#!/usr/bin/python

# Audio Tools, a module and set of tools for manipulating audio data
# Copyright (C) 2007-2014  Brian Langenberger

# This program 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 2 of the License, or
# (at your option) any later version.

# This program 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 this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA

from audiotools.bitstream import BitstreamWriter
from audiotools.bitstream import BitstreamRecorder
from audiotools.bitstream import format_size
from audiotools import BufferedPCMReader
from hashlib import md5

# sub block IDs
WV_WAVE_HEADER = 0x1
WV_WAVE_FOOTER = 0x2
WV_TERMS = 0x2
WV_WEIGHTS = 0x3
WV_SAMPLES = 0x4
WV_ENTROPY = 0x5
WV_SAMPLE_RATE = 0x7
WV_INT32_INFO = 0x9
WV_BITSTREAM = 0xA
WV_CHANNEL_INFO = 0xD
WV_MD5 = 0x6


class EncoderContext(object):
    def __init__(self, pcmreader, block_parameters,
                 wave_header=None, wave_footer=None):
        self.pcmreader = pcmreader
        self.block_parameters = block_parameters
        self.total_frames = 0
        self.block_offsets = []
        self.md5sum = md5()
        self.first_block_written = False
        self.wave_header = wave_header
        self.wave_footer = wave_footer


def write_wave_header(writer, pcmreader, total_frames, wave_footer_len):
    avg_bytes_per_second = (pcmreader.sample_rate *
                            pcmreader.channels *
                            (pcmreader.bits_per_sample // 8))
    block_align = (pcmreader.channels *
                   (pcmreader.bits_per_sample // 8))

    total_size = 4 * 3   # 'RIFF' + size + 'WAVE'

    total_size += 4 * 2  # 'fmt ' + size
    if ((pcmreader.channels <= 2) and (pcmreader.bits_per_sample <= 16)):
        # classic fmt chunk
        fmt = "16u 16u 32u 32u 16u 16u"
        fmt_fields = (1,   # compression code
                      pcmreader.channels,
                      pcmreader.sample_rate,
                      avg_bytes_per_second,
                      block_align,
                      pcmreader.bits_per_sample)

    else:
        # extended fmt chunk
        fmt = "16u 16u 32u 32u 16u 16u" + "16u 16u 32u 16b"
        fmt_fields = (0xFFFE,   # compression code
                      pcmreader.channels,
                      pcmreader.sample_rate,
                      avg_bytes_per_second,
                      block_align,
                      pcmreader.bits_per_sample,
                      22,       # CB size
                      pcmreader.bits_per_sample,
                      int(pcmreader.channel_mask),
                      '\x01\x00\x00\x00\x00\x00\x10\x00' +
                      '\x80\x00\x00\xaa\x00\x38\x9b\x71'  # sub format
                      )
    total_size += format_size(fmt) // 8

    total_size += 4 * 2  # 'data' + size
    data_size = (total_frames *
                 pcmreader.channels *
                 (pcmreader.bits_per_sample // 8))
    total_size += data_size

    total_size += wave_footer_len

    writer.build("4b 32u 4b 4b 32u" + fmt + "4b 32u",
                 (('RIFF', total_size - 8, 'WAVE',
                   'fmt ', format_size(fmt) // 8) + fmt_fields +
                  ('data', data_size)))


class CorrelationParameters(object):
    """the parameters for a single correlation pass"""

    def __init__(self, term, delta, weights, samples):
        """term is a signed integer
        delta is an unsigned integer
        weights[c] is a weight value per channel c
        samples[c][s] is sample "s" for channel "c"
        """

        # FIXME - sanity check these

        self.term = term
        self.delta = delta
        self.weights = weights
        self.samples = samples

    def __repr__(self):
        return "CorrelationParameters(%s, %s, %s, %s)" % \
            (self.term, self.delta, self.weights, self.samples)

    def update_weights(self, weights):
        """given a weights[c] list of weight values per channel c
        round-trips and sets this parameter's weights"""

        assert(len(weights) == len(self.weights))
        self.weights = [restore_weight(store_weight(w))
                        for w in weights]

    def update_samples(self, samples):
        """given a samples[c][s] list of sample lists
        round-trips and sets this parameter's samples"""

        assert(len(samples) == len(samples))
        self.samples = [[wv_exp2(wv_log2(s)) for s in c]
                        for c in samples]


class EncodingParameters(object):
    """the encoding parameters for a single 1-2 channel block
    multi-channel audio may have more than one set of these
    """

    def __init__(self, channel_count, correlation_passes):
        """channel_count is 1 or 2
        correlation_passes is in [0,1,2,5,10,16]
        """

        assert((channel_count == 1) or (channel_count == 2))
        assert(correlation_passes in (0, 1, 2, 5, 10, 16))

        self.channel_count = channel_count
        self.correlation_passes = correlation_passes
        self.entropy_variables = [[0, 0, 0], [0, 0, 0]]

        self.__parameters_channel_count__ = 0
        self.__correlation_parameters__ = None

    def __repr__(self):
        return "EncodingParameters(%s, %s, %s)" % \
            (self.channel_count,
             self.correlation_passes,
             self.entropy_variables)

    def correlation_parameters(self, false_stereo):
        """given a "false_stereo" boolean
        yields a CorrelationParameters object per correlation pass to be run

        this may be less than the object's "correlation_passes" count
        if "channel_count" is 1 or "false_stereo" is True
        """

        if ((self.channel_count == 2) and (not false_stereo)):
            channel_count = 2
        else:
            channel_count = 1

