Python Dataset.version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 version [as 别名]
def create_netcdf(
    a_netcdf_filename, a_lat_points, a_lon_points, a_nb_levels, a_celerity_arr, a_u_arr, a_v_arr, a_time, a_loc_names
):
    """
    dimensions:
      altitude = 401;
      profile  = 1 ;

    variables:
       float altitude(altitude) ;
         altitude:long_name = "height above mean sea level" ;
         altitude:units = "km" ;
         altitude:positive = "up" ; 

       double time(profile);
         time:long_name = "time" ;
         time:units = "days since 1970-01-01 00:00:00" ;
    
       string loc_name(profile) ;
        loc_name:units = "-" ;
        loc_name:long_name = "Location name" ;

       float lon(profile);
         lon:long_name = "longitude" ;
         lon:units = "degrees_east" ;

       float lat(profile);
         lat:long_name = "latitude" ;
         lat:units = "degrees_north" ;

       float celerity(profile, altitude) ;
         celerity:long_name = "celerity" ;
         celerity:units = "m s**-1" ;
         celerity:coordinates = "time lon lat altitude" ;

       float u(profile, altitude) ;
         u:long_name = "U velocity" ;
         celerity:units = "m s**-1" ;
         celerity:coordinates = "time lon lat altitude" ;

       float v(profile, altitude) ;
         u:long_name = "V velocity" ;
         celerity:units = "m s**-1" ;
         celerity:coordinates = "time lon lat altitude" ;
   
       attributes:
          :CF\:featureType = "profile";
 

    """
    print ("In create_netcdf %s" % (a_netcdf_filename))

    conf = Conf.get_instance()

    netcdf_format = conf.get("NETCDF", "produced_format", "NETCDF3_CLASSIC")

    # create file
    dataset = Dataset(a_netcdf_filename, "w", format=netcdf_format)

    # create dimension
    dataset.createDimension("altitude", a_nb_levels)
    dataset.createDimension("profile", len(a_lat_points))
    loc_name_len = dataset.createDimension("loc_name_len", 5)

    # create basic variables
    the_time = dataset.createVariable("time", "f8", ("profile"))
    lat = dataset.createVariable("latitude", "f4", ("profile"))
    lon = dataset.createVariable("longitude", "f4", ("profile"))
    altitudes = dataset.createVariable("altitude", "f4", ("altitude"))

    # create loc_name
    # In netcdf4 it would be
    # loc_names  = dataset.createVariable('loc_name', str,('profile'))
    if netcdf_format == "NETCDF3_CLASSIC":
        loc_names = dataset.createVariable("loc_name", "c", ("profile", "loc_name_len"))
    else:
        loc_names = dataset.createVariable("loc_name", str, ("profile"))

    # create param variables
    # u and v wind components
    u = dataset.createVariable("u", "f4", ("profile", "altitude"))
    v = dataset.createVariable("v", "f4", ("profile", "altitude"))
    # celerity
    c = dataset.createVariable("c", "f4", ("profile", "altitude"))

    # dataset.sync()

    # add attributes
    dataset.description = "CTBTO Infrasound wind profiles"
    dataset.history = "Created " + time.ctime(time.time()) + " by infra-profile-generator-v1.2.2"
    dataset.source = "infra-profile-generator-v1.2.2"
    dataset.version = "infrasound profile v1.0-20090801"
    # dataset.station     = 'IS42'
    lat.units = "degrees north"
    lat.long_name = "Latitude"
    lon.units = "degrees east"
    lon.long_name = "Longitude"
    altitudes.units = "m"
    altitudes.long_name = "Altitude"
    loc_names.units = "-"
#.........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 version [as 别名]
def create_netcdf(a_netcdf_filename, a_lat_points, a_lon_points, a_nb_levels, a_celerity_arr, a_u_arr, a_v_arr, a_time, a_loc_names):
    """
    dimensions:
      altitude = 401;
      profile  = 1 ;

    variables:
       float altitude(altitude) ;
         altitude:long_name = "height above mean sea level" ;
         altitude:units = "km" ;
         altitude:positive = "up" ; 

       double time(profile);
         time:long_name = "time" ;
         time:units = "days since 1970-01-01 00:00:00" ;
    
       string loc_name(profile) ;
        loc_name:units = "-" ;
        loc_name:long_name = "Location name" ;

       float lon(profile);
         lon:long_name = "longitude" ;
         lon:units = "degrees_east" ;

       float lat(profile);
         lat:long_name = "latitude" ;
         lat:units = "degrees_north" ;

       float celerity(profile, altitude) ;
         celerity:long_name = "celerity" ;
         celerity:units = "m s**-1" ;
         celerity:coordinates = "time lon lat altitude" ;

       float u(profile, altitude) ;
         u:long_name = "U velocity" ;
         u:units = "m s**-1" ;
         u:coordinates = "time lon lat altitude" ;

       float v(profile, altitude) ;
         u:long_name = "V velocity" ;
         v:units = "m s**-1" ;
         v:coordinates = "time lon lat altitude" ;
   
       attributes:
          :CF\:featureType = "profile";
 

