Python Dataset.naming_authority方法代码示例

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import naming_authority [as 别名]
def generate_nc(parser_context):
    parser = XLSParser()
    with open(parser_context.filepath, 'r') as f:
        doc = f.read()
    info = parser.extract_worksheets(doc)
    nccl = info[parser_context.worksheet]
    #header_line = 3
    #columns = nccl[header_line]
    #data_range = (4, 66)
    data_rows = nccl[parser_context.data_range[0]:parser_context.data_range[1]]
    print 'Generating',parser_context.output_file
    nc = Dataset(parser_context.output_file, 'w')
    nc.createDimension('time', len(data_rows)*12)
    nc.GDAL = "GDAL 1.9.2, released 2012/10/08"
    nc.history = "Created dynamically in IPython Notebook 2013-11-14"
    nc.title = nccl[0][0]
    nc.summary = nccl[1][0]
    nc.naming_authority = 'GLOS'
    nc.source = 'GLERL'
    nc.standard_name_vocabulary = "http://www.cgd.ucar.edu/cms/eaton/cf-metadata/standard_name.html"
    nc.project = 'GLOS'
    nc.Conventions = "CF-1.6"
    time = nc.createVariable('time', 'f8', ('time',))
    time.standard_name = 'time'
    time.units = 'seconds since 1970-01-01'
    time.long_name = 'Time'
    time.axis = 'T'
    precip = nc.createVariable(parser_context.variable, 'f8', ('time',), fill_value=parser_context.fill_value)
    #precip.standard_name = 'precipitation_amount'
    precip.standard_name = parser_context.standard_name

    precip.units = parser_context.units
    for i,row in enumerate(data_rows):
        for j in xrange(12):
            the_date = datetime(row[0], j+1, 1)
            timestamp = calendar.timegm(the_date.utctimetuple())
            time[i*12 + j] = timestamp
            try:
                value = float(row[j+1])
            except ValueError:
                continue
            except TypeError:
                continue

            precip[i*12 + j] = value
    nc.close() 

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import naming_authority [as 别名]

#.........这里部分代码省略.........
    if fields[4] == "":
      sals[i, 0] = -9999
    else:
      sals[i, 0] = fields[4]

    if fields[5] == "":
      fco2s[i, 0] = -9999
    else:
      fco2s[i, 0] = fields[5]

    if len(fields[6]) == 0:
      fco2qcs[i, 0] = -128
    else:
      fco2qcs[i, 0] = makeqcvalue_(int(fields[6]))

  depthvar[:,:] = depths
  positionvar[:,:] = positions
  sstvar[:,:] = temps
  sssvar[:,:] = sals
  fco2var[:,:] = fco2s
  fco2qcvar[:,:] = fco2qcs
  depthdmvar[:,:] = dms
  sstdmvar[:,:] = dms
  sssdmvar[:,:] = dms
  fco2dmvar[:,:] = dms

  # Global attributes
  nc.id = filenameroot

  nc.data_type = "OceanSITES trajectory data"
  nc.netcdf_version = "netCDF-4 classic model"
  nc.format_version = "1.2"
  nc.Conventions = "CF-1.6 OceanSITES-Manual-1.2 Copernicus-InSituTAC-SRD-1.3 "\
    + "Copernicus-InSituTAC-ParametersList-3.1.0"

  nc.cdm_data_type = "Trajectory"
  nc.data_mode = "R"
  nc.area = "Global Ocean"

  nc.geospatial_lat_min = str(minlat)
  nc.geospatial_lat_max = str(maxlat)
  nc.geospatial_lon_min = str(minlon)
  nc.geospatial_lon_max = str(maxlon)
  nc.geospatial_vertical_min = "5.00"
  nc.geospatial_vertical_max = "5.00"

  nc.last_latitude_observation = lats[-1]
  nc.last_longitude_observation = lons[-1]
  nc.last_date_observation = endtime.strftime("%Y-%m-%dT%H:%M:%SZ")
  nc.time_coverage_start = starttime.strftime("%Y-%m-%dT%H:%M:%SZ")
  nc.time_coverage_end = endtime.strftime("%Y-%m-%dT%H:%M:%SZ")

  #datasetdate = datetime.datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%SZ")
  #nc.date_update = datetime.datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%SZ")
  #nc.history = datasetdate + " : Creation"

  nc.update_interval = "daily"

  nc.data_assembly_center = "BERGEN"
  nc.institution = "University of Bergen / Geophysical Institute"
  nc.institution_edmo_code = "4595"
  nc.institution_references = " "
  nc.contact = "[email protected]"
  nc.title = "Global Ocean - In Situ near-real time carbon observation"
  nc.author = "cmems-service"
  nc.naming_authority = "Copernicus"

  nc.platform_code = getplatformcallsign_(platform_code)
  nc.site_code = getplatformcallsign_(platform_code)

  # For buoys -> Mooring observation.
  platform_category_code = getplatformcategorycode_(platform_code)
  nc.platform_name = getplatformname_(platform_code)
  nc.source_platform_category_code = platform_category_code
  nc.source = PLATFORM_CODES[platform_category_code]

  nc.quality_control_indicator = "6" # "Not used"
  nc.quality_index = "0"

  nc.comment = " "
  nc.summary = " "
  nc.reference = "http://marine.copernicus.eu/, https://www.icos-cp.eu/"
  nc.citation = "These data were collected and made freely available by the " \
    + "Copernicus project and the programs that contribute to it."
  nc.distribution_statement = "These data follow Copernicus standards; they " \
    + "are public and free of charge. User assumes all risk for use of data. " \
    + "User must display citation in any publication or product using data. " \
    + "User must contact PI prior to any commercial use of data."

