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<a href="netCDF4-module.html">Module netCDF4</a> ::
Class Dataset
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<!-- ==================== CLASS DESCRIPTION ==================== -->
<h1 class="epydoc">Class Dataset</h1><p class="nomargin-top"></p>
<pre class="base-tree">
object --+
|
<strong class="uidshort">Dataset</strong>
</pre>
<dl><dt>Known Subclasses:</dt>
<dd>
<ul class="subclass-list">
<li><a href="netCDF4.Group-class.html">Group</a></li><li>, <a href="netCDF4.MFDataset-class.html">MFDataset</a></li> </ul>
</dd></dl>
<hr />
<p>Dataset(self, filename, mode="r", clobber=True,
diskless=False, persist=False, format='NETCDF4')</p>
<p>A netCDF <a href="netCDF4.Dataset-class.html" class="link">Dataset</a>
is a collection of dimensions, groups, variables and attributes. Together
they describe the meaning of data and relations among data fields stored
in a netCDF file.</p>
<p><b>Parameters:</b></p>
<p><b><code>filename</code></b> - Name of netCDF file to hold
dataset.</p>
<p><b>Keywords</b>:</p>
<p><b><code>mode</code></b> - access mode. <code>r</code> means
read-only; no data can be modified. <code>w</code> means write; a new
file is created, an existing file with the same name is deleted.
<code>a</code> and <code>r+</code> mean append (in analogy with serial
files); an existing file is opened for reading and writing. Appending
<code>s</code> to modes <code>w</code>, <code>r+</code> or <code>a</code>
will enable unbuffered shared access to <code>NETCDF3_CLASSIC</code> or
<code>NETCDF3_64BIT</code> formatted files. Unbuffered acesss may be
useful even if you don't need shared access, since it may be faster for
programs that don't access data sequentially. This option is ignored for
<code>NETCDF4</code> and <code>NETCDF4_CLASSIC</code> formatted
files.</p>
<p><b><code>clobber</code></b> - if <code>True</code> (default), opening
a file with <code>mode='w'</code> will clobber an existing file with the
same name. if <code>False</code>, an exception will be raised if a file
with the same name already exists.</p>
<p><b><code>format</code></b> - underlying file format (one of
<code>'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_CLASSIC'</code> or
<code>'NETCDF3_64BIT'</code>. Only relevant if <code>mode = 'w'</code>
(if <code>mode = 'r','a'</code> or <code>'r+'</code> the file format is
automatically detected). Default <code>'NETCDF4'</code>, which means the
data is stored in an HDF5 file, using netCDF 4 API features. Setting
<code>format='NETCDF4_CLASSIC'</code> will create an HDF5 file, using
only netCDF 3 compatibile API features. netCDF 3 clients must be
recompiled and linked against the netCDF 4 library to read files in
<code>NETCDF4_CLASSIC</code> format. <code>'NETCDF3_CLASSIC'</code> is
the classic netCDF 3 file format that does not handle 2+ Gb files very
well. <code>'NETCDF3_64BIT'</code> is the 64-bit offset version of the
netCDF 3 file format, which fully supports 2+ GB files, but is only
compatible with clients linked against netCDF version 3.6.0 or later.</p>
<p><code>diskless</code> - create diskless (in memory) file. This is an
experimental feature added to the C library after the netcdf-4.2
release.</p>
<p><code>persist</code> - if diskless=True, persist file to disk when
closed (default False).</p>
<p><b>Returns:</b></p>
<p>a <a href="netCDF4.Dataset-class.html" class="link">Dataset</a>
instance. All further operations on the netCDF Dataset are accomplised
via <a href="netCDF4.Dataset-class.html" class="link">Dataset</a>
instance methods.</p>
<p>A list of attribute names corresponding to global netCDF attributes
defined for the <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> can be obtained with the <a
href="netCDF4.Dataset-class.html#ncattrs" class="link">ncattrs()</a>
method. These attributes can be created by assigning to an attribute of
the <a href="netCDF4.Dataset-class.html" class="link">Dataset</a>
instance. A dictionary containing all the netCDF attribute name/value
pairs is provided by the <code>__dict__</code> attribute of a <a
href="netCDF4.Dataset-class.html" class="link">Dataset</a> instance.</p>
<p>The instance variables <code>dimensions, variables, groups, cmptypes,
file_format</code> and <code>path</code> are read-only (and should not be
modified by the user).</p>
<!-- ==================== INSTANCE METHODS ==================== -->
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<span class="table-header">Instance Methods</span></td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#__delattr__" class="summary-sig-name">__delattr__</a>(<span class="summary-sig-arg">...</span>)</span><br />
x.__delattr__('name') <==> del x.name</td>
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<td><span class="summary-sig"><a name="__enter__"></a><span class="summary-sig-name">__enter__</span>(<span class="summary-sig-arg">...</span>)</span></td>
