# -*- coding: utf-8 -*-
"""
MiniSEED specific utilities.
"""
import collections
import ctypes as C  # NOQA
import os
from pathlib import Path
import sys
import warnings
from datetime import datetime
from struct import pack, unpack

import numpy as np

from obspy import UTCDateTime
from obspy.core.compatibility import from_buffer
from obspy.core.util.decorator import ObsPyDeprecationWarning
from . import InternalMSEEDParseTimeError
from .headers import (ENCODINGS, ENDIAN, FIXED_HEADER_ACTIVITY_FLAGS,
                      FIXED_HEADER_DATA_QUAL_FLAGS,
                      FIXED_HEADER_IO_CLOCK_FLAGS, HPTMODULUS,
                      SAMPLESIZES, UNSUPPORTED_ENCODINGS, MSRecord,
                      MS_NOERROR, clibmseed)


def get_start_and_end_time(file_or_file_object):
    """
    Returns the start and end time of a MiniSEED file or file-like object.

    :type file_or_file_object: str or file
    :param file_or_file_object: MiniSEED file name or open file-like object
        containing a MiniSEED record.
    :return: tuple (start time of first record, end time of last record)

    This method will return the start time of the first record and the end time
    of the last record. Keep in mind that it will not return the correct result
    if the records in the MiniSEED file do not have a chronological ordering.

    The returned end time is the time of the last data sample and not the
    time that the last sample covers.

    .. rubric:: Example

    >>> from obspy.core.util import get_example_file
    >>> filename = get_example_file(
    ...     "BW.BGLD.__.EHE.D.2008.001.first_10_records")
    >>> get_start_and_end_time(filename)  # doctest: +NORMALIZE_WHITESPACE
        (UTCDateTime(2007, 12, 31, 23, 59, 59, 915000),
        UTCDateTime(2008, 1, 1, 0, 0, 20, 510000))

    It also works with an open file pointer. The file pointer itself will not
    be changed.

    >>> f = open(filename, 'rb')
    >>> get_start_and_end_time(f)  # doctest: +NORMALIZE_WHITESPACE
        (UTCDateTime(2007, 12, 31, 23, 59, 59, 915000),
        UTCDateTime(2008, 1, 1, 0, 0, 20, 510000))

    And also with a MiniSEED file stored in a BytesIO

    >>> import io
    >>> file_object = io.BytesIO(f.read())
    >>> get_start_and_end_time(file_object)  # doctest: +NORMALIZE_WHITESPACE
        (UTCDateTime(2007, 12, 31, 23, 59, 59, 915000),
        UTCDateTime(2008, 1, 1, 0, 0, 20, 510000))
    >>> file_object.close()

    If the file pointer does not point to the first record, the start time will
    refer to the record it points to.

    >>> _ = f.seek(512)
    >>> get_start_and_end_time(f)  # doctest: +NORMALIZE_WHITESPACE
        (UTCDateTime(2008, 1, 1, 0, 0, 1, 975000),
        UTCDateTime(2008, 1, 1, 0, 0, 20, 510000))

    The same is valid for a file-like object.

    >>> file_object = io.BytesIO(f.read())
    >>> get_start_and_end_time(file_object)  # doctest: +NORMALIZE_WHITESPACE
        (UTCDateTime(2008, 1, 1, 0, 0, 1, 975000),
        UTCDateTime(2008, 1, 1, 0, 0, 20, 510000))
    >>> f.close()
    """
    # Get the starttime of the first record.
    info = get_record_information(file_or_file_object)
    starttime = info['starttime']
    # Get the end time of the last record.
    info = get_record_information(
        file_or_file_object,
        (info['number_of_records'] - 1) * info['record_length'])
    endtime = info['endtime']
    return starttime, endtime


def get_flags(files, starttime=None, endtime=None,
              io_flags=True, activity_flags=True,
              data_quality_flags=True, timing_quality=True):
    """
    Counts all data quality, I/O, and activity flags of the given MiniSEED
    file and returns statistics about the timing quality if applicable.

    :param files: MiniSEED file or list of MiniSEED files.
    :type files: list, str, :class:`~pathlib.Path`, file-like object
    :param starttime: Only use records whose end time is larger than this
        given time.
    :type starttime: str or :class:`obspy.core.utcdatetime.UTCDateTime`
    :param endtime: Only use records whose start time is smaller than this
        given time.
    :type endtime: str or :class:`obspy.core.utcdatetime.UTCDateTime`
    :param io_flags: Extract I/O flag counts.
    :type io_flags: bool
    :param activity_flags: Extract activity flag counts.
    :type activity_flags: bool
    :param data_quality_flags: Extract data quality flag counts.
    :type data_quality_flags: bool
    :param timing_quality: Extract timing quality and corresponding statistics.
    :type timing_quality: bool

    :return: Dictionary with information about the timing quality and the data
        quality, I/O, and activity flags. It has the following keys:
        ``"number_of_records_used"``, ``"record_count"``,
        ``"timing_correction"``, ``"timing_correction_count"``,
        ``"data_quality_flags_counts"``, ``"activity_flags_counts"``,
        ``"io_and_clock_flags_counts"``, ``"data_quality_flags_percentages"``,
        ``"activity_flags_percentages"``, ``"io_and_clock_flags_percentages"``,
        and ``"timing_quality"``.

    .. rubric:: Flags

    This method will count all set bit flags in the fixed header of a MiniSEED
    file and return the total count for each flag type. The following flags
    are extracted:

    **Data quality flags:**

    ========  =================================================
    Bit       Description
    ========  =================================================
    [Bit 0]   Amplifier saturation detected (station dependent)
    [Bit 1]   Digitizer clipping detected
    [Bit 2]   Spikes detected
    [Bit 3]   Glitches detected
    [Bit 4]   Missing/padded data present
    [Bit 5]   Telemetry synchronization error
    [Bit 6]   A digital filter may be charging
    [Bit 7]   Time tag is questionable
    ========  =================================================

    **Activity flags:**

    ========  =================================================
    Bit       Description
    ========  =================================================
    [Bit 0]   Calibration signals present
    [Bit 1]   Time correction applied
    [Bit 2]   Beginning of an event, station trigger
    [Bit 3]   End of the event, station detriggers
    [Bit 4]   A positive leap second happened during this record
    [Bit 5]   A negative leap second happened during this record
    [Bit 6]   Event in progress
    ========  =================================================

    **I/O and clock flags:**

    ========  =================================================
    Bit       Description
    ========  =================================================
    [Bit 0]   Station volume parity error possibly present
    [Bit 1]   Long record read (possibly no problem)
    [Bit 2]   Short record read (record padded)
    [Bit 3]   Start of time series
    [Bit 4]   End of time series
    [Bit 5]   Clock locked
    ========  =================================================

    .. rubric:: Timing quality

    If the file has a Blockette 1001 statistics about the timing quality will
    be returned if ``timing_quality`` is True. See the doctests for more
    information.

    This method will read the timing quality in Blockette 1001 for each
    record in the file if available and return the following statistics:
    Minima, maxima, average, median and upper and lower quartiles.

    .. rubric:: Examples

    >>> from obspy.core.util import get_example_file
    >>> filename = get_example_file("qualityflags.mseed")
    >>> flags = get_flags(filename)
    >>> for k, v in flags["data_quality_flags_counts"].items():
    ...     print(k, v)
    amplifier_saturation 9
    digitizer_clipping 8
    spikes 7
    glitches 6
    missing_padded_data 5
    telemetry_sync_error 4
    digital_filter_charging 3
    suspect_time_tag 2

    Reading a file with Blockette 1001 will return timing quality statistics if
    requested.

