{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Polarisation examples\n", "\n", "Below are a couple of examples of how to use `WODEN` to simulation polarisation data. Both examples include details on how to generate the FITS-style sky model, how t run the simulation, and check the results. This documentation is simply the notebook found in `WODEN/examples/polarisation/polarisation_examples.ipynb`. If you want to run it, you'll need a working `WODEN` installation, `WSClean` to do the imaging, and the `pygdsm` package (I install via `pip install git+https://github.com/telegraphic/pygdsm`) to generate the sky model.\n", "\n", "Big shout out to Emil for all the help in getting Jack to (kind of) understanding polarisation, and for the RM synthesis code.\n", "\n", "Apologies, I haven't worked out how to get outputs from cells to be scrollable in the online documentation, so please just scroll past the reams of output text to get to plots.\n", "\n", "\n", "\n", "## Southern Hotspot of PKS J0636−2036\n", "\n", "This is an example of a real source, details of which can be found in [O'Sullivan et al. (2018)](https://ui.adsabs.harvard.edu/abs/2018MNRAS.475.4263O/abstract). Assuming that the southern lobe is a single point source, at 216MHz, the component has the parameters (from Table 3 of this paper):\n", "\n", "Stokes $I = 13.9$ Jy (at reference 216MHz) \\\n", "Polarisation fraction $\\Pi = 0.092$ \\\n", "Spectral index $\\alpha = -0.815$ \\\n", "Faraday rotation $\\phi_\\textrm{RM} = 50.2 $ rad $m^{-2}$\n", "\n", "Ignoring the jump in frequency and instrument in the measurement (it's an example so we can do what we want) we can also say\n", "Intrinsic rotation angle $\\chi_0 = -71.1^{\\circ}$\n", "\n", "Furthermore, to make this more useful as an example, we'll say the source actually has a Stokes $V$ component that bounces around, so we can look at list-type polarisation data.\n", "\n", "First, we'll make a FITS table with these parameters. Then we'll stick it through `WODEN`, and process the outputs.\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "from astropy.table import Table, Column\n", "from astropy.coordinates import SkyCoord\n", "import numpy as np\n", "from subprocess import call\n", "from astropy.coordinates import EarthLocation\n", "from astropy import units as u\n", "from astropy.time import Time\n", "from astropy.io import fits\n", "import matplotlib.pyplot as plt\n", "from pygdsm import GlobalSkyModel16\n", "import healpy as hp\n", "from astropy.constants import c\n", "C = c.value" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "\n", "\n", "##Stick the source at location of it's name J0636−2036, good enough\n", "coord = SkyCoord(ra='6h36m', dec=\"-20d36m\")\n", "ra0 = coord.ra.deg\n", "dec0 = coord.dec.deg\n", "\n", "##These are the parameters for the source\n", "alpha = -0.815\n", "##hyperdrive/WODEN/LoBES catalogues are all referenced to 200MHz, so we need\n", "##to scale the stokesI flux\n", "stokesI = 13.9 * (200/216)**(alpha)\n", "pol_frac = 0.092\n", "phi_RM = 50.2\n", "chi_0 = np.radians(71.1)\n", "\n", "\n", "##The LoBES/hyperdrive/WODEN catalogues need a unique source ID (UNQ_SOURCE_ID),\n", "##a then edge component of that source needs a name (NAME)\n", "c_ids = Column(data=np.array(['PKS_J0636_source']), name='UNQ_SOURCE_ID', dtype='|S20')\n", "c_names = Column(data=np.array(['PKS_J0636_source_C00']), name='NAME', dtype='|S20')\n", "\n", "##Component position\n", "c_ras = Column(data=np.array([ra0]), name='RA')\n", "c_decs = Column(data=np.array([dec0]), name='DEC')\n", "\n", "##This says we have a point source\n", "c_comp_types = Column(data=np.array(['P'], dtype='|S1'), name=\"COMP_TYPE\", dtype='|S1')\n", "##This says we have a Stokes I power-law SED\n", "c_mod_types = Column(data=np.array(['pl'], dtype='|S3'), name=\"MOD_TYPE\", dtype='|S3')\n", "##Stokes I power law parameters\n", "c_stokes_I_ref = Column(data=np.array([stokesI]), name='NORM_COMP_PL')\n", "c_stokes_SI = Column(data=np.array([alpha]), name='ALPHA_PL')\n", "\n", "##This says we are using a polarisation fraction linear polarisation model\n", "c_lin_mod_type = Column(data=np.array(['pf'], dtype='|S3'), name='LIN_MOD_TYPE', dtype='|S3')\n", "##linear polarisation parameters\n", "c_lin_pol_frac = Column(data=np.array([pol_frac]), name='LIN_POL_FRAC')\n", "c_lin_pol_angle = Column(data=np.array([chi_0]), name='INTR_POL_ANGLE')\n", "c_rm = Column(data=np.array([phi_RM]), name='RM')\n", "\n", "##This says we are using a list-type circular polarisation model. The list info\n", "##goes into another table, see below.\n", "c_v_mod_type = Column(data=np.array(['nan'], dtype='|S3'), name='V_MOD_TYPE', dtype='|S3')\n", "\n", "##Stick all the columns in a list\n", "columns = [c_ids, c_names, c_ras, c_decs, c_comp_types, c_mod_types, c_stokes_I_ref, c_stokes_SI, c_lin_mod_type,c_lin_pol_frac, c_lin_pol_angle, c_rm, c_v_mod_type]\n", "\n", "##Make the main table\n", "main_table = Table(columns)\n", "\n", "##Now, make a table for Stokes V list-type SED. This goes in it's own table,\n", "##where the columns have the frequency in the title. We dupliate the NAME\n", "##column so that we can link the two tables\n", "\n", "v_cols = [c_names]\n", "\n", "v_freqs = np.arange(150, 250, 0.2) ##MHz\n", "v_fluxes = np.random.uniform(-0.5, 0.5, len(v_freqs))\n", "\n", "for freq, flux in zip(v_freqs, v_fluxes):\n", " col_name = f'V_INT_FLX{freq:.1f}'\n", " v_cols.append(Column(data=np.array([flux]), name=col_name))\n", "\n", "v_table = Table(v_cols)\n", "\n", "##Create an HDU list from the Tables, so we can easily write it to a FITS file\n", "hdu_list = [fits.PrimaryHDU(),\n", " fits.table_to_hdu(main_table),\n", " fits.table_to_hdu(v_table)]\n", "\n", "##Name the tables so WODEN can understand which is which\n", "hdu_list[1].name = 'MAIN'\n", "hdu_list[2].name = 'V_LIST_FLUXES'\n", "\n", "##convert and write out to a FITS table file\n", "hdu_list = fits.HDUList(hdu_list)\n", "cat_name = 'PKS_J0636.fits'\n", "hdu_list.writeto(cat_name, overwrite=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have our single source, let's setup a simple simulation command. For this example, we're just testing the polarisation reponse of `WODEN`, so make a very very basic simulatin. We'll run without a primary beam, put the source at phase centre, and run with just a few baselines via a custom array layout. \n", "\n", "Importantly, we'll set the `--IAU_order` flag, which means that `XX` = north-south, `YY` = east-west. This is the IAU convention for Stokes parameters." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "LST: 100.3181217509486, RA: 98.99999999999999\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/jack-line/software/WODEN_dev/woden_dev/bin/run_woden.py:4: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html\n", " __import__('pkg_resources').require('wodenpy==2.5.0')\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2025-03-14 17:11:17 - INFO - \n", " ) ( ) \n", " ( ( ( /( )\\ ) ( /( \n", " )\\))( ')\\())(()/( ( )\\()) \n", " ((_)()\\ )((_)\\ /(_)) )\\ ((_)\\ \n", " _(())\\_)() ((_)(_))_ ((_) _((_) \n", " \\ \\((_)/ // _ \\ | \\ | __|| \\| | \n", " \\ \\/\\/ /| (_) || |) || _| | .` | \n", " \\_/\\_/ \\___/ |___/ |___||_|\\_| \n", " \n", " You are using wodenpy version/git hash: a43c383\n", " \n", "2025-03-14 17:11:17 - INFO - Input arguments after parsing:\n", " \tPhase centre: 99.00000, -20.60000 deg\n", " \tArray central latitude: -26.703 deg\n", " \tArray central longitude: 116.671 deg\n", " \tArray central height: 377.827 m\n", " \tLowest channel frequency: 180.000 MHz\n", " \tChannel frequency resolution: 80.000 kHz\n", " \tCoarse band bandwidth: 1.280 MHz\n", " \tNum channels per coarse band: 375\n", " \tStart date: 2024-07-05T04:00:00\n", " \tTime resolution: 2.0 (s)\n", " \tNum time steps: 1\n", " \tHave read 10 antenna positions from array layout file: eg_array.txt\n", " \tWill write outputs to: /home/jack-line/software/WODEN_dev/examples/polarisation\n", "2025-03-14 17:11:18 - INFO - Obs epoch initial LST was 100.3222998343 deg\n", "2025-03-14 17:11:18 - INFO - Setting initial J2000 LST to 100.0765134441 deg\n", "2025-03-14 17:11:18 - INFO - Setting initial mjd to 60496.1666782406\n", "2025-03-14 17:11:18 - INFO - After precession initial latitude of the array is -26.6814845740 deg\n", "2025-03-14 17:11:18 - INFO - Precessing array layout to J2000\n", "2025-03-14 17:11:18 - INFO - No primary beam selected, no beam attenuation will be applied.\n", "2025-03-14 17:11:18 - INFO - Doing the initial mapping of sky model\n", "INFO: couldn't find second table containing shapelet information, so not attempting to load any shapelets.\n", "2025-03-14 17:11:18 - INFO - Sky model mapping took 0.0 mins\n", "2025-03-14 17:11:18 - INFO - Have read in 3 components\n", "2025-03-14 17:11:18 - INFO - After cropping there are 3 components\n", "2025-03-14 17:11:18 - INFO - Will load libwoden from /home/jack-line/software/WODEN_dev/wodenpy/libwoden_double.so\n", "2025-03-14 17:11:18 - INFO - Running in serial on GPU.\n", " Will read sky model using 1 threads\n", " There are 1 sets of sky models to run\n", "2025-03-14 17:11:18 - INFO - Reading set 0 sky models\n", "2025-03-14 17:11:18 - INFO - From sky set 0 thread num 0 reading 3 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 17:11:18 - INFO - Sending Sky set 0 to the GPU\n", "2025-03-14 17:11:19 - INFO - Sky set 0 has returned from the GPU after 0.1 seconds\n", "2025-03-14 17:11:19 - INFO - Have completed 3 of 3 components calcs (100.0%)\n", "2025-03-14 17:11:19 - INFO - Full run took 0:00:01.302348\n", "2025-03-14 17:11:19 - INFO - WODEN is done. Closing the log. S'later\n" ] }, { "data": { "text/plain": [ "0" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "np.random.seed(234987)\n", "\n", "##make a random array layout. Source is at phase centre, so the visibilities\n", "##should all be full real and just be set by the flux in the sky\n", "num_antennas = 10\n", "east = np.random.uniform(-1000, 1000, num_antennas)\n", "north = np.random.uniform(-1000, 1000, num_antennas)\n", "height = np.zeros(num_antennas)\n", "\n", "array = np.empty((num_antennas, 3))\n", "array[:,0] = east\n", "array[:,1] = north\n", "array[:,2] = height\n", "\n", "array_name = \"eg_array.txt\"\n", "np.savetxt(array_name, array)\n", "\n", "##stick our array in the MWA location. \n", "mwa_location = EarthLocation(lat=-26.703319405555554*u.deg, \n", " lon=116.67081523611111*u.deg,\n", " height=377.827)\n", "\n", "##pick a time/date that sticks our source overhead\n", "date = \"2024-07-05T04:00:00\"\n", "\n", "observing_time = Time(date, scale='utc', location=mwa_location)\n", "##Grab the LST\n", "LST = observing_time.sidereal_time('mean')\n", "LST_deg = LST.value*15\n", "print(f\"LST: {LST_deg}, RA: {ra0}\")\n", "\n", "##parameters for the simulation; setting the date sets an LST of about 0 deg\n", "##to match the phase centre\n", "\n", "uvfits_name = \"PKS_J0636\"\n", "freq_reso = 80e+3\n", "low_freq = 180e+6\n", "high_freq = 210e+6\n", "num_freq_chans = int((high_freq - low_freq) / freq_reso)\n", "\n", "##The command to run WODEN\n", "command = f'run_woden.py --ra0={ra0} --dec0={dec0} --array_layout={array_name} '\n", "command += f'--date={date} --output_uvfits_prepend={uvfits_name} '\n", "command += f'--cat_filename={cat_name} --primary_beam=none '\n", "command += f'--lowest_channel_freq={low_freq} --freq_res={freq_reso} '\n", "command += f'--num_freq_channels={num_freq_chans} --band_nums=1 '\n", "command += f'--time_res=2 --num_time_steps=1 --IAU_order '\n", "command += '--num_threads=1'\n", "\n", "##use subprocess to run the command\n", "call(command, shell=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Righto, now we have an output, let's read it in, convert it to Stokes parameters, and plot the SED." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "15\n" ] }, { "data": { "image/png": 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lGIZhGIZhQg4WsQzDMAzDMEzIwSKWYRiGYRiGCTlYxDIMwzAMwzAhB4tYhmEYhmEYJuRgEcswDMMwDMOEHCxiGYZhGIZhmJCDRSzDMAzDMAwTcoSMiJ09ezaGDRuG2NhYpKSkYOLEidi7d2+gm8UwDMMwDMMEgJARsStWrMBf//pX/Prrr/j+++9RVVWFcePGoaSkJNBNYxiGYRiGYZoYixBCBLoR/nD69GmkpKRgxYoVuOCCCwwtU1RUhPj4eBQWFiIuLq6RW8gwDMMwDMOYxaheC2vCNjUohYWFAIDWrVt7/UxFRQUqKipc/xcVFTV6uxiGYRiGYZjGJ2TsBGqcTifuuusujBo1Cv369fP6udmzZyM+Pt7117FjxyZsJcMwDMMwDNNYhKSd4M9//jO++eYb/PLLL+jQoYPXz2lFYjt27Mh2AoZhGIZhmCCl2doJ7rjjDnz99ddYuXKlroAFgIiICERERDRRyxiGYRiGYZimImRErBACf/vb37Bo0SIsX74c6enpgW4SwzAMwzAMEyBCRsT+9a9/xYIFC/Dll18iNjYWJ0+eBADEx8cjMjIywK1jGIZhGIZhmpKQ8cRaLBbN+XPnzsUtt9xiaB1cYothGIZhGCa4aXae2BDR2gzDMAzDMEwTEJIlthiGYRiGYZiWDYtYhmEYhmEYJuRgEcswDMMwDMOEHCxiGYZhGIZhmJCDRSzDMAzDMAwTcrCIZRiGYRiGYUIOFrEMwzAMwzBMyMEilmEYhmEYhgk5WMQyDMMwDMMwIQeLWIZhGIZhGCbkYBHLMAzDMAzDhBwsYhmGYRiGYZiQg0UswzAMwzAME3KwiGUYhmEYhmFCDhaxDMMwDMMwTMjBIpZhGIZhGIYJOVjEMgzDMAzDMCEHi1iGYRiGYRgm5GARyzAMwzAMw4QcLGIZhmEYhmGYkINFLMMwDMMwDBNysIhlGIZhGIZhQg4WsQzDMAzDMEzIwSKWYRiGYRiGCTlYxDIMwzAMwzAhB4tYhmEYhmEYJuRgEcswDMMwDMOEHCxiGYZhGIZhmJCDRSzDMAzDMAwTcrCIZRiGYRiGYUIOFrEMwzAMwzBMyMEilmEYhmEYhgk5WMQyDMMwDMMwIUdYoBvAMAzDMEzzo6amBlVVVYFuBhOE2O122Gy2eq+HRSzDMAzDMA2GEAInT55EQUFBoJvCBDEJCQlo27YtLBaL3+tgEcswDMMwTIMhBWxKSgqioqLqJVKY5ocQAqWlpcjNzQUAtGvXzu91sYhlGIZhGKZBqKmpcQnYpKSkQDeHCVIiIyMBALm5uUhJSfHbWsCJXQzDMAzDNAjSAxsVFRXgljDBjjxG6uObZhHLMAzDMEyDwhYCxhcNcYywiGUYhmEYhmFCDhaxDMMwDMMwjAfz5s1DQkJCoJvhFRaxDMMwDMO0eG655RZYLBZYLBbY7Xakp6fjgQceQHl5eaCbFtRYLBZ88cUXAflurk7AMAzDMAwDYPz48Zg7dy6qqqqwadMmTJs2DRaLBXPmzAl00/ympqYGFosFVmvzi1s2vy1iGIZhGCZoEEKgpKQkIH9CCFNtjYiIQNu2bdGxY0dMnDgRY8eOxffff+963+l0Yvbs2UhPT0dkZCQGDhyIhQsXuq1j586duPLKKxEXF4fY2FhkZmbiwIEDruUff/xxdOjQARERERg0aBCWLVvmWva8887DzJkz3dZ3+vRp2O12rFy5EgBQUVGB++67D+3bt0d0dDSGDx+O5cuXuz4vLQCLFy9Gnz59EBERgSNHjvhcTi7bqVMnREVFYdKkScjLyzO1/5oajsQyDMMwDNNolJaWIiYmJiDf7XA4EB0d7deyO3bswJo1a9C5c2fXvNmzZ+P999/H66+/joyMDKxcuRI333wzkpOTMXr0aOTk5OCCCy7AmDFj8NNPPyEuLg6rV69GdXU1AODll1/G888/jzfeeAODBw/GO++8gwkTJmDnzp3IyMjAlClT8Mwzz+Dpp592Ze9//PHHSEtLQ2ZmJgDgjjvuwK5du/DRRx8hLS0NixYtwvjx47F9+3ZkZGQAoH0+Z84cvPXWW0hKSkJKSorP5datW4fp06dj9uzZmDhxIpYtW4bHHnusPru/8REtiMLCQgFAFBYWBropDMMwDNPsKCsrE7t27RJlZWWueQ6HQwAIyJ/D4TDc9mnTpgmbzSaio6NFRESEACCsVqtYuHChEEKI8vJyERUVJdasWeO23PTp08XkyZOFEELMmjVLpKeni8rKSs3vSEtLE08++aTbvGHDhom//OUvQgghcnNzRVhYmFi5cqXr/ZEjR4qZM2cKIYQ4fPiwsNlsIicnx20dF198sZg1a5YQQoi5c+cKACIrK8v1vpHlJk+eLC6//HK392+44QYRHx/vZY8RAMSiRYt0P6OF1rEiMarXOBLLMAzDMEyjERUVBYfDEbDvNsOFF16I1157DSUlJXjxxRcRFhaGa6+9FgCwf/9+lJaW4pJLLnFbprKyEoMHDwYAZGVlITMzE3a73WPdRUVFOH78OEaNGuU2f9SoUdi6dSsAIDk5GePGjcMHH3yAzMxMZGdnY+3atXjjjTcAANu3b0dNTQ169Ojhto6Kigq3EdLCw8MxYMAA1/9Gltu9ezcmTZrk9v7IkSPd7A7BBotYhmEYhmEaDYvF4neXflMTHR2N7t27AwDeeecdDBw4EG+//TamT5/uEuJLlixB+/bt3ZaLiIgAoAynWh+mTJmCGTNm4JVXXsGCBQvQv39/9O/fHwDZI2w2GzZt2uQxVKvashEZGek2mIDR5UINFrEMwzAMwzB1sFqteOihh3DPPffgpptuckuSGj16tOYyAwYMwPz581FVVeURjY2Li0NaWhpWr17ttvzq1atx7rnnuv6/+uqr8cc//hHLli3DggULMHXqVNd7gwcPRk1NDXJzc10eWSMYWa53795Yt26d27xff/3V8HcEAq5OwDAMwzAMo8F1110Hm82GV199FbGxsbjvvvtw9913Y/78+Thw4AA2b96MV155BfPnzwdASVdFRUW48cYbsXHjRuzbtw/vvfce9u7dCwC4//77MWfOHHz88cfYu3cvHnzwQWRlZeHOO+90fWd0dDQmTpyIRx55BLt378bkyZNd7/Xo0QNTpkzB1KlT8fnnnyM7Oxvr16/H7NmzsWTJEq/bYWS5GTNmYNmyZXjuueewb98+/Oc//wlqKwHAIpZhGIZhGEaTsLAw3HHHHXjmmWdQUlKCf/3rX3jkkUcwe/Zs9O7dG+PHj8eSJUuQnp4OAEhKSsJPP/0Eh8OB0aNHY+jQoXjzzTddUdkZM2bgnnvuwb333ov+/ftj2bJlWLx4sauqgGTKlCnYunUrMjMz0alTJ7f35s6di6lTp+Lee+9Fz549MXHiRGzYsMHjc3XxtdyIESPw5ptv4uWXX8bAgQPx3Xff4e9//3tD7cpGwVKbWWaKqqoqnDx5EqWlpUhOTkbr1q0bo20NTlFREeLj41FYWIi4uLhAN4dhGIZhmhXl5eXIzs5Geno6WrVqFejmMEGM3rFiVK8ZjsQWFxfjtddew+jRoxEXF4cuXbqgd+/eSE5ORufOnXHbbbdhw4YN/m8NwzAMwzAMwxjEkIh94YUX0KVLF8ydOxdjx47FF198gaysLPz2229Yu3YtHnvsMVRXV2PcuHEYP3489u3b19jtZhiGYRiGYVowhqoTbNiwAStXrkTfvn013z/33HNx66234vXXX8fcuXOxatUqD38HwzAMwzAMwzQUhkTshx9+aGhlERERuP322+vVIIZhGIZhGIbxhenqBHPnzkVpaWljtIVhGIZhGIZhDGFaxD744INo27Ytpk+fjjVr1jRGmxiGYRiGYRhGF9MiNicnB/Pnz8eZM2cwZswY9OrVC3PmzMHJkycbo30MwzAMwzAM44FpERsWFoZJkybhyy+/xNGjR3Hbbbfhgw8+QKdOnTBhwgR8+eWXcDqdjdFWhmEYhmEYhgFQzxG7UlNTcf7552PkyJGwWq3Yvn07pk2bhm7dumH58uUN1ESGYRiGYRiGcccvEXvq1Ck899xz6Nu3L8aMGYOioiJ8/fXXyM7ORk5ODq6//npMmzatodvKMAzDMAzDNBHz5s1DQkJCoJvhFdMi9qqrrkLHjh0xb9483HbbbcjJycGHH36IsWPHAgCio6Nx77334ujRow3eWIZhGIZhmMbglltugcVigcVigd1uR3p6Oh544AGUl5cHumlBz9dff43Ro0cjNjYWUVFRGDZsGObNm9fo32uoTqyalJQUrFixAiNHjvT6meTkZGRnZ9erYQzDMAzDME3J+PHjMXfuXFRVVWHTpk2YNm0aLBYL5syZE+im+U1NTQ0sFgus1no5SL3yyiuv4K677sLMmTPx2muvITw8HF9++SVuv/127NixA88991yjfC/gRyT27bff1hWwAGCxWNC5c2e/G8UwDMMwTDNBCKCkJDB/QphqakREBNq2bYuOHTti4sSJGDt2LL7//nvX+06nE7Nnz0Z6ejoiIyMxcOBALFy40G0dO3fuxJVXXom4uDjExsYiMzMTBw4ccC3/+OOPo0OHDoiIiMCgQYOwbNky17