{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "IA74VDDSef_D" }, "source": [ "\n", "\n", "\n", "# Numerical accuracy of uvcontsub\n", "\n", "This notebook simulates MeasurementSets with known continuum shapes (for example, as polynomials of different order with known coefficients). It has functions to produce MSs including point sources, spectral lines, added noise, and polynomial continuum functions. These MSs can be used to test the numerical accuracy of the task uvcontsub, illustrate its usage and experiment with it under different simulated conditions. \n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "id": "Df3K_XIYf3g2" }, "source": [ "# Preparations. Installs and imports.\n" ] }, { "cell_type": "markdown", "metadata": { "id": "5gFAxq2kiQz0" }, "source": [ "## Install required packages" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "4EMXgMBBfCl5", "outputId": "4417e1c1-dbbe-41c3-a5a7-13e2d20fca82" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Running in colab, Python version 3.7.13 (default, Apr 24 2022, 01:04:09) \n", "[GCC 7.5.0]\n", "installing pre-requisite packages...\n", "installing casatools...\n", " (using Python 3.7 wheel for colab)\n", "installing casatasks...\n", " (using Python 3.7 wheel for colab)\n", "installing casadata...\n" ] } ], "source": [ "import os\n", "if 'google.colab' in str(get_ipython()):\n", " import sys\n", " print(f'Running in colab, Python version {sys.version}')\n", " print(\"installing pre-requisite packages...\")\n", " os.system(\"apt-get install libgfortran3\")\n", " \n", " print(\"installing casatools...\")\n", " print(\" (using Python 3.7 wheel for colab)\")\n", " os.system(\"pip install https://open-bamboo.nrao.edu/browse/CASA-C6B502-15/artifact/shared/casatools-python-3.7/casatools-6.5.2.7a13631.dev13-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl\")\n", " # os.system(\"pip install --extra-index-url --index-url=https://go.nrao.edu/pypi casatasks\")\n", " \n", " print(\"installing casatasks...\")\n", " print(\" (using Python 3.7 wheel for colab)\")\n", " os.system(\"pip install https://open-bamboo.nrao.edu/browse/CASA-C6B502-15/artifact/shared/Task-wheel/casatasks-6.5.2.7a13631.dev13-py3-none-any.whl\")\n", " # os.system(\"pip install --extra-index-url --index-url=https://go.nrao.edu/pypi casatasks\")\n", "\n", " print(\"installing casadata...\")\n", " os.system(\"pip install --extra-index-url --index-url=https://go.nrao.edu/pypi casadata\")\n", "else:\n", " print(\"installing casatasks...\")\n", " os.system(\"pip install --extra-index-url --index-url=https://go.nrao.edu/pypi casatasks\")\n", " print(\"installing casadata...\")\n", " os.system(\"pip install --extra-index-url --index-url=https://go.nrao.edu/pypi casadata\")\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "id": "B47xbRJIiUvS" }, "source": [ "## Import required CASA tasks and tools, and other packages" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "id": "Aj8AJGLrgsAG" }, "outputs": [], "source": [ "from casatools import componentlist, ctsys, measures, simulator, table\n", "from casatasks import flagdata, listobs\n", "from casatasks.private import simutil\n", "import numpy as np\n", "import glob\n", "import os, shutil\n", "\n", "cl = componentlist()\n", "sm = simulator()" ] }, { "cell_type": "markdown", "metadata": { "id": "aexYE59Ei73z" }, "source": [ "# Definition of simulation building blocks\n", "This section defines function to:\n", "* Create a MeasurementSet with basic structure\n", "* Plot visibilities\n", "* Populate and edit the visibilities of an MS (add sources, continuum, noise, etc.)\n", "\n", "Uses functions from https://github.com/urvashirau/Simulation-in-CASA/blob/master/Basic_Simulation_Demo/Simulation_Script_Demo.ipynb, adapted to this set of simulations for uvcontsub." ] }, { "cell_type": "markdown", "metadata": { "id": "zPyD7q_xIHxG" }, "source": [ "## Make MS structure" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "id": "nMfsk4WRiiHj" }, "outputs": [], "source": [ "def make_ms_frame(msname, ant_config, spw_params=None):\n", " \"\"\" \n", " Construct an empty MeasurementSet that has the desired observation setup. \n", "\n", " Args:\n", " msname: MS to create\n", " ant_config: a telescope configuration from casadata (alma/simmos) (for \n", " example alma/simmos/aca.cycle8.cfg)\n", " swp_params: parameters such as SPW name, number of channels, frequency\n", " \"\"\" \n", " ## Open the simulator\n", " sm.open(ms=msname);\n", "\n", " ## Read/create an antenna configuration. \n", " ## Canned antenna config text files are located here: /alma/simmos/*cfg\n", " antennalist = os.path.join(ctsys.resolve(\"alma/simmos\"), ant_config)\n", " verbose = False\n", " if verbose:\n", " print(f'Using antenna list file: {antennalist}')\n", " \n", " ## Fictitious telescopes can be simulated by specifying x, y, z, d, an, telname, antpos.\n", " ## x,y,z are locations in meters in ITRF (Earth centered) coordinates. \n", " ## d, an are lists of antenna diameter and name.\n", " ## telname and obspos are the name and coordinates of the observatory. \n", " mysu = simutil.simutil()\n", " (x,y,z,d,an,an2,telname, obspos) = mysu.readantenna(antennalist)\n", "\n", " ## Set the antenna configuration\n", " metool = measures()\n", " sm.setconfig(telescopename=telname,\n", " x=x,\n", " y=y,\n", " z=z,\n", " dishdiameter=d,\n", " mount=['alt-az'], \n", " antname=an,\n", " coordsystem='local',\n", " referencelocation=metool.observatory(telname));\n", "\n", " ## Set the polarization mode (this goes to the FEED subtable)\n", " sm.setfeed(mode='perfect X Y', pol=['']); # X Y / R L\n", "\n", " ## Set the spectral window and polarization (one data-description-id). \n", " ## Call multiple times with different names for multiple SPWs or pol setups.\n", " sm.setspwindow(spwname=spw_params['name'],\n", " freq=spw_params['freq'],\n", " deltafreq='0.1GHz',\n", " freqresolution='0.2GHz',\n", " nchannels=spw_params['nchan'],\n", " stokes='XX YY');\n", "\n", " ## Setup source/field information (i.e. where the observation phase center is)\n", " ## Call multiple times for different pointings or source locations.\n", " source_name = 'simulated_source'\n", " sm.setfield(sourcename=source_name,\n", " sourcedirection=metool.direction(rf='J2000',\n", " v0='19h59m28.5s',v1='+40d44m01.5s'));\n", "\n", " ## Set shadow/elevation limits (if you care). These set flags.\n", " sm.setlimits(shadowlimit=0.01, elevationlimit='1deg');\n", "\n", " ## Leave autocorrelations out of the MS.\n", " sm.setauto(autocorrwt=0.0); \n", "\n", " ## Set the integration time, and the convention to use for timerange specification\n", " ## Note : It is convenient to pick the hourangle mode as all times specified in sm.observe()\n", " ## will be relative to when the source transits.\n", " sm.settimes(integrationtime='2s',\n", " usehourangle=True,\n", " referencetime=metool.epoch('UTC','2021/10/14/00:01:02'));\n", "\n", " ## Construct MS metadata and UVW values for one scan and ddid \n", " ## Call multiple times for multiple scans.\n", " ## Call this with different sourcenames (fields) and spw/pol settings as defined above.\n", " ## Timesteps will be defined in intervals of 'integrationtime', between starttime and stoptime.\n", " sm.observe(sourcename=source_name,\n", " spwname=spw_params['name'],\n", " starttime='0', \n", " stoptime='+8s');\n", "\n", " ## Close the simulator\n", " sm.close()\n", " \n", " ## Unflag everything (unless you care about elevation/shadow flags)\n", " flagdata(vis=msname, mode='unflag', flagbackup=False)" ] }, { "cell_type": "markdown", "metadata": { "id": "CCG3b_GyQ5R7" }, "source": [ "## Plotting of visibilities and uv coverage" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "id": "17La0uyOdSGX" }, "outputs": [], "source": [ "def plot_ms_data(msname='sim_data.ms', myplot='uv', plot_complex='abs'):\n", " \"\"\"\n", " Options : myplot='uv'\n", " myplot='data_spectrum'\n", " Args:\n", " plot_complex: 'abs', 'real', or 'imag'\n", " \"\"\"\n", " from casatools import table\n", " import pylab as pl\n", " import numpy as np\n", "\n", " tb = table()\n", " from matplotlib.collections import LineCollection\n", " tb.open(msname)\n", "\n", " # UV coverage plot\n", " if myplot=='uv':\n", " pl.figure(figsize=(4,4))\n", " pl.clf()\n", " uvw = tb.getcol('UVW')\n", " pl.plot( uvw[0], uvw[1], '.')