PseudoNetCDF

https://pseudonetcdf.readthedocs.io/en/latest/
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PseudoNetCDF is a Python package providing NetCDF-like access and metadata-aware spatial and...
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### Install via Pip

Source: https://pseudonetcdf.readthedocs.io/en/latest/installing.html

Use pip to install PseudoNetCDF directly from the GitHub repository.

```bash
pip install http://github.com/barronh/pseudonetcdf.git
```

--------------------------------

### Initialize arltrajdump

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/noaafiles/_tdump.html

Example usage for initializing the arltrajdump parser.

```python
if __name__ == '__main__':
    f = arltrajdump('tdump_008')
```

--------------------------------

### Implement custom help action for file formats

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/pncparse.html

This class handles the --help-format command-line argument by inspecting the reader's constructor and printing usage examples.

```python
def __call__(self, parser, namespace, values, option_string=None):
        file_format = values[0].split(',')[0]
        print('')
        print('All formats require a "path". Some formats also ')
        print('take extra arguments. All arguments other than ')
        print('the input path must be specified using keyword')
        print('arguments.')
        print('')
        helpformat = allreaders[file_format]
        try:
            import inspect
            print('Example:')
            idef = inspect.getargspec(helpformat.__init__)
            args = idef.args[2:]
            if idef.defaults is None:
                defs = ['<VAL>'] * len(args)
            else:
                defs = (len(args) - len(idef.defaults)) * \
                    ['<VAL>'] + list(idef.defaults)
            longform = (
                'pncdump -f ' +
                ','.join([file_format] +
                         [karg + "=%s" % kdef
                          for karg, kdef in zip(args, defs)]) + ' path')
            shortform = (
                'pncdump -f ' +
                ','.join([file_format] +
                         [karg + "=%s" % kdef
                          for karg, kdef in zip(args, defs)
                          if kdef == '<VAL>']) +
                ' path')
            print(shortform)
            if longform != shortform:
                print('')
                print('Extended example with keywords:')
                print(longform)
                print('')
                print('* Any keyword with a non "<VAL>" default ' +
                      'can be omitted.')
            print('')
        except Exception:
            print('** Short help not available for ' + file_format)
            print('')

        if 'y' == input('Hit Y/y to see detailed help\n').lower():
            help(helpformat)
        setattr(namespace, self.dest, values)
        setattr(namespace, 'help', True)
```

--------------------------------

### Install via Conda

Source: https://pseudonetcdf.readthedocs.io/en/latest/installing.html

Use the conda package manager to install PseudoNetCDF.

```bash
conda install pseudonetcdf
```

--------------------------------

### PNC Function Usage Examples

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/pncparse.html

Examples demonstrating how to use the PNC function for single file, multiple file, and action-based processing.

```python
    # Single File
    out = PNC('--format=netcdf', inpath)
    infile = out.ifiles[0]
    O3 = infile.variables['O3']

    # Multiple Files
    out = PNC('--format=netcdf', inpath1, inpath2)
    infile1, infile2 = out.ifiles
    O3_1 = infile1.variables['O3']
    O3_2 = infile2.variables['O3']

    # With Actions
    out = PNC('dump', '--variables=O3', '--format=netcdf', inpath)
```

--------------------------------

### Initialize WOUDC Sonde

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/woudcfiles/_woudc.html

Example instantiation of a WOUDC sonde object from a CSV file.

```python
if __name__ == "__main__":
    f = woudcsonde('20150813.ECC.1Z.1Z27925.JMA.csv')
```

--------------------------------

### Initialize PseudoNetCDF Interface

Source: https://pseudonetcdf.readthedocs.io/en/latest/modules.html

Examples for initializing the PNC interface for single files, multiple files, or performing specific actions.

```python
# Single File
out = PNC(‘–format=netcdf’, inpath)
infile = out.ifiles[0]
O3 = infile.variables[‘O3’]
```

```python
# Multiple Files
out = PNC(‘–format=netcdf’, inpath1, inpath2)
infile1, infile2 = out.ifiles
O3_1 = infile1.variables[‘O3’]
O3_2 = infile2.variables[‘O3’]
```

```python
# With Actions
out = PNC(‘dump’, ‘–variables=O3’, ‘–format=netcdf’, inpath)
```

--------------------------------

### Execute PseudoNetCDF Actions

Source: https://pseudonetcdf.readthedocs.io/en/latest/modules.html

Example of using the PNC command-line interface to dump specific variables from a file.

```python
out = PNC(‘dump’, ‘–variables=O3’, ‘–format=netcdf’, inpath)
```

--------------------------------

### Manage file destinations and variable options

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_files.html

Methods for getting and setting file destination paths and variable creation options.

```python
def get_dest(self):
    """
    Returns the path where a new file is created on some action

    If None, a file is created in memory.
    Else, a netcdf file is created on disk.
    """
    return self.__dict__.get('_destination', None)

def set_dest(self, path, **options):
    """
    Sets the path where a new file is created on some action

    Arguments
    ---------
    path : path for new file
    options : options for new file creation

    Returns
    -------
    None
    """
    options['filename'] = path
    self.__dict__['_destination'] = options

def get_varopt(self):
    """
    Get options

    Arguments
    ---------
    None

    Returns
    -------
    options : dictionary of optiosn
    """
    return self.__dict__.get('_varopt', {}).copy()

def set_varopt(self, **options):
    """
    Set options to be used when creating any Variable

    Arguments
    ---------
    options : options for new Variable creation

    Returns
    -------
    None
    """
    self.__dict__['_varopt'] = options
```