LnnXceZs6c6ba+06dPw263Y+XKlQCAiooK3HfffWjfvj2io6MxfPhwtzwkaQFYvHgx+vTpg4iICBw5csTncnLZTp06ISoqCpMmTUJeXp7u/jp69Cjuvfde3HXXXXjqqafQp08fdO/eHffeey+effZZPP/881i3bp3h/W8Ww5HYf//7375XFhaGtm3b4vzzz0dKSkq9GsYwDMMwTDOgtBSIiQnMdzscQHS0X4vu2LEDa9ascQvKzZ49G++//z5ef/11ZGRkYOXKlbj55puRnJyM0aNHIycnBxdccAHGjBmDn376CXFxcVi9ejWqq6sBAC+//DKef/55vPHGGxg8eDDeeecdTJgwATt37kRGRgamTJmCZ555Bk8//TQsFgsA4OOPP0ZaWhoyMzMBAHfccQd27dqFjz76CGlpaVi0aBHGjx+P7du3IyMjAwBQWlqKOXPm4K233kJSUhJSUlJ8Lrdu3TpMnz4ds2fPxsSJE7Fs2TI89thjuvto4cKFqKqqwn333efx3p/+9Cc89NBD+PDDDzF8+HC/fgOfCIN06dLF51+nTp1EdHS0iIyMFJ999pnRVTcZhYWFAoAoLCwMdFMYhmEYptlRVlYmdu3aJcrKypSZDocQFBNt+j+Hw3Dbp02bJmw2m4iOjhYRERECgLBarWLhwoVCCCHKy8tFVFSUWLNmjdty06dPF5MnTxZCCDFr1iyRnp4uKisrNb8jLS1NPPnkk27zhg0bJv7yl78IIYTIzc0VYWFhYuXKla73R44cKWbOnCmEEOLw4cPCZrOJnJwct3VcfPHFYtasWUIIIebOnSsAiKysLNf7RpabPHmyuPzyy93ev+GGG0R8fLyXPSbE7bffrvv+gAEDxGWXXab5nuaxUotRvWY4EmvU4+p0OvH000/j4YcfxjXXXOOXsGYYhmEYppkQFUUR0UB9twkuvPBCvPbaaygpKcGLL76IsLAwXHvttQCA/fv3o7S0FJdcconbMpWVlRg8eDAAICsrC5mZmbDb7R7rLioqwvHjxzFq1Ci3+aNGjcLWrVsBUE7RuHHj8MEHHyAzMxPZ2dlYu3Yt3njjDQDA9u3bUVNTgx49erito6KiAklJSa7/w8PDMWDAANf/RpbbvXs3Jk2a5Pb+yJEj3ewO/hAeHl6v5fUwndjlC6vVimnTpuHFF19s6FUzDMMwDBNqWCx+d+k3NdHR0ejevTsA4J133sHAgQPx9ttvY/r06XDUCvElS5agffv2bstFREQAACIjI+vdhilTpmDGjBl45ZVXsGDBAvTv3x/9+/cHADgcDthsNmzatAk2m81tuRiVZSMyMtJlRzCznFkyMjJQWFiI48ePIy0tze29yspKHDhwAJdeeqnf6/eFocSujz76yPAKjx49ikOHDuH06dN+N4phGIZhGCaQWK1WPPTQQ/j73/+OsrIytySp7t27u/117NgRADBgwACsWrUKVVVVHuuLi4tDWloaVq9e7TZ/9erV6NOnj+v/q6++GuXl5Vi2bBkWLFiAKVOmuN4bPHgwampqkJub69GGtm3bet0WI8v17t3bIwnr119/1d1H//d//4ewsDA8//zzHu+9/vrrKC0txdSpU3XXUR8MidjXXnsNvXv3xjPPPIPdu3d7vF9YWIilS5fipptuwpAhQ3xmszEMwzAMwwQ71113HWw2G1599VXExsbivvvuw91334358+fjwIED2Lx5M1555RXMnz8fACVdFRUV4cYbb8TGjRuxb98+vPfee9i7dy8A4P7778ecOXPw8ccfY+/evXjwwQeRlZWFO++80/Wd0dHRmDhxIh555BHs3r0bkydPdr3Xo0cPTJkyBVOnTsXnn3+O7OxsrF+/HrNnz8aSJUu8boeR5WbMmIFly5bhueeew759+/Cf//zHp5WgU6dOeOaZZ/DSSy/h4Ycfxp49e3DgwAG88MILeOCBB/DEE0+gX79+fu9/n+g6ZlV8+eWXYuzYscJqtYrY2FjRvXt30a9fP9G+fXths9lEamqqmDlzpjh58qTRVTY5nNjFMAzDMI2HXrJOsDNt2jRx9dVXe8yfPXu2SE5OFg6HQzidTvHSSy+Jnj17CrvdLpKTk8Wll14qVqxY4fr81q1bxbhx40RUVJSIjY0VmZmZ4sCBA0IIIWpqasQ//vEP0b59e2G328XAgQPFN9984/GdS5cuFQDEBRdc4PFeZWWlePTRR0WXLl2E3W4X7dq1E5MmTRLbtm0TQlBil1ayla/lhBDi7bffFh06dBCRkZHiqquuEs8995xu4pbkiy++EJmZmSI6OloAEADEhx9+qLtMQyR2WYQwV0TtzJkz+OWXX3D48GGUlZWhTZs2GDx4MAYPHtxohXQbiqKiIsTHx6OwsBBxcXGBbg7DMAzDNCvKy8uRnZ2N9PR0tGrVKtDNYQLA2bNncfHFFyMuLg7ffPMNorwk1+kdK0b1munErjZt2mDixIlmF2MYhmEYhmGaOa1bt8YPP/yAV199FWvXrsXFF1/caN/V4NUJGIZhGIZhmJZLUlISHn300Ub/nuDu/2cYhmEYhmEYDVjEMgzDMAzDMCEHi1iGYRiGYRgm5DAtYsvLy72+d+LEiXo1hmEYhmEYhmGMYFrEDhkyBFlZWR7zP/vsM7dxehmGYRiGYRimsTAtYseMGYMRI0Zgzpw5AICSkhLccsst+N3vfoeHHnqowRvIMAzDMAzDMHUxXWLrv//9L6644gr84Q9/wNdff40TJ04gJiYG69evb9yhxRiGYRiGYZgmY968ebjrrrtQUFAQ6KZo4ldi12WXXYZrrrkGq1evxpEjRzBnzhwWsAzDMAzDhCy33HILLBYLLBYL7HY70tPT8cADD+jmArV0Dh06BIvFomkzHTNmDO66665G/X7TIvbAgQMYOXIkvv76a3z77bd44IEHMGHCBDzwwAOoqqpqjDYyDMMwDMM0OuPHj8eJEydw8OBBvPjii3jjjTfw2GOPBbpZ9aKmpgZOpzPQzWgUTIvYQYMGIT09HVu3bsUll1yCJ554Aj///DM+//xznHvuuY3RRoZhGIZhmEYnIiICbdu2RceOHTFx4kSMHTsW33//vet9p9OJ2bNnIz09HZGRkRg4cCAWLlzoto6dO3fiyiuvRFxcHGJjY5GZmYkDBw64ln/88cfRoUMHREREYNCgQVi2bJlr2fPOOw8zZ850W9/p06dht9uxcuVKAEBFRQXuu+8+tG/fHtHR0Rg+fDiWL1/u+vy8efOQkJCAxYsXo0+fPoiIiMCRI0d8LieX7dSpE6KiojBp0iTk5eU1xG5tNEyL2P/+97/46KOPkJCQ4Jp33nnnYcuWLRgyZEhDto1hGIZhmBBHCKCkJDB/Qvjf7h07dmDNmjUIDw93zZs9ezbeffddvP7669i5cyfuvvtu3HzzzVixYgUAICcnBxdccAEiIiLw008/YdOmTbj11ltRXV0NAHj55Zfx/PPP47nnnsO2bdtw6aWXYsKECdi3bx8AYMqUKfjoo48gVA3/+OOPkZaWhszMTADAHXfcgbVr1+Kjjz7Ctm3bcN1112H8+PGudQBAaWkp5syZg7feegs7d+5ESkqKz+XWrVuH6dOn44477kBWVhYuvPBCPPHEE/7vwKZAtCAKCwsFAFFYWBjopjAMwzBMs6OsrEzs2rVLlJWVueY5HEKQnGz6P4fDeNunTZsmbDabiI6OFhEREQKAsFqtYuHChUIIIcrLy0VUVJRYs2aN23LTp08XkydPFkIIMWvWLJGeni4qKys1vyMtLU08+eSTbvOGDRsm/vKXvwghhMjNzRVhYWFi5cqVrvdHjhwpZs6cKYQQ4vDhw8Jms4mcnBy3dVx88cVi1qxZQggh5s6dKwCIrKws1/tGlps8ebK4/PLL3d6/4YYbRHx8vJc9JkR2drYAILZs2eLx3ujRo8Wdd97pdVmtY0ViVK+Zrk7w7rvven3PYrHgd7/7nb96mmEYhmEYJmBceOGFeO2111BSUoIXX3wRYWFhuPbaawEA+/fvR2lpKS655BK3ZSorKzF48GAAQFZWFjIzM2G32z3WXVRUhOPHj2PUqFFu80eNGoWtW7cCAJKTkzFu3Dh88MEHyMzMRHZ2NtauXYs33ngDALB9+3bU1NSgR48ebuuoqKhAUlKS6//w8HC32v1Gltu9ezcmTZrk9v7IkSPd7A7BhmkRe+edd7r9X1VVhdLSUoSHhyMqKqpRRezKlSvx7LPPYtOmTThx4gQWLVqEiRMnNtr3MQzDMAxTP6KiAIcjcN9thujoaHTv3h0A8M4772DgwIF4++23MX36dDhqN2LJkiVo376923IREREAgMjIyHq3ecqUKZgxYwZeeeUVLFiwAP3790f//v0BAA6HAzabDZs2bYLNZnNbLiYmxvU6MjISFovF9b/R5cwSFxcHACgsLPR4r6CgAPHx8X6v2wimRWx+fr7HvH379uHPf/4z7r///gZplDdKSkowcOBA3Hrrrbjmmmsa9bsYhmEYhqk/FgsQHR3oVpjHarXioYcewj333IObbrrJLUlq9OjRmssMGDAA8+fPR1VVlUc0Ni4uDmlpaVi9erXb8qtXr3ZLjL/66qvxxz/+EcuWLcOCBQswdepU13uDBw9GTU0NcnNzXR5ZIxhZrnfv3li3bp3bvF9//VV3va1bt0abNm2wadMmt20qKirC/v37PSK/DY6u2cAEGzZsED179myo1fkEgFi0aJGpZdgTyzAMwzCNh57PMdiZNm2auPrqq93mVVVVifbt24tnn31WCCHEww8/LJKSksS8efPE/v37xaZNm8S///1vMW/ePCGEEGfOnBFJSUnimmuuERs2bBC//fabePfdd8WePXuEEEK8+OKLIi4uTnz00Udiz549YubMmcJut4vffvvN7XunTJkiBg4cKCwWizh8+LDHe126dBGfffaZOHjwoFi3bp146qmnxNdffy2EIE+slo/V13Jr164VVqtVPPvss+K3334Tr7zyikhISND1xAohxFNPPSWSkpLE+++/L/bv3y/WrVsnrrzyStGlSxdRWlrqdbmG8MQ2mIjdsmWLiI2NbajV+cSIiC0vLxeFhYWuv6NHj7KIZRiGYZhGormJWCGEmD17tkhOThYOh0M4nU7x0ksviZ49ewq73S6Sk5PFpZdeKlasWOH6/NatW8W4ceNEVFSUiI2NFZmZmeLAgQNCCCFqamrEP/7xD9G+fXtht9vFwIEDxTfffOPxnUuXLhUAxAUXXODxXmVlpXj00UdFly5dhN1uF+3atROTJk0S27ZtE0J4F7G+lhNCiLffflt06NBBREZGiquuuko899xzPkVsdXW1+Pe//y369+8voqKiRIcOHcQNN9wgsrOzdZdrCBFrEcJcAYrFixfXjeTixIkT+M9//oOOHTvim2++aZgQsQ8sFotPT+w//vEP/POf//SYX1hY6PJxMAzDMAzTMJSXlyM7Oxvp6elo1apVoJvDBDF6x0pRURHi4+N96jXTnti6otFisSA5ORkXXXQRnn/+ebOra1RmzZqFe+65x/V/UVEROnbsGMAWMQzDMAzDMA2BaREbSkOXRUREuDIGGYZhGIZhmOaD6RG7GIZhGIZhGCbQGIrEqrvkffHCCy/43RhfOBwO7N+/3/V/dnY2srKy0Lp1a3Tq1KnRvpdhJPPnA7NnA//+NzBuXKBbwzAMwzAtF0MidsuWLYZWpi6s2xhs3LgRF154oet/Ka6nTZuGefPmNep3M8xzzwGyFPLLLzczEfvbb8DNNwPXXAM8+GCgW8MwDMMwPjFdnSCUMZrtxjB1yc8HkpOBmhr6v1Ur4OxZoAEGZwk8Z84AI0cC+/fT8DanTgH1GMGFYZiWC1cnYIzSENUJDHtiDx48iBakdxnGjS1bSMCmpwMdOgDl5cDy5YFuVQNxxx0kYAGgtBT4/PPAtodhGIZhDGBYxGZkZOD06dOu/2+44QacOnWqURrFMMHG5s00HToUuPxyer10aeDa02AIAXz3Hb2+7DKavv9+4NrDMA3A/v3Ahg2BbgXDMI2NYRFbNwq7dOlSlJSUNHiDGCYYkSJ28GDgiivo9dKlpAFDmuxs8kqEhwMyKfPHH4HjxwPbLobxkxMngHPPpb+vvgp0a4KAyspAt4BhGg0uscUwBpC5jUOGABddBFitwMGDQG5uYNtVbzZtoumAAUCvXnTndzqBn38ObLsYxk9mzKDnMgD43e+AffsC256AMmsWkJgIcOIz4yfz5s1DQkJCoJvhFcMi1mKxeFQfaOxqBAwTDDgcwN699HrwYMp5kgO/HTgQuHY1CBs30nToUJoOGkTTPXsC0hyGqQ/ffQcsXAjYbED//kBhIfDYY4FuVYB4913g6afJ5/7HPwJr1wa6RUHPLbfc4tI6drsd6enpeOCBB1BeXh7opgUlp06dgt1ux0cffaT5/vTp0zFkyJBGbYPhEbuEELjllltcI2CVl5fj9ttvR3R0tNvnPuekEKaZsXUr2QbS0oDUVJrXrRtw+DCJ2PPOC2z76oWMxJ5zDk1796bp7t2BaQ/D1INFi2j6hz8AN90EjB5N7hghgBYVczl9Grj9dnrdsSNw9CgwZQqZha3cAavH+PHjMXfuXFRVVWHTpk2YNm0aLBYL5syZE+im+U1NTQ0sFgusDfzbp6am4oorrsA777yDG2+80e29kpISfPLJJ3j66acb9DvrYniLpk2bhpSUFMTHxyM+Ph4333wz0tLSXP/LP4Zpbkg/rPqBsls3moZ0JFYIRcTKSGyvXjTlSCwTgvzyC03HjQOGD6dSeLm5LfCZ7LvvgLIyoG9fYPt2IDqa/O/btwe6ZUFPREQE2rZti44dO2LixIkYO3Ysvv/+e9f7TqcTs2fPRnp6OiIjIzFw4EAsXLjQbR07d+7ElVdeibi4OMTGxiIzMxMHam8WTqcTjz/+ODp06ICIiAgMGjQIy5Ytcy173nnnYebMmW7rO336NOx2O1auXAkAqKiowH333Yf27dsjOjoaw4cPx3JVuRxpAVi8eDH69OmDiIgIHDlyxOdyctlOnTohKioKkyZNQl5enu7+mj59On788UccOXLEbf6nn36K6upqTJkyRX+H1xPDkdi5c+c2ZjsYJmiRN8D+/ZV5XbvSNKRF7MGDQEEBJXX17UvzpIjdtw+orgbCDF8iGCag5OcDO3bQ61GjgIgI6iX56Scqh9enT0Cb17TIiiNXXAHExwNjxgBLltD8gQObvDlCCJRWlTb59wJAlD3Kb+vjjh07sGbNGnTu3Nk1b/bs2Xj//ffx+uuvIyMjAytXrsTNN9+M5ORkjB49Gjk5ObjgggswZswY/PTTT4iLi8Pq1atRXV0NAHj55Zfx/PPP44033sDgwYPxzjvvYMKECdi5cycyMjIwZcoUPPPMM3j66add7f7444+RlpaGzMxMAMAdd9yBXbt24aOPPkJaWhoWLVqE8ePHY/v27cjIyAAAlJaWYs6cOXjrrbeQlJSElJQUn8utW7cO06dPx+zZszFx4kQsW7YMj/nw41x++eVITU3FvHnz8Oijj7rmz507F9dcc03j+2lFC6KwsFAAEIWFhYFuChNCXHmlEIAQr7+uzPvkE5o3cmTg2lVvFi2ijRgyRJlXUyNEZCTN37cvYE1jGLN8/TUdthkZyrx//YvmXXdd4NrV5DidQrRrRxv+ww807+WX6f+xYxv968vKysSuXbtEWVmZa56jwiHwDwTkz1HhMNz2adOmCZvNJqKjo0VERIQAIKxWq1i4cKEQQojy8nIRFRUl1qxZ47bc9OnTxeTJk4UQQsyaNUukp6eLyspKze9IS0sTTz75pNu8YcOGib/85S9CCCFyc3NFWFiYWLlypev9kSNHipkzZwohhDh8+LCw2WwiJyfHbR0XX3yxmDVrlhBCiLlz5woAIisry/W+keUmT54sLr/8crf3b7jhBhEfH+9ljxEPPvigSE9PF06nUwghxP79+4XFYhE/yOPPC1rHisSoXmNzDMP44OhRmnbqpMxrFnaCQ4doKjcGIL9cz570mi0FTAghrQTnn6/MGzOGpsuXN4NyeEbZtYvqjLVqRSFpQBkje9UqshkwXrnwwguRlZWFdevWYdq0afj973+Pa6+9FgCwf/9+lJaW4pJLLkFMTIzr791333XZBbKyspCZmQm73e6x7qKiIhw/fhyj5O9Sy6hRo7C7tssvOTkZ48aNwwcffAAAyM7Oxtq1a13d8tu3b0dNTQ169Ojh1oYVK1a42gAA4eHhGDBggOt/I8vt3r0bw4cPd2vbyJEjfe6zW2+9FdnZ2fi5tqrN3Llz0aVLF1x00UU+l60v3FfIMD6QVh9ZkQBQdF9uLlBcDMTGNn276s3hwzRVdZUBIEtBVhaJ2CuvbPJmMYw/SBFb2+MKgCrGRUZSntNvvynPZ80aaSW44AISsgBtuEzwWrVKEbVNRJQ9Co5Zjib9TvV3myE6Ohrdu3cHALzzzjsYOHAg3n77bUyfPh0OB23DkiVL0L59e7flZNJ7ZAOMRT5lyhTMmDEDr7zyChYsWID+/fujf62fzeFwwGazYdOmTbDZbG7LxaiGC4+MjHSzURhdzh8yMjKQmZmJuXPnYsyYMXj33Xdx2223NUkFKxaxDKNDSYlSc1ItYuPjgaQkIC+PrKUBsJnVHxmJ7dLFfb70xba4bBgmVKmpUarFqauFhIeTF3bTJjqcW4SIXbWKphdfrMyzWOj/efMCImItFguiw6N9fzDIsFqteOihh3DPPffgpptuckuSGj16tOYyAwYMwPz581FVVeURjY2Li0NaWhpWr17ttvzq1atx7rnnuv6/+uqr8cc//hHLli3DggULMHXqVNd7gwcPRk1NDXJzc10eWSMYWa53795Yt26d27xff/3V0PqnT5+OP//5z5gwYQJycnJwyy23GG5bfWA7AcPoIK0EcXEkXNWEvKXAWyRWltliOwETIhw5ApSXk2itDaK5aHHPZDK7rW59zsGD3d9nDHHdddfBZrPh1VdfRWxsLO677z7cfffdmD9/Pg4cOIDNmzfjlVdewfz58wFQ0lVRURFuvPFGbNy4Efv27cN7772HvbXFxu+//37MmTMHH3/8Mfbu3YsHH3wQWVlZuPPOO13fGR0djYkTJ+KRRx7B7t27MXnyZNd7PXr0wJQpUzB16lR8/vnnyM7Oxvr16zF79mwsWbLE63YYWW7GjBlYtmwZnnvuOezbtw//+c9/3Con+NpPdrsdf/rTnzBu3Dh0VEd9GhEWsQyjgxSxWudjsxWxsvSCfJ9hghw5GEn37jTQgZoW9UxWVka1YAGgXz/39+T/XGbLFGFhYbjjjjvwzDPPoKSkBP/617/wyCOPYPbs2ejduzfGjx+PJUuWID09HQCQlJSEn376CQ6HA6NHj8bQoUPx5ptvuqKyM2bMwD333IN7770X/fv3x7Jly7B48WJXVQHJlClTsHXrVmRmZqKTOiED5DmdOnUq7r33XvTs2RMTJ07Ehg0bPD5XF1/LjRgxAm+++SZefvllDBw4EN999x3+/ve/G9pPUVFRuPHGG5Gfn49bb73V0DINgUWIFmN3R1FREeLj41FYWIi4uLhAN4cJAd5+mwqnjx8PfPON+3sPPww89RTwl78Ar74amPb5jcOhGHkLCynULDl5EmjXjpK8Kiq4zBYT9Lz8MnDXXcCkSUDd8XY++wz4v/8Dhg0D1q8PSPOajs2bqeZzUhIZgdWexNOngZQUmldcTLVjG4Hy8nJkZ2cjPT0draQnl2E00DtWjOo1jsQyjA5alQkkaWk0PXGi6drTYMgoa0KCu4AF6EYXFgY4ncCpU03eNIYxi4zEanle1ZHYZh+ykVaBfv08hyhLTqZzWwiqYMAwzQAWsQyjg56doF07moa0iK1rJQAoAisV+rFjTdcmhvETPRErLQbFxcDx403briZHLWK1kPPZF8s0E1jEMowOzV7E1q1MIOnQgaYsYpkQ4LffaNqjh+d74eGKf73ZJ3f5ErFy2EH2xTLNBBaxDKODrBGrZSdQi9iQ66bUi8QCLGKZkKGkRDlMvZXQkhUKmn1yF0dimRYGi1iG8YIQ+pHYtm1pWlmp1JINGWSNWBaxTIgjo7BJSfSnRYsos1VYqFyw+vbV/gxXKGCaGSxiGcYLhYVAaSm9lppOTatWQGIivQ45S4EMMbOIZUIcPT+sRL4XsuXwjCDVfNu2yoWpLjLL7eRJMgk3Ii2o8BHjJw1xjLCIZRgv5ObSND5eGb2xLiHri5UNlglcdZFDKrKIZYIcWRZVyw8rkc9qsgOiWXLwIE3rjvagRg41qP58AyProZbKCADDeEEeI3VHNjMDF4BkGC9IEZuc7P0z7dpRtZqQErFCKKWzUlO1P8ORWCZE8JWjqH7v8GE6/JtgSPemR4aZ5WAl3ujWjcbLPnCgUcbLttlsSEhIQG7tBTQqKgqWZrnDGX8RQqC0tBS5ublISEiAre4IJSZgEcswXpAiNiXF+2dCMhLrcNDIPoBvEZuTQ/VirdxpwwQnvnIUAfK0Wyw0NG1urvfDPqSRkVVfIrZrVxr1oRG9FW1rEwakkGUYLRISElzHir+wiGUYLzRbESujsNHR3kftadeO7vpVVTTST7O86zPNAb0KIpLwcHLO5OSQpaBZHs5GRaysN9ZIdgIAsFgsaNeuHVJSUlBVVdVo38OELna7vV4RWAmL2EBTXU2VuLm7JehotiL25Ema6j0B2+30/okTdOdvlnd9JtQRwneOoqRLFzqUDx8Ghg9v9KY1PWZFbBNkudlstgYRKgzjDe4jDCR5eVR8esAAini1MCoqgjtb+PRpmjY7EevLDyuRyV2ybA/DBBmnT5MzxmLRriCiplknd1VWKuepFKnekCK3ESOxDNNUsIgNFEIAt95K1bd37CCPUgtCCOCaayiR9scfA90abYwmdgHNVMTKjZORW4YJMmQUtm1bICJC/7Pq5K5mx5Ej5F2PjPR9XkuRe/gw9QQyTAjDIjZQvP8+sHix8v933wWuLQHgyy+BpUvp9SuvBLYt3jBjJzh5UgCPPEIFKceMochIECEE8NZbwO23A2XH8mimr5udfF+KXoYJMowkdUmkiG2WkVi1lcCXNS0tjRR/dTX3sjAhD4vYQCEVnKzp14JEbEUFcO+9yv9ffx2cwT4zIra42IKSJ16gguMrVgCrVjV+Aw1SUwPccgtw223AG28AC9bU3vF9iVjpmQ0FEet0AlOnAhMnBrdHJchwOkNwyGQVZkSs/EyzjMQa9cMCVGkkPZ1e87nChDgsYgOFHPbvvvtoun59CI5d6h/Ll9M1NzUVGDKERNb8+YFulSdGRGxMDPXgAUAuUoDYWPpnyZLGbZwJPvsMePdd5f+Pdw2gF80pEvv998B771GIf8AAYM2aQLco6Nm7l4Jy48fTORiKGKlMIFFHYoUAPU1L43uoY0bEAk1SoYBhmgIWsYGgslIZK/Gyy2goQKcT+OmnwLaridi5k6aZmcCf/0yvP/wwcO3RoqaG8u4AfRFrsQDJyRTKykUKcP/99MbXXzdyC40jD6urrqLpj6f7IxfJxkVsMIbJ6/LGGzSNiqKxgv/zn8C2J8gpKQGuvZaeT777Dnj11UC3yD/MRGKl0C0pAc7uP0tJtZ07A7/80ngNbER27KDfrawMQHY2zTQqYmUkVi7HMCEKi9hAsGcP+ZHi46kK99ixNH/16sC2q4nYvZumvXsDl1xCr3ftCq4CDXl5ysg+cpRGb6TE0NB5p6O6ADNmUHmqffuUscwDzMqVNJ0+HRg6FHDChs9wbfOJxJ44ofjL58yh6YoVod1P3sg8+ig9TMpkqFmzQrOb3Wh5LYCGjpaH9OEpD9E5WlYGXH998B/jdXjxRerFuuOO2udmMyFpQNlhcrnmwv79tFNWrAh0S5gmgkVsIJBWgn79SCX17En/h+JdxA/UIrZjR6q3X1UVXPYsaSVISqIyvnok4wwt03UEPZiMHk1vBEE0NjdX2d/nnw/ceCO9XoRJzccT+957FDofNYoqftjtwPHjwXVABRlffknT996j3VZaSq9DDXnJNKrdOnak6bENx+nCk5FBD0EPPNA4DWwE1q0D7rlHeeh/7TVg88EE+kduoC/kDmtO95wPPyQr0auvAhMmNNMMPqYuLGIDgRSxA2q9ifLC09yeijUQwl3EWq1Anz70/65dgWtXXYz4YSUpZXQjON22P82Q4eV16xqhZeaQ+WX9+pEgHz2Mosbb0d94JLa4mFROsCK7g6+7juwE555L/3M0RpMTJ0jfWyzAuHHA5Mk0f/nygDbLNGVliuXHqHaTpY9z0B64+24q2QEAX30VMuWm3n+fptddR7+d0wncdeZhmml0RzS3SGxJCfCnP9FBER0NFBUBv/td6Jq9GcOwiA0EUsT2rxU98qm4uVxQdDh9Gjh71j0ALUWs9MoGA2ZEbHLeHlomPoNm9O1LU6nWA4i0EsjgcI94iqqeRDsUOWP0F46LU/qbgzkau3kzTc85h6ZyY1nEaiJdSwMGUMfBhRfS/2vWUK5TqJCTQ9OoKCAhwdgyHdqTxeQYOpCN67zzaOH8/JCo1V1dDXz8Mb2+9VbFPbMKF+BMeJp+UWs18p6TkxMy4l2XTz+lh+1u3YBt2yjB9pdfKOGTadawiA0E3kRsbm6tS7/5InVdly5KVn9IR2KLipBStA8AcDqstt5W7940/e23gEcCZJAyM5Om8aUnkApK1Nr7m496khZL8PtiT52iG7HFAgwcSPNYxOoij4nzz6dp7950nJeVhYSOcyFFbPv2xkft7hBOJ/YxW2dgxAggLIzC0QDwzTeN0MqG5YcfKBCQnAxcfDEFXvt0KQEArGp9tfEdkZoKhIdTGFfuyFBGRtSnT6fkNumbCoHflKkfLGKbmuJipcB0v340TUykLhAAOHYsMO1qItRWAkkwilhZecdnYOPwYSSDPpxbEE7zOnemCGZFRUB9WU6nsr8HD66deeoUeoIqYxjKOwt2X+yWLTTt2ZPqnQEUXQOoZ6O5lFBqQOqKWIuFxucAQstSoBaxRumQtxUAcCy+r9LLcNllNF22rAFb1zh88glNr7+erN8AMKY77YjlYRcbX5HV2nxsbHv2UPeCzQZMm0bz5G/KIrbZwyK2qZFG+sREpQ/MYmkxlgIpqqRwVb/euzd4erYMR2KPHEEK6MMuvWSzKV6JPXsapX1GOHaMomthYUpFHZw6hR4g9SqrvOkS7GW2pJXApdJBYrZDB3rNyV1uFBcrul+KWCA0Rax83pc/tRE6HCR/zTGrKhNs/HiabtyonPhBivS4y3J5ADA6mZ7+V5ScY25lzSW566uvaDpuHBU+BihMHRZGFSj4GtCsYRHb1MgobN102hYmYtWRWGktqKgInrKFhkWsOhKrvv/JDQygL1aK1G7dlKiNOhJrSsQGayRWitghQ9zny2LufANzY+tWitB36OAu/i64gKbr1tH7oYA/kdj2u8gjmVOSoFRga9tW8bEHQTKmN86coQpSADB8uDL/gvBfAQDb8jvi7FkTK2wuyV3S+C8TagHy848aRa9DIMLO+A+L2KbGWz2/FiJiZfREXdfRalU0X7Akd5kRsepIrOvG2KsXTQMoYqVdQAaFAZgXscFuJ/AlYuVdnwFAgSnA/SESoGMkPJySvEMlMGdaxJ45g/b5lI9QUmZDYaHqvaFDaSrD1EGI1Ne9e7snsrXN24le2A0Bq7nRrptDJLamRglPyycxiYywf/tt07aJaVJYxDY1LVzEnjhB03bt3Od3707TUI7EVlRQdy0ARSUE0E4gRao3Ebtvn4GoWzBHYgsLlQNm0CD39+QBxZFYN6Smz8hwnx8WphyyO3Y0bZv8xbSdYPduRKEMra35bssDUOwoQSxif6WAK0aMqPPG0aM4DzTMsnymM0RziMTu2EHXgdhYJbFTIrNZTe0UJtRgEdvUyAtG3Xp+8n9pN2iGlJUBBQX0uq6IldfTYAkKmEnsikIZoltVuy3nFokN0MhR3kRsOrIRZnOitNRAYnIwe2KlQE1JAVq3dn+P7QSayEis1PhqZJ5pqIhY05HY2gfKDlHNT8T2AfliTXX8NIfAibQSjBpFT2JqZPWfnByloDDT7GAR29S0YE+s1EEREZ51HYNJxFZUwNXVaCSxCwCSW1MpLZcvtkcPStjLzw9Yhrw3EWtHNbqmlQMwUKEgmCOxUqBqjRfPdgJNvEVigdASsTU1Sq+O4UisFLFt6Nh3E7Eykn/4MMwZS5uGmhrFTuAmYktKgLNn0RukXv0SsYcPh+4QzVLE1rUSAOSLlRmt27Y1XZuYJoVFbFNjxE4QqhcUH6itBHXLGQaTiJWaMyzMRxH1ykrXRqW0tboti8hIJVM2AGW2ysqUQ61HD9UbtWK0c6faou++KroFsyf24EGaSsGqRs7LzVV5PFo2QjSfSOypUyTsbDbfA8+5qFV47TvQxcetFyI+XnkYCsJo7N69dBhHRys5aABcQZHe0TQ1VZpa9v6VlNDDdigiR+5Ql9pQIy0GLGKbLSxim5KaGkU11BWxMpxQVha6FxQfePPDAsEViFb7YXVrhx89SsogMhLJ7cLclgVAZReAgIjY/fupaQkJKktEaalL0KV1onIFx4/7WFEwDz0rI7FaIjYhgcbZBRSx28LJzQUcDkqkdJVcUyFF7J49QFVV07bNLFKAtm1LQtYQMhKbQaOseDzABbGlQGqwgQPrbG+tiO3UCWjVip6rDecVREYqXU3BED0wy6lTdFOxWNxL7KmRQ7uziG22sIhtSk6doruD1eqp5CIiqPsDaLYF2vVErIzE5uVRYCCQmEnqAgB06oSUFFK7bj+dFLEBuEGoKxO4hLiMpkZEIK2zQREbzEPP6tkJAE7uqoOMwnbqpPykajp1ohK7lZXKZ4MVKWINWwnKylwPkx36JwIILRErB3mUDxouakWsrXMHl23IlKUglJO7srJo2qOHMtBJXWQkduvWJmkS0/SwiG1KpB+2fXtPEzoAtGlD0zNnmq5NTYieiI2Ppz8g8EEBM0ldAIDOnV2fdYvEyhtEACKxMhrjpu+kCG3bFmntSdn6FLHBPPSsnp1APZ99sQCU3aBlJQDo2Vp2VUvRFKxIAWo4qWvfPuqaSExEhz5xbutwIaN2wVLnT4W0eHgTsejY0b/S1MHUBWYW+bDhLQoLuP+mwTKSDtOgsIhtSrz5YSVSCbVAEQsEjy/WzGhdANxErGYkNgAiVu5D2QQAighNTXXd/H2KWCA4fbGVlcr+9yZiZZ95AIf+DSZkdFUrqUuiHj0vmDFdmUAqu1690KEjPcB5iFj1xhs2ljYNUsTKhHsXqmo3fonYYLno+oMUsXXL66np2pWMxOXlwd+9wPgFi9imxJeIlZHYFmgnAILnempYxMpyC2lprs8Gi51A6jb1oBJqEStzznyW2Kr9PIDgKrN1+DAVuY2MVER2XaTCkQdeC8dXJBZQkgCD/X5v2k4go/YZGa7DoqCgjnWpSxfyWZSXB9WDj8OhNN8tqQvgSCygH4m1WpWHkwDW7GYaDxaxTYnqgqNJC7ETeNMcISdiVR/UtBOoI7FNXHFC3oO9RWKliD1xIkQHPJB39a5dvWffyY00FG5u/sjzSiupSyKjtD5LrwUY03YClfUnLk6xULo9xNls8M9Y2rjsohKwSE3VsDhpiFhTUfRQHbWruFh5KtOLxALKUxvbipolLGKbEl99YM3cTiADec0mEitFXUqKdiRWXcKmCYttC+HbTiAfJKqrDRxuwWgn8JXUBbCIrYOR6KWMxP72W3BX+jMdiVX1glksynJeLQVSOQYB0p/sYSUQwq3uuHw4KShQBpXxSagmdm3bRtuflub7Qs0Jns0aFrFNibyZehOxzdhOUF2tiENvIjZYggKynT4Tu+QHU1PdIrGum3+rVsrGNuFG5ecrpVHdnCsqEWu3K9d+w2W2gknE+krqAhQRe/KkgXBz80Y9OIBe9FLuzoKC4B3kSAg/IrF1rFxeRaxfffKNi9ekLrUfokMHREcrtxDDlxt5gTh5kkZ5CRVktQFfUViAR+9r5rCIbUqkWpA317o0YzuBFHdWq3dxGCxBAfkMYSYSK7epqgooKlJ9JgDJXfKrUlPJMupCJWIBGE/uCkZPrF6NWElqKlkNDIWbmzdGBweIilI6EILVF1tYqJQsNiRi1V0TtRcZn5HYIBKxsliChx9WXijbtHGd6KZt+ElJ9KMDoTXkudwpHuFpDbhKSbOGRWxTIYRvEduM7QQyCpSa6r04ubx5njgRuGooQhi0E5SXK2o1NRWRkYrPLtBltjStBICHiDXc2x6MkVgjdoKwMKXtLdxSILvf27XzPThAsPtipfBs3brOQ5o3CgspOwpwXWSk+PVIbJSR2F27gsZPIfW01NcuNHIsTD8zWyyhmdwlw9Meyl4DaSc4coSqmjDNChaxTUVennICeetPb8Z2gjr6SZPUVNIdNTWB00slJVQXHfAhYqVStdtdBW6DpUKBZmUCQImkmhWxweaJFcKYnQBgX2wtZrrfg71CgWk/rDz32rRxRR29RmIzMkjlFxcHxTFTXKy0UeacudAQsX49MweLj8soQuiEpzVITaUyW05nUFWdYBoGFrFNhbwgJicD4eHan2nGdoKzZ2kqRwLVwmZTNEegerakNo2Kouuezw+qxqb1WaGgidCMxNaJHAMwXmYr2Iaezc2lpw2LRSPcXAf5wBgEgiSQmBF+oRKJ9dcPC+iI2PBwJXIXBMld8jdITta4dqqSuiR+PTMHi4/LKLm5FBSyWIBevXx/3mJhX2wzhkVsU+HLSgAoKqi4OLRM9gYwImIBnZtLE+FPUpdEMxIbADuBbo3Y8HAgIQGACU9ssA09K6OwHTpoj5+qhiOxAPyLxAariPW7MoHqhNC9zgRRcpdsgmySG6qBDiR+PTOHmp1ARmG7dlX8vL5gX2yzhUVsU2FExMbHK4a1ZhaNlSK2dWv9zwVaxPqT1CXRjcQePtxkHjtfNWJl5NhwkDLYhp41ktQlYRELwL9IrBypNdhoyEhsbq5GvCCIkrtkfX7NgGND2QmCpbahUcxYCSRcZqvZwiK2qZB3ET0Ra7UqocpmJmJluR5fIlZejwNtJzA80IHRSGxRkYnijfXDV41YiWZ7vRFMvlgjSV0SFrEAzAm/9HR6li4tDc7dVp8asZKkJCWI7zGgmzq5K8BIEasZidURsWfPKmX2fBJqkVivNcd04Ehss4VFbFPhq0aspJlWKAg1O0GDRWIjIxXh2ASWAnWhc29Dzkpke0+fNhBxC6YyW0aTugAWsbWYEX7h4coDUDAmd8lrQ31ErMWiXIqDucyWbIJHJNbpVBquErFxcUqgwHSt2CNHQqOesj+RWPnAy4ldzQ4WsU2FETsB0GwrFBi1E8jrcdCLWI0Peo1sNmF3nToR2y0xTScSW15eZwx5LdhOELII4XuwwLoEsy/W7LZoiVhA54FZlgE4fTqgwYTqauUhwkPE5uZSUWqLxeOeYtpS0KEDraeiIvjvO2YrE0jUFRiC0SPD+A2L2KbCrIhtppFYo57YQNsJfCZ26UQ23SKxQJNWKDBaIxYgkSvrbHq0uS6hbic4dSpwxYcDTEGBycEBELxltsrKFGuSoUiseqiyOgt4FbHR0YoSDGA0NjubdGpkpIf+VoR5WhqV+VNhukKB3a6cJ8Huiz1xgg5oq1Wj5pgOMjricFDdYKbZwCK2qTAaPmimdgKjnlh5Yzl+nO4/TU2jRGKbUMR6rRHrpVCv2lKgS7BEYktLFUuDkUhscjJFmZzOZndOGUVeepKSaCRkIwRrmS25LVFRrvLM+uTl0YXEYvE4qb3aCQDFUhBAX6zUzz17kmZzQ8MPK5HXUJ+l89SESpkt6Yft3t34wQzQASMDRMG+jYwpWMQ2BdXVys2/hUdifXli27alpBJ/BzwQon49Yg1RncDDY9qEZbY0KxMAXkWs4eSuYPHESj9sQoLvJyKADqZmatExigxE+rr0qAnWSKza21tbZEMfebwmJ9NIKip0xV4QlNkyW5lAYrj+s5pQSe6SVgIzSV2SUNlGxhQsYpuCU6coEmSz+e6nTkykaX5+47eriaipUZKNfOmO+gx4sH8/cN55pLc++MB0MwEYjMQ6nYog0rATVFfX+flM9O8tXUpBhuefr50hBPC3vwEXXGDohurVTlBntK66bfZpJ2ioSOyvvwKPP+7/8S1FrBErgcTwRjZPjIyWVxcZiT1wIDA9It4wXV5LKnhph1Ghm0QaBMldZisTSPyygYdKmS1//LCSUBuZjDEEi9imQH3l9TVwuRSxMnTZDCgsVCKTcvP08KfM1unTwPDhpJGEAO67Txku3ShqbaorYgsKlCxeGeUDleypHUfAr1G7fv4ZuOYaEg733Qd8+CGA//4X+M9/gFWrgJEjgdWrddfRaHaC+npihQAefpieMh57DJg82b9MaDNJXRLDG9k80eg08EnHjnQ8V1bWL3CVnQ3cey+dmz//7P96JKbLa8mHN7Mi1o8yW9XVwCefAHPmKENXA6AHti+/BN5919QTgdfKBICuiDU8iImaxopS5uY2bFJlfURsqFgmGFOwiG0KzNSEkaHKZhSJlX7YmBjvI+6q8UfEfvop6f6MDNI3J08Czzxjrp0FBUruj0qbeqKzQfJe6dbrLi+eBQVekwpqaoApUyhBWB4mt/7eiZx7akOynTrRsvfco7sNmnaCigolFF5fO4G/Q8+uWAE89RSJ2bAw4Ntv6W5vFjNJXRJTBXGbHxoljX1isynPCf76Yk+cAIYMAV54AVi/nh7Q6uuxNR2JlSeiHNlDhTzPTpzQyPmTIvbYMWW4Zh1ycqiH+4YbgAcfBCZMqD1NNm+mwrsTJwLTppGiN4AQPuwEXiouAH5GYhs6Snn2LDB1Kv1QXbsCCxbUf53+ViaQsJ2gWcIitimQasyIiG2GdgKjfliJPz1bH31E0z/9SRGvL71kLiFd3uzj432MZipFrMYGaYrY6GhFFXvZqLVr6WaakEA3r3POAcorrPis8krgkksoxGyxkBrwso7iYmVfu0Vi5YaFhXmEwg33tNd36Nl582g6fTrwv//R63/9y3y43EyNWAnbCQCYE7FA/X2x//oXPTv16UPHc0EBMGlS/ewJpiOxOnaC1FQd/31iorKMVJM6/P3vwN69dEmIiQF++AH4/S1O4Lbb6OFTCqiXXwbeesvn+nJzaX9ZLMrv4IYBO4G6KoVPGjpKefvtwHvv0QW4ooKe0A1sty5Hj9JFLizMy07xAYvYZgmL2KbAn0hsM7ITGC2vJTErYnNygF9+odfXX09Bj8REut5t3my8nYaTunRErNf8Jx+Wgi++oOmVV5LmvWky+S8+w7WkzNu1I18sACxcqLkOub8SE0lzulCrmDppzoZ72usz9KzDobR5+nTgllsoOlNWRiZgM7CdwDT+itj6VCg4eBB48016/dprwNdf0wParl31sxX4HYnVELE2mxKgrU9y1+7d5BQA6HD+5hs6XT751Io9m0tow9evJ1UPALNmaYx167lOgIK4Hkn4VVWKONcQsXFxlIwPmIjGSoGXl2egaLQPli+nrjGrldT83XfT/FmzzD+0qpFR2IwMY116dWER2yxhEdsUaIys4hV1JLaZFGX2V8QaTeb/9FPaVaNG0S62WhW9t3y58XYaLq+lE1rWjMQCuhslBFnmAODqq2l6TT9SDquQiVODx9PM66+n6SefaDbLbGUCoImGnl24kG6MPXoAI0bQHf666+i9Tz81vp6aGmUj/bETtPBIrBlPLFC/SOwLL1AQ7tJL6VxMTQVuvJHek4LPH/yOxGrYCdTrqU9y1z//SfbuiROBc88Fzj8fmHAVXbtfxN3A00/TDnjwQQqTnjmjnPBe0E3qOn6cLhp2u+aPqh6NzLCIjY9XapbVR+QJoYjWP/0JuPhi6hrr3p22+5VX/F+3P8PNqpEi9vhxehBgDPPjj8DNN9c/mN4YsIhtCsxEYqWIramp31NrEKETuNTEbCRWBvOkLgKAMWNo2igiVqforVcRq1OhYPduqqwQHk43fQDovGEhzsEGCFjx5Q+1Q29dc41iKdAwDMuedg8Rq3MjN9XT7m+ZLRmFnTpVqYskf6wlS4xHfnJyKNPIbjf2QCjhSCyApovE1tQoP/mddyrzp06l6Wef+Xdpq65WDuWGiMQC9U/uKi5WelEeeUSZf+8F6wEA8zENuVf8nmaGhQG33kqvZZjaC7p+WHkNkU/sGtTLF1sfEbtxI5CVRaHgxx+neWFhlMwJAM8+6/99bds2mg4Y4N/yKSl0kXU6TdYfYzZupIo/K1cGuiWesIhtCsx4YiMjFe9hM7EU+BuJzc+nm4QeNTVkFwUU4QoAo0fT9JdfjPtiDY/WZcAT6xGs1LETfPstTS+6CIiNrZ25eDGuwecAgK++Uq182DB6Lf0TKmRPe/fudd7QGS3Oa21bLfyxEzidSkWF8eOV+UOGUF+pGUuB3MAuXXxX+VDTgkWsEP4ldgFKJPbQIXp2MMqaNXSIxMdTIE4yYgQdm6WlwOefm2sLoFQqDAszEVXWSewCDIpYnUjssmXkDOjeHRg8WJl//saXcQ42oAKt8MkXqq7v6dPpQe6HH5SnTg2kbtYUsdnZNE1P97p8vWrF1ie5SyZwTZjgnh07eTL1nshKDf4gRezAgf4tb7WypcBP5O4yEztoKljENjY1NYqIMCJiLZZml9xlVsTGxiq7wNf1dOdOEroxMe69TAMGkBWtuBjYssXY9xrudjWb2AXoiljZvlGjamcUFwMbN2IsfgBAGtBVjWr4cJquX++xnv37aephF9URsXJby8sNBET9sRPs2kUZJtHR7jcfi4X6XwG6oRvBnxqxQIu2E+TnKw9xZu0EbdvSeeV06uotDz77jKZXX+1uXbRYSMsA5q3QgCI027Uz+AxTWqpUFvASiTU0atfBg3SCaLBoEU0nTVINvlBYCMsXizAZHwKoI9i7dKGnVUAJ4WqwfTtNNXvOTYhYv2rF+ivwamqUDNubbnJ/z2YDfvc7eu1PEe/KSuVhwt9ILODjqYXxhozDaRTDCDgsYhub3Fy6i6izCHzRzGrFmhWxgHFLwZo1NB0xwv3GZrMBmZn0etUqY99peGQjf0SszgZlZdF00KDaGevXA04nBnc6i+hoEiIypwHnnkvTdes81uM1EivDMRobFh1NwX+gkYaelRHjESM8RkzChRfS1Kjnw5+kLkCJxObntzgvnPypEhLM58JYLOYtBU6nImKvvdbz/bFjafrzz+Yt/37XiI2MVHVxuKMbfExNpR3ndGrugMpKcsMAJGJdfP01UF6OSV0pcrhiRZ1z64oraLpsmWabzpxRmq5ZScqAiA1IrdgVK6jhiYmKL0rNlCk0/e478w+Ue/bQuRsXVz8lxSLWLzgS25KRjzCGwwdodrVizXpiAfMi9rzzPN+TPe9btxr7TnnB9/msoaPKpYjNza1TSkhuUF6em0eivFzpOnSJ2NqNChs1HCNH0iyXEJeR2M2b3fp4a2p0qk/pRGIBP0btMuOJlVYCV5hZRWYmKaXffjN2t5VCwqyIbd1a8Q7Kg7GF4K8fVmI2uWv7dtIH0dHAuHGe7w8fTpoyN9fUOAIA6lkj1ssYtVIHaiaRWixKNFajsStWUKC3XTvltATgCjOnXz8MgweTBl68WPW+FHgrV2rWwJJR2PR0L9pbNrah7QT1HbVLhqWvvVb7iSkjgx7C1RFbo6j9sIbGG/aCPHjYE2sKjsS2ZMwkdUlauJ0AaBgRK3udzIrY+kRi27Sha6zTSREVF3Fxyg5QbdTOnXRNT0pS3ZxVG+URTe7enY6Pigrlbgc6zKqqvOQ8+dgwwxUKpEKXIWsjyEjs+ed7vpeQoBgJV6zwvS7dlG0dbDblt2phlgJ//bASs5HY77+n6ZgxGqWhQHZ/eSj89JO5tpiOBunUiJVIl8/x414cAzq+WHnIjhunyq+qqVEirJddhmuuoZduloLevWkjKio0M2Xkad2/v5dGy0isRwanQkASu777jqaXX+79M9JmIMP1RqlvUpeEI7GmKSlR7uEciW2J1EfEsp1AV8SeOkU9zBZLnUhILdKCuWuX715kp1MJ3NRHxIaFKZFNI5YCtZXAYqltiMxUGznSTcQKAfqQhqVA+mHT0+sE/KurlXCclxCWzL9wE91ayGM4J8dYX/Dx4xQ1slrJTqCFzMbzVTy0uloJB5oVsUCLTe5q6kistDdL24AW0kVitl6sgV50d3xUJgDo2I+uLf6hqd10ymzJ5zN5jgIANmygC158PDBypMv2/dNPqqFoLRYlGiuzOlXoitjKSuWeYtATa9i2Ia9Px46ZH5HiyBF60rHZlB9YC7lDfvnFXK9IQ4lYjsSaRkZh4+KUKmzBBIvYxqb2CPi49CqXf8onftoJKivJjuVlZNOAYVrEnj6Nzmc2AdAXsTK3qVcvCurVpXNn6o6rqvI96M6ZM6ST1DX9veLDH2EmuUuKWFdm8549lAgVFQUMGIDhwym6mpOjWkxDxHr1w546RXcxm81r2QUpYn3eU9q3px1UUWFMDG7cSNO+fb16Eg3XQsvOpgM8MtK/Pq0Wmtzlb41YiYzE7t3r+7Pl5UpgUU/Eyrym5ctVCYsGMC1ifdSIBehwluuT63fDS5mtykrl9HPrZPjmG5pecglgt6NvX3r2Ky+vc4hLEStD1yp0RezRo3Q+R0bqXqikiC0rM3E/aNuWnsLVtcyMIrfj3HO1L8aSzp0puuB0Gs/uE0K5UHIktskJZj8swCK28TlwAP/Dbbhx6VRMnGjwHuqHnaCsjB5yr7oKmDHDn4b64M47SQRdc40iTgxQU6NshmFP7I03osvsPwLQz4qWzZDe17pYLMo1Tz7Ie0N2u6WkkGj0SkWFksbvQ8QaKbPlkdS1di1Nhw0D7HZERQFDh9Isl6XgnHNoqiq74DXnSUYc2rXzWlPScCQ2PFy5cWrUqfXAQ6FrIH2x+/bpR0f27MFptMHshDm4+16rt0HLvFPPSKzDQXVOL7tMSXhvdFatooxunSx2X9QrErtsGXo/Qck4x4/7fshZu5auQ23b6g9tP3QoPaPl5xsa0dWF6eIUBiKxgEER+9tvbrX6Nm8mYdqmTZ0RUKUwq+1St1iU3nU3zSYf3nbudNuxTqdS019TxKqtBDre0MhI5TZiOOhosykiz6ylQIrYSy7x/dkJE2jqZhTW4ehR4NQpVFkjsPTE4PrZ2mUk9uRJc2OS61BSQpfioBibqLzcayUNfwlmPyzAIrbRWZ0Vjb/iVQB0zhiqj+jH0LM336wEAT75pIGjsWfPAv/9L6mcRYuAv/3N8KKFhcrJLS+qumzZAvz0E3qCQj+5ud53w4YNNPUmYgHFUuDLF2vYDysbY7V67VvxGomVd99ag6HTqbSrblKX2uTr4YuVG7V7t2v4Sn/Ka0kMi1hAeRw3ImKlyHZtnAZGfbG7d+NuvIiHTvwNL70E3HCDSb9fPURsYSFFFt97j+yOf/+76VWY56GHaKir998Hpk3z2x/vtyd2927g2msRv2QBulpJOMlnEm+orQR6uTdhYco5K50zvsjPV65pOlZQdwyKWN0RoTt1IsVdVaU8KUI5F88/X7WtubnKk7WqJvJll9FUXp8B0EknrQqqms+HDpEoCg9XouBuGPDDSupVZstMcpfTqfz4Wtl8dZEiVhbZ9cW6dTiJVFwcuQZXXNsKQ4f6N4ocADoRbDaKrpgdeVCDzZvpYWPIEHrIbWD9aI4DB6grrnVrGh7PbDTdCxyJbck4nfjP4atQDTvatCaPkZcRQ90xGYktKFDEcVoanUhmRvP0yeLFpMBlt9zGjYZHWZKaLybGYImfl16izyeGoyPo7Nmz2/MRVwhjItZsJNZnZQIZBkhM9BrZ9Jr/JMNTtfWyDh6kQgUREUDPnrWfkZFYPRHbqRMJ6OpqVyhLilgzAx1IZEDZlIg10h0nRaxeJBYwVGorL+soPgWN8pWWRvdNUwnO9bATvPoqdR3HxdH///mPcfHlF3l5wPPP0+ukJAr9vviiX6vyKxJbVUVDHJeWAuHhGOwka0/WZn2fpJlgnLRIa1SK00Rqt9RU0pSGMGAnAHxEYq1WZcQBlS9WM19R+lsHD3b7zosvpt6dAwfqiC95YquSu6QG7tfPS4+QCU9FvZK7zIhYGU2OjlasTnoMGUKNczgMlddz/roel+JbrCoZ4mpaZqafhUbUpS7r6Ys9eJB+f/mTvP++dlm5JiE3lywqOTnUHfLxx8BttzXIqqWI5UhsS+ToUax10kk952maJUvp6WJSxMoISefOipVg/nxzTdVFZpL+6U90JFdXG76Lm/LD5uYCH1KBcHzxBXpbSKDtXuWprg4fJtEVFqY/gIt8z6iIrU9Sl8RrAXVZufzgQaCkxPW79e9fW0L17FnlRqlKhJLVqfburdVgap/E1q1unl+PEX7khunUJWqUSGx+vnIj1IvEAoZ8se+u6Y5KRGBwl3w8/DDNe/99X41VUY9IrEw2f+YZirYIATz9tOnVGGfBAjJdDh4M/O9/NO+ll/xK9PTLE7t8OfVpt24N7NqFQVGkvLK+9R65ys9XBJh6lC5vyERMow8Dpv2wQMPYCQCP5C71IHRuIlb6BWTotZbYWEWvulkKLriApqpC1nJ/eMuDNLMj/KoVK7tyzIQ6pQgfNcqHF6sWq5V8b4AhS8GSZTZsw0DER1Zi5UqKUJ865d+YCQAazBf73/+SXhw+nDoo7Xb6fWUcokmZNYuekrp0IfuRzUZFjBugMfJSz5HYFsjxtYdxGF1gRQ2uu9GGc8+lC6Asp+cVk3YCGfAaMoRsBVYrRQoaxLteXKyUTrnmGs3ogR6masSuXUtRoH79gAsuQO+2BQCA3cs9b57yhjlggHYpH0m/fqT5TpzQ1y8NKWK9BjOSk0lNCAHs3u3ph5VhqR493IZsbN1a0b+unkeVT2LPHtI8cXEa97ZA2QnkxnXpop/oAZASsFq9+mKFU+DNo5QIc9uUEtxwA4n+LVtUg0D4wk8RW1Sk3AfGjSNrOAD8+KO5oVhNMXcuTX//ezK69+1L56HJYa6E8DMS++OPNL3ySqBbNwwakwAA2LLJexaWHLygd29jdVyliN2xw/fQ0oAfIlbdXewjEqtrJwA8krv27qXLQGSkqpOhpka3xJSmpUBeSzdvpqgkDIhYKS49ulw88atWrHwKNmNWljYgKcqNoPbF6plJq6vx/B7an3+cXIzMTMXN9t57xr/OjQYQseXlwLx59Prhh+k0lQOSPfOM36v1j9OnFUX//vs0VN4ttyiNqycciW3BrP2RCln3jzuM2FglIdXnMKgmI7GbN9N08GC6gciEABP5V975/nu6W2dkkJIyOQyWqUhsnar/vQaQ/2D3Ds9uTCNWAoBsDDK4oBeNNTxal9wgHRGrayuTanTHDs+8J+mHlSMcqPDqi9261bWegQM1HA46o3VJGkXEGrUSAD59sXt/OY3dzl6IQDlu+lsbJCUpOsFwuUk/7QTLl1PHQ/fuJKAGDSJB6HC4WRkbjm3baN+Fh1NNTatV6Z832vdei8OhlHXyS8TWhlQH30aJhHsK2qLsbJnmImasBAAdjp060UO9keuUaRGbl0fC0mLxWpVDItd5+rRLS7ojez1qLzrqQehcFql16+jakJCgWe9PHq/Ll6vGN+jYkRR0TQ2wdi0qKpRrucYlgHaWiVrJftkJ1NYJI5lKQigBDTMi9qKLyBdy7JjuDXHzpwewwnkBwlCFGY/RffHGG+khduNGc1rbRQOU2fr8czrEOnRQHlDuv58Oty+/9LNd/vLGG+QtHjZMsaE9+ihFY3/+2dyY0XUQghO7WjRrN9MVbmQ6dWvJh2dVfoA2UsQWFhqq1ycvfEPIMuTSA74SMQyxifxwGDOGzlCppn791VAoyi8RW9t91/tiugrvPuWZESajY0YsWEYGPTAdidXZIClic3NVtSElGiLWozKBxsgNuiJ2i3BfjxoTIvbsWQMlj8xGYo2IWEDXUvDLRxQxGRG9HfGpFHaXNlrDx7ifkVgZXJP5KlarkrPjFlVrKKR3Ydw45UFJhuVMGnGlXo+OVmqh+iQ/Xznna0Vs2lVD0caahxqEYceb2t2TRurD1kVqPSPa3O/KBG3a+Ozijo9XLrmaloJRo+jat3cvcPKkth9WdouPH+85vDJIc3bqRFrDrT6u6sTeupXeT0ryMihdTg7lIoSFGdoRfonYjAza1vx8Y0+1+/ZRxDsiwndEQU2rVkpU58svvX5swdt0Ab025Rd06ERyJTlZOQf9isY2QCRWfu8f/qD83L16UeeFEPWIEpuluhp47TV6feedSpZhp06KD83L8MZGOHNGSVYzPFJeE8MithFZe5C8WCMHUwamvDAZFrFC+CwzUFKiPPVJESvFjM+IrxHqps/37k1X2bIyQwrCQOBSQfYN1yZA9b6WxOyh6g4o+00RTWVlyo3PyMO/keSuhrQTJCZSBBjQqFRTK2JPbz6KnBy65vTvD3ogUA1yUBd5r9uypbb7tV8/UlRnziBrAz1MeIhYIQyFsOSmOJ2UJKiLFLE5OfoPWEYqE6jREbGrV9L3jOqh3FRlb4Nq0DJ9pIjNz/c98oUKrQhjo4pY+ZSiLhgvRWxWlsZTkXf89sMKQXfk2ruWxWbF4A607zct8TT0HzhAiYU2GzB6tPGvMqPNG6NGrBpZJkuzHm5iovLQuHKlW2UCF7IMmizmXweLxYelYOVKNyuBZnUHeaHv3t2Q99SvgGNUlPIUbiScKHtORozQ93VpIffVJ594jfou/pXO2/+72L1XcvJkmvqlz+oZia2uVqLxkya5v3fjjTT1aRlsKFatoptXUhJw3XXu78kDrh4iVsYq2ral55RghEVsI1FRAWwsoNDryIspnVaK2KNHfQQxw8OV0IkPS8G2bSQ+2rZVrtcy+NUgIlbdVw2oVBeUlHgdDAQuiZoaJampNhKbnB6D1rZCCFixd6GiVtato/3Xrp2XiEUdfJXZqqlxH2ZdFwMi1mLRsRTUitisbXTqde9eOw7A2rX0RJKaqllks0MH6nl0OmsDtpGRQI8eEACyttIdz0MvnjxJfZdWq9IgDex2JfPeZ/ClXTtSK+qRwOpSVqb8lkYjsTq+2F8O0MPg+RcqN275YHLggMFCGa1bK14LQ74JeliQw62qR2WSw4zu3NnANdOdTuXuqH4669SJTvDqaqXbxQB++WHlWLB1srPOG0ki46etnieyvGGPGaMcR0ZQi1i9nmunU/GrNuRoXWpk7ladMQ0UatV5ztdbkJ1dZxC6PXtI/drtHkldaqSlYPFiVY+H/J3XrcOaX+hhzasf1mv2pjbygfzECXODSpjyxfpjJZBMnEjKaM8ezYvz3m0V2FfSHnZUYtxf3D3A8nzculVlzzBKPSOxWVlkO0lIUDrWJFdcQYfB7t1NZCmQD08TJniW/5FP2z/9ZKyUmQbBXl4LCEER++qrr6JLly5o1aoVhg8fjvVy2KYgY9+uKljgRBucRvcxdNKkppI2VV+UvWLQF6tO6pJIMXP0KJD30fdUE8jEVayoiGphbvyhQBEU6pFSfGZCKBi2Exw+TP0WERGuO5XFAvROIcGxY7USkZYP/6NH69ejBAAIgQG7qBaTt+Fn5UXeZjMQtTKYqeZVxNYK1Kw8OiZcwlP2W48d67V0l5al4Bg64GxxOMLClBuxCxny79TJZ30zw75Ym025O3qzFOzcieoaYF/iuShNNNgHpfbFqqKxp45UYH95R1jgxMjJXVzzk5PpfBLCYHKXzab8ZgYtBTIql5Li/nO3bq2cDuvWgcx5X37pd7XzkhL6rsotOykUHhPj/kRisfhlKfBLxEqRLLsia7l0GonB74uGo/qE+/6TIrZuVEoXpxOD2+fCbhc4dUq/tn52Nt2DW7Uy4ctrJBG7+icSAwMHqgS77A6/6CJdFT9uHL199KjKT92jB5CSgsryGiz7ho4f2SnhgUkRm5pKh05NjUkXjUkRKwDsTR9vqHS0G3FxpPoApSqNisWv0MVzTPhaxI1yH/mhQwe6DNXU+JH7oY7E+nHOyuvvqFGel+r4eOX5zxWNXbdOp/SFOcrL6f5XXg5qu14PwMCBdPyXlPht4A92PywQYiL2448/xj333IPHHnsMmzdvxsCBA3HppZciNwiHkuwXdRBFiMPqVmNhaU83fYtFsTL5DGIarFAgvWKuOqOga4OMUGZNfYHSOe+/33Dbb78dePJJ4OobW6EYtZlR6mFDG0PEyrtHr14kOGoZ2Y8yLX7IUrL1TSXDPvooujx8E2JRhMpK7e5C+Vt06aJpZ3PHoD/Ca4WCuDigd29kYRAADRGrUyzcQ8QOGIDNoKeX3r01evO8joDgiV/JXd6Ux5Yt+BteQY/8dYiOseD3vzewTkDTUrB6wSEAQH/bLiQMdd8Ovy0FBq8XeppB2v/Wv72dBObEiUptVxPcfjtp1l69gCl/iKSZ553neSBKEWuiZI7pgQ6E8PClS4ZdkoBEWyEKkIgN8xWld/Kk0iQvPemelJQA/fsjsksqBlaRAtHT5nIEq9693S4N+pi0E/gUsbUXm19yugCoYyWQRbl97IBWrYD/+z967SoPV5tn8CMuRqEjDG3balriCZMi1m5Xfnu/krt8idjDh7HuSFt0xUH0uvU89OplOvdQ8QV89JFHoOWrpfRjTxh6zCNaYbEorivTNZvlQ3h5uV9l62TwWd07o0Y+zC36tJr8BSNG0D79178M5bh448ABWtWYMRQk+d8jR+kaHBWlnVFpsSjRWHl/MUkoRGJ93bKDihdeeAG33XYbfl97V3z99dexZMkSvPPOO3jwwQcD3Dp3REYGqg7tQvvjx1FSpfR3dOkBbN8D7NoPjNazFCTFAXYAeSeASu/9pYdyANiBlA5AiWp9/QYDB44A69ADI+zLgFdeAHp2VUpveOHjT4APF9I6jxcBf7fPwlOD17u3oVM7atuRA7ptA4DThbSu6AT39nmwYwuts19Pt3VeOKEKzy0vwdK8DBSXl6CqClizkdY5bJSPdX70ITDnCcAO9MF6rMNIrN8ikN7D/YK4Yy+tL72nj/UBQMFpamd8pO62t+tE6zxwRGOdV47D5v09AJSgV3+g5MQZYNtGWu+YUV7XO3QkrfPXzcDZYiCiX098am8NoATDz9f4ngO7aZ3dO/n8nRJSaN05uQb2QUZnYMMaYO8OoNKznNDxX/bgTfsjAOg7530A/PGvBoY9zxwB/BvAyh+ACgdgsWD5d6cBewec2+k3lFS59yX3HgD8sALYtA240Ui5q7ZJwD4Ap4763B8AsG0PADvQvY/nPhl4DoB5wK8/HEGJtYbCAQ/dD3TtSNkdBtiyBXjjHfoOAFi4sx2W24diWOYIz/YN7kuf27XVUNsB4NgpWndCioHfFKDQbUkBEGEBurT3+J4x3bdj0cHB+OqrfAy4h977ZBEgwoCh5wAJyQa/Z86/gH27ADswFCuwEX2w6udSXDlJexSDzdtpO3r2N7h+ADh1jPZXaqKh/dUlg75jz0GgsFTjYTa2FXDOAKzYOhRACc45r7YtGzYA2zYB0Xbgqkt9ftc1NwLvvEf77enna32G55+LDxfHACjBVdcAZd5GQ91P+wwZXQwfA6kdgZN5dB3qoTMUsBsZnel79u/S/Z7qH77HLfb/4BBSAJSgtAq4chIlrhm2fVwyBmgdC5w4Any50BWZdRTVYPXpNoC9BBfeHI0SjXYMGQ58thhYtQ74q5lyd1bQtSAvDzi8j35bgwgBrPoVgB3KMVCHi8fT+xt2OHFkx3dIsgMQlcC/HgVsTuC++0w0ljiTB4zIrA0y2IHcfOBPzyShp30IzrmsPa1X67c6bxjwwTxg8zrDx4ya7GP0fakdlW2NskfB4rMLtOmwCBEUI/76pLKyElFRUVi4cCEmqp54p02bhoKCAnypkeFYUVGBCpUXpKioCB07dkRhYSHizJi3/KCksgQxs2Ma9TsYhmEYhmGaCscsB6LDjZY78Z+ioiLEx8f71GshYyc4c+YMampqkFqnbyw1NRUnvQyBNXv2bMTHx7v+OgZzTJxhGIZhGIYxjggRcnJyBACxZs0at/n333+/OPfcczWXKS8vF4WFha6/o0ePCgCisLCw0dvrdDqFo8Lh8fflNw4Bu0P07Of5ntvfvTOEww7huG+G188UlTmELZLWt+eA+3tZ194lYHeIVpH5oqjMIRxD+tH63nvb6/qef4XWNXqsQzhKC8XfWj0tYHeI23533P2zJQXC0cpK6zu0T7d9CKd1HjjiY3u7daT1rfzR471Xhr4gYHeIpIRcAbtD2KMdYv9hH+t787+0vuGDhaPCIX54YqmA3SHaRh70+GyfgdTGz7/ysc68E7ROO4QjP1f3s79l0zqtrRyioMT9vX+/Ru9dZP9CODq3o/WlJArH6Rz9769wiIPHHKJVHC3fqTtNZ9ifFI63XvP8fGprWveGNT7X+9gTtK7fTfexDyocwrEri9Yb10o4yorc3vvijT0CdodIC98rCosLhaPCIUZeQOt+Yo6Bde/dIRwRFuGwQ2zreZGA3SHCW+WLfIfnZ08X0Hphd4ijpwys+x8PUbv/9Hufny0ocYiwKFr3rn0an/n8YzHC/p2A3SH+904xzbvmSlr/zLt9rv+uB2jdk66vnffFp+JK+wIBu0M8PtvLcgN60/q/XuR7Wyscolsv+o5lPxnYNxUO4fjrH2n9D9zl9TMzEl8SsDtEh/ZnRIeutP5HHje4/tJC4WifQt/x1efCUeEQxeUOkdLqELXzH0s8lsl3KL/Dzt8Mfk+FQzhax9L37NhseJkbf0ff89gT2u8/8Hd6f7L9DeHomS4cPbvSd4w+z3i7Khwir8gh0nvWXgMudYjwGHr9nP2PwvHSM9rLPT+bvmvi5aa+6+F/0Lqn3WZi31U4hOPaCfR9T/9L8/2lCw4I2B2itf2QOHvsmGv+RePp++642+T33Vd7v0uMFo6Jl4th9h8F7A7xxqundJfrP5S+7+PPTX7f7bfS9z36oKnl7p1F33fr7Tqf27ZRLLSPE7A7RJf0fGX+qp/oO1tZhePIAcPfOfUP9J1jL1fN/+wjcZ/9UQG7Q1x6lY91jBhC37tgnqltzXc4hCWCvlt9v3U6nY2un4QQorCw0JBeCxkRW1FRIWw2m1i0aJHb/KlTp4oJEyYYWofRndKYHDggBCBERIQQNTU6H3zySfrgrbd6/cjx4/QRq1WIqir396oGDBERKBOAEAcPCiEeeIA+PHWq1/VNnEgfeeopIcS+feJD3CAAIYYN0zhou3ShD//yi9f1nT1LHwGEqKjQ2daaGiHsdvrg4cMeb+fe+7RohxzXunR2iefG/POfQgghivYedy1/OrvY7asjI2n+vn0+1pmdrfx4Pk7kmhohwsO11/vnP9P8B2zPKTvo2WcNbBQxY4ayGCBEFgYIceed7h8qKFA+UFTkc51vvEEfNXQqVVUpG3fwoNtb/5y4SQBC3JT8rWveSy/RRy+5xMC6hRDixhuFAMQn+D8BCHFOvzKvH01NpXVv3mxgva++Sh+eNMnnR/fupY9GRno5T6dNE3fhBQEI8de/1s5buJAW6tjRx8ktRO/e9NEPP6yd8eij4iXMEIAQ48d7WUge0//+t8/2CyFEfDx9fPduQx8X4qKLaIF587x+pHjCTaIDjrgOrXbtDB1exM8/00KJiW4XhBt6bBaAEP8Y8qXHIjt30iIxMT53qUJJiXLsm7jWP/UULXLTTdrvjx5N7/8v/l5l/V26CHHokOHvkHz9tfs5fHnPfcIJCHHttdoLXH+96uJsnDffrF3/5SYbOGcOLXjNNZpv3zN2K91Okpe6zf/mG1osNlYIh8PE9xUVuY6/YkQLG6oEQJdcPW66ib5v9mwT3yWEEP/6l4mbicKVV9Jir7yi86HZs0URYkSYhbbhwAHVeyNH0gqeftrQ9xUVCREdTYusWqV64447xC70EgDdOvPzdVZy++20gvvvN/SdkkOHhGv9hs+9BsSoXgsZO0F4eDiGDh2KH+WQiACcTid+/PFHjNQcoy84kY6GigqlWpMmBkpsyTJ37drVSUSorETY7u3oASpyuWsXlKz3777TLCtSXa2MJHPxxQB278Yw0DCLW7daPOvaGqhQILcvJsZHhaczZ6j2lcWimU2cPLI7tqM/Hmv3P0ycCPzznzrrAijrVFapr02yie3RDl1tVCpg2+dKaYjjx6msaViYskk+NygpyWdtL6tVyZ6vW6/XNVLXC1NpwO3rrwf++lcfX67w2GPAbbfRsNhr/74EA7FNGWVJIstrpaS4V5bwgqnqBGFhSjkMWQ+2lnUb6UAcMbDcNU8mzq5cabBW/3//C7z8MrYMuhUAMOQ874kXukP81sXE0LMyMbtnT42KZ0IAS5bgXFB5PzkEMq64QqmhpFP678AB2m1hYUryMDZuxBgsB0DVcKq1knsyMmi6b5/P9peXK+OkGK5OIFPzdYY0jRk1EB/hRkxKW4ennqLNNHB4ETKLf9IktwvChZfS6593Jntcm9Tjn3ipPOeJtJdFRpponFLhTSvb3eFQRoUe/cOjwIwZdE39+WfdGszeuOIKqjJyzz3A1KnAvOfyYAFoplaainokBBP4NWoX4HM4ta/W0gXjqovck4UuvZQq8BQXA0uXmvi+2Fgqyn/ffVhz3v2oQRg6d/Z9TfZZVcIbfg54ICtlyGu7Jl99hVg4MLIbXWfkaHYAaIgvAHjrLUPlvT79lIp59OhRp+rd99+jN/agT8ciVFUBX32ls5KhQ2la9x7hA1leq0MHE+deAAjipnlyzz334M0338T8+fOxe/du/PnPf0ZJSYmrWkEoYLcr1Zm81YoHYErEytrNLmoLovax73f9i/PPp4v6yZOaZ/zmzXTTi4+vPeb37EFXHETr8GJUVmqMdmVAxBouryUvJKmp2iPRDBiAJJzFP/LvxKKFNZ7bW5dNm5SBA1TF9ge2pZvb1p+UpwepB9LTDZTXMlgjViJr96rr01dVqQZBuyQZePdd4OOP6bcxSOvWwP/+BzzxBDBiau1QQ+vXK+MDAkotMSOjQcCkiAUUoaMSsUIA607QU9rw8YluH23fnh7cDJUrTEwEZszA5lQqHK83XoLUDwaqvZkaelbuPs1qRkeOAGfOYFhYFgB6KKmsBNVQkuOuqh626yJvOJmZVB4XQgAbNqA/tiMxrhoOh5cxDaSINTDIiNTp4eG13+GL/HxF/OmVcBo+HKOwBp9b/w+zZmlce7xRUwN89hm9rjOy0Jhbqe7grxWDUb7tN7f35AOgxvgf3lHXiDWRRX3eeXSzPnjQswTyjz/SudutG5AxNA54+WXg228NPPl65/zzqSrb/PlA8iWDqFRBbq7nQ8rx43TMWa3mhnaFotVMi9ihQ+n7cnI8hN7e7ZXYV5JGgxDc7j78rcWilBFbuNDkd9rtwLPPYvnoxwDo1MtV4beI9WPAg+Ji5TpTd5ADF2fOuGrOjZ1AyU9uIvb66ymqs3+/UqtLh7ffpumtt6oO5aNH6QJlteL/JtMDoHw+1ESK2M2bTdXFleW1grlGLBBiIvaGG27Ac889h0cffRSDBg1CVlYWli1b5pHsFezI+tte8tEIA3VivYrY2lBf7/YUitm9G3SBPOccel+jOrQUF6NH19Zi3L0bFgDndKS7oSvaJDEhYn1qPnmR9DY4c9euVAuvvNzQDdwVPagzfuOAvlSHUC3I5eq6uw8Io00DiNgNG2iEmaQk99q+ftO9Ox1QlZXu0T8ZNjJ40/NbxKruHgc25iOvJhHhqMDAyUqdUYtFicbKALkvhFAEjJ6IlYehoUisiTqxcn2apYJqf9Bu/SKRmAj3hzxZ6VxHxH79NU2vuqp2xtGjwOnTsIbZMHo0Ha8ao++aisSqh5w1pOPkOtPS9IfdkuLm2DFzymjTJmpUXJzHaGA9BkaiXXgeKtAKa99yH7lCCgBTA0KZrBEriYtT7veyFrVERhUvu8yULjZORIQSZa07TKiMwvbvr4xnbRAZic3N9TFKZF1iYhSlVqdXYclrpG7G2Ncg7oJBHovKZ5Svv/ZjNC0ox74ZEbt7t8lRyfyIxMpegXbtdG4BS5fSxWvQIIy9Nh4AXQpcbYuJUcamXbBA9/v276fLuM1G0XoX8toybBiu+x31Un37rc6+7tuXHhAKCrwPUKOB/Giw58OHlIgFgDvuuAOHDx9GRUUF1q1bh+Gy2yOEkJq70SKxtSK2Tx+62rp0hrxCa4hYOcu1O2sjbMMGUImy+ohYw5FYbyLWZlMuqB4hYQ2kiK1zbAwcQ/t02wll4AQ5rKjUB7oYVuWE1gOwtGyMGdNAXTQWi3KHVz/Zy6cSt6rs3pEiNj/fYD1ujRDIuo9oVJrBrfYgIs19H0kRa7Tm9okTdOO12fTry/plJygo0B66TYXuSDW1ItYydIjrGcF1fkiBtnq15l2lrEwZrEIOQ+pauH9/jL6ICrzXFVEAlCet7Gyf7Zc63ecIdBKj47rGxChhUTOV7aUavegij94WiwW4sDcJz+9/VE6KvDzluqRVy90rJkfrUlM7MJfb/hdCEbGu36wxkFXyP/rIfb6fVgKALlVyd+sGTbSQ3yeHIq7ll+/IQnBJ/5OaF7GhQ+m8LC311OO+cDiU08GIiO3WjbavtFR/1DcP5E2zoMDguNXKoCq6VgJ5oFx5Jc49l1wSZ8/WsZTdcANNP/vMi29IeRugU8bteUxGAsaORd++9KBSWalzOoaHK9eOOvYvPTgSy3iloUSs1yclKWJH0Tp27aoVUTISq+GNkTeLc84Bfbj2YB98PnWJeAztqR6Y2wsycOlTxEo17k3EAoqSMSNizz3XbfbAq+hs3FHdC8WHSZBKUakettcrhjeI6N+fRNiZM4pOl/eDiy4ytApj1BWxhYXKfqozfKg35CYJ4XOkY0KGRzdtcpkv160gw+vwrp7d9VLbbdtmbP0yet2rl77TwpSdoHVr5abrw1KgewGXjRsyxHWIuURsjx50HFdWkpCtw6+/0ltpafRRAMrJN2yY67lL+qbdSEujnVFT43ODTQ85K58CjPg7ffglNZE3Xi9q9Mrx9OS0YN8wV9Tqxx/peOzXT7ncGEJek+ohYtWR8B076BLVqpUxYeU3119Px+fatcowpUIo/hOvQ3l5x2qthy9W1mP/+GPloamsDOsOUo/GiOu11Y3aUiCFmFHWrCFdZ8QPC7jb801ZCuLilKi2wWis9MN6tRIASvDg4osRFgZceCH962YpGDOGogZ5ecoNSANpx5D7EgAdD3JlY8e6xTBcIzlqIXvOjAwlXEsoDDkLsIgNCKbsBA6H16iL10hs7SNjxiVdYLORl+f4cSgiNivL7QmwoEDpTRw6FHQHLCwErFZ0z6RHQDm8rcdG6CjxBovEAsZF7KlTdEO2WDy60tP7RiHDdhCViMCS987i1ClFz7sSbPQwaSdo1UoJWm3eTJ5Q2csvL24NgryKrVlDx8ratdR/1bWr4bt/WJjinTRkKcjIIIVZVeXqQsvaFQEAOGdUhMfHU1NJtAmhqe08kJELXw8XpuwEVqsScjYoYjW70lQi1jX8rOxxtVh0LQXynnXhhapuaamAzznHdbwcP67hJLJalYiKD1tNk4hYneQ1N0pKlB/di4ideHtbxKEQh6vbY8UyehgyMBKzNvLCatJOAFDHhcVCu1ceA2+8QdNLLjFlXTdPu3aKSpbR2F9+IeERFWViXF935CXAZA4TbXBqKp0r334LADj2xhIcF2mwoRpD/+K9F1Q2delSn50GbsgIuJmHhabyxfoUsUeP0k622Vz3HmmRdxOxYWHAtdfSay9m1kOH6NnWaq3zs+/YQd0skZGucXe1OuI80Mhh8EUoDDkLsIgNCIYisfHxymsvoStNEVtQ4Lr7hffp7rrn7doFEh6xsdSnqTqY5T25S5dafSbf69oVXXuRcfzMGaCoSGMjZGUBDRrMEwsYF7Hyxtq7t4e3z2IB/i+NVOSni8NdXV3nnGPwZm9SxAKKCFu/nqJw5eWk/w0Of26Mvn0pcl9SQsJJRgO8De7tBdO+WNcg4YuAVavwWxkdiL1v0jaxGrrY1iKPST0/LKBorrNn6WHNJwaSu0pKlGPXIwpx4gSJJKsVGDDAJWJ37VJ9vwER67pJC+EWiY2LU7ZJ3jTdkG/66Ds1LWJlZNdI+EuK2A0bjHlPVq2ia0Tnzl7N55FdUnFj5GIAwPxXi1FRoXRF+y1i/YjEJiQop83TT9N+lMk1d91lenXmmTyZpm++SQGMN99U5vs5yqTfkdiwMOCmm+j1u+8CTifW/Zee+vu3O4OoWJvXRUeOpOtJQYHBZM5azPhhJfUWsQbVvQz0eL121yZ0YeBAIJp6MKWIXbWqTmWW66+n6eefa94/P/+cphdcUMcSpDaJR1CwQB6va9fqPDDIRpsQsRyJZbxiIIhJT3NSyGqIWCG8aD8ZUUlOBqKj3U9wq1VRVSpfrJuVwPVhAL16ITZWue+7RWOTknx2zTZoJFYakQ4dUmoHaeHFSiC5bgiVnlq6pZ3rIfiyy3y0T+KHiJXdk6+/Djz1FL2+6KIGTg6xWhXn/yOPKN2PBv2wEr9F7NKlKHz2fzgFOrB7DNFOPpEXW91ur1qMJHUB9EwmnTcNVWZLXrzj4tyfJQG4+xyiotCuHd0LhVAl8EkRu2mT27lbWqocnq5I/P79dDxHRLjC9jLSoyliZVjER4KGaU+smUhsnz7UFetwGLspqjx8egf+LQPpR//4+9a47jq6LCQlmX4Wq5edAAAef5ym//sflbIrLyfd3qC9J964/nq6DmZnA9dco0TqbrvN71X6XaEAUK4rn30GXHgh1u2jk234WH1BbbO5qhtCY0R4TYqLlRiEGREr9ZmsKGIYuWMMRGLLypRTzmsSsOxmU5X87NVLqczi1gMl1akXS4GmlQBQnuxUPRp9+tA9trTUS1UTwHQkVv0gz5FYxgMZHfFptNepUOBwKNmmbjeqOhEVj2NXo0KBh4it42DvWltFxU3E2myKuvWixg1bSI2I2NatlSdnzbt7LfIq6CXhb9CIVuiKAyivtmPJEppnOFnDZGIXAEyZQtokL4+6R+12YOZMw4sbZ9YsevrfuJGi1TExJtQ5YVrEnnMO/WYlJdj7NWXItWtT6TVgJMXIxo36Wct5eYqmGjTIdzP8qlCgE4nV7UaTPQGqhnkkd7VvT3cvIdzMldLt0bGjck65Tr5Bg1wZOPJ5TZ6GbhgUsaYisUKYE7E2m3KxMOKL9eGHlYy4MBLj8Q3Kq8Jcz2Fz51JPuinqYScA6MHzyispyCzb8dBDjVSVoC5xccAHH9CXff89Kejzz/f6UG4Ev+0EAEUV//xnsietXIl1oOvquWN8/ygTJtB08WJjlZ1WriSXW7du5iqXySqCsjS2YUzYCeS9Lz5euU56ICOxKhFrsehYCq65hl5/8onbao4dU1Yl4wQA6KIp/RYq/5vVqlxbvfZySaV/+rSPAvWE7oN8kMEiNgAYshMAusldUmhERta5yNcRsR5dLRqFj42KWI+LhI+QsqFIbGkp9TkB+iIW8G0pcDp9ilhLjwz8AW+5/u/a1UTpRZOJXQDpkldeUf5//HH9bHu/SU1V+jujooAlS3zvzzqYFrEWC424EB2NvaDsih59vY9q0aUL3Teqq/W1j0xq6trVWI1TU8ldJiKxmt1oMtyjGhDAI7kL0LQUqK0ELkGkshJIGiISa0rE5ucrXgijhfuNJnedPEnXE7VX2AuWIYPxJa7G75PIVvDww6oyZEZxOpWN9zMSCwAvvkjXwyuuAD78UBFkTcLo0VSHtk8f8jQsXVovBe23nQCg7331VeC111DTbyA2RlCiqJGiQOPGUQdDdrZGYrAGqnwlU0gRe+oUBXcMY6LMlroUo+ZPUV6udB/VGXxJU8QCiqVg0SI3H4C0EowaVSelYflyCul27Kjc2OH+lR5VhCTR0coFzUByV6j4YQEWsQFBXltzc31YyqRY0hGxHk+FvkSsOrmrqgpnzyqJsEOGgB6Z6zjYNSOxgE81bihwKS8g0dG+PV+6ISpQvazCQlL23tz33bvjQTyN/XFDsGkTXXds3q1d7vhhJwCoG/K554D77gPuv9/UouZ4+GHgH/8gtWSqsCYhN8uwiAUoSlNcjL13vw5Av/atxWIgYgC3vClDGLSJElLEGojEaopYWZPNVVoAnsldgK6IdeuWViV1SdSHuUcEqzFErIzCpqQYz1wyKmLl9g8erBPCgusz4ajCO47rkZ9bhSeeMNYUN86coYuqxWLCS+FJ9+7003z9tVLWs0n5299I+c2caWrUMS3qZScAaF/efjv2fZqF0oowREUZ8/RHRysCbvFi35+XAXsfzzoeJCYq8R55LzOEiUis9MN6LcVYez9FSopHmTq5PZs31wmCSkvB2bNuZcy8Wgm++YamGsWKdQoPKZiwFIRKeS2ARWxASE6mY9DpNDj0rIadwKiI7dmTvisvr/a+3a0b9Q9UVAC7drkO+u7da7/u6FHK4FLVLpFPul5FrBdfhKFIrLyypqX5jjb4isRKFTFkiPbIXwDQvTssALoVbcGQznnGcyVqapSIsUkRCwD33gs8+6wJwewPkZE0Jq2fXY/yWDLQ2+SOxYK9RymRwdcADkZ8sTI46csPKzEVaTIw4IFZESs7Nw4dUmljWQh4zx4gJ8et/qVLxFZUKDNVoa2ePek4KSzUCBJJEXvsmNc+2upq5Tc0pOPMWAkksobojh36NdPUflhfdO1KyqeiAgln615sDCKvRW3aeL8GtDDqZSdQIWMHffsav47JCLYvX+yJE6TZLRb/vMd+WQr8jMRqIu9Jgwd73MfataOYiro6FgDaiVKp1loKjh9XEuGk28CFWsTWQT7wHzyoMz6SiTJboTLQAcAiNiCEhSmCwd9asUZFbFSU4i/SSu6SgkHeiF1Xql69XOObe7UT6ERinU6l2boiVt71jdxt1SJW6wbuZZADN6KilIuXkdG/JOorgwk7QShh2k6gQvay+xKxMkDsLZNWCOUibrQspoGSxQoGIrFeL+B5eYo6VIVkEhKU7XZZzRMTlfPsxx+xerVG/Us5VHBqqtuOi4hQNLJHN6w8dsvLvf5QZ87QflRXFNPFTGUCSbt21Gan08vIDKBGGPTDAqCbv9wPJupZulHPpK7miDw/iopMdrfXQd4azNihpB1k/Xr981OKOyMBey38ErEyEnvqlM86YD4jsVLEetk5UncuWlTnDbWloLISH31Ep83IkXUeonftoo2z2zVD1YmJyj7wmtwlFbiBncSRWMYnhpK7GsBOAOhYCjZt8umHBRQRe/hwnQFGdDyxhYXKUHuGRKyMkOnRsyedxMXF2lk8RkQsYGr4Thdyhycm0lNIM8RfEet0KrtSFaDUpHdvJZPWbRSbWg4domiE3W48oNxkkVgZhe3QwVVCR+LLUqBpJZDi74ILPKI3cj96HKIREcrFw4ulQJ6ObdoYjJj5E4kFfA+xu307/SitWhmvlOFHUXY36pnU1RxR1/U39KDnBanTdEesqkO7dsp5LIdb1kKKO0P1ujXwGmjRQ0brhfC5YwxHYr2IWK9D8Z5/Pp3P+fnAjz/ivfdo9u9+V2cFH35I00sv9Wov0Uh3ccdrl6onHIllfGJq1C6jdoKCAqXLW3VD8hjmXlWhwEPEalR0TkujoGx1dR37kM5GyCbHxLgCutqYEbF2u6LI61oKysqArVvptS/1Y+KJ1IXXp4bmg78i9uhRCgza7b5HLbVaFT2j5YuVUdihQ41npZsSsT4Su4TQuYBLEasRbpaHnFtNTDcRSz0HmiJW1mFTIZ+zNDsLfPhiG3WgAzW+ROwXX9B03DgSskbwo56lGxyJ1aQhLAWGhl3V4OqraSp1WF0cDqWnXIo9s5jQZwpWq6EyW+XlyqmmGYkVwufOOecciiuVlCjbCsDNUrDjjdXIyqLrqAzQutYvB7+QdYQ18Cli1UrfR7kIjsQyPjFUK9asnUBGYWtrxErkw6Grq7P2aM/NOu46WF1JNBqP2zabEth1u0gYELE+e97NiFjAuy92/XpS2ampvm/GpjKBamkBItavxC4oQis93ViQWm+YRCkCzZS4lUG3wkL90l0AlOOsqIg8qXUoLKSbFqAx2Jn0TGiEm2Vv+cqVqi7bUaOA8HCcyKlxWV9dPYFVVUpdSQ0RK5+zNDsLGlrESvXvMfSfD2SZhd27tZ8gpIg1M9KUFLH1tROYGqe2+VOvCgWgY1pe+82K2ClT6DD5+WftxKslS+ic69aNKnr5g99ltgz4Yg8eJM0XF+fl8n/sGAWPwsK8Zryph+L1GKSrVrG++w1dmy6/vE7axaZNdJGNjNQtk6FRPdOdzp2pISUlunYq3Qf5IIRFbIAwZScwGon14m0bRVVRlPqcXbsCiYnYVEVXo549awsD5OcrkViXSZZQ55MY2QjD1agaSsSqU1t9JYjJx0sWsW7ITSsoMDdUpDzsXLVPfaCuUFD3e6SwNSNi4+KUqK3P7tKEBEVpa1zI5fIJCRrBQ42kLknPnrT9lZWqwGRUFHDeefgSV0MIC4YPV1U927SJTsakJI9yOUD9IrGmBzpQJ1eaoXVrJfuubjT28GHyi1itStV7I6hFrJHionXxd1uaOfWtUCBvC23bGr9USzp3Vh7e5s/3fF9m4193nf+VxKSIPXSojuXNFwYqFEjx3q2bl/bJe1HPnq5RtLSQ0dUvv6wT9zn/fBR1H4L/VU4DANx6a50F5U676irFF6KBDERlZ3vJtYyIULZXJ2Sdm0sPFRYLi1hGB0OZ4P5GYutEItPT6ZpeXV3r2bNYgDFj8DOob9NlIV21im4cPXt63AQ0RawMJ+fleVw5DI8L4K+IrWuoNJNAwiJWk8RE5SLtNcNVAxldMZoXNHQoPf8UFLhn6546pfQiG03qAqjNhiNN6mwnHRGr2RutYyewWJRBM5YuVb1x8cX4HJRm7JZtLO/cF12kjHynQkZiDx7UuCk3ZCTW6axf9FJu9AcfuM+XUdjzzzenejIyaH8UFhoYDUYDFrGa1DcS66+VQCKF2dy57mUljx9XBpTwKCllgvbtFcubj+pz7hgQsfK26tUqZTDj7ZxzyHZUXk5lgF1YrXh94GsoRAJ6h+3DlZeqnuyPH1eGHvYxaltCgnIN9jo6uwHfhdxeuU+DHRaxAcKQ/9CsiJUnYh0ji7o+p6sLd9w4LAXdgFwVOzwGdlfQPNfl0LNCeAiCRrMTDBtGkbT9+5W+1vx8pQ/FrIg1Gu1pASI2LEw55MyU2fJ5ka+DurLMxx8r86Xt65xzzEd7pKWgvr5Yr3lB6uw1LynKV1xB06VLlcPq7NjrXQ+Lk0bUisXqakX0TZmiua4OHShwUl2t8azVkCL29Gn6EovFhP9AxS230PS775QDoaYGeO01en3ttebWFxGhhPT9sRTIA4ATu9yorydWRmL9FbETJ9K94MgR4C1lrBk8/TS5es4/33hdaC2sVuX6Y6pWrAE7gU/LuI+kLonFQiO/ATR+hBw9vbAQeHE1ZYbOrH4C1jffUBaaPZt20KhRhgroSjuGTA/xwEAGnD/FSgIJi9gAYUjEGrATuEU6dYZvld2zUsQe7ncFdqIfrKjBuBFFNFMzhZrQFLE6Q882mohNTFTaJ4c2+flnEhm9exsbpcpAmSIPWoCIBfxL7jIbiQWAG26g6RdfKNZU2WsmdZEZGqrMllzeQwOdPEnHi83m9W42ejTZ1o4dU0abfX99D1TDjv7YhowfaoXd99/T+tq08To0sNWqBE08LAXyZPRy45WnoiE7gRR9qan+1VXt1o1urkJQmA2gH3XvXgoN/f735tfpry9WCI7EeqG+dgKZFNy3r3/LyxLWAI3JcvYsicP//Y/m/fOf9R/WV56WhoaflpiIxHq9vpko23DVVbQPi4qAqVMpH/nGG4GTJy1ITyrETVhARcXXraMRIt6oFbSPP25oB0kRK0c99MDryEUKLGIZQ5iyE1RU0NFeixDKcpqRWI0EDRmJXbuWAi/f7KBozkisReusn+iqIk9GjUQTuUqP4I+X5C5Dnlgh/BOHsl9Wilg5HIzR8QojIpT+YqOWghYmYnUqUHlgNhILKEMqFhaS5tm2jRwidrt/IyQ1VJktGYn1sBPIi36nTl7FXmQkMI1sbZg5k06pf/6T/v8L/kvdgqWlSpTyppt0++u8VoJTK3aNngRTVaYaQvT94Q80fe01uns++ST9f8cd/o025W+FgrNnyZQMcCS2DvW1E8ifQsO+bZi//IWK3uTl0fk/YgTd2jIz/RvgoC5SdBkafloiezV07gO6oq6iQkn4NFBA12oF/vtf8tsvXkzjDi1bRteOhd/GwX71FXQMjxhBZR2qqsgsbHAH+YzEmrATsIhldDGUCR4bqxR6VFkKCgsVX5HRSGy/fqSJHQ7KjpQ1+y7HUvLnLVpEN8TevTUNgZqeWEARBHU2xJAntrBQMfyZ6T+++mp6Kl2/Hvj2W+D992m+W10SH5j1xbYQEeujApUH5eXKjdHMRc9qVSKuf/4z6R2Akm/9GBDNPzuBmUis7H7zkb32j39Q7sWGDeTrPXsW6NvHiT+kfk3qMj2dTIAWi0YGhzvSF+sRiZWNKy9XSuqpMNWj3hAidtIkUjenT1Oi15YtlNQ2Y4Z/65OeYzN1nAFlW5KSdBNsWiJqO4HZfDn1yHGyXKM/hIUBb79NgY09e+h06NuXAvj1jcICfkZi5UUrJ8drNquXVBNizx66hyUkGK7uccEF9OAeGUlfGRND7qIhQy3UHaUWrLfcAixYYHgHDRpE0507vSS4cSSWaSikFsrP18mmtFg0a8VKPRUTo8qgFkK50micTDYbcPfd9PpPf6KyJgBwFb6iM+hvf6MZHlWW3Vd55oxSgshtQ7yIWEMDHbhtiAHatVMyfy6/nBT91VebS2mXItZoFkALEbGG6herkM8A0dHmd82jj1KiQ34+2VxatQLuu8/cOiR+1YrVSBzymtilTlHWITWVorCAEqB54UUrwhZ+RCdDbi6d12+95bOekNdIbKtWynWhzgZXVSmnlSFd2hAiNiKCxn6Xfc1dulAxTLPGZoms/iAT6YzCVgKvyF1SUaE/SrAWMgqblkaRw/pw7rl0Kj35JPlD163zeUoZxi8Rm5JCx6/TqWkpKClRLv2aIlZtJTChxC+9lK41e/fS+idNqn0jPp7OJdkz+s47pgbX6dKFYl/qALEbUsTm5NS5kSuwiGUMIcWdED4uKhrJXZp66swZn11p999PF4ziYvr/738H+s+szUYpK6MujPvv99qMyEh67XauexGxhuwEZv2wal56iSLOTied5M88Y255jsRqYlbEqi94ZqMpERHUCZCRQfl6GzfSIegPpjyx8vzQELFeu+INRmIB4MEHgXnzKHnju++o1j/OP5/u2NOmUa+HjygsoBOJBbyqdtn+sDCDEe2GEn6pqcDq1fSDbt+uFAP2ByliDx3SrOXrFa4R65WICOV4MGspkCK2PlFYNfHxJGCffNJj4Lt64ZeItVqVe4HGgnJWQgL9eeDPWLy1xMfToa7ZaZCYaFoYA7Q5simavtikJFK5Qmj6LtSzWcQyuhjOBNcYela3MkFqqlefXatWZKRPTqao7OOPA/jXv2isv3btqFvey1OfumacEREr9amu5quPiD3nHOozefxxSnH3Nd5pXcyI2MpKcuIDLGLrIJO6zPhh1XTsSBGD9ev9TxoBTNoJ5Ic1FK9XO4HBSCxAp9C0aeQBdCuW0b07qVs5hJEPZCRWs8yWFxGrbr9G5S5PZO9NQwi/+HiqRqBTy9IQqal0o3U6zQ3BxJUJdPG3QoFM6qqPH7YpkCL26FH3Ml4+0THT6loJAMOVCZoSXV+sxaLriw21GrEAi9iAYsgXq2MncNNTOn5YNRddRNGaF16ofciz26nr7/hxnzdozUROHyJWV5/WR8QCdNN85JE6BTgNYkbEyqcMm83L43jzoT6RWH9pCD+cvEEXFVEXoC7SK1BHxJaXK8+KXu0ERkd0aABkma2qKg3XixcRa1rHBWMXvMXin6UgGLcliPA3uashkrqagrQ0eoCsrja5jTohXDmrISoTNBXSF+tPma1QqxELsIgNKP7WitWNxBowlxuK0GhgVMRWVCiWhUYVsfXBjIhV1zPzd+eFCFLEGk3sqm8ktqGIjVXsLj4FuFR4skYq3JcLD1dOOwCUDSnfbCgDnwHUZba8VijwEok1rOOCVfixiG1wZHxDp5qUJjIS21B2gsbCZlOih6YsBToiVvch/cwZ5YTr18/EFzYuhmvFakRiQ81KALCIDSimasX6ErE6SV0NhWaNdY2NkNo0LMxH4DIYROyJE759dy3EDwsEJhLbEFgsSvTU50BPycl0xxPCbUPVSV1u0WGp1Fu3rn9mi0m8+mK9mIBNRWKrqpSnlWATfixiGxx5jpoReKWlyjke7JFYoJ4VCnRErKadQPphu3b1r5RcI9GvHz0Anzrl5VqoI2Llpc6rfSIIYREbQExFYn3ZCeTjtZFi/35iNBKr1qa6XcWBFLFt2igVEXyZxFqgiHU46Abmi2CJxAImRKzVqmyo6sMNkdTV0Pgss1WfSOypUyTkw8ICcw7qwSK2wZHCxEwd1b176RBp0yb4DhEt/BKxOjtG104QhFYCgKrbST+9ZjRWxxMre3zkdScUYBEbQEwNeBAEkVifIra2AKFhbSo3JBBXR7Vz3ZelwFCWWvMgNlbR9r6isaWlSiAv0JFYwISIBTSTuxoiqauh8TngQX08seoPB5tNxqyIranh6gQ+8GcwgFCxEkjqJWKPHqVkQhW6PU31qEzQ2OhaCtSR2DpFg32MrB2UBNmVq2VhKLHLbHWCRozEalYnkBtRXe3K4DcsYgMtDo36YltQJNZiMW4pkBf4+Pg6HtIAYcoKoZHc5bNGbDBFYtUiVnUjMqXjgjlyKe+iJ08qlUH0OHGCrkE2W3BuTxAghdiRIx5azSuhktQl8WvULpkRVlXldj0oK1OuJaEUiQV8JHd16kQPraWlHhdLFrGMKRrUTtCEkdjcXJWNNDJSKfZX2zDTIjZQ/VRGRWygxXYTY1bEBkMUFqh/JNannSCAkdiDB+uUDZIbW1Xl1pXT5KN1NRbx8cqBaGTkLhl669BBGeWQccOLVtOlRURiw8KUm5tK/crbQmysRm5HTQ2wYwe9DuJIrGat2PBw5d6nshQUFyvXQBaxjCHqm9jlKmZeVKREKxoxEtu6tRcbaZ0NkV3MzUbEeu1nbp6YFbHB4IcFmsBOEIBIbIcOdM+prKyTUBkRoZx3tWLU9GhdDVkjtjGQw88asRRI1RJKGSlNTFiY0ptmNFIZapFY+fMfOWJyeF15EVOJOt2BXA4epFBtq1ZBaSCVInbvXi8Dc2kkd8nenjZtgqNnzSgsYgOIP57YmholKOsKDMqbUXx8/QuN6+B1wAMpQs1EYktK6CLg84ONCItYTYyKWJnUFdKRWNWHNe0ENTXKhgZAxNpsBsps1TZcnadlqNMgmCOxgDlfrDyHWcTqYia5q7JSOeZCRcR27Ej3qbIy5T5kCI1jTbenSVoJ+vYNysh/WhoFuWpqaEwgDzRqxYailQBgERtQTA92IATy85UnTFck1uBABw2B7HXRLLNVe9UwNdBBRESjCm9dWMRq0lIjsZp2gpwcCnHa7Y1q1dHDkC8W7iLcUJ5WqIhYzUHg68CRWEOY8Yzu308iKDY2eA+RuoSHK+evKUuBjojVPKSCcKQuNRaLD18si1imIZDaLz9fY1hJibQT1NQAxcWuqG18PN1XAZga6KC+GCmzZXq0roYYsskf1CLWW9+TEDoZP80TowMeBFskVi2+fXYl1knscjoV0e72M8vuti5dAhZx8VqhoE6ZLfksZvhZNlRELNsJGgwzIlY93GygLtH+4Fdyl8ZJplteK4grE0gMVSiQF3GwiGX8IDFRuTio8rbciYykwm8AcOZMvYacbQg07QT1FbGBQm5MSQlQUKD9mcJCxVTUQiKxKSk0DbVIrBSxFRX0s+mithMIgbw8epBUV2cAENCkLonRSKzp30OK2Ca4bviFWsT6eiqRikM+mDKamBnwINSSuiR+JXdpHGu6doItW2gaAiJWM7mLRSzTEISFKW4BXUuBKmpU3yFn60ujRGIDRWSk8v3eLAWyjzk+XhnXtJnjpY6+G8XFipc7WCKxkZHKgFo+LQXynKqsBPLyXMH2Nm1UPRxAQJO6JEZrxZqqFlFerjw5B2sktmtX8kUUF+s/UQnBnliDmIlSyuT7vn0bqzWNg18iNj2delpKSly9M17tBPn5ypuDB9ejpY2LOhLr8Qwor2c5Oa4gDYtYxi+kr1U3uUsVNQpUeS2Jrif2zBlUVSlBzaAXsYBvX2wL88MCyi45etR7AExew5OSgmrEReO+2IgIJeR65Ih3x0gQRWI9ymzVR8TKDW7VysfY0AEkIkLZGD1LQX4+DTEHcCTWB+pIrNuxpIHshpZiKFTwS8SGhytdGL/9hooK5RTxOJ9kaLNLl6BO4+/dmx7ICws1bm+tWysX7kOHcPo03ZItFiUoHSqwiA0whspsGY3ENmFil7dIrGyf1arYeTUJlgEEfI3a1cL8sAAdRhYLdct7y/CV2i5YrAQSU8ldsvHZ2d5rxAZBJLZjR6XMltt5V6c6gSk7gbq8VjAbHo34YqVaSUlpMb0l/tKhAz23VFa69SR7UFqqROaCuMdcE79ELKCEIH/7zXU7iI5WJVBLpJUgiKOwAF0zZFUJD1+sxeJWZku+361b4PKs/YVFbIAxJGKDKBIrNd+pU3QhdGvMmTOuZKCkJB8Z0sESiZVXPG9X9BYYibXbFX3kTdsHa9eTqVG7VH2rPiOxARSxNpvy9W6WApWIFTVOc5HYYE/qkhipUMBWAsPYbEr5XVkDVoudO6kXJiWljkc8BPArsQtwe2BSWwk8nvFCRMQCShRdNtkNDREbalF3gEVswKl3JLaiQkkjb4JIbFIS9fIBKs+kaiOkNpXJQV4JFhGrYXB3owWKWMC3y0ImGQWbiDUVidUQsW4/85kzim80wAXN5X52S+5KTaU7bHU18n7LM9ejHioiVmYVaRa7rIWTukwhd6meiA1lUSMPg6Ii7/m6mkgRu2+ffmWCEBKx55xD0/XrNd5U3fvk7x1qUXeARWzAqXckVt59IyI0+j0aHotFCfi6BI5szNmzOH6MBuX22fseLCJWeh1V9fLcYBGriYwIBttgNQ1qJ9izh6adOysVQgKE3M9ukVi73XX+HNpMYrtdO2VUPV1CRcTKu6qsy6mF/J2C7YkqSDEiYoO8DKou0dHKLcmUpUCGqHfu9N6rUVamHG8hIGLPO4+ma9dSGUE3OBLLNASGErv0IrFqP2wTedvkvd/VXSPNr0LgyF4ahctnUCRYRKx6+D2tLCavZsnmTUuNxLo9fMm7fBDUGNKMxAIuEXpoZwkAE5UiQkXE9utH05wc73UIQ21s1AAjD2dZQkuLUBaxgJ++WDk6wIEDOPRbpdt6XGzbRhlxycnBf+6Afr+oKMp99HDk1N7IK/cfcZ1CLGIZ05iyE2hFYpvQDyvxGHbZbndlOB85UAUghESsvOura0apaYGJXYC+iC0rU6pThHQkViViT56kBxjNSGyvXg3VPL+RPZ0e0TMpYvfRedfsRGxcnLJRssB8XdRV+RmfyN20e7f2c7sQoW0nAMwNr+siKcl1rB3aXQpA43xavZqmI0YEd0JkLXY7cO659HrNmjpv1t7Idx8IR1UVlScMRVs5i9gAY8pOcOoUzpyhq47LOSDVRBMWLPcQsYBrQ44eoT4LXRFbUUGGJSDwIjYyUtl3bhtUC9sJPJC7KT6+SRwsppBJKIZErLxil5TgxHE6r4I1Etu/P03376dSli6kiD1CN9RmM9CBGj1LwZkzSk5AEDxshAIZGZTgVVysXQs6O5u8pHZ76O5SM4M6uDF0KC131Oq2Hhe//ELT88/3t2lNjrQUeIjY2qy1bWUUiRgwICR0uQcsYgOMIRFbOzRrldOKggKL23IuRdGEtY40hl12NejI8TAAShUDTeTG2mzBUaNSc4NAIUeZGcAi1oW6MkGwXfSkCD192ncdTEREAGlpcCAajhK6FAZrJDYlhbZNiDoByVoRm32SSksZjsSqS2wFO1LBa0Vi5YNG585khmR8Eh6upAJo+WJlsHHoUCWJN9Twu8zW0KGohB05hTFu6wFAJ58UsZmZ9W5jU+FVxLZqBbRvj18xAkBIWHw1YREbYAx5YsPCgJQUnAV5Ty0WVY1lKbyasF/XWyRWADiSS1klupFYaSVo08ZHHa4mQnODVP/HxQWH2G5C5O936pQy6q5E+jKDzUoAuJ73UFPj45ySdOmCkyDlGx2tGrihrEzpiwyCSCygdO26BSRrReiuM1QOxJBHubhYGRwgFB7O9CKx7If1Cz1fbAgGGz2oj4g9io4QsKJVqzpVdn77je5drVq5IrahwMiRNN2zR+lYdNG1K37AWADARRc1bbsaiiBQEC0bGVEtKACqqnQ+2LYtzoA+nJhIuhaAoiiacEQhqflOnqSi2ACANm1QiHg4KsIBGIzEBtpKIJH7rq6IlQXWe/QIvpBjI5OYqAS23ArsI3hrxALUBSrPKaMVCk6AhJyblUCOod66deAH5KhFPYyki7Q0FCAeh0pT3T6ji+xDjo0NruHWvCEjsTt2eKZYSxUWJA8aoYKMuq1d6/mejMSOGtV07Wlo6iNiD4MW7tKpxv2yv2oVTYcPp3B2iNC6teKL/eor9/eOJA/Fb+gJq8WJMWOavGkNAovYAJOYqOgjb8m3AIB27Vwi1nVPrapSztImDIslJiqBSVd51TZtcAQUvktK8lGRSB2JDQa8RWKlWgu1cfgaAItFicbWvRHIXvZgjMQC5pO7pIh1C0rKCF+vXkHzACMDkm4itl07bAUp186dDY6CGSpJXZKMDPKul5R4hg45qcsvRo+m6YoV7sld+flKSV7ZDR2KSBF7+nQdD7kvkpJwKImirJ3j8t3fkyI2BEPUEyfS9Isv3Of/WEMHwrltshEf36RNajBYxAYYm02pUOWrQoGHiJUDYEdGNnm3oIfua9MGR0Hh15CpTCDx5omVkdhgDDk2ATJALUUrQIGwYK/1bUrEDhzoshO4RWKlUgwicaS2E7gCkmlpyMIgAMCggRqp5lqEmogNC1PCgsuXu7/HItYvZDDxxAn3sm0yMpuRYWDAmiAmIYFcYID3MoHeONSejrUu5aqaVJWVwNdf0+sLL6x/A5sYKWJ//FHJqQaAH07Rk/HYqLqG2dCBRWwQYLRCQR6S3D7vNiRmE0eLtESsjMSGnIiVIcVjx9wf29V2ghaIFKmbNyvz9u0jS2VkZPD24Joaevacc5RIbEq1Ml/2qUpDWRDQsycJj+JiVXQ8JQVZoB9qcIbD2IpCTcQCinD4+WdlXnY2JajZbEDfvoFpV4gSGUlCFqBorES+DmUrAUC3Q38tBYdrI7FdDq9QnhaXLaOu0rZtEYr97r160W2sshL45huaV1kJ/LCHqpOMLf86gK2rHyxigwBDyV3dunlGYgOYYaMnYnX9sEDwiVhZuFoIICtLmd+C7QQAMGQITdUidtMmmg4cqPJlBxlm7QQnI+hu1w61C1RUABs20Osgupvb7YpWW7eudmZYGLaEDQMADErLNbaiUBaxy5crwuLbb2k6cqQSdmMMo7YUANSpt2ABvb7sssC0qSHxV8QeqiJh17l4uxKa/uADmk6eTA9NIYbFAkyaRK+ff55OobffBnLzw9EWJzAy90sfSTnBC4vYIMBQJLZvX08RKyOxTZjUJfEYrTWU7QSAkm26cSNNi4oUFdRC7QQyErtjB+k6QBGxckzuYMSUiLVYcCKWHlLaFtVG3jdvppIMbdoE3QPMWEokxpIlNK2sBHbVUBsHJRwythJZXisUasRKzjmHMg3PnlWqFEgRO3584NoVwkgR+/PPJGB//JE6oxITgQkTAtu2hsBfEXsgm2RRVxwEPvmEjrnFi+nNm29uwBY2LXfdRXmcGzYAL7wAPPEEzf972ByEiwrzvosggUVsEGBIxPbpo4jYqNqSAAGMxMqu5C1bahMDkpNdWZ0hKWKlKpMiVkZhU1MRso73etKpE/m1q6uVZA+5e4K5wowpEQvghJVGu2t3KotmSCvBeecFTVKX5KqraLp0Kf0u27cDVcKOBOSjU9UB/YUloRiJtduV2pw//URRox9/pP8vvTRw7QphzjuPBGtODvDWW8DcuTT/ppuoilSo48+oXWVlyjNeNxwAXn2VErnKy6kbJFgTAQzQti3wj3/Q6/vvp8tA587AbRnLaabWYD8hAIvYIMCQiI2Lw5lWdLNtU15b8yiAkdihQ6k7+fhxGjSsOqGNK8Gkd3cf3RLBLGJlqDGY60g1ERaLu6VAndTVnETsyQpK6W97sDa5IYhrDI0cScLj7Fng11+B996j+ZlYBcsJjeGXtAhFEQsoYvXll0nAFhfTxVMepIwpoqKAf/6TXt93H/Dpp/T61lsD16aGRDWqtGHkZ2NjBZKmXkkh6t27KVPs/feD7qHWLH/7GzlzIiMpSPHKK0B4t1r/H4tYxl8MeWIBnImg7r82RQfpyTAAAx1IoqKUbOm1a4GthxPgQCziUYB+bfXUOIJTxEpVtmcP3RxlSn6QdSc3Nerkrt27gz+pCzCX2FVdDZwuopqP7Q6upmQhWUonCEVsWBhw+eX0+oMPlOjZX/Gq9hiidREidEXsH/9IhvsjR5R06/Hjg2PAlBDl9tvpXHY4SK9NnRrSwUY3PCxvBlDiQhZY5r4DzJxJN7rvvgMGDfr/9u48Oooq3wP4tzsJ2ReyQBKzsERAFiWCcIJjCBghgAgi4CACgYwOEg4yKg9xRlTUcYMBV1COBHR8OPgQxHkjkCdhkU3DJAiIAYIMWwJKSAhJ6Gz3/XGp7jTpTjoh3dXV/f2c06c61UXn1rVM//pXv3tvm7fR0by85I2MykpZZjF6NKxPMakR/L/fCdiUiQWM5QRhF36S2SKDQU6t5cAlZxtSBm7v3Qvs2i0vpbuxG/qSJk6krs40Ia4zBbEdOwIxMabBXUoNlDMXfzqAkuTKyQGWLZPPBw923kFdgCkTe+mSrBltyoULgBA6eKAW4eIicNdd8h/Gx8vnTkgpKVixQpZud+9YivuQbVsQe/myqcBZC6t1NeTnByxeLJ8bDPLLu1LYR63i5QX84x9AerocgL9mjeaTjUZKEHvxovzybQuzm5t6PfD66/LzwEn/FrQJpaOUu48awyDWCdgcxBrk6jrhZ/PlN0MAGDZMtb86ShC7Z0+DJaWxy5RptaSkxDS7tjJBrrNQsrFvvy3vm3t5ARMnqtsmlaWmyjtpP/8s6+YAYMECVZvUrNBQ04I6jZZZvIFSctAhvB4eephuh7z/vtOuyjN+PDB9uunn2WPPQg/R/MkCpkA3NFSbhY8TJsgRKpMmyT88ZovbU2v06SMz+q5WWhwcbPpstTUbqyQjleSkW+jeXW4bTgiuIQxinYAtQazBAJRfkx+q4YX7TUHsfffZuXXWKUFsXh7wf/8nn/8O38mvvtYoAW779jJIdCbjxsnt+vVy+8ADploPNxUeDrzzjunnwYOB5GT12mMLvd408P7GJXNvpMR9UXHtgKeekj+MHw+MGmW/Bt4kDw9g1SogOxtYuhSYmXG9Bt2WTOyZM3KrpZkJGtLp5En/9387150cckpKpV3DBR2aouIwE/X06CG3J07I+iqNYRDrBGwJYpUEkR51CPntuGk+U2XOHRV06iRv3dbWAmVlQDt9Dfojt+liRGesh1VMmWIevKSnq9YUZ/Loo8Dvfy+/c2jl7q0Soykjja1RMrGRkZC3DrduNY2WcnKpqTIp6Rl3vbb1woXmP4SUaXSYwSQ30NK62IbrB7mN2Fg50KGmpmWj4JwEg1gnoCT7rlyxPt+wEuCG+VbKW4eALDRXRrGoQKcDnn9ezj0HAENjjsMHBu0GsTqdnAE6Pl4uY+lq99daSaeTg4h+/VU7y4bHyIk8bM/ERkGmOO+7T3u32SMiZNuFaH40mxLENjsPHpH2tSQTW18vx3UCbpaJ1etNA5g1WFLAINYJhISYBtham6FACWLDOwXISd4AWRemslmz5Ofmt98Cnz5yfT07rQaxgPxSUFAgJ1R3tnIHFen12pou19ZMrHJ3XQl6NUmvNw3Saq6kQJn5nZlYcgMtycSePy/L9jw83PA7nlIXW1CgbjtagUGsE/DwMI1xslZSYAxiw3XAm2/KaFcJZlXm6wsMHQqEd70e5Wg5iAUAb29NLi1IJrZmYl0mMakEsc1F7S5zwkTNa0kmVgl04+Ode/YVu1DqYhnEUms1VxdrCmKv7wgNdb65UGyZoFMLQSxpXkszsbGx9m2P3SlBaXNLRzKIJTeiBLFnz8qp1Zui3ElXkpJuRcMzFDCIdRJKXWxzQaxTD5ZnEEtOwpZMrBCmmE7zQawyV7RS1GdJXZ2pQxjEkhsID5djNoRo+n8NAPjpJ7nt2dP+7XI6zMTSzVIyrNZqYs1GUTurhkGsMhfsjRjEkgMoQez583LAhiVlZXKlIsAFglhb1tgsKpKBrKen9hY6IGoFnc60cnhzScajR+XWmVcjtBtlYNfFi6bFiDSCQayTaK6cQFNBbHU1UFpq+RhNnAhpXWSk/ACrqbG+9oZSShAaCvj7O65tdmFLJlZJO8fEsOab3Ebv3nJ75EjTx7l1JjYgwPRF+OBBVZvSUgxinYStQaxTJ1B8fICgIPncWkmBUqSotXXbSVO8vEzfk6zVxbpMPSxgWyZWmZmApQTkRpQg9vBh68eUlZn+TrhlJhYwrTGel6duO1qIQayTaK4mVjMJzKbqYisq5F8LgEEs2V1zq3a51BgnJYgtKwMuX7Z8jEudMJFtbAlilVKDqCg55aVbSkyUWwax1BpN1cQKoaEgVmmgpSBWmVne39+UsSWyk+YGd7lUJtbPD+jQQT63lo1lEEtuSAliCwpkpZslbl1KoGAQSzejqXKC8nKgqko+V3GBLts0lYlVJmKPjna+6cHI5TSXiXWpIBYw1cVaC2JZTkBuKCZG5kxqa4FjxywfwyAWpiD26FGgslLdtrQAg1gn0VQQq2RhAwM1MAClqSCW9bDkQEpMd/Kk5dddLjGplBRYG9ylfIIrw7WJ3IBO13xJgVvPTKCIipKf3/X1wKFDarfGZgxinYQtQazTlxIAtmVilRQZkR0pE50fP275dZfLxDY1uMtgMEXzypyQRG6iqSBWCCA3Vz7v08dxbXI6Op0mSwoYxDoJZWBXebn8vGlIEzMTKGwtJyCyMyXheOJE42mL6+tNZQYuE8Q2Nc1WYaGcIzYwUCN/SIjajhLEWkownjolP668vIB+/RzaLOejBLHff69uO1qAQayTCAkB2rWTz5WgVaGpTKzSSGUQV0MsJyAH6tJFJheuXGk8V+ypU3KQR7t2pgFgmqcEscoi8A0pw6979GA9OrkdJTbbt6/xF9q9e03H+Po6tl1OZ/Bguc3Otr5gkZNhEOsk9HpTRujG5c+VeFATQaxSYKgMImmI5QTkQD4+pv+nbiwpUGK6bt3kAlYuQRmVcuxY49s5DYNYIjdz113y78HFi41X7lKC2KQkx7fL6SQny446e9ZUKOzkGMQ6ESX+uzGI1VQmVqnL+/VX05qeCpYTkIM1LCloyCUHctxyC9C+vSwbUIZbKxjEkhvz9gYGDZLPt283f00JYpXX3Zqvrykbu3mzaX/DeT6dDINYJ2ItE6upIDYkxDRbdMNsrBAsJyCHU4LYGzOxLhnE6nTAHXfI5z/+aP4ag1hycykpctswiK2oAPLz5XNmYq8bPlxut2wx7fv2W5llmzNHnTY1gUGsE3GJTCxgeYBJaSlw7Zp8zoEl5CDWZihwySAWAG6/XW4brn8uBINYcnsNg1il3HPvXnnj4pZbXGiA581SgtgdO0wrbL7+OlBT45T19AxinYgSxCpT/yhcIohVSglCQ1k9Tw5jKRMrhAsHsUomtmEQW1Qkpz3x8AC6dlWnXUQqGzDAVBd75Ijcl5UltyNHqtcup3PbbfJhMACvvgr88IPMxHp6Ak89pXbrGmEQ60QsZWJrauT/dICGEpiWVg5SToqlBORAlqbZungRuHxZJhW6dVOvbXbRMIhVTvjAAblNSJDFgURuyNsbSE2Vz5cskcM2/ud/5M9//KN67XI6Oh3w1lvy+bJlwBNPyOeTJgHx8ao1yxoGsU7EUhB78qSc09LfXwNLziosrRykpL54O5McqEsXmUAoLzddjsqd9c6dXfCmQM+ecqqTS5dM05pkZ8vtkCHqtYvICTz/vNx+8gnwzDNymr3+/Tk/bCMjR8qygpoa+SXY0xP4r/9Su1UWMYh1IkpNTlmZqRSloEBuu3VzynIUyyyVEyj3b3r1cnx7yG15ewMDB8rnOTly67KlBICMyrt3l8+VDOzWrXI7bJg6bSJyEgMGAA88IBNDn3wi9zELa4FOB3z0EfDoo8D8+bJ4WFkxwskwiHUiAQFyhhzAVBerBLHK55ImNBXEKnNZEjnI0KFyqwSxyuhk5c67y1FGsHz+ubytU1Ags7PMxBLh9deBDh1kqdELLwDTp6vdIicVFwd8+qnssP791W6NVQxincyNg7s0GcQqdTNlZXJWAiFM81YyE0sOpsRu27YBVVXA//6v/PmBB9Rrk13NmCG369cD69bJ5wMHmqa+I3Jjt90ml5k9dgx48UU53pG0i0Gsk7mxLlaTQay/v/yqC8hs7JkzsijR09M00obIQZKSZFlBURHw3ntyDY6YGLmKj0vq109OtWUwAAsXyn0sJSAiF8Qg1skoQawysF+TQSxgmqDz4EFTFrZbN7lYPZED+fiYVuN5+WW5HTdO3mF3STodkJEhn1dVAWFhwLRp6raJiMgOXPXPuGYpd9v37ZPTAP36q/xZc1MBKYWI33zDelhS3cSJclteLrcPPaReWxxi+nR50nPmyOkYlDp1IiIX4ql2A8icEvvt2WNaDu+WW+SgL00ZORJ45RW5dJ0yNyXrYUklf/yjLAn96CM5Vd3dd6vdIjsLDAT+8Q+1W0FEZFcMYp1Mt24yaD13zrSaiOZKCQA5l0loKFBSYhpc0qePum0it6XTAb//vXwQEZFrYDmBk9HpgHvvlc/XrpVbTSYwPTyAtDT53GCQJ8G1/YiIiKiNaCaIffXVVzFo0CD4+fkhxMWnilGC2NpaOXf5nDnqtqfVlKDVx0fe2nS55ZGIiIhILZopJ6iursaECROQlJSEjz/+WO3m2JUSxAJynmFloL/mTJwoB3WlpGg0nUxERETOSjNB7EsvvQQAWL16tboNcYBbbgFefVWuEzB7ttqtuQleXsBf/6p2K4iIiMgFaSaIbQ2DwQCDwWD8+cqVKyq2pmWee07tFhARERE5L83UxLbGa6+9huDgYOMjNjZW7SYRERERURtQNYh99tlnodPpmnz8/PPPrX7/BQsWoKyszPg4c+ZMG7aeiIiIiNSiajnB008/jfT09CaP6dKlS6vf39vbG97KRPtERERE5DJUDWIjIiIQERGhZhOIiIiISIM0M7Dr9OnTKCkpwenTp1FXV4f862uyJiQkIEBza7ISERER0c3QTBC7cOFCrFmzxvhzYmIiACAnJwcpKSkqtYqIiIiI1KATQgi1G+EoV65cQXBwMMrKyhAUFKR2c4iIiIjoBrbGay49xRYRERERuSYGsURERESkOQxiiYiIiEhzGMQSERERkeYwiCUiIiIizWEQS0RERESawyCWiIiIiDSHQSwRERERaQ6DWCIiIiLSHAaxRERERKQ5DGKJiIiISHM81W6AIwkhAMg1eYmIiIjI+ShxmhK3WeNWQWx5eTkAIDY2VuWWEBEREVFTysvLERwcbPV1nWguzHUh9fX1OH/+PAIDA6HT6ez++65cuYLY2FicOXMGQUFBdv99JLHf1cF+Vw/7Xh3sd3Ww39XhyH4XQqC8vBzR0dHQ661XvrpVJlav1yMmJsbhvzcoKIj/o6mA/a4O9rt62PfqYL+rg/2uDkf1e1MZWAUHdhERERGR5jCIJSIiIiLNYRBrR97e3njhhRfg7e2tdlPcCvtdHex39bDv1cF+Vwf7XR3O2O9uNbCLiIiIiFwDM7FEREREpDkMYomIiIhIcxjEEhEREZHmMIglIiIiIs1hENtCO3fuxOjRoxEdHQ2dToeNGzeavX716lXMnj0bMTEx8PX1Rc+ePbFixQqzY65du4bMzEyEhYUhICAADz30EC5cuODAs9Cetuj3lJQU6HQ6s8fMmTMdeBba1FzfX7hwAenp6YiOjoafnx/S0tJw/Phxs2N4zbdcW/Q7r/mWe+2113DXXXchMDAQHTp0wNixY1FQUGB2jC3X8+nTpzFq1Cj4+fmhQ4cOmDdvHmprax15KprSVv1+4/Wu0+nw+eefO/JUNMWWfv/oo4+QkpKCoKAg6HQ6lJaWNnqfkpISTJ48GUFBQQgJCUFGRgauXr1q9/YziG2hiooK3HHHHXj//fctvv7UU09h8+bN+Pvf/46jR49i7ty5mD17NjZt2mQ85k9/+hO+/vprfPHFF9ixYwfOnz+PcePGOeoUNKkt+h0AHnvsMRQVFRkfb775piOar2lN9b0QAmPHjsXJkyfx1VdfIS8vD/Hx8UhNTUVFRYXxOF7zLdcW/Q7wmm+pHTt2IDMzE/v27UN2djZqamowbNiwFl3PdXV1GDVqFKqrq7Fnzx6sWbMGq1evxsKFC9U4JU1oi35XZGVlmV3zY8eOdeCZaIst/V5ZWYm0tDQ899xzVt9n8uTJOHLkCLKzs/HPf/4TO3fuxOOPP27/ExDUagDEhg0bzPb16tVLLFq0yGzfnXfeKf785z8LIYQoLS0VXl5e4osvvjC+fvToUQFA7N271+5tdgWt6XchhBg8eLB48sknHdBC13Vj3xcUFAgA4vDhw8Z9dXV1IiIiQqxcuVIIwWu+LbSm34XgNd8WLl68KACIHTt2CCFsu57/9a9/Cb1eL4qLi43HLF++XAQFBQmDweDYE9Co1vS7EJY/H8h2N/Z7Qzk5OQKAuHz5stn+n376SQAQP/zwg3HfN998I3Q6nTh37pxd28tMbBsbNGgQNm3ahHPnzkEIgZycHBw7dgzDhg0DABw4cAA1NTVITU01/psePXogLi4Oe/fuVavZmtdcvys+++wzhIeHo3fv3liwYAEqKytVarFrMBgMAAAfHx/jPr1eD29vb3z33XcAeM3bgy39ruA1f3PKysoAAKGhoQBsu5737t2LPn36oGPHjsZjhg8fjitXruDIkSMObL12tabfFZmZmQgPD8eAAQOwatUqCE6Hb7Mb+90We/fuRUhICPr372/cl5qaCr1ej/3797d5GxvytOu7u6F3330Xjz/+OGJiYuDp6Qm9Xo+VK1ciOTkZAFBcXIx27dohJCTE7N917NgRxcXFKrTYNTTX7wDwyCOPID4+HtHR0fjxxx8xf/58FBQU4Msvv1Sx5dqmfIgsWLAAH374Ifz9/bF06VKcPXsWRUVFAHjN24Mt/Q7wmr9Z9fX1mDt3Lu6++2707t0bgG3Xc3FxsVkAq7yuvEZNa22/A8CiRYswdOhQ+Pn5YevWrZg1axauXr2KOXPmOPIUNMlSv9uiuLgYHTp0MNvn6emJ0NBQu1/vDGLb2Lvvvot9+/Zh06ZNiI+Px86dO5GZmYno6Gizb5DUtmzp94b1OX369EFUVBTuvfdeFBYWomvXrmo1XdO8vLzw5ZdfIiMjA6GhofDw8EBqaipGjBjB7Icd2drvvOZvTmZmJg4fPtwou032dTP9/vzzzxufJyYmoqKiAm+99RaDWBto8XpnENuGqqqq8Nxzz2HDhg0YNWoUAOD2229Hfn4+Fi9ejNTUVERGRqK6uhqlpaVm3ygvXLiAyMhIlVqubbb0uyUDBw4EAJw4cYIf6DehX79+yM/PR1lZGaqrqxEREYGBAwcaby3xmreP5vrdEl7ztps9e7ZxgEpMTIxxvy3Xc2RkJL7//nuz91NG0fOab9rN9LslAwcOxMsvvwyDwQBvb297Nl3TrPW7LSIjI3Hx4kWzfbW1tSgpKbH79c6a2DZUU1ODmpoa6PXm3erh4YH6+noA8oPHy8sL3377rfH1goICnD59GklJSQ5tr6uwpd8tyc/PBwBERUXZs3luIzg4GBERETh+/Dhyc3MxZswYALzm7c1av1vCa755QgjMnj0bGzZswLZt29C5c2ez1225npOSknDo0CGzD/bs7GwEBQWhZ8+ejjkRjWmLfrckPz8f7du3ZwBrRXP9boukpCSUlpbiwIEDxn3btm1DfX298Yuz3dh12JgLKi8vF3l5eSIvL08AEH/7299EXl6e+M9//iOEkKOBe/XqJXJycsTJkydFVlaW8PHxER988IHxPWbOnCni4uLEtm3bRG5urkhKShJJSUlqnZIm3Gy/nzhxQixatEjk5uaKX375RXz11VeiS5cuIjk5Wc3T0oTm+n7dunUiJydHFBYWio0bN4r4+Hgxbtw4s/fgNd9yN9vvvOZb54knnhDBwcFi+/btoqioyPiorKw0HtPc9VxbWyt69+4thg0bJvLz88XmzZtFRESEWLBggRqnpAlt0e+bNm0SK1euFIcOHRLHjx8XH3zwgfDz8xMLFy5U45Q0wZZ+LyoqEnl5eWLlypUCgNi5c6fIy8sTly5dMh6TlpYmEhMTxf79+8V3330nbr31VjFp0iS7t59BbAspU0zc+Jg2bZoQQv7HTk9PF9HR0cLHx0d0795dLFmyRNTX1xvfo6qqSsyaNUu0b99e+Pn5iQcffFAUFRWpdEbacLP9fvr0aZGcnCxCQ0OFt7e3SEhIEPPmzRNlZWUqnpU2NNf3b7/9toiJiRFeXl4iLi5O/OUvf2k0jRCv+Za72X7nNd86lvocgMjKyjIeY8v1fOrUKTFixAjh6+srwsPDxdNPPy1qamocfDba0Rb9/s0334i+ffuKgIAA4e/vL+644w6xYsUKUVdXp8IZaYMt/f7CCy80e8ylS5fEpEmTREBAgAgKChLTp08X5eXldm+/7vpJEBERERFpBmtiiYiIiEhzGMQSERERkeYwiCUiIiIizWEQS0RERESawyCWiIiIiDSHQSwRERERaQ6DWCIiIiLSHAaxRERkVF1djYSEBOzZs0fVdmzevBl9+/ZtculoInJvDGKJyGWlp6dDp9M1epw4cULtpjmtFStWoHPnzhg0aJBxn9Jv+/btMzvWYDAgLCwMOp0O27dvNzt+48aNjd47PT0dY8eOtakdaWlp8PLywmeffdaa0yAiN8AglohcWlpaGoqKiswenTt3bnRcdXW1Cq1zLkIIvPfee8jIyGj0WmxsLLKyssz2bdiwAQEBAXZrT3p6Ot555x27vT8RaRuDWCJyad7e3oiMjDR7eHh4ICUlBbNnz8bcuXMRHh6O4cOHAwAOHz6MESNGICAgAB07dsSUKVPw22+/Gd+voqICU6dORUBAAKKiorBkyRKkpKRg7ty5xmMsZSJDQkKwevVq489nzpzBxIkTERISgtDQUIwZMwanTp0yvq5kLRcvXoyoqCiEhYUhMzMTNTU1xmMMBgPmz5+P2NhYeHt7IyEhAR9//DGEEEhISMDixYvN2pCfn99kJvrAgQMoLCzEqFGjGr02bdo0fP7556iqqjLuW7VqFaZNm2a175ty6tQpi1nylJQU4zGjR49Gbm4uCgsLW/U7iMi1MYglIre1Zs0atGvXDrt378aKFStQWlqKoUOHIjExEbm5udi8eTMuXLiAiRMnGv/NvHnzsGPHDnz11VfYunUrtm/fjn//+98t+r01NTUYPnw4AgMDsWvXLuzevRsBAQFIS0szywjn5OSgsLAQOTk5WLNmDVavXm0WCE+dOhVr167FO++8g6NHj+LDDz9EQEAAdDodZsyY0ShzmpWVheTkZCQkJFhs165du9CtWzcEBgY2eq1fv37o1KkT1q9fDwA4ffo0du7ciSlTprTo3BWxsbFm2fG8vDyEhYUhOTnZeExcXBw6duyIXbt2tep3EJGLE0RELmratGnCw8ND+Pv7Gx/jx48XQggxePBgkZiYaHb8yy+/LIYNG2a278yZMwKAKCgoEOXl5aJdu3Zi3bp1xtcvXbokfH19xZNPPmncB0Bs2LDB7H2Cg4NFVlaWEEKITz/9VHTv3l3U19cbXzcYDMLX11ds2bLF2Pb4+HhRW1trPGbChAni4YcfFkIIUVBQIACI7Oxsi+d+7tw54eHhIfbv3y+EEKK6ulqEh4eL1atXW+2vJ598UgwdOrTRfuV8li1bJoYMGSKEEOKll14SDz74oLh8+bIAIHJycsyO9/HxMet3f39/4enpKcaMGdPo/auqqsTAgQPF/fffL+rq6sxeS0xMFC+++KLVNhOR+/JUM4AmIrK3IUOGYPny5caf/f39jc/79etnduzBgweRk5Njsc6zsLAQVVVVqK6uxsCBA437Q0ND0b179xa16eDBgzhx4kSjjOe1a9fMbp336tULHh4exp+joqJw6NAhALI0wMPDA4MHD7b4O6KjozFq1CisWrUKAwYMwNdffw2DwYAJEyZYbVdVVRV8fHysvv7oo4/i2WefxcmTJ7F69eom61WXLl2K1NRUs33z589HXV1do2NnzJiB8vJyZGdnQ683v0Ho6+uLyspKq7+HiNwXg1gicmn+/v5Wb583DGgB4OrVqxg9ejTeeOONRsdGRUXZPKuBTqeDEMJsX8Na1qtXr6Jfv34WR95HREQYn3t5eTV6X2XKKV9f32bb8Yc//AFTpkzB0qVLkZWVhYcffhh+fn5Wjw8PDzcGyZaEhYXh/vvvR0ZGBq5du4YRI0agvLzc4rGRkZGN+j0wMBClpaVm+1555RVs2bIF33//vcUyhpKSErM+ISJSsCaWiOi6O++8E0eOHEGnTp2QkJBg9vD390fXrl3h5eWF/fv3G//N5cuXcezYMbP3iYiIQFFRkfHn48ePm2UT77zzThw/fhwdOnRo9HuCg4NtamufPn1QX1+PHTt2WD1m5MiR8Pf3x/Lly7F582bMmDGjyfdMTEzEzz//3CgAb2jGjBnYvn07pk6dapYlbo3169dj0aJFWLduHbp27drodSUznZiYeFO/h4hcE4NYIqLrMjMzUVJSgkmTJuGHH35AYWEhtmzZgunTp6Ourg4BAQHIyMjAvHnzsG3bNhw+fBjp6emNboEPHToU7733HvLy8pCbm4uZM2eaZVUnT56M8PBwjBkzBrt27cIvv/yC7du3Y86cOTh79qxNbe3UqROmTZuGGTNmYOPGjcb3WLdunfEYDw8PpKenY8GCBbj11luRlJTU5HsOGTIEV69exZEjR6wek5aWhl9//RWLFi2yqZ3WHD58GFOnTsX8+fPRq1cvFBcXo7i4GCUlJcZj9u3bB29v72bbTUTuiUEsEdF10dHR2L17N+rq6jBs2DD06dMHc+fORUhIiDFQfeutt3DPPfdg9OjRSE1Nxe9+97tGtbVLlixBbGws7rnnHjzyyCN45plnzG7j+/n5YefOnYiLi8O4ceNw2223GW/RBwUF2dze5cuXY/z48Zg1axZ69OiBxx57DBUVFWbHZGRkoLq6GtOnT2/2/cLCwvDggw82ucCATqdDeHg42rVrZ3M7LcnNzUVlZSVeeeUVREVFGR/jxo0zHrN27VpMnjy5yRIIInJfOtHUfSMiImpWSkoK+vbti2XLlqndlEZ27dqFe++9F2fOnEHHjh2bPf7HH3/Efffdh8LCQrsuZNCc3377Dd27d0dubq7FxSmIiJiJJSJyQQaDAWfPnsWLL76ICRMm2BTAAsDtt9+ON954A7/88oudW9i0U6dO4YMPPmAAS0RWcXYCIiIXtHbtWmRkZKBv37745JNPWvRv09PT7dOoFujfvz/69++vdjOIyImxnICIiIiINIflBERERESkOQxiiYiIiEhzGMQSERERkeYwiCUiIiIizWEQS0RERESawyCWiIiIiDSHQSwRERERaQ6DWCIiIiLSHAaxRERERKQ5/w/b1tzHYUYd9wAAAABJRU5ErkJggg==", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "def read_uvfits(uvfits_name):\n", " \"\"\"Real shorthand function to read in visibilities from a WODEN UVFITS file\"\"\"\n", " \n", " with fits.open(uvfits_name) as hdus:\n", " data = np.squeeze(hdus[0].data.data)\n", " ##Yup, this is the order of things in a UVFITS file\n", " XX = data[:, :, 0, 0] + 1j*data[:, :, 0, 1]\n", " YY = data[:, :, 1, 0] + 1j*data[:, :, 1, 1]\n", " XY = data[:, :, 2, 0] + 1j*data[:, :, 2, 1]\n", " YX = data[:, :, 3, 0] + 1j*data[:, :, 3, 1]\n", " \n", " return XX, XY, YX, YY\n", " \n", "XX, XY, YX, YY = read_uvfits(f'{uvfits_name}_band01.uvfits')\n", "\n", "##pick a random baseline to plot, they should all be the same\n", "baseline = np.random.randint(0, XX.shape[0])\n", "print(baseline)\n", "\n", "##converts instrumental pols into Stokes params. We didn't use a primary beam\n", "##at we're right at zenith so this is good enough without corrections\n", "recover_I = 0.5*(XX[baseline] + YY[baseline])\n", "recover_Q = 0.5*(XX[baseline] - YY[baseline])\n", "recover_U = 0.5*(XY[baseline] + YX[baseline])\n", "recover_V = -0.5j*(XY[baseline] - YX[baseline])\n", "\n", "##these are the freqs we put into the simulation\n", "freqs = np.arange(low_freq, high_freq, freq_reso)\n", "\n", "fig, axs = plt.subplots(1, 1, figsize=(8, 6))\n", "\n", "axs.plot(freqs / 1e+6, recover_I.real, 'k-', label='Recovered I')\n", "axs.plot(freqs / 1e+6, recover_Q.real, 'r', label='Recovered Q')\n", "axs.plot(freqs / 1e+6, recover_U.real, 'b', label='Recovered U')\n", "axs.plot(freqs / 1e+6, recover_V.real, 'g', label='Recovered V')\n", "\n", "axs.legend()\n", "\n", "axs.set_xlabel('Frequency (MHz)')\n", "axs.set_ylabel('Flux (Jy)')\n", "\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Lovely, we have some nice sinusoidal Q/U lines, a power-law Stokes I, and a noisy-like Stokes V. Let's see if we can recover the RM from this data. All credit to Emil for the RM synthesis code." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input resolutions going into RM-synthesis:\n", "\tFrequency range: 180.000 MHz - 209.920 MHz\n", "\tBandwidth: 29.920 MHz\n", "\tChannel width: 80.0 KHz\n", "\tdlambda2: 0.002\n", "\tDlambda2: 0.734\n", "\tphimax: 702.920\n", "\tdphi: 4.717\n", "\tphiR: 0.943\n", "\tNphi: 1490.189\n", "Recovered paramaters:\n", "\tS = 15.133\n", "\tPol frac from recovered peak = 9.167%\n", "\tMean recovered pol frac: 0.092, Expected: 0.092\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "def getFDF(dataQ, dataU, freqs, startPhi, stopPhi, dPhi, dType='float32'):\n", " \"\"\"\n", " # Perform RM-synthesis on Stokes Q and U data\n", " #\n", " # dataQ, dataU and freqs - contains the Q/U data at each frequency (in Hz) measured.