Python Dataset.keywords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 keywords [as 别名]
def create_mhl_sst_ncfile(txtfile, site_code_short, data,
                          time, dtime, spatial_data):
    """
    create NetCDF file for MHL Wave data
    """
    site_code = site_list[site_code_short][0]
    netcdf_filename = create_netcdf_filename(site_code, data, dtime)
    netcdf_filepath = os.path.join(
        output_folder, "%s.nc") % netcdf_filename
    ncfile = Dataset(netcdf_filepath, "w", format="NETCDF4")


    # generate site and deployment specific attributes
    ncfile.title = ("IMOS - ANMN New South Wales(NSW) %s "
                    "Sea water temperature (%s) -"
                    "Deployment No. %s %s to %s") % (
            site_list[site_code_short][1], site_code,
            spatial_data[0], min(dtime).strftime("%d-%m-%Y"),
            max(dtime).strftime("%d-%m-%Y"))
    ncfile.institution = 'Manly Hydraulics Laboratory'
    ncfile.keywords = ('Oceans | Ocean temperature |'
                           'Sea Surface Temperature')
    ncfile.principal_investigator = 'Mark Kulmar'
    ncfile.cdm_data_type = 'Station'
    ncfile.platform_code = site_code

    abstract_default = ("The sea water temperature is measured by a thermistor mounted in the "
                        "buoy hull approximately 400 mm below the water "
                        "surface.  The thermistor has a resolution of 0.05 "
                        "Celsius and an accuracy of 0.2 Celsius.  The "
                        "measurements are transmitted to a shore station "
                        "where it is stored on a PC before routine transfer "
                        "to Manly Hydraulics Laboratory via email.")

    if site_code_short in ['COF', 'CRH', 'EDE', 'PTK']:

        abstract_specific = ("This dataset contains sea water temperature "
                             "data collected by a wave monitoring buoy moored off %s. ") % site_list[site_code_short][1]
    else:
        abstract_specific = ("This dataset contains sea water temperature "
                             "data collected by a wave monitoring buoy moored off %s "
                             "approximately %s kilometres from the coastline. ") % (

                          site_list[site_code_short][1], site_list[site_code_short][2])

    ncfile.abstract = abstract_specific + abstract_default
    ncfile.comment = ("The sea water temperature data (SST) is routinely quality controlled (usually twice per week) "
                      "using a quality control program developed by Manly Hydraulics Laboratory.  The SST data gathered "
                      "by the buoy is regularly compared to the latest available satellite derived sea SST images available "
                      "from the Bluelink ocean forecasting web pages to ensure the integrity of the dataset.  Erroneous SST "
                      "records are removed and good quality data is flagged as \'Quality Controlled\' in the "
                      "Manly Hydraulics Laboratory SST database.") 
    ncfile.sourceFilename = os.path.basename(txtfile)
    ncfile.date_created = datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%SZ")
    ncfile.time_coverage_start = min(dtime).strftime("%Y-%m-%dT%H:%M:%SZ")
    ncfile.time_coverage_end = max(dtime).strftime("%Y-%m-%dT%H:%M:%SZ")
    ncfile.geospatial_lat_min = spatial_data[1]
    ncfile.geospatial_lat_max = spatial_data[1]
    ncfile.geospatial_lon_min = spatial_data[2]
    ncfile.geospatial_lon_max = spatial_data[2]
    ncfile.geospatial_vertical_max = 0.
    ncfile.geospatial_vertical_min = 0.
    ncfile.deployment_number = str(spatial_data[0])

    # add dimension and variables
    ncfile.createDimension('TIME', len(time))

    TIME = ncfile.createVariable('TIME', "d", 'TIME')
    TIMESERIES = ncfile.createVariable('TIMESERIES', "i")
    LATITUDE = ncfile.createVariable(
        'LATITUDE', "d", fill_value=99999.)
    LONGITUDE = ncfile.createVariable(
        'LONGITUDE', "d", fill_value=99999.)
    TEMP = ncfile.createVariable('TEMP', "f", 'TIME', fill_value=99999.)

