_type": "code", "execution_count": 20, "id": "48573091-7569-4ab4-9ee6-f8e996e5b11b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 46 s, sys: 5.45 s, total: 51.4 s\n", "Wall time: 54.3 s\n" ] } ], "source": [ "%%time\n", "\n", "from astropy.coordinates import SkyCoord\n", "\n", "with FullDetectorResponse.open(response_path) as response:\n", " psr = response.get_point_source_response(coord = coord, scatt_map = scatt_map)" ] }, { "cell_type": "markdown", "id": "36326805-b595-4110-8001-08980308718d", "metadata": {}, "source": [ "This is how a slice of the response looks like in galactic coordinates:" ] }, { "cell_type": "code", "execution_count": 21, "id": "07c397d6-63f5-4162-8cd4-536f3a5a2a6e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "psichi_slice = psr.slice[{'Ei':4, 'Phi':4}].project('PsiChi')\n", "\n", "ax,plot = psichi_slice.plot(ax_kw = {'coord':'G'})\n", "\n", "ax.scatter([coord.l.deg], [coord.b.deg], transform = ax.get_transform('world'), marker = 'x', color = 'red')" ] }, { "cell_type": "markdown", "id": "f8d9aa2e-345f-4b89-a298-06a2071ee1ea", "metadata": {}, "source": [ "And here in ICRC (RA/Dec), the default coordinates for plot()" ] }, { "cell_type": "code", "execution_count": 22, "id": "ff08be37-22eb-422a-810f-a1f9f2f47abf", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax,plot = psichi_slice.plot()\n", "\n", "ax.scatter([coord.icrs.ra.deg], [coord.icrs.dec.deg], transform = ax.get_transform('world'), marker = 'x', color = 'red')" ] }, { "cell_type": "markdown", "id": "fa7196b6-5981-4951-88ce-16be5f7abbe6", "metadata": {}, "source": [ "You can also used it the same way as a point source response obtained from a exposure map. e.g." ] }, { "cell_type": "code", "execution_count": 23, "id": "393d7309-64f4-4e1d-86a0-82a3ee2f4ea7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Expected counts')" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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//srPz1f9+vU1ZMgQjRs3Tu7u1f6PBQAAlFG1TwWrV69Wfn6+evWy3Gx8xx136L777lNwcLCuX7+uXbt2afny5Tp37pxef/31UtdLSUlRamqq+XNpV6wAAED1YNewZDKZ9Ouvv8rT01MBAQH2XNomcXFxioqKUs+ePXX//fdb9L300ksWn/v37693331XX3/9tUaNGqV77rnH6prr169XVFRURZUMAACcjE1haffu3dqzZ4+mTZumWrVqSZIuXryol156yXylpUePHnrllVfk5uZmv2rLITExUS+//LKCg4M1a9asMs0ZPXq0vv76ax08eLDUsBQREaEuXbpYfM+8efPsUjMAAHA+NoWldevW6cqVK+agJEkffvihzp49q7Zt2yojI0O7du3S/fffr6FDh9qt2LJKTk7WjBkz5OPjo7fffrvMm7cbNmwoScrMzCx1jL+/f4lnNgEAgOrLphfpnj17VmFhYebP2dnZ2rdvn3r16qVFixbpr3/9q5o2baoNGzbYrdCySk9P14wZM5Sfn6+FCxeWK9hcuHBBklS3bt0Kqg4AAFQ1NoWljIwM1a9f3/z58OHDKiwsVO/evSVJ7u7uateunc6fP2+fKq1ISUlRYmKiCgr+8/yTnJwczZw5UykpKXrnnXfUpEkTq3OvXbumvLw8izaTyaTly5dLktq3b19hdQMAgKrFpttwPj4+ysjIMH8+dOiQXF1d1bp16/8s7O6u69ev21TUF198oaysLPOvzmJjY3Xp0iVJ0ogRI+Tr66ulS5dq06ZNio6OVmDgjWe3zJ07V8eOHdOgQYOUmJho8Us1b29vdevWTZJ04sQJvf766+rTp4+CgoKUm5urf//73/rpp580dOhQhYaG2lQ3AACofmwKS3feeaf27t2r8ePHy9XVVdu2bdPdd99tsYcpKSlJ9erVs6mo6OhoJSUlmT/HxMQoJiZGktSvXz/5+vpanXfq1ClJ0oYNG0rcAmzUqJE5LAUEBKh169aKiYnRlStX5OrqqqZNm2rGjBmKiIiwqWYAAFA92RSWRowYoddee00jRowwX0EaP368xZj4+HjdfffdNhW1atWqm46ZM2eO5syZU+550o1nLBk9SwkAAKCYTWGpR48eeu655/Ttt99Kknr16qWBAwea++Pi4nTt2jV16NDBPlUCAAA4iM0PpXzooYf00EMPWe1r06aNQ34JBwAAYG82/RouKipKcXFxhmMOHz7Mk64BAECVZ1NY+uyzz24alopfNQIAAFCV2RSWyqKgoECurhW2PAAAQKWwOc24uLiU2pefn68ff/zR5kcHAAAAOIsyb/AePXq0xedVq1ZZ3cRdVFSk9PR05eXlaciQIbdeIQAAgAOVOSyZTCbzv7u4uMhkMlm0mRd0d9ddd92ltm3bauzYsfapEgAAwEHKHJb++4GP3bt316hRozRu3LiKqAkAAMBp2PScpejo6FJfOQIAAFCd2BSWGjVqZO86AAAAnJLNT/BOS0vThg0blJCQoKysLBUWFpYY4+Lioj//+c+3Uh8AAIBD2RSWTp8+rWeffVaZmZlWN3kXM3q8AAAAQFVgU1j6y1/+ooyMDD3xxBMaPHiwGjRoIDc3N3vXBgAA4HA2haWjR4+qa9eueuqpp+xdDwAAgFOx6Qne7u7uCgoKsnctAAAATsemsNSmTRsdP37c3rUAAAA4HZvC0uTJk3XmzBn961//snc9AAAATsWmPUv/+Mc/FBwcrL/+9a9av369WrRoIR8fH6tjX3rppVsqEAAAwJFsCksbN240//uFCxd04cIFq+NcXFwISwAAoEqz+XUnAAAAtwNedwIAAGDApg3eAAAAtwubrixt2rSpzGMHDBhgy1cAAAA4BZvC0oIFC2763jeTySQXFxfCEgAAqNJsCkul/cLt2rVrOnHihLZt26YuXbqoc+fOt1QcAACAo9kUlgYOHGjYHxERoWeffVYPPfSQLcsDAAA4jQrZ4H3vvfeqS5cuWrZsWUUsDwAAUGkq7NdwjRo10unTpytqeQAAgEpRIWHJZDLpxx9/lKenZ0UsDwAAUGls2rMUFxdntb2wsFApKSnavHmzEhIS1L9//1upDQAAwOFsCkvTp083fHSAyWTS7373O02dOtXmwgDAWeRczdWKqTscXUaZedRwV7vIEDXrGOjoUoBqwaawNHbsWKthydXVVb6+vgoLC1N4ePgtFwcAjuRRw11SrkwmKftKrqPLKYdcHVx9krAE2IlNYenJJ5+0dx0A4HTaRYbo4OqTyr9e4OhSyizn6o1wV5VqBpydTWEJAG4HzToGVrmrMyum7qhiV8EA53dLYenixYvaunWrTp06pWvXrsnHx0ctWrRQ3759FRhYtf4fDAAAgDU2h6XVq1fr448/VmFhoUwmk7l99+7d+vvf/66nn35akZGRNq2dnZ2tlStXKj4+XseOHVNmZqZmz5590yeHF8vMzNTHH3+smJgY5ebmKiwsTJMnT1ZoaGiJsXv27NFnn32mxMRE1a1bV4MGDdITTzwhd3cuugEAABvD0t69e/Xhhx+qTp06GjVqlO677z75+fnpypUr+uGHH7Rq1Sr95S9/UePGjdWpU6dyr5+enq6oqCgFBASoRYsWOnToUJnnFhUVadasWTp9+rQefvhh1alTR1999ZWmT5+uTz75RE2aNDGP3b9/v/74xz+qTZs2mj59us6cOaPly5fr6tWrmjFjRrnrBgAA1Y9NYSk6Olq1a9fWp59+qoYNG5rbGzVqpPDwcPXt21fjx49XdHS0TWHJz89Pa9eulZ+fnxISEjRx4sQyz921a5eOHDmiN954Qz169JAk9erVS48++qg+++wzvfrqq+axH330kZo3b6733nvPfCWpZs2a+vzzzzVy5Eg1bdq03LUDAIDqxaYneJ88eVI9e/a0CEr/LSAgQD179tSJEydsKsrT01N+fn42zd29e7fq16+vBx980NxWt25d9ezZU3v27FFeXp4k6ezZszp79qyGDh1qcctt2LBhMplM2rVrl03fDwAAqhebwlJ+fr68vb0Nx3h7eys/P9+mom7FiRMnFBISIldXy0MLCwvT9evXde7cOfM4SSX2Mfn7+6tBgwY6efKk1fVTUlJ0/Phx8z+JiYkVcBQAAMBZ2HQbrkmTJoqNjdWECROsboQuKCjQ3r17LfYHVZYrV66odevWJdqLr1SlpqaqefPmSk1NtWj/7dji/t9av369oqKi7FcwAABwajaFpf79++ujjz7SCy+8oEmTJllcnUlISNDSpUt17tw5TZ482W6FllVubq7VF/gWt+Xm3nj+SPHtuNLGZmdnW10/IiJCXbp0MX9OTEzUvHnzbrluAADgnGwKSyNHjtSPP/6o2NhY/eEPf5CXl5fq1aunq1evKjc3VyaTSV27dtXIkSPtXe9NeXl5mYPQfytu8/LykvSfkFTa2OJxv+Xv7y9/f397lQsAAJycTWHJzc1Nb775pjZt2qRNmzbp1KlTSk5Olo+Pj8LDwzVgwAD179/f3rWWSf369a3eQvvtbbf/vi0XEBBQYmxYWFgFVwoAAKqCW3ry4oABAzRgwAB71WIXISEhOnz4sIqKiiw2eR87dkw1atQw76MKCQmRJB0/ftzipb8pKSm6fPmyIiIiKrdwAADglGz6NZyzSElJUWJiogoK/vPCyO7du+vKlSuKiYkxt6WlpWnnzp3q3Lmz+fZbs2bNdOedd+rrr79WYWGheexXX30lFxcXde/evfIOBAAAOC2bn+D97bff6rnnnrO6fyclJUWLFi3S0KFD9cADD9hU2BdffKGsrCzz7bPY2FhdunRJkjRixAj5+vpq6dKl2rRpk6Kjo83vouvRo4fWrFmjBQsW6OzZs+YneBcVFenJJ5+0+I7Jkydr9uzZmjFjhnr37q0zZ85o7dq1GjJkiO666y6b6gYAANWLTWFp7dq1SklJKXWjs7+/v5KSkrR27Vqbw1J0dLSSkpLMn2NiYsxXi/r16ydfX1+r89zc3PTOO+/oo48+0hdffKHc3Fy1bNlSs2fP1p133mkxtnPnzpo3b56ioqK0ePFi1alTR2PGjNG4ceNsqhkAAFQ/NoWlU6dOqXPnzoZjwsLCtG/fPpuKkqRVq1bddMycOXM0Z86cEu21atXSrFmzNGvWrJuu0a1bN3Xr1s2mGgEAQPVn056lzMxM1a1b13BMnTp1lJ6ebsvyAAAATsOmsFSnTh3za0NKc+7cOdWqVcumogAAAJyFTWGpdevW2rt3r06fPm21/9SpU4qNjVWbNm1upTYAAACHs2nP0mOPPaaYmBhNmTJFDz/8sNq1a6cGDRro8uXL+u677xQdHS0XFxeNGTPG3vUCAABUKpvCUvPmzfXyyy9rwYIFioqKsnixrMlkkre3t1577TU1b97cXnUCAAA4hM1P8O7Ro4dat26tjRs3KiEhQVlZWapVq5ZatmypgQMH3nQDOAAAQFVwS687qVevnh599FF71QIAAOB0qvTrTgAAACoaYQkAAMAAYQkAAMAAYQkAAMAAYQkAAMAAYQkAAMAAYQkAAMBAmZ6zlJycbPMXBAQE2DwXAADA0coUlkaNGiUXF5dyL+7i4qKdO3eWex4AAICzKFNY6t+/f4mwdOHCBR0+fFi+vr5q0aKF6tevrytXrujUqVPKyspSq1atdMcdd1RI0QAAAJWlTGFpzpw5Fp9//vlnTZkyRWPGjNGYMWPk7e1t7svJydE//vEPffXVV5oxY4Z9qwUAAKhkNr0bbsmSJWrZsqUmTJhQos/b21sTJ05UQkKCPv74Y7311lu3XCQAoHxyruZqxdQdji6jzDxquKtdZIiadQx0dClACTaFpSNHjmjYsGGGY8LCwrR27VqbigIA2MajhrukXJlMUvaVXEeXUw65Orj6JGEJTsmmsFRUVKTz588bjvn1119lMplsKgoAYJt2kSE6uPqk8q8XOLqUMsu5eiPcVaWacXuxKSy1bt1au3fv1vbt29W7d+8S/du2bVNMTIw6dux4ywUCAMquWcfAKnd1ZsXUHVXsKhhuNzaFpUmTJunw4cOaO3euVqxYod/97neqV6+erl69qp9++kmnT59WzZo19fTTT9u7XgAAgEplU1i666679Je//EV//vOf9eOPP+rUqVMW/a1bt9Zzzz2nu+66yx41AgAAOIxNYUmSgoOD9f777ys5OVmnT59WVlaWfH191bx5c57aDQAAqg2bw1KxgIAAwhEAAKi2biks5efn6+DBg/rll190/fp1jR07VpKUm5ur7Oxs1alTR66uvKsXAABUXTaHpT179mjhwoVKS0uTyWSSi4uLOSydPn1akydP1h//+Ef17dvXbsUCAABUNpsu+/z000969dVX5eHhoWeeeUZ9+vSx6A8PD1dQUJB2795tlyIBAAAcxaYrS3//+9/l6+urTz75RHXr1lVGRkaJMaGhoTp27NgtFwgAAOBINl1Zio+PV9euXVW3bt1SxzRs2FBXrlyxtS4AAACnYFNYys/PV82aNQ3HZGVlycXFxaaiAAAAnIVNYemOO+5QQkKC4ZijR4/qzjvvtKkoAAAAZ2FTWOrevbuOHDmiDRs2WO3/17/+pZ9//lm9evW6peIAAAAczaYN3g8//LB2796td955R9u2bVNeXp4kacmSJTp69KiOHDmiFi1aaPjw4XYtFgAAoLLZFJZq1qypDz/8UIsWLdLOnTtVVFQkSVq5cqVcXFzUs2dPPf/88/L09LSpqLy8PC1btkxbtmxRZmammjdvrvHjx6t9+/aG80aNGqWkpCSrfUFBQfrXv/5l/vzggw9aHTdx4kSNGTPGproBAED1Y/NDKWvVqqVXX31V06dPV0JCgjIyMuTj46OWLVuqfv36t1TUggULtGvXLkVGRqpx48bauHGjZs6cqcWLF6tVq1alznvmmWeUk5Nj0ZaUlKRPP/3UatBq166dBgwYYNEWEhJyS7UDAIDq5ZbfDVenTh117NjRHrVIuvFYgu3bt2vSpEl65JFHJEn9+/fXuHHjtGTJEi1ZsqTUud26dSvR9ve//12SrD5JvEmTJurXr5+dKgcAANWRTRu8e/ToYQ4hpVm+fLl69uxZ7rV3794tNzc3RUREmNu8vLw0ePBgHT16VMnJyeVab9u2bQoMDNTvfvc7q/25ubnKzc0td50AAOD2YFNYMplMMplMZRpXXidPnlTjxo3l4+Nj0R4WFiZJOnXqVJnXOnHihBITE0u8jqXYpk2b1K9fP/Xt21ePP/64tm7dWu56AQBA9XbLt+FKk5aWJi8vr3LPS01NlZ+fX4n24raUlJQyr1Ucfqzdgrv33nvVs2dPBQYGKjU1VV9++aXmzp2ra9eu6aGHHip1zZSUFKWmppo/JyYmlrkeAABQ9ZQ5LG3atMni88mTJ0u0SVJRUZEuXbqkzZs3q1mzZuUuKDc3Vx4eHiXai39ZV9ZbZkVFRdqxY4dCQkJ01113lej/6KOPLD4PGjRI48eP19KlSzVw4MBSg9769esVFRVVphoAAEDVV+awtGDBAvPrS1xcXBQbG6vY2NgS44pvvXl5een3v/99uQvy8vJSfn5+ifbiZzmV9