--------------------------------

### Manage Variable Options

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_files.html

Methods to get or set options used when creating new variables in a destination file.

```python
    def get_varopt(self):
        """
        Get options

        Arguments
        ---------
        None

        Returns
        -------
        options : dictionary of options
        """
        return getattr(self, '_varopt', {}).copy()
```

```python
    def set_varopt(self, **options):
        """
        Set options to be used when creating any Variable

        Arguments
        ---------
        **options : options for createVariable
            optional keywords to be supplied when creating new variables in
            destination file

        Returns
        -------
        None
        """
        return object.__setattr__(self, '_varopt', options)
```

--------------------------------

### Define Argument Parser Options

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/pncparse.html

Example of adding custom arguments to a PseudoNetCDF parser using the padd function.

```python
padd('--no-squeeze', dest='squeeze', default=True,
     action='store_false',
     help=('Squeeze automatically removes singleton dimensions; ' +
           'disabling requires user to remove singleton dimensions ' +
           'with --remove-singleton option'))

padd("--figroot", help='Path for base of figure (suffixed by action)')
```

--------------------------------

### Create a Test File

Source: https://pseudonetcdf.readthedocs.io/en/latest/examples/oddsandends.html

Generates a basic IOAPI-like file with a dummy variable and grid metadata for testing purposes.

```python
import PseudoNetCDF as pnc

# create a GRIDDESC
with open('GRIDDESC', 'w') as gf:
    gf.write(
       "' '\n'LamCon_40N_97W'\n 2 33.000 45.000 -97.000 -97.000 40.000\n" +
       "' '\n'12US1'\n'LamCon_40N_97W' " +
       "-2556000.0 -1728000.0 12000.0 12000.0 459 299 1\n' '"
    )

# Create a Template
gf = pnc.pncopen('GRIDDESC', format='griddesc')
gf.SDATE = 2016001
gf.updatetflag(overwrite=True)
delattr(gf, 'VAR-LIST')
gf.updatemeta()
gf.save('test.nc').close()
```

--------------------------------

### arlpackedbit.__init__

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/noaafiles/_arl.html

Initializes the arlpackedbit reader and unpacks the contents of the specified ARL file.

```APIDOC
## __init__(path, shape=None, cache=False, earth_radius=6370000, synchlon=None, synchlat=None)

### Description
Reads and parses an ARL packed bit file, creating a PseudoNetCDF object with the unpacked data.

### Parameters
- **path** (string) - Required - Path to the ARL packed bit formatted file.
- **shape** (tuple or None) - Optional - Override the derived shape of the file.
- **cache** (bool) - Optional - Whether to enable caching.
- **earth_radius** (scalar) - Optional - Radius of the earth used in converting projected coordinates to lat/lon.
- **synchlon** (scalar) - Optional - Override for the SYNCHLON variable precision.
- **synchlat** (scalar) - Optional - Override for the SYNCHLAT variable precision.

### Returns
- **arlf** (arlpackedbit) - A PseudoNetCDF file object containing the unpacked data.
```

--------------------------------

### slice_dim

Source: https://pseudonetcdf.readthedocs.io/en/latest/modules.html

Subsets variable dimensions based on start, stop, and stride parameters.

```APIDOC
## slice_dim(f, slicedef, fuzzydim=True)

### Description
Subsets variables by slicing specific dimensions.

### Parameters
- **f** (file) - The input file object.
- **slicedef** (string) - Definition string in the format 'dim,start,stop,stride'.
- **fuzzydim** (boolean) - Whether to use fuzzy dimension matching.
```

--------------------------------

### Create File Instances

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_files.html

Class methods to initialize new file objects from existing variables or files.

```python
    @classmethod
    def from_ncvs(cls, *invars, **invarkw):
        """
        Arguments
        ---------
        invars : list
            NetCDF-like variable must have standard_name, long_name or name

        invarkw : kwds
            NetCDF-like variables

        Returns
        -------
        outf : PseudoNetcdf-like file
        """
        outf = cls()
        for invar in invars:
            for dk, ds in zip(invar.dimensions, invar.shape):
                if dk in outf.dimensions:
                    assert(ds == len(outf.dimensions[dk]))
                else:
                    outf.createDimension(dk, ds)
            outf.copyVariable(invar)

        for inkey, invar in invarkw.items():
            for dk, ds in zip(invar.dimensions, invar.shape):
                if dk in outf.dimensions:
                    assert(ds == len(outf.dimensions[dk]))
                else:
                    outf.createDimension(dk, ds)
            outf.copyVariable(invar, key=inkey)

        return outf
```

```python
    @classmethod
    def from_ncf(cls, infile):
        """
        Arguments
        ---------
        infile : PseudoNetCDF-like file

        Returns
        -------
        outf : PseudoNetcdf-like file
        """
        outf = cls()
        for pk in infile.ncattrs():
            pv = getattr(infile, pk)
            setattr(outf, pk, pv)

        for dk, dv in infile.dimensions.items():
            outf.copyDimension(dv, key=dk)

        for vk, vv in infile.variables.items():
            outf.copyVariable(vv, key=vk)

        return outf
```

