mirror of
https://github.com/gnss-sdr/gnss-sdr
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223 lines
7.2 KiB
C++
223 lines
7.2 KiB
C++
/*!
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* \file tracking_loop_filter_test.cc
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* \brief This file implements tests for the general loop filter
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* \author Cillian O'Driscoll, 2015. cillian.odriscoll(at)gmail.com
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*
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*
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* -------------------------------------------------------------------------
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*
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* Copyright (C) 2010-2015 (see AUTHORS file for a list of contributors)
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*
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* GNSS-SDR is a software defined Global Navigation
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* Satellite Systems receiver
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*
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* This file is part of GNSS-SDR.
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*
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* GNSS-SDR is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* GNSS-SDR is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with GNSS-SDR. If not, see <http://www.gnu.org/licenses/>.
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*
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* -------------------------------------------------------------------------
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*/
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#include "tracking_loop_filter.h"
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#include <gtest/gtest.h>
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TEST(TrackingLoopFilterTest, FirstOrderLoop)
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{
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int loop_order = 1;
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float noise_bandwidth = 5.0;
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float update_interval = 0.001;
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bool include_last_integrator = false;
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Tracking_loop_filter theFilter( update_interval,
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noise_bandwidth,
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loop_order,
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include_last_integrator );
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EXPECT_EQ( theFilter.get_noise_bandwidth(), noise_bandwidth );
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EXPECT_EQ( theFilter.get_update_interval(), update_interval );
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EXPECT_EQ( theFilter.get_include_last_integrator(), include_last_integrator );
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EXPECT_EQ( theFilter.get_order(), loop_order );
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std::vector< float > sample_data = { 0.0, 0.0, 1.0, 0.0, 0.0, 0.0 };
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theFilter.initialize( 0.0 );
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float g1 = noise_bandwidth * 4.0;
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float result = 0.0;
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for( unsigned int i = 0; i < sample_data.size(); ++i )
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{
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result = theFilter.apply( sample_data[i] );
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EXPECT_FLOAT_EQ( result, sample_data[i]*g1 );
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}
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}
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TEST(TrackingLoopFilterTest, FirstOrderLoopWithLastIntegrator)
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{
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int loop_order = 1;
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float noise_bandwidth = 5.0;
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float update_interval = 0.001;
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bool include_last_integrator = true;
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Tracking_loop_filter theFilter( update_interval,
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noise_bandwidth,
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loop_order,
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include_last_integrator );
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EXPECT_EQ( theFilter.get_noise_bandwidth(), noise_bandwidth );
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EXPECT_EQ( theFilter.get_update_interval(), update_interval );
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EXPECT_EQ( theFilter.get_include_last_integrator(), include_last_integrator );
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EXPECT_EQ( theFilter.get_order(), loop_order );
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std::vector< float > sample_data = { 0.0, 0.0, 1.0, 0.0, 0.0, 0.0 };
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std::vector< float > expected_out = { 0.0, 0.0, 0.01, 0.02, 0.02, 0.02 };
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theFilter.initialize( 0.0 );
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float result = 0.0;
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for( unsigned int i = 0; i < sample_data.size(); ++i )
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{
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result = theFilter.apply( sample_data[i] );
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EXPECT_NEAR( result, expected_out[i], 1e-4 );
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}
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}
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TEST(TrackingLoopFilterTest, SecondOrderLoop)
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{
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int loop_order = 2;
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float noise_bandwidth = 5.0;
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float update_interval = 0.001;
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bool include_last_integrator = false;
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Tracking_loop_filter theFilter( update_interval,
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noise_bandwidth,
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loop_order,
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include_last_integrator );
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EXPECT_EQ( theFilter.get_noise_bandwidth(), noise_bandwidth );
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EXPECT_EQ( theFilter.get_update_interval(), update_interval );
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EXPECT_EQ( theFilter.get_include_last_integrator(), include_last_integrator );
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EXPECT_EQ( theFilter.get_order(), loop_order );