\n", " # startPhi, dPhi - the starting RM (rad/m^2) and the step size (rad/m^2)\n", " \n", " Author: Emil Lenc\n", " \"\"\"\n", "\n", " # Calculate the RM sampling\n", " phiArr = np.arange(startPhi, stopPhi, dPhi)\n", "\n", " # Calculate the frequency and lambda sampling\n", " lamSqArr = np.power(C / np.array(freqs), 2.0)\n", "\n", " # Calculate the dimensions of the output RM cube\n", " nPhi = len(phiArr)\n", "\n", " # Initialise the complex Faraday Dispersion Function (FDF)\n", " FDF = np.ndarray((nPhi), dtype='complex')\n", "\n", " # Assume uniform weighting\n", " wtArr = np.ones(len(lamSqArr), dtype=dType)\n", "\n", " K = 1.0 / np.nansum(wtArr)\n", "\n", " # Get the weighted mean of the LambdaSq distribution (B&dB Eqn. 32)\n", " lam0Sq = K * np.nansum(lamSqArr)\n", "\n", " # Mininize the number of inner-loop operations by calculating the\n", " # argument of the EXP term in B&dB Eqns. (25) and (36) for the FDF\n", " a = (-2.0 * 1.0j * phiArr)\n", " b = (lamSqArr - lam0Sq) \n", " arg = np.exp( np.outer(a, b) )\n", "\n", " # Create a weighted complex polarised surface-brightness cube\n", " # i.e., observed polarised surface brightness, B&dB Eqns. (8) and (14)\n", " Pobs = (np.array(dataQ) + 1.0j * np.array(dataU))\n", "\n", " # Calculate the Faraday Dispersion Function\n", " # B&dB Eqns. (25) and (36)\n", " FDF = K * np.nansum(Pobs * arg, 1)\n", " return FDF, phiArr\n", "\n", "def findpeaks(freqs, fdf, phi, rmsf, rmsfphi, nsigma):\n", " \"\"\"Find peaks in the FDF\n", " Author: Emil Lenc\"\"\"\n", " # Create the Gaussian filter for reconstruction\n", " lam2 = (C / freqs) ** 2.0\n", " lam02 = np.mean(lam2)\n", " minl2 = np.min(lam2)\n", " maxl2 = np.max(lam2)\n", " width = (2.0 * np.sqrt(3.0)) / (maxl2 - minl2)\n", "\n", " Gauss = np.exp((-rmsfphi ** 2.0) / (2.0 * ((width / 2.355) ** 2.0)))\n", " components = np.zeros((len(phi)), np.float32)\n", " peaks = []\n", " phis = []\n", " std = 0.0\n", " rmsflen = int((len(rmsf) - 1) / 2)\n", " fdflen = len(phi) + rmsflen\n", " while True:\n", " std = np.std(np.abs(fdf))\n", " peak1 = np.max(np.abs(fdf))\n", " pos1 = np.argmax(np.abs(fdf))\n", " val1 = phi[pos1]\n", " if peak1 < nsigma * std :\n", " break\n", " fdf -= rmsf[rmsflen - pos1:fdflen - pos1] * fdf[pos1]\n", " peaks.append(peak1)\n", " phis.append(val1)\n", " components[pos1] += peak1\n", " fdf += np.convolve(components, Gauss, mode='valid')\n", " return phis, peaks, std\n", "\n", "startPhi = -100.0\n", "dPhi = 1.0\n", "stopPhi = -startPhi+dPhi\n", "lambda2 = np.power(C / np.array(freqs), 2.0)\n", "\n", "df = []\n", "for f in range(1, len(freqs)):\n", "\tdf.append(freqs[f] - freqs[f-1])\n", "chanBW = np.min(np.array(df))\n", "fmin = np.min(freqs)\n", "fmax = np.max(freqs)\n", "bw = fmax - fmin\n", "\n", "dlambda2 = np.power(C / fmin, 2) - np.power(C / (fmin + chanBW), 2)\n", "Dlambda2 = np.power(C / fmin, 2) - np.power(C / (fmin + bw), 2)\n", "phimax = np.sqrt(3) / dlambda2\n", "dphi = 2.0 * np.sqrt(3) / Dlambda2\n", "phiR = dphi / 5.0\n", "Nphi = 2 * phimax / phiR\n", "##These are things that mean something to polarisation peoples\n", "print(\"Input resolutions going into RM-synthesis:\")\n", "print(\"\\tFrequency range: %7.3f MHz - %7.3f MHz\" %(fmin / 1.0e6, (fmin + bw) / 1.0e6))\n", "print(\"\\tBandwidth: %7.3f MHz\" %(bw / 1.0e6))\n", "print(\"\\tChannel width: %.1f KHz\" %(chanBW / 1.0e3))\n", "print(\"\\tdlambda2: %7.3f\" %(dlambda2))\n", "print(\"\\tDlambda2: %7.3f\" %(Dlambda2))\n", "print(\"\\tphimax: %7.3f\" %(phimax))\n", "print(\"\\tdphi: %7.3f\" %(dphi))\n", "print(\"\\tphiR: %7.3f\" %(phiR))\n", "print(\"\\tNphi: %7.3f\" %(Nphi))\n", "fwhm = dphi\n", "\n", "# Determine the FDF using the q, u and ferquency values read from the file.\n", "dirty, phi = getFDF(recover_Q, recover_U, freqs, startPhi, stopPhi, dPhi)\n", "FDFqu, phi = getFDF(recover_Q, recover_U, freqs, startPhi, stopPhi, dPhi)\n", "rstartPhi = startPhi * 2\n", "rstopPhi = stopPhi * 2 - dPhi\n", "RMSF, rmsfphi = getFDF(np.ones((len(recover_Q))), np.zeros((len(recover_Q))), freqs, rstartPhi, rstopPhi, dPhi)\n", "\n", "phis, peaks, sigma = findpeaks(np.array(freqs), FDFqu, phi, RMSF, rmsfphi, 6.0)\n", "snr = peaks / sigma\n", "phierr = fwhm / (2 * snr)\n", "# print(phis, phierr, peaks, sigma)\n", "imean = np.mean(np.real(recover_I))\n", "\n", "print(\"Recovered paramaters:\")\n", "\n", "print(\"\\tS = %.3f\" %(imean))\n", "if len(peaks) > 0:\n", "\tprint(\"\\tPol frac from recovered peak = %.3f%%\" %(100.0 * peaks[0] / imean))\n", "\n", "##What is the polarised flux as a function of frequency\n", "# polarised_flux = np.sqrt(recover_Q**2 + recover_U**2)\n", "polarised_flux = np.abs(recover_Q + 1j*recover_U)\n", "\n", "recovered_pol_frac = (polarised_flux.real / recover_I.real)\n", "print(f'\\tMean recovered pol frac: {np.mean(recovered_pol_frac):.3f}, Expected: {pol_frac:.3f}')\n", "\n", "fig, axs = plt.subplots(1, 1, figsize=(6,4))\n", "\n", "axs.plot(phi, np.real(FDFqu), 'k-', label='FDF')\n", "\n", "axs.set_xlabel(\"${\\phi}$ (rad m$^{-2}$)\")\n", "axs.set_ylabel(\"Polarised Flux (Jy RMSF$^{-1}$)\")\n", "\n", "axs.set_xlim(-100, 100)\n", "\n", "axs.axvline(x=phi_RM, color='C1', linestyle='--', label='Expected RM')\n", "axs.legend()\n", "\n", "plt.show()\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using Emil's magic RM code, we can see a nice strong peak at the expected RM of 50.2 rad/m^2, and we recover the expected polarisation fraction of 9.2%." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Multiple components same direction\n", "\n", "Now let's try sticking a few different components in the same direction, to see if we can disentangle the RMs.\n", "\n", "Make a new sky model:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "\n", "num_comps = 3\n", "\n", "##Make some simple component params. Keep everything the same, but vary RM\n", "alpha = np.full(num_comps, -0.815)\n", "stokesI = np.full(num_comps, 1.0)\n", "pol_frac = np.full(num_comps, 0.3)\n", "phi_RM = np.array([10, 50, 90])\n", "chi_0 = np.full(num_comps, 0.0)\n", "\n", "##The LoBES/hyperdrive/WODEN catalogues need a unique source ID (UNQ_SOURCE_ID),\n", "##a then edge component of that source needs a name (NAME)\n", "c_ids = Column(data=np.full(num_comps, 'multi_comp', dtype='|S20'), name='UNQ_SOURCE_ID', dtype='|S20')\n", "c_names = Column(data=[f'multi_comp_C{comp:02d}' for comp in range(num_comps)], name='NAME', dtype='|S20')\n", "\n", "##Component position\n", "c_ras = Column(data=np.full(num_comps, ra0), name='RA')\n", "c_decs = Column(data=np.full(num_comps, dec0), name='DEC')\n", "\n", "##This says we have a point source\n", "c_comp_types = Column(data=np.full(num_comps, 'P', dtype='|S1'), name=\"COMP_TYPE\", dtype='|S1')\n", "##This says we have a Stokes I power-law SED\n", "c_mod_types = Column(data=np.full(num_comps, 'pl', dtype='|S3'), name=\"MOD_TYPE\", dtype='|S3')\n", "##Stokes I power law parameters\n", "c_stokes_I_ref = Column(data=stokesI, name='NORM_COMP_PL')\n", "c_stokes_SI = Column(data=alpha, name='ALPHA_PL')\n", "\n", "##This says we are using a polarisation fraction linear polarisation model\n", "c_lin_mod_type = Column(data=np.full(num_comps, 'pf', dtype='|S3'), name='LIN_MOD_TYPE', dtype='|S3')\n", "##linear polarisation parameters\n", "c_lin_pol_frac = Column(data=pol_frac, name='LIN_POL_FRAC')\n", "c_lin_pol_angle = Column(data=chi_0, name='INTR_POL_ANGLE')\n", "c_rm = Column(data=phi_RM, name='RM')\n", "\n", "##Stick all the columns in a list\n", "columns = [c_ids, c_names, c_ras, c_decs, c_comp_types, c_mod_types, c_stokes_I_ref, c_stokes_SI, c_lin_mod_type,c_lin_pol_frac, c_lin_pol_angle, c_rm]\n", "\n", "##Make a table\n", "table = Table(columns)\n", "\n", "##write the table\n", "cat_name = 'multi_comp.fits'\n", "table.write(cat_name, overwrite=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Run it through WODEN, convert outputs into I,Q,U,V, have a look:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/jack-line/software/WODEN_dev/woden_dev/bin/run_woden.py:4: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html\n", " __import__('pkg_resources').require('wodenpy==2.5.0')\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2025-03-14 17:11:46 - INFO - \n", " ) ( ) \n", " ( ( ( /( )\\ ) ( /( \n", " )\\))( ')\\())(()/( ( )\\()) \n", " ((_)()\\ )((_)\\ /(_)) )\\ ((_)\\ \n", " _(())\\_)() ((_)(_))_ ((_) _((_) \n", " \\ \\((_)/ // _ \\ | \\ | __|| \\| | \n", " \\ \\/\\/ /| (_) || |) || _| | .` | \n", " \\_/\\_/ \\___/ |___/ |___||_|\\_| \n", " \n", " You are using wodenpy version/git hash: a43c383\n", " \n", "2025-03-14 17:11:46 - INFO - Input arguments after parsing:\n", " \tPhase centre: 99.00000, -20.60000 deg\n", " \tArray central latitude: -26.703 deg\n", " \tArray central longitude: 116.671 deg\n", " \tArray central height: 377.827 m\n", " \tLowest channel frequency: 180.000 MHz\n", " \tChannel frequency resolution: 80.000 kHz\n", " \tCoarse band bandwidth: 1.280 MHz\n", " \tNum channels per coarse band: 375\n", " \tStart date: 2024-07-05T04:00:00\n", " \tTime resolution: 2.0 (s)\n", " \tNum time steps: 1\n", " \tHave read 10 antenna positions from array layout file: eg_array.txt\n", " \tWill write outputs to: /home/jack-line/software/WODEN_dev/examples/polarisation\n", "2025-03-14 17:11:47 - INFO - Obs epoch initial LST was 100.3222998343 deg\n", "2025-03-14 17:11:47 - INFO - Setting initial J2000 LST to 100.0765134441 deg\n", "2025-03-14 17:11:47 - INFO - Setting initial mjd to 60496.1666782406\n", "2025-03-14 17:11:47 - INFO - After precession initial latitude of the array is -26.6814845740 deg\n", "2025-03-14 17:11:47 - INFO - Precessing array layout to J2000\n", "2025-03-14 17:11:47 - INFO - No primary beam selected, no beam attenuation will be applied.\n", "2025-03-14 17:11:47 - INFO - Doing the initial mapping of sky model\n", "INFO: couldn't find second table containing shapelet information, so not attempting to load any shapelets.\n", "2025-03-14 17:11:47 - INFO - Sky model mapping took 0.0 mins\n", "2025-03-14 17:11:47 - INFO - Have read in 3 components\n", "2025-03-14 17:11:47 - INFO - After cropping there are 3 components\n", "2025-03-14 17:11:47 - INFO - Will load libwoden from /home/jack-line/software/WODEN_dev/wodenpy/libwoden_double.so\n", "2025-03-14 17:11:47 - INFO - Running in serial on GPU.\n", " Will read sky model using 1 threads\n", " There are 1 sets of sky models to run\n", "2025-03-14 17:11:47 - INFO - Reading set 0 sky models\n", "2025-03-14 17:11:47 - INFO - From sky set 0 thread num 0 reading 3 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 17:11:48 - INFO - Sending Sky set 0 to the GPU\n", "2025-03-14 17:11:48 - INFO - Sky set 0 has returned from the GPU after 0.1 seconds\n", "2025-03-14 17:11:48 - INFO - Have completed 3 of 3 components calcs (100.0%)\n", "2025-03-14 17:11:48 - INFO - Full run took 0:00:01.249432\n", "2025-03-14 17:11:48 - INFO - WODEN is done. Closing the log. S'later\n", "24\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "##The command to run WODEN\n", "command = f'run_woden.py --ra0={ra0} --dec0={dec0} --array_layout={array_name} '\n", "command += f'--date={date} --output_uvfits_prepend={uvfits_name} '\n", "command += f'--cat_filename={cat_name} --primary_beam=none '\n", "command += f'--lowest_channel_freq={low_freq} --freq_res={freq_reso} '\n", "command += f'--num_freq_channels={num_freq_chans} --band_nums=1 '\n", "command += f'--time_res=2 --num_time_steps=1 --IAU_order --num_threads=1'\n", "\n", "##use subprocess to run the command\n", "call(command, shell=True)\n", "\n", "XX, XY, YX, YY = read_uvfits(f'{uvfits_name}_band01.uvfits')\n", "\n", "##pick a random baseline to plot, they should all be the same\n", "baseline = np.random.randint(0, XX.shape[0])\n", "print(baseline)\n", "\n", "##converts instrumental pols into Stokes params. We didn't use a primary beam\n", "##at we're right at zenith so this is good enough without corrections\n", "recover_I = 0.5*(XX[baseline] + YY[baseline])\n", "recover_Q = 0.5*(XX[baseline] - YY[baseline])\n", "recover_U = 0.5*(XY[baseline] + YX[baseline])\n", "recover_V = -0.5j*(XY[baseline] - YX[baseline])\n", "\n", "##these are the freqs we put into the simulation\n", "freqs = np.arange(low_freq, high_freq, freq_reso)\n", "\n", "fig, axs = plt.subplots(1, 1, figsize=(8, 6))\n", "\n", "axs.plot(freqs / 1e+6, recover_I.real, 'k-', label='Recovered I')\n", "axs.plot(freqs / 1e+6, recover_Q.real, 'r', label='Recovered Q')\n", "axs.plot(freqs / 1e+6, recover_U.real, 'b', label='Recovered U')\n", "axs.plot(freqs / 1e+6, recover_V.real, 'g', label='Recovered V')\n", "\n", "axs.legend()\n", "\n", "axs.set_xlabel('Frequency (MHz)')\n", "axs.set_ylabel('Flux (Jy)')\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Wiggly! Alrighty, what do we have in RM space?" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Determine the FDF using the q, u and ferquency values read from the file.\n", "FDFqu, phi = getFDF(recover_Q, recover_U, freqs, startPhi, stopPhi, dPhi)\n", "\n", "fig, axs = plt.subplots(1, 1, figsize=(6,4))\n", "\n", "axs.plot(phi, np.real(FDFqu), 'k-', label='FDF')\n", "\n", "axs.set_xlabel(\"${\\phi}$ (rad m$^{-2}$)\")\n", "axs.set_ylabel(\"Polarised Flux (Jy RMSF$^{-1}$)\")\n", "\n", "for phi in phi_RM:\n", "\taxs.axvline(x=phi, color='C1', linestyle='--', label='Expected RM')\n", "\n", "axs.legend()\n", "\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "I don't know nothing about polarisation, so I don't know if a negative peak in the FDF is bad. But we have three peaks where we expected them to be, which is nice." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Linear polarisation diffuse sky\n", "\n", "In this example, we'll make a crazy made-up sky. Then we'll push it through an instrument which has symmetric X and Y primary beams, which means we can make I/Q/U/V images without beam correction (as there won't be direction dependent differences).\n", "\n", "First up, make the sky model. This will be a little involved as we're going to make the Stokes I, linear polarised, and Stokes V sky separately. We'll make Stokes I simple point sources. The linear sky will be the Haslam map (via the [pygdsm](https://github.com/telegraphic/pygdsm) package), and the Stokes V sky will be a bunch of Gaussian blobs. Everything will have a simple power-law SED." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "\n", "##We're going to use the EDA2 array\n", "##layout, so we can get away with low-resolution sky model. So set the \n", "##healpixel nside to 256\n", "nside = 256\n", "num_diffuse = hp.nside2npix(nside)\n", "\n", "##chuck in 1000 each for stokes I and V\n", "num_stokesI = 1000\n", "num_stokesV = 1000\n", "\n", "total_num_comps = num_diffuse + num_stokesI + num_stokesV\n", "\n", "##first, the diffuse sky linear polarised sky. Generate it at 200MHz,\n", "##convert it to the nside we want, and then convert it to Jy\n", "gsm_2016 = GlobalSkyModel16(freq_unit='MHz', data_unit='MJysr')\n", "output = gsm_2016.generate(200)\n", "map_nside = hp.npix2nside(len(output))\n", "output *= hp.nside2pixarea(map_nside)*1e+6\n", "\n", "##Set some power law properties, and set the RM to 2 ra/m^2 everywhere\n", "diffuse_ref_flux = hp.ud_grade(output, nside)\n", "diffuse_SI = np.full(num_diffuse, -2.7)\n", "diffuse_rm = np.full(num_diffuse, 2)\n", "\n", "##coords are natively in galactic, so we need to convert to ICRS\n", "l, b = hp.pix2ang(nside,np.arange(hp.nside2npix(nside)), lonlat=True)\n", "gal_coords = SkyCoord(l*u.deg, b*u.deg, frame='galactic')\n", "diff_ras = gal_coords.icrs.ra.value\n", "diff_decs = gal_coords.icrs.dec.value\n", "\n", "##next, make a simple point source stokes I sky\n", "##make 'em power laws\n", "comp_ras = np.random.uniform(0, 360, num_stokesI)\n", "comp_decs = np.random.uniform(-90.0, 90.0, num_stokesI)\n", "comp_ref_fluxes = np.random.uniform(1, 10, num_stokesI)\n", "comp_ref_SIs = np.random.uniform(-1, 0.2, num_stokesI)\n", "\n", "\n", "##finally, make some weird large gaussian source stokes V sky\n", "##also make 'em power laws\n", "v_ras = np.random.uniform(0, 360, num_stokesV)\n", "v_decs = np.random.uniform(-90.0, 90.0, num_stokesV)\n", "\n", "v_ref_fluxes = np.random.uniform(1, 50, num_stokesV)\n", "v_ref_SIs = np.random.uniform(-1, 0.2, num_stokesV)\n", "##these are the gaussian params; all these sizes are in degrees\n", "v_major_axes = np.random.uniform(10, 12, num_stokesV)\n", "v_minor_axes = np.random.uniform(0.25, 0.5, num_stokesV)\n", "v_pas = np.random.uniform(0,360, num_stokesV)\n", "\n", "##now we take all these individual parameters and stick them in a table\n", "\n", "all_stokes_I_ref = np.zeros(total_num_comps)\n", "all_stokes_I_ref[:num_stokesI] = comp_ref_fluxes\n", "all_stokes_SI = np.zeros(total_num_comps)\n", "all_stokes_SI[:num_stokesI] = comp_ref_SIs\n", "\n", "all_lin_mod_type = np.full(total_num_comps, '', dtype='|S3')\n", "all_lin_mod_type[num_stokesI:num_stokesI+num_diffuse] = 'pl'\n", "\n", "all_linpol_ref = np.zeros(total_num_comps)\n", "all_linpol_ref[num_stokesI:num_stokesI+num_diffuse] = diffuse_ref_flux\n", "\n", "all_linpol_SI = np.zeros(total_num_comps)\n", "all_linpol_SI[num_stokesI:num_stokesI+num_diffuse] = diffuse_SI\n", "\n", "all_rm = np.zeros(total_num_comps)\n", "all_rm[num_stokesI:num_stokesI+num_diffuse] = diffuse_rm\n", "\n", "all_v_mod_type = np.full(total_num_comps, '', dtype='|S3')\n", "all_v_mod_type[-num_stokesV:] = 'pl'\n", "\n", "all_v_ref = np.zeros(total_num_comps)\n", "all_v_ref[-num_stokesV:] = v_ref_fluxes\n", "\n", "all_v_SI = np.zeros(total_num_comps)\n", "all_v_SI[-num_stokesV:] = v_ref_SIs\n", "\n", "all_majors = np.full(total_num_comps, np.nan)\n", "all_majors[-num_stokesV:] = v_major_axes\n", "all_minors = np.full(total_num_comps, np.nan)\n", "all_minors[-num_stokesV:] = v_minor_axes\n", "all_pas = np.full(total_num_comps, np.nan)\n", "all_pas[-num_stokesV:] = v_pas\n", "\n", "##make everything except the stokes V sources gaussian\n", "all_comp_types = np.full(total_num_comps, 