--------------------------------

### Initialize IOAPI Metavariables and Variables

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/camxfiles/uamiv/Memmap.html

Sets up IOAPI-compliant metadata and creates time-flag variables for CAMx files.

```python
# Add IOAPI metavariables
        self.NLAYS = len(self.dimensions['LAY'])
        self.NROWS = len(self.dimensions['ROW'])
        self.NCOLS = len(self.dimensions['COL'])
        self.NVARS = len(self.dimensions['VAR'])
        self.NSTEPS = len(self.dimensions['TSTEP'])
        varlist = "".join([i.ljust(16) for i in self.__var_names__])
        setattr(self, 'VAR-LIST', varlist)
        self.NAME = self.__emiss_hdr['name'][0, :, 0].copy().view('S10')[
            0].decode()
        self.NOTE = self.__emiss_hdr['note'][0, :, 0].copy().view('S60')[
            0].decode()
        self.ITZON = self.__emiss_hdr['itzon'][0]
        self.FTYPE = 1
        self.VGTYP = 2
        self.VGTOP = 10000.
        self.VGLVLS = linspace(0, 1, self.NLAYS + 1)[::-1]
        self.GDNAM = "CAMx            "
        self.UPNAM = "CAMx            "
        self.FILEDESC = "CAMx            "
        # Create variables
        self.variables = PseudoNetCDFVariables(
            self.__variables, ['TFLAG', 'ETFLAG'] + self.__var_names__)
        tflag = ConvertCAMxTime(self.__memmap__['DATE']['BDATE'],
                                self.__memmap__['DATE']['BTIME'],
                                self.NVARS)
        etflag = ConvertCAMxTime(self.__memmap__['DATE']['EDATE'],
                                 self.__memmap__['DATE']['ETIME'],
                                 self.NVARS)
        tflagv = self.createVariable('TFLAG', 'i',
                                     ('TSTEP', 'VAR', 'DATE-TIME'),
                                     values=tflag, units='DATE-TIME',
                                     long_name='TFLAG'.ljust(16),
                                     var_desc='TFLAG'.ljust(80))
        etflagv = self.createVariable('ETFLAG', 'i',
                                      ('TSTEP', 'VAR', 'DATE-TIME'),
                                      values=etflag, units='DATE-TIME',
                                      long_name='ETFLAG'.ljust(16),
                                      var_desc='Ending TFLAG'.ljust(80))

        self.SDATE, self.STIME = self.variables['TFLAG'][0, 0, :]
        self.TSTEP = etflagv[0, 0, 1] - tflagv[0, 0, 1]
        if P_ALP is not None:
            self.P_ALP = P_ALP
        if P_BET is not None:
            self.P_BET = P_BET
        if P_GAM is not None:
            self.P_GAM = P_GAM
        if XCENT is not None:
            self.XCENT = XCENT
        if YCENT is not None:
            self.YCENT = YCENT
        if GDTYP is not None:
            self.GDTYP = GDTYP
```

--------------------------------

### Iterate Time Records

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/noaafiles/_cdump.html

Loops through the file to extract start and stop time records.

```python
start = np.fromfile(infile, dtype=thdr, count=1)
starts.append(start['f1'][0])
stop = np.fromfile(infile, dtype=thdr, count=1)
stops.append(stop['f1'][0])
```

--------------------------------

### Initialize Parser with getparser2

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/pncparse.html

Creates a parent parser for PseudoNetCDF with optional action commands.

```python
def getparser2(actions=False):
    rdesc = RawDescriptionHelpFormatter
    parent_parser = PNCArgumentParser(description="PseudoNetCDF",
                                      formatter_class=rdesc,
                                      add_help=False,
                                      prog='PNC')
    if actions:
        add_action_commands(
            parent_parser, withbasic=True, add_help=False)
    else:
        add_basic_options(parent_parser)
    return parent_parser
```

--------------------------------

### Get Variables from PseudoNetCDF

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_functions.html

Extracts a subset of variables from a file object, optionally filtering by coordinate keys.

```python
def getvarpnc(f, varkeys, coordkeys=None, copy=True):
    if coordkeys is None:
        coordkeys = f.getCoords()

    coordkeys = set(coordkeys)
    if varkeys is None:
        varkeys = list(f.variables.keys())
        varkeys = [k for k in varkeys if k not in coordkeys]
    else:
        newvarkeys = list(set(varkeys).intersection(f.variables.keys()))
        newvarkeys = [varkey for varkey in varkeys if varkey in newvarkeys]
        oldvarkeys = list(set(varkeys))
        oldvarkeys.sort()
        skipping = set(oldvarkeys).difference(newvarkeys)
        if len(skipping):
            warn('Skipping %s' % ', '.join(skipping))
        varkeys = newvarkeys

    if hasattr(f, 'copy'):
        outf = f.copy(props=True, dimensions=False,
                      variables=False, data=False)
    else:
        from PseudoNetCDF.sci_var import WrapPNC
        outf = WrapPNC(f).copy(props=True, dimensions=False,
                               variables=False, data=False)
```

--------------------------------

### Initialize and inspect uamiv file

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/camxfiles/uamiv/Memmap.html

