#!/usr/bin/env python
#
# Copyright 2004,2005,2007,2010,2012,2013,2014 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 gnuradio import gr, gr_unittest, blocks
import pmt
import os

class test_stream_mux (gr_unittest.TestCase):

    def setUp (self):
        os.environ['GR_CONF_CONTROLPORT_ON'] = 'False'
        self.tb = gr.top_block ()

    def tearDown (self):
        self.tb = None

    def help_stream_2ff(self, N, stream_sizes):
        v0 = blocks.vector_source_f(N*[1,], False)
        v1 = blocks.vector_source_f(N*[2,], False)

        mux = blocks.stream_mux(gr.sizeof_float, stream_sizes)

        dst = blocks.vector_sink_f ()

        self.tb.connect (v0, (mux,0))
        self.tb.connect (v1, (mux,1))
        self.tb.connect (mux, dst)
        self.tb.run ()

        return dst.data ()

    def help_stream_ramp_2ff(self, N, stream_sizes):
        r1 = list(range(N))
        r2 = list(range(N))
        r2.reverse()

        v0 = blocks.vector_source_f(r1, False)
        v1 = blocks.vector_source_f(r2, False)

        mux = blocks.stream_mux(gr.sizeof_float, stream_sizes)

        dst = blocks.vector_sink_f ()

        self.tb.connect (v0, (mux,0))
        self.tb.connect (v1, (mux,1))
        self.tb.connect (mux, dst)
        self.tb.run ()

        return dst.data ()

    def help_stream_tag_propagation(self, N, stream_sizes):
        src_data1           = stream_sizes[0]*N*[1,]
        src_data2           = stream_sizes[1]*N*[2,]
        src_data3           = stream_sizes[2]*N*[3,]
    # stream_mux scheme (3,2,4)
        src1 = blocks.vector_source_f(src_data1)
        src2 = blocks.vector_source_f(src_data2)
        src3 = blocks.vector_source_f(src_data3)
        tag_stream1 = blocks.stream_to_tagged_stream(gr.sizeof_float, 1,
                                                     stream_sizes[0], 'src1')
        tag_stream2 = blocks.stream_to_tagged_stream(gr.sizeof_float, 1,
                                                     stream_sizes[1], 'src2')
        tag_stream3 = blocks.stream_to_tagged_stream(gr.sizeof_float, 1,
                                                     stream_sizes[2], 'src3')

        mux = blocks.stream_mux(gr.sizeof_float, stream_sizes)
        dst = blocks.vector_sink_f()

        self.tb.connect(src1, tag_stream1)
        self.tb.connect(src2, tag_stream2)
        self.tb.connect(src3, tag_stream3)
        self.tb.connect(tag_stream1, (mux,0))
        self.tb.connect(tag_stream2, (mux,1))
        self.tb.connect(tag_stream3, (mux,2))
        self.tb.connect(mux, dst)
        self.tb.run()

        return (dst.data (), dst.tags ())


    def test_stream_2NN_ff(self):
        N = 40
        stream_sizes = [10, 10]
        result_data = self.help_stream_2ff(N, stream_sizes)

        exp_data = (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0)
        self.assertEqual (exp_data, result_data)

    def test_stream_ramp_2NN_ff(self):
        N = 40
        stream_sizes = [10, 10]
        result_data = self.help_stream_ramp_2ff(N, stream_sizes)

        exp_data = ( 0.0,  1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0,
                    39.0, 38.0, 37.0, 36.0, 35.0, 34.0, 33.0, 32.0, 31.0, 30.0,
                    10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0,
                    29.0, 28.0, 27.0, 26.0, 25.0, 24.0, 23.0, 22.0, 21.0, 20.0,
                    20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0,
                    19.0, 18.0, 17.0, 16.0, 15.0, 14.0, 13.0, 12.0, 11.0, 10.0,
                    30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0,
                     9.0,  8.0,  7.0,  6.0,  5.0,  4.0,  3.0,  2.0,  1.0,  0.0)
        self.assertEqual (exp_data, result_data)

    def test_stream_2NM_ff(self):
        N = 40
        stream_sizes = [7, 9]
        self.help_stream_2ff(N, stream_sizes)

        result_data = self.help_stream_2ff(N, stream_sizes)

        exp_data = (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0)

        self.assertEqual (exp_data, result_data)


    def test_stream_2MN_ff(self):
        N = 37
        stream_sizes = [7, 9]
        self.help_stream_2ff(N, stream_sizes)

        result_data = self.help_stream_2ff(N, stream_sizes)

        exp_data = (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    2.0)

        self.assertEqual (exp_data, result_data)

    def test_stream_2N0_ff(self):
        N = 30
        stream_sizes = [7, 0]
        self.help_stream_2ff(N, stream_sizes)

        result_data = self.help_stream_2ff(N, stream_sizes)

        exp_data = (1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                    1.0, 1.0)

        self.assertEqual (exp_data, result_data)

    def test_stream_20N_ff(self):
        N = 30
        stream_sizes = [0, 9]
        self.help_stream_2ff(N, stream_sizes)

        result_data = self.help_stream_2ff(N, stream_sizes)

        exp_data = (2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
                    2.0, 2.0, 2.0)

        self.assertEqual (exp_data, result_data)

    def test_largeN_ff(self):
        stream_sizes = [3, 8191]
        r1 = (1,) * stream_sizes[0]
        r2 = (2,) * stream_sizes[1]
        v0 = blocks.vector_source_f(r1, repeat=False)
        v1 = blocks.vector_source_f(r2, repeat=False)
        mux = blocks.stream_mux(gr.sizeof_float, stream_sizes)
        dst = blocks.vector_sink_f ()
        self.tb.connect (v0, (mux,0))
        self.tb.connect (v1, (mux,1))
        self.tb.connect (mux, dst)
        self.tb.run ()
        self.assertEqual (r1 + r2, dst.data())

    def test_tag_propagation(self):
        N = 10 # Block length
        stream_sizes = [1,2,3]

        expected_result     = N*(stream_sizes[0]*[1,]
                                 +stream_sizes[1]*[2,]
                                 +stream_sizes[2]*[3,])
        # check the data
        (result, tags) = self.help_stream_tag_propagation(N, stream_sizes)
        self.assertFloatTuplesAlmostEqual(expected_result, result, places=6)

        # check the tags
        expected_tag_offsets_src1 = [sum(stream_sizes)*i for i in range(N)]
        expected_tag_offsets_src2 = [stream_sizes[0]
                                     +sum(stream_sizes)*i for i in range(N)]
        expected_tag_offsets_src3 = [stream_sizes[0]+stream_sizes[1]
                                     +sum(stream_sizes)*i for i in range(N)]
        tags_src1 = [tag for tag in tags if tag.key == 'src1']
        tags_src2 = [tag for tag in tags if tag.key == 'src2']
        tags_src3 = [tag for tag in tags if tag.key == 'src3']

        for i in range(len(expected_tag_offsets_src1)):
            self.assertTrue(expected_tag_offsets_src1[i] == tags_src1[i].offset)
        for i in range(len(expected_tag_offsets_src2)):
            self.assertTrue(expected_tag_offsets_src2[i] == tags_src2[i].offset)
        for i in range(len(expected_tag_offsets_src3)):
            self.assertTrue(expected_tag_offsets_src3[i] == tags_src3[i].offset)

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