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<td><span class="summary-sig"><a name="__exit__"></a><span class="summary-sig-name">__exit__</span>(<span class="summary-sig-arg">...</span>)</span></td>
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<td><span class="summary-sig"><a name="__getattr__"></a><span class="summary-sig-name">__getattr__</span>(<span class="summary-sig-arg">...</span>)</span></td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#__getattribute__" class="summary-sig-name">__getattribute__</a>(<span class="summary-sig-arg">...</span>)</span><br />
x.__getattribute__('name') <==> x.name</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#__init__" class="summary-sig-name">__init__</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">filename</span>,
<span class="summary-sig-arg">mode</span>=<span class="summary-sig-default">"r"</span>,
<span class="summary-sig-arg">clobber</span>=<span class="summary-sig-default">True</span>,
<span class="summary-sig-arg">diskless</span>=<span class="summary-sig-default">False</span>,
<span class="summary-sig-arg">persist</span>=<span class="summary-sig-default">False</span>,
<span class="summary-sig-arg">format</span>=<span class="summary-sig-default">'NETCDF4'</span>)</span><br />
x.__init__(...) initializes x; see help(type(x)) for signature</td>
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<span class="summary-type">a new object with type S, a subtype of T</span>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#__new__" class="summary-sig-name">__new__</a>(<span class="summary-sig-arg">T</span>,
<span class="summary-sig-arg">S</span>,
<span class="summary-sig-arg">...</span>)</span></td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#__setattr__" class="summary-sig-name">__setattr__</a>(<span class="summary-sig-arg">...</span>)</span><br />
x.__setattr__('name', value) <==> x.name = value</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#__str__" class="summary-sig-name">__str__</a>(<span class="summary-sig-arg">x</span>)</span><br />
str(x)</td>
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<td><span class="summary-sig"><a name="__unicode__"></a><span class="summary-sig-name">__unicode__</span>(<span class="summary-sig-arg">...</span>)</span></td>
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<td><span class="summary-sig"><a name="close"></a><span class="summary-sig-name">close</span>(<span class="summary-sig-arg">self</span>)</span><br />
Close the Dataset.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#createCompoundType" class="summary-sig-name">createCompoundType</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">datatype</span>,
<span class="summary-sig-arg">datatype_name</span>)</span><br />
Creates a new compound data type named <code>datatype_name</code>
from the numpy dtype object <code>datatype</code>.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#createDimension" class="summary-sig-name">createDimension</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">dimname</span>,
<span class="summary-sig-arg">size</span>=<span class="summary-sig-default">None</span>)</span><br />
Creates a new dimension with the given <code>dimname</code> and
<code>size</code>.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#createGroup" class="summary-sig-name">createGroup</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">groupname</span>)</span><br />
Creates a new <a href="netCDF4.Group-class.html"
class="link">Group</a> with the given <code>groupname</code>.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#createVLType" class="summary-sig-name">createVLType</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">datatype</span>,
<span class="summary-sig-arg">datatype_name</span>)</span><br />
Creates a new VLEN data type named <code>datatype_name</code> from a
numpy dtype object <code>datatype</code>.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#createVariable" class="summary-sig-name">createVariable</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">varname</span>,
<span class="summary-sig-arg">datatype</span>,
<span class="summary-sig-arg">dimensions</span>=<span class="summary-sig-default">()</span>,
<span class="summary-sig-arg">zlib</span>=<span class="summary-sig-default">False</span>,
<span class="summary-sig-arg">complevel</span>=<span class="summary-sig-default">4</span>,
<span class="summary-sig-arg">shuffle</span>=<span class="summary-sig-default">True</span>,
<span class="summary-sig-arg">fletcher32</span>=<span class="summary-sig-default">False</span>,
<span class="summary-sig-arg">contiguous</span>=<span class="summary-sig-default">False</span>,
<span class="summary-sig-arg">chunksizes</span>=<span class="summary-sig-default">None</span>,
