[netcdf4-python] 01/05: Imported Upstream version 1.2.6
Bas Couwenberg
sebastic at debian.org
Sat Dec 10 18:36:05 UTC 2016
This is an automated email from the git hooks/post-receive script.
sebastic pushed a commit to branch master
in repository netcdf4-python.
commit 95be670ea54394f9cdc0de0ceb970546512bc017
Author: Bas Couwenberg <sebastic at xs4all.nl>
Date: Sat Dec 10 19:20:41 2016 +0100
Imported Upstream version 1.2.6
---
.travis.yml | 4 +-
Changelog | 15 +
README.md | 4 +
docs/netCDF4/index.html | 153 +-
netCDF4/_netCDF4.c | 25306 +++++++++++++++++++--------------------
netCDF4/_netCDF4.pyx | 123 +-
setup.py | 2 +-
test/tst_compound_alignment.py | 3 +-
test/tst_multifile.py | 6 +
9 files changed, 12350 insertions(+), 13266 deletions(-)
diff --git a/.travis.yml b/.travis.yml
index e84b56b..b56218d 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -23,11 +23,11 @@ python:
matrix:
include:
# Absolute minimum dependencies.
- - python: 2.6
+ - python: 2.7
env:
- DEPENDS="numpy==1.7.0 cython==0.19 ordereddict==1.1"
# Test without Cython installed.
- - python: 2.6
+ - python: 2.7
env:
- DEPENDS="numpy ordereddict"
diff --git a/Changelog b/Changelog
index 0746d53..51e74db 100644
--- a/Changelog
+++ b/Changelog
@@ -1,3 +1,18 @@
+ version 1.2.6 (tag v1.2.6rel)
+==============================
+ * fix some test failures on big endian PPC64 that were due to
+ errors in byte-swapping logic. Also fixed bug in enum
+ code exposed on PPC64 (issue #608).
+ * remove support for python 2.6 (it probably still will work for a while
+ though).
+ * Sometimes checking that data being assigned to a variable has
+ an 'ndim' attribute is not sufficient, instead check to see that
+ the object supports the buffer interface (issue #613).
+ * make get_variables_by_attributes work in MFDataset (issue #610)
+ The hack is also applied for set_auto_maskandscale, set_auto_scale,
+ set_automask, so these don't have to be duplicated in MFDataset (pull
+ request #571).
+
version 1.2.5 (tag v1.2.5rel)
==============================
* Add MFDataset.set_auto_maskandscale (plus set_auto_scale, set_auto_mask).
diff --git a/README.md b/README.md
index 432a803..474c3de 100644
--- a/README.md
+++ b/README.md
@@ -8,6 +8,10 @@
## News
For the latest updates, see the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog).
+12/10/2016: Version [1.2.6](https://github.com/Unidata/netcdf4-python/releases/tag/v1.2.6rel) released.
+Bug fixes for Enum data type, and _FillValue/missing_value usage when data is stored
+in non-native endian format. Add get_variables_by_attributes to MFDataset. Support for python 2.6 removed.
+
12/1/2016: Version [1.2.5](https://pypi.python.org/pypi/netCDF4/1.2.5) released.
See the [Changelog](https://github.com/Unidata/netcdf4-python/blob/master/Changelog) for changes.
diff --git a/docs/netCDF4/index.html b/docs/netCDF4/index.html
index 9004cc9..a3105aa 100644
--- a/docs/netCDF4/index.html
+++ b/docs/netCDF4/index.html
@@ -4,7 +4,7 @@
<meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
<title>netCDF4 API documentation</title>
- <meta name="description" content="Version 1.2.5
+ <meta name="description" content="Version 1.2.6
-------------
- - -
@@ -1179,6 +1179,9 @@ table {
<li class="mono"><a href="#netCDF4.MFDataset.renameDimension">renameDimension</a></li>
<li class="mono"><a href="#netCDF4.MFDataset.renameGroup">renameGroup</a></li>
<li class="mono"><a href="#netCDF4.MFDataset.renameVariable">renameVariable</a></li>
+ <li class="mono"><a href="#netCDF4.MFDataset.set_auto_mask">set_auto_mask</a></li>
+ <li class="mono"><a href="#netCDF4.MFDataset.set_auto_maskandscale">set_auto_maskandscale</a></li>
+ <li class="mono"><a href="#netCDF4.MFDataset.set_auto_scale">set_auto_scale</a></li>
<li class="mono"><a href="#netCDF4.MFDataset.set_fill_off">set_fill_off</a></li>
<li class="mono"><a href="#netCDF4.MFDataset.set_fill_on">set_fill_on</a></li>
<li class="mono"><a href="#netCDF4.MFDataset.setncattr">setncattr</a></li>
@@ -1188,9 +1191,6 @@ table {
<li class="mono"><a href="#netCDF4.MFDataset.__init__">__init__</a></li>
<li class="mono"><a href="#netCDF4.MFDataset.close">close</a></li>
<li class="mono"><a href="#netCDF4.MFDataset.ncattrs">ncattrs</a></li>
- <li class="mono"><a href="#netCDF4.MFDataset.set_auto_mask">set_auto_mask</a></li>
- <li class="mono"><a href="#netCDF4.MFDataset.set_auto_maskandscale">set_auto_maskandscale</a></li>
- <li class="mono"><a href="#netCDF4.MFDataset.set_auto_scale">set_auto_scale</a></li>
</ul>
</li>
@@ -1259,7 +1259,7 @@ table {
<header id="section-intro">
<h1 class="title"><span class="name">netCDF4</span> module</h1>
- <h2>Version 1.2.5</h2>
+ <h2>Version 1.2.6</h2>
<hr />
<h1>Introduction</h1>
<p>netcdf4-python is a Python interface to the netCDF C library. </p>
@@ -1287,7 +1287,7 @@ types) are not supported.</p>
</ul>
<h1>Requires</h1>
<ul>
-<li>Python 2.6 or later (python 3 works too).</li>
+<li>Python 2.7 or later (python 3 works too).</li>
<li><a href="http://numpy.scipy.org">numpy array module</a>, version 1.7.0 or later.</li>
<li><a href="http://cython.org">Cython</a>, version 0.19 or later, is optional - if it is installed setup.py will
use it to recompile the Cython source code into C, using conditional compilation
@@ -1295,7 +1295,6 @@ types) are not supported.</p>
Cython is not installed, these features (such as the ability to rename Group objects)
will be disabled to preserve backward compatibility with older versions of the netCDF
library.</li>
-<li>For python < 2.7, the <a href="http://python.org/pypi/ordereddict">ordereddict module</a>.</li>
<li>The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
from <a href="ftp://ftp.hdfgroup.org/HDF5/current/src"></a>.
<strong><em>netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
@@ -1306,8 +1305,8 @@ types) are not supported.</p>
<a href="http://opendap.org">OPeNDAP</a> support.</li>
<li><a href="http://www.hdfgroup.org/products/hdf4">HDF4</a>, if you want
to be able to read HDF4 "Scientific Dataset" (SD) files.</li>
-<li>The netCDF-4 C library from
- <a href="ftp://ftp.unidata.ucar.edu/pub/netcdf">ftp://ftp.unidata.ucar.edu/pub/netcdf</a>.
+<li>The netCDF-4 C library from the <a href="https://github.com/Unidata/netcdf-c/releases">github releases
+ page</a>.
Version 4.1.1 or higher is required (4.2 or higher recommended).
Be sure to build with <code>--enable-netcdf-4 --enable-shared</code>, and set
<code>CPPFLAGS="-I $HDF5_DIR/include"</code> and <code>LDFLAGS="-L $HDF5_DIR/lib"</code>,
@@ -5085,6 +5084,78 @@ name as one of the reserved python attributes.</p></div>
<div class="item">
+ <div class="name def" id="netCDF4.MFDataset.set_auto_mask">
+ <p>def <span class="ident">set_auto_mask</span>(</p><p>self, True_or_False)</p>
+ </div>
+
+ <p class="inheritance">
+ <strong>Inheritance:</strong>
+ <code><a href="#netCDF4.Dataset">Dataset</a></code>.<code><a href="#netCDF4.Dataset.set_auto_mask">set_auto_mask</a></code>
+ </p>
+
+
+
+ <div class="desc inherited"><p>Call <a href="#netCDF4.Variable.set_auto_mask"><code>set_auto_mask</code></a> for all variables contained in this <a href="#netCDF4.Dataset"><code>Dataset</code></a> or
+<a href="#netCDF4.Group"><code>Group</code></a>, as well as for all variables in all its subgroups.</p>
+<p><strong><code>True_or_False</code></strong>: Boolean determining if automatic conversion to masked arrays
+shall be applied for all variables.</p>
+<p><strong><em>Note</em></strong>: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.</p></div>
+ <div class="source_cont">
+</div>
+
+ </div>
+
+
+ <div class="item">
+ <div class="name def" id="netCDF4.MFDataset.set_auto_maskandscale">
+ <p>def <span class="ident">set_auto_maskandscale</span>(</p><p>self, True_or_False)</p>
+ </div>
+
+ <p class="inheritance">
+ <strong>Inheritance:</strong>
+ <code><a href="#netCDF4.Dataset">Dataset</a></code>.<code><a href="#netCDF4.Dataset.set_auto_maskandscale">set_auto_maskandscale</a></code>
+ </p>
+
+
+
+ <div class="desc inherited"><p>Call <a href="#netCDF4.Variable.set_auto_maskandscale"><code>set_auto_maskandscale</code></a> for all variables contained in this <a href="#netCDF4.Dataset"><code>Dataset</code></a> or
+<a href="#netCDF4.Group"><code>Group</code></a>, as well as for all variables in all its subgroups.</p>
+<p><strong><code>True_or_False</code></strong>: Boolean determining if automatic conversion to masked arrays
+and variable scaling shall be applied for all variables.</p>
+<p><strong><em>Note</em></strong>: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.</p></div>
+ <div class="source_cont">
+</div>
+
+ </div>
+
+
+ <div class="item">
+ <div class="name def" id="netCDF4.MFDataset.set_auto_scale">
+ <p>def <span class="ident">set_auto_scale</span>(</p><p>self, True_or_False)</p>
+ </div>
+
+ <p class="inheritance">
+ <strong>Inheritance:</strong>
+ <code><a href="#netCDF4.Dataset">Dataset</a></code>.<code><a href="#netCDF4.Dataset.set_auto_scale">set_auto_scale</a></code>
+ </p>
+
+
+
+ <div class="desc inherited"><p>Call <a href="#netCDF4.Variable.set_auto_scale"><code>set_auto_scale</code></a> for all variables contained in this <a href="#netCDF4.Dataset"><code>Dataset</code></a> or
+<a href="#netCDF4.Group"><code>Group</code></a>, as well as for all variables in all its subgroups.</p>
+<p><strong><code>True_or_False</code></strong>: Boolean determining if automatic variable scaling
+shall be applied for all variables.</p>
+<p><strong><em>Note</em></strong>: Calling this function only affects existing variables. Variables created
+after calling this function will follow the default behaviour.</p></div>
+ <div class="source_cont">
+</div>
+
+ </div>
+
+
+ <div class="item">
<div class="name def" id="netCDF4.MFDataset.set_fill_off">
<p>def <span class="ident">set_fill_off</span>(</p><p>self)</p>
</div>
@@ -5293,70 +5364,6 @@ Default is an empty list.</p></div>
</div>
-
- <div class="item">
- <div class="name def" id="netCDF4.MFDataset.set_auto_mask">
- <p>def <span class="ident">set_auto_mask</span>(</p><p>self, True_or_False)</p>
- </div>
-
- <p class="inheritance">
- <strong>Inheritance:</strong>
- <code><a href="#netCDF4.Dataset">Dataset</a></code>.<code><a href="#netCDF4.Dataset.set_auto_mask">set_auto_mask</a></code>
- </p>
-
-
-
- <div class="desc"><p>Call <code>Variable.set_auto_mask</code> for all variables contained in this <code>MFDataset</code>.</p>
-<p><strong><code>True_or_False</code></strong>: Boolean determining if automatic conversion to masked arrays
-shall be applied for all variables.</p></div>
- <div class="source_cont">
-</div>
-
- </div>
-
-
- <div class="item">
- <div class="name def" id="netCDF4.MFDataset.set_auto_maskandscale">
- <p>def <span class="ident">set_auto_maskandscale</span>(</p><p>self, True_or_False)</p>
- </div>
-
- <p class="inheritance">
- <strong>Inheritance:</strong>
- <code><a href="#netCDF4.Dataset">Dataset</a></code>.<code><a href="#netCDF4.Dataset.set_auto_maskandscale">set_auto_maskandscale</a></code>
- </p>
-
-
-
- <div class="desc"><p>Call <code>Variable.set_auto_maskandscale</code> for all variables contained in this
-<code>MFDataset</code>.</p>
-<p><strong><code>True_or_False</code></strong>: Boolean determining if automatic conversion to masked arrays
-and variable scaling shall be applied for all variables.</p></div>
- <div class="source_cont">
-</div>
-
- </div>
-
-
- <div class="item">
- <div class="name def" id="netCDF4.MFDataset.set_auto_scale">
- <p>def <span class="ident">set_auto_scale</span>(</p><p>self, True_or_False)</p>
- </div>
-
- <p class="inheritance">
- <strong>Inheritance:</strong>
- <code><a href="#netCDF4.Dataset">Dataset</a></code>.<code><a href="#netCDF4.Dataset.set_auto_scale">set_auto_scale</a></code>
- </p>
-
-
-
- <div class="desc"><p>Call <code>Variable.set_auto_scale</code> for all variables contained in this <code>MFDataset</code>.</p>
-<p><strong><code>True_or_False</code></strong>: Boolean determining if automatic variable scaling
-shall be applied for all variables.</p></div>
- <div class="source_cont">
-</div>
-
- </div>
-
</div>
</div>
diff --git a/netCDF4/_netCDF4.c b/netCDF4/_netCDF4.c
index a9a4296..3f68736 100644
--- a/netCDF4/_netCDF4.c
+++ b/netCDF4/_netCDF4.c
@@ -642,7 +642,7 @@ struct __pyx_opt_args_7netCDF4_8_netCDF4__strencode;
struct __pyx_defaults;
typedef struct __pyx_defaults __pyx_defaults;
-/* "netCDF4/_netCDF4.pyx":1241
+/* "netCDF4/_netCDF4.pyx":1242
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
*
* cdef _set_att(grp, int varid, name, value,\ # <<<<<<<<<<<<<<
@@ -655,7 +655,7 @@ struct __pyx_opt_args_7netCDF4_8_netCDF4__set_att {
PyObject *force_ncstring;
};
-/* "netCDF4/_netCDF4.pyx":4723
+/* "netCDF4/_netCDF4.pyx":4732
* return xtype
*
* cdef _read_compound(group, nc_type xtype, endian=None): # <<<<<<<<<<<<<<
@@ -667,7 +667,7 @@ struct __pyx_opt_args_7netCDF4_8_netCDF4__read_compound {
PyObject *endian;
};
-/* "netCDF4/_netCDF4.pyx":4896
+/* "netCDF4/_netCDF4.pyx":4905
* return xtype, dt
*
* cdef _read_vlen(group, nc_type xtype, endian=None): # <<<<<<<<<<<<<<
@@ -679,7 +679,7 @@ struct __pyx_opt_args_7netCDF4_8_netCDF4__read_vlen {
PyObject *endian;
};
-/* "netCDF4/_netCDF4.pyx":5019
+/* "netCDF4/_netCDF4.pyx":5028
* return xtype, dt
*
* cdef _read_enum(group, nc_type xtype, endian=None): # <<<<<<<<<<<<<<
@@ -691,7 +691,7 @@ struct __pyx_opt_args_7netCDF4_8_netCDF4__read_enum {
PyObject *endian;
};
-/* "netCDF4/_netCDF4.pyx":5055
+/* "netCDF4/_netCDF4.pyx":5064
* return EnumType(group, dt, name, enum_dict, typeid=xtype)
*
* cdef _strencode(pystr,encoding=None): # <<<<<<<<<<<<<<
@@ -706,7 +706,7 @@ struct __pyx_defaults {
PyObject *__pyx_arg_exclude;
};
-/* "netCDF4/_netCDF4.pyx":1590
+/* "netCDF4/_netCDF4.pyx":1591
* __pdoc__ = {}
*
* cdef class Dataset: # <<<<<<<<<<<<<<
@@ -734,7 +734,7 @@ struct __pyx_obj_7netCDF4_8_netCDF4_Dataset {
};
-/* "netCDF4/_netCDF4.pyx":2591
+/* "netCDF4/_netCDF4.pyx":2604
*
*
* cdef class Group(Dataset): # <<<<<<<<<<<<<<
@@ -746,7 +746,7 @@ struct __pyx_obj_7netCDF4_8_netCDF4_Group {
};
-/* "netCDF4/_netCDF4.pyx":2686
+/* "netCDF4/_netCDF4.pyx":2699
*
*
* cdef class Dimension: # <<<<<<<<<<<<<<
@@ -763,7 +763,7 @@ struct __pyx_obj_7netCDF4_8_netCDF4_Dimension {
};
-/* "netCDF4/_netCDF4.pyx":2847
+/* "netCDF4/_netCDF4.pyx":2860
* return False
*
* cdef class Variable: # <<<<<<<<<<<<<<
@@ -793,7 +793,7 @@ struct __pyx_obj_7netCDF4_8_netCDF4_Variable {
};
-/* "netCDF4/_netCDF4.pyx":4558
+/* "netCDF4/_netCDF4.pyx":4567
* # Compound datatype support.