Demonstrates how to open a CAMx uamiv file and inspect its variables, dimensions, and data structure.

```python
>>> uamiv_path = 'camx_uamiv.bin'
>>> uamivfile = uamiv(uamiv_path)
>>> uamivfile.variables.keys()
['TFLAG', 'O3', 'NO', 'NO2', ...]
>>> tflag = uamivfile.variables['TFLAG']
>>> tflag.dimensions
('TSTEP', 'VAR', 'DATE-TIME')
>>> tflag[0,0,:]
array([2005185,       0])
>>> tflag[-1,0,:]
array([2005185,  240000])
>>> v = uamivfile.variables['O3']
>>> v.dimensions
('TSTEP', 'LAY', 'ROW', 'COL')
>>> v.shape
(25, 28, 65, 83)
>>> uamivfile.dimensions
{'TSTEP': 25, 'LAY': 28, 'ROW': 65, 'COL': 83}
```

--------------------------------

### Variable Attribute Management Methods

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_variables.html

Methods for getting, setting, and deleting NetCDF-style attributes on variable objects.

```python
    def __delattr__(self, k):
        if k in self._ncattrs:
            self._ncattrs = tuple([k_ for k_ in self._ncattrs if k_ != k])
        object.__delattr__(self, k)

    def setncattr(self, k, v):
        return setattr(self, k, v)

    def getncattr(self, k):
        return getattr(self, k)

    def setncatts(self, attdict):
        for pk, pv in attdict.items():
            setattr(self, pk, pv)

    def getncatts(self):
        outd = OrderedDict()
        for pk in self.ncattrs():
            outd[pk] = getattr(self, pk)
        return outd


[docs]    def ncattrs(self):
        """
        Returns
        -------
        ncattrs : tuple of strings
            attributes that have been user defined
        """

        return self._ncattrs
```

--------------------------------

### Access Documentation

Source: https://pseudonetcdf.readthedocs.io/en/latest/quick.html

Use the built-in help function to inspect PseudoNetCDF objects.

```python
help(pnc.pncopen)
```

--------------------------------

### Initialize PseudoNetCDFFile from existing file

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_files.html

Class method to create a new PseudoNetCDFFile instance by copying attributes, dimensions, and variables from an existing file.

```python
@classmethod
def from_ncf(cls, infile):
    outf = PseudoNetCDFFile()
    for pk in infile.ncattrs():
        pv = getattr(infile, pk)
        setattr(outf, pk, pv)

    for dk, dv in infile.dimensions.items():
        outf.copyDimension(dv, key=dk)

    for vk, vv in infile.variables.items():
        outf.copyVariable(vv, key=vk)

    return outf
```

--------------------------------

### Object Initialization

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_files.html

Handles the creation and initialization of PseudoNetCDFFile instances.

```python
    def __new__(mcl, *args, **kwds):
        new = super(PseudoNetCDFFile, mcl).__new__(mcl)
        new.variables = OrderedDict()
        new.dimensions = PseudoNetCDFDimensions()
        new._ncattrs = ()
        new._operator_exclude_vars = ()
        return new

    def __init__(self, *args, **properties):
        mode = properties.pop('mode', 'w')
        self._mode = mode
        for k, v in properties.items():
            setattr(self, k, v)
```

--------------------------------

### Get Vertical Level Text Representations

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/noaafiles/_arl.html

Converts a list of vertical level floats into formatted 6-character strings.

```python
def getvgtxts(vglvls):
    vgtxts = []
    for vglvl in vglvls:
        if vglvl == 0:
            dp = 0
        else:
            dp = np.floor(np.log10(vglvl) + 1)
        tmpl = '%%6.%df' % np.minimum(5, (5 - dp))
        vgtxt = (tmpl % vglvl)[-6:]
        if len(vgtxt) != 6:
            raise ValueError('Unable to format vglvl:' + str(vglvl))
        vgtxts.append(vgtxt)
    return vgtxts
```

--------------------------------

### Execute Test Suite

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/geoschemfiles/_bpchmaster.html

Standard entry point for running the unit test suite.

```python
    def runTest(self):
        pass


if __name__ == '__main__':
    unittest.main()
```

--------------------------------

### Load trajectory data with pandas

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/noaafiles/_tdump.html

Reads trajectory data from a file using pandas, requiring the pandas library to be installed.

```python
try:
    import pandas as pd
except Exception:
    raise ImportError('arltrajdump requires pandas; ' +
                      'install pandas (e.g., pip install pandas)')
# , parse_dates = ['YEAR MONTH DAY HOUR MINUTE'.split()])
data = pd.read_csv(f, delimiter='\s+',
                   names=(('trajid metgridid year month day hour ' +
                           'minute forecast_hour age latitude ' +
                           'longitude altitude').split() +
                          diagnostics[1:]))
```

--------------------------------

### Initialize and verify cdump file

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/noaafiles/_cdump.html

Demonstrates how to check if a file is a valid cdump format and initialize the reader.

```python
if __name__ == '__main__':
    print(arlconcdump.isMine('cdump24'))
    f = arlconcdump('cdump24')
```