<span class="summary-sig-arg">endian</span>=<span class="summary-sig-default">'native'</span>,
<span class="summary-sig-arg">least_significant_digit</span>=<span class="summary-sig-default">None</span>,
<span class="summary-sig-arg">fill_value</span>=<span class="summary-sig-default">None</span>)</span><br />
Creates a new variable with the given <code>varname</code>,
<code>datatype</code>, and <code>dimensions</code>.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#delncattr" class="summary-sig-name">delncattr</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">name</span>,
<span class="summary-sig-arg">value</span>)</span><br />
delete a netCDF dataset or group attribute.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#getncattr" class="summary-sig-name">getncattr</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">name</span>)</span><br />
retrievel a netCDF dataset or group attribute.</td>
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<td><span class="summary-sig"><a name="ncattrs"></a><span class="summary-sig-name">ncattrs</span>(<span class="summary-sig-arg">self</span>)</span><br />
return netCDF global attribute names for this <a
href="netCDF4.Dataset-class.html" class="link">Dataset</a> or <a
href="netCDF4.Group-class.html" class="link">Group</a> in a list.</td>
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<td><span class="summary-sig"><a name="renameDimension"></a><span class="summary-sig-name">renameDimension</span>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">oldname</span>,
<span class="summary-sig-arg">newname</span>)</span><br />
rename a <a href="netCDF4.Dimension-class.html"
class="link">Dimension</a> named <code>oldname</code> to
<code>newname</code>.</td>
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<td><span class="summary-sig"><a name="renameVariable"></a><span class="summary-sig-name">renameVariable</span>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">oldname</span>,
<span class="summary-sig-arg">newname</span>)</span><br />
rename a <a href="netCDF4.Variable-class.html"
class="link">Variable</a> named <code>oldname</code> to
<code>newname</code></td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#set_fill_off" class="summary-sig-name">set_fill_off</a>(<span class="summary-sig-arg">self</span>)</span><br />
Sets the fill mode for a <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> open for writing to <code>off</code>.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#set_fill_on" class="summary-sig-name">set_fill_on</a>(<span class="summary-sig-arg">self</span>)</span><br />
Sets the fill mode for a <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> open for writing to <code>on</code>.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#setncattr" class="summary-sig-name">setncattr</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">name</span>,
<span class="summary-sig-arg">value</span>)</span><br />
set a netCDF dataset or group attribute using name,value pair.</td>
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<td><span class="summary-sig"><a href="netCDF4.Dataset-class.html#setncatts" class="summary-sig-name">setncatts</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">attdict</span>)</span><br />
set a bunch of netCDF dataset or group attributes at once using a
python dictionary.</td>
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<td><span class="summary-sig"><a name="sync"></a><span class="summary-sig-name">sync</span>(<span class="summary-sig-arg">self</span>)</span><br />
Writes all buffered data in the <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> to the disk file.</td>
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<tr>
<td colspan="2" class="summary">
<p class="indent-wrapped-lines"><b>Inherited from <code>object</code></b>:
<code>__format__</code>,
<code>__hash__</code>,
<code>__reduce__</code>,
<code>__reduce_ex__</code>,
<code>__repr__</code>,
<code>__sizeof__</code>,
<code>__subclasshook__</code>
</p>
</td>
</tr>
</table>
<!-- ==================== INSTANCE VARIABLES ==================== -->
<a name="section-InstanceVariables"></a>
<table class="summary" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr bgcolor="#70b0f0" class="table-header">
<td align="left" colspan="2" class="table-header">
<span class="table-header">Instance Variables</span></td>
</tr>
<tr>
<td width="15%" align="right" valign="top" class="summary">
<span class="summary-type"> </span>
</td><td class="summary">
<a name="cmptypes"></a><span class="summary-name">cmptypes</span><br />
The <code>cmptypes</code> dictionary maps the names of compound types
defined for the <a href="netCDF4.Group-class.html"
class="link">Group</a> or <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> to instances of the <a
href="netCDF4.CompoundType-class.html" class="link">CompoundType</a>
class.