    >>> filename = get_example_file("timingquality.mseed")
    >>> flags = get_flags(filename)
    >>> for k, v in sorted(flags["timing_quality"].items()):
    ...     print(k, v)  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
    all_values [...]
    lower_quartile 25.0
    max 100.0
    mean 50.0
    median 50.0
    min 0.0
    upper_quartile 75.0
    """
    # Splat input files to array
    if not isinstance(files, list):
        files = [files]

    starttime = float(UTCDateTime(starttime)) if starttime else None
    endtime = float(UTCDateTime(endtime)) if endtime else None

    records = []

    # Use clibmseed to get header parameters for all files
    for file in files:

        # If it's a file name just read it.
        if isinstance(file, (str, Path)):
            # Read to NumPy array which is used as a buffer.
            bfr_np = np.fromfile(file, dtype=np.int8)
        elif hasattr(file, 'read'):
            bfr_np = from_buffer(file.read(), dtype=np.int8)

        offset = 0

        msr = clibmseed.msr_init(C.POINTER(MSRecord)())

        while True:
            # Read up to max record length.
            record = bfr_np[offset: offset + 8192]
            if len(record) < 48:
                break

            retcode = clibmseed.msr_parse(record, len(record), C.pointer(msr),
                                          -1, 0, 0)

            if retcode != MS_NOERROR:
                break

            offset += msr.contents.reclen

            # Check starttime and endtime of the record
            # Read the sampling rate from the header (is this unsafe?)
            # Tried using msr.msr_nomsamprate(msr) but the return is strange
            r_start = clibmseed.msr_starttime(msr) / HPTMODULUS
            r_delta = (1 / msr.contents.samprate)
            r_end = (clibmseed.msr_endtime(msr) / HPTMODULUS) + r_delta

            # Cut off records to start & endtime
            if starttime is not None:
                if r_end <= starttime:
                    continue
                if r_start < starttime:
                    r_start = starttime

            if endtime is not None:
                if r_start >= endtime:
                    continue
                if r_end > endtime:
                    r_end = endtime

            # Get the timing quality in blockette1001 if it exists
            if msr.contents.Blkt1001:
                r_tq = msr.contents.Blkt1001.contents.timing_qual
            else:
                r_tq = None

            # Collect all records and parameters in the range
            records.append({
                'start': r_start,
                'delta': r_delta,
                'end': r_end,
                'tq': r_tq,
                'tc': msr.contents.fsdh.contents.time_correct,
                'io': msr.contents.fsdh.contents.io_flags,
                'dq': msr.contents.fsdh.contents.dq_flags,
                'ac': msr.contents.fsdh.contents.act_flags
            })

        # Free memory to be ready for next file.
        clibmseed.msr_free(C.pointer(msr))

    # It should be faster to sort by record endtime
    # if we reverse the array first
    records.reverse()
    records.sort(key=lambda x: x["end"], reverse=True)

    # Create collections for the flags
    dq_flags_counts = collections.OrderedDict([
        ("amplifier_saturation", 0),
        ("digitizer_clipping", 0),
        ("spikes", 0),
        ("glitches", 0),
        ("missing_padded_data", 0),
        ("telemetry_sync_error", 0),
        ("digital_filter_charging", 0),
        ("suspect_time_tag", 0)
    ])
    dq_flags_seconds = collections.OrderedDict([
        ("amplifier_saturation", 0),
        ("digitizer_clipping", 0),
        ("spikes", 0),
        ("glitches", 0),
        ("missing_padded_data", 0),
        ("telemetry_sync_error", 0),
        ("digital_filter_charging", 0),
        ("suspect_time_tag", 0)
    ])

    io_flags_counts = collections.OrderedDict([
        ("station_volume", 0),
        ("long_record_read", 0),
        ("short_record_read", 0),
        ("start_time_series", 0),
        ("end_time_series", 0),
        ("clock_locked", 0)
    ])
    io_flags_seconds = collections.OrderedDict([
        ("station_volume", 0),
        ("long_record_read", 0),
        ("short_record_read", 0),
        ("start_time_series", 0),
        ("end_time_series", 0),
        ("clock_locked", 0)
    ])

    ac_flags_counts = collections.OrderedDict([
        ("calibration_signal", 0),
        ("time_correction_applied", 0),
        ("event_begin", 0),
        ("event_end", 0),
        ("positive_leap", 0),
        ("negative_leap", 0),
        ("event_in_progress", 0)
    ])
    ac_flags_seconds = collections.OrderedDict([
        ("calibration_signal", 0),
        ("time_correction_applied", 0),
        ("event_begin", 0),
        ("event_end", 0),
        ("positive_leap", 0),
        ("negative_leap", 0),
        ("event_in_progress", 0)
    ])

    coverage = None
    used_record_count = 0
    timing_correction = 0.0
    timing_correction_count = 0
    tq = []

    # Go over all sorted records from back to front
    for record in records:

        # For counts we do not care about overlaps
        # simply count contribution from all the records
        if io_flags:
            for _i, key in enumerate(io_flags_seconds.keys()):
                if (record["io"] & (1 << _i)) != 0:
                    io_flags_counts[key] += 1

        if activity_flags:
            for _i, key in enumerate(ac_flags_seconds.keys()):
                if (record["ac"] & (1 << _i)) != 0:
                    ac_flags_counts[key] += 1

        if data_quality_flags:
            for _i, key in enumerate(dq_flags_seconds.keys()):
                if (record["dq"] & (1 << _i)) != 0:
                    dq_flags_counts[key] += 1

        # Coverage is the timewindow that is covered by the records
        # so bits in overlapping records are not counted
        # The first record starts a clean window
        if coverage is None:
            coverage = [record["start"], record["end"]]
        else:

            # Account for time tolerance
            time_tolerance = 0.5 * record['delta']
            tolerated_end = coverage[0] - time_tolerance

            # Start is beyond coverage, skip the overlapping record
            if record["start"] >= coverage[0]:
                continue

            # Fix end to the start of the coverage if it is overlaps
            # with the coverage window. Or if it is within the allowed
            # time tolerance
            if record["end"] > coverage[0] or record["end"] > tolerated_end:
                record["end"] = coverage[0]

            # Extend the coverage
            if record["start"] < coverage[0]:
                coverage[0] = record["start"]

        # Get the record length in seconds
        record_length_seconds = (record["end"] - record["start"])

        # Skip if the record length is 0 (or negative)
        if record_length_seconds <= 0.0:
            continue

        # Overlapping records do not count ot the used_records
        # used records tracks the amount of timing quality
        # parameters we expect
        used_record_count += 1

        # Bitwise AND to count flags and store in orderedDicts
        if io_flags:
            for _i, key in enumerate(io_flags_seconds.keys()):
                if (record["io"] & (1 << _i)) != 0:
                    io_flags_seconds[key] += record_length_seconds

        if activity_flags:
            for _i, key in enumerate(ac_flags_seconds.keys()):
                if (record["ac"] & (1 << _i)) != 0:
                    ac_flags_seconds[key] += record_length_seconds

        if data_quality_flags:
            for _i, key in enumerate(dq_flags_seconds.keys()):
                if (record["dq"] & (1 << _i)) != 0:
                    dq_flags_seconds[key] += record_length_seconds

        # Get the timing quality parameter and append to array
        if timing_quality and record["tq"] is not None:
            tq.append(float(record["tq"]))

        # Check if a timing correction is specified
        # (not whether it has been applied)
        if record["tc"] != 0:
            timing_correction += record_length_seconds
            timing_correction_count += 1

    # Get the total time analyzed
    if endtime is not None and starttime is not None:
        total_time_seconds = endtime - starttime
    # If zero records agree with the selections, zero seconds have been
    # analysed.
    elif coverage is None:
        total_time_seconds = 0
    else:
        total_time_seconds = coverage[1] - coverage[0]

    # Percentage of time of bit flags set
    if total_time_seconds:
        if io_flags:
            for _i, key in enumerate(io_flags_seconds.keys()):
                io_flags_seconds[key] /= total_time_seconds * 1e-2
        if data_quality_flags:
            for _i, key in enumerate(dq_flags_seconds.keys()):
                dq_flags_seconds[key] /= total_time_seconds * 1e-2
        if activity_flags:
            for _i, key in enumerate(ac_flags_seconds.keys()):
                ac_flags_seconds[key] /= total_time_seconds * 1e-2

        timing_correction /= total_time_seconds * 1e-2

    # Add the timing quality if it is set for all used records
    if timing_quality:
        if len(tq) == used_record_count:
            tq = np.array(tq, dtype=np.float64)
            tq = {
                "all_values": tq,
                "min": tq.min(),
                "max": tq.max(),
                "mean": tq.mean(),
                "median": np.median(tq),
                "lower_quartile": np.percentile(tq, 25),
                "upper_quartile": np.percentile(tq, 75)
            }

        else:
            tq = {}

    return {
        'timing_correction': timing_correction,
        'timing_correction_count': timing_correction_count,
        'io_and_clock_flags_percentages': io_flags_seconds,
        'io_and_clock_flags_counts': io_flags_counts,
        'data_quality_flags_percentages': dq_flags_seconds,
        'data_quality_flags_counts': dq_flags_counts,
        'activity_flags_percentages': ac_flags_seconds,
        'activity_flags_counts': ac_flags_counts,
        'timing_quality': tq,
        'record_count': len(records),
        'number_of_records_used': used_record_count,
    }


def get_record_information(file_or_file_object, offset=0, endian=None):
    """
    Returns record information about given files and file-like object.