WpVXFycLl++rMjIyDKN9/Dw0PDhw/Xee+/p+PHjpf7qLiIiQl26dDF/TkxM1Lx588r0HQAAoOopc1h66aWXzP/+1ltvqWvXruratWuJcW5ubqpVq5buvfde1apVq9wF+fn56fLlyyXai299+fv7l2mdrVu3ytXVtdT9StY0bNhQkpSRkVHqGH9//zLXAAAAqr4yh6WBAwea/z0uLk7dunWzGpZuVYsWLXTo0CFdu3bNYpN3fHy8uf9m8vLytHv3brVp06ZcwebChQuSpLp165avaAAAUG3Z9Gu42bNnV0hQkm48lqCwsFDr1683t+Xl5WnDhg0KDw9XQECAJCk5ObnUzdX79+9XVlaW1Y3d0o3N57+VnZ2tNWvWqE6dOgoNDb31AwEAANWCTb+G27t3r7799ls999xzVq/cpKSkaNGiRRo6dKgeeOCBcq0dHh6unj17aunSpUpLS1NQUJA2bdqkpKQkzZo1yzxu/vz5iouLU0xMTIk1tm7dKk9PT3Xv3t3qd3z55Zfas2ePOnfurICAAKWmpmrDhg1KTk7WH//4R6sbzAEAwO3JprC0du1apaSklHqLy9/fX0lJSVq7dm25w5IkzZkzRwEBAdq8ebOysrIUHByst99+W23atLnp3GvXrmnfvn164IEH5Ovra3XM7373Ox05ckTffPONMjIyVKNGDYWFhWnWrFm6//77y10vAACovmwKS6dOnVLnzp0Nx4SFhWnfvn02FeXl5aXJkydr8uTJpY55//33rbb7+Pho27Zthuu3b9/+pi/lBQAAkGzcs5SZmXnTTdB16tRRenq6LcsDAAA4DZvCUp06dXTu3DnDMefOnbPp0QEAAADOxKaw1Lp1a+3du1enT5+22n/q1CnFxsaWaY8RAACAM7Npz9Jjjz2mmJgYTZkyRQ8//LDatWunBg0a6PLly/ruu+8UHR0tFxcXjRkzxt71AgAAVCqbwlLz5s318ssva8GCBYqKirJ4V5rJZJK3t7dee+01NW/e3F51AgAAOIRNYUm68fDI1q1ba+PGjUpISFBWVpZq1aqlli1bauDAgTwFGwAAVAs2hyVJqlevnh599FF71QIAAOB0bNrg/VsZGRlKTk62x1IAAABOxeYrS1lZWVq2bJl27Nih9PR0ubi4aOfOnZJuvPT2s88+0/jx43nPGgAAqNJsurKUkZGhp59+Wl9++aUaNmyopk2bymQymfubN2+uI0eOaOvWrXYrFAAAwBFsCkufffaZzp07p9dee02ffPKJevToYdHv5eWl1q1b64cffrBHjQAAAA5jU1iKjY1Vp06d1KtXr1LHBAYG6vLlyzYXBgAA4AxsCkupqam66667DMd4eHgoJyfHluUBAACchk1hqXbt2rp06ZLhmF9++UV+fn42FQUAAOAsbPo1XOvWrRUbG6tLly6pYcOGJfrPnj2r//u//9OgQYNuuUAAwO0h52quVkzd4egyysWjhrvaRYaoWcdAR5eCCmRTWHr88ce1Z88eTZkyRRMmTFB6erqkGyHpyJEj+vTTT+Xp6amHH37YrsUCAKofjxruknJlMknZV3IdXU455erg6pOEpWrO5nfD/e///q/mz5+vN998U9KNd8KNGzdOJpNJNWvW1P/+7/+qSZMmdi0WAFD9tIsM0cHVJ5V/vcDRpZRLztUbAa+q1Y3ys/mhlF27dlV0dLQ2bdqk+Ph4ZWRkyMfHR+Hh4bwbDgBQZs06BlbJKzMrpu6oglfCYItbejdc7dq1NWrUKHvVAgAA4HTs8m64goICZWZmqqCAS5EAAKB6sfnKUmFhob744gtt3LhRZ8+elclkkouLi+666y4NHDhQw4cPl7v7LV24AgAAcDib0kx2drZeeOEFxcfHy8XFRQ0bNlT9+vV15coVnT17Vh999JF2796thQsXytvb2941AwAAVBqbwtLf/vY3HT16VH369NHEiRMVEBBg7ktOTtZf//pXbd++XcuWLdPUqVPtViwAAEBls2nP0s6dOxUaGqpXXnnFIihJUkBAgF599VWFhoZq586ddikSAADAUWwKS+np6WrXrp3hmPvvv18ZGRk2FQUAAOAsbApLjRs31tWrVw3HpKWlKSgoyKaiAAAAnIVNYWnkyJHasWOHfv75Z6v9p0+f1o4dOxQZGXlLxQEAADiaTRu8GzdurLZt22rChAkaMGCAWrVqpXr16unq1av68ccftXnzZnXo0EFBQUGKi4uzmNumTRs7lA0AAFA5bApL06dPl4uLi0wmk77++mt988035j6TySRJ2rt3r/bu3Vti7q5du2yrFAAAwAFsCktjx46Vi4uLvWsBAABwOjaFpSeffNLedQAAADglu7wbrjRFRUUVuTwAAECFsyks/elPf1JeXp7hmIsXL/L0bgAAUOXZFJbWrVuniRMnlvrogO3bt+upp57SsWPHbqk4AAAAR7MpLE2YMEHnzp3TxIkT9eWXX5rbc3Jy9Oabb2ru3Lny8vLSu+++a7dCAQAAHMGmDd5jxoxR27ZtNXfuXL3//vs6cOCAhg8frj//+c86f/68OnXqpJdeekl169a1c7kAAACVy6awJEnh4eFatmyZFi1apC1btmj//v3y9PTUs88+q2HDht1SUXl5eVq2bJm2bNmizMxMNW/eXOPHj1f79u0N5/3tb39TVFRUiXZPT09t27atRPs333yjlStXKikpSQ0aNNDIkSM1YsSIW6odAABULzaHJUnKzs7WpUuXJN14GKWrq6tq1Khxy0UtWLBAu3btUmRkpBo3bqyNGzdq5syZWrx4sVq1anXT+TNmzJC3t7f5s6trybuN69at03vvvafu3btr9OjROnz4sBYvXqzr16