</td>
</tr>
<tr>
<td width="15%" align="right" valign="top" class="summary">
<span class="summary-type"> </span>
</td><td class="summary">
<a name="dimensions"></a><span class="summary-name">dimensions</span><br />
The <code>dimensions</code> dictionary maps the names of dimensions
defined for the <a href="netCDF4.Group-class.html"
class="link">Group</a> or <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> to instances of the <a
href="netCDF4.Dimension-class.html" class="link">Dimension</a> class.
</td>
</tr>
<tr>
<td width="15%" align="right" valign="top" class="summary">
<span class="summary-type"> </span>
</td><td class="summary">
<a href="netCDF4.Dataset-class.html#file_format" class="summary-name">file_format</a><br />
The <code>file_format</code> attribute describes the netCDF file
format version, one of <code>NETCDF3_CLASSIC</code>,
<code>NETCDF4</code>, <code>NETCDF4_CLASSIC</code> or
<code>NETCDF3_64BIT</code>.
</td>
</tr>
<tr>
<td width="15%" align="right" valign="top" class="summary">
<span class="summary-type"> </span>
</td><td class="summary">
<a name="groups"></a><span class="summary-name">groups</span><br />
The groups dictionary maps the names of groups created for this <a
href="netCDF4.Dataset-class.html" class="link">Dataset</a> or <a
href="netCDF4.Group-class.html" class="link">Group</a> to instances
of the <a href="netCDF4.Group-class.html" class="link">Group</a>
class (the <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> class is simply a special case of the <a
href="netCDF4.Group-class.html" class="link">Group</a> class which
describes the root group in the netCDF file).
</td>
</tr>
<tr>
<td width="15%" align="right" valign="top" class="summary">
<span class="summary-type"> </span>
</td><td class="summary">
<a href="netCDF4.Dataset-class.html#path" class="summary-name">path</a><br />
The <code>path</code> attribute shows the location of the <a
href="netCDF4.Group-class.html" class="link">Group</a> in the <a
href="netCDF4.Dataset-class.html" class="link">Dataset</a> in a unix
directory format (the names of groups in the hierarchy separated by
backslashes).
</td>
</tr>
<tr>
<td width="15%" align="right" valign="top" class="summary">
<span class="summary-type"> </span>
</td><td class="summary">
<a name="variables"></a><span class="summary-name">variables</span><br />
The <code>variables</code> dictionary maps the names of variables
defined for this <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> or <a href="netCDF4.Group-class.html"
class="link">Group</a> to instances of the <a
href="netCDF4.Variable-class.html" class="link">Variable</a> class.