    :param endian: If given, the byte order will be enforced. Can be either "<"
        or ">". If None, it will be determined automatically.
        Defaults to None.

    .. rubric:: Example

    >>> from obspy.core.util import get_example_file
    >>> filename = get_example_file("test.mseed")
    >>> ri = get_record_information(filename)
    >>> for k, v in sorted(ri.items()):
    ...     print(k, v)
    activity_flags 0
    byteorder >
    channel BHZ
    data_quality_flags 0
    encoding 11
    endtime 2003-05-29T02:15:51.518400Z
    excess_bytes 0
    filesize 8192
    io_and_clock_flags 0
    location 00
    network NL
    npts 5980
    number_of_records 2
    record_length 4096
    samp_rate 40.0
    starttime 2003-05-29T02:13:22.043400Z
    station HGN
    time_correction 0
    """
    if isinstance(file_or_file_object, (str, Path)):
        with open(file_or_file_object, 'rb') as f:
            info = _get_record_information(f, offset=offset, endian=endian)
    else:
        info = _get_record_information(file_or_file_object, offset=offset,
                                       endian=endian)
    return info


def _decode_header_field(name, content):
    """
    Helper function to decode header fields. Fairly fault tolerant and it
    will also raise nice warnings in case in encounters anything wild.
    """
    try:
        return content.decode("ascii", errors="strict")
    except UnicodeError:
        r = content.decode("ascii", errors="ignore")
        msg = (u"Failed to decode {name} code as ASCII. "
               u"Code in file: '{result}' (\ufffd indicates characters "
               u"that could not be decoded). "
               u"Will be interpreted as: '{f_result}'. "
               u"This is an invalid MiniSEED file - please "
               u"contact your data provider.")
        warnings.warn(msg.format(
            name=name,
            result=content.decode("ascii", errors="replace"),
            f_result=r))
        return r


def _get_record_information(file_object, offset=0, endian=None):
    """
    Searches the first MiniSEED record stored in file_object at the current
    position and returns some information about it.

    If offset is given, the MiniSEED record is assumed to start at current
    position + offset in file_object.

    :param endian: If given, the byte order will be enforced. Can be either "<"
        or ">". If None, it will be determined automatically.
        Defaults to None.
    """
    initial_position = file_object.tell()
    record_start = initial_position
    samp_rate = None

    info = {}

    # Apply the offset.
    if offset:
        file_object.seek(offset, 1)
        record_start += offset

    # Get the size of the buffer.
    file_object.seek(0, 2)
    info['filesize'] = int(file_object.tell() - record_start)
    file_object.seek(record_start, 0)

    _code = file_object.read(8)[6:7]
    # Reset the offset if starting somewhere in the middle of the file.
    if info['filesize'] % 128 != 0:
        # if a multiple of minimal record length 256
        record_start = 0
    elif _code not in [b'D', b'R', b'Q', b'M', b' ']:
        # if valid data record start at all starting with D, R, Q or M
        record_start = 0
    # Might be a noise record or completely empty.
    elif _code == b' ':
        try:
            _t = file_object.read(120).decode().strip()
        except Exception:
            raise ValueError("Invalid MiniSEED file.")
        if not _t:
            info = _get_record_information(file_object=file_object,
                                           endian=endian)
            file_object.seek(initial_position, 0)
            return info
        else:
            raise ValueError("Invalid MiniSEED file.")
    file_object.seek(record_start, 0)

    # check if full SEED or MiniSEED
    if file_object.read(8)[6:7] == b'V':
        # found a full SEED record - seek first MiniSEED record
        # search blockette 005, 008 or 010 which contain the record length
        blockette_id = file_object.read(3)
        while blockette_id not in [b'010', b'008', b'005']:
            if not blockette_id.startswith(b'0'):
                msg = "SEED Volume Index Control Headers: blockette 0xx" + \
                      " expected, got %s"
                raise Exception(msg % blockette_id)
            # get length and jump to end of current blockette
            blockette_len = int(file_object.read(4))
            file_object.seek(blockette_len - 7, 1)
            # read next blockette id
            blockette_id = file_object.read(3)
        # Skip the next bytes containing length of the blockette and version
        file_object.seek(8, 1)
        # get record length
        rec_len = pow(2, int(file_object.read(2)))
        # reset file pointer
        file_object.seek(record_start, 0)
        # cycle through file using record length until first data record found
        while True:
            data = file_object.read(7)[6:7]
            if data in [b'D', b'R', b'Q', b'M']:
                break
            # stop looking when hitting end of file
            # the second check should be enough.. but play it safe
            if not data or record_start > info['filesize']:
                msg = "No MiniSEED data record found in file."
                raise ValueError(msg)
            record_start += rec_len
            file_object.seek(record_start, 0)

    # Jump to the network, station, location and channel codes.
    file_object.seek(record_start + 8, 0)
    data = file_object.read(12)

    info["station"] = _decode_header_field("station", data[:5].strip())
    info["location"] = _decode_header_field("location", data[5:7].strip())
    info["channel"] = _decode_header_field("channel", data[7:10].strip())
    info["network"] = _decode_header_field("network", data[10:12].strip())

    # Use the date to figure out the byte order.
    file_object.seek(record_start + 20, 0)
    # Capital letters indicate unsigned quantities.
    data = file_object.read(28)

    def fmt(s):
        return '%sHHBBBxHHhhBBBxlxxH' % s

    def _parse_time(values):
        if not (1 <= values[1] <= 366):
            msg = 'julday out of bounds (wrong endian?): {!s}'.format(
                values[1])
            raise InternalMSEEDParseTimeError(msg)
        # The spec says values[5] (.0001 seconds) must be between 0-9999 but
        # we've  encountered files which have a value of 10000. We interpret
        # this as an additional second. The approach here is general enough
        # to work for any value of values[5].
        msec = values[5] * 100
        offset = msec // 1000000
        if offset:
            warnings.warn(
                "Record contains a fractional seconds (.0001 secs) of %i - "
                "the maximum strictly allowed value is 9999. It will be "
                "interpreted as one or more additional seconds." % values[5],
                category=UserWarning)
        try:
            t = UTCDateTime(
                year=values[0], julday=values[1],
                hour=values[2], minute=values[3], second=values[4],
                microsecond=msec % 1000000) + offset
        except TypeError:
            msg = 'Problem decoding time (wrong endian?)'
            raise InternalMSEEDParseTimeError(msg)
        return t

    if endian is None:
        try:
            endian = ">"
            values = unpack(fmt(endian), data)
            starttime = _parse_time(values)
        except InternalMSEEDParseTimeError:
            endian = "<"
            values = unpack(fmt(endian), data)
            starttime = _parse_time(values)
    else:
        values = unpack(fmt(endian), data)
        try:
            starttime = _parse_time(values)
        except InternalMSEEDParseTimeError:
            msg = ("Invalid starttime found. The passed byte order is likely "
                   "wrong.")
            raise ValueError(msg)
    npts = values[6]
    info['npts'] = npts
    samp_rate_factor = values[7]
    samp_rate_mult = values[8]
    info['activity_flags'] = values[9]
    # Bit 1 of the activity flags.
    time_correction_applied = bool(info['activity_flags'] & 2)
    info['io_and_clock_flags'] = values[10]
    info['data_quality_flags'] = values[11]
    info['time_correction'] = values[12]
    time_correction = values[12]
    blkt_offset = values[13]

    # Correct the starttime if applicable.
    if (time_correction_applied is False) and time_correction:
        # Time correction is in units of 0.0001 seconds.
        starttime += time_correction * 0.0001

    # Traverse the blockettes and parse Blockettes 100, 500, 1000 and/or 1001
    # if any of those is found.
    while blkt_offset:
        file_object.seek(record_start + blkt_offset, 0)
        blkt_type, next_blkt = unpack('%sHH' % endian,
                                      file_object.read(4))
        if next_blkt != 0 and (next_blkt < 4 or next_blkt - 4 <= blkt_offset):
            msg = ('Invalid blockette offset (%d) less than or equal to '
                   'current offset (%d)') % (next_blkt, blkt_offset)
            raise ValueError(msg)
        blkt_offset = next_blkt