'P', dtype='|S1')\n", "all_comp_types[-num_stokesV:] = 'G'\n", "\n", "\n", "##create Columns to go into the table\n", "c_ids = Column(data=np.array(['{:08d}'.format(i) for i in range(total_num_comps)]), name='UNQ_SOURCE_ID', dtype='|S20')\n", "c_names = Column(data=np.array(['{:08d}_C00'.format(i) for i in range(total_num_comps)]), name='NAME', dtype='|S20')\n", "\n", "c_ras = Column(data=np.concatenate([comp_ras, diff_ras, v_ras]), name='RA')\n", "c_decs = Column(data=np.concatenate([comp_decs, diff_decs, v_decs]), name='DEC')\n", "c_comp_types = Column(data=all_comp_types, name=\"COMP_TYPE\", dtype='|S1')\n", "c_mod_types = Column(data=np.full(total_num_comps, 'pl', dtype='|S3'), name=\"MOD_TYPE\", dtype='|S3')\n", "\n", "c_stokes_I_ref = Column(data=all_stokes_I_ref, name='NORM_COMP_PL')\n", "c_stokes_SI = Column(data=all_stokes_SI, name='ALPHA_PL')\n", "\n", "c_lin_mod_type = Column(data=all_lin_mod_type, name='LIN_MOD_TYPE', dtype='|S3')\n", "c_linpol_ref = Column(data=all_linpol_ref, name='LIN_NORM_COMP_PL')\n", "c_linpol_SI = Column(data=all_linpol_SI, name='LIN_ALPHA_PL')\n", "c_rm = Column(data=all_rm, name='RM')\n", "\n", "\n", "c_v_mod_type = Column(data=all_v_mod_type, name='V_MOD_TYPE', dtype='|S3')\n", "c_v_ref = Column(data=all_v_ref, name='V_NORM_COMP_PL')\n", "c_v_SI = Column(data=all_v_SI, name='V_ALPHA_PL')\n", "\n", "c_major = Column(data=all_majors, name='MAJOR_DC')\n", "c_minor = Column(data=all_majors, name='MINOR_DC')\n", "c_pas = Column(data=all_pas, name='PA_DC')\n", "\n", "\n", "##Make a da table\n", "columns = [c_ids, c_names, c_ras, c_decs, c_comp_types, c_mod_types,\n", " c_stokes_I_ref, c_stokes_SI, c_lin_mod_type, c_linpol_ref,\n", " c_linpol_SI, c_rm, c_v_mod_type, c_v_ref, c_v_SI, c_major,\n", " c_minor, c_pas]\n", "\n", "table = Table(columns)\n", "table.write('polarised_sky.fits', overwrite=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "OK, now we have a sky model, let's run the simulation (which takes 14 mins on my desktop). We'll use the EDA2 array layout, and set the `--IAU_order` flag again. We'll also set both X and Y beams to be a Gaussian beam with FWHM of 100 deg. This will let us see most of the sky, but chop the horizon off to make imaging nicer. This beam also has zero leakage, which means we keep the I/Q/U/V all nice and separate. We'll phase things up to EoR1 so the galactic plane is down. Do it with `float` precision as we don't really care too much about accuracy, just want some fun images" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/jack-line/software/WODEN_dev/woden_dev/bin/run_woden.py:4: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html\n", " __import__('pkg_resources').require('wodenpy==2.5.0')\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2025-03-14 16:44:19 - INFO - \n", " ) ( ) \n", " ( ( ( /( )\\ ) ( /( \n", " )\\))( ')\\())(()/( ( )\\()) \n", " ((_)()\\ )((_)\\ /(_)) )\\ ((_)\\ \n", " _(())\\_)() ((_)(_))_ ((_) _((_) \n", " \\ \\((_)/ // _ \\ | \\ | __|| \\| | \n", " \\ \\/\\/ /| (_) || |) || _| | .` | \n", " \\_/\\_/ \\___/ |___/ |___||_|\\_| \n", " \n", " You are using wodenpy version/git hash: a43c383\n", " \n", "2025-03-14 16:44:19 - INFO - Input arguments after parsing:\n", " \tPhase centre: 60.00000, -27.00000 deg\n", " \tArray central latitude: -26.703 deg\n", " \tArray central longitude: 116.671 deg\n", " \tArray central height: 377.827 m\n", " \tLowest channel frequency: 167.035 MHz\n", " \tChannel frequency resolution: 80.000 kHz\n", " \tCoarse band bandwidth: 1.280 MHz\n", " \tNum channels per coarse band: 16\n", " \tStart date: 2016-01-09T13:11:19\n", " \tTime resolution: 8.0 (s)\n", " \tNum time steps: 14\n", " \tHave read 255 antenna positions from array layout file: ../../test_installation/array_layouts/EDA2_layout_255.txt\n", " \tWill write outputs to: /home/jack-line/software/WODEN_dev/examples/polarisation\n", "2025-03-14 16:44:20 - INFO - Obs epoch initial LST was 63.0347905707 deg\n", "2025-03-14 16:44:20 - INFO - Setting initial J2000 LST to 62.8702463523 deg\n", "2025-03-14 16:44:20 - INFO - Setting initial mjd to 57396.5495717593\n", "2025-03-14 16:44:20 - INFO - After precession initial latitude of the array is -26.7414173539 deg\n", "2025-03-14 16:44:20 - INFO - Precessing array layout to J2000\n", "2025-03-14 16:44:20 - INFO - Using Gaussian primary beam with the following parameters:\n", " \tLocked to pointing: HA -0.2 deg, Dec -26.74111165708009 deg\n", " \tFWHM: 100.0 at reference frequency: 150.0 MHz\n", "2025-03-14 16:44:20 - INFO - Doing the initial mapping of sky model\n", "INFO: couldn't find second table containing shapelet information, so not attempting to load any shapelets.\n", "2025-03-14 16:44:23 - INFO - Sky model mapping took 0.0 mins\n", "2025-03-14 16:44:23 - INFO - Have read in 788432 components\n", "2025-03-14 16:44:23 - INFO - After cropping there are 394238 components\n", "2025-03-14 16:44:23 - INFO - Will load libwoden from /home/jack-line/software/WODEN_dev/wodenpy/libwoden_float.so\n", "2025-03-14 16:44:24 - INFO - Running in parallel on GPU.\n", " Will read sky model using 8 threads\n", " There are 3 sets of sky models to run\n", "2025-03-14 16:44:24 - INFO - Reading set 0 sky models\n", "2025-03-14 16:44:25 - INFO - From sky set 0 thread num 0 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:26 - INFO - From sky set 0 thread num 1 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:26 - INFO - From sky set 0 thread num 2 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:27 - INFO - From sky set 0 thread num 3 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:27 - INFO - From sky set 0 thread num 4 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:28 - INFO - From sky set 0 thread num 5 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:29 - INFO - From sky set 0 thread num 6 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:29 - INFO - From sky set 0 thread num 7 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:30 - INFO - Reading set 1 sky models\n", "2025-03-14 16:44:31 - INFO - From sky set 1 thread num 0 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:31 - INFO - Sending Sky set 0 to the GPU\n", "2025-03-14 16:44:31 - INFO - From sky set 1 thread num 1 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:32 - INFO - From sky set 1 thread num 2 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:33 - INFO - From sky set 1 thread num 3 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:33 - INFO - From sky set 1 thread num 4 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:34 - INFO - From sky set 1 thread num 5 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:35 - INFO - From sky set 1 thread num 6 reading 24608 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:44:35 - INFO - From sky set 1 thread num 7 reading 24590 points, 0 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:51:30 - INFO - Sky set 0 has returned from the GPU after 418.4 seconds\n", "2025-03-14 16:51:30 - INFO - Have completed 196864 of 394238 components calcs (49.9%)\n", "2025-03-14 16:51:30 - INFO - Reading set 2 sky models\n", "2025-03-14 16:51:31 - INFO - From sky set 2 thread num 0 reading 0 points, 66 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:51:31 - INFO - Sending Sky set 1 to the GPU\n", "2025-03-14 16:51:32 - INFO - From sky set 2 thread num 1 reading 0 points, 66 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:51:32 - INFO - From sky set 2 thread num 2 reading 0 points, 66 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:51:33 - INFO - From sky set 2 thread num 3 reading 0 points, 66 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:51:33 - INFO - From sky set 2 thread num 4 reading 0 points, 66 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:51:34 - INFO - From sky set 2 thread num 5 reading 0 points, 66 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:51:35 - INFO - From sky set 2 thread num 6 reading 0 points, 66 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:51:35 - INFO - From sky set 2 thread num 7 reading 0 points, 66 gauss, 0 shape, 0 shape coeffs\n", "2025-03-14 16:58:19 - INFO - Sky set 1 has returned from the GPU after 407.2 seconds\n", "2025-03-14 16:58:19 - INFO - Have completed 393710 of 394238 components calcs (99.9%)\n", "2025-03-14 16:58:19 - INFO - Sending Sky set 2 to the GPU\n", "2025-03-14 16:58:23 - INFO - Sky set 2 has returned from the GPU after 3.9 seconds\n", "2025-03-14 16:58:23 - INFO - Have completed 394238 of 394238 components calcs (100.0%)\n", "2025-03-14 16:58:23 - INFO - Finished all rounds of processing\n", "2025-03-14 16:58:26 - INFO - Full run took 0:14:06.392452\n", "2025-03-14 16:58:26 - INFO - WODEN is done. Closing the log. S'later\n" ] }, { "data": { "text/plain": [ "0" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metafits=\"../metafits/1136380296_metafits_ppds.fits\"\n", "uvfits_name = \"scary_sky\"\n", "array_layout = \"../../test_installation/array_layouts/EDA2_layout_255.txt\"\n", "\n", "command = \"run_woden.py \"\n", "command += \" --ra0=60.0 --dec0=-27.0\"\n", "command += \" --num_freq_channels=16 --num_time_steps=14\"\n", "command += \" --freq_res=80e+3 --time_res=8.0\"\n", "command += \" --cat_filename=polarised_sky.fits\"\n", "command += f\" --metafits_filename={metafits}\"\n", "command += \" --band_nums=1\"\n", "command += f\" --output_uvfits_prepend={uvfits_name}\"\n", "command += \" --primary_beam=Gaussian --gauss_beam_FWHM=100\"\n", "command += f\" --array_layout={array_layout}\"\n", "command += \" --sky_crop_components\"\n", "command += \" --chunking_size=5e+10\"\n", "command += \" --precision=float\"\n", "\n", "call(command, shell=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can image it using WSClean. To be clear, normally you'd need to beam correct the images, and direction dependent differences between XX,XY,YX,YY mess with the conversion from instrumental to Stokes parameters. But as the primary beam is the same for both polarisations, you just get Stokes I/Q/U/V times a Gaussian beam after running through `WSClean`." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/jack-line/software/WODEN_dev/woden_dev/bin/woden_uv2ms.py:4: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html\n", " __import__('pkg_resources').require('wodenpy==2.5.0')\n", "rm: cannot remove 'scary_sky_band01.ms': No such file or directory\n", "The telescope frame is set to '????', which generally indicates ignorance. Defaulting the frame to 'itrs', but this may lead to other warnings or errors.\n", "Writing in the MS file that the units of the data are uncalib, although some CASA process will ignore this and assume the units are all in Jy (or may not know how to handle data in these units).\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "WSClean version 3.4 (2023-10-11)\n", "This software package is released under the GPL version 3.\n", "Author: André Offringa (offringa@gmail.com).\n", "\n", "No corrected data in first measurement set: tasks will be applied on the data column.\n", "=== IMAGING TABLE ===\n", " # Pol Ch JG ²G FG FI In Freq(MHz)\n", "| Independent group:\n", "+-+-J- 0 I 0 0 0 0 0 0 167-168 (16)\n", "| Independent group:\n", "+-+-J- 1 Q 0 1 1 1 0 0 167-168 (16)\n", "| Independent group:\n", "+-+-J- 2 U 0 2 2 2 0 0 167-168 (16)\n", "| Independent group:\n", "+-+-J- 3 V 0 3 3 3 0 0 167-168 (16)\n", "Reordering scary_sky_band01.ms into 1 x 4 parts.\n", "Reordering: 0%....10%....20%....30%....40%....50%....60%....70%....80%....90%....100%\n", "Initializing model visibilities: 0%....10%....20%....30%....40%....50%....60%....70%....80%....90%....100%\n", " == Constructing PSF ==\n", "Precalculating weights for Briggs'(0) weighting...\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Detected 62.7 GB of system memory, usage not limited.\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Determining min and max w & theoretical beam size... DONE (w=[2.02049e-06:0.99262] lambdas, maxuvw=19.749 lambda)\n", "Theoretic beam = 2.9 deg\n", "Minimal inversion size: 102 x 102, using optimal: 108 x 108\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", "Fitting beam... major=119.87', minor=119.53', PA=48.03 deg, theoretical=2.9 deg.\n", "Writing psf image... DONE\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", "Writing dirty image...\n", " == Deconvolving (1) ==\n", "Estimated standard deviation of background noise: 159.09 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 407.35 mJy, 387: 116.39 mJy, 774: 83.59 mJy, 1547: 57.43 mJy}\n", "Starting multi-scale cleaning. Start peak=10.93 Jy, major iteration threshold=1.64 Jy\n", "Iteration 4, scale 0 px : 8.28 Jy at 1952,2044\n", "Iteration 13, scale 0 px : 6.49 Jy at 2003,1791\n", "Iteration 28, scale 0 px : 5.08 Jy at 1793,1908\n", "Iteration 52, scale 0 px : 4.05 Jy at 2417,2394\n", "Iteration 94, scale 0 px : 3.24 Jy at 2374,2175\n", "Iteration 147, scale 0 px : 2.59 Jy at 2508,2450\n", "Iteration 220, scale 0 px : 2.06 Jy at 2278,1964\n", "Iteration 304, scale 0 px : 1.64 Jy at 1517,1441\n", "Subminor loop is near minor loop threshold. Initiating countdown.\n", "(7) Iteration 306, scale 0 px : 1.64 Jy at 2504,2446\n", "Minor loop finished, continuing cleaning after inversion/prediction round.\n", "Assigning from 1 to 1 channels...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", " == Deconvolving (2) ==\n", "Estimated standard deviation of background noise: 74.81 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 171.59 mJy, 387: 45.45 mJy, 774: 26.22 mJy, 1547: 15.88 mJy}\n", "Starting multi-scale cleaning. Start peak=1.69 Jy, major iteration threshold=253.76 mJy\n", "Iteration 383, scale 0 px : 1.35 Jy at 2090,3070\n", "Iteration 497, scale 0 px : 1.08 Jy at 2617,2665\n", "Iteration 613, scale 0 px : 859.64 mJy at 1136,2509\n", "Iteration 749, scale 0 px : 687.48 mJy at 2098,1258\n", "Iteration 921, scale 0 px : 559.55 mJy at 2475,1168\n", "Iteration 1000, scale 0 px : 499.7 mJy at 1541,1979\n", "Cleaning finished because maximum number of iterations was reached.\n", "Auto-masking threshold reached; continuing next major iteration with deeper threshold and mask.\n", "Maximum number of minor deconvolution iterations was reached: not continuing deconvolution.\n", "Assigning from 1 to 1 channels...\n", "Writing model image...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", "2 major iterations were performed.\n", "Rendering sources to restored image (beam=119.53'-119.87', PA=48.03 deg)... DONE\n", "Writing restored image... DONE\n", "Multi-scale cleaning summary:\n", "- Scale 0 px, nr of components cleaned: 1000 (154.87 Jy)\n", "- Scale 387 px, nr of components cleaned: 0 (0 Jy)\n", "- Scale 774 px, nr of components cleaned: 0 (0 Jy)\n", "- Scale 1547 px, nr of components cleaned: 0 (0 Jy)\n", "Total: 1000 components (154.87 Jy)\n", "Inversion: 00:00:08.256919, prediction: 00:00:02.163137, deconvolution: 00:00:20.704123\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Determining min and max w & theoretical beam size... DONE (w=[2.02049e-06:0.99262] lambdas, maxuvw=19.749 lambda)\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", "Writing dirty image...\n", " == Deconvolving (1) ==\n", "Estimated standard deviation of background noise: 1.15 Jy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 1.2 Jy, 387: 1.17 Jy, 774: 1.09 Jy, 1547: 877.75 mJy}\n", "Starting multi-scale cleaning. Start peak=-16.38 Jy, major iteration threshold=3.44 Jy (final)\n", "Iteration 5, scale 1547 px : -12.62 Jy at 1906,2109\n", "Iteration 10, scale 1547 px : -9.72 Jy at 1906,2109\n", "Iteration 15, scale 1547 px : -7.49 Jy at 1826,2168\n", "Iteration 23, scale 1547 px : -5.84 Jy at 1642,2307\n", "Iteration 33, scale 1547 px : -4.59 Jy at 1597,2348\n", "Iteration 48, scale 774 px : -3.87 Jy at 1710,1621\n", "Subminor loop is near minor loop threshold. Initiating countdown.\n", "(7) Iteration 51, scale 1547 px : -3.64 Jy at 2419,2100\n", "(6) Iteration 56, scale 1547 px : -3.38 Jy at 2024,1622\n", "Cleaning finished because the final threshold was reached.\n", "Auto-masking threshold reached; continuing next major iteration with deeper threshold and mask.\n", "Assigning from 1 to 1 channels...