</td>
</tr>
</table>
<!-- ==================== PROPERTIES ==================== -->
<a name="section-Properties"></a>
<table class="summary" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr bgcolor="#70b0f0" class="table-header">
<td align="left" colspan="2" class="table-header">
<span class="table-header">Properties</span></td>
</tr>
<tr>
<td width="15%" align="right" valign="top" class="summary">
<span class="summary-type"> </span>
</td><td class="summary">
<a name="maskanscale"></a><span class="summary-name">maskanscale</span>
</td>
</tr>
<tr>
<td width="15%" align="right" valign="top" class="summary">
<span class="summary-type"> </span>
</td><td class="summary">
<a name="parent"></a><span class="summary-name">parent</span>
</td>
</tr>
<tr>
<td width="15%" align="right" valign="top" class="summary">
<span class="summary-type"> </span>
</td><td class="summary">
<a name="vltypes"></a><span class="summary-name">vltypes</span>
</td>
</tr>
<tr>
<td colspan="2" class="summary">
<p class="indent-wrapped-lines"><b>Inherited from <code>object</code></b>:
<code>__class__</code>
</p>
</td>
</tr>
</table>
<!-- ==================== METHOD DETAILS ==================== -->
<a name="section-MethodDetails"></a>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr bgcolor="#70b0f0" class="table-header">
<td align="left" colspan="2" class="table-header">
<span class="table-header">Method Details</span></td>
</tr>
</table>
<a name="__delattr__"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">__delattr__</span>(<span class="sig-arg">...</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>x.__delattr__('name') <==> del x.name</p>
<dl class="fields">
<dt>Overrides:
object.__delattr__
</dt>
</dl>
</td></tr></table>
</div>
<a name="__getattribute__"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">__getattribute__</span>(<span class="sig-arg">...</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>x.__getattribute__('name') <==> x.name</p>
<dl class="fields">
<dt>Overrides:
object.__getattribute__
</dt>
</dl>
</td></tr></table>
</div>
<a name="__init__"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">__init__</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">filename</span>,
<span class="sig-arg">mode</span>=<span class="sig-default">"r"</span>,
<span class="sig-arg">clobber</span>=<span class="sig-default">True</span>,
<span class="sig-arg">diskless</span>=<span class="sig-default">False</span>,
<span class="sig-arg">persist</span>=<span class="sig-default">False</span>,
<span class="sig-arg">format</span>=<span class="sig-default">'NETCDF4'</span>)</span>
<br /><em class="fname">(Constructor)</em>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>x.__init__(...) initializes x; see help(type(x)) for signature</p>
<dl class="fields">
<dt>Overrides:
object.__init__
</dt>
</dl>
</td></tr></table>
</div>
<a name="__new__"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">__new__</span>(<span class="sig-arg">T</span>,
<span class="sig-arg">S</span>,
<span class="sig-arg">...</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<dl class="fields">
<dt>Returns: a new object with type S, a subtype of T</dt>
<dt>Overrides:
object.__new__
</dt>
</dl>
</td></tr></table>
</div>
<a name="__setattr__"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">__setattr__</span>(<span class="sig-arg">...</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>x.__setattr__('name', value) <==> x.name = value</p>
<dl class="fields">
<dt>Overrides:
object.__setattr__
</dt>
</dl>
</td></tr></table>
</div>
<a name="__str__"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">__str__</span>(<span class="sig-arg">x</span>)</span>
<br /><em class="fname">(Informal representation operator)</em>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>str(x)</p>
<dl class="fields">
<dt>Overrides:
object.__str__
</dt>
</dl>
</td></tr></table>
</div>
<a name="createCompoundType"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">createCompoundType</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">datatype</span>,
<span class="sig-arg">datatype_name</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>Creates a new compound data type named <code>datatype_name</code> from
the numpy dtype object <code>datatype</code>.</p>
<dl class="fields">
</dl>
<div class="fields"> <p><strong>Attention:</strong>
If the new compound data type contains other compound data types
(i.e. it is a 'nested' compound type, where not all of the elements
are homogenous numeric data types), then the 'inner' compound types
<b>must</b> be created first.
<p>The return value is the <a
href="netCDF4.CompoundType-class.html"
class="link">CompoundType</a> class instance describing the new
datatype.</p>
</p>
</div></td></tr></table>
</div>
<a name="createDimension"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">createDimension</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">dimname</span>,
<span class="sig-arg">size</span>=<span class="sig-default">None</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>Creates a new dimension with the given <code>dimname</code> and
<code>size</code>.</p>
<p><code>size</code> must be a positive integer or <code>None</code>,
which stands for "unlimited" (default is <code>None</code>).
Specifying a size of 0 also results in an unlimited dimension. The return
value is the <a href="netCDF4.Dimension-class.html"
class="link">Dimension</a> class instance describing the new dimension.