        # Parse in order of likeliness.
        if blkt_type == 1000:
            encoding, word_order, record_length = \
                unpack('%sBBB' % endian,
                       file_object.read(3))
            if word_order not in ENDIAN:
                msg = ('Invalid word order "%s" in blockette 1000 for '
                       'record with ID %s.%s.%s.%s at offset %i.') % (
                    str(word_order), info["network"], info["station"],
                    info["location"], info["channel"], offset)
                warnings.warn(msg, UserWarning)
            elif ENDIAN[word_order] != endian:
                msg = 'Inconsistent word order.'
                warnings.warn(msg, UserWarning)
            info['encoding'] = encoding
            info['record_length'] = 2 ** record_length
        elif blkt_type == 1001:
            info['timing_quality'], mu_sec = \
                unpack('%sBb' % endian,
                       file_object.read(2))
            starttime += float(mu_sec) / 1E6
        elif blkt_type == 500:
            file_object.seek(14, 1)
            mu_sec = unpack('%sb' % endian,
                            file_object.read(1))[0]
            starttime += float(mu_sec) / 1E6
        elif blkt_type == 100:
            samp_rate = unpack('%sf' % endian,
                               file_object.read(4))[0]

    # No blockette 1000 found.
    if "record_length" not in info:
        file_object.seek(record_start, 0)
        # Read 16 kb - should be a safe maximal record length.
        buf = from_buffer(file_object.read(2 ** 14), dtype=np.int8)
        # This is a messy check - we just delegate to libmseed.
        reclen = clibmseed.ms_detect(buf, len(buf))
        if reclen < 0:
            raise ValueError("Could not detect data record.")
        elif reclen == 0:
            # It might be at the end of the file.
            if len(buf) in [2 ** _i for _i in range(7, 256)]:
                reclen = len(buf)
            else:
                raise ValueError("Could not determine record length.")
        info["record_length"] = reclen

    # If samprate not set via blockette 100 calculate the sample rate according
    # to the SEED manual.
    if not samp_rate:
        if samp_rate_factor > 0 and samp_rate_mult > 0:
            samp_rate = float(samp_rate_factor * samp_rate_mult)
        elif samp_rate_factor > 0 and samp_rate_mult < 0:
            samp_rate = -1.0 * float(samp_rate_factor) / float(samp_rate_mult)
        elif samp_rate_factor < 0 and samp_rate_mult > 0:
            samp_rate = -1.0 * float(samp_rate_mult) / float(samp_rate_factor)
        elif samp_rate_factor < 0 and samp_rate_mult < 0:
            samp_rate = 1.0 / float(samp_rate_factor * samp_rate_mult)
        else:
            samp_rate = 0

    info['samp_rate'] = samp_rate

    info['starttime'] = starttime
    # If sample rate is zero set endtime to startime
    if samp_rate == 0:
        info['endtime'] = starttime
    # Endtime is the time of the last sample.
    else:
        info['endtime'] = starttime + (npts - 1) / samp_rate
    info['byteorder'] = endian

    info['number_of_records'] = int(info['filesize'] //
                                    info['record_length'])
    info['excess_bytes'] = int(info['filesize'] % info['record_length'])

    # Reset file pointer.
    file_object.seek(initial_position, 0)
    return info


def _ctypes_array_2_numpy_array(buffer_, buffer_elements, sampletype):
    """
    Takes a Ctypes array and its length and type and returns it as a
    NumPy array.

    :param buffer_: Ctypes c_void_p pointer to buffer.
    :param buffer_elements: length of the whole buffer
    :param sampletype: type of sample, on of "a", "i", "f", "d"
    """
    # Allocate NumPy array to move memory to
    numpy_array = np.empty(buffer_elements, dtype=sampletype)
    datptr = numpy_array.ctypes.data
    # Manually copy the contents of the C allocated memory area to
    # the address of the previously created NumPy array
    C.memmove(datptr, buffer_, buffer_elements * SAMPLESIZES[sampletype])
    return numpy_array


def _convert_msr_to_dict(m):
    """
    Internal method used for setting header attributes.
    """
    h = {}
    attributes = ('network', 'station', 'location', 'channel',
                  'dataquality', 'starttime', 'samprate',
                  'samplecnt', 'numsamples', 'sampletype')
    # loop over attributes
    for _i in attributes:
        h[_i] = getattr(m, _i)
    return h


def _convert_datetime_to_mstime(dt):
    """
    Takes a obspy.util.UTCDateTime object and returns an epoch time in ms.

    :param dt: obspy.util.UTCDateTime object.
    """
    rest = (dt._ns % 10**3) >= 500 and 1 or 0
    return dt._ns // 10**3 + rest


def _convert_mstime_to_datetime(timestring):
    """
    Takes a MiniSEED timestamp and returns a obspy.util.UTCDateTime object.

    :param timestamp: MiniSEED timestring (Epoch time string in ms).
    """
    return UTCDateTime(ns=int(round(timestring * 10**3)))


def _unpack_steim_1(data, npts, swapflag=0, verbose=0):
    """
    Unpack steim1 compressed data given as numpy array.

    :type data: :class:`numpy.ndarray`
    :param data: steim compressed data as a numpy array
    :param npts: number of data points
    :param swapflag: Swap bytes, defaults to 0
    :return: Return data as numpy.ndarray of dtype int32
    """
    datasize = len(data)
    samplecnt = npts
    datasamples = np.empty(npts, dtype=np.int32)

    nsamples = clibmseed.msr_decode_steim1(
        data.ctypes.data,
        datasize, samplecnt, datasamples,
        npts, None, swapflag)
    if nsamples != npts:
        raise Exception("Error in unpack_steim1")
    return datasamples


def _unpack_steim_2(data, npts, swapflag=0, verbose=0):
    """
    Unpack steim2 compressed data given as numpy array.

    :type data: :class:`numpy.ndarray`
    :param data: steim compressed data as a numpy array
    :param npts: number of data points
    :param swapflag: Swap bytes, defaults to 0
    :return: Return data as numpy.ndarray of dtype int32
    """
    datasize = len(data)
    samplecnt = npts
    datasamples = np.empty(npts, dtype=np.int32)

    nsamples = clibmseed.msr_decode_steim2(
        data.ctypes.data,
        datasize, samplecnt, datasamples,
        npts, None, swapflag)
    if nsamples != npts:
        raise Exception("Error in unpack_steim2")
    return datasamples


def set_flags_in_fixed_headers(filename, flags):
    """
    Updates a given MiniSEED file with some fixed header flags.

    :type filename: str
    :param filename: Name of the MiniSEED file to be changed
    :type flags: dict
    :param flags: The flags to update in the MiniSEED file

        Flags are stored as a nested dictionary::

            { trace_id:
                { flag_group:
                    { flag_name: flag_value,
                                 ...
                    },
                    ...
                },
                ...
            }

        with:

        * ``trace_id``
            A string identifying the trace. A string looking like
            ``NETWORK.STATION.LOCATION.CHANNEL`` is expected, the values will
            be compared to those found in the fixed header of every record. An
            empty field will be interpreted  as "every possible value", so
            ``"..."`` will apply to every single trace in the file. Padding
            spaces are ignored.
        * ``flag_group``
            Which flag group is to be changed. One of ``'activity_flags'``,
            ``'io_clock_flags'``, ``'data_qual_flags'`` is expected. Invalid
            flag groups raise a ``ValueError``.
        * ``flag_name``
            The name of the flag. Possible values are matched with
            ``obspy.io.mseed.headers.FIXED_HEADER_ACTIVITY_FLAGS``,
            ``FIXED_HEADER_IO_CLOCK_FLAGS`` or ``FIXED_HEADER_DATA_QUAL_FLAGS``
            depending on the flag_group. Invalid flags raise a ``ValueError``.
        * ``flag_value``
            The value you want for this flag. Expected value is a bool (always
            ``True``/``False``) or a dict to store the moments and durations
            when this flag is ``True``. Expected syntax for this dict is
            accurately described in ``obspy.io.mseed.util._check_flag_value``.