/rscceu+VjAAAA1YPNYWnPnj16++23lZGRof/5n/9Rt27d9M477+jtt9/WgQMH9MILL8jHx6fc68bHx2v79u2aNGmSHnnkEUlS//79NW7cOC1ZskRLliy56Rrdu3c3vAWYm5urTz/9VJ06ddLcuXMlSUOHDlVRUZGWL1+uiIgI1apVq9y1AwCA6sfmRwe8/PLLkqT58+fr+eefV/v27fXZZ5+pe/fu2rFjh37/+9/rp59+Kvfau3fvlpubmyIiIsxtXl5eGjx4sI4ePark5OQyrXPt2jXzq1d+64cfflB6eroeeughi/Zhw4YpJydH+/btK3fdAACgerL50QH33XefPvvsM3Xt2tXc7uvrq9dff10vvvii0tPTNX369HKvffLkSTVu3LjEVamwsDBJ0qlTp266xujRozVw4EANGDBAc+fO1ZUrV0p8hyS1bNnSoj00NFSurq46ceJEuesGAADVk0234SZOnKhHH3201PfDDRkyRK1bt9Ybb7xR7rVTU1Pl5+dXor24LSUlpdS5tWrV0vDhw3XPPffIw8NDhw8f1tq1a3Xs2DF98skn5gCWmpoqNzc31atXz2K+h4eHateurdTU1FK/IyUlxaI/MTGxXMcHAACqFpvCUlk2QDdp0qRM+4t+Kzc3Vx4eHiXaPT09zf2liYyMtPjco0cPhYWFae7cuVq7dq3GjBljXsPd3fqhe3p6Gn7H+vXrrf7iDgAAVE+39Gs4I/n5+crLyys1lJTGy8tL+fn5JdqLX6/i5eVVrvX69u2rv/zlL/r+++/NYcnLy0sFBQVWx+fl5Rl+R0REhLp06WL+nJiYqHnz5pWrJgAAUHWUec/S6NGjtWbNGou2AwcO6MMPP7Q6/vPPP9fgwYPLXZCfn5/V22DFbf7+/uVes2HDhsrIyLD4jsLCQl29etViXH5+vjIyMqzeBizm7++v0NBQ8z9NmzYtdz0AAKDqKPNln6SkJGVlZVm0HT16VGvWrLHrC3NbtGihQ4cO6dq1axabvOPj48395WEymZSUlKSQkBBzW/G/JyQkqFOnTub2hIQEFRUVWYwFAMBIztVcrZi6w9FllJlHDXe1iwxRs46Bji6lyqiw23C26tGjh1auXKn169ebn7OUl5enDRs2KDw8XAEBAZKk5ORkXb9+3eLKTlpaWonnK3311VdKS0tTx44dzW1t27ZV7dq1tW7dOouwtG7dOtWoUcOiDQAAazxquEvKlckkZV8pfa+r88nVwdUnCUvl4HRhKTw8XD179tTSpUuVlpamoKAgbdq0SUlJSZo1a5Z53Pz58xUXF6eYmBhzW2RkpHr16qXg4GB5enrqp59+0vbt2xUSElLiuU1PPfWUFi1apFdffVUdOnTQjz/+qC1btmjChAmqXbt2pR4zAKDqaRcZooOrTyr/uvU9sM4o5+qNcFeVanYGTheWJGnOnDkKCAjQ5s2blZWVpeDgYL399ttq06aN4by+ffvqyJEj2r17t/Ly8hQQEKBHHnlETzzxRInXsAwbNkzu7u6Kjo5WbGysGjZsqKlTp5b4RR0AANY06xhY5a7OrJi6o4pdBXMOThmWvLy8NHnyZE2ePLnUMe+//36JtpkzZ5bre4YOHaqhQ4eWuz4AAHD7sOkJ3gAAALeLcl1Z2rJli44ePWr+fP78eUnSiy++WGJscR8AAEBVVq6wdP78eash6MCBA1bHl/Y6FAAAgKqizGEpOjq6IusAAABwSmUOS40aNarIOgAAAJwSG7wBAAAMEJYAAAAMEJYAAAAMOOVDKXHDmf0X9f2aqvcofQAAqhPCkhP7fs1JpV+45ugybHLjBZMAAFR9/I3mxIqvKLm4SN71vBxcTdl51HBXu8gQR5cBAIBdEJaqAO96Xnr0w16OLgMAgNsSG7wBAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMEJYAAAAMuDu6AGvy8vK0bNkybdmyRZmZmWrevLnGjx+v9u3bG87bvXu3duzYoYSEBF25ckUNGzZUp06dNHbsWNWqVcti7KhRo5SUlFRijYiICL3wwgt2PR4AAFB1OWVYWrBggXbt2qXIyEg1btxYGzdu1MyZM7V48WK1atWq1HkLFy6Un5+f+vXrp4CAAJ0+fVpr167V/v37tWzZMnl5eVmMDwkJ0ejRoy3aGjduXCHHBAAAqianC0vx8fHavn27Jk2apEceeUSS1L9/f40bN05LlizRkiVLSp37xhtv6L777rNoCw0N1ZtvvqmtW7dqyJAhFn3+/v7q16+f/Q8CAABUG063Z2n37t1yc3NTRESEuc3Ly0uDBw/W0aNHlZycXOrc3wYlSXrwwQclSWfPnrU6Jz8/Xzk5ObdWNAAAqLac7srSyZMn1bhxY/n4+Fi0h4WFSZJOnTqlgICAMq+XmpoqSapbt26Jvh9++EH9+vVTYWGhGjVqpMjISEVGRtpePAAAqHacLiylpqbKz8+vRHtxW0pKSrnWW7Fihdzc3NS9e3eL9uDgYLVq1UpNmjRRRkaGNm7cqA8++EApKSmaNGlSqeulpKSYA5gkJSYmlqseAABQtThdWMrNzZWHh0eJdk9PT3N/WW3dulXffvutHnnkETVp0sSi76233rL4PGjQIL344otatWqVRowYoYYNG1pdc/369YqKiipzDQAAoGpzurDk5eWl/Pz8Eu15eXnm/rL48ccf9fbbb6tDhw6aMGHCTce7uLho1KhROnDggOLi4krd+B0REaEuXbqYPycmJmrevHllqgkAAFQ9TheW/Pz8dPny5RLtxbe+/P39b7rGqVOnNHv2bAUHB+uNN96Qu3vZDrP4alJGRkapY/z9/