        if (channel_count != self.__parameters_channel_count__):
            if (channel_count == 1):
                if (self.correlation_passes == 0):
                    self.__correlation_parameters__ = []
                elif (self.correlation_passes == 1):
                    self.__correlation_parameters__ = [
                        CorrelationParameters(18, 2, [0], [[0] * 2])]
                elif (self.correlation_passes == 2):
                    self.__correlation_parameters__ = [
                        CorrelationParameters(17, 2, [0], [[0] * 2]),
                        CorrelationParameters(18, 2, [0], [[0] * 2])]
                elif (self.correlation_passes in (5, 10, 16)):
                    self.__correlation_parameters__ = [
                        CorrelationParameters(3, 2, [0], [[0] * 3]),
                        CorrelationParameters(17, 2, [0], [[0] * 2]),
                        CorrelationParameters(2, 2, [0], [[0] * 2]),
                        CorrelationParameters(18, 2, [0], [[0] * 2]),
                        CorrelationParameters(18, 2, [0], [[0] * 2])]
                else:
                    raise ValueError("invalid correlation pass count")
            elif (channel_count == 2):
                if (self.correlation_passes == 0):
                    self.__correlation_parameters__ = []
                elif (self.correlation_passes == 1):
                    self.__correlation_parameters__ = [
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2])]
                elif (self.correlation_passes == 2):
                    self.__correlation_parameters__ = [
                        CorrelationParameters(17, 2, [0, 0], [[0] * 2,
                                                              [0] * 2]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2])]
                elif (self.correlation_passes == 5):
                    self.__correlation_parameters__ = [
                        CorrelationParameters(3, 2, [0, 0], [[0] * 3,
                                                             [0] * 3]),
                        CorrelationParameters(17, 2, [0, 0], [[0] * 2,
                                                              [0] * 2]),
                        CorrelationParameters(2, 2, [0, 0], [[0] * 2,
                                                             [0] * 2]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2])]
                elif (self.correlation_passes == 10):
                    self.__correlation_parameters__ = [
                        CorrelationParameters(4, 2, [0, 0], [[0] * 4,
                                                             [0] * 4]),
                        CorrelationParameters(17, 2, [0, 0], [[0] * 2,
                                                              [0] * 2]),
                        CorrelationParameters(-1, 2, [0, 0], [[0] * 1,
                                                              [0] * 1]),
                        CorrelationParameters(5, 2, [0, 0], [[0] * 5,
                                                             [0] * 5]),
                        CorrelationParameters(3, 2, [0, 0], [[0] * 3,
                                                             [0] * 3]),
                        CorrelationParameters(2, 2, [0, 0], [[0] * 2,
                                                             [0] * 2]),
                        CorrelationParameters(-2, 2, [0, 0], [[0] * 1,
                                                              [0] * 1]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2])]
                elif (self.correlation_passes == 16):
                    self.__correlation_parameters__ = [
                        CorrelationParameters(2, 2, [0, 0], [[0] * 2,
                                                             [0] * 2]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2]),
                        CorrelationParameters(-1, 2, [0, 0], [[0] * 1,
                                                              [0] * 1]),
                        CorrelationParameters(8, 2, [0, 0], [[0] * 8,
                                                             [0] * 8]),
                        CorrelationParameters(6, 2, [0, 0], [[0] * 6,
                                                             [0] * 6]),
                        CorrelationParameters(3, 2, [0, 0], [[0] * 3,
                                                             [0] * 3]),
                        CorrelationParameters(5, 2, [0, 0], [[0] * 5,
                                                             [0] * 5]),
                        CorrelationParameters(7, 2, [0, 0], [[0] * 7,
                                                             [0] * 7]),
                        CorrelationParameters(4, 2, [0, 0], [[0] * 4,
                                                             [0] * 4]),
                        CorrelationParameters(2, 2, [0, 0], [[0] * 2,
                                                             [0] * 2]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2]),
                        CorrelationParameters(-2, 2, [0, 0], [[0] * 1,
                                                              [0] * 1]),
                        CorrelationParameters(3, 2, [0, 0], [[0] * 3,
                                                             [0] * 3]),
                        CorrelationParameters(2, 2, [0, 0], [[0] * 2,
                                                             [0] * 2]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2]),
                        CorrelationParameters(18, 2, [0, 0], [[0] * 2,
                                                              [0] * 2])]
                else:
                    raise ValueError("invalid correlation pass count")

        for parameters in self.__correlation_parameters__:
            yield parameters


def block_parameters(channel_count, channel_mask, correlation_passes):
    if (channel_count == 1):
        return [EncodingParameters(1, correlation_passes)]
    elif (channel_count == 2):
        return [EncodingParameters(2, correlation_passes)]
    elif ((channel_count == 3) and (channel_mask == 0x7)):
        # front left, front right, front center
        return [EncodingParameters(2, correlation_passes),
                EncodingParameters(1, correlation_passes)]
    elif ((channel_count == 4) and (channel_mask == 0x33)):
        # front left, front right, back left, back right
        return [EncodingParameters(2, correlation_passes),
                EncodingParameters(2, correlation_passes)]
    elif ((channel_count == 4) and (channel_mask == 0x107)):
        # front left, front right, front center, back center
        return [EncodingParameters(2, correlation_passes),
                EncodingParameters(1, correlation_passes),
                EncodingParameters(1, correlation_passes)]
    elif ((channel_count == 5) and (channel_mask == 0x37)):
        # front left, front right, front center, back left, back right
        return [EncodingParameters(2, correlation_passes),
                EncodingParameters(1, correlation_passes),
                EncodingParameters(2, correlation_passes)]
    elif ((channel_count == 6) and (channel_mask == 0x3F)):
        # front left, front right, front center, LFE, back left, back right
        return [EncodingParameters(2, correlation_passes),
                EncodingParameters(1, correlation_passes),
                EncodingParameters(1, correlation_passes),
                EncodingParameters(2, correlation_passes)]
    else:
        return [EncodingParameters(1, correlation_passes)
                for c in range(channel_count)]


def encode_wavpack(filename,
                   pcmreader,
                   block_size,
                   total_pcm_frames=0,
                   false_stereo=False,
                   wasted_bits=False,
                   joint_stereo=False,
                   correlation_passes=0,
                   wave_header=None,
                   wave_footer=None):
    pcmreader = BufferedPCMReader(pcmreader)
    output_file = open(filename, "wb")
    writer = BitstreamWriter(output_file, 1)
    context = EncoderContext(pcmreader,
                             block_parameters(pcmreader.channels,
                                              pcmreader.channel_mask,
                                              correlation_passes),
                             wave_header,
                             wave_footer)

    block_index = 0

    # walk through PCM reader's FrameLists
    frame = pcmreader.read(block_size)
    while (len(frame) > 0):
        context.total_frames += frame.frames
        context.md5sum.update(
            frame.to_bytes(False, pcmreader.bits_per_sample >= 16))

        c = 0
        for parameters in context.block_parameters:
            if (parameters.channel_count == 1):
                channel_data = [list(frame.channel(c))]
            else:
                channel_data = [list(frame.channel(c)),
                                list(frame.channel(c + 1))]

            first_block = parameters is context.block_parameters[0]
            last_block = parameters is context.block_parameters[-1]

            if (total_pcm_frames == 0):
                context.block_offsets.append(output_file.tell())
            write_block(writer,
                        context,
                        channel_data,
                        total_pcm_frames,
                        block_index,
                        first_block,
                        last_block,
                        parameters)

            c += parameters.channel_count

        block_index += frame.frames
        frame = pcmreader.read(block_size)