    # add global attributes and variable attributes stored in config files
    config_file = os.path.join(os.getcwd(), 'global_att_sst.att')
    generate_netcdf_att(ncfile, config_file,
                        conf_file_point_of_truth=False)
    
    # replace nans with fillvalue in dataframe
    data = data.fillna(value=float(99999.))

    TIME[:] = time
    TIMESERIES[:] = 1
    LATITUDE[:] = spatial_data[1]
    LONGITUDE[:] = spatial_data[2]
    TEMP[:] = data['SEA_TEMP'].values
    ncfile.close()

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import keywords [as 别名]
def create_mhl_wave_ncfile(txtfile, site_code_short, data,
                           time, dtime, spatial_data):
    """
    create NetCDF file for MHL Wave data
    """
    site_code = site_list[site_code_short][0]
    netcdf_filename = create_netcdf_filename(site_code, data, dtime)
    netcdf_filepath = os.path.join(
        output_folder, "%s.nc") % netcdf_filename
    ncfile = Dataset(netcdf_filepath, "w", format="NETCDF4")

    # add IMOS1.4 global attributes and variable attributes stored in config
    # files
    config_file = os.path.join(os.getcwd(),'mhl_wave_library', 'global_att_wave.att')
    generate_netcdf_att(ncfile, config_file,
                        conf_file_point_of_truth=False)
    # Additional attribute either retrieved from original necdtf file
    # (if exists) or defined below
    original_netcdf_file_path = os.path.join(
        input_folder, "%s.nc") % netcdf_filename

    if os.path.exists(original_netcdf_file_path):
        # get glob attributes from original netcdf files.
        parse_nc_attribute(original_netcdf_file_path, ncfile)
    else:
        # generate site and deployment specific attributes
        ncfile.title = ("IMOS - ANMN New South Wales(NSW) %s"
                        "Offshore Wave Data (% s) -"
                        "Deployment No. %s %s to %s") % (
            site_list[site_code_short][1], site_code,
            spatial_data[0], min(dtime).strftime("%d-%m-%Y"),
            max(dtime).strftime("%d-%m-%Y"))
        ncfile.institution = 'Manly Hydraulics Laboratory'
        ncfile.keywords = ('Oceans | Ocean Waves |'
                           'Significant Wave Height, Oceans | Ocean Waves'
                           '| Wave Period, Oceans | Ocean Waves |'
                           'Wave Spectra, Oceans | Ocean Waves |'
                           'Wave Speed / direction')
        ncfile.principal_investigator = 'Mark Kulmar'
        ncfile.cdm_data_type = 'Station'
        ncfile.platform_code = site_code
        ncfile.site_name = site_list[site_code_short][1]
        if site_code in ['WAVEPOK', 'WAVECOH', 'WAVECRH', 'WAVEEDN']:
            config_file = os.path.join(
                os.getcwd(), 'common', 'abstract_WAVE_default.att')
        elif site_code == 'WAVEBAB':
            config_file = os.path.join(os.getcwd(),'common', 'abstract_WAVEBAB.att')
        elif site_code == 'WAVEBYB':
            config_file = os.path.join(os.getcwd(), 'common', 'abstract_WAVEBYB.att')
        else:  # WAVESYD
            config_file = os.path.join(os.getcwd(), 'common', 'abstract_WAVESYD.att')

        generate_netcdf_att(ncfile, config_file,
                            conf_file_point_of_truth=False)

    ncfile.sourceFilename = os.path.basename(txtfile)
    ncfile.date_created = datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%SZ")
    ncfile.time_coverage_start = min(dtime).strftime("%Y-%m-%dT%H:%M:%SZ")
    ncfile.time_coverage_end = max(dtime).strftime("%Y-%m-%dT%H:%M:%SZ")
    ncfile.geospatial_lat_min = spatial_data[1]
    ncfile.geospatial_lat_max = spatial_data[1]
    ncfile.geospatial_lon_min = spatial_data[2]
    ncfile.geospatial_lon_max = spatial_data[2]
    ncfile.geospatial_vertical_max = 0.
    ncfile.geospatial_vertical_min = 0.
    ncfile.deployment_number = str(spatial_data[0])