ctUAwAAqB6cLiy1aNFChw4d0rVr1yw2ecfHx5v7jZw/f14vvPCC6tWrp3feeUc1a9Ys83dfuHBBkvXN4AAAVBc5V3O1YuoOR5dRZh413NUuMkTNOgY65PudLiz16NFDK1eu1Pr1683PWcrLy9OGDRsUHh5u/iVccnKyrl+/rqZNm5rnpqamasaMGXJ1ddXChQtLDT0ZGRny8fGRm5ubua2goED//Oc/5eHhYfURBAAAVHUeNdwl5cpkkrKvlH0PsOPl6uDqk4SlYuHh4erZs6eWLl2qtLQ0BQUFadOmTUpKStKsWbPM4+bPn6+4uDjFxMSY21588UVduHBBjzzyiH766Sf99NNP5r569eqZX5cSGxur5cuXq3v37goMDFRmZqa2bt2qn3/+WRMnTrT6azwAAKq6dpEhOrj6pPKvFzi6lDLLuXoj3DmyZqcLS5I0Z84cBQQEaPPmzcrKylJwcLDefvtttWnTxnDeqVOnJEn/+te/SvS1adPGHJaCg4PVtGlTbd26VWlpaXJ3d1dISIhef/119ezZ0+7HAwCAM2jWMdBhV2dstWLqDodfBXPKsOTl5aXJkydr8uTJpY55//33S7T991UmI6GhoSUeHQAAAGCN073uBAAAwJkQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAy4O7oAa/Ly8rRs2TJt2bJFmZmZat68ucaPH6/27dvfdO7ly5f14Ycf6rvvvlNRUZHuu+8+PfPMM7rjjjtKjP3mm2+0cuVKJSUlqUGDBho5cqRGjBhREYcEAACqKKe8srRgwQKtWrVKffv21bRp0+Tq6qqZM2fq8OHDhvOys7M1ffp0xcXFacyYMXryySd18uRJPfPMM0pPT7cYu27dOr3zzjtq1qyZpk+frnvvvVeLFy/WP//5z4o8NAAAUMU43ZWl+Ph4bd++XZMmTdIjjzwiSerfv7/GjRunJUuWaMmSJaXO/eqrr/Trr7/qr3/9q8LCwiRJHTt21Lhx4xQdHa2JEydKknJzc/Xpp5+qU6dOmjt3riRp6NChKioq0vLlyxUREaFatWpV8JECAICqwOmuLO3evVtubm6KiIgwt3l5eWnw4ME6evSokpOTS527a9cutWzZ0hyUJKlp06Zq27atdu7caW774YcflJ6eroceeshi/rBhw5STk6N9+/bZ74AAAECV5nRh6eTJk2rcuLF8fHws2osD0KlTp6zOKyoq0pkzZ9SyZcsSfWFhYTp//ryys7PN3yGpxNjQ0FC5urrqxIkTt3wcAACgenC623Cpqany8/Mr0V7clpKSYnVeRkaG8vLybjr3zjvvVGpqqtzc3FSvXj2LcR4eHqpdu7ZSU1NLrS8lJcWiPzEx8eYHBQAAqiynC0u5ubny8PAo0e7p6WnuL22epDLNzc3Nlbu79UP39PQs9Tskaf369YqKiir9AAAAQLXidGHJy8tL+fn5Jdrz8vLM/aXNk1SmuV5eXiooKLC6Tl5eXqnfIUkRERHq0qWL+XNiYqLmzZtX6vhbUbOOl8V/AgBwu3GGvwudLiz5+fnp8uXLJdqLb335+/tbnVe7dm15enpavYX227l+fn4qLCzU1atXLW7F5efnKyMjw+qtvGL+/v6l1mBvD83vcvNBAABUY87wd6HTbfBu0aKFfv31V127ds2iPT4+3txvjaurq4KDg5WQkFCiLz4+XnfccYdq1qwpSQoJCZGkEmMTEhJUVFRk7gcAAHC6sNSjRw8VFhZq/fr15ra8vDxt2LBB4eHhCggIkCQlJyeX2FzdvXt3JSQkWISgX375RYcOHVKPHj3MbW3btlXt2rW1bt06i/nr1q1TjRo11KlTpwo4MgAAUBU53W248PBw9ezZU0uXLlVaWpqCgoK0adMmJSUladasWeZx8+fPV1xcnGJiYsxtw4YN0zfffKNZs2bp4Ycflpubm1atWqV69erp4YcfNo/z8vLSU089pUWLFunVV19Vhw4d9OOPP2rLli2aMGGCateuXanHDAAAnJfThSVJmjNnjgICArR582ZlZWUpODhYb7/9ttq0aWM4r2bNmlq8eLE+/PBDLV++3PxuuKlTp6pu3boWY4cNGyZ3d3dFR0crNjZWDRs21NSpUxUZGVlxBwYAAKocF5PJZHJ0EVXZ8ePHNWHCBH3yyScKDQ11dDkAAMDOnG7PEgAAgDMhLAEAABggLAEAABggLAEAABggLAEAABggLAEAABggLAEAABggLAEAABhwyid4VyW5ubmSVOI9dQAAwPk1bdpUNWrUMBxDWLpFSUlJkqR58+Y5uBIAAFBeZXkDB687uUVpaWk6cOCAvvrqK02fPr3M8z744AM988wzhmMSExM1b948vfzyy2ratOmtllotlOXPzVEcUVtFfKe91ryVdWyZW945nIO2ceZzUKr8+irq+26H87CsYyv6POTKUiWoW7eu+vXrpx07dpTr3XC+vr5lHt+0aVPeO/f/lefPrbI5oraK+E57rXkr69gyt7xzOAdt48znoFT59VXU990O52F513fkecgGbzvp06dPhY7HDc785+aI2iriO+215q2sY8tczsHK4ex/bpVdX0V93+1wHjr7/y39N27DObHjx49rwoQJZbqfCsD+OAcBx3OG85ArS07Mz89P48aNk5+fn6NLAW5LnIOA4znDeciVJQAAAANcWQIAADBAWAIAADBAWKrC8vLy9NZbb2nkyJEaMGCAnn76aR05csTRZQG3lXfffVcPPfSQBgwYoLFjxyo2NtbRJQG3rSNHjqh79+76+9//btd12bNUheXk5Cg6OloDBw5UgwYNtHPnTv35z39WdHS0atas6ejygNtCYmKiAgMD5enpqWPHjun555/XypUrVadOHUeXBtxWioqKNHnyZJlMJnXu3Fljx46129pcWarCvL29NW7cOAUEBMjV1VW9e/eWu7u7zp075+jSgNtG06ZN5enpKUlycXFRfn6+UlJSHFwVcPv5+uuvFRYWViFP+eYJ3pUoOztbK1euVHx8vI4dO6bMzEzNnj1bAwcOLDE2Ly9Py5Yt05YtW5SZmanmzZtr/Pjxat++fanrnzt3TpmZmQoKCqrIwwCqrIo6B//0pz9pw4YNysvL0wMPPKDg4ODKOBygSqqI8zA9PV2rV6/WkiVL9MEHH9i9Zq4sVaL09HRFRUUpMTFRLVq0MBy7YMECrVq1Sn379tW0adPk6uqqmTNn6vDhw1bH5+bmat68eXrsscfk6+tbEeUDVV5FnYPPP/+8Nm/erEWLFql9+/ZycXGpqEMAqryKOA8/+eQTRUZGqlatWhVTtAmVJjc315SSkmIymUymY8eOmbp162basGFDiXFHjx41devWzbRixQpz2/Xr100PP/yw6emnny4xPj8/3zRz5kzT66+/bioqKqq4AwCquIo6B//brFmzTHv37rVv4UA1Yu/z8Pjx46annnrKVFBQYDKZTKb58+eboqKi7FozV5YqkaenZ5meQLp79265ubkpIiLC3Obl5aXBgwfr6NGjSk5ONrcXFRVp3rx5cnFx0Zw5c/hftICBijgHf6uwsFDnz5+3S71AdWTv8zAuLk7nzp3TiBEj9NBDD2nHjh1asWKFFixYYLea2bPkhE6ePKnGjRvLx8fHoj0sLEySdOrUKQUEBEiSFi5cqNTUVC1cuFDu7vzXCdhDWc/BrKws7du3T126dJGnp6f+/e9/69ChQ5o4caIjygaqlbKehxEREerdu7e5//3331dgYKAee+wxu9XC365OKDU11WrqLm4r/qVNUlKSvvnmG3l6elok73feeUetW7eunGKBaqis56CLi4u++eYbLVq0SCaTSUFBQXrllVcUEhJSqfUC1VFZz8MaNWqoRo0a5n4vLy95e3vbdf8SYckJ5ebmysPDo0R78c+Tc3NzJUmNGjVSTExMpdYG3A7Keg76+Pho8eLFlVobcLso63n4W3PmzLF7LexZckJeXl7Kz88v0Z6Xl2fuB1BxOAcBx3Om85Cw5IT8/PyUmppaor24zd/fv7JLAm4rnIOA4znTeUhYckItWrTQr7/+qmvXrlm0x8fHm/sBVBzOQcDxnOk8JCw5oR49eqiwsFDr1683t+Xl5WnDhg0KDw83/xIOQMXgHAQcz5nOQzZ4V7IvvvhCWVlZ5suIsbGxunTpkiRpxIgR8vX1VXh4uHr27KmlS5cqLS1NQUFB2rRpk5KSkjRr1ixHlg9UeZyDgONVtfPQxWQymSr1G29zo0aNUlJSktW+6OhoBQYGSrqxy7/4fThZWVkKDg7W+PHj1aFDh8osF6h2OAcBx6tq5yFhCQAAwAB7lgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgAAAAwQlgDg/3vwwQct/snNzTX3bdy4UQ8++KA2btzowAr/Y926dRa1vvnmm44uCai23B1dAIDbz8WLFzV69GjDMY0aNdKqVasqqSLL7x0wYIAkyc3NrUK/68CBA3rhhRfUvn17vffee4Zj33jjDW3btk2vvPKK+vbtq9DQUI0bN05ZWVlas2ZNhdYJ3O4ISwAcJigoSH379rXa5+vrW8nV3NCoUSM9+eSTlfJd7dq1U0BAgL7//nslJycrICDA6risrCz9+9//lq+vrx588EFJUsuWLdWyZUtdvHiRsARUMMISAIcJCgqqtGDijFxdXTVw4EBFRUVp06ZNGjt2rNVx27ZtU25urgYNGiQvL69KrhIAe5YAVAkPPvigpk2bpsuXL+uNN97Q0KFD1b9/f82cOVMXLlyQJJ09e1Zz5szR4MGD1b9/f73yyiu6cuVKhdZ16dIljR07Vn369NGuXbvM7VevXtUHH3ygRx55RL1799bQoUP18ssv68yZMxbzBw0aJBcXF23cuFEmk8nqd2zYsEGSNHjw4Ao7DgClIywBqDIyMzM1ZcoUXbx4Uf3799d9992n/fv36/nnn9eZM2c0efJk5eTkaNCgQWrZsqV2796t119/vcLqOXv2rCZPnqxLly7p3XffVY8ePSRJ58+f1/jx47V69WrdcccdGj58uB544AEdOHBAkyZNUnx8vHmNRo0a6f7779eFCxd06NChEt9x5swZJSQkKCQkRHfffXeFHQuA0nEbDoDDnD9/Xn/729+s9t1zzz3q2LGjRdvp06c1atQoTZ061dz2pz/9SV999ZWmTp2q3//+94qMjJQkmUwmzZo1S/v379fx48cVGhpq19qPHj2qWbNmyd3dXR988IFatGhh7ps/f76uXLmihQsXqkOHDub2J554QhMmTNA777yjqKgoc/vgwYN18OBBbdiwQW3btrX4Hq4qAY7HlSUADnP+/HlFRUVZ/ef//u//Soz39vbW+PHjLdp69+4tSapTp45GjhxpbndxcTH3nT592q5179u3T88995xq1aqljz76yCIonThxQkeOHFH//v0tgpIkNWnSREOGDNGZM2csbsd169ZNderU0e7du3Xt2jVze0FBgbZs2SJPT89SN8IDqHhcWQLgMB06dNDChQvLPL5x48aqUaOGRZufn58kKTg4WC4uLlb7UlJSbrHS/9i5c6e+++47NW/eXO+++67q1atn0V98i+3q1atWr5r98ssv5v8MDg6WJHMYWrNmjbZt26b/+Z//kSTFxsYqLS1Nffr0Ua1atex2DADKh