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", " == Deconvolving (2) ==\n", "Estimated standard deviation of background noise: 578.96 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 553.64 mJy, 387: 522.39 mJy, 774: 479.75 mJy, 1547: 363.44 mJy}\n", "Starting multi-scale cleaning. Start peak=-3.45 Jy, major iteration threshold=516.81 mJy\n", "Iteration 73, scale 774 px : -2.89 Jy at 1710,1621\n", "Iteration 77, scale 1547 px : -2.78 Jy at 2419,2100\n", "Iteration 91, scale 1547 px : -2.21 Jy at 2419,2100\n", "Iteration 109, scale 774 px : -1.95 Jy at 1710,1621\n", "Iteration 113, scale 1547 px : -1.8 Jy at 2419,2100\n", "Iteration 127, scale 1547 px : 1.43 Jy at 1491,819\n", "Iteration 145, scale 774 px : -1.36 Jy at 1710,1621\n", "Iteration 149, scale 774 px : -1.08 Jy at 1710,1621\n", "Iteration 153, scale 1547 px : -1.17 Jy at 2419,2100\n", "Iteration 165, scale 1547 px : -930.79 mJy at 2419,2100\n", "Iteration 183, scale 1547 px : 890.55 mJy at 1906,2109\n", "Iteration 201, scale 1547 px : -840.1 mJy at 1888,1660\n", "Iteration 231, scale 774 px : -694.65 mJy at 1710,1621\n", "Iteration 235, scale 1547 px : -670.28 mJy at 1559,2399\n", "Iteration 299, scale 1547 px : -531.11 mJy at 2419,2100\n", "Subminor loop is near minor loop threshold. Initiating countdown.\n", "(7) Iteration 314, scale 1547 px : -512.48 mJy at 1564,2400\n", "Minor loop finished, continuing cleaning after inversion/prediction round.\n", "Assigning from 1 to 1 channels...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", " == Deconvolving (3) ==\n", "Estimated standard deviation of background noise: 330.12 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 372.97 mJy, 387: 335.63 mJy, 774: 286.88 mJy, 1547: 194.29 mJy}\n", "Starting multi-scale cleaning. Start peak=-612.04 mJy, major iteration threshold=165.06 mJy (final)\n", "Iteration 329, scale 1547 px : -544.22 mJy at 2419,2100\n", "Iteration 390, scale 1547 px : 434.82 mJy at 1491,819\n", "Iteration 479, scale 1547 px : -347.51 mJy at 1888,1660\n", "Iteration 570, scale 1547 px : 275.86 mJy at 2085,1985\n", "Iteration 667, scale 1547 px : -220.34 mJy at 1888,1660\n", "Iteration 757, scale 1547 px : -176.06 mJy at 1564,2400\n", "Subminor loop is near minor loop threshold. Initiating countdown.\n", "(7) Iteration 787, scale 1547 px : 163.64 mJy at 2085,1985\n", "Cleaning finished because the final threshold was reached.\n", "Assigning from 1 to 1 channels...\n", "Writing model image...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", "3 major iterations were performed.\n", "Rendering sources to restored image (beam=119.53'-119.87', PA=48.03 deg)... DONE\n", "Writing restored image... DONE\n", "Multi-scale cleaning summary:\n", "- Scale 0 px, nr of components cleaned: 0 (0 Jy)\n", "- Scale 387 px, nr of components cleaned: 0 (0 Jy)\n", "- Scale 774 px, nr of components cleaned: 23 (-53.1 Jy)\n", "- Scale 1547 px, nr of components cleaned: 764 (-1.95 KJy)\n", "Total: 787 components (-2 KJy)\n", "Inversion: 00:00:13.748209, prediction: 00:00:05.396248, deconvolution: 00:02:15.731349\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Determining min and max w & theoretical beam size... DONE (w=[2.02049e-06:0.99262] lambdas, maxuvw=19.749 lambda)\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", "Writing dirty image...\n", " == Deconvolving (1) ==\n", "Estimated standard deviation of background noise: 265.47 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 277.57 mJy, 387: 269.08 mJy, 774: 254.38 mJy, 1547: 202.53 mJy}\n", "Starting multi-scale cleaning. Start peak=3.8 Jy, major iteration threshold=796.42 mJy (final)\n", "Iteration 5, scale 1547 px : 2.92 Jy at 1906,2109\n", "Iteration 10, scale 1547 px : 2.25 Jy at 1906,2109\n", "Iteration 15, scale 1547 px : 1.74 Jy at 1988,2051\n", "Iteration 23, scale 1547 px : 1.36 Jy at 2215,1915\n", "Iteration 34, scale 1547 px : 1.04 Jy at 1592,2347\n", "Iteration 50, scale 774 px : 877.01 mJy at 1706,1622\n", "Subminor loop is near minor loop threshold. Initiating countdown.\n", "(7) Iteration 52, scale 1547 px : 828.27 mJy at 1564,2403\n", "(6) Iteration 55, scale 1547 px : 789.35 mJy at 1563,2408\n", "Cleaning finished because the final threshold was reached.\n", "Auto-masking threshold reached; continuing next major iteration with deeper threshold and mask.\n", "Assigning from 1 to 1 channels...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", " == Deconvolving (2) ==\n", "Estimated standard deviation of background noise: 134.81 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 129.06 mJy, 387: 122.88 mJy, 774: 111.48 mJy, 1547: 85.22 mJy}\n", "Starting multi-scale cleaning. Start peak=820.55 mJy, major iteration threshold=123.08 mJy\n", "Iteration 71, scale 774 px : 710.69 mJy at 1706,1622\n", "Iteration 75, scale 1547 px : 654.88 mJy at 2427,2103\n", "Iteration 92, scale 1547 px : 505.15 mJy at 1869,1656\n", "Iteration 111, scale 774 px : 458.2 mJy at 1706,1622\n", "Iteration 115, scale 774 px : 364.08 mJy at 1706,1622\n", "Iteration 119, scale 1547 px : 413.06 mJy at 2427,2103\n", "Iteration 131, scale 1547 px : 328.85 mJy at 2427,2103\n", "Iteration 150, scale 1547 px : 257.54 mJy at 1564,2403\n", "Iteration 168, scale 774 px : 231.16 mJy at 1706,1622\n", "Iteration 172, scale 774 px : 183.68 mJy at 1706,1622\n", "Iteration 176, scale 1547 px : 209.58 mJy at 1564,2403\n", "Iteration 206, scale 1547 px : 203.63 mJy at 1869,1656\n", "Iteration 212, scale 1547 px : -186.38 mJy at 1988,2051\n", "Iteration 252, scale 1547 px : 148.68 mJy at 1564,2403\n", "Subminor loop is near minor loop threshold. Initiating countdown.\n", "(7) Iteration 313, scale 1547 px : 122.57 mJy at 1869,1656\n", "Minor loop finished, continuing cleaning after inversion/prediction round.\n", "Assigning from 1 to 1 channels...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", " == Deconvolving (3) ==\n", "Estimated standard deviation of background noise: 76 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 86.21 mJy, 387: 77.01 mJy, 774: 66.52 mJy, 1547: 45.09 mJy}\n", "Starting multi-scale cleaning. Start peak=143.59 mJy, major iteration threshold=38 mJy (final)\n", "Iteration 330, scale 1547 px : 127.86 mJy at 2423,2109\n", "Iteration 376, scale 1547 px : 102.04 mJy at 1869,1656\n", "Iteration 447, scale 1547 px : -80.48 mJy at 1988,2051\n", "Iteration 517, scale 1547 px : 64.15 mJy at 2423,2109\n", "Iteration 591, scale 1547 px : 51 mJy at 1869,1656\n", "Iteration 687, scale 1547 px : 40.71 mJy at 2423,2109\n", "Subminor loop is near minor loop threshold. Initiating countdown.\n", "(7) Iteration 714, scale 1547 px : 37.99 mJy at 1564,2403\n", "Cleaning finished because the final threshold was reached.\n", "Assigning from 1 to 1 channels...\n", "Writing model image...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", "3 major iterations were performed.\n", "Rendering sources to restored image (beam=119.53'-119.87', PA=48.03 deg)... DONE\n", "Writing restored image... DONE\n", "Multi-scale cleaning summary:\n", "- Scale 0 px, nr of components cleaned: 0 (0 Jy)\n", "- Scale 387 px, nr of components cleaned: 0 (0 Jy)\n", "- Scale 774 px, nr of components cleaned: 22 (11.67 Jy)\n", "- Scale 1547 px, nr of components cleaned: 692 (453.11 Jy)\n", "Total: 714 components (464.79 Jy)\n", "Inversion: 00:00:19.245613, prediction: 00:00:08.507912, deconvolution: 00:04:07.420747\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Determining min and max w & theoretical beam size... DONE (w=[2.02049e-06:0.99262] lambdas, maxuvw=19.749 lambda)\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", "Writing dirty image...\n", " == Deconvolving (1) ==\n", "Estimated standard deviation of background noise: 280.57 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 333.71 mJy, 387: 317.21 mJy, 774: 285.52 mJy, 1547: 219.77 mJy}\n", "Starting multi-scale cleaning. Start peak=4.17 Jy, major iteration threshold=841.71 mJy (final)\n", "Iteration 5, scale 774 px : 3.29 Jy at 2044,2166\n", "Iteration 9, scale 1547 px : 3.01 Jy at 1949,1779\n", "Iteration 14, scale 1547 px : 2.32 Jy at 1950,1780\n", "Iteration 20, scale 774 px : 2.15 Jy at 2094,2222\n", "Iteration 26, scale 774 px : 1.72 Jy at 2094,2222\n", "Iteration 48, scale 1547 px : 1.39 Jy at 1719,1652\n", "Iteration 57, scale 774 px : 1.32 Jy at 2225,1423\n", "Iteration 77, scale 774 px : 1.05 Jy at 2490,1787\n", "Iteration 107, scale 1547 px : 848.52 mJy at 2456,2048\n", "Subminor loop is near minor loop threshold. Initiating countdown.\n", "(7) Iteration 108, scale 774 px : 843.91 mJy at 2247,1420\n", "(6) Iteration 109, scale 1547 px : 842.97 mJy at 1568,1706\n", "(5) Iteration 110, scale 387 px : -845.66 mJy at 2043,1774\n", "(4) Iteration 111, scale 774 px : 822.16 mJy at 2200,2330\n", "Cleaning finished because the final threshold was reached.\n", "Auto-masking threshold reached; continuing next major iteration with deeper threshold and mask.\n", "Assigning from 1 to 1 channels...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", " == Deconvolving (2) ==\n", "Estimated standard deviation of background noise: 110.52 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 134.8 mJy, 387: 124.41 mJy, 774: 104.45 mJy, 1547: 73.96 mJy}\n", "Starting multi-scale cleaning. Start peak=831.2 mJy, major iteration threshold=124.68 mJy\n", "Iteration 122, scale 387 px : -850.99 mJy at 2043,1774\n", "Iteration 126, scale 774 px : 823.13 mJy at 2243,1419\n", "Iteration 145, scale 774 px : 672.34 mJy at 1442,1680\n", "Iteration 178, scale 387 px : -614.95 mJy at 2043,1774\n", "Iteration 182, scale 387 px : -486.27 mJy at 2043,1774\n", "Iteration 186, scale 1547 px : 531.63 mJy at 2456,2048\n", "Iteration 198, scale 774 px : 547.1 mJy at 2247,1420\n", "Iteration 211, scale 774 px : 437.27 mJy at 2683,1951\n", "Iteration 244, scale 1547 px : 357.51 mJy at 1568,1706\n", "Iteration 253, scale 387 px : -407.91 mJy at 2043,1774\n", "Iteration 257, scale 387 px : -322.55 mJy at 2043,1774\n", "Iteration 261, scale 774 px : 353.73 mJy at 2247,1420\n", "Iteration 281, scale 774 px : 293.83 mJy at 1442,1680\n", "Iteration 311, scale 1547 px : 247.95 mJy at 1568,1706\n", "Iteration 319, scale 387 px : -244.22 mJy at 2043,1774\n", "Iteration 323, scale 774 px : 242.66 mJy at 2247,1420\n", "Iteration 342, scale 774 px : 196.03 mJy at 1442,1680\n", "Iteration 375, scale 387 px : -177.25 mJy at 2043,1774\n", "Iteration 379, scale 1547 px : 170.2 mJy at 1568,1706\n", "Iteration 386, scale 774 px : 159.27 mJy at 2247,1420\n", "Iteration 409, scale 774 px : 124.97 mJy at 1705,2210\n", "Subminor loop is near minor loop threshold. Initiating countdown.\n", "(7) Iteration 410, scale 387 px : -141.87 mJy at 2043,1774\n", "(6) Iteration 413, scale 1547 px : 135.53 mJy at 1568,1706\n", "(5) Iteration 415, scale 774 px : 124.91 mJy at 2195,2310\n", "(4) Iteration 416, scale 774 px : 124.96 mJy at 2683,1951\n", "(3) Iteration 417, scale 774 px : 123.64 mJy at 2247,1420\n", "Minor loop finished, continuing cleaning after inversion/prediction round.\n", "Assigning from 1 to 1 channels...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", " == Deconvolving (3) ==\n", "Estimated standard deviation of background noise: 48.2 mJy\n", "Scale info:\n", "- Scale 0, bias factor=1, psfpeak=1, gain=0.1, kernel peak=0.000118546\n", "- Scale 387, bias factor=1.7, psfpeak=0.109965, gain=0.909382, kernel peak=2.99227e-05\n", "- Scale 774, bias factor=2.8, psfpeak=0.0273488, gain=3.65646, kernel peak=7.55434e-06\n", "- Scale 1547, bias factor=4.6, psfpeak=0.00622096, gain=16.0747, kernel peak=1.89546e-06\n", "RMS per scale: {0: 76.43 mJy, 387: 64.64 mJy, 774: 47.82 mJy, 1547: 29.25 mJy}\n", "Starting multi-scale cleaning. Start peak=142.49 mJy, major iteration threshold=24.1 mJy (final)\n", "Iteration 422, scale 774 px : 122.98 mJy at 1705,2210\n", "Iteration 447, scale 387 px : -120.41 mJy at 2043,1774\n", "Iteration 451, scale 1547 px : 103.99 mJy at 1568,1706\n", "Iteration 458, scale 387 px : -99.49 mJy at 2043,1774\n", "Iteration 462, scale 774 px : 99.12 mJy at 2247,1420\n", "Iteration 484, scale 774 px : 79.26 mJy at 2044,2165\n", "Iteration 519, scale 1547 px : -80 mJy at 1950,1780\n", "Iteration 534, scale 1547 px : 65.44 mJy at 2456,2048\n", "Iteration 567, scale 774 px : 86.34 mJy at 2247,1420\n", "Iteration 575, scale 774 px : 69.06 mJy at 2247,1420\n", "Iteration 594, scale 774 px : 55.03 mJy at 2449,1746\n", "Iteration 616, scale 1547 px : -77.41 mJy at 1950,1780\n", "Iteration 621, scale 1547 px : -59.63 mJy at 1950,1780\n", "Iteration 641, scale 1547 px : 53.4 mJy at 2456,2048\n", "Iteration 661, scale 1547 px : 42.56 mJy at 1568,1706\n", "Iteration 695, scale 774 px : 72.87 mJy at 2103,1409\n", "Iteration 704, scale 774 px : 57.55 mJy at 2044,2165\n", "Iteration 734, scale 774 px : -45.84 mJy at 2511,1817\n", "Iteration 822, scale 774 px : 48.56 mJy at 2683,1951\n", "Iteration 826, scale 774 px : -41.81 mJy at 2511,1817\n", "Iteration 849, scale 774 px : 44.18 mJy at 2449,1746\n", "Iteration 853, scale 774 px : -40.94 mJy at 2511,1817\n", "Iteration 910, scale 774 px : 45.83 mJy at 2683,1951\n", "Iteration 914, scale 774 px : -37.54 mJy at 2511,1817\n", "Iteration 936, scale 1547 px : -57.37 mJy at 1950,1780\n", "Iteration 941, scale 1547 px : 51.87 mJy at 1568,1706\n", "Iteration 955, scale 1547 px : -40.56 mJy at 1950,1780\n", "Iteration 989, scale 774 px : -52.23 mJy at 1545,1616\n", "Iteration 1000, scale 774 px : 42 mJy at 2103,1409\n", "Cleaning finished because maximum number of iterations was reached.\n", "Maximum number of minor deconvolution iterations was reached: not continuing deconvolution.\n", "Assigning from 1 to 1 channels...\n", "Writing model image...\n", " == Converting model image to visibilities ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Predicting 453390 rows...\n", "Writing...\n", " == Constructing image ==\n", "Opening reordered part 0 spw 0 for scary_sky_band01.ms\n", "Loading data in memory...\n", "Gridding 453390 rows...\n", "Gridded visibility count: 7.25424e+06\n", "3 major iterations were performed.\n", "Rendering sources to restored image (beam=119.53'-119.87', PA=48.03 deg)... DONE\n", "Writing restored image... DONE\n", "Multi-scale cleaning summary:\n", "- Scale 0 px, nr of components cleaned: 0 (0 Jy)\n", "- Scale 387 px, nr of components cleaned: 40 (-7.34 Jy)\n", "- Scale 774 px, nr of components cleaned: 692 (266.19 Jy)\n", "- Scale 1547 px, nr of components cleaned: 268 (277.32 Jy)\n", "Total: 1000 components (536.17 Jy)\n", "Inversion: 00:00:24.659906, prediction: 00:00:11.692319, deconvolution: 00:07:54.554818\n", "Cleaning up temporary files...\n" ] }, { "data": { "text/plain": [ "0" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "command = \"woden_uv2ms.py \"\n", "command += f\" --uvfits_prepend={uvfits_name}_band --band_nums=1\"\n", "call(command, shell=True)\n", "\n", "command = f\"wsclean -name {uvfits_name} -size 4096 4096 -niter 1000 \"\n", "command += \" -auto-threshold 0.5 -auto-mask 3 \"\n", "command += \" -pol I,Q,U,V -multiscale -weight briggs 0 -scale 0.03 -j 12 -mgain 0.85 \"\n", "command += \" -no-update-model-required \" #-join-polarizations\n", "command += f\" {uvfits_name}*.ms\"\n", "\n", "call(command, shell=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can plot the images" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: FITSFixedWarning: 'datfix' made the change 'Set MJD-OBS to 57396.549571 from DATE-OBS'. [astropy.wcs.wcs]\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from astropy.wcs import WCS\n", "\n", "\n", "with fits.open(f'{uvfits_name}-I-image.fits') as hdus:\n", " w = WCS(hdus[0].header)\n", "\n", "fig, axs = plt.subplots(2, 2, figsize=(10, 8), subplot_kw={'projection': w.celestial})\n", "\n", "\n", "names = ['I', 'Q', 'U', 'V']\n", "\n", "files = [f'{uvfits_name}-I-image.fits', f'{uvfits_name}-Q-image.fits',\n", " f'{uvfits_name}-U-image.fits', f'{uvfits_name}-V-image.fits']\n", "\n", "for name, file, ax in zip(names, files, axs.flatten()):\n", " with fits.open(file) as hdus:\n", " data = np.squeeze(hdus[0].data)\n", " \n", " im = ax.imshow(data, origin='lower', cmap='inferno')\n", " ax.set_title(name)\n", " \n", " ax.set_xticks([])\n", " ax.set_yticks([])\n", " \n", " plt.colorbar(im, ax=ax, label='Jy/beam')\n", " \n", " ax.grid(alpha=0.5)\n", " \n", " \n", "plt.tight_layout()\n", "plt.show()\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Great success! We have boring point sources in Stokes I. As we have a constant rotation measure for all directions, and we've only done a 1.28MHz bandwidth, at these frequencies we get a negative Stokes Q and positive Stokes U; both look like the (low-res) Haslam map. The Stokes V is just a bunch of Gaussian blobs." ] } ], "metadata": { "kernelspec": { "display_name": "woden_dev", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 2 }