\n", " pl.plot( -uvw[0], -uvw[1], '.')\n", " pl.title('UV Coverage')\n", " \n", " # Spectrum of chosen column. Make a linecollection out of each row in the MS.\n", " if myplot=='data_spectrum' or myplot=='corr_spectrum' or myplot=='resdata_spectrum' or myplot=='rescorr_spectrum' or myplot=='model_spectrum':\n", " dats=None\n", " if myplot=='data_spectrum':\n", " dats = tb.getcol('DATA')\n", " if myplot=='corr_spectrum':\n", " dats = tb.getcol('CORRECTED_DATA')\n", " if myplot=='resdata_spectrum':\n", " dats = tb.getcol('DATA') - tb.getcol('MODEL_DATA') \n", " if myplot=='rescorr_spectrum':\n", " dats = tb.getcol('CORRECTED_DATA') - tb.getcol('MODEL_DATA') \n", " if myplot=='model_spectrum':\n", " dats = tb.getcol('MODEL_DATA')\n", " \n", " xs = np.zeros((dats.shape[2],dats.shape[1]),'int')\n", " for chan in range(0,dats.shape[1]):\n", " xs[:,chan] = chan\n", " \n", " npl = dats.shape[0]\n", " fig, ax = pl.subplots(1,npl,figsize=(10,4))\n", " \n", " if plot_complex == 'abs':\n", " complex_func = np.abs\n", " elif plot_complex == 'real':\n", " complex_func = np.real\n", " elif plot_complex == 'imag':\n", " complex_func = np.imag\n", " else:\n", " raise ValueError(f'Invalid plot_complex: {plot_complex}')\n", " \n", " for pol in range(0,dats.shape[0]):\n", " x = xs\n", " y = complex_func(dats[pol,:,:]).T \n", " data = np.stack(( x,y ), axis=2)\n", " ax[pol].add_collection(LineCollection(data))\n", " ax[pol].set_title(myplot + ' \\n pol '+str(pol))\n", " ax[pol].set_xlim(x.min(), x.max())\n", " ax[pol].set_ylim(y.min(), y.max())\n", " pl.show()" ] }, { "cell_type": "markdown", "metadata": { "id": "x-p8It4VIOp0" }, "source": [ "## Update visibilities\n", "Define functions to manipulate visibilities. These functions can be used to introduce noise, point sources, spectral lines, and polynomial-shaped continuum, into MSs in an additive way. The main functions defined here that will be used in the following sections are:\n", "\n", "* add_ms_gaussian_noise: use the simulator 'simplenoise' mode to add random Gaussian noise\n", "* add_point_source_component: adds a point source that can be flat or spectral index\n", "* add_spectral_line: adds a simulated line (with Gaussian shape) to the visibilities (real part)\n", "* add_polynomial_cont: adds continuum defined as polynomial of a given order and known coefficients. The polynomials are added to both the real and imaginary parts of the visibilities, for verification testing.\n", "\n" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "id": "03b9RDLHLaMg" }, "outputs": [], "source": [ "def add_ms_gaussian_noise(ms_name, noise_level_sigma='0.1Jy'):\n", " \"\"\"\n", " Adds Gaussian random noise using simulator / corrupt\n", " \n", " Args:\n", " ms_name: MS to modify\n", " noise_level_sigma: noise sigma as used in the simulator corrupt function\n", " \"\"\"\n", " try:\n", " sm.openfromms(ms_name)\n", " sm.setseed(4321)\n", " sm.setnoise(mode='simplenoise', simplenoise=noise_level_sigma)\n", " sm.corrupt()\n", " finally:\n", " sm.close()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "id": "__KFp_JJ03OV" }, "outputs": [], "source": [ "def make_point_source_comp_list(cl_name, freq, flux, spectrumtype, index):\n", " \"\"\"\n", " Makes a component list file with a point source\n", " \n", " Args:\n", " cl_name: name of the component list file to create\n", " freq: freq quantity (with units) as used in the component list tool \n", " flux: flux, units are assumed in Jy\n", " spectrumtype: as used in component list tool: constant/spectral index\n", " index: spectral index\n", " \"\"\"\n", " try:\n", " cl.addcomponent(dir='J2000 19h59m28.5s +40d44m01.5s', \n", " flux=flux,\n", " fluxunit='Jy', \n", " freq=freq,\n", " shape='point', # shape='gaussian',\n", " # majoraxis=\"5.0arcmin\", minoraxis='2.0arcmin',\n", " # polarization='linear', / 'Stokes'\n", " # spectrumtype:'spectral index' / 'constant'\n", " spectrumtype=spectrumtype,\n", " index=index,\n", " label='sim_point_source')\n", " cl.rename(filename=cl_name)\n", " finally:\n", " cl.close()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "id": "-jHQyuHY05jz" }, "outputs": [], "source": [ "def sim_from_comp_list(ms_name, cl_name):\n", " \"\"\"\n", " Updates the MS visibilities using simulator.predict to add\n", " components from the components list\n", "\n", " Args:\n", " ms_name: MS to modify\n", " cl_name: name of components list file to simulate\n", " \"\"\"\n", " try:\n", " sm.openfromms(ms_name)\n", " sm.predict(complist=cl_name, incremental=False)\n", " finally:\n", " sm.close()" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "id": "l1ocsptzO0Mx" }, "outputs": [], "source": [ "def add_point_source_component(ms_name, freq=None, flux=5.0, \n", " spectrumtype='constant', index=-1):\n", " \"\"\"\n", " Adds a point source to the MS\n", " \n", " Args:\n", " ms_name: MS to modify\n", " freq: \n", " spectrumtype:\n", " flux: In Jy, as used in componentlist.addcomponent\n", " \"\"\"\n", " cl_name = 'sim_point_source.cl'\n", " make_point_source_comp_list(cl_name=cl_name, freq=freq, flux=flux, \n", " spectrumtype=spectrumtype, index=index)\n", " sim_from_comp_list(ms_name, cl_name)\n", " shutil.rmtree(cl_name)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "id": "_zlKaBMjrucO" }, "outputs": [], "source": [ "def add_spectral_line(ms_name, chan_range=[60,86], amp_factor=None):\n", " \"\"\"Adds a spectral line as a Gaussian function in the range \n", " of channels given\n", " \n", " Args:\n", " ms_name: MS to modify\n", " chan_range: list with indices of the first and last channel\n", " amp_factor: factor to multiply the peak height / flux density\n", " \"\"\"\n", " try:\n", " tbtool = table()\n", " tbtool.open(ms_name, nomodify=False)\n", " data = tbtool.getcol('DATA')\n", "\n", " def gauss(x, mu, sigma):\n", " return np.exp(-np.power(x - mu, 2.) / (2 * np.power(sigma, 2.)))\n", " x = np.linspace(-3, 3, chan_range[1]-chan_range[0])\n", " bell_line = gauss(x, 0, 0.58)\n", "\n", " ## Add same gaussian to real and imag part\n", " # data has indices pol:chan:time\n", " if not amp_factor:\n", " amp_factor = 1.0/np.max(bell_line)\n", " data[:,chan_range[0]:chan_range[1],:] +=\\\n", " amp_factor * (1+0j) * bell_line.reshape((1, len(bell_line),1))\n", "\n", " tbtool.putcol('DATA', data)\n", " finally:\n", " tbtool.done()" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "id": "7zeS73pRVdjl" }, "outputs": [], "source": [ "def add_polynomial_cont(ms_name, pol_coeff, nchan, amp_factor=1.0):\n", " \"\"\"\n", " Update MS visibilities adding a polynomial evaluated for all channels.\n", "\n", " Args:\n", " ms_name: MS to modify\n", " pol_coeff: polynomial coefficients, evaluated [0.5, 0.25] => 0.5x + 0.25\n", " nchan: number of channels in the SPW (x axis to eval polynomial)\n", " \"\"\"\n", " try:\n", " tbtool = table()\n", " tbtool.open(ms_name, nomodify=False)\n", " data = tbtool.getcol('DATA')\n", "\n", " x = np.linspace(0, 1, nchan)\n", " polynomial = np.polyval(pol_coeff, x)\n", " # Add same polynomial to real and imag part\n", " data += amp_factor * (1+1j) * polynomial.reshape((1, len(polynomial),1))\n", "\n", " tbtool.putcol('DATA', data)\n", " finally:\n", " tbtool.done()" ] }, { "cell_type": "markdown", "metadata": { "id": "uv7isCSzmjI9" }, "source": [ "# Produce simulated MeasurementSets - for task verfication test" ] }, { "cell_type": "markdown", "source": [ "Produce simulated MeasurementSets that are used in the uvcontsub task verification test.