Python Dataset.data_variable_name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 data_variable_name [as 别名]
def setNetCDFDataVariableNameAttribute(netCDF_File, variableName):
    # open the file with read/write mode (r+)
    rootGrp = Dataset(netCDF_File, 'r+', format='NETCDF3_CLASSIC')

    rootGrp.data_variable_name = variableName

    #close the file
    rootGrp.close()

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import data_variable_name [as 别名]
    #open a new blank netcdf file to which we will be writting data
    outRootGrp = Dataset(outNetCDF_File, 'w', format='NETCDF3_CLASSIC')

    if (inRootGrp.start_year != startDate.year):
        raise Exception("Specified simulation start year ({0}) does not match with input vapor pressure data file data year.".format(startDate.year))
        exit()

     # DEBUG: print global attributes of the original file:
##    for gAttribute in inRootGrp.ncattrs():
##        print 'Global attribute name:', gAttribute, '=', getattr(inRootGrp,gAttribute)


    # add global file level attributes to the new netcdf file
    outRootGrp.start_year = inRootGrp.start_year
    outRootGrp.data_variable_name = inRootGrp.data_variable_name
    outRootGrp.data_time_step = inTimeStep
    outRootGrp.orginal_data_source = 'Daymet Software Version 2.0'
    outRootGrp.conventions = 'CF-1.0'
    outRootGrp.modified_data_source = 'CI Water System'
    outRootGrp.spatial_reference = 'NAD83_UTM_Zone_12N'
    outRootGrp.datum = 'D_North_America_1983'

    # get dimension values from the original netcdf file
    inputTimeVar = inRootGrp.variables['time']
    inputXvar = inRootGrp.variables['x']
    inputYvar = inRootGrp.variables['y']
    inputVpVar = inRootGrp.variables[inRootGrp.data_variable_name]

    print(inputTimeVar.shape[0])
    print(inputXvar.shape[0])

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import data_variable_name [as 别名]
    inRootGrp = Dataset(inNetCDF_File, 'r', format='NETCDF3_CLASSIC')

    # open a new blank netcdf file to which we will be writting data
    outRootGrp = Dataset(outNetCDF_File, 'w', format='NETCDF3_CLASSIC')

    if (inRootGrp.start_year != startDate.year):
        raise Exception("Specified simulation start year ({0}) does not match with input precp data file data year.".format(startDate.year))
        exit()

    # DEBUG: print global attributes of the original file:
##    for gAttribute in inRootGrp.ncattrs():
##        print 'Global attribute name:', gAttribute, '=', getattr(inRootGrp,gAttribute)

    # add global file level attributes to the new netcdf file
    outRootGrp.start_year = inRootGrp.start_year
    outRootGrp.data_variable_name = 'Prec'
    outRootGrp.data_time_step = inTimeStep
    outRootGrp.orginal_data_source = 'Daymet Software Version 2.0'
    outRootGrp.conventions = 'CF-1.0'
    outRootGrp.modified_data_source = 'CI Water System'
    outRootGrp.spatial_reference = 'NAD83_UTM_Zone_12N'
    outRootGrp.datum = 'D_North_America_1983'

    # get dimension values from the original netcdf file
    inputTimeVar = inRootGrp.variables['time']
    inputXvar = inRootGrp.variables['x']
    inputYvar = inRootGrp.variables['y']
    inputPrecVar = inRootGrp.variables['Prec']

    print(inputTimeVar.shape[0])
    print(inputXvar.shape[0])

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import data_variable_name [as 别名]
    inputTaYVar = inRootGrpTa.variables['y']
    inputTaTimeVar = inRootGrpTa.variables['time']

    inputVpVar = inRootGrpVp.variables[inRootGrpVp.data_variable_name]
    inputVpTimeVar = inRootGrpVp.variables['time']

    #DEBUG: print netcdf variable diemensions
    print('Dimension of Temp var: ' + str(inputTaVar.shape))
    print('Dimension of Vp var: ' + str(inputVpVar.shape))

    #open a new blank netcdf file to which we will be writting data
    outRootGrp = Dataset(outRH_NetCDFFile, 'w', format='NETCDF3_CLASSIC')

    # add global file level attributes to the new netcdf file
    outRootGrp.start_year = inRootGrpTa.start_year
    outRootGrp.data_variable_name = outNetCDFDataVariableName
    outRootGrp.data_time_step = inRootGrpTa.data_time_step
    outRootGrp.orginal_data_source = 'Daymet Software Version 2.0'
    outRootGrp.conventions = 'CF-1.0'
    outRootGrp.modified_data_source = 'CI Water System'
    outRootGrp.spatial_reference = 'NAD83_UTM_Zone_12N'
    outRootGrp.datum = 'D_North_America_1983'

    # create 3 dimensions for the output netcdf file
    outTimeDimensionSize = inputVpVar.shape[0]
    outYvarDimensionSize = inputVpVar.shape[1]
    outXvarDimensionSize = inputVpVar.shape[2]

    outRootGrp.createDimension('time', outTimeDimensionSize)
    outRootGrp.createDimension('x', outXvarDimensionSize)
    outRootGrp.createDimension('y', outYvarDimensionSize)

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import data_variable_name [as 别名]
    inputTminVar = inRootGrpTmin.variables['tmin']
    inputTmaxVar = inRootGrpTmax.variables['tmax']
    inputXminVar = inRootGrpTmin.variables['x']
    inputYminVar = inRootGrpTmin.variables['y']

    # open a new blank netcdf file to which we will be writting data
    # TODO: date:11/12/2013 change the format for writting to netcdf to
    # NETCDF4_CLASSIC in order to be able to create a nc file size greater
    # than 2 GB
    # Ref: http://www.ncl.ucar.edu/Support/talk_archives/2011/0599.html
    outNetCDF_File = os.path.join(outNetCDFFilePath, outNetCDF_FileName)
    outRootGrp = Dataset(outNetCDF_File, 'w', format='NETCDF3_CLASSIC')

    # add global file level attributes to the new netcdf file
    outRootGrp.start_year = inRootGrpTmin.start_year
    outRootGrp.data_variable_name = outDataVariableName
    outRootGrp.data_time_step = inTimeStep
    outRootGrp.orginal_data_source = 'Daymet Software Version 2.0'
    outRootGrp.conventions = 'CF-1.0'
    outRootGrp.modified_data_source = 'CI Water System'
    outRootGrp.spatial_reference = 'NAD83_UTM_Zone_12N'
    outRootGrp.datum = 'D_North_America_1983'

    print(inputTminVar.shape)

    # Create 3 dimensions for the 3 variables: time, x and y
    dataPointsPerDayNeeded = 24/inTimeStep
    outTimeDimensionSize = inputTminVar.shape[0] * dataPointsPerDayNeeded
    outYvarDimensionSize = inputTminVar.shape[1]
    outXvarDimensionSize = inputTminVar.shape[2]
    outRootGrp.createDimension('time', outTimeDimensionSize)