#!/usr/bin/env python
#
# Copyright 2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your option)
# any later version.
#
# GNU Radio is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with GNU Radio; see the file COPYING.  If not, write to
# the Free Software Foundation, Inc., 51 Franklin Street,
# Boston, MA 02110-1301, USA.
#

from __future__ import division

from gnuradio import gr, gr_unittest, filter, blocks
import math

def sig_source_c(samp_rate, freq, amp, N):
    t = [float(x) / samp_rate for x in range(N)]
    y = [math.cos(2.*math.pi*freq*x) + \
                1j*math.sin(2.*math.pi*freq*x) for x in t]
    return y

def sig_source_f(samp_rate, freq, amp, N):
    t = [float(x) / samp_rate for x in range(N)]
    y = [math.sin(2.*math.pi*freq*x) for x in t]
    return y

class test_pfb_arb_resampler(gr_unittest.TestCase):

    def setUp(self):
        self.tb = gr.top_block()

    def tearDown(self):
        self.tb = None

    def test_fff_000(self):
        N = 500         # number of samples to use
        fs = 5000.0     # baseband sampling rate
        rrate = 2.3421  # resampling rate

        nfilts = 32
        taps = filter.firdes.low_pass_2(nfilts, nfilts*fs, fs / 2, fs / 10,
                                        attenuation_dB=80,
                                        window=filter.firdes.WIN_BLACKMAN_hARRIS)

        freq = 121.213
        data = sig_source_f(fs, freq, 1, N)
        signal = blocks.vector_source_f(data)
        pfb = filter.pfb_arb_resampler_fff(rrate, taps, nfilts)
        snk = blocks.vector_sink_f()

        self.tb.connect(signal, pfb, snk)
        self.tb.run()

        Ntest = 50
        L = len(snk.data())

        # Get group delay and estimate of phase offset from the filter itself.
        delay = pfb.group_delay()
        phase = pfb.phase_offset(freq, fs)

        # Create a timeline offset by the filter's group delay
        t = [float(x) / (fs*rrate) for x in range(-delay, L-delay)]

        # Data of the sinusoid at frequency freq with the delay and phase offset.
        expected_data = [math.sin(2.*math.pi*freq*x+phase) for x in t]

        dst_data = snk.data()

        self.assertFloatTuplesAlmostEqual(expected_data[-Ntest:], dst_data[-Ntest:], 2)

    def test_ccf_000(self):
        N = 5000         # number of samples to use
        fs = 5000.0      # baseband sampling rate
        rrate = 2.4321   # resampling rate

        nfilts = 32
        taps = filter.firdes.low_pass_2(nfilts, nfilts*fs, fs / 2, fs / 10,
                                        attenuation_dB=80,
                                        window=filter.firdes.WIN_BLACKMAN_hARRIS)

        freq = 211.123
        data = sig_source_c(fs, freq, 1, N)
        signal = blocks.vector_source_c(data)
        pfb = filter.pfb_arb_resampler_ccf(rrate, taps, nfilts)
        snk = blocks.vector_sink_c()

        self.tb.connect(signal, pfb, snk)
        self.tb.run()

        Ntest = 50
        L = len(snk.data())

        # Get group delay and estimate of phase offset from the filter itself.
        delay = pfb.group_delay()
        phase = pfb.phase_offset(freq, fs)

        # Create a timeline offset by the filter's group delay
        t = [float(x) / (fs*rrate) for x in range(-delay, L-delay)]

        # Data of the sinusoid at frequency freq with the delay and phase offset.
        expected_data = [math.cos(2.*math.pi*freq*x+phase) + \
                                1j*math.sin(2.*math.pi*freq*x+phase) for x in t]

        dst_data = snk.data()

        self.assertComplexTuplesAlmostEqual(expected_data[-Ntest:], dst_data[-Ntest:], 2)

    def test_ccf_001(self):
        N = 50000        # number of samples to use
        fs = 5000.0      # baseband sampling rate
        rrate = 0.75     # resampling rate

        nfilts = 32
        taps = filter.firdes.low_pass_2(nfilts, nfilts*fs, fs / 4, fs / 10,
                                        attenuation_dB=80,
                                        window=filter.firdes.WIN_BLACKMAN_hARRIS)

        freq = 211.123
        data = sig_source_c(fs, freq, 1, N)
        signal = blocks.vector_source_c(data)
        pfb = filter.pfb_arb_resampler_ccf(rrate, taps, nfilts)
        snk = blocks.vector_sink_c()

        self.tb.connect(signal, pfb, snk)
        self.tb.run()