--------------------------------

### pncmfopen(*args, stackdim=None, **kwds)

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/_getreader.html

Opens multiple files and stacks them along a specified dimension.

```APIDOC
## pncmfopen(*args, stackdim=None, **kwds)

### Description
Opens a list of files using pncopen and stacks them into a single PseudoNetCDF object along the provided dimension.

### Parameters
- **args** (tuple) - args[0] must be a list of file paths.
- **stackdim** (str) - The dimension name upon which to stack the files.
- **kwds** (dict) - Additional arguments passed to pncopen.

### Returns
- **pfile** (PseudoNetCDF) - The stacked file object.
```

--------------------------------

### Get and Set File Destination

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_files.html

Methods to retrieve or define the destination path for new file creation. If the destination is None, files are created in memory.

```python
    def get_dest(self):
        """
        Returns
        -------
        path : str
            path where a new file is created on some action

        Notes
        -----
        If None, a file is created in memory.
        Else, a netcdf file is created on disk.
        """
        return getattr(self, '_destination', None)
```

```python
    def set_dest(self, path, **options):
        """
        Sets the path where a new file is created on some action

        Arguments
        ---------
        path : str
            path for new file
        **options : keywords for constructor
            options for new file creation

        Returns
        -------
        None
        """
        options['filename'] = path
        return object.__setattr__(self, '_destination', options)
```

--------------------------------

### Get File Path

Source: https://pseudonetcdf.readthedocs.io/en/latest/readers/cmaq.html

Retrieves the file system path or OPeNDAP URL used to open the dataset. Requires netCDF4 version 4.1.2 or higher.

```python
filepath(self,encoding=None)
```

--------------------------------

### Initialize CAMx UAMIV Grid and Data Mapping

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/camxfiles/uamiv/Memmap.html

Extracts grid metadata, sets up memory-mapped file structures, and calculates time-step dimensions for UAMIV files.

```python
        self.XORIG = self.__grid_hdr['xorg'][0]
        self.YORIG = self.__grid_hdr['yorg'][0]
        self.XCELL = self.__grid_hdr['delx'][0]
        self.YCELL = self.__grid_hdr['dely'][0]
        self.PLON = plon = self.__grid_hdr['plon'][0]
        self.PLAT = plat = self.__grid_hdr['plat'][0]
        self.TLAT1 = tlat1 = self.__grid_hdr['tlat1'][0]
        self.TLAT2 = tlat2 = self.__grid_hdr['tlat2'][0]
        self.IUTM = iutm = self.__grid_hdr['iutm'][0]
        self.ISTAG = self.__grid_hdr['istag'][0]
        self.CPROJ = cproj = self.__grid_hdr['iproj'][0]
        if hasattr(self, 'GDTYP'):
            GDTYPE = self.GDTYP
        else:
            GDTYPE = self.GDTYP = {0: 1, 1: 5, 2: 2, 3: 6}[cproj]
        if (
            cproj == 0 or
            not all([x == 0 for x in [plon, plat, tlat1, tlat2, iutm, cproj]])
        ):
            # Map CAMx projection constants to IOAPI
            self.XCENT = plon
            self.YCENT = plat
            if GDTYPE in (1, 2):
                self.P_ALP = tlat1
                self.P_BET = tlat2
                self.P_GAM = plon
            elif GDTYPE == 5:
                self.P_ALP = iutm
                self.P_BET = 0.
                self.P_GAM = 0.
            elif GDTYPE == 6:
                self.P_ALP = {90: 1, -90: -1}[plat]
                self.P_BET = tlat1
                self.P_GAM = plon
            else:
                raise ValueError('Unknown projection')

        nx = self.__grid_hdr['nx'][0]
        ny = self.__grid_hdr['ny'][0]
        nz = max(self.__grid_hdr['nz'], array([1]))[0]

        offset += self.__grid_hdr.dtype.itemsize * self.__grid_hdr.size
        self.__cell_hdr = memmap(
            self.__rffile, mode=self.__mode, dtype=self.__cell_hdr_fmt,
            shape=1, offset=offset)

        offset += self.__cell_hdr.dtype.itemsize * self.__cell_hdr.size + 4
        self.__spc_hdr = memmap(self.__rffile, mode=self.__mode,
                                dtype=self.__spc_fmt, shape=nspec,
                                offset=offset)

        offset += self.__spc_hdr.dtype.itemsize * self.__spc_hdr.size + 4

        date_time_fmt = dtype(dict(
            names=['SPAD', 'BDATE', 'BTIME', 'EDATE', 'ETIME', 'EPAD'],
            formats=['i', 'i', 'f', 'i', 'f', 'i'])).newbyteorder(ep)
        date_time_block_size = 6
        spc_1_lay_fmt = dtype(dict(
            names=['SPAD', 'IONE', 'SPC', 'DATA', 'EPAD'],
            formats=['i', 'i', '(10,4)S1',
                     '(%d,%d)f' % (ny, nx), 'i'])).newbyteorder(ep)
        spc_1_lay_block_size = 13 + nx * ny
        spc_3d_fmt = dtype((spc_1_lay_fmt, (nz,)))

        # Get species names from spc_hdr
        var_names = [spc[:, 0].copy().view('S10')[0] for spc in self.__spc_hdr]
        var_names = [v.decode() if hasattr(v, 'decode')
                     else v for v in var_names]
        self.__var_names__ = [''.join(v).strip() for v in var_names]

        data_block_fmt = dtype(dict(
            names=['DATE'] + self.__var_names__,
            formats=[date_time_fmt] + [spc_3d_fmt] * nspec))

        data_block_size = (date_time_block_size + nspec * nz *
                           spc_1_lay_block_size)
        f = open(self.__rffile)
        f.seek(0, 2)
        size = f.tell()
        f.close()
        del f
        ntimes = float(size - offset) / 4. / data_block_size
        if int(ntimes) != ntimes:
            raise ValueError(
                ("Partial time output (%f times); partial time indicates " +
                 "incomplete file.") % ntimes)
        ntimes = int(ntimes)

        self.createDimension('LAY', nz)
        self.createDimension('COL', nx)
        self.createDimension('ROW', ny)
        tstep = self.createDimension('TSTEP', ntimes)
        tstep.setunlimited(True)
        self.createDimension('VAR', nspec)

        self.__memmap__ = memmap(self.__rffile, mode=self.__mode,
                                 dtype=data_block_fmt, offset=offset)
```

