Source code for obspy.io.mseed.util
# -*- 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, collections_abc
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)
[docs]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
[docs]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, 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):
# 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,
}
[docs]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):
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
[docs]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
[docs]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
[docs]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
[docs]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
[docs]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
[docs]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)))
[docs]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
[docs]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
[docs]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+samp_rate*(nb_samples-1)
# 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)
[docs]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
[docs]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
[docs]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
[docs]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] = 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[:]
time[5] = minute[:]
time[6] = second[:]
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)
[docs]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
[docs]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)