*
* cdef class CompoundType: # <<<<<<<<<<<<<<
@@ -808,7 +808,7 @@ struct __pyx_obj_7netCDF4_8_netCDF4_CompoundType {
};
-/* "netCDF4/_netCDF4.pyx":4807
+/* "netCDF4/_netCDF4.pyx":4816
* # VLEN datatype support.
*
* cdef class VLType: # <<<<<<<<<<<<<<
@@ -823,7 +823,7 @@ struct __pyx_obj_7netCDF4_8_netCDF4_VLType {
};
-/* "netCDF4/_netCDF4.pyx":4925
+/* "netCDF4/_netCDF4.pyx":4934
* # Enum datatype support.
*
* cdef class EnumType: # <<<<<<<<<<<<<<
@@ -839,7 +839,7 @@ struct __pyx_obj_7netCDF4_8_netCDF4_EnumType {
};
-/* "netCDF4/_netCDF4.pyx":1033
+/* "netCDF4/_netCDF4.pyx":1032
* _format_dict['NETCDF3_64BIT'] = NC_FORMAT_64BIT
* # invert dictionary mapping
* _reverse_format_dict = dict((v, k) for k, v in _format_dict.iteritems()) # <<<<<<<<<<<<<<
@@ -1616,6 +1616,7 @@ int __pyx_module_is_main_netCDF4___netCDF4 = 0;
/* Implementation of 'netCDF4._netCDF4' */
static PyObject *__pyx_builtin_ImportError;
+static PyObject *__pyx_builtin_memoryview;
static PyObject *__pyx_builtin_object;
static PyObject *__pyx_builtin_AttributeError;
static PyObject *__pyx_builtin_MemoryError;
@@ -1782,7 +1783,7 @@ static const char __pyx_k_vlen[] = "vlen";
static const char __pyx_k_warn[] = "warn";
static const char __pyx_k_year[] = "year";
static const char __pyx_k_zlib[] = "zlib";
-static const char __pyx_k_1_2_5[] = "1.2.5";
+static const char __pyx_k_1_2_6[] = "1.2.6";
static const char __pyx_k_4_2_1[] = "4.2.1";
static const char __pyx_k_4_4_0[] = "4.4.0";
static const char __pyx_k_4_4_1[] = "4.4.1";
@@ -1843,6 +1844,7 @@ static const char __pyx_k_aggdim[] = "aggdim";
static const char __pyx_k_append[] = "append";
static const char __pyx_k_around[] = "around";
static const char __pyx_k_astype[] = "astype";
+static const char __pyx_k_buffer[] = "buffer";
static const char __pyx_k_decode[] = "decode";
static const char __pyx_k_dims_2[] = "dims";
static const char __pyx_k_dset_2[] = "_dset";
@@ -1913,6 +1915,7 @@ static const char __pyx_k_group_s[] = "group %s:\n";
static const char __pyx_k_has_lsd[] = "_has_lsd";
static const char __pyx_k_nc_type[] = "_nc_type";
static const char __pyx_k_ncattrs[] = "ncattrs";
+static const char __pyx_k_ndarray[] = "ndarray";
static const char __pyx_k_newname[] = "newname";
static const char __pyx_k_offsets[] = "offsets";
static const char __pyx_k_oldname[] = "oldname";
@@ -1963,6 +1966,7 @@ static const char __pyx_k_grpnames[] = "grpnames";
static const char __pyx_k_has_cdf5[] = "__has_cdf5__";
static const char __pyx_k_hr_units[] = "hr_units";
static const char __pyx_k_ismasked[] = "ismasked";
+static const char __pyx_k_isnative[] = "isnative";
static const char __pyx_k_isscalar[] = "isscalar";
static const char __pyx_k_itemsize[] = "itemsize";
static const char __pyx_k_newSlice[] = "newSlice";
@@ -2036,6 +2040,7 @@ static const char __pyx_k_groups_s_2[] = " groups = %s\n";
static const char __pyx_k_iscompound[] = "_iscompound";
static const char __pyx_k_masterDims[] = "masterDims";
static const char __pyx_k_masterType[] = "masterType";
+static const char __pyx_k_memoryview[] = "memoryview";
static const char __pyx_k_ncdump_var[] = "ncdump_var";
static const char __pyx_k_nctonptype[] = "_nctonptype";
static const char __pyx_k_netcdftime[] = "netcdftime";
@@ -2194,7 +2199,6 @@ static const char __pyx_k_size_cannot_be_altered[] = "size cannot be altered";
static const char __pyx_k_unlimited_dimensions_s[] = "unlimited dimensions: %s\n";
static const char __pyx_k_unsupported_time_units[] = "unsupported time units";
static const char __pyx_k_variables_dimensions_s[] = " variables(dimensions): %s\n";
-static const char __pyx_k_MFDataset_set_auto_mask[] = "MFDataset.set_auto_mask";
static const char __pyx_k_VLType_is_not_picklable[] = "VLType is not picklable";
static const char __pyx_k_Variable_set_auto_scale[] = "_Variable.set_auto_scale";
static const char __pyx_k_least_significant_digit[] = "least_significant_digit";
@@ -2203,7 +2207,6 @@ static const char __pyx_k_shape_cannot_be_altered[] = "shape cannot be altered";
static const char __pyx_k_unlimited_name_s_size_s[] = " (unlimited): name = '%s', size = %s\n";
static const char __pyx_k_Dataset_is_not_picklable[] = "Dataset is not picklable";
static const char __pyx_k_MFDataset___getattribute[] = "MFDataset.__getattribute__";
-static const char __pyx_k_MFDataset_set_auto_scale[] = "MFDataset.set_auto_scale";
static const char __pyx_k_needsworkaround_issue485[] = "_needsworkaround_issue485";
static const char __pyx_k_unlimited_dimensions_s_2[] = "unlimited dimensions = %s\n";
static const char __pyx_k_EnumType_is_not_picklable[] = "EnumType is not picklable";
@@ -2230,11 +2233,10 @@ static const char __pyx_k_Always_True_Indicates_to_client[] = "Always `True`. I
static const char __pyx_k_Class_for_reading_multi_file_ne[] = "\nClass for reading multi-file netCDF Datasets, making variables\nspanning multiple files appear as if they were in one file.\nDatasets must be in `NETCDF4_CLASSIC, NETCDF3_CLASSIC, NETCDF3_64BIT_OFFSET\nor NETCDF3_64BIT_DATA` format (`NETCDF4` Datasets won't work).\n\nAdapted from [pycdf](http://pysclint.sourceforge.net/pycdf) by Andre Gosselin.\n\nExample usage (See `netCDF4.MFDataset.__init__` for more details):\n\n ::: [...]
static const char __pyx_k_Class_providing_an_interface_to[] = "\nClass providing an interface to a MFDataset time Variable by imposing a unique common\ntime unit to all files. \n\nExample usage (See `netCDF4.MFTime.__init__` for more details):\n\n :::python\n >>> import numpy\n >>> f1 = Dataset(\"mftest_1.nc\",\"w\", format=\"NETCDF4_CLASSIC\")\n >>> f2 = Dataset(\"mftest_2.nc\",\"w\", format=\"NETCDF4_CLASSIC\")\n >>> f1.createDimension(\"time\",None)\n >>> f2.createDi [...]
static const char __pyx_k_FillValue_attribute_must_be_set[] = "_FillValue attribute must be set when variable is ";
-static const char __pyx_k_MFDataset_set_auto_maskandscale[] = "MFDataset.set_auto_maskandscale";
static const char __pyx_k_The_vltypes_dictionary_maps_the[] = "The `vltypes` dictionary maps the names of\n variable-length types defined for the `netCDF4.Group` or `netCDF4.Dataset` to instances of the\n `netCDF4.VLType` class.";
+static const char __pyx_k_Users_jsw_python_netcdf4_python[] = "/Users/jsw/python/netcdf4-python.git/netCDF4/_netCDF4.pyx";
static const char __pyx_k_Variable_object_no_longer_valid[] = "Variable object no longer valid";
-static const char __pyx_k_Version_1_2_5_Introduction_netc[] = "\nVersion 1.2.5\n-------------\n- - - \n\nIntroduction\n============\n\nnetcdf4-python is a Python interface to the netCDF C library. \n\n[netCDF](http://www.unidata.ucar.edu/software/netcdf/) version 4 has many features\nnot found in earlier versions of the library and is implemented on top of\n[HDF5](http://www.hdfgroup.org/HDF5). This module can read and write\nfiles in both the new netCDF 4 and the old netCDF 3 format, a [...]
-static const char __pyx_k_Volumes_Drobo_python_netcdf4_py[] = "/Volumes/Drobo/python/netcdf4-python.git/netCDF4/_netCDF4.pyx";
+static const char __pyx_k_Version_1_2_6_Introduction_netc[] = "\nVersion 1.2.6\n-------------\n- - - \n\nIntroduction\n============\n\nnetcdf4-python is a Python interface to the netCDF C library. \n\n[netCDF](http://www.unidata.ucar.edu/software/netcdf/) version 4 has many features\nnot found in earlier versions of the library and is implemented on top of\n[HDF5](http://www.hdfgroup.org/HDF5). This module can read and write\nfiles in both the new netCDF 4 and the old netCDF 3 format, a [...]