    """
    print("In create_netcdf %s" %(a_netcdf_filename))
    
    conf = Conf.get_instance()
    
    netcdf_format  = conf.get('NETCDF', 'produced_format', 'NETCDF3_CLASSIC')
    
    #create file
    dataset = Dataset(a_netcdf_filename, 'w', format=netcdf_format)
    
    #create dimension
    dataset.createDimension('altitude', a_nb_levels)
    dataset.createDimension('profile', len(a_lat_points))
    loc_name_len = dataset.createDimension('loc_name_len', 5)

    #create basic variables
    the_time  = dataset.createVariable('time',      'f8', ('profile'))
    lat       = dataset.createVariable('latitude',  'f4', ('profile'))
    lon       = dataset.createVariable('longitude', 'f4', ('profile'))
    altitudes = dataset.createVariable('altitude',  'f4', ('altitude'))

    # create loc_name
    # In netcdf4 it would be 
    #loc_names  = dataset.createVariable('loc_name', str,('profile'))
    if netcdf_format == 'NETCDF3_CLASSIC':
        loc_names  = dataset.createVariable('loc_name', 'c', ('profile','loc_name_len') )
    else:
        loc_names  = dataset.createVariable('loc_name', str, ('profile') )
 
 
    # create param variables
    # u and v wind components
    u         = dataset.createVariable('u',   'f4', ('profile', 'altitude'))
    v         = dataset.createVariable('v',   'f4', ('profile', 'altitude'))
    # celerity 
    c         = dataset.createVariable('c',    'f4', ('profile','altitude'))

    #dataset.sync()

    # add attributes
    dataset.description = 'CTBTO Infrasound wind profiles'
    dataset.history     = 'Created ' + time.ctime(time.time()) + ' by infra-profile-generator-v1.2.2'
    dataset.source      = 'infra-profile-generator-v1.2.2'
    dataset.version     = 'infrasound profile v1.0-20090801'
    #dataset.station     = 'IS42'
    lat.units           = 'degrees north'
    lat.long_name       = 'Latitude'
    lon.units           = 'degrees east'
    lon.long_name       = 'Longitude'
    altitudes.units     = 'm'
    altitudes.long_name = 'Altitude'
    loc_names.units     = '-'
    loc_names.long_name = 'Location name'
#.........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 version [as 别名]
      usage(sys.argv[0])
    if opt[0]=="-o":
      overwrite=1
    if opt[0]=="-g":
      doget=1
  if overwrite and doget:
    print "Unable overwrite the file while getting it"
    print "Make a better selection of command line options"
    sys.exit(1)

  # If we must overwrite the reference file, we need to
  # create it, first, otherwise, just open it for reading
  refname="reference.cdf"
  if overwrite:
    nc=Dataset(refname,"w")
    nc.version=sys.version
    nc.platform=sys.platform
    if 'byteorder' in dir(sys):
      nc.byteorder=sys.byteorder
    else:
      nc.byteorder="Unknown, Python older than 2.0??"
  else:
    # If there is no local copy of the file, get it from
    # its URL
    if os.access(refname,os.F_OK)==0 or doget:
      thedir="http://starship.python.net/crew/jsaenz/pyclimate/"
      thedir=thedir+"references/"
      theurl=thedir+pyclimate.tools.pyclimateversion()+"/"+refname
      print "There is no local copy of:",refname
      print "Do you want me to get it from"
      print theurl,"?[no]/yes"

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import version [as 别名]
foo.createDimension('time', None)
foo.createDimension('latitude', pcp.shape[1])
foo.createDimension('longitude', pcp.shape[2])

foo.institution = 'Climate Hazards Group.  University of California at Santa Barbara'
foo.creator_name = 'Pete Peterson'
foo.history = 'created by Climate Hazards Group - Modified by Funceme (NetCDF3 - South America)'
foo.title = 'CHIRPS Version 2.0'
foo.creator_email = '[email protected].edu'
foo.documentation = 'http://pubs.usgs.gov/ds/832/'
foo.comments = 'time variable denotes the first day of the given month.'
foo.ftp_url = 'ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/'
foo.website = 'http://chg.geog.ucsb.edu/data/chirps/index.html'
foo.faq = 'http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ'
foo.version = 'Version 2.0'
foo.date_created = '2015-12-02'

lats = foo.createVariable('latitude', 'f4', ('latitude'))
lats.units = 'degrees_north'
lats.long_name = 'latitude'
lats.axis = "Y"
lats[:] = lat[:]

lons = foo.createVariable('longitude', 'f4', ('longitude'))
lons.units = 'degrees_east'
lons.long_name = 'longitude'
lons.axis = "X"
lons[:] = lon[:]

times = foo.createVariable('time', 'f4', ('time'))

# 需要导入模块: from netCDF4 import Dataset [as 别名]
# 或者: from netCDF4.Dataset import version [as 别名]
def write_exodus_file(filename, cells, vertices, shape="SHELL4"):
    """
    Write Exodus-II file compatible with CUBIT.

    cells is a 0-based array (ncells, ncorners).

    vertices is (nvertices, dim).