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std::vector< float > sample_data = { 0.0, 0.0, 1.0, 0.0, 0.0, 0.0 };
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std::vector< float > expected_out = { 0.0, 0.0, 13.37778, 0.0889, 0.0889, 0.0889 };
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theFilter.initialize( 0.0 );
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float result = 0.0;
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for( unsigned int i = 0; i < sample_data.size(); ++i )
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{
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result = theFilter.apply( sample_data[i] );
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EXPECT_NEAR( result, expected_out[i], 1e-4 );
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}
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}
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TEST(TrackingLoopFilterTest, SecondOrderLoopWithLastIntegrator)
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{
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int loop_order = 2;
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float noise_bandwidth = 5.0;
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float update_interval = 0.001;
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bool include_last_integrator = true;
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Tracking_loop_filter theFilter( update_interval,
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noise_bandwidth,
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loop_order,
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include_last_integrator );
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EXPECT_EQ( theFilter.get_noise_bandwidth(), noise_bandwidth );
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EXPECT_EQ( theFilter.get_update_interval(), update_interval );
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EXPECT_EQ( theFilter.get_include_last_integrator(), include_last_integrator );
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EXPECT_EQ( theFilter.get_order(), loop_order );
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std::vector< float > sample_data = { 0.0, 0.0, 1.0, 0.0, 0.0, 0.0 };
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std::vector< float > expected_out = { 0.0, 0.0, 0.006689, 0.013422, 0.013511, 0.013600 };
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theFilter.initialize( 0.0 );
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float result = 0.0;
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for( unsigned int i = 0; i < sample_data.size(); ++i )
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{
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result = theFilter.apply( sample_data[i] );
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EXPECT_NEAR( result, expected_out[i], 1e-4 );
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}
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}
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TEST(TrackingLoopFilterTest, ThirdOrderLoop)
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{
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int loop_order = 3;
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float noise_bandwidth = 5.0;
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float update_interval = 0.001;
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bool include_last_integrator = false;
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Tracking_loop_filter theFilter( update_interval,
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noise_bandwidth,
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loop_order,
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include_last_integrator );
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EXPECT_EQ( theFilter.get_noise_bandwidth(), noise_bandwidth );
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EXPECT_EQ( theFilter.get_update_interval(), update_interval );
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EXPECT_EQ( theFilter.get_include_last_integrator(), include_last_integrator );
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EXPECT_EQ( theFilter.get_order(), loop_order );
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std::vector< float > sample_data = { 0.0, 0.0, 1.0, 0.0, 0.0, 0.0 };
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std::vector< float > expected_out = { 0.0, 0.0, 15.31877, 0.04494, 0.04520, 0.04546};
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theFilter.initialize( 0.0 );
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float result = 0.0;
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for( unsigned int i = 0; i < sample_data.size(); ++i )
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{
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result = theFilter.apply( sample_data[i] );
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EXPECT_NEAR( result, expected_out[i], 1e-4 );
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}
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}
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TEST(TrackingLoopFilterTest, ThirdOrderLoopWithLastIntegrator)
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{
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int loop_order = 3;
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float noise_bandwidth = 5.0;
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float update_interval = 0.001;
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bool include_last_integrator = true;
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Tracking_loop_filter theFilter( update_interval,
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noise_bandwidth,
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loop_order,
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include_last_integrator );
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EXPECT_EQ( theFilter.get_noise_bandwidth(), noise_bandwidth );
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EXPECT_EQ( theFilter.get_update_interval(), update_interval );
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EXPECT_EQ( theFilter.get_include_last_integrator(), include_last_integrator );
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EXPECT_EQ( theFilter.get_order(), loop_order );
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std::vector< float > sample_data = { 0.0, 0.0, 1.0, 0.0, 0.0, 0.0 };
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std::vector< float > expected_out = { 0.0, 0.0, 0.007659, 0.015341, 0.015386, 0.015432};
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theFilter.initialize( 0.0 );
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float result = 0.0;
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for( unsigned int i = 0; i < sample_data.size(); ++i )
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{
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result = theFilter.apply( sample_data[i] );
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EXPECT_NEAR( result, expected_out[i], 1e-4 );
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}
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}
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