    # add dimension and variables
    ncfile.createDimension('TIME', len(time))

    TIME = ncfile.createVariable('TIME', "d", 'TIME')
    TIMESERIES = ncfile.createVariable('TIMESERIES', "i")
    LATITUDE = ncfile.createVariable(
        'LATITUDE', "d", fill_value=99999.)
    LONGITUDE = ncfile.createVariable(
        'LONGITUDE', "d", fill_value=99999.)
    WHTH = ncfile.createVariable('WHTH', "f", 'TIME', fill_value=99999.)
    WMSH = ncfile.createVariable('WMSH', "f", 'TIME', fill_value=99999.)
    HRMS = ncfile.createVariable('HRMS', "f", 'TIME', fill_value=99999.)
    WHTE = ncfile.createVariable('WHTE', "f", 'TIME', fill_value=99999.)
    WMXH = ncfile.createVariable('WMXH', "f", 'TIME', fill_value=99999.)
    TCREST = ncfile.createVariable('TCREST', "f", 'TIME', fill_value=99999.)
    WPMH = ncfile.createVariable('WPMH', "f", 'TIME', fill_value=99999.)
    WPTH = ncfile.createVariable('WPTH', "f", 'TIME', fill_value=99999.)
    YRMS = ncfile.createVariable('YRMS', "f", 'TIME', fill_value=99999.)
    WPPE = ncfile.createVariable('WPPE', "f", 'TIME', fill_value=99999.)
    TP2 = ncfile.createVariable('TP2', "f", 'TIME', fill_value=99999.)
    M0 = ncfile.createVariable('M0', "f", 'TIME', fill_value=99999.)
    WPDI = ncfile.createVariable('WPDI', "f", 'TIME', fill_value=99999.)

    # add global attributes and variable attributes stored in config files
    config_file = os.path.join(os.getcwd(),'mhl_wave_library', 'global_att_wave.att')
    generate_netcdf_att(ncfile, config_file,
                        conf_file_point_of_truth=True)

    for nc_var in [WPTH, WPPE, WPMH, WPDI, WMXH,WMSH, WHTH, WHTE, TP2, TCREST]:
        nc_var.valid_max = np.float32(nc_var.valid_max)
        nc_var.valid_min = np.float32(nc_var.valid_min)

    # replace nans with fillvalue in dataframe
#.........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 keywords [as 别名]
fid.summary = ["An improved, enhanced-resolution, gridded passive microwave Earth System Data Record \n",
               "for monitoring cryospheric and hydrologic time series\n" ]fid.title = "MEaSUREs Calibrated Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature ESDR"
fid.institution = ["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 = ["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"

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import keywords [as 别名]
def initialize_output(filename, id_dim_name, time_len,
                      id_len, time_step_seconds):
    """Creates netCDF file with CF dimensions and variables, but no data.

    Arguments:
        filename -- full path and filename for output netCDF file
        id_dim_name -- name of Id dimension and variable, e.g., COMID
        time_len -- (integer) length of time dimension (number of time steps)
        id_len -- (integer) length of Id dimension (number of time series)
        time_step_seconds -- (integer) number of seconds per time step
    """

    cf_nc = Dataset(filename, 'w', format='NETCDF3_CLASSIC')