        Ntest = 50
        L = len(snk.data())

        # Get group delay and estimate of phase offset from the filter itself.
        delay = pfb.group_delay()
        phase = pfb.phase_offset(freq, fs)

        # Create a timeline offset by the filter's group delay
        t = [float(x) / (fs*rrate) for x in range(-delay, L-delay)]

        # Data of the sinusoid at frequency freq with the delay and phase offset.
        expected_data = [math.cos(2.*math.pi*freq*x+phase) + \
                                1j*math.sin(2.*math.pi*freq*x+phase) for x in t]

        dst_data = snk.data()

        self.assertComplexTuplesAlmostEqual(expected_data[-Ntest:], dst_data[-Ntest:], 2)

    def test_ccc_000(self):
        N = 5000         # number of samples to use
        fs = 5000.0      # baseband sampling rate
        rrate = 3.4321   # resampling rate

        nfilts = 32
        taps = filter.firdes.complex_band_pass_2(nfilts, nfilts*fs, 50, 400, fs / 10,
                                                 attenuation_dB=80,
                                                 window=filter.firdes.WIN_BLACKMAN_hARRIS)

        freq = 211.123
        data = sig_source_c(fs, freq, 1, N)
        signal = blocks.vector_source_c(data)
        pfb = filter.pfb_arb_resampler_ccc(rrate, taps, nfilts)
        snk = blocks.vector_sink_c()

        self.tb.connect(signal, pfb, snk)
        self.tb.run()

        Ntest = 50
        L = len(snk.data())

        # Get group delay and estimate of phase offset from the filter itself.
        delay = pfb.group_delay()
        phase = pfb.phase_offset(freq, fs)

        # Create a timeline offset by the filter's group delay
        t = [float(x) / (fs*rrate) for x in range(-delay, L-delay)]

        # Data of the sinusoid at frequency freq with the delay and phase offset.
        expected_data = [math.cos(2.*math.pi*freq*x+phase) + \
                                1j*math.sin(2.*math.pi*freq*x+phase) for x in t]

        dst_data = snk.data()

        self.assertComplexTuplesAlmostEqual(expected_data[-Ntest:], dst_data[-Ntest:], 2)

    def test_ccc_001(self):
        N = 50000        # number of samples to use
        fs = 5000.0      # baseband sampling rate
        rrate = 0.715    # resampling rate

        nfilts = 32
        taps = filter.firdes.complex_band_pass_2(nfilts, nfilts*fs, 50, 400, fs / 10,
                                                 attenuation_dB=80,
                                                 window=filter.firdes.WIN_BLACKMAN_hARRIS)

        freq = 211.123
        data = sig_source_c(fs, freq, 1, N)
        signal = blocks.vector_source_c(data)
        pfb = filter.pfb_arb_resampler_ccc(rrate, taps, nfilts)
        snk = blocks.vector_sink_c()

        self.tb.connect(signal, pfb, snk)
        self.tb.run()

        Ntest = 50
        L = len(snk.data())

        # Get group delay and estimate of phase offset from the filter itself.
        delay = pfb.group_delay()
        phase = pfb.phase_offset(freq, fs)

        # Create a timeline offset by the filter's group delay
        t = [float(x) / (fs*rrate) for x in range(-delay, L-delay)]

        # Data of the sinusoid at frequency freq with the delay and phase offset.
        expected_data = [math.cos(2.*math.pi*freq*x+phase) + \
                                1j*math.sin(2.*math.pi*freq*x+phase) for x in t]

        dst_data = snk.data()

        self.assertComplexTuplesAlmostEqual(expected_data[-Ntest:], dst_data[-Ntest:], 2)

if __name__ == '__main__':
    gr_unittest.run(test_pfb_arb_resampler, "test_pfb_arb_resampler.xml")
