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
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, :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, }
[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, 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
[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+(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)
[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[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)
[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)