\n", "These simulations produce MSs that include:\n", "* a constant spectrum source, with flux density 0.5Jy by default\n", "* a line of with approximately 20% of the SPW, with peak flux density 1Jy\n", "* various polynomials of order 0, 1, 2, etc., \n", "* noise with sigma 0.1Jy. \n", "\n", "The polynomials are added to the real an imaginary parts of the visibilities for all channels. The accuracy in fitting these polynomials is then tested in the verification test of uvcontsub. More details and discussion can be found in [CAS-13632](https://open-jira.nrao.edu/browse/CAS-13632).\n", "\n", "The list of verification tests of uvcontsub is detailed here, including the tests of numerical accuracy that use the MSs simulated in this notebook: https://open-confluence.nrao.edu/display/CASA/uvcontsub2021\n", "For further details, the tests implemented in the uvcontsub can be seen here: https://open-bitbucket.nrao.edu/projects/CASA/repos/casa6/browse/casatasks/tests/tasks/test_task_uvcontsub.py?at=refs%2Fheads%2FCAS-13631 (note: link to the current development branch, should be updated once the branch is merged)." ], "metadata": { "id": "G-MbCLievcha" } }, { "cell_type": "code", "execution_count": 33, "metadata": { "id": "ZjJUjicTmii3" }, "outputs": [], "source": [ "def make_test_ms_alma_verif(ms_name, noise_sigma='0.1Jy', pol_coeffs=[0.5], \n", " verbose=True):\n", " \"\"\"\n", " Adds a point source, a spectral line, noise, and a continuum as a polynomial\n", "\n", " Args:\n", " noise_sigma: sigma for the Gaussian noise, set to None for no noise\n", " pol_coeffs: coefficients of the cont polynomial, ordered from higher to \n", " lower order\n", " verbose: print and plot what is being done\n", " \"\"\"\n", " ant_config = 'alma.cycle8.8.cfg'\n", " spw_params = {'name': \"Simulated_Band\",\n", " 'freq': '150GHz',\n", " 'nchan': 128}\n", "\n", " make_ms_frame(ms_name, ant_config=ant_config, spw_params=spw_params)\n", "\n", " add_point_source_component(ms_name, freq='100GHz', flux=0.5,\n", " spectrumtype='constant')\n", " if verbose:\n", " print('Data plots. Only point source:')\n", " plot_ms_data(ms_name, 'data_spectrum')\n", "\n", " add_spectral_line(ms_name, chan_range=[60,86])\n", " if verbose:\n", " print('Data plots, + spectral line, width ~20% band:')\n", " plot_ms_data(ms_name, 'data_spectrum')\n", "\n", " # polynomial order 0,1,2,3 around 0.5Jy\n", " add_polynomial_cont(ms_name, pol_coeffs, spw_params['nchan']) \n", " if verbose:\n", " print('Data plots + polynomial cont:')\n", " plot_ms_data(ms_name, 'data_spectrum')\n", "\n", " if noise_sigma:\n", " add_ms_gaussian_noise(ms_name, noise_sigma)\n", " if verbose:\n", " print('Data plots + Gaussian noise:')\n", " plot_ms_data(ms_name, 'data_spectrum')" ] }, { "cell_type": "markdown", "metadata": { "id": "ubHeh12bzISj" }, "source": [ "## Simple MS with continuum, line, and noise, plotted step by step\n", "\n", "Using order 0 continuum.\n", "\n", "The structure of this MS is the one used at the moment in the task test (test_task_req_uvcontsub). nchan=128. The spectral line is added to channels 60-85.\n", "The value of the fitspec parameter for this MS structure would be '0:0\\~59;86\\~127'" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "3oyAu-C-pI8l", "outputId": "00e5055f-5de9-4503-ba31-daddd4f681d6" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Data plots. Only point source:\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:62: UserWarning: Attempting to set identical bottom == top == 0.5 results in singular transformations; automatically expanding.\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "Data plots, + spectral line, width ~20% band:\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "Data plots + polynomial cont:\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "Data plots + Gaussian noise:\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "os.system('rm -rf example_sim_alma_*.ms sim_alma_*.ms')\n", "\n", "ms_name = 'example_sim_alma_noise_cont_poly_order_0.ms'\n", "make_test_ms_alma_verif(ms_name, pol_coeffs=[0.05], verbose=True)\n" ] }, { "cell_type": "markdown", "metadata": { "id": "gs1_lUbYEPcD" }, "source": [ "## More simple examples of test MSs" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 313 }, "id": "zYL5Yo7RzOG6", "outputId": "3933ee33-35da-4f94-b644-85e98c23e1d3" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Plotting no-noise MS, with continuum as polynomial order 1\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "# Still make a trivial order 0 without noise, for the most basic verif test\n", "ms_name = 'example_sim_alma_nonoise_cont_poly_order_0.ms'\n", "make_test_ms_alma_verif(ms_name, pol_coeffs=[0.5], noise_sigma=None, verbose=False)\n", "\n", "ms_name = 'example_sim_alma_nonoise_cont_poly_order_1.ms'\n", "make_test_ms_alma_verif(ms_name, pol_coeffs=[-0.1, 0.75], noise_sigma=None, verbose=False)\n", "print('Plotting no-noise MS, with continuum as polynomial order 1')\n", "plot_ms_data(ms_name, 'data_spectrum')" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "g8x4evqodZPm", "outputId": "152359b1-914f-4d6a-82fc-f9068facd3fc" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "35M\texample_sim_alma_noise_cont_poly_order_0.ms\n", "35M\texample_sim_alma_nonoise_cont_poly_order_0.ms\n", "35M\texample_sim_alma_nonoise_cont_poly_order_1.ms\n", "12M\tuvcont_noise_sub_0.ms\n", "12M\tuvcont_noise_sub_1.ms\n", "12M\tuvcont_noise_sub_2.ms\n", "12M\tuvcont_noise_sub_3.ms\n", "12M\tuvcont_nonoise_sub_1.ms\n", "162M\ttotal\n" ] } ], "source": [ "!du -hsc *.ms" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Ptw3qQ-z7msd", "outputId": "f89e5e75-3718-44d7-e39d-2992ec62a513" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "{'BeginTime': 59500.802114409686,\n", " 'EndTime': 59500.80220700228,\n", " 'IntegrationTime': 8.0,\n", " 'field_0': {'code': '',\n", " 'direction': {'m0': {'unit': 'rad', 'value': -1.0494882958398402},\n", " 'm1': {'unit': 'rad', 'value': 0.7109380541842404},\n", " 'refer': 'J2000',\n", " 'type': 'direction'},\n", " 'name': 'simulated_source'},\n", " 'nfields': 1,\n", " 'numrecords': 3612,\n", " 'scan_1': {'0': {'BeginTime': 59500.802114409686,\n", " 'EndTime': 59500.80220700228,\n", " 'FieldId': 0,\n", " 'FieldName': 'simulated_source',\n", " 'IntegrationTime': 2.0,\n", " 'SpwIds': array([0]),\n", " 'StateId': 0,\n", " 'nRow': 3612,\n", " 'scanId': 1}},\n", " 'timeref': 'UTC'}\n", "{'BeginTime': 59500.802114409686, 'EndTime': 59500.80220700228, 'IntegrationTime': 8.0, 'field_0': {'code': '', 'direction': {'m0': {'unit': 'rad', 'value': -1.0494882958398402}, 'm1': {'unit': 'rad', 'value': 0.7109380541842404}, 'refer': 'J2000', 'type': 'direction'}, 'name': 'simulated_source'}, 'nfields': 1, 'numrecords': 3612, 'scan_1': {'0': {'BeginTime': 59500.802114409686, 'EndTime': 59500.80220700228, 'FieldId': 0, 'FieldName': 'simulated_source', 'IntegrationTime': 2.0, 'SpwIds': array([0]), 'StateId': 0, 'nRow': 3612, 'scanId': 1}}, 'timeref': 'UTC'}\n" ] } ], "source": [ "from casatasks import listobs\n", "res = listobs(vis=ms_name)\n", "import pprint\n", "pprint.pprint(res)\n", "print(res)" ] }, { "cell_type": "markdown", "metadata": { "id": "ZBJU4xIydSvH" }, "source": [ "## MeasurementSets with continuum polynomials of order 0, 1, 2, 3, etc." ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "6FnwsU1mlZvk", "outputId": "5d1edf75-8edc-4b3f-f855-24f34231d523" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Plotting polynomial order 0:\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "Plotting polynomial order 1:\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "Plotting polynomial order 2:\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "Plotting polynomial order 3:\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "# Giving coefficients as [0.1, 0.45] == 0.1x + 0.45\n", "polynomials = {0: [0.025],\n", " 1: [-0.1, 0.75],\n", " 2: [-1, 1, 0.15],\n", " 3: [1, -0.75, -0.25, 0.15]\n", " # Order 3 could also be of the style (not sure what type we'd \n", " # want): \n", " # [-1.35, 0, 1.5, 0.2]\n", "}\n", "for order, poly in polynomials.items():\n", " ms_name = f'sim_alma_cont_poly_order_{order}_nonoise.ms'\n", " os.system('rm -rf sim_*.cl')\n", " make_test_ms_alma_verif(ms_name, pol_coeffs=poly, noise_sigma=None, verbose=False)\n", "\n", " ms_name = f'sim_alma_cont_poly_order_{order}_noise.ms'\n", " os.system('rm -rf sim_*.cl')\n", " make_test_ms_alma_verif(ms_name, pol_coeffs=poly, verbose=False)\n", " print(f'Plotting polynomial order {order}:')\n", " plot_ms_data(ms_name, 'data_spectrum')" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "5gJFJ6tIivPG", "outputId": "97cdbc0c-1f38-491f-8508-9b257ad887fb" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "35M\texample_sim_alma_noise_cont_poly_order_0.ms\n", "35M\texample_sim_alma_nonoise_cont_poly_order_0.ms\n", "35M\texample_sim_alma_nonoise_cont_poly_order_1.ms\n", "35M\tsim_alma_cont_poly_order_0_noise.ms\n", "35M\tsim_alma_cont_poly_order_0_nonoise.ms\n", "35M\tsim_alma_cont_poly_order_1_noise.ms\n", "35M\tsim_alma_cont_poly_order_1_nonoise.ms\n", "35M\tsim_alma_cont_poly_order_2_noise.ms\n", "35M\tsim_alma_cont_poly_order_2_nonoise.ms\n", "35M\tsim_alma_cont_poly_order_3_noise.ms\n", "35M\tsim_alma_cont_poly_order_3_nonoise.ms\n", "12M\tuvcont_noise_sub_0.ms\n", "12M\tuvcont_noise_sub_1.ms\n", "12M\tuvcont_noise_sub_2.ms\n", "12M\tuvcont_noise_sub_3.ms\n", "12M\tuvcont_nonoise_sub_1.ms\n", "440M\ttotal\n" ] } ], "source": [ "# Check all MSs are there and their sizes\n", "!du -hsc *.ms" ] }, { "cell_type": "markdown", "source": [ "## Noise level in the line free channels before and after continuum subtraction\n", "\n", "When applying continuum subtraction, the output RMS increases with respect to the input RMS by a factor of \n", "\n", "$\\mathrm{sqrt}(1+1/N_c)),$\n", "\n", "where $N_c$ is the number of channels for which the continuum has been fitted. In the simple MeasurementSet examples above, where fitspec='0:0\\~59;86\\~127', $N_c = 102$ (from the 128 channels, there are 60 (left) + 42 (right) line free channels and 26 line channels.\n", "\n", "The output residual continuum flux deviates from 0 following a standard deviation of \n", "\n", "$N_l s (1 + N_l / N_c)$, \n", "\n", "where $N_l$ is the number of line channels (26 in the simple simulations above) and $s$ is the sigma of the added artificial Gaussian noise." ], "metadata": { "id": "fwMovMpq5o32" } }, { "cell_type": "markdown", "source": [ "### Output RMS\n", "\n", "Since a fit can never be noise free the output will always have more noise, although for a good fit this extra noise would probably be close to negligible when the number of channels to fit is sufficiently large.\n", "\n", "In the case in which the simulation is a flat continuum (polynomial of order 0) with known artificial Gaussian noise of sigma $s$, fitting a 0-order polynomial is numerically equivalent to compute the average across all the $N_c$ channels ($x_c$). The [standard error of that average](https://en.wikipedia.org/wiki/Standard_error#Standard_error_of_the_mean) is then $s/\\sqrt{N_c}$ and the variance $s^2/N_c$. For a given visibility value in a channel ($x_i$), the value with continuum subtracted ($x_i - x_c$) has a variance of\n", "\n", "$var(x_i) + var(x_{mean}) = s^2 + s^2/N_c = s^2 (1+1/N_c)$.\n", "\n", "In other words, the variance of the output has been increased by a factor ($1+1/N_c)$ (or the RMS by a factor of $\\sqrt{1+1/N_c}$). For the simulations above, where $N_c = 102$ line-free channels than means a factor $~1.005$. Note that this factor depends only on the number of line-free channels and is independent of the absolute values of the visibilities or the added noise." ], "metadata": { "id": "VUvGx99-7xpP" } }, { "cell_type": "markdown", "source": [ "### Output residual continuum flux\n", "\n", "Assuming a simulated line profile $P_i$ with and additional continuum with a Gaussian distribution of mean $C$ and sigma $s$, each channel in the input spectrum is a statistical variable with a mean of $P_i + C$ and a standard deviation of $s$. Or in statistical notation:\n", "\n", "$x_i \\sim N(P_i + C, s),$ \n", "\n", "where $N(m,s)$ denotes the normal distribution with mean $m$ and sigma $s$.\n", "\n", "The integrated flux ($F$) computed on the output spectrum is the sum over $N_l$ channels and is also a statistical variable that is the sum of several $x_i$ minus the estimated continuum $x_c$ that is itself a statistical variable:\n", "\n", "$x_c \\sim N(C, \\sqrt{(s^2/N_c})$\n", "\n", "$F \\sim N(\\sum P_i + (N_l C -N_l C), \\sqrt{N_l s^2 + N_l s^2 / N_c} ),$\n", "\n", "where $\\sum P_i$ is the summation of the profile over the $N_l$ channels of the line.\n", "\n", "\n", "The integrated flux minus the theoretical flux ($\\sum P_i$) is also a statistical variable:\n", "\n", "$F - F_{theor} \\sim N(0, \\sqrt{N_l s^2 + N_l s^2 / N_c} ).$\n", "\n", "Or in other words: the measured flux in the output spectrum minus the theoretical flux follows a normal distribution that will have a mean of 0 and a standard deviation of $\\sqrt{N_l s^2 + N_l s^2 / N_c}$, or a variance of $N_l s (1 + N_l / N_c)$.\n", "\n", "The interesting point is that, for this model, the residual continuum flux is independent of the line flux, and it will deviate from 0 following a standard deviation of $N_l s (1 + N_l / N_c)$. \n", "\n", "Note that the analysis would be different if one assumes different models in which the flux of the line contributes to the noise, like a Poisson distribution. In this model it is assumed that the noise is constant and independent of the visibility value." ], "metadata": { "id": "zdFOwuJa_OWs" } }, { "cell_type": "markdown", "metadata": { "id": "VIVJuDY_8NLz" }, "source": [ "# Continuum subtraction with uvcontsub\n", "\n", "Several example commands to illustrate how uvcontsub is applied to the simulated MSs." ] }, { "cell_type": "markdown", "source": [ "## Using MeasurementSets for task verification test" ], "metadata": { "id": "7xNUxUYJ0d5V" } }, { "cell_type": "code", "execution_count": 45, "metadata": { "id": "lAMCxb2bLTMw" }, "outputs": [], "source": [ "# Copy files to drive if needed to work with them outside of colab\n", "copy_files = False\n", "if 'google.colab' in str(get_ipython()) and copy_files:\n", " from google.colab import drive\n", " #drive.mount('/content/drive')\n", " !cp -r sim_*.ms /content/drive/MyDrive/sim_ms" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "mtU0YsUk8RxE", "outputId": "5e8c8071-87cb-4434-cc53-b9370a5a0d5a" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "{'description': 'summary of data fitting results in uv-continuum subtraction', 'goodness_of_fit': {'field': {'0': {'scan': {'1': {'spw': {'0': {'polarization': {'0': {'chi_squared': {'average': {'imag': 1.0526342391967773, 'real': 0.9639652371406555}, 'max': {'imag': 1.1145819425582886, 'real': 1.0763975381851196}, 'min': {'imag': 1.081458568572998, 'real': 0.7475039958953857}}, 'count': 4}, '1': {'chi_squared': {'average': {'imag': 1.047758936882019, 'real': 1.035971760749817}, 'max': {'imag': 1.0653717517852783, 'real': 1.148736834526062}, 'min': {'imag': 0.9923614263534546, 'real': 0.9539858102798462}}, 'count': 4}}}}}}}}}}\n", "uv-cont result, polynomial order 0\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "uv-cont result (no noise), polynomial order 1\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "uv-cont result, polynomial order 