    # write MD5 sum and optional Wave footer in final block
    sub_blocks = BitstreamRecorder(1)
    sub_block = BitstreamRecorder(1)

    sub_block.reset()
    sub_block.write_bytes(context.md5sum.digest())
    write_sub_block(sub_blocks, WV_MD5, 1, sub_block)

    # write Wave footer in final block, if present
    if (context.wave_footer is not None):
        sub_block.reset()
        sub_block.write_bytes(context.wave_footer)
        write_sub_block(sub_blocks, WV_WAVE_FOOTER, 1, sub_block)

    if (total_pcm_frames == 0):
        context.block_offsets.append(output_file.tell())
    write_block_header(
        writer,
        sub_blocks.bytes(),
        (total_pcm_frames if (total_pcm_frames > 0) else 0xFFFFFFFF),
        0xFFFFFFFF,
        0,
        pcmreader.bits_per_sample,
        1,
        0,
        0,
        0,
        1,
        1,
        0,
        pcmreader.sample_rate,
        0,
        0xFFFFFFFF)
    sub_blocks.copy(writer)

    # update Wave header's "data" chunk size, if generated
    if (context.wave_header is None):
        output_file.seek(32 + 2)
        if (context.wave_footer is None):
            write_wave_header(writer, context.pcmreader,
                              context.total_frames, 0)
        else:
            write_wave_header(writer, context.pcmreader,
                              context.total_frames, len(context.wave_footer))

    # go back and populate block headers with total samples
    for block_offset in context.block_offsets:
        output_file.seek(block_offset + 12, 0)
        writer.write(32, block_index)

    if (total_pcm_frames > 0):
        assert(block_index == total_pcm_frames)

    writer.close()


def write_block(writer,
                context,
                channels,
                total_pcm_frames,
                block_index,
                first_block,
                last_block,
                parameters):
    """writer is a BitstreamWriter-compatible object
    context is an EncoderContext object
    channels[c][s] is sample "s" in channel "c"
    block_index is an integer of the block's offset in PCM frames
    first_block and last_block are flags indicating the block's sequence
    parameters is an EncodingParameters object
    """

    assert((len(channels) == 1) or (len(channels) == 2))

    if ((len(channels) == 1) or (channels[0] == channels[1])):
        # 1 channel block or equivalent
        if (len(channels) == 1):
            false_stereo = 0
        else:
            false_stereo = 1

        # calculate maximum magnitude of channel_0
        magnitude = max(map(bits, channels[0]))

        # determine wasted bits
        wasted = min(map(wasted_bps, channels[0]))
        if (wasted == INFINITY):
            # all samples are 0
            wasted = 0

        # if wasted bits, remove them from channel_0
        if ((wasted > 0) and (wasted != INFINITY)):
            shifted = [[s >> wasted for s in channels[0]]]
        else:
            shifted = [channels[0]]

        # calculate CRC of shifted_0
        crc = calculate_crc(shifted)
    else:
        # 2 channel block
        false_stereo = 0

        # calculate maximum magnitude of channel_0/channel_1
        magnitude = max(max(map(bits, channels[0])),
                        max(map(bits, channels[1])))

        # determine wasted bits
        wasted = min(min(map(wasted_bps, channels[0])),
                     min(map(wasted_bps, channels[1])))
        if (wasted == INFINITY):
            # all samples are 0
            wasted = 0

        # if wasted bits, remove them from channel_0/channel_1
        if (wasted > 0):
            shifted = [[s >> wasted for s in channels[0]],
                       [s >> wasted for s in channels[1]]]
        else:
            shifted = channels

        # calculate CRC of shifted_0/shifted_1
        crc = calculate_crc(shifted)

        # joint stereo conversion of shifted_0/shifted_1 to mid/side channels
        mid_side = joint_stereo(shifted[0], shifted[1])

    sub_blocks = BitstreamRecorder(1)
    sub_block = BitstreamRecorder(1)

    # if first block in file, write Wave header
    if (not context.first_block_written):
        sub_block.reset()
        if (context.wave_header is None):
            if (context.wave_footer is None):
                write_wave_header(sub_block, context.pcmreader, 0, 0)
            else:
                write_wave_header(sub_block, context.pcmreader, 0,
                                  len(context.wave_footer))
        else:
            sub_block.write_bytes(context.wave_header)
        write_sub_block(sub_blocks, WV_WAVE_HEADER, 1, sub_block)
        context.first_block_written = True

    # if correlation passes, write three sub blocks of pass data
    if (parameters.correlation_passes > 0):
        sub_block.reset()
        write_correlation_terms(
            sub_block,
            [p.term for p in
             parameters.correlation_parameters(false_stereo)],
            [p.delta for p in
             parameters.correlation_parameters(false_stereo)])
        write_sub_block(sub_blocks, WV_TERMS, 0, sub_block)

        sub_block.reset()
        write_correlation_weights(
            sub_block,
            [p.weights for p in
             parameters.correlation_parameters(false_stereo)])
        write_sub_block(sub_blocks, WV_WEIGHTS, 0, sub_block)

        sub_block.reset()
        write_correlation_samples(
            sub_block,
            [p.term for p in
             parameters.correlation_parameters(false_stereo)],
            [p.samples for p in
             parameters.correlation_parameters(false_stereo)],
            2 if ((len(channels) == 2) and (not false_stereo)) else 1)
        write_sub_block(sub_blocks, WV_SAMPLES, 0, sub_block)

    # if wasted bits, write extended integers sub block
    if (wasted > 0):
        sub_block.reset()
        write_extended_integers(sub_block, 0, wasted, 0, 0)
        write_sub_block(sub_blocks, WV_INT32_INFO, 0, sub_block)

    # if channel count > 2, write channel info sub block
    if (context.pcmreader.channels > 2):
        sub_block.reset()
        sub_block.write(8, context.pcmreader.channels)
        sub_block.write(32, context.pcmreader.channel_mask)
        write_sub_block(sub_blocks, WV_CHANNEL_INFO, 0, sub_block)

    # if nonstandard sample rate, write sample rate sub block
    if (context.pcmreader.sample_rate not in
        (6000, 8000, 9600, 11025, 12000, 16000, 22050, 24000,
         32000, 44100, 48000, 64000, 88200, 96000, 192000)):
        sub_block.reset()
        sub_block.write(32, context.pcmreader.sample_rate)
        write_sub_block(sub_blocks, WV_SAMPLE_RATE, 1, sub_block)

    if ((len(channels) == 1) or (false_stereo)):
        # 1 channel block

        # correlate shifted_0 with terms/deltas/weights/samples
        if (parameters.correlation_passes > 0):
            assert(len(shifted) == 1)
            correlated = correlate_channels(
                shifted,
                parameters.correlation_parameters(false_stereo),
                1)
        else:
            correlated = shifted
    else:
        # 2 channel block

        # correlate shifted_0/shifted_1 with terms/deltas/weights/samples
        if (parameters.correlation_passes > 0):
            assert(len(mid_side) == 2)
            correlated = correlate_channels(
                mid_side,
                parameters.correlation_parameters(false_stereo),
                2)
        else:
            correlated = mid_side

    # write entropy variables sub block
    sub_block.reset()
    write_entropy_variables(sub_block, correlated,
                            parameters.entropy_variables)
    write_sub_block(sub_blocks, WV_ENTROPY, 0, sub_block)

    # write bitstream sub block
    sub_block.reset()
    write_bitstream(sub_block, correlated,
                    parameters.entropy_variables)
    write_sub_block(sub_blocks, WV_BITSTREAM, 0, sub_block)

    # write block header with size of all sub blocks
    write_block_header(
        writer,
        sub_blocks.bytes(),
        total_pcm_frames,
        block_index,
        len(channels[0]),
        context.pcmreader.bits_per_sample,
        len(channels),
        (len(channels) == 2) and (false_stereo == 0),
        len(set([-1, -2, -3]) &
            set([p.term for p in
                 parameters.correlation_parameters(false_stereo)])) > 0,
        wasted,
        first_block,
        last_block,
        magnitude,
        context.pcmreader.sample_rate,
        false_stereo,
        crc)

    # write sub block data to stream
    sub_blocks.copy(writer)

    # round-trip entropy variables
    parameters.entropy_variables = [
        [wv_exp2(wv_log2(p)) for p in parameters.entropy_variables[0]],
        [wv_exp2(wv_log2(p)) for p in parameters.entropy_variables[1]]]


def bits(sample):
    sample = abs(sample)
    total = 0
    while (sample > 0):
        total += 1
        sample >>= 1
    return total

INFINITY = 2 ** 32


def wasted_bps(sample):
    if (sample == 0):
        return INFINITY
    else:
        total = 0
        while ((sample % 2) == 0):
            total += 1
            sample //= 2
        return total


def calculate_crc(samples):
    crc = 0xFFFFFFFF

    for frame in zip(*samples):
        for s in frame:
            crc = 3 * crc + s

    if (crc >= 0):
        return crc % 0x100000000
    else:
        return (2 ** 32 - (-crc)) % 0x100000000


def joint_stereo(left, right):
    from itertools import izip

    assert(len(left) == len(right))

    mid = []
    side = []
    for (l, r) in izip(left, right):
        mid.append(l - r)
        side.append((l + r) // 2)
    return [mid, side]


def write_block_header(writer,
                       sub_blocks_size,
                       total_pcm_frames,
                       block_index,
                       block_samples,
                       bits_per_sample,
                       channel_count,
                       joint_stereo,
                       cross_channel_decorrelation,
                       wasted_bps,
                       initial_block_in_sequence,
                       final_block_in_sequence,
                       maximum_magnitude,
                       sample_rate,
                       false_stereo,
                       CRC):
    writer.write_bytes("wvpk")              # block ID
    writer.write(32, sub_blocks_size + 24)  # block size
    writer.write(16, 0x0410)                # version
    writer.write(8, 0)                      # track number
    writer.write(8, 0)                      # index number
    writer.write(32, total_pcm_frames)
    writer.write(32, block_index)
    writer.write(32, block_samples)
    writer.write(2, (bits_per_sample // 8) - 1)
    writer.write(1, 2 - channel_count)
    writer.write(1, 0)                      # hybrid mode
    writer.write(1, joint_stereo)
    writer.write(1, cross_channel_decorrelation)
    writer.write(1, 0)                      # hybrid noise shaping
    writer.write(1, 0)                      # floating point data
    if (wasted_bps > 0):                    # extended size integers
        writer.write(1, 1)
    else:
        writer.write(1, 0)
    writer.write(1, 0)                      # hybrid controls bitrate
    writer.write(1, 0)                      # hybrid noise balanced
    writer.write(1, initial_block_in_sequence)
    writer.write(1, final_block_in_sequence)
    writer.write(5, 0)                      # left shift data
    writer.write(5, maximum_magnitude)
    writer.write(4, {6000: 0,
                     8000: 1,
                     9600: 2,
                     11025: 3,
                     12000: 4,
                     16000: 5,
                     22050: 6,
                     24000: 7,
                     32000: 8,
                     44100: 9,
                     48000: 10,
                     64000: 11,
                     88200: 12,
                     96000: 13,
                     192000: 14}.get(sample_rate, 15))
    writer.write(2, 0)                      # reserved
    writer.write(1, 0)                      # use IIR
    writer.write(1, false_stereo)
    writer.write(1, 0)                      # reserved
    writer.write(32, CRC)


def write_sub_block(writer, function, nondecoder_data, recorder):
    recorder.byte_align()

    actual_size_1_less = recorder.bytes() % 2

    writer.build("5u 1u 1u",
                 (function,
                  nondecoder_data,
                  actual_size_1_less))

    if (recorder.bytes() > (255 * 2)):
        writer.write(1, 1)
        writer.write(24, (recorder.bytes() // 2) + actual_size_1_less)
    else:
        writer.write(1, 0)
        writer.write(8, (recorder.bytes() // 2) + actual_size_1_less)

    recorder.copy(writer)

    if (actual_size_1_less):
        writer.write(8, 0)


def write_correlation_terms(writer, correlation_terms, correlation_deltas):
    """correlation_terms[p] and correlation_deltas[p]
    are ints for each correlation pass, in descending order
    writes the terms and deltas to sub block data in the proper order/format"""

    assert(len(correlation_terms) == len(correlation_deltas))

    for (term, delta) in zip(correlation_terms, correlation_deltas):
        writer.write(5, term + 5)
        writer.write(3, delta)


def write_correlation_weights(writer, correlation_weights):
    """correlation_weights[p][c]
    are lists of correlation weight ints for each pass and channel
    in descending order
    writes the weights to sub block data in the proper order/format"""

    for weights in correlation_weights:
        for weight in weights:
            writer.write(8, store_weight(weight))