    :raises IOError: if the file is not a MiniSEED file
    :raises ValueError: if one of the flag group, flag name or flag value is
        incorrect

    Example: to add a *Calibration Signals Present* flag (which belongs to the
    Activity Flags section of the fixed header) to every record, flags should
    be::

        { "..." : { "activity_flags" : { "calib_signal" : True }}}

    Example: to add a *Event in Progress* flag (which belongs to the
    Activity Flags section of the fixed header) from 2009/12/23 06:00:00 to
    2009/12/23 06:30:00, from 2009/12/24 10:00:00 to 2009/12/24 10:30:00 and
    at precise times 2009/12/26 18:00:00 and 2009/12/26 18:04:00,
    flags should be::

        date1 = UTCDateTime("2009-12-23T06:00:00.0")
        date2 = UTCDateTime("2009-12-23T06:30:00.0")
        date3 = UTCDateTime("2009-12-24T10:00:00.0")
        date4 = UTCDateTime("2009-12-24T10:30:00.0")
        date5 = UTCDateTime("2009-12-26T18:00:00.0")
        date6 = UTCDateTime("2009-12-26T18:04:00.0")
        { "..." :
            { "activity_flags" :
                { "event_in_progress" :
                    {"INSTANT" : [date5, date6],
                    "DURATION" : [(date1, date2), (date3, date4)]}}}}

    Alternative way to mark duration::

        { "..." :
            { "activity_flags" :
                { "event_in_progress" :
                    { "INSTANT" : [date5, date6],
                      "DURATION" : [date1, date2, date3, date4]}}}}

    """
    # import has to be here to break import loop
    from .core import _is_mseed
    # Basic check
    if not Path(filename).is_file() or not _is_mseed(filename):
        raise IOError("File %s is not a valid MiniSEED file" % filename)
    filesize = Path(filename).stat().st_size

    # Nested dictionaries to allow empty strings as wildcards
    class NestedDict(dict):
        def __missing__(self, key):
            value = self[key] = type(self)()
            return value
    # Define wildcard character
    wildcard = ""

    # Check channel identifier value
    flags_bytes = NestedDict()
    for (key, value) in flags.items():
        split_key = key.split(".")
        if len(split_key) != 4:
            msg = "Invalid channel identifier. " +\
                  "Expected 'Network.Station.Location.Channel' " +\
                  "(empty fields allowed), got '%s'."
            raise ValueError(msg % key)

        # Remove padding spaces and store in new dict
        net = split_key[0].strip()
        sta = split_key[1].strip()
        loc = split_key[2].strip()
        cha = split_key[3].strip()

        # Check flag value for invalid data
        for flag_group in value:
            # Check invalid flag group, and prepare check for invalid flag name
            if flag_group == 'activity_flags':
                record_to_check = FIXED_HEADER_ACTIVITY_FLAGS
            elif flag_group == 'io_clock_flags':
                record_to_check = FIXED_HEADER_IO_CLOCK_FLAGS
            elif flag_group == 'data_qual_flags':
                record_to_check = FIXED_HEADER_DATA_QUAL_FLAGS
            else:
                msg = "Invalid flag group %s. One of 'activity_flags', " +\
                      "'io_clock_flags', 'data_qual_flags' is expected."
                raise ValueError(msg % flag_group)

            for flag_name in value[flag_group]:
                # Check invalid flag name
                if flag_name not in record_to_check.values():
                    msg = "Invalid flag name %s. One of %s is expected."
                    raise ValueError(msg % (flag_name,
                                            str(record_to_check.values())))

                # Check flag values and store them in an "easy to parse" way:
                # either bool or list of tuples (start, end)
                flag_value = value[flag_group][flag_name]
                corrected_flag = _check_flag_value(flag_value)
                flags_bytes[net][sta][loc][cha][flag_group][flag_name] = \
                    corrected_flag

    # Open file
    with open(filename, 'r+b') as mseed_file:
        # Run through all records
        while mseed_file.tell() < filesize:
            record_start = mseed_file.tell()

            # Ignore sequence number and data header
            mseed_file.seek(8, os.SEEK_CUR)
            # Read identifier
            sta = mseed_file.read(5).strip().decode()
            loc = mseed_file.read(2).strip().decode()
            chan = mseed_file.read(3).strip().decode()
            net = mseed_file.read(2).strip().decode()

            # Search the nested dict for the network identifier
            if net in flags_bytes:
                dict_to_use = flags_bytes[net]
            elif wildcard in flags_bytes:
                dict_to_use = flags_bytes[wildcard]
            else:
                dict_to_use = None

            # Search the nested dict for the station identifier
            if dict_to_use is not None and sta in dict_to_use:
                dict_to_use = dict_to_use[sta]
            elif dict_to_use is not None and wildcard in dict_to_use:
                dict_to_use = dict_to_use[wildcard]
            else:
                dict_to_use = None

            # Search the nested dict for the location identifier
            if dict_to_use is not None and loc in dict_to_use:
                dict_to_use = dict_to_use[loc]
            elif dict_to_use is not None and wildcard in dict_to_use:
                dict_to_use = dict_to_use[wildcard]
            else:
                dict_to_use = None

            # Search the nested dict for the channel identifier
            if dict_to_use is not None and chan in dict_to_use:
                flags_value = dict_to_use[chan]
            elif dict_to_use is not None and wildcard in dict_to_use:
                flags_value = dict_to_use[wildcard]
            else:
                flags_value = None

            if flags_value is not None:
                # Calculate the real start and end of the record
                recstart = mseed_file.read(10)
                (yr, doy, hr, mn, sec, _, mil) = unpack(">HHBBBBH",
                                                        recstart)
                # Transformation to UTCDatetime()
                recstart = UTCDateTime(year=yr, julday=doy, hour=hr, minute=mn,
                                       second=sec, microsecond=mil * 100)
                # Read data to date begin and end of record
                (nb_samples, fact, mult) = unpack(">Hhh",
                                                  mseed_file.read(6))

                # Manage time correction
                act_flags = unpack(">B", mseed_file.read(1))[0]
                time_correction_applied = bool(act_flags & 2)
                (_, _, _, time_correction) = unpack(">BBBl",
                                                    mseed_file.read(7))
                if (time_correction_applied is False) and time_correction:
                    # Time correction is in units of 0.0001 seconds.
                    recstart += time_correction * 0.0001

                # Manage blockette's datation informations
                # Search for blockette 100's "Actual sample rate" field
                samp_rate = _search_flag_in_blockette(mseed_file, 4, 100, 4, 1)
                if samp_rate is not None:
                    samp_rate = unpack(">b", samp_rate)[0]
                # Search for blockette 1001's "microsec" field
                microsec = _search_flag_in_blockette(mseed_file, 4, 1001, 5, 1)
                if microsec is not None:
                    microsec = unpack(">b", microsec)[0]
                else:
                    microsec = 0

                realstarttime = recstart + microsec * 0.000001

                # If samprate not set via blockette 100 calculate the sample
                # rate according to the SEED manual.
                if samp_rate is None:
                    if (fact > 0) and (mult) > 0:
                        samp_rate = float(fact * mult)
                    elif (fact > 0) and (mult) < 0:
                        samp_rate = -1.0 * float(fact) / float(mult)
                    elif (fact < 0) and (mult) > 0:
                        samp_rate = -1.0 * float(mult) / float(fact)
                    elif (fact < 0) and (mult) < 0:
                        samp_rate = -1.0 / float(fact * mult)
                    else:
                        # if everything is unset or 0 set sample rate to 1
                        samp_rate = 1

                # date of the last sample is recstart+(nb_samples-1)/samp_rate
                # We assume here that a record with samples [0, 1, ..., n]
                # has a period [ date_0, date_n+1 [  AND NOT [ date_0, date_n ]
                realendtime = recstart + nb_samples / samp_rate

                # Convert flags to bytes : activity
                if 'activity_flags' in flags_value:
                    act_flag = _convert_flags_to_raw_byte(
                        FIXED_HEADER_ACTIVITY_FLAGS,
                        flags_value['activity_flags'],
                        realstarttime, realendtime)
                else:
                    act_flag = 0

                # Convert flags to bytes : i/o and clock
                if 'io_clock_flags' in flags_value:
                    io_clock_flag = _convert_flags_to_raw_byte(
                        FIXED_HEADER_IO_CLOCK_FLAGS,
                        flags_value['io_clock_flags'],
                        realstarttime, realendtime)
                else:
                    io_clock_flag = 0

                # Convert flags to bytes : data quality flags
                if 'data_qual_flags' in flags_value:
                    data_qual_flag = _convert_flags_to_raw_byte(
                        FIXED_HEADER_DATA_QUAL_FLAGS,
                        flags_value['data_qual_flags'],
                        realstarttime, realendtime)
                else:
                    data_qual_flag = 0

                flagsbytes = pack("BBB", act_flag,
                                  io_clock_flag, data_qual_flag)
                # Go back right before the fixed header flags
                mseed_file.seek(-8, os.SEEK_CUR)
                # Update flags*
                mseed_file.write(flagsbytes)
                # Seek to first blockette
                mseed_file.seek(9, os.SEEK_CUR)
            else:
                # Seek directly to first blockette
                mseed_file.seek(28, os.SEEK_CUR)

            # Read record length in blockette 1000 to seek to the next record
            reclen_pow = _search_flag_in_blockette(mseed_file, 0, 1000, 6, 1)

            if reclen_pow is None:
                msg = "Invalid MiniSEED file. No blockette 1000 was found."
                raise IOError(msg)
            else:
                reclen_pow = unpack("B", reclen_pow)[0]
                reclen = 2**reclen_pow
                mseed_file.seek(record_start + reclen, os.SEEK_SET)


def _check_flag_value(flag_value):
    """
    Search for a given flag in a given blockette for the current record.