1\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlMAAAEXCAYAAACJYMEPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3dd5gkV3k2/PuZsLM5r6RNCsAiJARCWMbwYV6DASPJRnoNGEtkE3QZkOE12CDAiGwjG0SQhIKVERIKSLDKaaVdSRu0s6vNYXZ2Z2cn5+mc+3x/VJ3q7poO1dPd01Uz9++69trpruru01XVTz11zqlzRCkFIiIiIpqchnoXgIiIiMjLmEwRERERVYDJFBEREVEFmEwRERERVYDJFBEREVEFmEwRERERVYDJ1DQiIneIyI/rXQ4ionIxfpGXMZmaoUTkBRH5fL3LUS4GXCJi/CK3YTJF04qINNW7DEREk8H45V1MpjxMRM4TkZ0iEhCR+wDMzlq2REQeFZEhERkz/15jLvsJgHcBuE5EgiJynfn8r0SkS0T8IrJDRN7loAxvE5FW8zUDInKN+fzpIqJE5HIR6RWRPhH5t6zXNYjIlSJyVERGROR+EVmatfwvRWSziIybZfqMiFwO4OMAvmGW+xFz3eMi8k0R2QMgJCJN5me/Luv9rCtCEXm3iHSLyDdEZNAs2/8VkYtEpE1ERkXk25XsGyIqjvGL8WtaUUrxnwf/AZgFoBPAvwJoBvARAAkAPzaXLwPwYQBzASwA8ACAP2a9/gUAn7e95yfM1zUB+DqAfgCzS5RjC4BPmn/PB/B28+/TASgA9wKYB+BNAIYAvM9c/lUAWwGsAdAC4CYA95rLTgMQAHCZ+d2WAXiLuewO/R2zynAcwC4AawHMMZ9TAF6XtY71OgDvBpAEcJX5/l8wy3aPua3eCCAC4Ix672f+47/p+I/xK6cMjF/T4B9rprzr7TB+SL9USiWUUg8C2K4XKqVGlFJ/UEqFlVIBAD8B8FfF3lApdbf5uqRS6ucwgsSZJcqRAPA6EVmulAoqpbbalv9AKRVSSu0FcDuMAAMA/wzgO0qpbqVUDMD3AXzErOb+GIBnlVL3mt9tRCm1q0Q5fq2U6lJKRUqsl13unyilEgB+D2A5gF8ppQJKqf0ADgA41+F7EVF5GL9yMX55HJMp71oFoEcplT1Tdaf+Q0TmishNItIpIn4AmwAsFpHGQm8oIv8mIgdFxCci4wAWwfiRFvM5AK8HcEhEtovI39mWd9nKt8r8+zQAD5vV4OMADgJIATgZxhXa0RKfa9dVepUcI0qplPm3DmADWcsjMK5Uiaj6GL8Kf44TjF8uw2TKu/oArBYRyXru1Ky/vw7jquwvlFILAfwf83m9fnYQg9m/4BsAPgpgiVJqMQBf1vp5KaWOKKUuA3ASgKsBPCgi87JWWWsrX6/5dxeAC5VSi7P+zVZK9ZjLXlvoIx0+H4bRRKCdUux7ENGUYvwq/jzjl8cwmfKuLTDazb8iIs0i8iEAb8tavgDG1cm42THye7bXDwB4jW39JIy29yYRuQrAwlKFEJFPiMgKpVQawLj5dDprle+aV5lvBPBPAO4zn78RwE9E5DTzfVaIyCXmst8BeJ+IfNTsjLlMRN5SoNyF7ALwMRFpFJELUKKJgIimFONXcYxfHsNkyqOUUnEAHwLwGQCjAP4RwENZq/wSwBwAwzA6Sj5pe4tfwWjjHxORXwN4ylynDUZ1dhTOqp4vALBfRILme15qa/ffCKAdwHMAfqaUejrr89cDeFpEAmYZ/8L8bicAXATj6nQURmDR7f+3AjjbrF7/Y5FyfRXAB2EEyI8DKLYuEU0hxi/Gr+lGcpusiapDRE4H0AGgWSmVrG9piIicY/yicrFmioiIiKgCTKaoJBF5whxkzv6PA8MRkasxftFUYDMfERERUQVYM0VERERUASZTVDeSmf+Kk3sSkecwhpHGZIpcS0SWisjDIhIyR0L+WL3LRETklIhcIcZEyjERuaPe5aHaYTZNbnY9gDiMKRreAuAxEdltzj1FROR2vQB+DOADMMbNommKNVNUMbOa+ysickxEhkXkf0SkwVzWICL/YdYsDYrIXSKyyMF7zoMxa/x3zQlIX4IxSN4na/ttiGimqUUMAwCl1ENKqT8CGKnpF6C6YzJF1fL3AM4H8FYAlwD4rPn8Z8x/74ExjcJ8ANc5eL/XA0gqpdqyntsN4I3VKS4RUY5qxzCaQZhMUbVcrZQaNadS+CWAy8znPw7gGqXUMaVUEMC3AFzqoMPmfAB+23M+GHNwERFVW7VjGM0gTKaoWrLnweoEsMr8e5X5OHtZE4x+UMUEMXGi0oUAAhWUkYiokGrHMJpBmExRtazN+vtUGB0vYf5/mm1ZEsbs6cW0wZj9fV3Wc+cCYOdzIqqFascwmkGYTFG1/LuILBGRtTBmPL/PfP5eAP8qImeIyHwA/wngvlKThyqlQjBmkf+hiMwTkXfC6Mfw29p9BSKawaoawwBARJpEZDaARgCNIjKbzYPTE5MpqpY/AdgBYBeAxwDcaj5/G4wEaBOMWdijAP7F4Xt+CcbtxIMwAtoXOSwCEdVILWLYfwCIALgSwCfMv/+jekUmt+DcfFQxEVEA1iml2utdFiKicjGGUaVYM0VERERUASZTRERERBVgMx8RERFRBVgzRURERFSBut2iuXz5cnX66afX6+PJwzqGQxAApy+fV++iUJl27NgxrJRaUe9yVANjGE3GWDiO7rEIzjxlAWY1sj7DS4rFr7olU6effjpaW1vr9fHkYZdc9xIaGwQPfemd9S4KlUlEOkuv5Q2MYTQZN7zQjqufPIzrP/c2vGvdtLiumDGKxS+mxeQ5sWQaiRT7+hGR9+zqGgcA7O/11bkkVE0ciZU8J55Mg/dNEJEXBWPGwOnHh8N1LglVE5Mp8pxYMg3mUkTkRdFEGgDQPRapc0momphMkecEogk0seMmEXlQLJECAPSOM5maTphMkecEYkkIgHtfOYFGEXz0z9eWfA0RkRvEkkbNVJ8vCqUURKTOJaJqYDJFnqMUoAD85+MH0dTAZIqIvCNuJlORRApj4QSWzptV5xJRNbCthDwrlkwjnkrXuxhERI5lx6zOkVAdS0LVxGSKPCWZFYgSyTRiCSZTROQdumYKANbv6q1jSaiamEyRp2Rf1SkAqTTv6yMi78iOYbdvPo5+HzuiTwdMpshT7DVRTKWIyEvC5jhTDWa/865RJlPTAZMp8hT2kSIiL9OV6WL+HzGHSiBvYzJFnpLd34CIyGus2nSzZmo0FKtXUaiKmEyRp8SYTBGRR6msebB0DdVAIFqn0lA1MZkiT2HNFBF5VfbFoE6rhvysmZoOmEyRp8SS7F9ARN4UiU+MXwd6fXUoCVUbkynylHzjSnF4BCLygnCezuasmZoemEyRpwRiiQnPJXiHHxF5QL6aKV80WYeSULUxmSJPGQ/HJzwXzROgiIjcJl8yFYhOjGnkPUymyFPGwxNrpnzRic8REblNOD6xFirGiqlpgckUeUq+xGk4yD4HROR++fpMsZPC9MBkijzFl6dmqm88XIeSEBGVJ18zH00PTKbIU0by1EL1+TjoHRG5H5Op6YvJFHnKSGhiZ82uMdZMEZH7hdhBatpiMkWekq8D+pH+YB1KQkRUngCTqWmLyRR5ij9PB/Tjw0ymiMj9ggXGlLr++facefvIe5hMkafkC0YjeWqriIjcJpRnaAQA+J+nDqPfz76fXlYymRKR20RkUET2FVj+cRHZIyJ7RWSziJxb/WISGaJ5bi1mn04qhjGM3CJYpJkvmWLNlJc5qZm6A8AFRZZ3APgrpdSbAPwIwM1VKBdRXnmm5gMAVpFTMXeAMYxcIFRk6pg4p8XytJLJlFJqE4DRIss3K6XGzIdbAaypUtmIcvzX4wcLLusei0xhSchLGMPILYp1QOcco95W7T5TnwPwRKGFInK5iLSKSOvQ0FCVP5qmu3tfOVFw2b4e3xSWhKYxxjCqiWgihcEi/aLYzOdtVUumROQ9MALRNwuto5S6WSl1vlLq/BUrVlTro2mGiCcLX7nt62UyRZVhDKNaenxvH9qHQgWXs5nP26qSTInImwHcAuASpdRINd6TyC5dpF/U0/v7p7AkNN0whlGtFet8DuQfQ4+8o+JkSkROBfAQgE8qpdoqLxJRfqkiydTx4cJXfETFMIbRVChWsw4AvsjE2R3IO5pKrSAi9wJ4N4DlItIN4HsAmgFAKXUjgKsALAPwGxEBgKRS6vxaFZhmrmK14IXu8iNiDCM3SJToE9U9ymmxvKxkMqWUuqzE8s8D+HzVSkREVEWMYeQG8WTxAfHaBwNTVBKqBY6ATkREVGOHB4onSwOB2BSVhGqByRQREVGNtfUVv+N42M8+U17GZIqIiKjG+gPFk6VggXn7yBuYTJEnpNIc0I6IvCtSYhLRCJMpT2MyRZ5Q6rZiIiI3KzXAOSds9zYmU+QJTKaIaDpLpZlNeRmTKfKEULz06MBpNgUSkUclmEt5GpMp8gQnUy1EGY2IyKN4KehtTKbIE4b8pcdgKTX3FRERUS0wmSJP6PdHSq4TiHKiUCIimnpMpsgTBvzRkuuMc6JQIiKqAyZT5AnDDqZaGOJ0DEREVAdMpsgT+oMOkikHtVdERETVxmSKPGHUQa1Tr4/JFBERTT0mU+QJow5qpvp9pTupExERVRuTKfKEYKL0COgDDoZPICIiqjYmU+QJoWjpO/WG2WeKiIjqgMkUeYKT8TjHIhxnioiIph6TKfKEpIO5FoJRjoBORERTj8kUTRsRTs1HRER1wGSKiIiIqAJMpoiIiGoomSp9NzJ5W8lkSkRuE5FBEdlXYLmIyK9FpF1E9ojIW6tfTCKiyWEMo3oLObmDhjzNSc3UHQAuKLL8QgDrzH+XA7ih8mIREVXNHWAMozoZDETxi2fb6l0MqrGSyZRSahOA0SKrXALgLmXYCmCxiKysVgGJiCrBGEb19NzBQdyxubPexaAaq0afqdUAurIed5vPTSAil4tIq4i0Dg0NVeGjiYgqxhhGNZNMOxjXhTxvSjugK6VuVkqdr5Q6f8WKFVP50UREFWMMo3Kl2Pl8RqhGMtUDYG3W4zXmc0REXsAYRjXDmqmZoRrJ1HoAnzLviHk7AJ9Sqq8K70tENBUYw6hmUmUkU0ox8fKqplIriMi9AN4NYLmIdAP4HoBmAFBK3QjgcQAXAWgHEAbwT7UqLBFRuRjDqJ7KqZlKphWaG6WGpaFaKZlMKaUuK7FcAfhy1UpERFRFjGFUT+XUTP386TZ884IzIcKEyms4AjpNK6wmJyI3Kadm6saNRzHgj9WwNFQrTKZoWokmeOcMEblHIlleTErw7j9PYjJFrvfkPud9gQPRRA1LQkRUnrbBQFnr8+4/b2IyRa53w8ajjtf1M5kiIhfxR8qLSZwU2ZuYTJHrReIpx+v6IpxQlIjcY8AfLWv93vFIjUpCtcRkilyvnODii8RrWBIiovKMh8urmeovM/kid2AyRa4XijmvmRoJMpkiIvdIpMrrA1VOTTy5B5Mpcr1yQtHdWzk7OxG5R0qV1wfKV2YfK3IHJlM0rfSwvwERuUi6zP7kY2HWrnsRkymaVoIxdkAnIvdIlzmQcJjNfJ7EZIqmFQ7aSURuUu6wUeUOpUDuwGSKiIjIJXg3nzcxmSIiInIJP/tMeRKTKXI1jgZMRDPJSIgTHXsRkylytXLHaCEi8rJAlBeQXsRkilwtluCdLUQ0czCV8iYmU+RqId4mTERELsdkilzNFy2/M6Yqc1wXIiKiSjCZIlcbDZSfTMWTrCgnIqKpw2SKXG0oUP6dLQGOgk5ERFOIyRS52ki4/GRqcDxcg5IQERHlx2SKXG1grPyJiw8NBGpQEiIiovwcJVMicoGIHBaRdhG5Ms/yU0XkeRF5VUT2iMhF1S8qzURdk6hlOtDHZIoyGL+IqNZKJlMi0gjgegAXAjgbwGUicrZttf8AcL9S6jwAlwL4TbULSjNTn7/8Zr4jA74alIS8iPGLiKaCk5qptwFoV0odU0rFAfwewCW2dRSAhebfiwD0Vq+INJONhcq/m69njNMxkIXxi4hqzkkytRpAV9bjbvO5bN8H8AkR6QbwOIB/yfdGInK5iLSKSOvQ0NAkikszjT+aKPs1I5wolDKqFr8AxjAiyq9aHdAvA3CHUmoNgIsA/FZEJry3UupmpdT5SqnzV6xYUaWPpuksPIkR0CMcNZ3K4yh+AYxhVB5O1D5zOEmmegCszXq8xnwu2+cA3A8ASqktAGYDWF6NAtLMNpm8KM7JkSmD8YvqJs5kasZwkkxtB7BORM4QkVkwOmiut61zAsB7AUBEzoIRjFgHTnWRZi5FGYxfVDecjWHmKJlMKaWSAK4A8BSAgzDuetkvIj8UkYvN1b4O4AsishvAvQA+ozhBGhHVGeMX1dN4uPw+n+RNTU5WUko9DqNjZvZzV2X9fQDAO6tbNCKiyjF+Ub10jQTrXQSaIhwBnYiIqAbaBkP1LgJNESZTRERENdDeP17vItAUYTJF09I9207UuwhENMMdHy1/blEAeM/PXuAQLx7DZIqmpWs3HKl3EYhohuvxRSf1uo7hEMY4+LCnMJmiaYmBiIjqbSw4+TiU5Hh5nsJkilzrmmfaJv1aju9CRPUWiE8+DiXTjGFewmSKXOulI5MfN5HXdETkZUmOPuwpTKbItSKJCjpgMg4RUR0NB2MVvT7BqWg8hckUuVY0MflgwlyKiOrp2QMDFb2efaa8hckUudagf3J3whAR1Vu0kpp1sM+U1zCZIteqqJmPiKiOYhXeBJNgzZSnMJki1yrW/7KxQUq+nnPVElG9+CPFJzkuFcHYzOctTKbIk+a3lJ6jO84OnERUJ3t7fEWXN5Y4+7KZz1uYTJEnXXnhmSXXqbSanYhosvb3+osun91c/IKQNVPewmSKXClZolbpsredVvI9YhXcDUhEVIlAtPjo5wtaGosuZ82UtzCZIldy0kQ3t7n44RuOJ6tVHCKispSap/i8U5cUXd41Fq5iaajWmEyRKzmpVTpp4eyiy0MxJlNE5E4rFxWPX6MVzOtHU4/JFLmSk/5OLU3Fq8mDTKaIyIWaGwTLF7QUXWcwUNkI6jS1mEyRKzmZqHhWU/HDNxBlMkVE7vOry87DB89dhfeddVLBdbrHQlNYIqoUkylypVCs8Bgts82jdl5LI+YUuSGGyRQRudHSebOwZslcfOodhW+k6fOxZspLmEyRK40UmSR03hyjee97H3wj3vHa5QXXCxRJyIiI6kXXqs8rMl5eIMr45SVMpsiV+ovMy7d87iwAwFkrF+LslQsLrhdkzRQRudAsc8TOubMKJ1PhGKfT8hJHyZSIXCAih0WkXUSuLLDOR0XkgIjsF5F7qltMmml6xwsnUyfNz3TcXLl4TsH1QgxGBMYvcp+WJp1MFb6JJllsPi1ynZJzcohII4DrAbwfQDeA7SKyXil1IGuddQC+BeCdSqkxESncq47IgX5f4WTq1GXzrb9XLS58e3Gxflc0MzB+kRvpZr45RZIpDoDuLU5qpt4GoF0pdUwpFQfwewCX2Nb5AoDrlVJjAKCUGqxuMWmmKXZb8MolmdqokxcWrpni0AgExi9yIavPVJFmPvIWJ8nUagBdWY+7zeeyvR7A60XkZRHZKiIXVKuANDONhgsnU8uyxmdZavafyqfUrO00I1Q1fonI5SLSKiKtQ0NDNSguzQS6z9Sc5uJj5ZF3VKsDehOAdQDeDeAyAP8rIovtKzEQkVO+cOFEaElWAjV/TnPB9caZTJEzjuIXACilblZKna+UOn/FihVTWESaTnTNVEOD1LkkVC1OkqkeAGuzHq8xn8vWDWC9UiqhlOoA0AYjOOVgICKn/EVuC56fdTvx7CIDd46G4pxShqoWv4ic2HZsBO/67w1F1yk14DB5j5M9uh3AOhE5Q0RmAbgUwHrbOn+EcVUHEVkOo9r8WBXLSTNMpMjcfNljszQ1Fj6EO0dC+OYf9lS1XOQ5jF80pdqHgugajRRdZ1aRuEXeVHKPKqWSAK4A8BSAgwDuV0rtF5EfisjF5mpPARgRkQMAngfw70qpkVoVmqa/YmOsOO20GU9xfquZjvGLplrCwVRYImzem24cnZWUUo8DeNz23FVZfysAXzP/EVWsWDiaP9v5HTBO5vij6Y3xi6ZSPMWYMxOxrpE8Z36RKRjsmEwR0VRKlBggyl4nxTqq6YHJFHnOnGbnh+1oKF7DkhAR5YqVuICzt/Dxhr7pgckUuc7h/kDR5c1NzsdmGQszmSKiqZMo0czXYMumWnhn37TAvUiu80+3v1LW+sUu7NKKczIQ0dSJJ9NFT6z2G/kWzC488DB5B5Mpcp2xMgfbXDK38MCdKU4WSkRTKJ5Mo1jUaW7IPe0umsspZaYDJlPkOtF44WER8lmxoPBkx8yliGgqJVLFk6lZtj6fqxYVnl9UsWbdM5hMkesUCx/5DtjViwsnU0RUPdFEeRc6M1GpOUFbGnP7fL7upPkF173++faqlIlqzxXJ1Oajw/jZU4frXQwq4E+7evDbrZ31LgYAoLFxYg+p6z721qKv4dUdUeUO9vlxzveeQudIqN5FcbWuseKjn7fYaqZOXTa34Lo/e7oNR4eCVSkX1ZYrkqnH9/bh5hc5e4NbPdDajXu2nah3MQAAjXnuI55bYtypJNv6iCrWORJGMq3QM148WZjp4snitXf2u/fee9bJRdff0z1ecZmo9lzR8y0USyGeTCOZSheda226Gw/HEUmksLJIG3o9hONJROK1nzD46f39RZv4AGBOc/mHbCKVRvMMPq6IqkE38ZUaR2mmGw4WH47FHotWLy4e7/tK1HSRO7gimQrGjBN1OJHCwhl80vvpE4ewr9eHR//lXfUuSo5IIo3IFPSVuHnTsZK1SKcuLT/RjCVSmOtwPj8iyi9s3hgSY7+posZLjG03u9n5OHkA0MWaQE9wReYS0slUkcltsyVSaSsBm06GAjGMlLiqqYQvksBwsPyJfyPxpBVIaykcT1nHQiGzJjHA3VSU3Ys6R0IcIZ4cC5u106yZKq5Ur4K5s8pLprzaRy2eTKPfF613MaaMO5Ip82QXdtiU9Jvnj+KS614quLzPF8GOzrGqlG0qheJJRBMpbGwbwr2vVL+P0g8e2Y8v3b2z7NeF4ylEEyk8uKMbt7/cUfVyZT4nWTJJfte6FWW/rz9a3rhVM8Vn79iOnz/NGz/IGd3Mxzv6iivVVWFBnona5xSpOO8Yrk4H9PbBAH706AGkp6gP6X3bT+D912wsOSK8W923/QQ+9JuXHa/vjmRK10w5rEHoHgsX7QT5X48fxD/dUd4o2m4QiacQTaRx3/YTuOGFo45fd7DPj63HRkquNxSIYahIzdSzBwbwhx3decuVSCn8YWcXHmiduLxawvFUyYT6K+9dV/b7svYlv/FwgtPtkGM6PkcT3jw5ukVLnma+xUUGHvaFq9MKs+HQIG59qWPKfvODgRgCsWTVk+9UWk1Jy9TBvgD2dPscr+/JZCqSMJKOQre87+72wR/xXjNgKJ4yvptZE+TUtRuO4Ko/7Su5XiyRLvq+d2/rxI0bJyZxur9UKJZCrMSdKpWIxFM12W+jk2janAmi5u+IyImI1QGdNVOVmJ1novaVCwv3BY0k0vjELdsQr7B5Vf/WozVupg3GktjVNV6zGxbu3tqJ9/zshZoPeRNLppFMK8c1ea5IpnSWGXLYzKd3UvdYJO9to7ESJ4iNbUO4bsORMktZe5GsK79ykqmwmYTFk8VfF0sWT9JiifSEPktx84ACjKS3Vv0llFIIxZMlq8gnY6iG/dDc6Ip7duZNirU/7erBzhNjiCbT1jFXjsf29GF/r/MrNipuOBjDR2/c4vohByLTvGbqxEgYX75nZ82bMZfNnTgX36nLC481pQC81D5ctFXBCZ0E1/r73bvtBD5645bMDQtVPmf0jkcwFIghXuPmQ729nH5O3ZMppZR1Anca2PUV0k0bj+Gzd7ROWK6/fKF52R7d3YtbX6pd35/J0slkJJEsK2BFzUTqR48ewGfv2F5kveJ35cWSKQRsyVT2PgnHJ1eTcd2GI3kHZd1+fNRqnowl0zWb+qXSIOQ1rcfHsOtE4bFprn7iEO7cfByptJrUXZrff2Q/7tx8vIISUrZtx0bxyvFR7O+ZugQ1njRu4vn++v2O+6pmTo7Ts2ZqW8cIHtvTh67RcE0/J18z39rFhZMprdLhaayaqRonUyOhOOKpzIV5te/+1MlZNF5pTV0Kfb7CFzD6c0pVzmh1T6aiicxJtNSdXJr+UfuicQRjEzsX6w5vheZ4iyan5lZ/u18804bP3F64L5fVJyGZRjyVdjxJbyyZRiyZxonRMHqLXN1Gk8WbR2NmgM1eHk5k9kkkPrlmvk1HhrGxbWjC8z9/+rCVZE2mhsSpjqGQZ++ImYxIIoVwkeM7kkhl1TKUv93ZPGio9KSklMKzBwZwZCAAYOIVfCSewvf+tK/qN1C0DwZw9lVP4tE9vbhj83Hs7MyfeHeOhPDOn26wTjiRRH1rppSq7YChgai+mJ3cfk2lFTqGS8eZlqaJydQaB0O+VHpXcrVqFjccGsDF172EZIEam3A8dztWu2ZKn4Oyz02TcetLHfjgtYU7mOskKpZytt3rnkxlN+3pjT8ejuNwf6Dga6yDIm7UyNiTA51MBfIkWkDmZDDV04zs7/XhUN/E7+WLJNA7HrbaxK2d6DBxiSXSiCXSCMfzN8M90NqF659vL9mGHUumoRRw7YZ2/OfjBwHkJjnRRGpSPwxje2fe58o/7MHX7tuFYCwz5ILTJt7J2HBoEJ+8dZv1+IHWLjy6pxcvHB501HG/kOPDoaJXNuU61O9H91jlV8WReArhIhcm2TWUkUQKXaNhjIfjGPBHEXBw4jaS94nH5nAwVtOk2G0qvbFhX48fn7+rFZvNY9CenO3pHsedWzqxvWO0os+x6xqNGCOZjxrHbr6aqVRaoX0wiJ7xCI4OGglCpM41U1uOjeAvr95Qs5oj3WXESUKUz1P7+/G+azaWXC/f8C4rFpaeX7TS4+3IoHHuKTV3YJDt1RAAACAASURBVCl7u/3Y0+1DqMBQRkFbS1P1k6l0zvtP1qA/iuFgrGClhW7hctpXrf7JVFbQ1zvnho1H8fFbthV6SeYWXbNpyD7Qo944oUI1U3UaydcfSea96vnpE4fw+Tt3WI+takwzqUqX6ASn+0uF4/mTnaufPIRfP3ekZLXlmPlj3XRkCC8cHgSQezUUTabzJq+l2JOwwwMBtA8FEY6lEDUDcy1PwvGUwoA/09R315ZO3LPtBK55pg3XVtB37l/v34UfP3qwGkUEAPy/3+/Cfz9Z2VAFyZRRq1noKlYphWgylUmm4in80x3b8fOn2/D317+Mbz+011r3Izdsxi+fbZvw+rhZE/rr547g+UOD1rKP3rgFv3y2DXu7fRjwT//xZSptltY1TifM5MDeMdgeB6pF73v9+fpxIJrAdx7ei93d43jDd5+wkhadbOn/61UzNeiPQSmgv4xjy0msSqbS2NE5Zv1mRiaZtGw9OuyoNSFfMrV0XkvJ150YqSyJ1N0d9A058WQaxyeRONpvRPBFEjkXpXq8SB0Dqj17hpVMVVgzrI/jQu8TKzNPqGsyFTWvijW90cdC8aKjyGaqm80OYrYvqw/oYDT/TowmnJ3ANxwawLXPVa+jui+SyLvjhgJRDAUyJ/uY7fv95+MH8anbJjYPKqWglMKgP4qUUkYylef9Y0mjydAKhgWuLPUts6FYMqfmIt/7OXFiJIxjQ8EJHeoj8ZTR2T2etBK7QolvtWR3IowlUwjHU/CFExitoHO6L5yAr4yrvKNDwZyarJFgLKcmaDQUx/gkrhp/9tRhPLTTGLIiWiLQxFNG7WM0a/+OhuIYCcXQ74/i1a5Mk0/bQADtg8EJrweMhPz2lzvw2N4+AMaxeGI0jF5fFF+4q3VGzHafrrBmW8cf/du3/3arddIo9LnWjT/mya+1cwy/23YCL7YNI5F1AZKJBZPrc9M1GsZlN28tOTJ4Kfpz7bfFHxsK4sM3bJ7QHLqjcwxnXfVkyYGKnzkwgA/fsNmKf77w5Gpudju8jX5Wnlk+VjhIprIvCCdDf68B83j7w85ufOCXmwr2mevzRfLOyZoZb8w4Hu7bfgIfv2Wb9bxuZRg1t2egwHl4smJV6vulz4P6+z+yuxefy+pzrMvviZqpXz93BFfc86r1ODN4ZwrJtCo42Jf9LoHsk7tSakIfrIN9fjyyu9dap1RGqj26pw93bjnu/AsVcOPGo/jy73bCH00gnpzYFyqSSOUkOPqEpQ+W4yOhvFXPP37sID59+3Zr/ULNfIlUGmmlEE+qnPd9pWMUzx0csNbLbLdMn5p8NRxOk6nvP7IfV/5h74RmvmAsiXAiiXDWUAtOO8FOVvZ5L2be9djni6KzgiaDQs1dhVxxz6v4z8cPWY8v/+0O/OjRA9bjUCxZtHmukIdf7cFT+/sRS6YQNE8ohfof6mM/nswcY9FECqFYCmmVeV4pZTXDPranD/vMztGZ31wKoawhPAKxJJJphWDUSDDLSTK9Kl+tx1goDl8kgU/css3q3xOJp/DNB/dgxHZS1/FHxwP776rU3Vddo2G89UfP4OhQ/kEd48k0btx4dMIxqj9XX2xaF1m2wZMz/+uLz8mNgL7h0CC2HBvBIbPrRjKVxjMHBqztl0il8eS+vpK1SPpz7RfJu7vHsaNzbELNTcdwCNFEGn3jxWuy9ElT//Ym20dtMOAs2clXM7Vk3sQ7/OzGwsXff0/3OL5wV2vB82YyZWxfn/n9jg4FEUumrd+qL5LIqWn+065efPvhvRN+y1Y3G/O4GgsnkEqrTDJlbseE+XlVT6as1ozKO6Ab72P8v/PEGDYcHrSOQz0bSVWTKRG5QEQOi0i7iFxZZL0Pi4gSkfOdvO/zhwZzrsQzP9r8tSIPv9qNK7JuXdU7LfvLZv/Qh4MxdI2GcdeW4/jOw5nmC/2+D7R24Uu/yzSv2cWShZtLyrGnexw7T4xZB6X9e0Vs40rFbdX7eugDu7aBAI4NBTPNmjEjCbV3DEymVE6ThH7fGzcezdusFEkkM/sgT5LjCycc3SzgiyQwGo5PaOYbDMQw6I+ZI747b/+uVuYfTRg1U6m0Kmvslt9u7cT6rKQ8HE8iFEthT/c42gcL9/HT+n0RqykVMGokdABOpxVCcaNcg/5oWVfHsWQKgWgSn7hlG35hNssV2p6Z5NX4P5FSOR3SdZN5OG4kV8FYEt9bvx83bzpmvD7rqtAYisN4rL9XIGrUvhbqT1EPtYpf9hadrtEw/uzHz2D9rl681D6M3WYt375eH+5r7cI2W9+nMVtzko4B/b4o3vvzF9BjTnBbKJnqGDamAzrQ6895PhBN4BsP7sYLbYP46ROHsOVobr/ATA1C7rGgY4yVRCVyl2fuui7v5Hiwzyhf50gYX7n3VTyxrx9fuKsVB83+oxsPD+Gf796JfT3Geqm0wub24QnvY6+ZUkqhbSCQU/7W45lt3DZgvF+/v3i/Rn3s6+a9/hL9IBNms2AilcarJzIzbTjpbwjkT6bmOJhiplSt9ZajI3jmwIBV0/n0/n687SfPWtstmTb7Epvv89IRYxu3dozimqcP486XO/DZO7db3yNsS641e8uQTkJ1LNDJqE7qsm8Sy+6ukkilcy4wBgPRnIv7QuK2GttD/X7c8uKxkq+zi2SdX4FMn2F9rtLnUaf9eUuen0SkEcD1AC4EcDaAy0Tk7DzrLQDwVQCFOzvZ+GwH396ecXzw2pcyd7XZTghbj47i2YMDVsZrVY+bJ4i7t3bmVNM9/GoPPnbLVoyG4vBHk9aO1AfB7u5xvHgk86MNRBM5zTCxhJHEVNpRXTdz2ZNFLZJIW98JABJpPbhaJkjkq7kJxoykRx+fhe6esNeERbOCZiiexIFeP7Z3ZAJuJJ62vne+JO4njx3Al35XelqaSDyFYNRImGJZfa2SqbRZWzYxsBczv1kKLisn0YqZd3OmlXJ8xyQA3PTCUdya9aP1RRLoGgvj2w/vxdVZSek1Tx/Gb7d25rw2mUpjLJzA8ay7CmPJTBITyqoN+MAvN+ETt251XK5oIo1ANInjI2F0jkSs98t33OpkKHsOSKWyhuWI6/4zugkoiWAsgcFA1CozkAlEsayrUwDwm687OjQxucw+8UyVWsYvezNf73gEaQXrJgKdfOiTk71GpSPrWGhsEASiSXzt/l3YenQER7PuQC2UGOuY0DkSwqdve8WKh6+eGMf9rd3Ya3aoHgzE8NDObutYj9hOkjou6Q7O4+a+tF9Q6SRmNOQ80e8dj1jJ1N7ucazf3YvW4yM520U3r+m+UBvbBvGxW7ZZdzlqOq7p7brpyDD+5hebrKTz2QMD+MiNW/Bi2yD++bc70GV2sO8eK54c6e+vT9LjBS5kEqk0th8fxZP7+vHhGzbjd1s78aEbNlt9g5z2JcuXTIkUjm1ax1AQn79zu5WkpNIKg4Eojg0F8YNH9ltJtW7W3Nk5jsFAzLqI16cYPfyNvvP70T19+PWGduzt9UOpzG84ZlVa5K/Z9EeSONTvRzCWm1zp900kc1//4I5uvP2/nrPK/+vnjuCdV2+wjsvfv9JVtGZN09tbJ3EPv9qDHz920HEs7xuP4On9/dbFjP1iQf+fLNFdyM7JOehtANqVUseUUnEAvwdwSZ71fgTgagCOewdmB4lFc5oxFk7g8EDAuiLSO+2hnd344t07EIzljr9kZb7ml93VZdQAaSPBGIYCMevHHLBl0MeHwwhEk4jEkxgPx/HLZ4/kdHy3Z6p2o6E4OoZDVt+lW148hi/nSTLst5LbrzTtV3r6WMquhowm0hM6oQeiyZys395c8MjuXtzy4rEJA2FGs34MgWgS1zxzGFet35/1vY0E7dUT49bVY7be8WjRu87ub+3CXVuOI5pMIRhLZvrZJI3vkFaZq3pdk+bkanf5gsL9CuYXno3BooNlIJLEWDAGBWNAPKcj3Pb7o+gw7+AbDsasZrFgNJlzVfro3r4JV1i6KSG7NkIn2V2jYasTcsjsy5XvjqWRYCynv8jebh+6RsOIxJPwR+Jm8mqUI13guNX7PpXOXWbV8tquJkPmb07XoFm1prYmqEzNlPE+2f1jjg4FMR6O49KbnSeIVVSz+KUUsPXYiHX86Lg1sWN3pvnofzcdta54ddxqbBAsmN2E3vEIHtrZg9bOUXN5/hr6UCyJbz64x0qeDvb5sbFtyGqK1Z+nk54dnWP42v278VL7UM772ZMq3T+uz6eTg9yaqVhW07BWrN9K6/FR/H8/3YCD/Ub8PWQmR6+YtUf67jJ9TOskQCcz9uYlnbjr77fX7KPUZ568D5gDya7f3Ycn9/dj2Nw+/f4IvvenfQVroa1a2nRusmZ308aj+Icbt+CIWeN1fCQMpYATIyFc/3y745N5S54+U070jEfw7MFB60Lokd29+D///Twe3d2L218+bl2odY9G4I8msLPLOBfq7aOPU53c6N/6MXPuP/299Pc/ZJ43fZHcGlR93Dy5vw8XX/eyFft0TNDHiR5RQH/e0aEgBgMx9I5FMBqKY/PREUQTaSt2BGPJnAtsuz++2oMLf/Witf/1+Vx3eHdag/S1+3fj8t/usOY81N9Hf199POj9aR97sZAi0ytaVgPoynrcDeAvslcQkbcCWKuUekxE/t3RJyM32K9Y0ILRYMy4K80M5I/t7cPebh8Wz52F5w4O4h2vXZbzep05DoeMH43RcTrznt1jkZzOz9c/fwT7e/3wmYFen+B+9nQbNrUN4cxTFmAwq5OfvqKJxFOYnTXQ2qa2IRwZDGJ31zhaO0fxofPWYFvHCE5aOBvbOkbwxN4+tA0E8dE/X4OxUMJs5socIDtPjGFfjw8XvmklgMLVw88dHMTWoyOZW00TKcxryeyyYDSJWDJP7YP5Wfdt78qb9HSNhbFkYBa6RsMIxoyEKrtdW9eS/eLZNhwZmNgfI5zIPyHxwT4/Eqk0HtrZjUA0iWg8lbPeiZEwGvLEkajD5tSTi9w+vHR+C/xjxfsUPLSzGysXzUbKVqMQjCWwcE6mz8JYKI6GBsGiObkZWkopJFIKX7n3VSwz+zgkUkZTV84QEnGjxmk4GENzYwMWzWm2rvqTaYX2wQDmzmoyaqYSKXzpdztx8kIjUQzHkkgDCMZSeLl9GEvnzcJZKxcCAC67eSvOWrkQyxe04LUr5uOWF4/hnNULkVJG59RYKp2zvS/61Yt466mL8bOPvsV6zn7VZX9e12b5bQFryB+z+gMBQCxrzJp0WmHU/A1m+mxlfoefuvUVvO/sk6b87llTzeJXKq1w6c1b8W9/83pc80wbPvfOMwDAmhJJn0R0crKpbRCbjowgkVL40nteZ+2rRgFmNzVayUSbmXQEYpkbQmLJFBpFcOeWTrx2xTzc19qF5sZTjfc3T5b9viju3HwcTQ1GLYeu8dFN0K3Hx/BXrz/JalrRzVq6JiFsq4HKTqbiWYPq6v24v9eHS657Gc99/a9w2rJ5E7aPvkDQfTV1DdKAz/j8QX/m+wGZloZCcwDqx7p8u81koddsTQjamut0cnu4P4gXDg/hQ29dg3PXLp5QTn0hZ538dZN3Ko0DfX68eY3xGn1zxg5zXC693TYdGca1G5zfcJGvZsoJ+5A53WNhRBNp7DNrpPR22dg2hG/8YQ9WLTLipd4euia1zxfBJde9ZPWh0n37dK22Phfo1w0FbMmUdQFl9AHWMUKXT1+n6b3XMx7G9c+3W8fpb7d14oHWbqxebJRvOBjD8gUt6PcZx8tNG4/iwZ09ePiL78C+3gDefeYK+CMJ7O3x4WCf35ooWid5OokKxZJYOLsZf3y1B3dtOY5bP/3nOD4SwnmnLskpf5d5TtTH8ZHBAPzRhHW3o34/q/uMw5opJ8lUUSLSAOAaAJ9xsO7lAC4HgCWrz8CyrOq8FfNbcMLMrEPWj2UcLxwewkVvWol4Kj0hMdA77faXO/DTxw9NGKtDbyx9RfLwzp6cqUV0zdYrHSM4OhTEmiVzrOYREbGuriOJFLJ3x3XPt2Nfjw+LZjej3x9F+2AQHcMhLJjdjEA0iUf29OKVjlE8e6Afx4ZDOG3ZvJz+Ffdv78LxkTDOWb0IvkjCaiKxe+nIEMYiCav/jD2ZGgnlTx56xyNIJBWODQfzznV31+YOpCHGnV3QEwxPTGYC0aT1w21qEOsErJvv7L549w6E4ymsWNACf547F69an//q8OFXu7Gto/R4T6uWFB4l+JTFc3C8RDJ108ajOHnRxMHxhoNxLJwzC4P+KJoaG/DPd7diydxZuOmTRteZR3b3Yn5LI5QyfmDDwXhm2AqV6YythRMpRJNpfPHuHVi7dC6+9v7XW2P1JNMKX7l3F85YPtfsCJ9Gvy9q1WaEE5mron+551WsO3k+PnjuKqxaPBttg0F0j0WwZN4snL1qIYaDMQyagS6WzOxL7dhwCL3jESuZ6h7L1IDZWwD156aV2dctmHuiC8SS+MiNm/Em88QSy7pJ4oPXvYQl5kStOoFIZtV8jYfjJTsB10s58ctc34phs095LQDghcODSCtgb69xktVJkb7y1bWMPeY20MmVPhmklTFfmz6J6eXHzQ7Vr3SM4uzvPomffvjN+NGjB3DFe14HIKuPj5mEPLGvF5uOjOCdr10KIHOy1wmwLpfuyqD3rY4/9m4IOn6GY0nsy5o+SP+uO4ZDSKYVDvcHcH9rFz7/l6/BbS934MJzTsGnbnsFH/+L03K2ndXhXY8naH7/QFbNlHFxkjK3Vxgfu3krbv7Un6HPF7WSwO6xMD556zbrfKBP9rrZZ9BsBtLJhf5fNw9tPz6Kz9/Zils/fT6ufvIQ1iw2YoK+yBoPJ/Cm7z+Fb190Fr710F689M33IJpIW6/XSZ/+HKeDTWuTTaZ0/N18dBifvu0V/PUbTgIAbD02bJbHKNeRAb9xkaybZc3zmP7Nj4US6PdHoRsWw2ZHbh0SXm4fxnce3mv9hjuHg/j9Kyfwf89bjc6RsHVhaMUG8/iKJlJImueU7PdrGwjgj7t6ceYp8wEA7QNB+CIJNJtJ/5A/hjesBF7pMJLjJ/f1o98XxU+fOIQ/7e7Df/ztG3D980dx6lIj/ifM41Kf2yK2Zrq9PT7sPDGObz+8B0/tH8Cx//pbAMAvn23DA63dVuWFTibX7+rB3h4/9G7Rx5lOPp3eae4kmeoBsDbr8RrzOW0BgHMAvGC2+54CYL2IXKyUypnrRSl1M4CbAaBl5Tq1yPwyzY1GNbdu09UHf/dYxOgEbtZU2Zs+9Jd9ud242stONIDMjyNh3cWQe9DrndJn9nXwR5PmbeNpzJnVaL3OfodV50gIEbMDs0Km71LEHOfp6EAAI8G4mYykrStNzReJIxBN4OdPH8aeHl/B8Wp6xqM5NR76b18kgUg8ldPPKtv31+/HWCiBoUD+AcnGwkZ1ql7W54vkHcgtkkghnkqjuVEwu6nR+nFGEkby0DUaRlop66p0wB9FIqWsK2kgtx/AgV5/3vbwnzx20FFH8DVLCo8SvHJB6UHvArEkFuWpQt56bASptMKnbnsF81uacHwkhNlNDQjFkmhsEFy3oR3L5xs1Uam0wngobmvqSE/YT9F4CuNJo0Yz+47VdFphOBDFgtkNUMrYlsFY0toXOuApGEGwbSCAmzcdwxtOWWB8llmbFYgkEIglrROy3sv2pDi7NuiS617GMvN72I+K7PL/401bsMpMOrNrBzqGQ9aJwOpfEoljOBC3kim9dnayFk2mp2ym+jyqFr+A3Bg2Z9XrFQB0mTUu+m6y3qyaIiAzSKJujtCJc79ZQ5NMG8OaQOkaGuN14+ZJayQUR0rBGvut1bzw6DDv4vObyZC+4/eImbjrpll9MaYTWn2Lvd6HvnAC779mIxbONvahfaTz7vEIPvSbzdY2iCRym9mePtCPB3f0YO6sJly7oR2zGhswHIxbzZWafSibfd3jeNP3n8J5pxoJ+r4eH8767pO48E2nADD68mw+NoKbNh3DtRvase4kI84c7PPjxGgELeaxOGxuL52k6WRHn/R10qNrJP74ag98kQQe3dOL7cfHMGed0eqgm8FiiRSC8ZTVbPjonj7895OHMM/sJD5m/ub0MV3uIJiTTaZ0uH9y3wCOj4SzKh90c7DZh848T+qkQR9H+icZNy+QCzVKbjg0gEP9Aavm6KFXe3B4IIjH9vTixfYRa6JmnaTrDvuj4Tj25pkSyeqTFNU1h+aQG2Y5Bsz9p1uV9HbVNYGdo2HzjkHj++rmSb3d9X7SFyP687YfHzMudhMptDQ34un9A+gZj2CuWX79/Y8Ph5FMKytmHRkIIDaJmVmcJFPbAawTkTNgBKFLAXxML1RK+QAs149F5AUA/5YvENnpLzOrsQHzWpqsg1n3FdBXAofNtnx78qAf6efHbDU1+kerM2x735i4+Tr7ztnWMYLRUNx63agZjJ7c14cDvQGEYymo7NeZdzDpK79jwyFjufX5uZ87bCZag2bTSSGJVDqnSSpkTvXyk8cOYL/tDp5sB/sCEz4zmx56Qr+3P5LMu/6gP4poIoV5s5rQ2JBJjHRQ/M7De3GoP4Dv/t1ZSKYVomYfs1QiZR6Y9o7v6Zwai+znnTh1WfGaqVIC0WTeUYSvfe4I1i6dhwF/FCONgkRKIZlK4R9u3IIl84zaR6uvkVIYiySArAAaTaZyqoZ1B/cB83WjoTgazA6mCsBgMG7t96h5A0Ghmdz90SQaGxqswJhWRuKjE397vxJ74q/7hDU0CEZtSWC27N1/uD+Qd1qitMr8JvVvbjgQN2rEbO+r3y5pTotUx6ESahe/VG6Hbn1S08lL50gY/3DjZjSYFxX6GOkaDWPbsRH4s/qiDAZimNdinKx10729pkgna21mPNRJXKavltk3y9zW47ZxfvptJy3r9x9NYDAQw2lLdQKtL9qM1+uaMk1fhA4Hc5uB9ElQnyz1yb65AUikM3FQH2v7en2Ip4CD5snw2JBR03XQjG06Keo2kwOdBNpvWdc1B7rmK2g1O+Xuj3azy4KO04O2ZkX9C9QXIHvMZLG1YxRpBQRs+1d/751l3liRb5ypcuiakyNDxvbVp0V9nar3t26KHw3Fc4aNKNWlQifl+jjRx9k2c2BO/dvX+1nXbD21rx+P7+uf8H7jVrcaY/2xUG7NUJ8vgn5f1OpLqO9aHDGP11FzO+vzrT5+2gYC+Pydreg1LxJ6xyM479QlWcdvpkZ29ZK5BW/Q0n299HZ8oLUHh7MqQEIFZlKxK5lMKaWSInIFgKcANAK4TSm1X0R+CKBVKbXe0ScVkUorvHhkyArA+qvqH4s/bPbnKPE+9qk99EZPmMGp8LDxZs2VufHv2XYCOzrHrM/XB+8PHzmQM/quznPGQ0ZnZB10dG5QqLzDAaPz856ecetOiHzs5b3++SMYNzuNnygyPlKxRAoAwvEE4qlM+e19iDSjxgSYO6spZx19MO48MY5gLIlrnjmC2c0NmVqVAh9f6Szfq4tMBnrKotI1U7FkGr15+pANBmMIxfU4S2YNEYC2wQBaGhvMZtDCVydKGQGq3x9BImsMMz2ZrBF8cjdKwlYLW+jYNJoVYzk/6EgiZfWDsd95lG8L94xHsGbJnAnNgAW/T5H1ErY+evpRvlH1+8YjVhI+5HAMnmqrZfzS393qyG3WDOgr7tFQDJ2jYaw0j00dzAf9UfzjzVsxqzG35lbfvWwlolbNulnjYsYhK1lIZppmjfXS5v/mRaLu5qBv8dZzz5nHsn6dPvmM25v79IC6tpNJ0jppmye9oBF3h81kp92sGRu2ulQIADUhHupDTHeU1++nj5Vx82Q9ZsZl/T30dtTvp0+CusZPJ1d6O+jtpN9XtxToKcv06/RvUMdPfT5psw17opfr9+0vczDNydZMaXqoB/uFuL1yQceYl48O4X+z7kKOlYjD9r5ZVo2i+TK9nXTyrNcbCcXztjBYyZ35vj7rwtBsWTo6gptf7LCSK128hPk5OnlO2ipT+nxR7Mia0P1wvx9/++ZVVqzW5TzQ40P3WMSqYbI36NhjV9dYKOccmq+rTD6O+kwppR4H8LjtuasKrPtuR5+cJZ5KZ/3wMvRJ2+kgatFE/hOS1fRQ6POtW2LNEXAjcevOAiDTN2E4GM/bJJfd/OWEPh8VS6SAibded45EMGTOf+b0ds18IrbtVOhErn+URkKQOeDSVvmNMnQMh1D6xt7KLSsysN2K+aVrpoDMts+WSuevHUumFFIpoxayUJOqFk+m8TfXbMJis7nLF05AYWIAsCt1gaBFbOXTFwBOkqO//83LePPqRWV9Xqn5quzyrf2RG7fgPW9YAcD5GDy1UOv4ZZ2EzV2h97neZzqu6GNI147ajyn7oaIrcRNW0pH7Ovuu0M/ruKGX611pNTfaLgz0SUbHFF1DYA1imedkcvld260O5cfNjsu6I7RudtHff2IalcuqWTH/13FU9/XpNPue6RqxQteK9u1hTy66x8L46ROHrOlUdJ+rPtvQCfp1Ornst9XMpW3lTTjooqB98d2vtZrQJ2s4qJPP/OcA++Y52BdEdhELXeyK+Vod62OJ4ttbD5qpt0Oh2mf7/g3bLiA7hkMIRJMTziF6fx4fDZnlyC2I/Xz7/MEBxJIqM3afufp1zxvDPjQXqBG0772wbTDQAX8E+3p8OMeMoYVU3AG9lnTgLlXTok223iNzZWf8MR7OHUl8zLoTK/8n6GDk9Bb7csul9YyH4Ys4q6Wrpnx37tlNRXmWFJlyYfE8B2MjFFFOklCI0Qxr/G0FpPrcwZZjOBjHy0fLm9C51IWHEz3jETxuTjfjgs1QM/aLNavGxBrXLv9daaWOrUzNi66hUjnP21+fLLE8FEviwR3dCNlOFtbJzvY43wwT2tMHBjHHPHvomrmecSM5GQ3nr8lyyqpZMQt0wkx2SlyXFKRf1+OL4MaNR9HSZJy2dS10oMAFp3msOwAADmlJREFUSTyVu90LcXp+EgDfvOANjtZ1wunmKHVBZ38/vXqp72Vf3u1wNgn9/jpW6uTK/ml6vZCtJlWzT7+0ty+IvX1BnGwbQufgQABphbz9dfOxf6+D/X58/JZt+PVl5xV9nSuSqUL7rMKxMsumP653PPegONTvx/rdPQXLqX+LtS7uiFkdPhW1QG60cHbhw9V+80E9pFQmKZviQ7ekcq6eiyn3e012nrPpoFBSM9k94TT5KiSpgH97YLfjz9MnlULvqyus7MlXpSYmpVV5WwSius9M8e9VqDyTXa5V2Lo3aVMViwrdlV6ILlepFh171wItX9eCfO+nk+bJ1nWMhYzham5/uaPoevU/A7lQwNb89syBfjy2d2LHunpx24l6qsxqLjzlQktzXaeZtLihJiqfepVqsrUJ5D1VrpifdmY1lZ4yxssmu/tLhcxCMbVQCuakJaUc+tNfOjJUdD13nIFcrgrT81GNtUzzQEVE3jbbJRd8XlNuklarpL5U0se9S9NCS73q0ImIHJhbpGadvI9nIJoWKr3dmIioluYV6fNJ3sczEE0LrJkiIjebN4vJ1HTGMxBNC+wzRURu5oY7jql2mEzRtNDcOFMHjCAiL9DzVxZcPofJlpcxmaJpwZyklojIlZYWmcEBAF538oIpKgnVApMp8gT2iSIiL1u+oPAMDgBw0vziy8ndeIYiTyg0r1K2BlZOEZFLXfTGU4ouv+J966aoJFQLTKbIE5wMeDebndCJyIUaBFi7bF7Rdc46ZeEUlYZqgckUecLC2aUnMp7TwmSKiNxnxfwWNDmoXSfv4t4lT1juoD/BgpbSCRcR0VRbPI+xabpjMkWecMqi0snUQt5aTEQudPKC2fUuAtUYkynyhFWL55Rc5yQGLCJyobVLS8cvAJjFM7JncdeRJ6xZMrfkOq87af4UlISIqDyvKdH5XFvG5kDPYjJFnnD6MiZTRORNpzpMpl6zjAN3ehWTKfKEM5aXDkavXeEsYBERTaVTl5a+GASA15zsbD1yHyZT5AknLSzdH+q1rJkiIhdyEr8A4MyTOdaUVzGZIk9wMgK6k7GoiIim2qI5zmLTGSt4QehVTKaIiIhqqMHhXFcrF/GOZK9ylEyJyAUiclhE2kXkyjzLvyYiB0Rkj4g8JyKnVb+oRETlY/wir1g0d1a9i0CTVDKZEpFGANcDuBDA2QAuE5Gzbau9CuB8pdSbATwI4L+rXVAionIxfpGXsKuCdzmpmXobgHal1DGlVBzA7wFckr2CUup5pVTYfLgVwJrqFpOIaFIYv8gzmpvY88arnOy51QC6sh53m88V8jkAT+RbICKXi0iriLQ6LyKRc5zqmGyqFr8AxjAiyq+qabCIfALA+QD+J99ypdTNSqnzlVLnV/NzibTFpafwI8qrVPwCGMOIKD8nyVQPgLVZj9eYz+UQkfcB+A6Ai5VSseoUj6i8+apOWuhsDiyaMRi/iKjmnJymtgNYJyJniMgsAJcCWJ+9goicB+AmGIFosPrFpJlsXrPzxruTF/PWYsrB+EVENVcymVJKJQFcAeApAAcB3K+U2i8iPxSRi83V/gfAfAAPiMguEVlf4O2IyrZ8ofO2u5WLOR0DZTB+EdFUaHKyklLqcQCP2567Kuvv91W5XESWNUudN92dzGY+smH8IqJa432Y5HqnLnE+gfGqxUymiIhoajGZItdbtch5M99aJlNERDTFmEyR6y0vo+luBee2IiKiKcZkilxvSRnzVS2ey+kYiIhoajGZItcrJ5la0MJkioiIphaTKXK9hXMc3XQKAGgpY0wqIiKiamAyRa43v8V5MkVE5CaNUu8S0FRgMkWuN5fJFBF5VFMjT7MzAfcyuV4zgxEReVQLq6ZmBJ6lyPVmMZkiIo9aMq+8m2KYenkTz1Lkeg0NDC9E5E3L5zsfdBgAWpp5WvYi7jUiIqIaWb2kvMnXWRPvTdxrNO1w4E4icouTFpQ3K8NqTonlSUymaNp5y9rF9S4CEREAYGmZfaY+cM4pNSoJ1RKTKZp2fv4P59a7CEREAIBl88rrM7V0nvMZH8g9mEyRq02m6