def store_weight(w):
    w = min(max(w, -1024), 1024)

    if (w > 0):
        return (w - ((w + 2 ** 6) // 2 ** 7) + 4) // (2 ** 3)
    elif (w == 0):
        return 0
    elif (w < 0):
        return (w + 4) // (2 ** 3)


def restore_weight(v):
    if (v > 0):
        return ((v * 2 ** 3) + ((v * 2 ** 3 + 2 ** 6) // 2 ** 7))
    elif(v == 0):
        return 0
    else:
        return v * (2 ** 3)


def write_correlation_samples(writer, correlation_terms, correlation_samples,
                              channel_count):
    """correlation_terms[p] are correlation term ints for each pass

    correlation_samples[p][c][s] are lists of correlation sample ints
    for each pass and channel in descending order

    writes the samples to sub block data in the proper order/format"""

    assert(len(correlation_terms) == len(correlation_samples))

    if (channel_count == 2):
        for (term, samples) in zip(correlation_terms, correlation_samples):
            if ((17 <= term) and (term <= 18)):
                writer.write_signed(16, wv_log2(samples[0][0]))
                writer.write_signed(16, wv_log2(samples[0][1]))
                writer.write_signed(16, wv_log2(samples[1][0]))
                writer.write_signed(16, wv_log2(samples[1][1]))
            elif ((1 <= term) and (term <= 8)):
                for s in range(term):
                    writer.write_signed(16, wv_log2(samples[0][s]))
                    writer.write_signed(16, wv_log2(samples[1][s]))
            elif ((-3 <= term) and (term <= -1)):
                writer.write_signed(16, wv_log2(samples[0][0]))
                writer.write_signed(16, wv_log2(samples[1][0]))
            else:
                raise ValueError("invalid correlation term")
    elif (channel_count == 1):
        for (term, samples) in zip(correlation_terms, correlation_samples):
            if ((17 <= term) and (term <= 18)):
                writer.write_signed(16, wv_log2(samples[0][0]))
                writer.write_signed(16, wv_log2(samples[0][1]))
            elif ((1 <= term) and (term <= 8)):
                for s in range(term):
                    writer.write_signed(16, wv_log2(samples[0][s]))
            else:
                raise ValueError("invalid correlation term")
    else:
        raise ValueError("invalid channel count")


def wv_log2(value):
    from math import log

    a = abs(value) + (abs(value) // 2 ** 9)
    if (a != 0):
        c = int(log(a) / log(2)) + 1
    else:
        c = 0
    if (value > 0):
        if ((0 <= a) and (a < 256)):
            return (c * 2 ** 8) + WLOG[(a * 2 ** (9 - c)) % 256]
        else:
            return (c * 2 ** 8) + WLOG[(a // 2 ** (c - 9)) % 256]
    else:
        if ((0 <= a) and (a < 256)):
            return -((c * 2 ** 8) + WLOG[(a * 2 ** (9 - c)) % 256])
        else:
            return -((c * 2 ** 8) + WLOG[(a // 2 ** (c - 9)) % 256])


WLOG = [0x00, 0x01, 0x03, 0x04, 0x06, 0x07, 0x09, 0x0a,
        0x0b, 0x0d, 0x0e, 0x10, 0x11, 0x12, 0x14, 0x15,
        0x16, 0x18, 0x19, 0x1a, 0x1c, 0x1d, 0x1e, 0x20,
        0x21, 0x22, 0x24, 0x25, 0x26, 0x28, 0x29, 0x2a,
        0x2c, 0x2d, 0x2e, 0x2f, 0x31, 0x32, 0x33, 0x34,
        0x36, 0x37, 0x38, 0x39, 0x3b, 0x3c, 0x3d, 0x3e,
        0x3f, 0x41, 0x42, 0x43, 0x44, 0x45, 0x47, 0x48,
        0x49, 0x4a, 0x4b, 0x4d, 0x4e, 0x4f, 0x50, 0x51,
        0x52, 0x54, 0x55, 0x56, 0x57, 0x58, 0x59, 0x5a,
        0x5c, 0x5d, 0x5e, 0x5f, 0x60, 0x61, 0x62, 0x63,
        0x64, 0x66, 0x67, 0x68, 0x69, 0x6a, 0x6b, 0x6c,
        0x6d, 0x6e, 0x6f, 0x70, 0x71, 0x72, 0x74, 0x75,
        0x76, 0x77, 0x78, 0x79, 0x7a, 0x7b, 0x7c, 0x7d,
        0x7e, 0x7f, 0x80, 0x81, 0x82, 0x83, 0x84, 0x85,
        0x86, 0x87, 0x88, 0x89, 0x8a, 0x8b, 0x8c, 0x8d,
        0x8e, 0x8f, 0x90, 0x91, 0x92, 0x93, 0x94, 0x95,
        0x96, 0x97, 0x98, 0x99, 0x9a, 0x9b, 0x9b, 0x9c,
        0x9d, 0x9e, 0x9f, 0xa0, 0xa1, 0xa2, 0xa3, 0xa4,
        0xa5, 0xa6, 0xa7, 0xa8, 0xa9, 0xa9, 0xaa, 0xab,
        0xac, 0xad, 0xae, 0xaf, 0xb0, 0xb1, 0xb2, 0xb2,
        0xb3, 0xb4, 0xb5, 0xb6, 0xb7, 0xb8, 0xb9, 0xb9,
        0xba, 0xbb, 0xbc, 0xbd, 0xbe, 0xbf, 0xc0, 0xc0,
        0xc1, 0xc2, 0xc3, 0xc4, 0xc5, 0xc6, 0xc6, 0xc7,
        0xc8, 0xc9, 0xca, 0xcb, 0xcb, 0xcc, 0xcd, 0xce,
        0xcf, 0xd0, 0xd0, 0xd1, 0xd2, 0xd3, 0xd4, 0xd4,
        0xd5, 0xd6, 0xd7, 0xd8, 0xd8, 0xd9, 0xda, 0xdb,
        0xdc, 0xdc, 0xdd, 0xde, 0xdf, 0xe0, 0xe0, 0xe1,
        0xe2, 0xe3, 0xe4, 0xe4, 0xe5, 0xe6, 0xe7, 0xe7,
        0xe8, 0xe9, 0xea, 0xea, 0xeb, 0xec, 0xed, 0xee,
        0xee, 0xef, 0xf0, 0xf1, 0xf1, 0xf2, 0xf3, 0xf4,
        0xf4, 0xf5, 0xf6, 0xf7, 0xf7, 0xf8, 0xf9, 0xf9,
        0xfa, 0xfb, 0xfc, 0xfc, 0xfd, 0xfe, 0xff, 0xff]


def wv_exp2(value):
    if ((-32768 <= value) and (value < -2304)):
        return -(WEXP[-value & 0xFF] << ((-value >> 8) - 9))
    elif ((-2304 <= value) and (value < 0)):
        return -(WEXP[-value & 0xFF] >> (9 - (-value >> 8)))
    elif ((0 <= value) and (value <= 2304)):
        return WEXP[value & 0xFF] >> (9 - (value >> 8))
    elif ((2304 < value) and (value <= 32767)):
        return WEXP[value & 0xFF] << ((value >> 8) - 9)