7AEoMrw8fEp0Vb8LCSjvoKCArvVcPToURUWFqpVq1YlgpIkZWRkSLpx9Wnfvn2lrpOTk2PxefDgwVqzZo02bNhgDkvcggOcA2EJAMph4sSJ2rNnj9asWSM3NzdNmTLFor84tE2fPl0jRowo87rNmzdXy5YtdezYMf3888+qVauWDhw4oMDAwBL7mABULvYsAUA5eHp6av78+erUqZOio6P14YcfWvSHhYVJunEFqryKryB9++232rx5swoLC82PFgDgOIQlACgnT09PzZs3T507d9aqVav0wQcfmPvCw8MVHh6u7du3a/v27SXmFhUVKS4uzuq6ffr0UY0aNbRlyxZt2LBBrq6u5levAHAcbsMBcBijRwdI0mOPPea0T6z28PDQ3Llz9eqrr2r16tUymUyaNm2aJOnVV1/Vs88+q9dff11r1qxRSEiIvLy8dOnSJR05ckTp6enatm1biTV9fHzUvXt3bd68WWlpaerYsWOpr0ABUHkISwAcpvjRAaWJjIx02rAk/Scwvfbaa1qzZo1MJpOmT5+uO+64Q8uWLVN0dLT+/e9/a+PGjXJ1dZWfn59at25tfnilNYMHD9bmzZsl3Xi6NwDHczGV9nx9ALjNPPjgg2rTpo3ef/99R5dSZhcvXtTo0aM1YMAAzZkzx9HlANUSV5YA4L/ExcXpwQcflCRt3brVaa9srVu3Tu+9956jywBuC4QlAPj/xo0bZ/G5+DlNzig0NNSi3pCQEMcVA1Rz3IYDAAAwwKMDAAAADBCWAAAADBCWAAAADBCWAAAADBCWAAAADBCWAAAADBCWAAAADBCWAAAADBCWAAAADPw/UrlFIdys1ZIAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "expectation = psr.get_expectation(spectrum)\n", "\n", "ax, plot = expectation.project('Em').plot()\n", "\n", "ax.set_ylabel('Expected counts')" ] }, { "cell_type": "markdown", "id": "925a766d-e677-4df6-88e8-eb4df1cd1fd3", "metadata": {}, "source": [ "## XSPEC support" ] }, { "cell_type": "markdown", "id": "145c3988-a437-42df-90c6-ac25384dd849", "metadata": {}, "source": [ "You can also convert the point source response to XSPEC readable files (arf, rmf and pha) if you want to do spetral fitting or simulation in XSPEC. See the `SpacecraftFile` class functions `get_arf()`, `get_rmf()` and `get_pha()`, respectively." ] }, { "cell_type": "markdown", "id": "6ba9dcf2-4372-4e95-8dec-7c8135931837", "metadata": {}, "source": [ "
\n", "Note: This functionality will be moved to the DetectorResponse class in the near future.
" ] }, { "cell_type": "code", "execution_count": 25, "id": "3c260ffd-fb4c-43cb-8795-94781b5efdb7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Getting the effective area ...\n", "Getting the energy redistribution matrix ...\n" ] } ], "source": [ "ori.get_psr_rsp(response = response_path);" ] }, { "cell_type": "code", "execution_count": 26, "id": "e5a5d7a2-5a80-443d-bd10-4ac17bc59c1e", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ori.get_arf()\n", "ori.plot_arf()" ] }, { "cell_type": "code", "execution_count": 27, "id": "45ce929d-2a45-442c-b3b7-249677521675", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\n", "WARNING VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n", "\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ori.get_rmf()\n", "ori.plot_rmf()" ] }, { "cell_type": "code", "execution_count": null, "id": "10c4fd3c-8b6f-4c63-b270-2f9dd9aced49", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:cosi_nomegalib]", "language": "python", "name": "conda-env-cosi_nomegalib-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": "3.9.6" } }, "nbformat": 4, "nbformat_minor": 5 }