  # Write the netCDF
  nc.close()

  # Read the netCDF file into memory
  with open(ncpath, "rb") as ncfile:
    ncbytes = ncfile.read()

  # Delete the temp netCDF file
  os.remove(ncpath)

  return [filenameroot, ncbytes]

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import naming_authority [as 别名]
def modify_aims_netcdf(netcdf_file_path, channel_id_info):
    """ Modify the downloaded netCDF file so it passes both CF and IMOS checker
    input:
       netcdf_file_path(str)    : path of netcdf file to modify
       channel_id_index(dict) : information from xml for the channel
    """
    imos_env_path = os.path.join(os.environ.get('DATA_SERVICES_DIR'), 'lib', 'netcdf', 'imos_env')
    if not os.path.isfile(imos_env_path):
        logger = logging_aims()
        logger.error('%s is not accessible' % imos_env_path)
        close_logger(logger)
        sys.exit(1)

    dotenv.load_dotenv(imos_env_path)
    netcdf_file_obj = Dataset(netcdf_file_path, 'a', format='NETCDF4')
    netcdf_file_obj.naming_authority = 'IMOS'

    # add gatts to NetCDF
    netcdf_file_obj.aims_channel_id = int(channel_id_info['channel_id'])

    if not (channel_id_info['metadata_uuid'] == 'Not Available'):
        netcdf_file_obj.metadata_uuid = channel_id_info['metadata_uuid']

    if not netcdf_file_obj.instrument_serial_number:
        del(netcdf_file_obj.instrument_serial_number)

    # add CF gatts, values stored in lib/netcdf/imos_env
    netcdf_file_obj.Conventions            = os.environ.get('CONVENTIONS')
    netcdf_file_obj.data_centre_email      = os.environ.get('DATA_CENTRE_EMAIL')
    netcdf_file_obj.data_centre            = os.environ.get('DATA_CENTRE')
    netcdf_file_obj.project                = os.environ.get('PROJECT')
    netcdf_file_obj.acknowledgement        = os.environ.get('ACKNOWLEDGEMENT')
    netcdf_file_obj.distribution_statement = os.environ.get('DISTRIBUTION_STATEMENT')

    netcdf_file_obj.date_created           = strftime("%Y-%m-%dT%H:%M:%SZ", gmtime())
    netcdf_file_obj.quality_control_set    = 1
    imos_qc_convention                     = 'IMOS standard set using the IODE flags'
    netcdf_file_obj.author                 = 'laurent besnard'
    netcdf_file_obj.author_email           = '[email protected]'

    rename_netcdf_attribute(netcdf_file_obj, 'geospatial_LAT_max', 'geospatial_lat_max')
    rename_netcdf_attribute(netcdf_file_obj, 'geospatial_LAT_min', 'geospatial_lat_min')
    rename_netcdf_attribute(netcdf_file_obj, 'geospatial_LON_max', 'geospatial_lon_max')
    rename_netcdf_attribute(netcdf_file_obj, 'geospatial_LON_min', 'geospatial_lon_min')

    # variables modifications
    time           = netcdf_file_obj.variables['time']
    time.calendar  = 'gregorian'
    time.axis      = 'T'
    time.valid_min = 0.0
    time.valid_max = 9999999999.0
    netcdf_file_obj.renameDimension('time', 'TIME')
    netcdf_file_obj.renameVariable('time', 'TIME')

    netcdf_file_obj.time_coverage_start = num2date(time[:], time.units, time.calendar).min().strftime('%Y-%m-%dT%H:%M:%SZ')
    netcdf_file_obj.time_coverage_end   = num2date(time[:], time.units, time.calendar).max().strftime('%Y-%m-%dT%H:%M:%SZ')

    # latitude longitude
    latitude                  = netcdf_file_obj.variables['LATITUDE']
    latitude.axis             = 'Y'
    latitude.valid_min        = -90.0
    latitude.valid_max        = 90.0
    latitude.reference_datum  = 'geographical coordinates, WGS84 projection'
    latitude.standard_name    = 'latitude'
    latitude.long_name        = 'latitude'

    longitude                 = netcdf_file_obj.variables['LONGITUDE']
    longitude.axis            = 'X'
    longitude.valid_min       = -180.0
    longitude.valid_max       = 180.0
    longitude.reference_datum = 'geographical coordinates, WGS84 projection'
    longitude.standard_name   = 'longitude'
    longitude.long_name       = 'longitude'