To determine the current maximum size of the dimension, use the
<code>len</code> function on the <a href="netCDF4.Dimension-class.html"
class="link">Dimension</a> instance. To determine if a dimension is
'unlimited', use the <code>isunlimited()</code> method of the <a
href="netCDF4.Dimension-class.html" class="link">Dimension</a>
instance.</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="createGroup"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">createGroup</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">groupname</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>Creates a new <a href="netCDF4.Group-class.html"
class="link">Group</a> with the given <code>groupname</code>.</p>
<p>The return value is a <a href="netCDF4.Group-class.html"
class="link">Group</a> class instance describing the new group.</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="createVLType"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">createVLType</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">datatype</span>,
<span class="sig-arg">datatype_name</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>Creates a new VLEN data type named <code>datatype_name</code> from a
numpy dtype object <code>datatype</code>.</p>
<p>The return value is the <a href="netCDF4.VLType-class.html"
class="link">VLType</a> class instance describing the new datatype.</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="createVariable"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">createVariable</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">varname</span>,
<span class="sig-arg">datatype</span>,
<span class="sig-arg">dimensions</span>=<span class="sig-default">()</span>,
<span class="sig-arg">zlib</span>=<span class="sig-default">False</span>,
<span class="sig-arg">complevel</span>=<span class="sig-default">4</span>,
<span class="sig-arg">shuffle</span>=<span class="sig-default">True</span>,
<span class="sig-arg">fletcher32</span>=<span class="sig-default">False</span>,
<span class="sig-arg">contiguous</span>=<span class="sig-default">False</span>,
<span class="sig-arg">chunksizes</span>=<span class="sig-default">None</span>,
<span class="sig-arg">endian</span>=<span class="sig-default">'native'</span>,
<span class="sig-arg">least_significant_digit</span>=<span class="sig-default">None</span>,
<span class="sig-arg">fill_value</span>=<span class="sig-default">None</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>Creates a new variable with the given <code>varname</code>,
<code>datatype</code>, and <code>dimensions</code>. If dimensions are not
given, the variable is assumed to be a scalar.</p>
<p>The <code>datatype</code> can be a numpy datatype object, or a string
that describes a numpy dtype object (like the <code>dtype.str</code>
attribue of a numpy array). Supported specifiers include: <code>'S1' or
'c' (NC_CHAR), 'i1' or 'b' or 'B' (NC_BYTE), 'u1' (NC_UBYTE), 'i2' or 'h'
or 's' (NC_SHORT), 'u2' (NC_USHORT), 'i4' or 'i' or 'l' (NC_INT), 'u4'
(NC_UINT), 'i8' (NC_INT64), 'u8' (NC_UINT64), 'f4' or 'f' (NC_FLOAT),
'f8' or 'd' (NC_DOUBLE)</code>. <code>datatype</code> can also be a <a
href="netCDF4.CompoundType-class.html" class="link">CompoundType</a>
instance (for a structured, or compound array), a <a
href="netCDF4.VLType-class.html" class="link">VLType</a> instance (for a
variable-length array), or the python <code>str</code> builtin (for a
variable-length string array).</p>
<p>Data from netCDF variables is presented to python as numpy arrays with
the corresponding data type.</p>
<p><code>dimensions</code> must be a tuple containing dimension names
(strings) that have been defined previously using
<code>createDimension</code>. The default value is an empty tuple, which
means the variable is a scalar.</p>
<p>If the optional keyword <code>zlib</code> is <code>True</code>, the
data will be compressed in the netCDF file using gzip compression
(default <code>False</code>).</p>
<p>The optional keyword <code>complevel</code> is an integer between 1
and 9 describing the level of compression desired (default 4). Ignored if
<code>zlib=False</code>.</p>
<p>If the optional keyword <code>shuffle</code> is <code>True</code>, the
HDF5 shuffle filter will be applied before compressing the data (default
<code>True</code>). This significantly improves compression. Default is
<code>True</code>. Ignored if <code>zlib=False</code>.</p>
<p>If the optional keyword <code>fletcher32</code> is <code>True</code>,
the Fletcher32 HDF5 checksum algorithm is activated to detect errors.