/my+S2YxT7rROQCa5aU12x3ysLZmDeLMzl4DZMpcrXGSd7Jt2pJeVeDRES1UG4H9L954ynY8d3316g0VCtMpsi1ls5pwrqT5k/qtX9++tIql4aIqHxNkxi0czbnGPUcJlPkWgvmNE964uK/XHdSlUtDRFSer7//9bw7b4bgpGfkWisWzMb82ZM7RHlHHxHV27+8d129i0BThMkUudYPLn4jls6f3J0ta5bOq3JpiIiI8mMyRa515ikLJj3j+mQ7rhMRVcMsdqKZUbi7ybUmm0gREdXb2qXl3cVH3sazFblOgxj/iIi86vJ3nVHR65dxWixPqWsypSfHPnWx0S+m1H1b9sm0C63/Z2sXIftuVL3eKQtnQTBxIEj7+y5oMV5R6nyuP+P1J81Fc56VW5py31iv0mD7X1s6txmNDUCT5F+uLZ83K2/ZdHnmNAsairy+pU57vblB0JLnNuEG5G7rS96yGhe/eVXFn3fBOSfjknNXokGAphLfOd/+q4bJvq1+3ewm4+/5ZpuBvV2+0NeaU+oLl3ifOU25JW+x/djsye5sc339sfPzHGSbv/nussrkdi1mzWmLuS0WmSPFrlthzMWm95V+vHqB8czyucbrls0x/j9tce5enWX7X9Ob/KI3LgcAnLPS6Be4ZmH+k67eBXPMF9qPnTNPMu4yO3WR8UnzzbfRu3p2Y+5j/f/J83K/t7bQLPCS2bn73l66xeYT823H1DyzgHPM/3V3Sf38a5YZY8eduTz/XHf6dfbNocszz9w/i/Rjc/2TzC/+plULjNebG86+/XVxV5j7b74ZNPT5a9Uio1xffe9rMKtRcMGbV+ctp1Nf/uvXoblR8N4zlwEATplvFHjlAuPzzl1lDBtj/6UtNr+f3j36f13+peYBMa9EJx993Mw1v+cCc/udtcI4buyhfI75Abo89s/Xy/XusZf7TSfn7tdCsfMU8/izf/6CAiM161Cm/58/yRz13NULii4XpdTk3rlCIhIAcLguH+7McgDD9S5EESxfZVi+yky2fKcppVZUuzD1wBhWETeXDWD5KjVdy1cwftWzA/phpdT5dfz8okSkleWbPJavMiyfJzCGTZKbywawfJWaieVjnykiIiKiCjCZIiIiIqpAPZOpm+v42U6wfJVh+SrD8rmf27eBm8vn5rIBLF+lZlz56tYBnYiIiGg6YDMfERERUQWYTBERERFVoC7JlIhcICKHRaRdRK6sRxls5VkrIs+LyAER2S8iXzWfXyoiz4jIEfP/JXUsY6OIvCoij5qPzxCRbeY2vE9EJjcjcHXKtlhEHhSRQyJyUETe4bJt96/mft0nIveKyOx6bz8RuU1EBkVkX9ZzebeZGH5tlnWPiLy1DmX7H3P/7hGRh0Vkcdayb5llOywiH6hl2dyA8WvS5WQMm3z5XBXD3By/ipSvpjFsypMpEWkEcD2ACwGcDeAyETl7qsthkwTwdaXU2QDeDuDLZpmuBPCcUmodgOfMx/XyVQAHsx5fDeAXSqnXARgD8Lm6lMrwKwBPKqXeAOBcGOV0xbYTkdUAvgLgfKXUOTAGAr4U9d9+dwC4wPZcoW12IYB15r/LAdxQh7I9A+AcpdSbAbQB+BYAmL+TSwG80XzNb8zf+LTE+FURxrBJcGkMuwPujV+FylfbGKaUmtJ/AN4B4Kmsx98C8K2pLkeJMv4JwPthjG680nxuJYxB+upRnjUwDs6/BvAojJH2hwE05dumU1y2RQA6YN7MkPW8W7bdagBdAJbCGKT2UQAfcMP2A3A6gH2lthmAmwBclm+9qSqbbdnfA/id+XfO7xfAUwDeUY99PUX7jPFrcmViDJt8+VwZw9wcv/KVz7as6jGsHs18+sDQus3nXEFETgdwHoBtAE5WSvWZi/oBnFynYv0SwDcApM3HywCMK6WS5uN6bsMzAAwBuN2swr9FRObBJdtOKdUD4GcATgDoA+ADsAPu2X7ZCm0zt/1mPgvgCfNvt5Wt1lz9fV0avwDGsEnzUAzzSvwCahDD2AE9i4jMB/AHAP9PKeXPXqaMlHXKx5EQkb8DMKiU2jHVn+1QE4C3ArhBKXUegBBs1eH12nYAYLbbXwIjYK4CMA8Tq39dp57brBgR+Q6MZqXf1bsslMuN8cssF2NYBbwYw9wav4DaxbB6JFM9ANZmPV5jPldXItIMIxD9Tin1kPn0gIisNJevBDBYh6K9E8DFInIcwO9hVJP/CsBiEdFzK9ZzG3YD6FZKbTMfPwgjMLlh2wHA+wB0KKWGlFIJAA/B2KZu2X7ZCm0zV/xmROQzAP4OwMfNYAm4pGxTyJXf18XxC2AMq5RXYpir4xdQ2xhWj2RqO4B15p0Is2B0/Fpfh3JYREQA3ArgoFLqmqxF6wF82vz70zD6IkwppdS3lFJrlFKnw9hWG5RSHwfwPICP1LNsZvn6AXSJyJnmU+8FcAAu2HamEwDeLiJzzf2sy+eK7WdTaJutB/Ap866YtwPwZVWnTwkRuQBGM83FSqlw1qL1AC4VkRYROQNGJ9NXprJsU4zxq0yMYRXzSgxzbfwCpiCG1boTWIHOXxfB6E1/FMB36lEGW3n+EkaV5B4Au8x/F8Fo138OwBEAzwJYWudyvhvAo+bfrzF3eDuABwC01LFcbwHQam6/PwJY4qZtB+AHAA4B2AfgtwBa6r39ANwLo/9DAsaV8ecKbTMYnXWvN38ve2Hc1TPVZWuH0a9A/z5uzFr/O2bZDgO4sF77eQr3HePX5MvKGDa58rkqhrk5fhUpX01jGKeTISIiIqoAO6ATERERVYDJFBEREVEFmEwRERERVYDJFBEREVEFmEwRERERVYDJFBEREVEFmEwRERERVeD/B/+3uf5NUl+QAAAAAElFTkSuQmCC\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "uv-cont result, polynomial order 2\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "uv-cont result, polynomial order 3\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "try:\n", " from casatasks import uvcontsub\n", " fitspec='0:0~59;86~127'\n", " ms_uvcont = 'uvcont_noise_sub_0.ms'\n", " res = uvcontsub(vis='sim_alma_cont_poly_order_0_noise.ms', outputvis=ms_uvcont, \n", " fitorder=0, fitspec=fitspec)\n", " print(res)\n", " print('uv-cont result, polynomial order 0')\n", " plot_ms_data(ms_uvcont, 'data_spectrum')\n", "\n", " ms_uvcont = 'uvcont_nonoise_sub_1.ms'\n", " res = uvcontsub(vis='sim_alma_cont_poly_order_1_nonoise.ms', outputvis=ms_uvcont, \n", " fitorder=1, fitspec=fitspec)\n", " print('uv-cont result (no noise), polynomial order 1')\n", " plot_ms_data(ms_uvcont, 'data_spectrum')\n", "\n", " ms_uvcont = 'uvcont_noise_sub_1.ms'\n", " res = uvcontsub(vis='sim_alma_cont_poly_order_1_noise.ms', outputvis=ms_uvcont, \n", " fitorder=1, fitspec=fitspec)\n", " print('uv-cont result, polynomial order 1')\n", " plot_ms_data(ms_uvcont, 'data_spectrum')\n", "\n", " ms_uvcont = 'uvcont_noise_sub_2.ms'\n", " res = uvcontsub(vis='sim_alma_cont_poly_order_2_noise.ms', outputvis=ms_uvcont, \n", " fitorder=2, fitspec=fitspec)\n", " print('uv-cont result, polynomial order 2')\n", " plot_ms_data(ms_uvcont, 'data_spectrum')\n", "\n", " ms_uvcont = 'uvcont_noise_sub_3.ms'\n", " res = uvcontsub(vis='sim_alma_cont_poly_order_3_noise.ms', outputvis=ms_uvcont, \n", " fitorder=3, fitspec=fitspec)\n", " print('uv-cont result, polynomial order 3')\n", " plot_ms_data(ms_uvcont, 'data_spectrum')\n", "\n", "except ImportError as exc:\n", " print('Import error, most likely related to casatasks/tools not yet including '\n", " f'new uvcontsub: {exc}')" ] }, { "cell_type": "markdown", "source": [ "# Produce simulated MeasurementSets - for further testing and characterization" ], "metadata": { "id": "vJoVKr9xx8NW" } }, { "cell_type": "markdown", "source": [ "As opposed to the MSs produced for the task verification test, in the following functions we produce MSs without adding polynomials to the real and imaginary part of the visibilities. These MSs can be used to test the behavior of the task with sources " ], "metadata": { "id": "C8XRZ85jyJLW" } }, { "cell_type": "code", "source": [ "def make_test_ms_alma_further(ms_name, noise_sigma='0.5Jy', verbose=True):\n", " \"\"\"\n", " Adds a point source, a spectral line, noise\n", "\n", " Args:\n", " noise_sigma: sigma for the Gaussian noise, set to None for no noise\n", " verbose: print and plot what is being done\n", " \"\"\"\n", " ant_config = 'alma.cycle8.8.cfg'\n", " spw_params = {'name': \"Simulated_Band\",\n", " 'freq': '150GHz',\n", " 'nchan': 128}\n", "\n", " make_ms_frame(ms_name, ant_config=ant_config, spw_params=spw_params)\n", "\n", " add_point_source_component(ms_name, freq='125GHz', flux=0.5, \n", " spectrumtype='spectral index', index=-1.1)\n", "\n", " if verbose:\n", " print('Data plots. Only point source:')\n", " plot_ms_data(ms_name, 'data_spectrum')\n", "\n", " add_spectral_line(ms_name, chan_range=[60,86])\n", " if verbose:\n", " print('Data plots, + spectral line, width ~20% band:')\n", " plot_ms_data(ms_name, 'data_spectrum')\n", "\n", " if noise_sigma:\n", " add_ms_gaussian_noise(ms_name, noise_sigma)\n", " if verbose:\n", " print('Data plots + Gaussian noise:')\n", " plot_ms_data(ms_name, 'data_spectrum')" ], "metadata": { "id": "lB2Cp0lIyHko" }, "execution_count": 47, "outputs": [] }, { "cell_type": "markdown", "source": [ "## Simple MSs" ], "metadata": { "id": "0EQ_Ude_0xZE" } }, { "cell_type": "code", "source": [ "ms_name = 'sim_alma_source_phase_center_nonoise.ms'\n", "make_test_ms_alma_further(ms_name, noise_sigma=None, verbose=False)\n", "print('Plotting no-noise MS, with spectral index source')\n", "plot_ms_data(ms_name, 'data_spectrum')\n", "\n", "ms_name = 'sim_alma_source_phase_center_noise.ms'\n", "make_test_ms_alma_further(ms_name, noise_sigma='0.1Jy', verbose=False)\n", "print('Plotting no-noise MS, with spectral index source')\n", "plot_ms_data(ms_name, 'data_spectrum')" ], "metadata": { "id": "H0nC8mGc0zq0", "outputId": "8a34aa94-5da3-4842-e55a-8a5841b623ac", "colab": { "base_uri": "https://localhost:8080/", "height": 610 } }, "execution_count": 48, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Plotting no-noise MS, with spectral index source\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } }, { "output_type": "stream", "name": "stdout", "text": [ "Plotting no-noise MS, with spectral index source\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": { "needs_background": "light" } } ] } ], "metadata": { "colab": { "collapsed_sections": [ "zPyD7q_xIHxG", "CCG3b_GyQ5R7" ], "name": "simulations_uvcontsub_ALMA_WIP.ipynb", "provenance": [], "toc_visible": true }, "kernelspec": { "display_name": "Python 3", "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": "3.6.7" } }, "nbformat": 4, "nbformat_minor": 0 }