    This is a utility function for set_flags_in_fixed_headers and is not
    designed to be called by someone else.

    This function checks for valid entries for a flag. A flag can be either
    * ``bool`` value to be always True or False for all the records
    * ``datetime`` or ``UTCDateTime`` value to add a single 'INSTANT' datation
    (see below)
    * ``dict`` to allow complex flag datation
    ** The dict keys may be the keyword INSTANT to mark arbitrarly short
    duration flags, or the keyword DURATION to mark events that span across
    time.
    ** The dict values are:
    *** for the INSTANT value, a single UTCDateTime or datetime object, or a
    list of these datation objects
    *** for the DURATION value, either a list of
    [start1, end1, start2, end2, ...] or a list of tuples
    [(start1, end1), (start2, end2), ...]


    This function then returns all datation events as a list of tuples
    [(start1, end1), ...] to ease the work of _convert_flags_to_raw_byte. Bool
    values are unchanged, instant events become a tuple
    (event_date, event_date).

    If the flag value is incorrect, a ValueError is raised with a (hopefully)
    explicit enough message.

    :type flag_value: bool or dict
    :param flag_value: the flag value to check.
    :return: corrected value of the flag.
    :raises: If the flag is not the one expected, a ``ValueError`` is raised
    """

    if isinstance(flag_value, bool):
        # bool allowed
        corrected_flag = flag_value

    elif isinstance(flag_value, datetime) or \
            isinstance(flag_value, UTCDateTime):
        # A single instant value is allowed
        utc_val = UTCDateTime(flag_value)
        corrected_flag = [(utc_val, utc_val)]

    elif isinstance(flag_value, collections.abc.Mapping):
        # dict allowed if it has the right format
        corrected_flag = []
        for flag_key in flag_value:
            if flag_key == "INSTANT":
                # Expected: list of UTCDateTime
                inst_values = flag_value[flag_key]
                if isinstance(inst_values, datetime) or \
                   isinstance(inst_values, UTCDateTime):
                    # Single value : ensure it's UTCDateTime and store it
                    utc_val = UTCDateTime(inst_values)
                    corrected_flag.append((utc_val, utc_val))
                elif isinstance(inst_values, collections.abc.Sequence):
                    # Several instant values : check their types
                    # and add each of them
                    for value in inst_values:
                        if isinstance(value, datetime) or \
                           isinstance(value, UTCDateTime):
                            utc_val = UTCDateTime(value)
                            corrected_flag.append((utc_val, utc_val))
                        else:
                            msg = "Unexpected type for flag duration " +\
                                  "'INSTANT' %s"
                            raise ValueError(msg % str(type(inst_values)))
                else:
                    msg = "Unexpected type for flag duration 'INSTANT' %s"
                    raise ValueError(msg % str(type(inst_values)))

            elif flag_key == "DURATION":
                # Expecting either a list of tuples (start, end) or
                # a list of (start1, end1, start1, end1)
                dur_values = flag_value[flag_key]
                if isinstance(dur_values, collections.abc.Sequence):
                    if len(dur_values) != 0:
                        # Check first item
                        if isinstance(dur_values[0], datetime) or \
                           isinstance(dur_values[0], UTCDateTime):
                            # List of [start1, end1, start2, end2, etc]
                            # Check len
                            if len(dur_values) % 2 != 0:
                                msg = "Expected even length of duration " +\
                                      "values, got %s"
                                raise ValueError(msg % len(dur_values))

                            # Add values
                            duration_iter = iter(dur_values)
                            for value in duration_iter:
                                start = value
                                end = dur_values[dur_values.index(value) + 1]

                                # Check start type
                                if not isinstance(start, datetime) and \
                                   not isinstance(start, UTCDateTime):
                                    msg = "Incorrect type for duration " +\
                                          "start %s"
                                    raise ValueError(msg % str(type(start)))

                                # Check end type
                                if not isinstance(end, datetime) and \
                                   not isinstance(end, UTCDateTime):
                                    msg = "Incorrect type for duration " +\
                                          "end %s"
                                    raise ValueError(msg % str(type(end)))

                                # Check duration validity
                                start = UTCDateTime(start)
                                end = UTCDateTime(end)
                                if start <= end:
                                    corrected_flag.append((start, end))
                                else:
                                    msg = "Flag datation: expected end of " +\
                                          "duration after its start"
                                    raise ValueError(msg)
                                next(duration_iter)

                        elif isinstance(dur_values[0],
                                        collections.abc.Sequence):
                            # List of tuples (start, end)
                            for value in dur_values:
                                if not isinstance(value,
                                                  collections.abc.Sequence):
                                    msg = "Incorrect type %s for flag duration"
                                    raise ValueError(msg % str(type(value)))
                                elif len(value) != 2:
                                    msg = "Incorrect len %s for flag duration"
                                    raise ValueError(msg % len(value))
                                else:
                                    start = value[0]
                                    end = value[1]

                                    # Check start type
                                    if not isinstance(start, datetime) and \
                                       not isinstance(start, UTCDateTime):
                                        msg = "Incorrect type for duration " +\
                                              "start %s"
                                        raise ValueError(msg %
                                                         str(type(start)))

                                    # Check end type
                                    if not isinstance(end, datetime) and \
                                       not isinstance(end, UTCDateTime):
                                        msg = "Incorrect type for duration " +\
                                              "end %s"
                                        raise ValueError(msg % str(type(end)))
                                    if start <= end:
                                        corrected_flag.append((start, end))
                                    else:
                                        msg = "Flag datation: expected end " +\
                                              "of duration after its start"
                                        raise ValueError(msg)

                    # Else: len(dur_values) == 0, empty duration list:
                    # do nothing
                else:
                    msg = "Incorrect DURATION value: expected a list of " +\
                          "tuples (start, end), got %s"
                    raise ValueError(msg % str(type(dur_values)))

            else:
                msg = "Invalid key %s for flag value. One of " +\
                      "'INSTANT', 'DURATION' is expected."
                raise ValueError(msg % flag_key)
    else:
        msg = "Invalid type %s for flag value. Allowed values " +\
              "are bool or dict"
        raise ValueError(msg % str(type(flag_value)))

    return corrected_flag


def _search_flag_in_blockette(mseed_file_desc, first_blockette_offset,
                              blockette_number, field_offset, field_length):
    """
    Search for a given flag in a given blockette for the current record.

    This is a utility function for set_flags_in_fixed_headers and is not
    designed to be called by someone else.

    This function uses the file descriptor``mseed_file_desc``, seeks
    ``first_blockette_offset`` to go to the first blockette, reads through all
    the blockettes until it finds the one with number ``blockette_number``,
    then skips ``field_offset`` bytes to read ``field_length`` bytes and
    returns them. If the blockette does not exist, it returns None

    Please note that this function does not decommute the binary value into an
    exploitable data (int, float, string, ...)
    :type mseed_file_desc: File object
    :param mseed_file_desc: a File descriptor to the current miniseed file.
    The value of mseed_file_desc.tell() is set back by this funcion before
    returning, use in multithread applications at your own risk.
    :type first_blockette_offset: int
    :param first_blockette_offset: tells the function where the first blockette
    of the record is compared to the mseed_file_desc current position in the
    file. A positive value means the blockette is after the current position.
    :type blockette_number: int
    :param blockette_number: the blockette number to search for
    :type field_offset: int
    :param field_offset: how many bytes we have to skip before attaining the
    wanted field. Please note that it also counts blockette number and next
    blockette index's field.
    :type field_length: int
    :param field_length: length of the wanted field, in bytes
    :return: bytes containing the field's value in this record

    """
    previous_position = mseed_file_desc.tell()

    try:
        # Go to first blockette
        mseed_file_desc.seek(first_blockette_offset, os.SEEK_CUR)
        mseed_record_start = mseed_file_desc.tell() - 48
        read_data = mseed_file_desc.read(4)
        # Read info in the first blockette
        [cur_blkt_number, next_blkt_offset] = unpack(">HH",
                                                     read_data)

        while cur_blkt_number != blockette_number \
                and next_blkt_offset != 0:
            # Nothing here, read next blockette
            mseed_file_desc.seek(mseed_record_start + next_blkt_offset,
                                 os.SEEK_SET)
            read_data = mseed_file_desc.read(4)
            [cur_blkt_number, next_blkt_offset] = unpack(">HH",
                                                         read_data)

        if cur_blkt_number == blockette_number:
            # Blockette found: we want to skip ``field_offset`` bytes but we
            # have already read 4 of the offset to get informations about the
            # current blockette, so we remove them from skipped data
            mseed_file_desc.seek(field_offset - 4, os.SEEK_CUR)
            returned_bytes = mseed_file_desc.read(field_length)
        else:
            returned_bytes = None

    finally:
        mseed_file_desc.seek(previous_position, os.SEEK_SET)

    return returned_bytes


def _convert_flags_to_raw_byte(expected_flags, user_flags, recstart, recend):
    """
    Converts a flag dictionary to a byte, ready to be encoded in a MiniSEED
    header.