static const char __pyx_k_assign_vlen_method_only_for_use[] = "_assign_vlen method only for use with VLEN variables";
static const char __pyx_k_cannot_set__FillValue_attribute[] = "cannot set _FillValue attribute for VLEN or compound variable";
static const char __pyx_k_cannot_specify_chunksizes_for_a[] = "cannot specify chunksizes for a contiguous dataset";
@@ -2257,7 +2259,7 @@ static const char __pyx_k_zero_not_allowed_as_a_reference[] = "zero not allowed
static const char __pyx_k_A_numpy_integer_dtype_object_des[] = "A numpy integer dtype object describing the base type for the Enum.";
static const char __pyx_k_A_python_dictionary_describing_t[] = "A python dictionary describing the enum fields and values.";
static const char __pyx_k_A_tuple_with_the_current_shape_l[] = "A tuple with the current shape (length of all dimensions).";
-static const char __pyx_k_Dataset_get_variables_by_attribu[] = "Dataset.get_variables_by_attributes (line 2541)";
+static const char __pyx_k_Dataset_get_variables_by_attribu[] = "Dataset.get_variables_by_attributes (line 2550)";
static const char __pyx_k_Describes_the_power_of_ten_of_th[] = "Describes the power of ten of the \n smallest decimal place in the data the contains a reliable value. Data is\n truncated to this decimal place when it is assigned to the `netCDF4.Variable`\n instance. If `None`, the data is not truncated.";
static const char __pyx_k_Dimension_object_no_longer_valid[] = "Dimension object no longer valid";
static const char __pyx_k_If_True_child_Dimension_and_Vari[] = "If `True`, child Dimension and Variables objects only keep weak references to\n the parent Dataset or Group.";
@@ -2334,7 +2336,7 @@ static PyObject *__pyx_kp_s_;
static PyObject *__pyx_kp_s_0m;
static PyObject *__pyx_kp_s_1;
static PyObject *__pyx_kp_s_1_10;
-static PyObject *__pyx_kp_s_1_2_5;
+static PyObject *__pyx_kp_s_1_2_6;
static PyObject *__pyx_kp_s_4_2_1;
static PyObject *__pyx_kp_s_4_4_0;
static PyObject *__pyx_kp_s_4_4_1;
@@ -2401,9 +2403,6 @@ static PyObject *__pyx_n_s_MFDataset___setattr;
static PyObject *__pyx_n_s_MFDataset_close;
static PyObject *__pyx_kp_s_MFDataset_is_not_picklable;
static PyObject *__pyx_n_s_MFDataset_ncattrs;
-static PyObject *__pyx_n_s_MFDataset_set_auto_mask;
-static PyObject *__pyx_n_s_MFDataset_set_auto_maskandscale;
-static PyObject *__pyx_n_s_MFDataset_set_auto_scale;
static PyObject *__pyx_kp_s_MFNetCDF4_only_works_with_NETCDF;
static PyObject *__pyx_n_s_MFTime;
static PyObject *__pyx_n_s_MFTime___getitem;
@@ -2444,6 +2443,7 @@ static PyObject *__pyx_n_s_UNDEFINED;
static PyObject *__pyx_n_s_UnicodeDecodeError;
static PyObject *__pyx_n_s_UnicodeError;
static PyObject *__pyx_kp_s_Unsupported_compound_type_elemen;
+static PyObject *__pyx_kp_s_Users_jsw_python_netcdf4_python;
static PyObject *__pyx_n_s_V;
static PyObject *__pyx_kp_s_VLType_dtype;
static PyObject *__pyx_kp_s_VLType_is_not_picklable;
@@ -2475,7 +2475,6 @@ static PyObject *__pyx_n_s_Variable_set_auto_scale;
static PyObject *__pyx_kp_s_Variable_shape;
static PyObject *__pyx_kp_s_Variable_size;
static PyObject *__pyx_n_s_Variable_typecode;
-static PyObject *__pyx_kp_s_Volumes_Drobo_python_netcdf4_py;
static PyObject *__pyx_kp_s_WARNING_Backwards_incompatible;
static PyObject *__pyx_kp_s_WARNING_unsupported_Compound_typ;
static PyObject *__pyx_kp_s_WARNING_unsupported_Enum_type_sk;
@@ -2524,6 +2523,7 @@ static PyObject *__pyx_n_s_basedate;
static PyObject *__pyx_n_s_big;
static PyObject *__pyx_n_s_bool;
static PyObject *__pyx_n_s_bs;
+static PyObject *__pyx_n_s_buffer;
static PyObject *__pyx_n_s_byteorder;
static PyObject *__pyx_n_s_bytestr;
static PyObject *__pyx_n_s_byteswap;
@@ -2727,6 +2727,7 @@ static PyObject *__pyx_n_s_iscompound;
static PyObject *__pyx_n_s_isenum;
static PyObject *__pyx_n_s_ismasked;
static PyObject *__pyx_n_s_isnan;
+static PyObject *__pyx_n_s_isnative;
static PyObject *__pyx_n_s_isostring;
static PyObject *__pyx_n_s_isprimitive;
static PyObject *__pyx_n_s_isscalar;
@@ -2767,6 +2768,7 @@ static PyObject *__pyx_n_s_masterType;
static PyObject *__pyx_kp_s_master_dataset_s_does_not_have_a;
static PyObject *__pyx_kp_s_master_dataset_s_does_not_have_a_2;
static PyObject *__pyx_n_s_mastervar;
+static PyObject *__pyx_n_s_memoryview;
static PyObject *__pyx_n_s_metaclass;
static PyObject *__pyx_n_s_microsec_units;
static PyObject *__pyx_n_s_microseconds;
@@ -2799,6 +2801,7 @@ static PyObject *__pyx_n_s_ncdump;
static PyObject *__pyx_n_s_ncdump_var;
static PyObject *__pyx_n_s_nctime;
static PyObject *__pyx_n_s_nctonptype;
+static PyObject *__pyx_n_s_ndarray;
static PyObject *__pyx_n_s_ndim;
static PyObject *__pyx_n_s_needsworkaround_issue485;
static PyObject *__pyx_kp_s_negative_reference_year_in_time;
@@ -3288,12 +3291,9 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset___init__(CYTHON_UNUSED P
static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_2__setattr__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_4__getattribute__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_6ncattrs(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_8set_auto_maskandscale(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_10set_auto_mask(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_12set_auto_scale(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_14close(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_16__repr__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_18__reduce__(CYTHON_UNUSED PyObject *__pyx_self, CYTHON_UNUSED PyObject *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_8close(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_10__repr__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self); /* proto */
+static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9MFDataset_12__reduce__(CYTHON_UNUSED PyObject *__pyx_self, CYTHON_UNUSED PyObject *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7netCDF4_8_netCDF4_10_Dimension___init__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_dimname, CYTHON_UNUSED PyObject *__pyx_v_dim, PyObject *__pyx_v_dimlens, PyObject *__pyx_v_dimtotlen); /* proto */
static PyObject *__pyx_pf_7netCDF4_8_netCDF4_10_Dimension_2__len__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7netCDF4_8_netCDF4_10_Dimension_4isunlimited(CYTHON_UNUSED PyObject *__pyx_self, CYTHON_UNUSED PyObject *__pyx_v_self); /* proto */
@@ -3502,10 +3502,7 @@ static PyObject *__pyx_tuple__197;
static PyObject *__pyx_tuple__199;
static PyObject *__pyx_tuple__201;
static PyObject *__pyx_tuple__203;
-static PyObject *__pyx_tuple__205;
-static PyObject *__pyx_tuple__207;
-static PyObject *__pyx_tuple__209;
-static PyObject *__pyx_tuple__210;
+static PyObject *__pyx_tuple__204;
static PyObject *__pyx_codeobj__131;
static PyObject *__pyx_codeobj__132;
static PyObject *__pyx_codeobj__139;
@@ -3540,13 +3537,10 @@ static PyObject *__pyx_codeobj__196;
static PyObject *__pyx_codeobj__198;
static PyObject *__pyx_codeobj__200;
static PyObject *__pyx_codeobj__202;
-static PyObject *__pyx_codeobj__204;
-static PyObject *__pyx_codeobj__206;
-static PyObject *__pyx_codeobj__208;
-static PyObject *__pyx_codeobj__211;
+static PyObject *__pyx_codeobj__205;
static PyObject *__pyx_gb_7netCDF4_8_netCDF4_24generator(__pyx_CoroutineObject *__pyx_generator, PyObject *__pyx_sent_value); /* proto */
-/* "netCDF4/_netCDF4.pyx":1033
+/* "netCDF4/_netCDF4.pyx":1032
* _format_dict['NETCDF3_64BIT'] = NC_FORMAT_64BIT
* # invert dictionary mapping
* _reverse_format_dict = dict((v, k) for k, v in _format_dict.iteritems()) # <<<<<<<<<<<<<<
@@ -3563,12 +3557,12 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_22genexpr(CYTHON_UNUSED PyObject *_
if (unlikely(!__pyx_cur_scope)) {
__pyx_cur_scope = ((struct __pyx_obj_7netCDF4_8_netCDF4___pyx_scope_struct__genexpr *)Py_None);
__Pyx_INCREF(Py_None);
- __PYX_ERR(0, 1033, __pyx_L1_error)
+ __PYX_ERR(0, 1032, __pyx_L1_error)
} else {
__Pyx_GOTREF(__pyx_cur_scope);
}
{
- __pyx_CoroutineObject *gen = __Pyx_Generator_New((__pyx_coroutine_body_t) __pyx_gb_7netCDF4_8_netCDF4_24generator, (PyObject *) __pyx_cur_scope, __pyx_n_s_genexpr, __pyx_n_s_genexpr, __pyx_n_s_netCDF4__netCDF4); if (unlikely(!gen)) __PYX_ERR(0, 1033, __pyx_L1_error)
+ __pyx_CoroutineObject *gen = __Pyx_Generator_New((__pyx_coroutine_body_t) __pyx_gb_7netCDF4_8_netCDF4_24generator, (PyObject *) __pyx_cur_scope, __pyx_n_s_genexpr, __pyx_n_s_genexpr, __pyx_n_s_netCDF4__netCDF4); if (unlikely(!gen)) __PYX_ERR(0, 1032, __pyx_L1_error)
__Pyx_DECREF(__pyx_cur_scope);
__Pyx_RefNannyFinishContext();
return (PyObject *) gen;
@@ -3604,17 +3598,17 @@ static PyObject *__pyx_gb_7netCDF4_8_netCDF4_24generator(__pyx_CoroutineObject *
return NULL;
}
__pyx_L3_first_run:;
- if (unlikely(!__pyx_sent_value)) __PYX_ERR(0, 1033, __pyx_L1_error)
- __pyx_r = PyDict_New(); if (unlikely(!__pyx_r)) __PYX_ERR(0, 1033, __pyx_L1_error)
+ if (unlikely(!__pyx_sent_value)) __PYX_ERR(0, 1032, __pyx_L1_error)
+ __pyx_r = PyDict_New(); if (unlikely(!__pyx_r)) __PYX_ERR(0, 1032, __pyx_L1_error)
__Pyx_GOTREF(__pyx_r);
__pyx_t_2 = 0;
- __pyx_t_5 = __Pyx_GetModuleGlobalName(__pyx_n_s_format_dict); if (unlikely(!__pyx_t_5)) __PYX_ERR(0, 1033, __pyx_L1_error)
+ __pyx_t_5 = __Pyx_GetModuleGlobalName(__pyx_n_s_format_dict); if (unlikely(!__pyx_t_5)) __PYX_ERR(0, 1032, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_5);
if (unlikely(__pyx_t_5 == Py_None)) {
PyErr_Format(PyExc_AttributeError, "'NoneType' object has no attribute '%s'", "iteritems");
- __PYX_ERR(0, 1033, __pyx_L1_error)
+ __PYX_ERR(0, 1032, __pyx_L1_error)
}
- __pyx_t_6 = __Pyx_dict_iterator(__pyx_t_5, 0, __pyx_n_s_iteritems, (&__pyx_t_3), (&__pyx_t_4)); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1033, __pyx_L1_error)
+ __pyx_t_6 = __Pyx_dict_iterator(__pyx_t_5, 0, __pyx_n_s_iteritems, (&__pyx_t_3), (&__pyx_t_4)); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1032, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_6);
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__Pyx_XDECREF(__pyx_t_1);
@@ -3623,7 +3617,7 @@ static PyObject *__pyx_gb_7netCDF4_8_netCDF4_24generator(__pyx_CoroutineObject *
while (1) {
__pyx_t_7 = __Pyx_dict_iter_next(__pyx_t_1, __pyx_t_3, &__pyx_t_2, &__pyx_t_6, &__pyx_t_5, NULL, __pyx_t_4);
if (unlikely(__pyx_t_7 == 0)) break;
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__Pyx_GOTREF(__pyx_t_5);
__Pyx_XGOTREF(__pyx_cur_scope->__pyx_v_k);
@@ -3634,7 +3628,7 @@ static PyObject *__pyx_gb_7netCDF4_8_netCDF4_24generator(__pyx_CoroutineObject *
__Pyx_XDECREF_SET(__pyx_cur_scope->__pyx_v_v, __pyx_t_5);
__Pyx_GIVEREF(__pyx_t_5);
__pyx_t_5 = 0;
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__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
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@@ -3655,7 +3649,7 @@ static PyObject *__pyx_gb_7netCDF4_8_netCDF4_24generator(__pyx_CoroutineObject *
return __pyx_r;
}
-/* "netCDF4/_netCDF4.pyx":959
+/* "netCDF4/_netCDF4.pyx":958
* # check for required version of netcdf-4 and hdf5.
*
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PyObject *__pyx_t_6 = NULL;
__Pyx_RefNannySetupContext("_gethdf5libversion", 0);
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*
* def _gethdf5libversion():
* majorvers = H5_VERS_MAJOR # <<<<<<<<<<<<<<
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*/
__pyx_v_majorvers = H5_VERS_MAJOR;
- /* "netCDF4/_netCDF4.pyx":961
+ /* "netCDF4/_netCDF4.pyx":960
* def _gethdf5libversion():
* majorvers = H5_VERS_MAJOR
* minorvers = H5_VERS_MINOR # <<<<<<<<<<<<<<
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*/
__pyx_v_minorvers = H5_VERS_MINOR;
- /* "netCDF4/_netCDF4.pyx":962
+ /* "netCDF4/_netCDF4.pyx":961
* majorvers = H5_VERS_MAJOR
* minorvers = H5_VERS_MINOR
* releasevers = H5_VERS_RELEASE # <<<<<<<<<<<<<<
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*/
__pyx_v_releasevers = H5_VERS_RELEASE;
- /* "netCDF4/_netCDF4.pyx":963
+ /* "netCDF4/_netCDF4.pyx":962
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* releasevers = H5_VERS_RELEASE
* patchstring = H5_VERS_SUBRELEASE.decode('ascii') # <<<<<<<<<<<<<<
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*/
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- __pyx_t_2 = __Pyx_PyObject_IsTrue(__pyx_v_patchstring); if (unlikely(__pyx_t_2 < 0)) __PYX_ERR(0, 964, __pyx_L1_error)
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* patchstring = H5_VERS_SUBRELEASE.decode('ascii')
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goto __pyx_L11;
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@@ -4749,7 +4743,7 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_att(PyObject *__pyx_v_grp, int
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{
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}
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goto __pyx_L0;
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*/
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*/
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+ /* "netCDF4/_netCDF4.pyx":1198
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return __pyx_r;
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goto __pyx_L29;
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+ /* "netCDF4/_netCDF4.pyx":1331
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- /* "netCDF4/_netCDF4.pyx":1331
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- /* "netCDF4/_netCDF4.pyx":1332
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- /* "netCDF4/_netCDF4.pyx":1333
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#endif
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- /* "netCDF4/_netCDF4.pyx":1334
+ /* "netCDF4/_netCDF4.pyx":1335
* typeids = <nc_type *>malloc(sizeof(nc_type) * ntypes)
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}
- /* "netCDF4/_netCDF4.pyx":1333
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* if ntypes > 0:
* typeids = <nc_type *>malloc(sizeof(nc_type) * ntypes)
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}
}
- /* "netCDF4/_netCDF4.pyx":1335
+ /* "netCDF4/_netCDF4.pyx":1336
* with nogil:
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if (__pyx_t_3) {
- /* "netCDF4/_netCDF4.pyx":1336
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* ierr = nc_inq_typeids(_grpid, &ntypes, typeids)
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- /* "netCDF4/_netCDF4.pyx":1331
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*/
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- /* "netCDF4/_netCDF4.pyx":1338
+ /* "netCDF4/_netCDF4.pyx":1339
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@@ -8148,24 +8142,24 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_types(PyObject *__pyx_v_group)
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__pyx_t_1 = 0;
- /* "netCDF4/_netCDF4.pyx":1339
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* # create empty dictionary for CompoundType instances.
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@@ -8178,24 +8172,24 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_types(PyObject *__pyx_v_group)
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* vltypes = OrderedDict()
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if (__pyx_t_3) {
- /* "netCDF4/_netCDF4.pyx":1342
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for (__pyx_v_n = 0; __pyx_v_n < __pyx_t_2; __pyx_v_n++) {
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- /* "netCDF4/_netCDF4.pyx":1344
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#endif
/*try:*/ {
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}
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if (__pyx_t_3) {
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__pyx_L38_try_end:;
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*/
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goto __pyx_L43_except_error;
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__pyx_L48_try_end:;
}
- /* "netCDF4/_netCDF4.pyx":1381
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__pyx_L13_continue:;
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*/
free(__pyx_v_typeids);
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*/
}
- /* "netCDF4/_netCDF4.pyx":1383
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__pyx_t_5 = 0;
goto __pyx_L0;
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return __pyx_r;
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*/
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- /* "netCDF4/_netCDF4.pyx":1401
+ /* "netCDF4/_netCDF4.pyx":1402
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goto __pyx_L8;
}
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for (__pyx_v_n = 0; __pyx_v_n < __pyx_t_2; __pyx_v_n++) {
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}
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#endif
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- /* "netCDF4/_netCDF4.pyx":1411
+ /* "netCDF4/_netCDF4.pyx":1412
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}
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{
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*/
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*/
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goto __pyx_L0;
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goto __pyx_L0;
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return __pyx_r;
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int __pyx_t_28;
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#endif
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#endif
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}
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__Pyx_DECREF_SET(__pyx_v_endianness, __pyx_kp_s__14);
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default: break;
}
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*/
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+ /* "netCDF4/_netCDF4.pyx":1504
* endianness = '>'
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__Pyx_XGOTREF(__pyx_t_13);
/*try:*/ {
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__pyx_t_14 = (__pyx_t_3 != 0);
if (__pyx_t_14) {
- /* "netCDF4/_netCDF4.pyx":1506
+ /* "netCDF4/_netCDF4.pyx":1507
* datatype = _nctonptype[xtype]
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*/
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+ __pyx_t_6 = PyNumber_Add(__pyx_v_endianness, __pyx_v_datatype); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1507, __pyx_L36_error)
__Pyx_GOTREF(__pyx_t_6);
__Pyx_DECREF_SET(__pyx_v_datatype, __pyx_t_6);
__pyx_t_6 = 0;
- /* "netCDF4/_netCDF4.pyx":1505
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*/
}
- /* "netCDF4/_netCDF4.pyx":1503
+ /* "netCDF4/_netCDF4.pyx":1504
* endianness = '>'
* # check to see if it is a supported user-defined type.