WEXP = [0x100, 0x101, 0x101, 0x102, 0x103, 0x103, 0x104, 0x105,
        0x106, 0x106, 0x107, 0x108, 0x108, 0x109, 0x10a, 0x10b,
        0x10b, 0x10c, 0x10d, 0x10e, 0x10e, 0x10f, 0x110, 0x110,
        0x111, 0x112, 0x113, 0x113, 0x114, 0x115, 0x116, 0x116,
        0x117, 0x118, 0x119, 0x119, 0x11a, 0x11b, 0x11c, 0x11d,
        0x11d, 0x11e, 0x11f, 0x120, 0x120, 0x121, 0x122, 0x123,
        0x124, 0x124, 0x125, 0x126, 0x127, 0x128, 0x128, 0x129,
        0x12a, 0x12b, 0x12c, 0x12c, 0x12d, 0x12e, 0x12f, 0x130,
        0x130, 0x131, 0x132, 0x133, 0x134, 0x135, 0x135, 0x136,
        0x137, 0x138, 0x139, 0x13a, 0x13a, 0x13b, 0x13c, 0x13d,
        0x13e, 0x13f, 0x140, 0x141, 0x141, 0x142, 0x143, 0x144,
        0x145, 0x146, 0x147, 0x148, 0x148, 0x149, 0x14a, 0x14b,
        0x14c, 0x14d, 0x14e, 0x14f, 0x150, 0x151, 0x151, 0x152,
        0x153, 0x154, 0x155, 0x156, 0x157, 0x158, 0x159, 0x15a,
        0x15b, 0x15c, 0x15d, 0x15e, 0x15e, 0x15f, 0x160, 0x161,
        0x162, 0x163, 0x164, 0x165, 0x166, 0x167, 0x168, 0x169,
        0x16a, 0x16b, 0x16c, 0x16d, 0x16e, 0x16f, 0x170, 0x171,
        0x172, 0x173, 0x174, 0x175, 0x176, 0x177, 0x178, 0x179,
        0x17a, 0x17b, 0x17c, 0x17d, 0x17e, 0x17f, 0x180, 0x181,
        0x182, 0x183, 0x184, 0x185, 0x187, 0x188, 0x189, 0x18a,
        0x18b, 0x18c, 0x18d, 0x18e, 0x18f, 0x190, 0x191, 0x192,
        0x193, 0x195, 0x196, 0x197, 0x198, 0x199, 0x19a, 0x19b,
        0x19c, 0x19d, 0x19f, 0x1a0, 0x1a1, 0x1a2, 0x1a3, 0x1a4,
        0x1a5, 0x1a6, 0x1a8, 0x1a9, 0x1aa, 0x1ab, 0x1ac, 0x1ad,
        0x1af, 0x1b0, 0x1b1, 0x1b2, 0x1b3, 0x1b4, 0x1b6, 0x1b7,
        0x1b8, 0x1b9, 0x1ba, 0x1bc, 0x1bd, 0x1be, 0x1bf, 0x1c0,
        0x1c2, 0x1c3, 0x1c4, 0x1c5, 0x1c6, 0x1c8, 0x1c9, 0x1ca,
        0x1cb, 0x1cd, 0x1ce, 0x1cf, 0x1d0, 0x1d2, 0x1d3, 0x1d4,
        0x1d6, 0x1d7, 0x1d8, 0x1d9, 0x1db, 0x1dc, 0x1dd, 0x1de,
        0x1e0, 0x1e1, 0x1e2, 0x1e4, 0x1e5, 0x1e6, 0x1e8, 0x1e9,
        0x1ea, 0x1ec, 0x1ed, 0x1ee, 0x1f0, 0x1f1, 0x1f2, 0x1f4,
        0x1f5, 0x1f6, 0x1f8, 0x1f9, 0x1fa, 0x1fc, 0x1fd, 0x1ff]


def correlate_channels(uncorrelated_samples,
                       correlation_parameters,
                       channel_count):
    """uncorrelated_samples[c][s] is sample 's' for channel 'c'
    correlation_parameters is a list of CorrelationParameters objects
    which are updated by each pass
    returns correlated_samples[c][s] with sample 's' for channel 'c'
    """

    if (channel_count == 1):
        latest_pass = uncorrelated_samples[0]
        for p in correlation_parameters:
            (latest_pass,
             weight,
             samples) = correlation_pass_1ch(latest_pass,
                                             p.term,
                                             p.delta,
                                             p.weights[0],
                                             p.samples[0])
            p.update_weights([weight])
            p.update_samples([samples])
        return [latest_pass]
    else:
        latest_pass = uncorrelated_samples
        for p in correlation_parameters:
            (latest_pass,
             weights,
             samples) = correlation_pass_2ch(latest_pass,
                                             p.term,
                                             p.delta,
                                             p.weights,
                                             p.samples)
            p.update_weights(weights)
            p.update_samples(samples)
        return latest_pass


def correlation_pass_1ch(uncorrelated_samples,
                         term, delta, weight, correlation_samples):
    """given a list of uncorrelated_samples[s]
    term, delta and weight ints
    and a list of correlation_samples[s] ints
    returns a (correlated[s], weight, samples[s]) tuple
    containing correlated samples and updated weight/samples"""