--------------------------------

### Define basic command-line options

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/pncparse.html

Configures standard arguments for PseudoNetCDF command-line tools, including file formats, verbosity, and processing flags.

```python
def add_basic_options(parser):
    padd = parser.add_argument
    parser.add_argument('ifiles', nargs='*',
                        help='path to a file formatted as type -f')
    parser.add_argument("--verbose", dest="verbose", action="count",
                        default=0, help="Provides verbosity with pncgen")

    try:
        padd("--help",
             dest="help", action=_HelpAction, default=False,
             help="Displays help")
    except Exception:
        pass

    padd('--pnc', action='append', default=[],
         help='Set of pseudonetcdf commands to be process separately')

    padd("-f", "--format", dest="format", default='netcdf',
         metavar='{see --list-formats for choices}',
         help=("File format (default netcdf), can be one of the choices " +
               "listed, or an expression that evaluates to a reader. " +
               "Keyword arguments are passed via ,kwd=value."))

    padd("--list-formats", dest="help", default=None,
         action=_HelpListFormats, help="Show format options for -f")

    padd("--help-format", dest='helpformat',
         action=_HelpFormat, default=None,
         help="Show help for file format (must be one of the options for -f)")

    padd("--sep", dest="separator", action='store_true',
         default=False,
         help=("Used to separate groups of arguments for parsing (e.g., " +
               "pncgen -- [options1] file(s)1 [--sep [options2] file(s)2 " +
               "[... [--sep [optionsN] file(s)N]] "))

    padd("--inherit", dest="inherit", action="store_true",
         default=False,
         help=("Allow subparsed sections (separated with -- and --sep) to " +
               "inherit from global options (-f, --format is always " +
               "inherited)."))

    padd("--diskless", dest="diskless", action="store_true",
         default=False,
         help="Load file into memory; useful for subsequent processing")

    padd("--mangle", dest="mangle", action="store_true",
         default=False, help="Remove non-standard ascii from names")

    padd("--rename", dest="rename", action="append", default=[],
         help=("Provide pairs of strings to be substituted " +
               "--rename=type,oldkey,newkey (type: v = variable; d = " +
               "dimension;)"))

    padd("--remove-singleton", dest="removesingleton",
         type=lambda x: [k for k in x.split(',') if k != ''], default=[],
         help="Remove singleton (length 1) dimensions")

    padd("--coordkeys", dest="coordkeys", type=str,
         action=AggCommaString, default=_coordkeys, metavar="key1,key2",
         help="Variables to be ignored in pncbo.")
```

--------------------------------

### Configure Parser with getparser

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/pncparse.html

Constructs a full PseudoNetCDF argument parser with options for output, plotting, mapping, and interactivity.

```python
def getparser(has_ofile, plot_options=False, map_options=False,
              interactive=False, actions=False):
    """getparser produces a parser for PseudoNetCDF

Parameters
----------
has_ofile : boolean
            Requires the outpath option and processes existence check
plot_options : boolean, optional
               Adds options for plotting including matplotlibrc, spatial
               overlays, and normalization options, default is False
interactive : boolean, optional
              Adds for interactive option, default is False

Returns
-------
parser : ArgumentParser with options that are processable with pncparse

    """
    parser = PNCArgumentParser(description="""PseudoNetCDF Argument Parsing


""", formatter_class=RawDescriptionHelpFormatter)
    parser.epilog = _pncepilog
    add_basic_options(parser)
    if interactive:
        add_interactive_options(parser)

    if actions:
        add_action_commands(parser, add_help=False)
    else:
        # Only has output file if pncgen is called.
        if has_ofile:
            add_output_options(parser)
        else:
            add_dump_options(parser)

        if plot_options:
            add_plot_options(parser)
        if map_options:
            add_map_options(parser)

    return parser
```

--------------------------------

### Import PseudoNetCDF

Source: https://pseudonetcdf.readthedocs.io/en/latest/quick.html

Import the library using the standard alias.

```python
import PseudoNetCDF as pnc
```