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@@ -11124,7 +11118,7 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
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__Pyx_XDECREF(__pyx_t_6); __pyx_t_6 = 0;
- /* "netCDF4/_netCDF4.pyx":1507
+ /* "netCDF4/_netCDF4.pyx":1508
* if endianness is not None:
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@@ -11134,12 +11128,12 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
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if (__pyx_t_9) {
__Pyx_AddTraceback("netCDF4._netCDF4._get_vars", __pyx_clineno, __pyx_lineno, __pyx_filename);
- if (__Pyx_GetException(&__pyx_t_6, &__pyx_t_1, &__pyx_t_10) < 0) __PYX_ERR(0, 1507, __pyx_L38_except_error)
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__Pyx_GOTREF(__pyx_t_10);
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* datatype = endianness + datatype
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__pyx_t_14 = ((__pyx_v_xtype == NC_STRING) != 0);
if (__pyx_t_14) {
- /* "netCDF4/_netCDF4.pyx":1509
+ /* "netCDF4/_netCDF4.pyx":1510
* except KeyError:
* if xtype == NC_STRING:
* datatype = str # <<<<<<<<<<<<<<
@@ -11159,7 +11153,7 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
__Pyx_INCREF(((PyObject *)(&PyString_Type)));
__Pyx_XDECREF_SET(__pyx_v_datatype, ((PyObject *)(&PyString_Type)));
- /* "netCDF4/_netCDF4.pyx":1508
+ /* "netCDF4/_netCDF4.pyx":1509
* datatype = endianness + datatype
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@@ -11169,7 +11163,7 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
goto __pyx_L47;
}
- /* "netCDF4/_netCDF4.pyx":1511
+ /* "netCDF4/_netCDF4.pyx":1512
* datatype = str
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@@ -11184,7 +11178,7 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
#endif
/*try:*/ {
- /* "netCDF4/_netCDF4.pyx":1512
+ /* "netCDF4/_netCDF4.pyx":1513
* else:
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@@ -11194,7 +11188,7 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
__pyx_v_ierr = nc_inq_user_type(__pyx_v__grpid, __pyx_v_xtype, __pyx_v_namstring_cmp, NULL, NULL, NULL, (&__pyx_v_classp));
}
- /* "netCDF4/_netCDF4.pyx":1511
+ /* "netCDF4/_netCDF4.pyx":1512
* datatype = str
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@@ -11212,7 +11206,7 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
}
}
- /* "netCDF4/_netCDF4.pyx":1514
+ /* "netCDF4/_netCDF4.pyx":1515
* ierr = nc_inq_user_type(_grpid, xtype, namstring_cmp,
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@@ -11222,7 +11216,7 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
switch (__pyx_v_classp) {
case NC_COMPOUND:
- /* "netCDF4/_netCDF4.pyx":1516
+ /* "netCDF4/_netCDF4.pyx":1517
* if classp == NC_COMPOUND: # a compound type
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__Pyx_XGOTREF(__pyx_t_17);
/*try:*/ {
- /* "netCDF4/_netCDF4.pyx":1517
+ /* "netCDF4/_netCDF4.pyx":1518
* # create CompoundType instance describing this compound type.
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*/
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__pyx_t_18.endian = __pyx_v_endianness;
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__Pyx_XDECREF_SET(__pyx_v_datatype, __pyx_t_7);
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* if classp == NC_COMPOUND: # a compound type
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__Pyx_XDECREF(__pyx_t_7); __pyx_t_7 = 0;
- /* "netCDF4/_netCDF4.pyx":1518
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__Pyx_GOTREF(__pyx_t_5);
__Pyx_GOTREF(__pyx_t_8);
- /* "netCDF4/_netCDF4.pyx":1519
+ /* "netCDF4/_netCDF4.pyx":1520
* datatype = _read_compound(group, xtype, endian=endianness)
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__pyx_t_19 = 0;
- /* "netCDF4/_netCDF4.pyx":1520
+ /* "netCDF4/_netCDF4.pyx":1521
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+ __pyx_t_20 = __Pyx_GetModuleGlobalName(__pyx_n_s_warnings); if (unlikely(!__pyx_t_20)) __PYX_ERR(0, 1521, __pyx_L55_except_error)
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@@ -11320,13 +11314,13 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
}
}
if (!__pyx_t_20) {
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@@ -11334,19 +11328,19 @@ static PyObject *__pyx_f_7netCDF4_8_netCDF4__get_vars(PyObject *__pyx_v_group) {
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{
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__Pyx_DECREF(__pyx_t_19); __pyx_t_19 = 0;
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goto __pyx_L55_except_error;
__pyx_L55_except_error:;
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+ /* "netCDF4/_netCDF4.pyx":1517
* if classp == NC_COMPOUND: # a compound type
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__pyx_L60_try_end:;
}
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*/
break;
- /* "netCDF4/_netCDF4.pyx":1522
+ /* "netCDF4/_netCDF4.pyx":1523
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*/
case NC_VLEN:
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__Pyx_XGOTREF(__pyx_t_15);
/*try:*/ {
- /* "netCDF4/_netCDF4.pyx":1525
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goto __pyx_L65_except_error;
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__pyx_L70_try_end:;
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__pyx_L80_try_end:;
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goto __pyx_L8;
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+ /* "netCDF4/_netCDF4.pyx":1842
* ierr = nc_create(path, NC_WRITE | NC_SHARE | NC_NOCLOBBER | NC_DISKLESS , &grpid)
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__pyx_L23:;
- /* "netCDF4/_netCDF4.pyx":1837
+ /* "netCDF4/_netCDF4.pyx":1838
* ierr = nc_create(path, NC_SHARE | NC_CLOBBER, &grpid)
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goto __pyx_L22;
}
- /* "netCDF4/_netCDF4.pyx":1843
+ /* "netCDF4/_netCDF4.pyx":1844
* ierr = nc_create(path, NC_SHARE | NC_NOCLOBBER | NC_DISKLESS , &grpid)
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}
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- /* "netCDF4/_netCDF4.pyx":1827
+ /* "netCDF4/_netCDF4.pyx":1828
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goto __pyx_L6;
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@@ -13593,7 +13587,7 @@ static int __pyx_pf_7netCDF4_8_netCDF4_7Dataset___init__(struct __pyx_obj_7netCD
__pyx_t_1 = ((__pyx_v_ierr != NC_NOERR) != 0);
if (__pyx_t_1) {
- /* "netCDF4/_netCDF4.pyx":1847
+ /* "netCDF4/_netCDF4.pyx":1848
* raise ValueError("mode must be 'w', 'r', 'a' or 'r+', got '%s'" % mode)
* if ierr != NC_NOERR:
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__Pyx_INCREF(__pyx_t_6);
__Pyx_GIVEREF(__pyx_t_6);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_6);
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*/
}
- /* "netCDF4/_netCDF4.pyx":1849
+ /* "netCDF4/_netCDF4.pyx":1850
* raise IOError((<char *>nc_strerror(ierr)).decode('ascii'))
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*/
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__Pyx_GIVEREF(__pyx_t_6);
__Pyx_GOTREF(__pyx_v_self->data_model);
@@ -13640,7 +13634,7 @@ static int __pyx_pf_7netCDF4_8_netCDF4_7Dataset___init__(struct __pyx_obj_7netCD
__pyx_v_self->data_model = __pyx_t_6;
__pyx_t_6 = 0;
- /* "netCDF4/_netCDF4.pyx":1852
+ /* "netCDF4/_netCDF4.pyx":1853
* # data_model attribute used to be file_format (versions < 1.0.8), retain
* # file_format for backwards compatibility.
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__pyx_v_self->file_format = __pyx_t_6;
__pyx_t_6 = 0;
- /* "netCDF4/_netCDF4.pyx":1853
+ /* "netCDF4/_netCDF4.pyx":1854
* # file_format for backwards compatibility.
* self.file_format = self.data_model
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__Pyx_GIVEREF(__pyx_t_6);
__Pyx_GOTREF(__pyx_v_self->disk_format);
@@ -13670,7 +13664,7 @@ static int __pyx_pf_7netCDF4_8_netCDF4_7Dataset___init__(struct __pyx_obj_7netCD
__pyx_v_self->disk_format = __pyx_t_6;
__pyx_t_6 = 0;
- /* "netCDF4/_netCDF4.pyx":1858
+ /* "netCDF4/_netCDF4.pyx":1859
* #if diskless and self.data_model != 'NETCDF3_CLASSIC' and ncopen:
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*/
__pyx_v_self->_grpid = __pyx_v_grpid;
- /* "netCDF4/_netCDF4.pyx":1859
+ /* "netCDF4/_netCDF4.pyx":1860
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*/
__pyx_v_self->_isopen = 1;
- /* "netCDF4/_netCDF4.pyx":1860
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* self.path = '/' # <<<<<<<<<<<<<<
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__Pyx_DECREF(__pyx_v_self->path);
__pyx_v_self->path = __pyx_kp_s__15;
- /* "netCDF4/_netCDF4.pyx":1861
+ /* "netCDF4/_netCDF4.pyx":1862
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* self.path = '/'
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__Pyx_DECREF(__pyx_v_self->parent);
__pyx_v_self->parent = Py_None;
- /* "netCDF4/_netCDF4.pyx":1862
+ /* "netCDF4/_netCDF4.pyx":1863
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* self.parent = None
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__pyx_v_self->keepweakref = __pyx_v_keepweakref;
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+ /* "netCDF4/_netCDF4.pyx":1865
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@@ -13782,7 +13776,7 @@ static int __pyx_pf_7netCDF4_8_netCDF4_7Dataset___init__(struct __pyx_obj_7netCD
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__pyx_v_self->enumtypes = __pyx_t_8;
__pyx_t_8 = 0;
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__Pyx_GIVEREF(__pyx_t_6);
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@@ -13824,14 +13818,14 @@ static int __pyx_pf_7netCDF4_8_netCDF4_7Dataset___init__(struct __pyx_obj_7netCD
__pyx_v_self->dimensions = __pyx_t_6;
__pyx_t_6 = 0;
- /* "netCDF4/_netCDF4.pyx":1868
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__Pyx_GIVEREF(__pyx_t_6);
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__pyx_v_self->variables = __pyx_t_6;
__pyx_t_6 = 0;
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__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
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__Pyx_GIVEREF(__pyx_v_datatype_name);
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else {
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values[4] = ((PyObject *)__pyx_int_4);
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+ /* "netCDF4/_netCDF4.pyx":2653
* self._grpid = kwargs['id']
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*/
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PyObject* sequence = __pyx_t_1;
@@ -24635,7 +24723,7 @@ static int __pyx_pf_7netCDF4_8_netCDF4_5Group___init__(struct __pyx_obj_7netCDF4
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if (size > 3) __Pyx_RaiseTooManyValuesError(3);
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@@ -24651,17 +24739,17 @@ static int __pyx_pf_7netCDF4_8_netCDF4_5Group___init__(struct __pyx_obj_7netCDF4
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__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
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__pyx_v_self->__pyx_base.enumtypes = __pyx_t_2;
__pyx_t_2 = 0;
- /* "netCDF4/_netCDF4.pyx":2642
+ /* "netCDF4/_netCDF4.pyx":2655
* self.cmptypes, self.vltypes, self.enumtypes = _get_types(self)
* # get dimensions in this Group.
* self.dimensions = _get_dims(self) # <<<<<<<<<<<<<<
* # get variables in this Group.
* self.variables = _get_vars(self)
*/
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__Pyx_GOTREF(__pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
__Pyx_GOTREF(__pyx_v_self->__pyx_base.dimensions);
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__pyx_v_self->__pyx_base.dimensions = __pyx_t_1;
__pyx_t_1 = 0;
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+ /* "netCDF4/_netCDF4.pyx":2657
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__Pyx_GOTREF(__pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
__Pyx_GOTREF(__pyx_v_self->__pyx_base.variables);
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__pyx_v_self->__pyx_base.variables = __pyx_t_1;
__pyx_t_1 = 0;
- /* "netCDF4/_netCDF4.pyx":2646
+ /* "netCDF4/_netCDF4.pyx":2659
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__Pyx_GOTREF(__pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
__Pyx_GOTREF(__pyx_v_self->__pyx_base.groups);
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__pyx_v_self->__pyx_base.groups = __pyx_t_1;
__pyx_t_1 = 0;
- /* "netCDF4/_netCDF4.pyx":2637
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goto __pyx_L3;
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+ /* "netCDF4/_netCDF4.pyx":2661
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- /* "netCDF4/_netCDF4.pyx":2651
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*/
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@@ -24851,10 +24939,10 @@ static int __pyx_pf_7netCDF4_8_netCDF4_5Group___init__(struct __pyx_obj_7netCDF4
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__pyx_v_self->__pyx_base.cmptypes = __pyx_t_1;
__pyx_t_1 = 0;
- /* "netCDF4/_netCDF4.pyx":2654
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return __pyx_r;
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if (__pyx_t_1) {
- /* "netCDF4/_netCDF4.pyx":2820
+ /* "netCDF4/_netCDF4.pyx":2833
* ierr = nc_inq_unlimdims(self._grpid, &numunlimdims, NULL)
* if ierr != NC_NOERR:
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii')) # <<<<<<<<<<<<<<
@@ -27108,22 +27196,22 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
* return False
*/
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+ __pyx_t_3 = __Pyx_PyObject_Call(__pyx_builtin_RuntimeError, __pyx_t_4, NULL); if (unlikely(!__pyx_t_3)) __PYX_ERR(0, 2833, __pyx_L1_error)
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- /* "netCDF4/_netCDF4.pyx":2819
+ /* "netCDF4/_netCDF4.pyx":2832
* if self._data_model == 'NETCDF4':
* ierr = nc_inq_unlimdims(self._grpid, &numunlimdims, NULL)
* if ierr != NC_NOERR: # <<<<<<<<<<<<<<
@@ -27132,7 +27220,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
*/
}
- /* "netCDF4/_netCDF4.pyx":2821
+ /* "netCDF4/_netCDF4.pyx":2834
* if ierr != NC_NOERR:
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
* if numunlimdims == 0: # <<<<<<<<<<<<<<
@@ -27142,7 +27230,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
__pyx_t_1 = ((__pyx_v_numunlimdims == 0) != 0);
if (__pyx_t_1) {
- /* "netCDF4/_netCDF4.pyx":2822
+ /* "netCDF4/_netCDF4.pyx":2835
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
* if numunlimdims == 0:
* return False # <<<<<<<<<<<<<<
@@ -27154,7 +27242,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
__pyx_r = Py_False;
goto __pyx_L0;
- /* "netCDF4/_netCDF4.pyx":2821
+ /* "netCDF4/_netCDF4.pyx":2834
* if ierr != NC_NOERR:
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
* if numunlimdims == 0: # <<<<<<<<<<<<<<
@@ -27163,7 +27251,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
*/
}
- /* "netCDF4/_netCDF4.pyx":2824
+ /* "netCDF4/_netCDF4.pyx":2837
* return False
* else:
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@@ -27173,7 +27261,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
/*else*/ {
__pyx_v_unlimdimids = ((int *)malloc(((sizeof(int)) * __pyx_v_numunlimdims)));
- /* "netCDF4/_netCDF4.pyx":2825
+ /* "netCDF4/_netCDF4.pyx":2838
* else:
* unlimdimids = <int *>malloc(sizeof(int) * numunlimdims)
* dimid = self._dimid # <<<<<<<<<<<<<<
@@ -27183,7 +27271,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
__pyx_t_5 = __pyx_v_self->_dimid;
__pyx_v_dimid = __pyx_t_5;
- /* "netCDF4/_netCDF4.pyx":2826
+ /* "netCDF4/_netCDF4.pyx":2839
* unlimdimids = <int *>malloc(sizeof(int) * numunlimdims)
* dimid = self._dimid
* with nogil: # <<<<<<<<<<<<<<
@@ -27197,7 +27285,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
#endif
/*try:*/ {
- /* "netCDF4/_netCDF4.pyx":2827
+ /* "netCDF4/_netCDF4.pyx":2840
* dimid = self._dimid
* with nogil:
* ierr = nc_inq_unlimdims(self._grpid, &numunlimdims, unlimdimids) # <<<<<<<<<<<<<<
@@ -27207,7 +27295,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
__pyx_v_ierr = nc_inq_unlimdims(__pyx_v_self->_grpid, (&__pyx_v_numunlimdims), __pyx_v_unlimdimids);
}
- /* "netCDF4/_netCDF4.pyx":2826
+ /* "netCDF4/_netCDF4.pyx":2839
* unlimdimids = <int *>malloc(sizeof(int) * numunlimdims)
* dimid = self._dimid
* with nogil: # <<<<<<<<<<<<<<
@@ -27225,7 +27313,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
}
}
- /* "netCDF4/_netCDF4.pyx":2828
+ /* "netCDF4/_netCDF4.pyx":2841
* with nogil:
* ierr = nc_inq_unlimdims(self._grpid, &numunlimdims, unlimdimids)