    if (term == 18):
        assert(len(correlation_samples) == 2)
        uncorrelated = ([correlation_samples[1],
                         correlation_samples[0]] +
                        uncorrelated_samples)
        correlated = []
        for i in range(2, len(uncorrelated)):
            temp = (3 * uncorrelated[i - 1] - uncorrelated[i - 2]) // 2
            correlated.append(uncorrelated[i] - apply_weight(weight, temp))
            weight += update_weight(temp, correlated[i - 2], delta)
        return (correlated, weight, list(reversed(correlated[-2:])))
    elif (term == 17):
        assert(len(correlation_samples) == 2)
        uncorrelated = ([correlation_samples[1],
                         correlation_samples[0]] +
                        uncorrelated_samples)
        correlated = []
        for i in range(2, len(uncorrelated)):
            temp = 2 * uncorrelated[i - 1] - uncorrelated[i - 2]
            correlated.append(uncorrelated[i] - apply_weight(weight, temp))
            weight += update_weight(temp, correlated[i - 2], delta)
        return (correlated, weight, list(reversed(correlated[-2:])))
    elif ((1 <= term) and (term <= 8)):
        assert(len(correlation_samples) == term)
        uncorrelated = correlation_samples[:] + uncorrelated_samples
        correlated = []
        for i in range(term, len(uncorrelated)):
            correlated.append(uncorrelated[i] -
                              apply_weight(weight, uncorrelated[i - term]))
            weight += update_weight(uncorrelated[i - term],
                                    correlated[i - term], delta)
        return (correlated, weight, correlated[-term:])
    else:
        raise ValueError("unsupported term")


def correlation_pass_2ch(uncorrelated_samples,
                         term, delta, weights, correlation_samples):
    """given a list of uncorrelated_samples[c][s] lists
    term and delta ints
    a list of weight[c] ints
    and a list of correlation_samples[c][s] lists
    returns (correlated[c][s], weights[c], samples[c][s]) tuple
    containing correlated samples and updated weights/samples"""

    assert(len(uncorrelated_samples) == 2)
    assert(len(uncorrelated_samples[0]) == len(uncorrelated_samples[1]))
    assert(len(weights) == 2)

    if (((17 <= term) and (term <= 18)) or ((1 <= term) and (term <= 8))):
        (uncorrelated1,
         weight1,
         samples1) = correlation_pass_1ch(uncorrelated_samples[0],
                                          term, delta, weights[0],
                                          correlation_samples[0])
        (uncorrelated2,
         weight2,
         samples2) = correlation_pass_1ch(uncorrelated_samples[1],
                                          term, delta, weights[1],
                                          correlation_samples[1])
        return ([uncorrelated1, uncorrelated2],
                [weight1, weight2],
                [samples1, samples2])

    elif ((-3 <= term) and (term <= -1)):
        assert(len(correlation_samples[0]) == 1)
        assert(len(correlation_samples[1]) == 1)
        uncorrelated = (correlation_samples[1] + uncorrelated_samples[0],
                        correlation_samples[0] + uncorrelated_samples[1])
        correlated = [[], []]
        weights = list(weights)
        if (term == -1):
            for i in range(1, len(uncorrelated[0])):
                correlated[0].append(uncorrelated[0][i] -
                                     apply_weight(weights[0],
                                                  uncorrelated[1][i - 1]))
                correlated[1].append(uncorrelated[1][i] -
                                     apply_weight(weights[1],
                                                  uncorrelated[0][i]))
                weights[0] += update_weight(uncorrelated[1][i - 1],
                                            correlated[0][-1],
                                            delta)
                weights[1] += update_weight(uncorrelated[0][i],
                                            correlated[1][-1],
                                            delta)
                weights[0] = max(min(weights[0], 1024), -1024)
                weights[1] = max(min(weights[1], 1024), -1024)
        elif (term == -2):
            for i in range(1, len(uncorrelated[0])):
                correlated[0].append(uncorrelated[0][i] -
                                     apply_weight(weights[0],
                                                  uncorrelated[1][i]))
                correlated[1].append(uncorrelated[1][i] -
                                     apply_weight(weights[1],
                                                  uncorrelated[0][i - 1]))
                weights[0] += update_weight(uncorrelated[1][i],
                                            correlated[0][-1],
                                            delta)
                weights[1] += update_weight(uncorrelated[0][i - 1],
                                            correlated[1][-1],
                                            delta)
                weights[0] = max(min(weights[0], 1024), -1024)
                weights[1] = max(min(weights[1], 1024), -1024)
        elif (term == -3):
            for i in range(1, len(uncorrelated[0])):
                correlated[0].append(uncorrelated[0][i] -
                                     apply_weight(weights[0],
                                                  uncorrelated[1][i - 1]))
                correlated[1].append(uncorrelated[1][i] -
                                     apply_weight(weights[1],
                                                  uncorrelated[0][i - 1]))
                weights[0] += update_weight(uncorrelated[1][i - 1],
                                            correlated[0][-1],
                                            delta)
                weights[1] += update_weight(uncorrelated[0][i - 1],
                                            correlated[1][-1],
                                            delta)
                weights[0] = max(min(weights[0], 1024), -1024)
                weights[1] = max(min(weights[1], 1024), -1024)

        # FIXME - use proper end-of-stream correlation samples
        return (correlated, weights, correlation_samples)
    else:
        raise ValueError("unsupported term")


def apply_weight(weight, sample):
    return ((weight * sample) + 512) >> 10


def update_weight(source, result, delta):
    if ((source == 0) or (result == 0)):
        return 0
    elif ((source ^ result) >= 0):
        return delta
    else:
        return -delta


def write_entropy_variables(writer, channels, entropies):
    if (len(channels) == 2):
        for e in entropies[0]:
            writer.write(16, wv_log2(e))
        for e in entropies[1]:
            writer.write(16, wv_log2(e))
    else:
        for e in entropies[0]:
            writer.write(16, wv_log2(e))


class Residual(object):
    def __init__(self, zeroes, m, offset, add, sign):
        self.zeroes = zeroes
        self.m = m
        self.offset = offset
        self.add = add
        self.sign = sign

    def __repr__(self):
        return "Residual(%s, %s, %s, %s, %s)" % \
            (repr(self.zeroes),
             repr(self.m),
             repr(self.offset),
             repr(self.add),
             repr(self.sign))

    @classmethod
    def encode(cls, residual, entropy):
        """given a residual integer and list of three entropies
        returns a Residual object and updates the entropies"""

        # figure out unsigned from signed
        if (residual >= 0):
            unsigned = residual
            sign = 0
        else:
            unsigned = -residual - 1
            sign = 1

        medians = [e // 2 ** 4 + 1 for e in entropy]