    This is a utility function for set_flags_in_fixed_headers and is not
    designed to be called by someone else.

    expected_signals describes all the possible bit names for the user flags
    and their place in the result byte. Expected: dict { exponent: bit_name }.
    The fixed header flags are available in obspy.io.mseed.headers as
    FIXED_HEADER_ACTIVITY_FLAGS, FIXED_HEADER_DATA_QUAL_FLAGS and
    FIXED_HEADER_IO_CLOCK_FLAGS.

    This expects a user_flags as a dictionary { bit_name : value }. bit_name is
    compared to the expected_signals, and its value is converted to bool.
    Missing values are considered false.

    :type expected_flags: dict
    :param expected_flags: every possible flag in this field, with its offset.
        Structure: {int: str}.
    :type user_flags: dict
    :param user_flags: user defined flags and its value.
        Structure: {str: bool}.
    :type recstart: UTCDateTime
    :param recstart: date of the first sample of the current record
    :type recstart: UTCDateTime
    :param recend: date of the last sample of the current record
    :return: raw int value for the flag group
    """

    flag_byte = 0

    for (bit, key) in expected_flags.items():
        use_in_this_record = False
        if key in user_flags:
            if isinstance(user_flags[key], bool) and user_flags[key]:
                # Boolean value, we accept it for all records
                use_in_this_record = True
            elif isinstance(user_flags[key], collections.abc.Sequence):
                # List of tuples (start, end)
                use_in_this_record = False
                for tuple_value in user_flags[key]:
                    # Check wether this record is concerned
                    event_start = tuple_value[0]
                    event_end = tuple_value[1]

                    if (event_start < recend) and (recstart <= event_end):
                        use_in_this_record = True
                        break

        if use_in_this_record:
            flag_byte += 2**bit

    return flag_byte


def shift_time_of_file(input_file, output_file, timeshift):
    """
    Takes a MiniSEED file and shifts the time of every record by the given
    amount.

    The same could be achieved by reading the MiniSEED file with ObsPy,
    modifying the starttime and writing it again. The problem with this
    approach is that some record specific flags and special blockettes might
    not be conserved. This function directly operates on the file and simply
    changes some header fields, not touching the rest, thus preserving it.

    Will only work correctly if all records have the same record length which
    usually should be the case.

    All times are in 0.0001 seconds, that is in 1/10000 seconds. NOT ms but one
    order of magnitude smaller! This is due to the way time corrections are
    stored in the MiniSEED format.

    :type input_file: str
    :param input_file: The input filename.
    :type output_file: str
    :param output_file: The output filename.
    :type timeshift: int
    :param timeshift: The time-shift to be applied in 0.0001, e.g. 1E-4
        seconds. Use an integer number.

    Please do NOT use identical input and output files because if something
    goes wrong, your data WILL be corrupted/destroyed. Also always check the
    resulting output file.

    .. rubric:: Technical details

    The function will loop over every record and change the "Time correction"
    field in the fixed section of the MiniSEED data header by the specified
    amount. Unfortunately a further flag (bit 1 in the "Activity flags" field)
    determines whether or not the time correction has already been applied to
    the record start time. If it has not, all is fine and changing the "Time
    correction" field is enough. Otherwise the actual time also needs to be
    changed.

    One further detail: If bit 1 in the "Activity flags" field is 1 (True) and
    the "Time correction" field is 0, then the bit will be set to 0 and only
    the time correction will be changed thus avoiding the need to change the
    record start time which is preferable.
    """
    timeshift = int(timeshift)
    # A timeshift of zero makes no sense.
    if timeshift == 0:
        msg = "The timeshift must to be not equal to 0."
        raise ValueError(msg)

    # Get the necessary information from the file.
    info = get_record_information(input_file)
    record_length = info["record_length"]

    byteorder = info["byteorder"]
    sys_byteorder = "<" if (sys.byteorder == "little") else ">"
    do_swap = False if (byteorder == sys_byteorder) else True

    # This is in this scenario somewhat easier to use than BytesIO because one
    # can directly modify the data array.
    data = np.fromfile(input_file, dtype=np.uint8)
    array_length = len(data)
    record_offset = 0
    # Loop over every record.
    while True:
        remaining_bytes = array_length - record_offset
        if remaining_bytes < 48:
            if remaining_bytes > 0:
                msg = "%i excessive byte(s) in the file. " % remaining_bytes
                msg += "They will be appended to the output file."
                warnings.warn(msg)
            break
        # Use a slice for the current record.
        current_record = data[record_offset: record_offset + record_length]
        record_offset += record_length

        activity_flags = current_record[36]
        is_time_correction_applied = bool(activity_flags & 2)

        current_time_shift = current_record[40:44]
        current_time_shift.dtype = np.int32
        if do_swap:
            current_time_shift = current_time_shift.byteswap(False)
        current_time_shift = current_time_shift[0]

        # If the time correction has been applied, but there is no actual
        # time correction, then simply set the time correction applied
        # field to false and process normally.
        # This should rarely be the case.
        if current_time_shift == 0 and is_time_correction_applied:
            # This sets bit 2 of the activity flags to 0.
            current_record[36] = np.int64(current_record[36]) & (~2)
            is_time_correction_applied = False
        # This is the case if the time correction has been applied. This
        # requires some more work by changing both, the actual time and the
        # time correction field.
        elif is_time_correction_applied:
            msg = "The timeshift can only be applied by actually changing the "
            msg += "time. This is experimental. Please make sure the output "
            msg += "file is correct."
            warnings.warn(msg)
            # The whole process is not particularly fast or optimized but
            # instead intends to avoid errors.
            # Get the time variables.
            time = current_record[20:30]
            year = time[0:2]
            julday = time[2:4]
            hour = time[4:5]
            minute = time[5:6]
            second = time[6:7]
            msecs = time[8:10]
            # Change dtype of multibyte values.
            year.dtype = np.uint16
            julday.dtype = np.uint16
            msecs.dtype = np.uint16
            if do_swap:
                year = year.byteswap(False)
                julday = julday.byteswap(False)
                msecs = msecs.byteswap(False)
            dtime = UTCDateTime(year=year[0], julday=julday[0], hour=hour[0],
                                minute=minute[0], second=second[0],
                                microsecond=msecs[0] * 100)
            dtime += (float(timeshift) / 10000)
            year[0] = dtime.year
            julday[0] = dtime.julday
            hour[0] = dtime.hour
            minute[0] = dtime.minute
            second[0] = dtime.second
            msecs[0] = dtime.microsecond / 100
            # Swap again.
            if do_swap:
                year = year.byteswap(False)
                julday = julday.byteswap(False)
                msecs = msecs.byteswap(False)
            # Change dtypes back.
            year.dtype = np.uint8
            julday.dtype = np.uint8
            msecs.dtype = np.uint8
            # Write to current record.
            time[0:2] = year[:]
            time[2:4] = julday[:]
            time[4] = hour[0]
            time[5] = minute[0]
            time[6] = second[0]
            time[8:10] = msecs[:]
            current_record[20:30] = time[:]

        # Now modify the time correction flag.
        current_time_shift += timeshift
        current_time_shift = np.array([current_time_shift], np.int32)
        if do_swap:
            current_time_shift = current_time_shift.byteswap(False)
        current_time_shift.dtype = np.uint8
        current_record[40:44] = current_time_shift[:]

    # Write to the output file.
    data.tofile(output_file)


def spread_time_over_file(input_file, output_file, timeshift):
    """
    Takes a MiniSEED file and a time shift and changes each record to gradually
    spread the given time shift across all of the blockettes.  The intended use
    is to correct apparent gaps or overlaps less than a sample interval in
    continuous data that could arise due to hardware (clock drift) or
    software (rounding errors in time calculations during data management).