* if ierr != NC_NOERR: # <<<<<<<<<<<<<<
@@ -27235,7 +27323,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
__pyx_t_1 = ((__pyx_v_ierr != NC_NOERR) != 0);
if (__pyx_t_1) {
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+ /* "netCDF4/_netCDF4.pyx":2842
* ierr = nc_inq_unlimdims(self._grpid, &numunlimdims, unlimdimids)
* if ierr != NC_NOERR:
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii')) # <<<<<<<<<<<<<<
@@ -27243,22 +27331,22 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
* for n from 0 <= n < numunlimdims:
*/
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* if ierr != NC_NOERR: # <<<<<<<<<<<<<<
@@ -27267,19 +27355,19 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
*/
}
- /* "netCDF4/_netCDF4.pyx":2830
+ /* "netCDF4/_netCDF4.pyx":2843
* if ierr != NC_NOERR:
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
* unlimdim_ids = [] # <<<<<<<<<<<<<<
* for n from 0 <= n < numunlimdims:
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*/
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__pyx_v_unlimdim_ids = ((PyObject*)__pyx_t_3);
__pyx_t_3 = 0;
- /* "netCDF4/_netCDF4.pyx":2831
+ /* "netCDF4/_netCDF4.pyx":2844
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
* unlimdim_ids = []
* for n from 0 <= n < numunlimdims: # <<<<<<<<<<<<<<
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for (__pyx_v_n = 0; __pyx_v_n < __pyx_t_5; __pyx_v_n++) {
- /* "netCDF4/_netCDF4.pyx":2832
+ /* "netCDF4/_netCDF4.pyx":2845
* unlimdim_ids = []
* for n from 0 <= n < numunlimdims:
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* free(unlimdimids)
* if dimid in unlimdim_ids:
*/
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+ /* "netCDF4/_netCDF4.pyx":2846
* for n from 0 <= n < numunlimdims:
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*/
free(__pyx_v_unlimdimids);
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+ /* "netCDF4/_netCDF4.pyx":2847
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+ /* "netCDF4/_netCDF4.pyx":2848
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__pyx_r = Py_True;
goto __pyx_L0;
- /* "netCDF4/_netCDF4.pyx":2834
+ /* "netCDF4/_netCDF4.pyx":2847
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*/
}
- /* "netCDF4/_netCDF4.pyx":2837
+ /* "netCDF4/_netCDF4.pyx":2850
* return True
* else:
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@@ -27361,7 +27449,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
}
}
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+ /* "netCDF4/_netCDF4.pyx":2830
* cdef int ierr, n, numunlimdims, ndims, nvars, ngatts, xdimid
* cdef int *unlimdimids
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@@ -27370,7 +27458,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_9Dimension_12isunlimited(struct __p
*/
}
- /* "netCDF4/_netCDF4.pyx":2840
+ /* "netCDF4/_netCDF4.pyx":2853
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#endif
/*try:*/ {
- /* "netCDF4/_netCDF4.pyx":2841
+ /* "netCDF4/_netCDF4.pyx":2854
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}
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}
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if (__pyx_t_7) {
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__pyx_r = Py_True;
goto __pyx_L0;
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return __pyx_r;
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goto __pyx_L39;
}
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*/
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goto __pyx_L70;
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}
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#endif
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* ierr = nc_inq_var_deflate(self._grpid, self._varid, &ishuffle, &ideflate, &ideflate_level)
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- __pyx_t_1 = __Pyx_decode_c_string(__pyx_t_4, 0, strlen(__pyx_t_4), NULL, NULL, PyUnicode_DecodeASCII); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 3532, __pyx_L1_error)
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- __pyx_t_5 = PyTuple_New(1); if (unlikely(!__pyx_t_5)) __PYX_ERR(0, 3532, __pyx_L1_error)
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__Pyx_GIVEREF(__pyx_t_1);
PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_t_1);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
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__Pyx_GOTREF(__pyx_t_1);
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__Pyx_Raise(__pyx_t_1, 0, 0, 0);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
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* with nogil:
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@@ -35999,7 +35993,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_26filters(struct __pyx_ob
*/
}
- /* "netCDF4/_netCDF4.pyx":3533
+ /* "netCDF4/_netCDF4.pyx":3546
* if ierr != NC_NOERR:
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* with nogil: # <<<<<<<<<<<<<<
@@ -36013,7 +36007,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_26filters(struct __pyx_ob
#endif
/*try:*/ {
- /* "netCDF4/_netCDF4.pyx":3534
+ /* "netCDF4/_netCDF4.pyx":3547
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
* with nogil:
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@@ -36023,7 +36017,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_26filters(struct __pyx_ob
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}
- /* "netCDF4/_netCDF4.pyx":3533
+ /* "netCDF4/_netCDF4.pyx":3546
* if ierr != NC_NOERR:
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* with nogil: # <<<<<<<<<<<<<<
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}
}
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* with nogil:
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__pyx_t_3 = ((__pyx_v_ierr != NC_NOERR) != 0);
if (__pyx_t_3) {
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+ /* "netCDF4/_netCDF4.pyx":3549
* ierr = nc_inq_var_fletcher32(self._grpid, self._varid, &ifletcher32)
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- __pyx_t_1 = __Pyx_decode_c_string(__pyx_t_4, 0, strlen(__pyx_t_4), NULL, NULL, PyUnicode_DecodeASCII); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 3536, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_t_5);
__Pyx_INCREF(__pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_t_1);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
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__Pyx_GOTREF(__pyx_t_1);
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__Pyx_Raise(__pyx_t_1, 0, 0, 0);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
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@@ -36083,7 +36077,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_26filters(struct __pyx_ob
*/
}
- /* "netCDF4/_netCDF4.pyx":3537
+ /* "netCDF4/_netCDF4.pyx":3550
* if ierr != NC_NOERR:
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* if ideflate: # <<<<<<<<<<<<<<
@@ -36093,28 +36087,28 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_26filters(struct __pyx_ob
__pyx_t_3 = (__pyx_v_ideflate != 0);
if (__pyx_t_3) {
- /* "netCDF4/_netCDF4.pyx":3538
+ /* "netCDF4/_netCDF4.pyx":3551
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
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- if (unlikely(PyDict_SetItem(__pyx_v_filtdict, __pyx_n_s_zlib, Py_True) < 0)) __PYX_ERR(0, 3538, __pyx_L1_error)
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*/
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- /* "netCDF4/_netCDF4.pyx":3540
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* filtdict['zlib']=True
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@@ -36133,16 +36127,16 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_26filters(struct __pyx_ob
__pyx_t_3 = (__pyx_v_ishuffle != 0);
if (__pyx_t_3) {
- /* "netCDF4/_netCDF4.pyx":3541
+ /* "netCDF4/_netCDF4.pyx":3554
* filtdict['complevel']=ideflate_level
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* if ifletcher32:
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*/
- if (unlikely(PyDict_SetItem(__pyx_v_filtdict, __pyx_n_s_shuffle, Py_True) < 0)) __PYX_ERR(0, 3541, __pyx_L1_error)
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- /* "netCDF4/_netCDF4.pyx":3540
+ /* "netCDF4/_netCDF4.pyx":3553
* filtdict['zlib']=True
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* if ishuffle: # <<<<<<<<<<<<<<
@@ -36151,7 +36145,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_26filters(struct __pyx_ob
*/
}
- /* "netCDF4/_netCDF4.pyx":3542
+ /* "netCDF4/_netCDF4.pyx":3555
* if ishuffle:
* filtdict['shuffle']=True
* if ifletcher32: # <<<<<<<<<<<<<<
@@ -36161,16 +36155,16 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_26filters(struct __pyx_ob
__pyx_t_3 = (__pyx_v_ifletcher32 != 0);
if (__pyx_t_3) {
- /* "netCDF4/_netCDF4.pyx":3543
+ /* "netCDF4/_netCDF4.pyx":3556
* filtdict['shuffle']=True
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*
*/
- if (unlikely(PyDict_SetItem(__pyx_v_filtdict, __pyx_n_s_fletcher32, Py_True) < 0)) __PYX_ERR(0, 3543, __pyx_L1_error)
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- /* "netCDF4/_netCDF4.pyx":3542
+ /* "netCDF4/_netCDF4.pyx":3555
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*/
}
- /* "netCDF4/_netCDF4.pyx":3544
+ /* "netCDF4/_netCDF4.pyx":3557
* if ifletcher32:
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__pyx_r = __pyx_v_filtdict;
goto __pyx_L0;
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+ /* "netCDF4/_netCDF4.pyx":3534
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return __pyx_r;
}
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* return filtdict
*
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PyObject *__pyx_t_5 = NULL;
__Pyx_RefNannySetupContext("endian", 0);
- /* "netCDF4/_netCDF4.pyx":3552
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*/
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+ __pyx_t_1 = __Pyx_PyObject_GetAttrStr(__pyx_v_self->_grp, __pyx_n_s_data_model); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 3565, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_1);
- __pyx_t_3 = (__Pyx_PyString_Equals(__pyx_t_1, __pyx_n_s_NETCDF4_CLASSIC, Py_NE)); if (unlikely(__pyx_t_3 < 0)) __PYX_ERR(0, 3552, __pyx_L1_error)
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if (__pyx_t_3) {
} else {
__pyx_t_2 = __pyx_t_3;
goto __pyx_L4_bool_binop_done;
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__pyx_L4_bool_binop_done:;
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if (__pyx_t_3) {
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__pyx_r = __pyx_n_s_native;
goto __pyx_L0;
- /* "netCDF4/_netCDF4.pyx":3552
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*/
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#endif
/*try:*/ {
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}
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@@ -36331,7 +36325,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_28endian(struct __pyx_obj
}
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if (__pyx_t_3) {
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__Pyx_GIVEREF(__pyx_t_1);
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*/
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* if iendian == NC_ENDIAN_LITTLE: # <<<<<<<<<<<<<<
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switch (__pyx_v_iendian) {
case NC_ENDIAN_LITTLE:
- /* "netCDF4/_netCDF4.pyx":3559
+ /* "netCDF4/_netCDF4.pyx":3572
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
* if iendian == NC_ENDIAN_LITTLE:
* return 'little' # <<<<<<<<<<<<<<
@@ -36395,7 +36389,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_28endian(struct __pyx_obj
__pyx_r = __pyx_n_s_little;
goto __pyx_L0;
- /* "netCDF4/_netCDF4.pyx":3558
+ /* "netCDF4/_netCDF4.pyx":3571
* if ierr != NC_NOERR:
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
* if iendian == NC_ENDIAN_LITTLE: # <<<<<<<<<<<<<<
@@ -36404,7 +36398,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_28endian(struct __pyx_obj
*/
break;
- /* "netCDF4/_netCDF4.pyx":3560
+ /* "netCDF4/_netCDF4.pyx":3573
* if iendian == NC_ENDIAN_LITTLE:
* return 'little'
* elif iendian == NC_ENDIAN_BIG: # <<<<<<<<<<<<<<
@@ -36413,7 +36407,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_28endian(struct __pyx_obj
*/
case NC_ENDIAN_BIG:
- /* "netCDF4/_netCDF4.pyx":3561
+ /* "netCDF4/_netCDF4.pyx":3574
* return 'little'
* elif iendian == NC_ENDIAN_BIG:
* return 'big' # <<<<<<<<<<<<<<
@@ -36425,7 +36419,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_28endian(struct __pyx_obj
__pyx_r = __pyx_n_s_big;
goto __pyx_L0;
- /* "netCDF4/_netCDF4.pyx":3560
+ /* "netCDF4/_netCDF4.pyx":3573
* if iendian == NC_ENDIAN_LITTLE:
* return 'little'
* elif iendian == NC_ENDIAN_BIG: # <<<<<<<<<<<<<<
@@ -36435,7 +36429,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_28endian(struct __pyx_obj
break;
default:
- /* "netCDF4/_netCDF4.pyx":3563
+ /* "netCDF4/_netCDF4.pyx":3576
* return 'big'
* else:
* return 'native' # <<<<<<<<<<<<<<
@@ -36449,7 +36443,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_28endian(struct __pyx_obj
break;
}
- /* "netCDF4/_netCDF4.pyx":3546
+ /* "netCDF4/_netCDF4.pyx":3559
* return filtdict
*
* def endian(self): # <<<<<<<<<<<<<<
@@ -36469,7 +36463,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_28endian(struct __pyx_obj
return __pyx_r;
}
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+/* "netCDF4/_netCDF4.pyx":3578
* return 'native'
*
* def chunking(self): # <<<<<<<<<<<<<<
@@ -36509,22 +36503,22 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
int __pyx_t_7;
__Pyx_RefNannySetupContext("chunking", 0);
- /* "netCDF4/_netCDF4.pyx":3575
+ /* "netCDF4/_netCDF4.pyx":3588
* cdef int ierr, icontiguous, ndims
* cdef size_t *chunksizesp
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- __pyx_t_1 = __Pyx_PyObject_GetAttrStr(__pyx_v_self->_grp, __pyx_n_s_data_model); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 3575, __pyx_L1_error)
+ __pyx_t_1 = __Pyx_PyObject_GetAttrStr(__pyx_v_self->_grp, __pyx_n_s_data_model); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 3588, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_1);
- __pyx_t_3 = (__Pyx_PyString_Equals(__pyx_t_1, __pyx_n_s_NETCDF4_CLASSIC, Py_NE)); if (unlikely(__pyx_t_3 < 0)) __PYX_ERR(0, 3575, __pyx_L1_error)
+ __pyx_t_3 = (__Pyx_PyString_Equals(__pyx_t_1, __pyx_n_s_NETCDF4_CLASSIC, Py_NE)); if (unlikely(__pyx_t_3 < 0)) __PYX_ERR(0, 3588, __pyx_L1_error)
if (__pyx_t_3) {
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__pyx_t_2 = __pyx_t_3;
goto __pyx_L4_bool_binop_done;
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- __pyx_t_3 = (__Pyx_PyString_Equals(__pyx_t_1, __pyx_n_s_NETCDF4, Py_NE)); if (unlikely(__pyx_t_3 < 0)) __PYX_ERR(0, 3575, __pyx_L1_error)
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__pyx_L4_bool_binop_done:;
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@@ -36536,17 +36530,17 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
goto __pyx_L0;
}
- /* "netCDF4/_netCDF4.pyx":3576
+ /* "netCDF4/_netCDF4.pyx":3589
* cdef size_t *chunksizesp
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* ndims = self.ndim # <<<<<<<<<<<<<<
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__pyx_v_ndims = __pyx_t_4;
- /* "netCDF4/_netCDF4.pyx":3577
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* if self._grp.data_model not in ['NETCDF4_CLASSIC','NETCDF4']: return None
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@@ -36555,7 +36549,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
*/
__pyx_v_chunksizesp = ((size_t *)malloc(((sizeof(size_t)) * __pyx_v_ndims)));
- /* "netCDF4/_netCDF4.pyx":3578
+ /* "netCDF4/_netCDF4.pyx":3591
* ndims = self.ndim
* chunksizesp = <size_t *>malloc(sizeof(size_t) * ndims)
* with nogil: # <<<<<<<<<<<<<<
@@ -36569,7 +36563,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
#endif
/*try:*/ {
- /* "netCDF4/_netCDF4.pyx":3579
+ /* "netCDF4/_netCDF4.pyx":3592
* chunksizesp = <size_t *>malloc(sizeof(size_t) * ndims)
* with nogil:
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@@ -36579,7 +36573,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
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}
- /* "netCDF4/_netCDF4.pyx":3578
+ /* "netCDF4/_netCDF4.pyx":3591
* ndims = self.ndim
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* with nogil: # <<<<<<<<<<<<<<
@@ -36597,7 +36591,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
}
}
- /* "netCDF4/_netCDF4.pyx":3580
+ /* "netCDF4/_netCDF4.pyx":3593
