Python Dataset.platform_code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 platform_code [as 别名]
def makenetcdf_(datasetname, lines):
  filedate = getlinedate_(lines[0])
  ncbytes = None


  platform_code = getplatformcode_(datasetname)
  filenameroot = "GL_TS_TS_" + getplatformcallsign_(platform_code) + "_" + filedate

  # Open a new netCDF file
  ncpath = tempfile.gettempdir() + "/" + filenameroot + ".nc"
  nc = Dataset(ncpath, format="NETCDF4_CLASSIC", mode="w")

  # The DEPTH dimension is singular. Assume 5m for ships
  depthdim = nc.createDimension("DEPTH", 1)

  # Time, lat and lon dimensions are created per record
  timedim = nc.createDimension("TIME", None)
  timevar = nc.createVariable("TIME", "d", ("TIME"), fill_value = 999999.0)
  timevar.long_name = "Time"
  timevar.standard_name = "time"
  timevar.units = "days since 1950-01-01T00:00:00Z"
  timevar.valid_min = -90000;
  timevar.valid_max = 90000;
  timevar.axis = "T"

  latdim = nc.createDimension("LATITUDE", len(lines))
  latvar = nc.createVariable("LATITUDE", "f", ("LATITUDE"),
    fill_value = 99999.0)

  latvar.long_name = "Latitude of each location"
  latvar.standard_name = "latitude"
  latvar.units = "degree_north"
  latvar.valid_min = -90
  latvar.valid_max = 90
  latvar.axis = "Y"
  latvar.reference = "WGS84"
  latvar.coordinate_reference_frame = "urn:ogc:crs:EPSG::4326"

  londim = nc.createDimension("LONGITUDE", len(lines))
  lonvar = nc.createVariable("LONGITUDE", "f", ("LONGITUDE"),
    fill_value = 99999.0)

  lonvar.long_name = "Longitude of each location"
  lonvar.standard_name = "longitude"
  lonvar.units = "degree_east"
  lonvar.valid_min = -180
  lonvar.valid_max = 180
  lonvar.axis = "X"
  lonvar.reference = "WGS84"
  lonvar.coordinate_reference_frame = "urn:ogc:crs:EPSG::4326"

  positiondim = nc.createDimension("POSITION", len(lines))

  # Record position bounds
  minlon = 180
  maxlon = -180
  minlat = 90
  maxlat = -90

  # Fill in dimension variables
  print(len(lines))
  times = [0] * len(lines)
  lats = [0] * len(lines)
  lons = [0] * len(lines)
  for i in range(0, len(lines)):
    fields = str.split(lines[i], ",")
    times[i] = maketimefield_(fields[0])
    if i == 0:
      starttime = maketimeobject_(fields[0])
    
    if i == len(lines) - 1:
      endtime = maketimeobject_(fields[0])

    lats[i] = float(fields[2])
    if lats[i] < minlat:
      minlat = lats[i]

    if lats[i] > maxlat:
      maxlat = lats[i]

    lons[i] = float(fields[1])
    if lons[i] < minlon:
      minlon = lons[i]

    if lons[i] > maxlon:
      maxlon = lons[i]

  timevar[:] = times
  latvar[:] = lats
  lonvar[:] = lons

  # QC flags for dimension variables. Assume all are good
  timeqcvar = nc.createVariable("TIME_QC", "b", ("TIME"), \
   fill_value = QC_FILL_VALUE)
  assignqcvarattributes_(timeqcvar)
  timeqcvar[:] = 1

  positionqcvar = nc.createVariable("POSITION_QC", "b", ("POSITION"), \
   fill_value = QC_FILL_VALUE)
  assignqcvarattributes_(positionqcvar)
#.........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 platform_code [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 platform_code [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 platform_code [as 别名]
def modify_anmn_nrs_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(tupple) : information from xml for the channel
    """
    modify_aims_netcdf(netcdf_file_path, channel_id_info)

    netcdf_file_obj                 = Dataset(netcdf_file_path, 'a', format='NETCDF4')
    netcdf_file_obj.aims_channel_id =  int(channel_id_info['channel_id'])

    if 'Yongala' in channel_id_info['site_name']:
        netcdf_file_obj.site_code     = 'NRSYON'
        netcdf_file_obj.platform_code = 'Yongala NRS Buoy'
    elif 'Darwin' in channel_id_info['site_name']:
        netcdf_file_obj.site_code     = 'NRSDAR'
        netcdf_file_obj.platform_code = 'Darwin NRS Buoy'
    elif 'Beagle' in channel_id_info['site_name']:
        netcdf_file_obj.site_code     = 'DARBGF'
        netcdf_file_obj.platform_code = 'Beagle Gulf Mooring'
    else:
        return False

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

    # some weather stations channels don't have a depth variable if sensor above water
    if 'depth' in netcdf_file_obj.variables.keys():
        var                 = netcdf_file_obj.variables['depth']
        var.long_name       = 'nominal depth'
        var.positive        = 'down'
        var.axis            = 'Z'
        var.reference_datum = 'sea surface'
        var.valid_min       = -10.0
        var.valid_max       = 30.0
        var.units           = 'm'  # some channels put degrees celcius instead ...
        netcdf_file_obj.renameVariable('depth', 'NOMINAL_DEPTH')

    if 'DEPTH' in netcdf_file_obj.variables.keys():
        var                 = netcdf_file_obj.variables['DEPTH']
        var.coordinates     = "TIME LATITUDE LONGITUDE NOMINAL_DEPTH"
        var.long_name       = 'actual depth'
        var.reference_datum = 'sea surface'
        var.positive        = 'down'
        var.valid_min       = -10.0
        var.valid_max       = 30.0
        var.units           = 'm'  # some channels put degrees celcius instead ...

    netcdf_file_obj.close()
    netcdf_file_obj = Dataset(netcdf_file_path, 'a', format='NETCDF4')  # need to close to save to file. as we call get_main_var just after
    main_var        = get_main_anmn_nrs_var(netcdf_file_path)
    # DEPTH, LATITUDE and LONGITUDE are not dimensions, so we make them into auxiliary cooordinate variables by adding this attribute
    if 'NOMINAL_DEPTH' in netcdf_file_obj.variables.keys():
        netcdf_file_obj.variables[main_var].coordinates = "TIME LATITUDE LONGITUDE NOMINAL_DEPTH"
    else:
        netcdf_file_obj.variables[main_var].coordinates = "TIME LATITUDE LONGITUDE"

    netcdf_file_obj.close()

    if not convert_time_cf_to_imos(netcdf_file_path):
        return False

    remove_dimension_from_netcdf(netcdf_file_path)  # last modification to do in this order!
    return True

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

# Copy the glider file to another directory
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')