Default <code>False</code>.</p>
<p>If the optional keyword <code>contiguous</code> is <code>True</code>,
the variable data is stored contiguously on disk. Default
<code>False</code>. Setting to <code>True</code> for a variable with an
unlimited dimension will trigger an error.</p>
<p>The optional keyword <code>chunksizes</code> can be used to manually
specify the HDF5 chunksizes for each dimension of the variable. A
detailed discussion of HDF chunking and I/O performance is available <a
href="http://www.hdfgroup.org/HDF5/doc/H5.user/Chunking.html"
target="_top">here</a>. Basically, you want the chunk size for each
dimension to match as closely as possible the size of the data block that
users will read from the file. <code>chunksizes</code> cannot be set if
<code>contiguous=True</code>.</p>
<p>The optional keyword <code>endian</code> can be used to control
whether the data is stored in little or big endian format on disk.
Possible values are <code>little, big</code> or <code>native</code>
(default). The library will automatically handle endian conversions when
the data is read, but if the data is always going to be read on a
computer with the opposite format as the one used to create the file,
there may be some performance advantage to be gained by setting the
endian-ness.</p>
<p>The <code>zlib, complevel, shuffle, fletcher32, contiguous,
chunksizes</code> and <code>endian</code> keywords are silently ignored
for netCDF 3 files that do not use HDF5.</p>
<p>The optional keyword <code>fill_value</code> can be used to override
the default netCDF <code>_FillValue</code> (the value that the variable
gets filled with before any data is written to it, defaults given in
netCDF4.default_fillvals). If fill_value is set to <code>False</code>,
then the variable is not pre-filled.</p>
<p>If the optional keyword parameter <code>least_significant_digit</code>
is specified, variable data will be truncated (quantized). In conjunction
with <code>zlib=True</code> this produces 'lossy', but significantly more
efficient compression. For example, if
<code>least_significant_digit=1</code>, data will be quantized using
<code>numpy.around(scale*data)/scale</code>, where scale = 2**bits, and
bits is determined so that a precision of 0.1 is retained (in this case
bits=4). From <a
href="http://www.cdc.noaa.gov/cdc/conventions/cdc_netcdf_standard.shtml"
target="_top">http://www.cdc.noaa.gov/cdc/conventions/cdc_netcdf_standard.shtml</a>:
"least_significant_digit -- power of ten of the smallest decimal
place in unpacked data that is a reliable value." Default is
<code>None</code>, or no quantization, or 'lossless' compression.</p>
<p>When creating variables in a <code>NETCDF4</code> or
<code>NETCDF4_CLASSIC</code> formatted file, HDF5 creates something
called a 'chunk cache' for each variable. The default size of the chunk
cache may be large enough to completely fill available memory when
creating thousands of variables. The optional keyword
<code>chunk_cache</code> allows you to reduce (or increase) the size of
the default chunk cache when creating a variable. The setting only
persists as long as the Dataset is open - you can use the
set_var_chunk_cache method to change it the next time the Dataset is
opened. Warning - messing with this parameter can seriously degrade
performance.</p>
<p>The return value is the <a href="netCDF4.Variable-class.html"
class="link">Variable</a> class instance describing the new variable.</p>
<p>A list of names corresponding to netCDF variable attributes can be
obtained with the <a href="netCDF4.Variable-class.html"
class="link">Variable</a> method <code>ncattrs()</code>. A dictionary
containing all the netCDF attribute name/value pairs is provided by the
<code>__dict__</code> attribute of a <a
href="netCDF4.Variable-class.html" class="link">Variable</a>
instance.</p>
<p><a href="netCDF4.Variable-class.html" class="link">Variable</a>
instances behave much like array objects. Data can be assigned to or
retrieved from a variable with indexing and slicing operations on the <a
href="netCDF4.Variable-class.html" class="link">Variable</a> instance. A
<a href="netCDF4.Variable-class.html" class="link">Variable</a> instance
has five Dataset standard attributes: <code>dimensions, dtype, shape,
ndim</code> and <code>least_significant_digit</code>. Application
programs should never modify these attributes. The
<code>dimensions</code> attribute is a tuple containing the names of the
dimensions associated with this variable. The <code>dtype</code>
attribute is a string describing the variable's data type (<code>i4, f8,
S1,</code> etc). The <code>shape</code> attribute is a tuple describing
the current sizes of all the variable's dimensions. The
<code>least_significant_digit</code> attributes describes the power of
ten of the smallest decimal place in the data the contains a reliable
value. assigned to the <a href="netCDF4.Variable-class.html"
class="link">Variable</a> instance. If <code>None</code>, the data is not