    # handle masked arrays
    lon_array = longitude[:]
    lat_array = latitude[:]
    if type(lon_array) != numpy.ma.core.MaskedArray or len(lon_array) == 1:
        netcdf_file_obj.geospatial_lon_min = min(lon_array)
        netcdf_file_obj.geospatial_lon_max = max(lon_array)
    else:
        netcdf_file_obj.geospatial_lon_min = numpy.ma.MaskedArray.min(lon_array)
        netcdf_file_obj.geospatial_lon_max = numpy.ma.MaskedArray.max(lon_array)

    if type(lat_array) != numpy.ma.core.MaskedArray or len(lat_array) == 1:
        netcdf_file_obj.geospatial_lat_min = min(lat_array)
        netcdf_file_obj.geospatial_lat_max = max(lat_array)
    else:
        numpy.ma.MaskedArray.min(lat_array)
        netcdf_file_obj.geospatial_lat_min = numpy.ma.MaskedArray.min(lat_array)
        netcdf_file_obj.geospatial_lat_max = numpy.ma.MaskedArray.max(lat_array)

    # Change variable name, standard name, longname, untis ....
    if 'Seawater_Intake_Temperature' in netcdf_file_obj.variables.keys():
        var                     = netcdf_file_obj.variables['Seawater_Intake_Temperature']
        var.units               = 'Celsius'
        netcdf_file_obj.renameVariable('Seawater_Intake_Temperature', 'TEMP')
        netcdf_file_obj.renameVariable('Seawater_Intake_Temperature_quality_control', 'TEMP_quality_control')
        var.ancillary_variables = 'TEMP_quality_control'

#.........这里部分代码省略.........

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import naming_authority [as 别名]
                   "University of Colorado at Boulder\n",
                   "Boulder, CO"]
fid.publisher = ["National Snow and Ice Data Center\n",
                   "Cooperative Institute for Research in Environmental Sciences\n",
                   "University of Colorado at Boulder\n",
                   "Boulder, CO"]
fid.publisher_url = "http://nsidc.org/charis"
fid.publisher_email = "[email protected]"
fid.project = "CHARIS"
fid.standard_name_vocabulary = "CF Standard Name Table (v27, 28 September 2013)"
fid.cdm_data_type = "grid"
fid.keywords = "EARTH SCIENCE > SPECTRAL/ENGINEERING > MICROWAVE > BRIGHTNESS TEMPERATURE" 
fid.keywords_vocabulary = "NASA Global Change Master Directory (GCMD) Earth Science Keywords, Version 8.1"
fid.platform = "TBD"
fid.sensor = "TBD"
fid.naming_authority = "org.doi.dx"
fid.id = "10.5067/MEASURES/CRYOSPHERE/nsidc-0630.001"
fid.date_created = "TBD"
fid.acknowledgement = ["This data set was created with funding from NASA MEaSUREs Grant #NNX13AI23A.\n",
                       "Data archiving and distribution is supported by the NASA NSIDC Distributed Active Archive Center (DAAC)."]
fid.license = "No constraints on data access or use"
fid.processing_level = "Level 3"
fid.creator_name = "Mary J. Brodzik"
fid.creator_email = "[email protected]"
fid.creator_url = "http://nsidc.org/charis"
fid.contributor_name = "T. H. Painter, M. J. Brodzik, R. L. Armstrong"
fid.contributor_role = "Principal Investigator, Co-Investigator, Co-Investigator"
fid.citation = ["Brodzik, M. J., D. G. Long, M. A. Hardman, A. C. Paget. 2015.\n",
                "MEaSUREs Calibrated Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature ESDR.\n",
                "Version 0.01.\n",
                "[Indicate subset used].\n",

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import naming_authority [as 别名]
shutil.copy2(gliderdir + gliderfile, outputdir + outputfile)

# Open netCDF file to modify names and attributes
rootgrp = Dataset(outputdir + outputfile, 'r+', format='NETCDF4')

# Dimension
rootgrp.renameDimension('time', 'TIME')


# Global attributes
rootgrp.data_type = 'EGO glider time-series data'
rootgrp.format_version = '1.0'
rootgrp.platform_code = '99999'
rootgrp.date_update = change_dataformat(rootgrp.date_modified)  # should be converted from rootgrp.date_modified
rootgrp.data_mode = data_mode_dic[rootgrp.data_mode]
rootgrp.naming_authority = 'EGO'
rootgrp.id = outputfile.split('.')[0]  # taken from file name... maybe something better to do
rootgrp.source = "Glider observation"
rootgrp.Conventions = "CF-1.4 EGO-1.0"
rootgrp.geospatial_lat_min = str(rootgrp.geospatial_lat_min)
rootgrp.geospatial_lat_max = str(rootgrp.geospatial_lat_max)
rootgrp.geospatial_lon_min = str(rootgrp.geospatial_lon_min)
rootgrp.geospatial_lon_max = str(rootgrp.geospatial_lon_max)

rootgrp.time_coverage_start = change_dataformat(rootgrp.time_coverage_start)
rootgrp.time_coverage_end = change_dataformat(rootgrp.time_coverage_end)

rootgrp.renameVariable('depth', 'DEPTH')

# Rename TIME variable and add attributes
rootgrp.renameVariable('time', 'TIME')