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@@ -36607,7 +36601,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
__pyx_t_3 = ((__pyx_v_ierr != NC_NOERR) != 0);
if (__pyx_t_3) {
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@@ -36615,22 +36609,22 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
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__Pyx_GOTREF(__pyx_t_1);
- __pyx_t_6 = PyTuple_New(1); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 3581, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_t_6);
__Pyx_INCREF(__pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_t_1);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
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+ __pyx_t_1 = __Pyx_PyObject_Call(__pyx_builtin_RuntimeError, __pyx_t_6, NULL); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 3594, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_1);
__Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
__Pyx_Raise(__pyx_t_1, 0, 0, 0);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
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* with nogil:
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* if ierr != NC_NOERR: # <<<<<<<<<<<<<<
@@ -36639,19 +36633,19 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
*/
}
- /* "netCDF4/_netCDF4.pyx":3582
+ /* "netCDF4/_netCDF4.pyx":3595
* if ierr != NC_NOERR:
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* chunksizes=[] # <<<<<<<<<<<<<<
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*/
- __pyx_t_1 = PyList_New(0); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 3582, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_t_1);
__pyx_v_chunksizes = ((PyObject*)__pyx_t_1);
__pyx_t_1 = 0;
- /* "netCDF4/_netCDF4.pyx":3583
+ /* "netCDF4/_netCDF4.pyx":3596
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
* chunksizes=[]
* for n from 0 <= n < ndims: # <<<<<<<<<<<<<<
@@ -36661,20 +36655,20 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
__pyx_t_4 = __pyx_v_ndims;
for (__pyx_v_n = 0; __pyx_v_n < __pyx_t_4; __pyx_v_n++) {
- /* "netCDF4/_netCDF4.pyx":3584
+ /* "netCDF4/_netCDF4.pyx":3597
* chunksizes=[]
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- __pyx_t_1 = __Pyx_PyInt_FromSize_t((__pyx_v_chunksizesp[__pyx_v_n])); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 3584, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_t_1);
- __pyx_t_7 = __Pyx_PyList_Append(__pyx_v_chunksizes, __pyx_t_1); if (unlikely(__pyx_t_7 == -1)) __PYX_ERR(0, 3584, __pyx_L1_error)
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__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
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- /* "netCDF4/_netCDF4.pyx":3585
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* for n from 0 <= n < ndims:
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@@ -36683,7 +36677,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
*/
free(__pyx_v_chunksizesp);
- /* "netCDF4/_netCDF4.pyx":3586
+ /* "netCDF4/_netCDF4.pyx":3599
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__pyx_t_3 = (__pyx_v_icontiguous != 0);
if (__pyx_t_3) {
- /* "netCDF4/_netCDF4.pyx":3587
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__pyx_r = __pyx_n_s_contiguous;
goto __pyx_L0;
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*/
}
- /* "netCDF4/_netCDF4.pyx":3589
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@@ -36728,7 +36722,7 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_30chunking(struct __pyx_o
goto __pyx_L0;
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* return 'native'
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return __pyx_r;
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* return chunksizes
*
* def get_var_chunk_cache(self): # <<<<<<<<<<<<<<
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PyObject *__pyx_t_5 = NULL;
__Pyx_RefNannySetupContext("get_var_chunk_cache", 0);
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* cdef float preemptionp
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#endif
/*try:*/ {
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+ /* "netCDF4/_netCDF4.pyx":3615
* cdef float preemptionp
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}
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}
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__pyx_t_1 = ((__pyx_v_ierr != NC_NOERR) != 0);
if (__pyx_t_1) {
- /* "netCDF4/_netCDF4.pyx":3605
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goto __pyx_L0;
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return __pyx_r;
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@@ -37094,17 +37088,17 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_34set_var_chunk_cache(str
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__pyx_t_4 = 0;
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goto __pyx_L5;
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goto __pyx_L6;
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goto __pyx_L35;
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__Pyx_XDECREF_SET(__pyx_v_fval, __pyx_t_7);
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__Pyx_XGOTREF(__pyx_t_13);
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@@ -42246,19 +42091,19 @@ static PyObject *__pyx_pf_7netCDF4_8_netCDF4_8Variable_46_toma(struct __pyx_obj_
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__pyx_v_fvalisnan = __pyx_t_7;
__pyx_t_7 = 0;
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* fval = numpy.array(self._FillValue, self.dtype)
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__Pyx_XDECREF(__pyx_t_7); __pyx_t_7 = 0;
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__pyx_L45_try_end:;
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__pyx_t_2 = 0;
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+ /* "netCDF4/_netCDF4.pyx":3877
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goto __pyx_L48;
}
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+ /* "netCDF4/_netCDF4.pyx":3879
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}
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__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
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__pyx_t_2 = 0;
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goto __pyx_L48;
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}
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__pyx_t_10 = (__pyx_t_9 != 0);
if (__pyx_t_10) {
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__pyx_t_9 = (__pyx_t_10 != 0);
if (__pyx_t_9) {
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__Pyx_DECREF_SET(__pyx_v_fill_value, __pyx_v_fval);
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*/
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goto __pyx_L37;
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#endif
/*try:*/ {
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+ /* "netCDF4/_netCDF4.pyx":3891
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if (__pyx_t_15) {
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goto __pyx_L40;
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__pyx_t_1 = 0;
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}
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__Pyx_GIVEREF(__pyx_v_datatype);
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__pyx_v_dt = __pyx_t_6;
__pyx_t_6 = 0;
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* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
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goto __pyx_L0;
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*/
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if (__pyx_t_6) {
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- __pyx_tuple__9 = PyTuple_Pack(1, __pyx_n_s_i4); if (unlikely(!__pyx_tuple__9)) __PYX_ERR(0, 1259, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__9);
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__Pyx_GOTREF(__pyx_slice__10);
__Pyx_GIVEREF(__pyx_slice__10);
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+ /* "netCDF4/_netCDF4.pyx":1310
* xtype = _find_cmptype(grp,value_arr.dtype)
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__Pyx_GOTREF(__pyx_slice__11);
__Pyx_GIVEREF(__pyx_slice__11);
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* raise TypeError, 'illegal data type for attribute, must be one of %s, got %s' % (_supportedtypes, value_arr.dtype.str[1:])
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__Pyx_GOTREF(__pyx_slice__12);
__Pyx_GIVEREF(__pyx_slice__12);
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+ /* "netCDF4/_netCDF4.pyx":1888
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*/
- __pyx_tuple__16 = PyTuple_Pack(1, __pyx_kp_s__15); if (unlikely(!__pyx_tuple__16)) __PYX_ERR(0, 1887, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__16);
__Pyx_GIVEREF(__pyx_tuple__16);
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+ /* "netCDF4/_netCDF4.pyx":1946
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__Pyx_GOTREF(__pyx_tuple__17);
__Pyx_GIVEREF(__pyx_tuple__17);
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+ /* "netCDF4/_netCDF4.pyx":1947
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__Pyx_GOTREF(__pyx_tuple__19);
__Pyx_GIVEREF(__pyx_tuple__19);
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+ /* "netCDF4/_netCDF4.pyx":1948
* .replace("u'",""))\
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__Pyx_GOTREF(__pyx_tuple__22);
__Pyx_GIVEREF(__pyx_tuple__22);
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__Pyx_GOTREF(__pyx_tuple__25);
__Pyx_GIVEREF(__pyx_tuple__25);
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+ /* "netCDF4/_netCDF4.pyx":1992
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__Pyx_GOTREF(__pyx_tuple__26);
__Pyx_GIVEREF(__pyx_tuple__26);
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+ /* "netCDF4/_netCDF4.pyx":2309
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- __pyx_tuple__27 = PyTuple_Pack(1, __pyx_kp_s__15); if (unlikely(!__pyx_tuple__27)) __PYX_ERR(0, 2308, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__27);
__Pyx_GIVEREF(__pyx_tuple__27);
- /* "netCDF4/_netCDF4.pyx":2406
+ /* "netCDF4/_netCDF4.pyx":2407
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*/
- __pyx_tuple__29 = PyTuple_Pack(1, __pyx_n_s__28); if (unlikely(!__pyx_tuple__29)) __PYX_ERR(0, 2406, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__29);
__Pyx_GIVEREF(__pyx_tuple__29);
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+ /* "netCDF4/_netCDF4.pyx":2417
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- __pyx_tuple__30 = PyTuple_Pack(1, __pyx_n_s__28); if (unlikely(!__pyx_tuple__30)) __PYX_ERR(0, 2416, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__30);
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- __pyx_tuple__31 = PyTuple_Pack(1, __pyx_n_s__28); if (unlikely(!__pyx_tuple__31)) __PYX_ERR(0, 2416, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__31);
__Pyx_GIVEREF(__pyx_tuple__31);
- /* "netCDF4/_netCDF4.pyx":2666
+ /* "netCDF4/_netCDF4.pyx":2679
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__Pyx_GOTREF(__pyx_tuple__32);
__Pyx_GIVEREF(__pyx_tuple__32);
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+ /* "netCDF4/_netCDF4.pyx":2696
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*
*/
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__Pyx_GOTREF(__pyx_tuple__33);
__Pyx_GIVEREF(__pyx_tuple__33);
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+ /* "netCDF4/_netCDF4.pyx":3118
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__Pyx_GOTREF(__pyx_slice__39);
__Pyx_GIVEREF(__pyx_slice__39);
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+ /* "netCDF4/_netCDF4.pyx":3132
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+ /* "netCDF4/_netCDF4.pyx":3172
* # of vars are created. This change only lasts as long as file is
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__Pyx_GOTREF(__pyx_tuple__41);
__Pyx_GIVEREF(__pyx_tuple__41);
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__Pyx_GOTREF(__pyx_tuple__42);
__Pyx_GIVEREF(__pyx_tuple__42);
- /* "netCDF4/_netCDF4.pyx":3209
+ /* "netCDF4/_netCDF4.pyx":3222
* if len(chunksizes) != len(dimensions):
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- __pyx_tuple__43 = PyTuple_Pack(1, __pyx_kp_s_chunksizes_must_be_a_sequence_wi); if (unlikely(!__pyx_tuple__43)) __PYX_ERR(0, 3209, __pyx_L1_error)
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+ /* "netCDF4/_netCDF4.pyx":3273
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__Pyx_GOTREF(__pyx_tuple__44);
__Pyx_GIVEREF(__pyx_tuple__44);
- /* "netCDF4/_netCDF4.pyx":3264
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* else:
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__Pyx_GOTREF(__pyx_tuple__45);
__Pyx_GIVEREF(__pyx_tuple__45);
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__Pyx_GOTREF(__pyx_slice__46);
__Pyx_GIVEREF(__pyx_slice__46);
- /* "netCDF4/_netCDF4.pyx":3347
+ /* "netCDF4/_netCDF4.pyx":3360
* except AttributeError:
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__Pyx_GOTREF(__pyx_slice__47);
__Pyx_GIVEREF(__pyx_slice__47);
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+ /* "netCDF4/_netCDF4.pyx":3415
* return self._getname()
* def __set__(self,value):
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*
* property datatype:
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- __pyx_tuple__48 = PyTuple_Pack(1, __pyx_kp_s_name_cannot_be_altered); if (unlikely(!__pyx_tuple__48)) __PYX_ERR(0, 3402, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__48);
__Pyx_GIVEREF(__pyx_tuple__48);
- /* "netCDF4/_netCDF4.pyx":3428
+ /* "netCDF4/_netCDF4.pyx":3441
* return shape
* def __set__(self,value):
* raise AttributeError("shape cannot be altered") # <<<<<<<<<<<<<<
*
* property size:
*/
- __pyx_tuple__49 = PyTuple_Pack(1, __pyx_kp_s_shape_cannot_be_altered); if (unlikely(!__pyx_tuple__49)) __PYX_ERR(0, 3428, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__49);
__Pyx_GIVEREF(__pyx_tuple__49);
- /* "netCDF4/_netCDF4.pyx":3440
+ /* "netCDF4/_netCDF4.pyx":3453
* return self._getdims()
* def __set__(self,value):
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*
*
*/
- __pyx_tuple__50 = PyTuple_Pack(1, __pyx_kp_s_dimensions_cannot_be_altered); if (unlikely(!__pyx_tuple__50)) __PYX_ERR(0, 3440, __pyx_L1_error)
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- * value = numpy.array(value, self.dtype).byteswap(True) # <<<<<<<<<<<<<<
- * else:
- * value = numpy.array(value, self.dtype)
+ /* "netCDF4/_netCDF4.pyx":3680
+ * # (the same as the data)
+ * value = numpy.array(value, self.dtype)
+ * if not value.dtype.isnative: value.byteswap(True) # <<<<<<<<<<<<<<
+ * self.setncattr(name, value)
+ * elif not name.endswith('__'):
*/
- __pyx_tuple__51 = PyTuple_Pack(1, Py_True); if (unlikely(!__pyx_tuple__51)) __PYX_ERR(0, 3665, __pyx_L1_error)
+ __pyx_tuple__51 = PyTuple_Pack(1, Py_True); if (unlikely(!__pyx_tuple__51)) __PYX_ERR(0, 3680, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__51);
__Pyx_GIVEREF(__pyx_tuple__51);
- /* "netCDF4/_netCDF4.pyx":3669
- * value = numpy.array(value, self.dtype)
+ /* "netCDF4/_netCDF4.pyx":3682
+ * if not value.dtype.isnative: value.byteswap(True)
* self.setncattr(name, value)
* elif not name.endswith('__'): # <<<<<<<<<<<<<<
* if hasattr(self,name):
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*/
- __pyx_tuple__52 = PyTuple_Pack(1, __pyx_n_s__28); if (unlikely(!__pyx_tuple__52)) __PYX_ERR(0, 3669, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__52);
__Pyx_GIVEREF(__pyx_tuple__52);
- /* "netCDF4/_netCDF4.pyx":3679
+ /* "netCDF4/_netCDF4.pyx":3692
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* if name.startswith('__') and name.endswith('__'): # <<<<<<<<<<<<<<
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*/
- __pyx_tuple__53 = PyTuple_Pack(1, __pyx_n_s__28); if (unlikely(!__pyx_tuple__53)) __PYX_ERR(0, 3679, __pyx_L1_error)
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- __pyx_tuple__54 = PyTuple_Pack(1, __pyx_n_s__28); if (unlikely(!__pyx_tuple__54)) __PYX_ERR(0, 3679, __pyx_L1_error)
+ __pyx_tuple__54 = PyTuple_Pack(1, __pyx_n_s__28); if (unlikely(!__pyx_tuple__54)) __PYX_ERR(0, 3692, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__54);
__Pyx_GIVEREF(__pyx_tuple__54);
- /* "netCDF4/_netCDF4.pyx":3727
+ /* "netCDF4/_netCDF4.pyx":3740
* # The convention used is that for those cases,
* # put_ind for this dimension is set to -1 by _StartCountStride.