--------------------------------

### Extracting Boundary Conditions with PseudoNetCDF

Source: https://pseudonetcdf.readthedocs.io/en/latest/examples/cmaqbcon.html

Creates a grid description file and extracts perimeter data from an existing IOAPI file to generate a boundary condition file.

```python
import PseudoNetCDF as pnc

# create a GRIDDESC
with open('GRIDDESC', 'w') as gf:
    gf.write(
       "' '\n'LamCon_40N_97W'\n 2 33.000 45.000 -97.000 -97.000 40.000\n" +
       "' '\n'12US1'\n'LamCon_40N_97W' " +
       "-2556000.0 -1728000.0 12000.0 12000.0 459 299 1\n' '"
    )

# Create a Template
gf = pnc.pncopen('GRIDDESC', format='griddesc', FTYPE=2)
concf = pnc.pncopen('CONC.nc', format='ioapi')
i, j = concf.ll2ij(
    gf.variables['longitude'][:],
    gf.variables['latitude'][:]
)
bconf = concf.sliceDimensions(COL=i, ROW=j, newdims=('PERIM',))
bconf.FTYPE = 2
bconf.save('bcon.nc', format='NETCDF3_CLASSIC')
```

--------------------------------

### Stack Files

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_functions.html

Initializes a file structure for stacking multiple files along a new dimension.

```python
def stack_files(fs, stackdim, coordkeys=None):
    """
    Create files with dimensions extended by stacking.

    Currently, there is no sanity check...

    """
    f = PseudoNetCDFFile()
    tmpf = fs[0]
    if coordkeys is None:
        coordkeys = tmpf.getCoords()
```

--------------------------------

### Prepare Files for Processing

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/pncparse.html

Prepares file lists by applying operators and expressions before processing.

```python
def pncprep(args):
    # nifiles = len(args.ifiles) - has_ofile
    ipaths = args.ifiles[:]
    fs = getfiles(ipaths, args)
    fs = subsetfiles(fs, args)
    fs = seqpncbo(args.operators, fs, coordkeys=args.coordkeys)
    for expr in args.expressions:
        fs = [pncexpr(expr, f) for f in fs]
    for script in args.expressionscripts:
        expr = open(script).read()
        fs = [pncexpr(expr, f) for f in fs]
    args.ifiles = fs
    if getattr(args, 'cdlname', None) is None:
        try:
            args.cdlname = args.ipath[0]
        except Exception:
            args.cdlname = 'unknown'
    return fs, args
```

--------------------------------

### Create New File Instance

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_files.html

Internal method to instantiate a new file object of the same class or type.

```python
    def _newlike(self):
        """
        Internal function to return a file of the same class if a
        PseudoNetCDFFile
        """
        if self.get_dest() is not None:
            outf = netcdf(**self.get_dest())
        elif isinstance(self, PseudoNetCDFFile):
            outt = type(self)
            outf = outt.__new__(outt)
        else:
            outf = PseudoNetCDFFile()
        outf.set_varopt(**self.get_varopt())
        return outf
```

--------------------------------

### IOAPI Default Metadata Configuration

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/cmaqfiles/_ioapi.html

Initializes default IOAPI metadata attributes using an OrderedDict.

```python
from PseudoNetCDF.pncwarn import warn
from ..core._files import PseudoNetCDFFile, netcdf
from collections import OrderedDict
from PseudoNetCDF._getwriter import registerwriter

import numpy as np
import datetime
today = datetime.datetime.today()
# Assuming some fo the most common
# options
_i = _ioapi_defaults = OrderedDict()
_i['IOAPI_VERSION'] = "N/A".ljust(80)
_i['EXEC_ID'] = "????????????????".ljust(80)
_i['FTYPE'] = 1
_i['CDATE'] = int(today.strftime('%Y%j'))
_i['CTIME'] = int(today.strftime('%H%M%S'))
_i['WDATE'] = int(today.strftime('%Y%j'))
_i['WTIME'] = int(today.strftime('%H%M%S'))
_i['NTHIK'] = 1
_i['GDTYP'] = 1
_i['P_ALP'] = 33.
_i['P_BET'] = 45.
_i['P_GAM'] = -97.
_i['XCENT'] = -97.
_i['YCENT'] = 40.
_i['VGTYP'] = 2
_i['VGTOP'] = np.float32(5000)
_i['GDNAM'] = "UNKNOWN         "
_i['UPNAM'] = "MAKEIOAPI       "
_i['FILEDESC'] = "".ljust(80)
_i['HISTORY'] = ""
```

--------------------------------

### Multi-file Dataset Opening

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/core/_files.html

Opens multiple files and stacks them along a specified dimension.

```python
    @classmethod
    def open_mfdataset(cls, *paths, stackdim=None, **kwds):
        files = [cls(p, **kwds) for p in paths]
        file1 = files[0]
        if stackdim is None:
            for dk, dv in file1.dimensions.items():
                if dv.isunlimited():
                    stackdim = dk
            else:
                for dk in list(file1.dimensions):
                    if dk in ('TSTEP', 'time', 'Time', 't'):
                        stackdim = dk
                else:
                    raise ValueError(
                        'No dimension is unlimited or time; ' +
                        'must specify stackdim'
                    )
        return file1.stack(files[1:], stackdim=stackdim)
```

--------------------------------

### Initialize Data Record Parsing

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/noaafiles/_cdump.html

Sets up the data structures and formats required to iterate through time-series records in the CDUMP file.

```python
thdr = np.dtype('>i,>6i,>i')
nopackdfmt = '>({},{})f'.format(nlats, nlons)
nopackfmt = np.dtype(
    dict(
        names=['B', 'POL', 'LAY', 'data', 'E'],
        formats=['>i', '>S4', '>i', nopackdfmt, '>i']
    )
)
```