    # Create global attributes
    log('    globals', 'DEBUG')
    cf_nc.featureType = 'timeSeries'
    cf_nc.Metadata_Conventions = 'Unidata Dataset Discovery v1.0'
    cf_nc.Conventions = 'CF-1.6'
    cf_nc.cdm_data_type = 'Station'
    cf_nc.nodc_template_version = (
        'NODC_NetCDF_TimeSeries_Orthogonal_Template_v1.1')
    cf_nc.standard_name_vocabulary = ('NetCDF Climate and Forecast (CF) ' +
                                      'Metadata Convention Standard Name ' +
                                      'Table v28')
    cf_nc.title = 'RAPID Result'
    cf_nc.summary = ("Results of RAPID river routing simulation. Each river " +
                     "reach (i.e., feature) is represented by a point " +
                     "feature at its midpoint, and is identified by the " +
                     "reach's unique NHDPlus COMID identifier.")
    cf_nc.time_coverage_resolution = 'point'
    cf_nc.geospatial_lat_min = 0.0
    cf_nc.geospatial_lat_max = 0.0
    cf_nc.geospatial_lat_units = 'degrees_north'
    cf_nc.geospatial_lat_resolution = 'midpoint of stream feature'
    cf_nc.geospatial_lon_min = 0.0
    cf_nc.geospatial_lon_max = 0.0
    cf_nc.geospatial_lon_units = 'degrees_east'
    cf_nc.geospatial_lon_resolution = 'midpoint of stream feature'
    cf_nc.geospatial_vertical_min = 0.0
    cf_nc.geospatial_vertical_max = 0.0
    cf_nc.geospatial_vertical_units = 'm'
    cf_nc.geospatial_vertical_resolution = 'midpoint of stream feature'
    cf_nc.geospatial_vertical_positive = 'up'
    cf_nc.project = 'National Flood Interoperability Experiment'
    cf_nc.processing_level = 'Raw simulation result'
    cf_nc.keywords_vocabulary = ('NASA/Global Change Master Directory ' +
                                 '(GCMD) Earth Science Keywords. Version ' +
                                 '8.0.0.0.0')
    cf_nc.keywords = 'DISCHARGE/FLOW'
    cf_nc.comment = 'Result time step (seconds): ' + str(time_step_seconds)

    timestamp = datetime.utcnow().isoformat() + 'Z'
    cf_nc.date_created = timestamp
    cf_nc.history = (timestamp + '; added time, lat, lon, z, crs variables; ' +
                     'added metadata to conform to NODC_NetCDF_TimeSeries_' +
                     'Orthogonal_Template_v1.1')

    # Create dimensions
    log('    dimming', 'DEBUG')
    cf_nc.createDimension('time', time_len)
    cf_nc.createDimension(id_dim_name, id_len)

    # Create variables
    log('    timeSeries_var', 'DEBUG')
    timeSeries_var = cf_nc.createVariable(id_dim_name, 'i4', (id_dim_name,))
    timeSeries_var.long_name = (
        'Unique NHDPlus COMID identifier for each river reach feature')
    timeSeries_var.cf_role = 'timeseries_id'

    log('    time_var', 'DEBUG')
    time_var = cf_nc.createVariable('time', 'i4', ('time',))
    time_var.long_name = 'time'
    time_var.standard_name = 'time'
    time_var.units = 'seconds since 1970-01-01 00:00:00 0:00'
    time_var.axis = 'T'

    log('    lat_var', 'DEBUG')
    lat_var = cf_nc.createVariable('lat', 'f8', (id_dim_name,),
                                   fill_value=-9999.0)
    lat_var.long_name = 'latitude'
    lat_var.standard_name = 'latitude'
    lat_var.units = 'degrees_north'
    lat_var.axis = 'Y'

    log('    lon_var', 'DEBUG')
    lon_var = cf_nc.createVariable('lon', 'f8', (id_dim_name,),
                                   fill_value=-9999.0)
    lon_var.long_name = 'longitude'
    lon_var.standard_name = 'longitude'
    lon_var.units = 'degrees_east'
    lon_var.axis = 'X'

    log('    z_var', 'DEBUG')
    z_var = cf_nc.createVariable('z', 'f8', (id_dim_name,),
                                 fill_value=-9999.0)
    z_var.long_name = ('Elevation referenced to the North American ' +
                       'Vertical Datum of 1988 (NAVD88)')
    z_var.standard_name = 'surface_altitude'
    z_var.units = 'm'
#.........这里部分代码省略.........