* squeeze = data.ndim * [slice(None),] # <<<<<<<<<<<<<<
* for i,n in enumerate(put_ind.shape[:-1]):
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- __pyx_slice__55 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_slice__55)) __PYX_ERR(0, 3727, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_slice__55);
__Pyx_GIVEREF(__pyx_slice__55);
- /* "netCDF4/_netCDF4.pyx":3728
+ /* "netCDF4/_netCDF4.pyx":3741
* # put_ind for this dimension is set to -1 by _StartCountStride.
* squeeze = data.ndim * [slice(None),]
* for i,n in enumerate(put_ind.shape[:-1]): # <<<<<<<<<<<<<<
* if n == 1 and put_ind[...,i].ravel()[0] == -1:
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- __pyx_slice__56 = PySlice_New(Py_None, __pyx_int_neg_1, Py_None); if (unlikely(!__pyx_slice__56)) __PYX_ERR(0, 3728, __pyx_L1_error)
+ __pyx_slice__56 = PySlice_New(Py_None, __pyx_int_neg_1, Py_None); if (unlikely(!__pyx_slice__56)) __PYX_ERR(0, 3741, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__56);
__Pyx_GIVEREF(__pyx_slice__56);
- /* "netCDF4/_netCDF4.pyx":3826
+ /* "netCDF4/_netCDF4.pyx":3837
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* byte_type = self.dtype.str[1:] in ['u1','i1'] # <<<<<<<<<<<<<<
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*/
- __pyx_slice__57 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__57)) __PYX_ERR(0, 3826, __pyx_L1_error)
+ __pyx_slice__57 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__57)) __PYX_ERR(0, 3837, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__57);
__Pyx_GIVEREF(__pyx_slice__57);
- /* "netCDF4/_netCDF4.pyx":3830
+ /* "netCDF4/_netCDF4.pyx":3841
* fval = numpy.array(self._FillValue, self.dtype)
* else:
* fval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype) # <<<<<<<<<<<<<<
* if byte_type: fval = None
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*/
- __pyx_slice__58 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__58)) __PYX_ERR(0, 3830, __pyx_L1_error)
+ __pyx_slice__58 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__58)) __PYX_ERR(0, 3841, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__58);
__Pyx_GIVEREF(__pyx_slice__58);
- /* "netCDF4/_netCDF4.pyx":3895
+ /* "netCDF4/_netCDF4.pyx":3906
* # small to assume one of the values should appear as a missing
* # value unless a _FillValue attribute is set explicitly."
* if no_fill != 1 and self.dtype.str[1:] not in ['u1','i1']: # <<<<<<<<<<<<<<
* fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype)
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*/
- __pyx_slice__59 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__59)) __PYX_ERR(0, 3895, __pyx_L1_error)
+ __pyx_slice__59 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__59)) __PYX_ERR(0, 3906, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__59);
__Pyx_GIVEREF(__pyx_slice__59);
- /* "netCDF4/_netCDF4.pyx":3896
+ /* "netCDF4/_netCDF4.pyx":3907
* # value unless a _FillValue attribute is set explicitly."
* if no_fill != 1 and self.dtype.str[1:] not in ['u1','i1']:
* fillval = numpy.array(default_fillvals[self.dtype.str[1:]],self.dtype) # <<<<<<<<<<<<<<
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*/
- __pyx_slice__60 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__60)) __PYX_ERR(0, 3896, __pyx_L1_error)
+ __pyx_slice__60 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__60)) __PYX_ERR(0, 3907, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__60);
__Pyx_GIVEREF(__pyx_slice__60);
- /* "netCDF4/_netCDF4.pyx":3927
+ /* "netCDF4/_netCDF4.pyx":3938
* cdef ndarray data2
* if not self._isvlen:
* raise TypeError('_assign_vlen method only for use with VLEN variables') # <<<<<<<<<<<<<<
* ndims = self.ndim
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*/
- __pyx_tuple__61 = PyTuple_Pack(1, __pyx_kp_s_assign_vlen_method_only_for_use); if (unlikely(!__pyx_tuple__61)) __PYX_ERR(0, 3927, __pyx_L1_error)
+ __pyx_tuple__61 = PyTuple_Pack(1, __pyx_kp_s_assign_vlen_method_only_for_use); if (unlikely(!__pyx_tuple__61)) __PYX_ERR(0, 3938, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__61);
__Pyx_GIVEREF(__pyx_tuple__61);
- /* "netCDF4/_netCDF4.pyx":3939
+ /* "netCDF4/_netCDF4.pyx":3950
* elem = self.shape[0]+elem
* else:
* raise IndexError("Illegal index") # <<<<<<<<<<<<<<
* elif isinstance(elem, tuple):
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*/
- __pyx_tuple__62 = PyTuple_Pack(1, __pyx_kp_s_Illegal_index); if (unlikely(!__pyx_tuple__62)) __PYX_ERR(0, 3939, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__62);
__Pyx_GIVEREF(__pyx_tuple__62);
- /* "netCDF4/_netCDF4.pyx":3942
+ /* "netCDF4/_netCDF4.pyx":3953
* elif isinstance(elem, tuple):
* if len(elem) != ndims:
* raise IndexError("Illegal index") # <<<<<<<<<<<<<<
* elemnew = []
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*/
- __pyx_tuple__63 = PyTuple_Pack(1, __pyx_kp_s_Illegal_index); if (unlikely(!__pyx_tuple__63)) __PYX_ERR(0, 3942, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__63);
__Pyx_GIVEREF(__pyx_tuple__63);
- /* "netCDF4/_netCDF4.pyx":3950
+ /* "netCDF4/_netCDF4.pyx":3961
* enew = self.shape[n]+e
* if enew < 0:
* raise IndexError("Illegal index") # <<<<<<<<<<<<<<
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__Pyx_GOTREF(__pyx_tuple__64);
__Pyx_GIVEREF(__pyx_tuple__64);
- /* "netCDF4/_netCDF4.pyx":4122
+ /* "netCDF4/_netCDF4.pyx":4133
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* else:
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*/
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__Pyx_GOTREF(__pyx_slice__65);
__Pyx_GIVEREF(__pyx_slice__65);
- /* "netCDF4/_netCDF4.pyx":4140
+ /* "netCDF4/_netCDF4.pyx":4151
* def __len__(self):
* if not self.shape:
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__Pyx_GOTREF(__pyx_tuple__66);
__Pyx_GIVEREF(__pyx_tuple__66);
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+ /* "netCDF4/_netCDF4.pyx":4163
* Scientific.IO.NetCDF, can also be done by assigning to an Ellipsis slice ([...])."""
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* raise IndexError('to assign values to a non-scalar variable, use a slice') # <<<<<<<<<<<<<<
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*/
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__Pyx_GOTREF(__pyx_tuple__67);
__Pyx_GIVEREF(__pyx_tuple__67);
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+ /* "netCDF4/_netCDF4.pyx":4164
* if len(self.dimensions):
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__Pyx_GOTREF(__pyx_slice__68);
__Pyx_GIVEREF(__pyx_slice__68);
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+ /* "netCDF4/_netCDF4.pyx":4173
* Scientific.IO.NetCDF, can also be done by slicing with an Ellipsis ([...])."""
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__Pyx_GOTREF(__pyx_tuple__69);
__Pyx_GIVEREF(__pyx_tuple__69);
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+ /* "netCDF4/_netCDF4.pyx":4174
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__Pyx_GOTREF(__pyx_slice__70);
__Pyx_GIVEREF(__pyx_slice__70);
- /* "netCDF4/_netCDF4.pyx":4310
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__Pyx_GOTREF(__pyx_slice__71);
__Pyx_GIVEREF(__pyx_slice__71);
- /* "netCDF4/_netCDF4.pyx":4314
+ /* "netCDF4/_netCDF4.pyx":4325
* startp[n] = start[n]
* stridep[n] = stride[n]
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__Pyx_GOTREF(__pyx_slice__72);
__Pyx_GIVEREF(__pyx_slice__72);
- /* "netCDF4/_netCDF4.pyx":4320
+ /* "netCDF4/_netCDF4.pyx":4331
* dataelem = PyArray_SIZE(data)
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__Pyx_GOTREF(__pyx_tuple__73);
__Pyx_GIVEREF(__pyx_tuple__73);
- /* "netCDF4/_netCDF4.pyx":4347
+ /* "netCDF4/_netCDF4.pyx":4357
* elif self._isvlen:
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*/
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+ __pyx_tuple__74 = PyTuple_Pack(1, __pyx_kp_s_data_to_put_in_string_variable_m); if (unlikely(!__pyx_tuple__74)) __PYX_ERR(0, 4357, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__74);
__Pyx_GIVEREF(__pyx_tuple__74);
- /* "netCDF4/_netCDF4.pyx":4366
+ /* "netCDF4/_netCDF4.pyx":4376
* startp, countp, strdata)
* else:
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__Pyx_GOTREF(__pyx_tuple__75);
__Pyx_GIVEREF(__pyx_tuple__75);
- /* "netCDF4/_netCDF4.pyx":4382
+ /* "netCDF4/_netCDF4.pyx":4392
* elptr = (<void**>databuff)[0]
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+ __pyx_slice__76 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__76)) __PYX_ERR(0, 4392, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__76);
__Pyx_GIVEREF(__pyx_slice__76);
- /* "netCDF4/_netCDF4.pyx":4394
+ /* "netCDF4/_netCDF4.pyx":4404
* startp, countp, vldata)
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* raise IndexError('strides must all be 1 for vlen variables') # <<<<<<<<<<<<<<
* #ierr = nc_put_vars(self._grpid, self._varid,
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- __pyx_tuple__77 = PyTuple_Pack(1, __pyx_kp_s_strides_must_all_be_1_for_vlen_v); if (unlikely(!__pyx_tuple__77)) __PYX_ERR(0, 4394, __pyx_L1_error)
+ __pyx_tuple__77 = PyTuple_Pack(1, __pyx_kp_s_strides_must_all_be_1_for_vlen_v); if (unlikely(!__pyx_tuple__77)) __PYX_ERR(0, 4404, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__77);
__Pyx_GIVEREF(__pyx_tuple__77);
- /* "netCDF4/_netCDF4.pyx":4422
+ /* "netCDF4/_netCDF4.pyx":4432
* for lendim in count:
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*/
- __pyx_tuple__78 = PyTuple_Pack(1, __pyx_int_1); if (unlikely(!__pyx_tuple__78)) __PYX_ERR(0, 4422, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__78);
__Pyx_GIVEREF(__pyx_tuple__78);
- /* "netCDF4/_netCDF4.pyx":4443
+ /* "netCDF4/_netCDF4.pyx":4453
* startp[n] = start[n]+stride[n]*(count[n]-1)
* stride[n] = -stride[n]
* sl.append(slice(None, None, -1)) # this slice will reverse the data # <<<<<<<<<<<<<<
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* startp[n] = start[n]
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- __pyx_slice__79 = PySlice_New(Py_None, Py_None, __pyx_int_neg_1); if (unlikely(!__pyx_slice__79)) __PYX_ERR(0, 4443, __pyx_L1_error)
+ __pyx_slice__79 = PySlice_New(Py_None, Py_None, __pyx_int_neg_1); if (unlikely(!__pyx_slice__79)) __PYX_ERR(0, 4453, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__79);
__Pyx_GIVEREF(__pyx_slice__79);
- /* "netCDF4/_netCDF4.pyx":4447
+ /* "netCDF4/_netCDF4.pyx":4457
* startp[n] = start[n]
* stridep[n] = stride[n]
* sl.append(slice(None,None, 1)) # <<<<<<<<<<<<<<
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- __pyx_slice__80 = PySlice_New(Py_None, Py_None, __pyx_int_1); if (unlikely(!__pyx_slice__80)) __PYX_ERR(0, 4447, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_slice__80);
__Pyx_GIVEREF(__pyx_slice__80);
- /* "netCDF4/_netCDF4.pyx":4480
+ /* "netCDF4/_netCDF4.pyx":4490
* else:
* # FIXME: is this a bug in netCDF4?
* raise IndexError('strides must all be 1 for string variables') # <<<<<<<<<<<<<<
* #ierr = nc_get_vars(self._grpid, self._varid,
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*/
- __pyx_tuple__81 = PyTuple_Pack(1, __pyx_kp_s_strides_must_all_be_1_for_string); if (unlikely(!__pyx_tuple__81)) __PYX_ERR(0, 4480, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__81);
__Pyx_GIVEREF(__pyx_tuple__81);
- /* "netCDF4/_netCDF4.pyx":4510
+ /* "netCDF4/_netCDF4.pyx":4520
* startp, countp, vldata)
* else:
* raise IndexError('strides must all be 1 for vlen variables') # <<<<<<<<<<<<<<
* #ierr = nc_get_vars(self._grpid, self._varid,
* # startp, countp, stridep, vldata)
*/
- __pyx_tuple__82 = PyTuple_Pack(1, __pyx_kp_s_strides_must_all_be_1_for_vlen_v); if (unlikely(!__pyx_tuple__82)) __PYX_ERR(0, 4510, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__82);
__Pyx_GIVEREF(__pyx_tuple__82);
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- * (self.endian() == 'little' and is_native_big):
- * data.byteswap(True) # in-place byteswap # <<<<<<<<<<<<<<
+ /* "netCDF4/_netCDF4.pyx":4553
+ * # (pull request #555, issue #554).
+ * if not data.dtype.isnative:
+ * data.byteswap(True) # in-place byteswap # <<<<<<<<<<<<<<
* if not self.dimensions:
* return data[0] # a scalar
*/
- __pyx_tuple__83 = PyTuple_Pack(1, Py_True); if (unlikely(!__pyx_tuple__83)) __PYX_ERR(0, 4544, __pyx_L1_error)
+ __pyx_tuple__83 = PyTuple_Pack(1, Py_True); if (unlikely(!__pyx_tuple__83)) __PYX_ERR(0, 4553, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__83);
__Pyx_GIVEREF(__pyx_tuple__83);
- /* "netCDF4/_netCDF4.pyx":4554
+ /* "netCDF4/_netCDF4.pyx":4563
* def __reduce__(self):
* # raise error is user tries to pickle a Variable object.
* raise NotImplementedError('Variable is not picklable') # <<<<<<<<<<<<<<
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- __pyx_tuple__84 = PyTuple_Pack(1, __pyx_kp_s_Variable_is_not_picklable); if (unlikely(!__pyx_tuple__84)) __PYX_ERR(0, 4554, __pyx_L1_error)
+ __pyx_tuple__84 = PyTuple_Pack(1, __pyx_kp_s_Variable_is_not_picklable); if (unlikely(!__pyx_tuple__84)) __PYX_ERR(0, 4563, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__84);
__Pyx_GIVEREF(__pyx_tuple__84);
- /* "netCDF4/_netCDF4.pyx":4621
+ /* "netCDF4/_netCDF4.pyx":4630
* def __reduce__(self):
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* raise NotImplementedError('CompoundType is not picklable') # <<<<<<<<<<<<<<
*
* cdef _def_compound(grp, object dt, object dtype_name):
*/
- __pyx_tuple__85 = PyTuple_Pack(1, __pyx_kp_s_CompoundType_is_not_picklable); if (unlikely(!__pyx_tuple__85)) __PYX_ERR(0, 4621, __pyx_L1_error)
+ __pyx_tuple__85 = PyTuple_Pack(1, __pyx_kp_s_CompoundType_is_not_picklable); if (unlikely(!__pyx_tuple__85)) __PYX_ERR(0, 4630, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__85);
__Pyx_GIVEREF(__pyx_tuple__85);
- /* "netCDF4/_netCDF4.pyx":4651
+ /* "netCDF4/_netCDF4.pyx":4660
* if format.kind != 'V': # scalar primitive type
* try:
* xtype_tmp = _nptonctype[format.str[1:]] # <<<<<<<<<<<<<<
* except KeyError:
* raise ValueError('Unsupported compound type element')
*/
- __pyx_slice__86 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__86)) __PYX_ERR(0, 4651, __pyx_L1_error)
+ __pyx_slice__86 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__86)) __PYX_ERR(0, 4660, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__86);
__Pyx_GIVEREF(__pyx_slice__86);
- /* "netCDF4/_netCDF4.pyx":4653
+ /* "netCDF4/_netCDF4.pyx":4662
* xtype_tmp = _nptonctype[format.str[1:]]
* except KeyError:
* raise ValueError('Unsupported compound type element') # <<<<<<<<<<<<<<
* ierr = nc_insert_compound(grp._grpid, xtype, namstring,
* offset, xtype_tmp)
*/
- __pyx_tuple__87 = PyTuple_Pack(1, __pyx_kp_s_Unsupported_compound_type_elemen); if (unlikely(!__pyx_tuple__87)) __PYX_ERR(0, 4653, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__87);
__Pyx_GIVEREF(__pyx_tuple__87);
- /* "netCDF4/_netCDF4.pyx":4676
+ /* "netCDF4/_netCDF4.pyx":4685
* if format.subdtype[0].str[1] != 'V': # primitive type.