    All cells are placed in a single block.

    Requires netCDF4 module.
    """
    import numpy
    from netCDF4 import Dataset

    len_string = 33

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

    # Set global attributes
    root.api_version = 4.98
    root.version = 4.98
    root.floating_point_word_size = 8
    root.file_size = 0
    root.title = "cubit"

    # Setup dimensions

    # Generic information
    root.createDimension('len_string', len_string)
    root.createDimension('len_line', 81)
    root.createDimension('four', 4)
    root.createDimension('num_qa_rec', 1)
    root.createDimension('time_step', None)

    # Mesh specific information
    (ncells, ncorners) = cells.shape
    (nvertices, dim) = vertices.shape
    root.createDimension('num_dim', dim)
    root.createDimension('num_el_blk', 1)
    root.createDimension('num_nod_per_el1', ncorners)
    root.createDimension('num_att_in_blk1', 1)

    root.createDimension('num_nodes', nvertices)
    root.createDimension('num_elem', ncells)
    root.createDimension('num_el_in_blk1', ncells)

    # Setup variables
    connect1 = root.createVariable('connect1', numpy.int32,
                                   ('num_el_in_blk1', 'num_nod_per_el1',))

    coord = root.createVariable('coord', numpy.float64,
                                ('num_dim', 'num_nodes',))
    
    time_whole = root.createVariable('time_whole', numpy.float64,
                                     ('time_step',))
    
    coor_names = root.createVariable('coor_names', 'S1',
                                     ('num_dim', 'len_string',))
    
    qa_records = root.createVariable('qa_records', 'S1',
                                     ('num_qa_rec', 'four', 'len_string',))
    
    eb_names = root.createVariable('eb_names', 'S1',
                                   ('num_el_blk', 'len_string',))

    elem_map = root.createVariable('elem_map', numpy.int32,
                                   ('num_elem',))

    eb_status = root.createVariable('eb_status', numpy.int32,
                                    ('num_el_blk',))

    eb_prop1 = root.createVariable('eb_prop1', numpy.int32,
                                   ('num_el_blk',))

    attrib1 = root.createVariable('attrib1', numpy.float64,
                                  ('num_el_in_blk1', 'num_att_in_blk1',))

    # Set variable values
    connect1[:] = 1+cells[:]
    connect1.elem_type = shape

    coord[:] = vertices.transpose()[:]

    from netCDF4 import stringtoarr
    if dim == 2:
        coor_names[0,:] = stringtoarr("x", len_string)
        coor_names[1,:] = stringtoarr("y", len_string)
    elif dim == 3:
        coor_names[0,:] = stringtoarr("x", len_string)
        coor_names[1,:] = stringtoarr("y", len_string)
        coor_names[2,:] = stringtoarr("z", len_string)


    qa_records[0,0,:] = stringtoarr("CUBIT", len_string)
    qa_records[0,1,:] = stringtoarr("11.0", len_string)
    qa_records[0,2,:] = stringtoarr("01/01/2000", len_string)
    qa_records[0,3,:] = stringtoarr("12:00:00", len_string)

    elem_map[:] = numpy.arange(1, ncells+1, dtype=numpy.int32)[:]
#.........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 version [as 别名]
def ConvertNCCF(TheFileIn,TheFileOut,TheTimes,TheDaysArray,TheCLats,TheCLongs,TheClimPeriod,TheMissing,TheType):
    ''' Discover what is in the file '''
    ''' Open and read in all bits '''
    ''' Write out in cf compliant style '''

    ncf=Dataset(TheFileIn,'r')
    nc_dims = list(ncf.dimensions)	# list of dimensions [dim for dim in ncf.dimensions]
    nc_vars = list(ncf.variables)  # list of nc variables [var for var in ncf.variables]
    nc_attrs = ncf.ncattrs()		# list of global attributes

    ndims=len(nc_dims)
    nvars=len(nc_vars)
    ngatts=len(nc_attrs)