--------------------------------

### Initialize data block iteration

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/geoschemfiles/_bpch.html

Prepares the file pointer and memory mapping to iterate through data blocks in the BPCH file.

```python
if (
    len(tracer_names) == 0 and
    not isinstance(tracer_names, defaultdictfromkey)
):
    raise IOError("Error parsing %s for Tracer data" % tracerinfo)
file_size = os.stat(bpch_path).st_size
offset = _general_header_type.itemsize
data_types = []
first_header = None
keys = []
self._groups = OrderedDefaultDict(set)
while first_header is None or \
        offset < file_size:
    header = memmap(bpch_path, offset=offset, shape=(
        1,), dtype=_datablock_header_type, mode=mode)[0]
```

--------------------------------

### HelpAction and HelpListFormats Actions

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/pncparse.html

Custom argparse Actions for displaying help information and listing available file formats supported by the library.

```python
class _HelpAction(Action):
    def __init__(self,
                 option_strings,
                 dest=SUPPRESS,
                 default=SUPPRESS,
                 help=None):
        super(_HelpAction, self).__init__(
            option_strings=option_strings,
            dest=dest,
            default=default,
            nargs=0,
            help=help)

    def __call__(self, parser, namespace, values, option_string=None):
        parser.print_help()
        setattr(namespace, self.dest, True)


class _HelpListFormats(Action):
    def __init__(self,
                 option_strings,
                 dest=SUPPRESS,
                 default=SUPPRESS,
                 help=None):
        super(_HelpListFormats, self).__init__(
            option_strings=option_strings,
            dest=dest,
            default=default,
            nargs=0,
            help=help)

    def __call__(self, parser, namespace, values, option_string=None):
        print('The formats listed below are available ' +
              'for the following options')
        print('-f FORMAT or --format FORMAT or --help-format FORMAT')
        print('where FORMAT is one of the options below')
        print('\t' + '\n\t'.join(_readernames))
        print('**Some readers are listed twice (e.g., without dotted form)')
        setattr(namespace, 'help', True)
```

--------------------------------

### pncopen(*args, **kwds)

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/_getreader.html

Opens a file using a supported PseudoNetCDF format, with support for auto-detection and CF convention wrapping.

```APIDOC
## pncopen(*args, **kwds)

### Description
Opens any PseudoNetCDF supported format. It handles format auto-detection, optional CF convention addition, and diskless file handling.

### Parameters
- **args** (tuple) - Arguments for opening the file.
- **kwds** (dict) - Keywords for the reader.
- **format** (string) - Optional name of the reader; defaults to auto-detect.
- **addcf** (boolean) - Whether to add CF conventions; default is False.
- **diskless** (boolean) - Whether to use diskless mode; default is False.
- **help** (boolean) - If True, returns help information for the reader.

### Returns
- **pfile** (PseudoNetCDF) - The opened file object.
```

--------------------------------

### Initialize ARL Grid and Coordinate Variables

Source: https://pseudonetcdf.readthedocs.io/en/latest/_modules/PseudoNetCDF/noaafiles/_arl.html

Configures grid dimensions and coordinate variables based on ARL header properties. Handles both projected and geographic coordinate systems.

```python
        if synchlat is None:
            self._synchlat = float(self.SYNCHLAT)
        else:
            self._synchlat = synchlat

        gridx = float(t0hdr['GRIDX']) * 1000.
        nx = props['NX']
        ny = props['NY']
        if gridx != 0:
            self.XSIZE = self.YSIZE = gridx
            self.createDimension('x', nx)
            self.createDimension('y', ny)
            x = self.createVariable('x', 'f', ('x',))
            x[:] = np.arange(x[:].size) * gridx
            y = self.createVariable('y', 'f', ('y',))
            y[:] = np.arange(y[:].size) * gridx
            self._addcrs()
        else:
            self.createDimension('x', nx)
            self.createDimension('y', ny)
            self.createDimension('nv', 2)
            x = self.createVariable('x', 'f', ('x',))
            x.standard_name = 'longitude'
            x.units = 'degrees'
            xe = self.createVariable('x_bounds', 'f', ('x', 'nv'))
            xe.standard_name = 'longitude_bounds'
            xe.units = 'degrees'
            x[:] = np.arange(0, nx) * float(self.REFLON) + self._synchlon
            xe[:-1, 1] = x[:1] + np.diff(x) / 2
            xe[1:, 0] = x[1:] - np.diff(x) / 2
            xe[0, 0] = x[0] - np.diff(x)[0] / 2
            xe[1, 1] = x[1] + np.diff(x)[1] / 2
            y = self.createVariable('y', 'f', ('y',))
            y.standard_name = 'latitude'
            y.units = 'degrees'
            ye = self.createVariable('y_bounds', 'f', ('y', 'nv'))
            ye.standard_name = 'latitude_bounds'
            ye.units = 'degrees'
            y[:] = np.arange(0, ny) * float(self.REFLAT) + self._synchlat
            ye[:-1, 1] = y[:1] + np.diff(y) / 2
            ye[1:, 0] = y[1:] - np.diff(y) / 2
            ye[0, 0] = y[0] - np.diff(y)[0] / 2
            ye[1, 1] = y[1] + np.diff(y)[1] / 2
```
Tokens:
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