        # figure out m, offset, add and update channel's entropies
        if (unsigned < medians[0]):
            m = 0
            offset = unsigned
            add = medians[0] - 1
            entropy[0] -= ((entropy[0] + 126) // 128) * 2
        elif ((unsigned - medians[0]) < medians[1]):
            m = 1
            offset = unsigned - medians[0]
            add = medians[1] - 1
            entropy[0] += ((entropy[0] + 128) // 128) * 5
            entropy[1] -= ((entropy[1] + 62) // 64) * 2
        elif ((unsigned - (medians[0] + medians[1])) < medians[2]):
            m = 2
            offset = unsigned - (medians[0] + medians[1])
            add = medians[2] - 1
            entropy[0] += ((entropy[0] + 128) // 128) * 5
            entropy[1] += ((entropy[1] + 64) // 64) * 5
            entropy[2] -= ((entropy[2] + 30) // 32) * 2
        else:
            m = (((unsigned - (medians[0] + medians[1])) // medians[2]) + 2)
            offset = (unsigned -
                      (medians[0] + medians[1] + ((m - 2) * medians[2])))
            add = medians[2] - 1
            entropy[0] += ((entropy[0] + 128) // 128) * 5
            entropy[1] += ((entropy[1] + 64) // 64) * 5
            entropy[2] += ((entropy[2] + 32) // 32) * 5

        # zeroes will be populated later
        return cls(zeroes=None, m=m, offset=offset, add=add, sign=sign)

    def flush(self, writer, u_i_2, m_i):
        """given a BitstreamWriter, u_{i - 2} and m_{i},
        encodes residual_{i - 1}'s values to disk"""

        from math import log

        if (self.zeroes is not None):
            write_egc(writer, self.zeroes)

        if (self.m is not None):
            # calculate unary_{i - 1} based on m_{i}
            if ((self.m > 0) and (m_i > 0)):
                # positive m to positive m
                if ((u_i_2 is None) or (u_i_2 % 2 == 0)):
                    u_i_1 = (self.m * 2) + 1
                else:
                    # passing 1 from previous u
                    u_i_1 = (self.m * 2) - 1
            elif ((self.m == 0) and (m_i > 0)):
                # zero m to positive m
                if ((u_i_2 is None) or (u_i_2 % 2 == 1)):
                    u_i_1 = 1
                else:
                    # passing 0 from previous u
                    u_i_1 = None
            elif ((self.m > 0) and (m_i == 0)):
                # positive m to zero m
                if ((u_i_2 is None) or (u_i_2 % 2 == 0)):
                    u_i_1 = self.m * 2
                else:
                    # passing 1 from previous u
                    u_i_1 = (self.m - 1) * 2
            elif ((self.m == 0) and (m_i == 0)):
                # zero m to zero m
                if ((u_i_2 is None) or (u_i_2 % 2 == 1)):
                    u_i_1 = 0
                else:
                    # passing 0 from previous u
                    u_i_1 = None
            else:
                raise ValueError("invalid m")

            # write residual_{i - 1} to disk based on unary_{i - 1}
            if (u_i_1 is not None):
                if (u_i_1 < 16):
                    writer.unary(0, u_i_1)
                else:
                    writer.unary(0, 16)
                    write_egc(writer, u_i_1 - 16)

            if (self.add > 0):
                p = int(log(self.add) / log(2))
                e = 2 ** (p + 1) - self.add - 1
                if (self.offset < e):
                    writer.write(p, self.offset)
                else:
                    writer.write(p, (self.offset + e) // 2)
                    writer.write(1, (self.offset + e) % 2)

            writer.write(1, self.sign)
        else:
            u_i_1 = None

        return u_i_1


def write_bitstream(writer, channels, entropies):
    # residual_{-1}
    r_i_1 = Residual(zeroes=None, m=None, offset=None, add=None, sign=None)

    # u_{-2}
    u_i_2 = None

    i = 0

    while (i < (len(channels) * len(channels[0]))):
        r = channels[i % len(channels)][i // len(channels)]

        if (((entropies[0][0] < 2) and (entropies[1][0] < 2) and
             unary_undefined(u_i_2, r_i_1.m))):
            if ((r_i_1.zeroes is not None) and (r_i_1.m is None)):
                # in a block of zeroes
                if (r == 0):
                    # continue block of zeroes
                    r_i_1.zeroes += 1
                else:
                    # end block of zeroes
                    r_i = Residual.encode(r, entropies[i % len(channels)])
                    r_i.zeroes = r_i_1.zeroes
                    r_i_1 = r_i
            else:
                # start a new block of zeroes
                if (r == 0):
                    r_i = Residual(zeroes=1,
                                   m=None, offset=None, add=None, sign=None)
                    u_i_2 = r_i_1.flush(writer, u_i_2, 0)
                    entropies[0][0] = entropies[0][1] = entropies[0][2] = 0
                    entropies[1][0] = entropies[1][1] = entropies[1][2] = 0
                    r_i_1 = r_i
                else:
                    # false alarm block of zeroes
                    r_i = Residual.encode(r, entropies[i % len(channels)])
                    r_i.zeroes = 0
                    u_i_2 = r_i_1.flush(writer, u_i_2, r_i.m)
                    r_i_1 = r_i
        else:
            # encode regular residual
            r_i = Residual.encode(r, entropies[i % len(channels)])
            r_i.zeroes = None
            u_i_2 = r_i_1.flush(writer, u_i_2, r_i.m)
            r_i_1 = r_i

        i += 1

    # flush final residual
    u_i_2 = r_i_1.flush(writer, u_i_2, 0)


def unary_undefined(prev_u, m):
    """given u_{i - 1} and m_{i},
    returns True if u_{i} is undefined,
    False if defined"""

    if (m is None):
        return True
    if ((m == 0) and (prev_u is not None) and (prev_u % 2 == 0)):
        return True
    else:
        return False


def write_egc(writer, value):
    from math import log

    assert(value >= 0)

    if (value > 1):
        t = int(log(value) / log(2)) + 1
        writer.unary(0, t)
        writer.write(t - 1, value % (2 ** (t - 1)))
    else:
        writer.unary(0, value)


def write_residual(writer, u, offset, add, sign):
    """given u_{i}, offset_{i}, add_{i} and sign_{i}
    writes residual data to the given BitstreamWriter
    u_{i} may be None, indicated an undefined unary value"""


def write_extended_integers(writer,
                            sent_bits, zero_bits, one_bits, duplicate_bits):
    writer.build("8u 8u 8u 8u",
                 (sent_bits, zero_bits, one_bits, duplicate_bits))


if (__name__ == '__main__'):
    write_bitstream(None,
                    [[1, 2, 3, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
                      0, 0, 0, 0, 0, 0, 0, 0, 0, -1, -2, -3, -2, -1]],
                    [[0, 0, 0], [0, 0, 0]])