# Get all global attributes
    TheGAtts=np.empty(ngatts,dtype=object)	# an empty array with the right number of string elements
    for (noo,att) in enumerate(nc_attrs):	# enumerate and use elements of the list
        TheGAtts[noo]=ncf.getncattr(att)	# get each global attribute and populate array

# Get all dimensions
    TheDims=np.empty(ndims)	# an empty array with the right number of string elements
    for (noo,dim) in enumerate(nc_dims):	# enumerate and use elements of the list
        TheDims[noo]=len(ncf.dimensions[dim])	# get length of each dimension
# NO DIMENSION ATTRIBUTES - 
#    TheDimAttrNames=[[] for i in xrange(ndims)]		# create list of lists - one for the attribute names of each dimension
#    TheDimAttrs=[[] for i in xrange(ndims)]		# create list of lists - one for the attributes of each dimension
#    for (noo,dim) in enumerate(nc_dims):	# enumerate and use elements of the list
#        TheDimAttrNames[noo]=ncf.dimensions[dim].ncattrs()	# fill names
#        for (nee,nats) in enumerate(TheDimAttrNames[noo]):      # loop through each name and get the attribute   
#            TheDimAttrs[noo][nee]=f.dimensions[dim].getncattr(nats)	

# Get all variables, and their attributes
    TheVarAttrNames=[[] for i in xrange(nvars)]		# create list of lists - one for the attribute names of each dimension
    TheVarAttrs=[[] for i in xrange(nvars)]		# create list of lists - one for the attributes of each dimension
    TheVars=[[] for i in xrange(nvars)]		# create list of lists - one for the attributes of each dimension
    for (noo,var) in enumerate(nc_vars):	# enumerate and use elements of the list
        TheVarAttrNames[noo]=ncf.variables[var].ncattrs()	# fill names
        for (nee,nats) in enumerate(TheVarAttrNames[noo]):      # loop through each name and get the attribute   
            TheVarAttrs[noo].append(ncf.variables[var].getncattr(nats))	
        TheVars[noo]=ncf.variables[nc_vars[noo]][:]


# Now write out, checking if the standard stuff is not there, and if not, then add in
    ncfw=Dataset(TheFileOut,'w',format='NETCDF3_CLASSIC')
    
# Set up the global attributes
# Is there a description?
    moo=np.where(np.array(nc_attrs) == 'description')
    if (moo[0] >= 0):
        ncfw.description=TheGAtts[moo[0]]
    else:
        ncfw.description="HadISDH monthly mean land surface "+TheType+" climate monitoring product from 1973 onwards. Quality control, homogenisation, uncertainty estimation, averaging over gridboxes (no smoothing or interpolation)."
# Is there a title?
    moo=np.where(np.array(nc_attrs) == 'title')
    if (moo[0] >= 0):
        ncfw.title=TheGAtts[moo[0]]
    else:
        ncfw.title="HadISDH monthly mean land surface "+TheType+" climate monitoring product from 1973 onwards."
# Is there an institution?
    moo=np.where(np.array(nc_attrs) == 'institution')
    if (moo[0] >= 0):
        ncfw.institution=TheGAtts[moo[0]]
    else:
        ncfw.institution="Met Office Hadley Centre (UK), National Climatic Data Centre (USA), Climatic Research Unit (UK), National Physical Laboratory (UK), Bjerknes Centre for Climate Research (Norway)"
# Is there a history?
    moo=np.where(np.array(nc_attrs) == 'history')
    if (moo[0] >= 0):
        ncfw.history=TheGAtts[moo[0]]
    else:
        ncfw.history="Updated 4 February 2014"
# Is there a source?
    moo=np.where(np.array(nc_attrs) == 'source')
    if (moo[0] >= 0):
        ncfw.source=TheGAtts[moo[0]]
    else:
        ncfw.source="HadISD.1.0.2.2013f (Dunn et al., 2012)"
# Is there a comment?
    moo=np.where(np.array(nc_attrs) == 'comment')
    if (moo[0] >= 0):
        ncfw.comment=TheGAtts[moo[0]]
    else:
        ncfw.comment=""
# Is there a reference?
    moo=np.where(np.array(nc_attrs) == 'reference')
    if (moo[0] >= 0):
        ncfw.reference=TheGAtts[moo[0]]
    else:
        ncfw.reference="Willett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014."
# Is there a version?
    moo=np.where(np.array(nc_attrs) == 'version')
    if (moo[0] >= 0):
        ncfw.version=TheGAtts[moo[0]]
    else:
        ncfw.version="HadISDH.2.0.0.2013p"
# Is there a Conventions?
    moo=np.where(np.array(nc_attrs) == 'Conventions')
    if (moo[0] >= 0):
        ncfw.Conventions=TheGAtts[moo[0]]
    else:
        ncfw.Conventions="CF-1.0"
#.........这里部分代码省略.........