    The same could be achieved by reading the MiniSEED file with ObsPy,
    modifying the sample times and writing it again. The problem with this
    approach is that some record specific flags and special blockettes might
    not be conserved. This function directly operates on the file and simply
    changes some header fields, not touching the rest, thus preserving it.

    Will work correctly only if all records have the same record length; this
    usually should be the case.

    All times are in 0.0001 seconds, that is in 1/10000 seconds. NOT ms but one
    order of magnitude smaller! This is due to the way time corrections are
    stored in the MiniSEED format.

    :type input_file: str
    :param input_file: The input filename.
    :type output_file: str
    :param output_file: The output filename.
    :type timeshift: int
    :param timeshift: The cumulative time shift to be progressively applied in
        units of 0.0001 s.  Use an integer number, e.g. ``10`` for a total
        cumulative time shift of one millisecond.

    It is strongly recommended to not work directly on the original data to
    avoid data loss in case anything goes wrong. Also always check
    the resulting output file.

    .. rubric:: Technical details

    The function will loop over every record and change the "Time correction"
    field in the fixed section of the MiniSEED header by ``I*timeshift/(N-1)``,
    where N is the number of blockettes in the file and I is the blockette
    number (starting with zero).  Thus the start time of the file will be
    unchanged, but the end time will be later or earlier.  Unfortunately
    a further flag (bit 1 in the "Activity flags" field) determines whether or
    not the time correction has already been applied to the record start time.
    If it has not, all is fine and changing the "Time correction" field is
    enough.  Otherwise the actual time also needs to be changed.

    One further detail: If bit 1 in the "Activity flags" field is 1 (True) and
    the "Time correction" field is 0, then the bit will be set to 0 and only
    the time correction will be changed thus avoiding the need to change the
    record start time which is preferable.
    """

    if timeshift != int(timeshift):
        msg = "The time shift must be an integer."
        raise ValueError(msg)

    timeshift = int(timeshift)
    # A timeshift of zero makes no sense.
    if timeshift == 0:
        msg = "The timeshift must to be not equal to 0."
        raise ValueError(msg)

    # Get the necessary information from the file.
    info = get_record_information(input_file)
    record_length = info["record_length"]

    byteorder = info["byteorder"]
    sys_byteorder = "<" if (sys.byteorder == "little") else ">"
    do_swap = False if (byteorder == sys_byteorder) else True

    # This is in this scenario somewhat easier to use than BytesIO because one
    # can directly modify the data array.
    data = np.fromfile(input_file, dtype=np.uint8)
    array_length = len(data)
    N = int(array_length / record_length) - 1
    shift = timeshift / N

    # Loop over every record after the first.
    for i in range(1, N+1):
        remaining_bytes = array_length - i*record_length
        if remaining_bytes < 48:
            if remaining_bytes > 0:
                msg = "%i excessive byte(s) in the file. " % remaining_bytes
                msg += "They will be appended to the output file."
                warnings.warn(msg)
            break
        # Use a slice for the current record.
        current_record = data[i*record_length: (i+1)*record_length]

        activity_flags = current_record[36]
        is_time_correction_applied = bool(activity_flags & 2)

        current_time_shift = current_record[40:44]
        current_time_shift.dtype = np.int32
        if do_swap:
            current_time_shift = current_time_shift.byteswap(False)
        current_time_shift = current_time_shift[0]

        # If the time correction has been applied, but there is no actual
        # time correction, then simply set the time correction applied
        # field to false and process normally.
        # This should rarely be the case.
        if current_time_shift == 0 and is_time_correction_applied:
            # This sets bit 2 of the activity flags to 0.
            current_record[36] = current_record[36] & (~2)
            is_time_correction_applied = False
        # This is the case if the time correction has been applied. This
        # requires some more work by changing both, the actual time and the
        # time correction field.
        elif is_time_correction_applied:
            msg = "The time shift can only be applied by actually changing the"
            msg += " time. This is experimental. Please make sure the output "
            msg += "file is correct."
            warnings.warn(msg)
            # The whole process is not particularly fast or optimized but
            # instead intends to avoid errors.
            # Get the time variables.
            time = current_record[20:30]
            year = time[0:2]
            julday = time[2:4]
            hour = time[4:5]
            minute = time[5:6]
            second = time[6:7]
            msecs = time[8:10]
            # Change dtype of multibyte values.
            year.dtype = np.uint16
            julday.dtype = np.uint16
            msecs.dtype = np.uint16
            if do_swap:
                year = year.byteswap(False)
                julday = julday.byteswap(False)
                msecs = msecs.byteswap(False)
            dtime = UTCDateTime(year=year[0], julday=julday[0], hour=hour[0],
                                minute=minute[0], second=second[0],
                                microsecond=msecs[0] * 100)
            dtime += (float(i*shift) / 10000)
            year[0] = dtime.year
            julday[0] = dtime.julday
            hour[0] = dtime.hour
            minute[0] = dtime.minute
            second[0] = dtime.second
            msecs[0] = dtime.microsecond / 100
            # Swap again.
            if do_swap:
                year = year.byteswap(False)
                julday = julday.byteswap(False)
                msecs = msecs.byteswap(False)
            # Change dtypes back.
            year.dtype = np.uint8
            julday.dtype = np.uint8
            msecs.dtype = np.uint8
            # Write to current record.
            time[0:2] = year[:]
            time[2:4] = julday[:]
            time[4] = hour[:]
            time[5] = minute[:]
            time[6] = second[:]
            time[8:10] = msecs[:]
            current_record[20:30] = time[:]

        # Now modify the time correction flag.
        current_time_shift += int(i*shift)
        if current_time_shift != 0:
            current_time_shift = np.array([current_time_shift], np.int32)
            if do_swap:
                current_time_shift = current_time_shift.byteswap(False)
            current_time_shift.dtype = np.uint8
            current_record[40:44] = current_time_shift[:]

    # Write to the output file.
    data.tofile(output_file)


def _convert_and_check_encoding_for_writing(encoding):
    """
    Helper function to handle and test encodings.

    If encoding is a string, it will be converted to the appropriate
    integer. It will furthermore be checked if the specified encoding can be
    written using libmseed. Appropriate errors will be raised if necessary.
    """
    # Check if encoding kwarg is set and catch invalid encodings.
    encoding_strings = {v[0]: k for k, v in ENCODINGS.items()}

    try:
        encoding = int(encoding)
    except Exception:
        pass

    if isinstance(encoding, int):
        if (encoding in ENCODINGS and ENCODINGS[encoding][3] is False) or \
                encoding in UNSUPPORTED_ENCODINGS:
            msg = ("Encoding %i cannot be written with ObsPy. Please "
                   "use another encoding.") % encoding
            raise ValueError(msg)
        elif encoding not in ENCODINGS:
            raise ValueError("Unknown encoding: %i." % encoding)
    else:
        if encoding not in encoding_strings:
            raise ValueError("Unknown encoding: '%s'." % str(encoding))
        elif ENCODINGS[encoding_strings[encoding]][3] is False:
            msg = ("Encoding '%s' cannot be written with ObsPy. Please "
                   "use another encoding.") % encoding
            raise ValueError(msg)
        encoding = encoding_strings[encoding]
    return encoding


def get_timing_and_data_quality(file_or_file_object):
    warnings.warn("The obspy.io.mseed.util.get_timing_and_data_quality() "
                  "function is deprecated and will be removed with the next "
                  "release. Please use the "
                  "improved obspy.io.mseed.util.get_flags() method instead.",
                  ObsPyDeprecationWarning)
    flags = get_flags(files=file_or_file_object, io_flags=False,
                      activity_flags=False, data_quality_flags=True,
                      timing_quality=True)

    ret_val = {}
    ret_val["data_quality_flags"] = \
        list(flags["data_quality_flags_counts"].values())

    if flags["timing_quality"]:
        tq = flags["timing_quality"]
        ret_val["timing_quality_average"] = tq["mean"]
        ret_val["timing_quality_lower_quantile"] = tq["lower_quartile"]
        ret_val["timing_quality_max"] = tq["max"]
        ret_val["timing_quality_median"] = tq["median"]
        ret_val["timing_quality_min"] = tq["min"]
        ret_val["timing_quality_upper_quantile"] = tq["lower_quartile"]

    return ret_val


if __name__ == '__main__':
    import doctest
    doctest.testmod(exclude_empty=True)