truncated. The <code>ndim</code> attribute is the number of variable
dimensions.</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="delncattr"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">delncattr</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">name</span>,
<span class="sig-arg">value</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>delete a netCDF dataset or group attribute. Only use if you need to
delete a netCDF attribute with the same name as one of the reserved
python attributes.</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="getncattr"></a>
<div>
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cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">getncattr</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">name</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>retrievel a netCDF dataset or group attribute. Only use if you need
to set a netCDF attribute with the same name as one of the reserved
python attributes.</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="set_fill_off"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">set_fill_off</span>(<span class="sig-arg">self</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>Sets the fill mode for a <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> open for writing to <code>off</code>.</p>
<p>This will prevent the data from being pre-filled with fill values,
which may result in some performance improvements. However, you must then
make sure the data is actually written before being read.</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="set_fill_on"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">set_fill_on</span>(<span class="sig-arg">self</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>Sets the fill mode for a <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a> open for writing to <code>on</code>.</p>
<p>This causes data to be pre-filled with fill values. The fill values
can be controlled by the variable's <code>_Fill_Value</code> attribute,
but is usually sufficient to the use the netCDF default
<code>_Fill_Value</code> (defined separately for each variable type). The
default behavior of the netCDF library correspongs to
<code>set_fill_on</code>. Data which are equal to the
<code>_Fill_Value</code> indicate that the variable was created, but
never written to.</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="setncattr"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">setncattr</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">name</span>,
<span class="sig-arg">value</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>set a netCDF dataset or group attribute using name,value pair. Only
use if you need to set a netCDF attribute with the same name as one of
the reserved python attributes.</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="setncatts"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<table width="100%" cellpadding="0" cellspacing="0" border="0">
<tr valign="top"><td>
<h3 class="epydoc"><span class="sig"><span class="sig-name">setncatts</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">attdict</span>)</span>
</h3>
</td><td align="right" valign="top"
>
</td>
</tr></table>
<p>set a bunch of netCDF dataset or group attributes at once using a
python dictionary. This may be faster when setting a lot of attributes
for a NETCDF3 formatted file, since nc_redef/nc_enddef is not called in
between setting each attribute</p>
<dl class="fields">
</dl>
</td></tr></table>
</div>
<br />
<!-- ==================== INSTANCE VARIABLE DETAILS ==================== -->
<a name="section-InstanceVariableDetails"></a>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr bgcolor="#70b0f0" class="table-header">
<td align="left" colspan="2" class="table-header">
<span class="table-header">Instance Variable Details</span></td>
</tr>
</table>
<a name="file_format"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<h3 class="epydoc">file_format</h3>
The <code>file_format</code> attribute describes the netCDF file format
version, one of <code>NETCDF3_CLASSIC</code>, <code>NETCDF4</code>,
<code>NETCDF4_CLASSIC</code> or <code>NETCDF3_64BIT</code>. This module
can read and write all formats.
<dl class="fields">
</dl>
</td></tr></table>
</div>
<a name="path"></a>
<div>
<table class="details" border="1" cellpadding="3"
cellspacing="0" width="100%" bgcolor="white">
<tr><td>
<h3 class="epydoc">path</h3>
The <code>path</code> attribute shows the location of the <a
href="netCDF4.Group-class.html" class="link">Group</a> in the <a
href="netCDF4.Dataset-class.html" class="link">Dataset</a> in a unix
directory format (the names of groups in the hierarchy separated by
backslashes). A <a href="netCDF4.Dataset-class.html"
class="link">Dataset</a>, instance is the root group, so the path is
simply <code>'/'</code>.
<dl class="fields">
</dl>
</td></tr></table>
</div>
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