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* xtype_tmp = _nptonctype[format.subdtype[0].str[1:]] # <<<<<<<<<<<<<<
* except KeyError:
* raise ValueError('Unsupported compound type element')
*/
- __pyx_slice__88 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__88)) __PYX_ERR(0, 4676, __pyx_L1_error)
+ __pyx_slice__88 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__88)) __PYX_ERR(0, 4685, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__88);
__Pyx_GIVEREF(__pyx_slice__88);
- /* "netCDF4/_netCDF4.pyx":4678
+ /* "netCDF4/_netCDF4.pyx":4687
* xtype_tmp = _nptonctype[format.subdtype[0].str[1:]]
* except KeyError:
* raise ValueError('Unsupported compound type element') # <<<<<<<<<<<<<<
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*/
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__Pyx_GOTREF(__pyx_tuple__89);
__Pyx_GIVEREF(__pyx_tuple__89);
- /* "netCDF4/_netCDF4.pyx":4716
+ /* "netCDF4/_netCDF4.pyx":4725
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* if parent_grp is None:
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__Pyx_GOTREF(__pyx_tuple__90);
__Pyx_GIVEREF(__pyx_tuple__90);
- /* "netCDF4/_netCDF4.pyx":4718
+ /* "netCDF4/_netCDF4.pyx":4727
* raise ValueError("cannot find compound type in this group or parent groups")
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+ __pyx_tuple__91 = PyTuple_Pack(1, __pyx_kp_s_cannot_find_compound_type_in_thi); if (unlikely(!__pyx_tuple__91)) __PYX_ERR(0, 4727, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__91);
__Pyx_GIVEREF(__pyx_tuple__91);
- /* "netCDF4/_netCDF4.pyx":4792
+ /* "netCDF4/_netCDF4.pyx":4801
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__Pyx_GOTREF(__pyx_tuple__92);
__Pyx_GIVEREF(__pyx_tuple__92);
- /* "netCDF4/_netCDF4.pyx":4868
+ /* "netCDF4/_netCDF4.pyx":4877
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+ __pyx_tuple__93 = PyTuple_Pack(1, __pyx_kp_s_VLType_is_not_picklable); if (unlikely(!__pyx_tuple__93)) __PYX_ERR(0, 4877, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__93);
__Pyx_GIVEREF(__pyx_tuple__93);
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+ /* "netCDF4/_netCDF4.pyx":4894
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+ __pyx_slice__94 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__94)) __PYX_ERR(0, 4894, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__94);
__Pyx_GIVEREF(__pyx_slice__94);
- /* "netCDF4/_netCDF4.pyx":4888
+ /* "netCDF4/_netCDF4.pyx":4897
* # find netCDF primitive data type corresponding to
* # specified numpy data type.
* xtype_tmp = _nptonctype[dt.str[1:]] # <<<<<<<<<<<<<<
* ierr = nc_def_vlen(grp._grpid, namstring, xtype_tmp, &xtype);
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*/
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+ __pyx_slice__95 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__95)) __PYX_ERR(0, 4897, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__95);
__Pyx_GIVEREF(__pyx_slice__95);
- /* "netCDF4/_netCDF4.pyx":4893
+ /* "netCDF4/_netCDF4.pyx":4902
* raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
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*
*/
- __pyx_tuple__96 = PyTuple_Pack(1, __pyx_kp_s_unsupported_datatype_specified_f); if (unlikely(!__pyx_tuple__96)) __PYX_ERR(0, 4893, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__96);
__Pyx_GIVEREF(__pyx_tuple__96);
- /* "netCDF4/_netCDF4.pyx":4920
+ /* "netCDF4/_netCDF4.pyx":4929
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*/
- __pyx_tuple__97 = PyTuple_Pack(1, __pyx_kp_s_unsupported_component_type_for_V); if (unlikely(!__pyx_tuple__97)) __PYX_ERR(0, 4920, __pyx_L1_error)
+ __pyx_tuple__97 = PyTuple_Pack(1, __pyx_kp_s_unsupported_component_type_for_V); if (unlikely(!__pyx_tuple__97)) __PYX_ERR(0, 4929, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__97);
__Pyx_GIVEREF(__pyx_tuple__97);
- /* "netCDF4/_netCDF4.pyx":4987
+ /* "netCDF4/_netCDF4.pyx":4996
* def __reduce__(self):
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* raise NotImplementedError('EnumType is not picklable') # <<<<<<<<<<<<<<
*
* cdef _def_enum(grp, object dt, object dtype_name, object enum_dict):
*/
- __pyx_tuple__98 = PyTuple_Pack(1, __pyx_kp_s_EnumType_is_not_picklable); if (unlikely(!__pyx_tuple__98)) __PYX_ERR(0, 4987, __pyx_L1_error)
+ __pyx_tuple__98 = PyTuple_Pack(1, __pyx_kp_s_EnumType_is_not_picklable); if (unlikely(!__pyx_tuple__98)) __PYX_ERR(0, 4996, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__98);
__Pyx_GIVEREF(__pyx_tuple__98);
- /* "netCDF4/_netCDF4.pyx":4998
+ /* "netCDF4/_netCDF4.pyx":5008
* namstring = bytestr
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*/
- __pyx_slice__99 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__99)) __PYX_ERR(0, 4998, __pyx_L1_error)
+ __pyx_slice__99 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__99)) __PYX_ERR(0, 5008, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__99);
__Pyx_GIVEREF(__pyx_slice__99);
- /* "netCDF4/_netCDF4.pyx":5001
+ /* "netCDF4/_netCDF4.pyx":5011
* # find netCDF primitive data type corresponding to
* # specified numpy data type.
* xtype_tmp = _intnptonctype[dt.str[1:]] # <<<<<<<<<<<<<<
* ierr = nc_def_enum(grp._grpid, xtype_tmp, namstring, &xtype);
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*/
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+ __pyx_slice__100 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__100)) __PYX_ERR(0, 5011, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__100);
__Pyx_GIVEREF(__pyx_slice__100);
- /* "netCDF4/_netCDF4.pyx":5042
+ /* "netCDF4/_netCDF4.pyx":5051
* dt = numpy.dtype(datatype) # see if it is a primitive type
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* raise KeyError("unsupported component type for VLEN") # <<<<<<<<<<<<<<
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- __pyx_tuple__101 = PyTuple_Pack(1, __pyx_kp_s_unsupported_component_type_for_V); if (unlikely(!__pyx_tuple__101)) __PYX_ERR(0, 5042, __pyx_L1_error)
+ __pyx_tuple__101 = PyTuple_Pack(1, __pyx_kp_s_unsupported_component_type_for_V); if (unlikely(!__pyx_tuple__101)) __PYX_ERR(0, 5051, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__101);
__Pyx_GIVEREF(__pyx_tuple__101);
- /* "netCDF4/_netCDF4.pyx":5070
+ /* "netCDF4/_netCDF4.pyx":5079
* return str(bytestr,encoding='ascii')
* else:
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*
* #----------------------------------------
*/
- __pyx_tuple__102 = PyTuple_Pack(1, __pyx_n_s_ascii); if (unlikely(!__pyx_tuple__102)) __PYX_ERR(0, 5070, __pyx_L1_error)
+ __pyx_tuple__102 = PyTuple_Pack(1, __pyx_n_s_ascii); if (unlikely(!__pyx_tuple__102)) __PYX_ERR(0, 5079, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__102);
__Pyx_GIVEREF(__pyx_tuple__102);
- /* "netCDF4/_netCDF4.pyx":5090
+ /* "netCDF4/_netCDF4.pyx":5099
* units = timestr_split[0].lower()
* if timestr_split[1].lower() != 'since':
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* # parse the date string.
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*/
- __pyx_tuple__103 = PyTuple_Pack(1, __pyx_kp_s_no_since_in_unit_string); if (unlikely(!__pyx_tuple__103)) __PYX_ERR(0, 5090, __pyx_L1_error)
+ __pyx_tuple__103 = PyTuple_Pack(1, __pyx_kp_s_no_since_in_unit_string); if (unlikely(!__pyx_tuple__103)) __PYX_ERR(0, 5099, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__103);
__Pyx_GIVEREF(__pyx_tuple__103);
- /* "netCDF4/_netCDF4.pyx":5092
+ /* "netCDF4/_netCDF4.pyx":5101
* raise ValueError("no 'since' in unit_string")
* # parse the date string.
* n = timestr.find('since')+6 # <<<<<<<<<<<<<<
* isostring = timestr[n:]
* year, month, day, hour, minute, second, utc_offset =\
*/
- __pyx_tuple__104 = PyTuple_Pack(1, __pyx_n_s_since); if (unlikely(!__pyx_tuple__104)) __PYX_ERR(0, 5092, __pyx_L1_error)
+ __pyx_tuple__104 = PyTuple_Pack(1, __pyx_n_s_since); if (unlikely(!__pyx_tuple__104)) __PYX_ERR(0, 5101, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__104);
__Pyx_GIVEREF(__pyx_tuple__104);
- /* "netCDF4/_netCDF4.pyx":5104
+ /* "netCDF4/_netCDF4.pyx":5113
* basedate = netcdftime.datetime(year, month, day, hour, minute, second)
* else:
* raise ValueError('cannot use utc_offset for reference years <= 0') # <<<<<<<<<<<<<<
* return basedate
*
*/
- __pyx_tuple__105 = PyTuple_Pack(1, __pyx_kp_s_cannot_use_utc_offset_for_refere); if (unlikely(!__pyx_tuple__105)) __PYX_ERR(0, 5104, __pyx_L1_error)
+ __pyx_tuple__105 = PyTuple_Pack(1, __pyx_kp_s_cannot_use_utc_offset_for_refere); if (unlikely(!__pyx_tuple__105)) __PYX_ERR(0, 5113, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__105);
__Pyx_GIVEREF(__pyx_tuple__105);
- /* "netCDF4/_netCDF4.pyx":5125
+ /* "netCDF4/_netCDF4.pyx":5134
* (default) or `'U1'` (if dtype=`'U'`)"""
* if dtype not in ["S","U"]:
* raise ValueError("dtype must string or unicode ('S' or 'U')") # <<<<<<<<<<<<<<
* arr = numpy.zeros(NUMCHARS,dtype+'1')
* arr[0:len(string)] = tuple(string)
*/
- __pyx_tuple__106 = PyTuple_Pack(1, __pyx_kp_s_dtype_must_string_or_unicode_S_o); if (unlikely(!__pyx_tuple__106)) __PYX_ERR(0, 5125, __pyx_L1_error)
+ __pyx_tuple__106 = PyTuple_Pack(1, __pyx_kp_s_dtype_must_string_or_unicode_S_o); if (unlikely(!__pyx_tuple__106)) __PYX_ERR(0, 5134, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__106);
__Pyx_GIVEREF(__pyx_tuple__106);
- /* "netCDF4/_netCDF4.pyx":5144
+ /* "netCDF4/_netCDF4.pyx":5153
* dtype = a.dtype.kind
* if dtype not in ["S","U"]:
* raise ValueError("type must string or unicode ('S' or 'U')") # <<<<<<<<<<<<<<
* b = numpy.array(tuple(a.tostring().decode(default_encoding)),dtype+'1')
* b.shape = a.shape + (a.itemsize,)
*/
- __pyx_tuple__107 = PyTuple_Pack(1, __pyx_kp_s_type_must_string_or_unicode_S_or); if (unlikely(!__pyx_tuple__107)) __PYX_ERR(0, 5144, __pyx_L1_error)
+ __pyx_tuple__107 = PyTuple_Pack(1, __pyx_kp_s_type_must_string_or_unicode_S_or); if (unlikely(!__pyx_tuple__107)) __PYX_ERR(0, 5153, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__107);
__Pyx_GIVEREF(__pyx_tuple__107);
- /* "netCDF4/_netCDF4.pyx":5163
+ /* "netCDF4/_netCDF4.pyx":5172
* dtype = b.dtype.kind
* if dtype not in ["S","U"]:
* raise ValueError("type must string or unicode ('S' or 'U')") # <<<<<<<<<<<<<<
* bs = b.tostring().decode(default_encoding)
* slen = int(b.shape[-1])
*/
- __pyx_tuple__108 = PyTuple_Pack(1, __pyx_kp_s_type_must_string_or_unicode_S_or); if (unlikely(!__pyx_tuple__108)) __PYX_ERR(0, 5163, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__108);
__Pyx_GIVEREF(__pyx_tuple__108);
- /* "netCDF4/_netCDF4.pyx":5167
+ /* "netCDF4/_netCDF4.pyx":5176
* slen = int(b.shape[-1])
* a = numpy.array([bs[n1:n1+slen] for n1 in range(0,len(bs),slen)],dtype+repr(slen))
* a.shape = b.shape[:-1] # <<<<<<<<<<<<<<
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*
*/
- __pyx_slice__109 = PySlice_New(Py_None, __pyx_int_neg_1, Py_None); if (unlikely(!__pyx_slice__109)) __PYX_ERR(0, 5167, __pyx_L1_error)
+ __pyx_slice__109 = PySlice_New(Py_None, __pyx_int_neg_1, Py_None); if (unlikely(!__pyx_slice__109)) __PYX_ERR(0, 5176, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__109);
__Pyx_GIVEREF(__pyx_slice__109);
- /* "netCDF4/_netCDF4.pyx":5249
+ /* "netCDF4/_netCDF4.pyx":5258
* times.append(totaltime/1.e6/3600./24.)
* else:
* raise ValueError('unsupported time units') # <<<<<<<<<<<<<<
* if isscalar:
* return times[0]
*/
- __pyx_tuple__110 = PyTuple_Pack(1, __pyx_kp_s_unsupported_time_units); if (unlikely(!__pyx_tuple__110)) __PYX_ERR(0, 5249, __pyx_L1_error)
+ __pyx_tuple__110 = PyTuple_Pack(1, __pyx_kp_s_unsupported_time_units); if (unlikely(!__pyx_tuple__110)) __PYX_ERR(0, 5258, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__110);
__Pyx_GIVEREF(__pyx_tuple__110);
- /* "netCDF4/_netCDF4.pyx":5343
+ /* "netCDF4/_netCDF4.pyx":5352
* tsecs = time*86400.
* else:
* raise ValueError('unsupported time units') # <<<<<<<<<<<<<<
* # compute time delta.
* days = tsecs // 86400.
*/
- __pyx_tuple__111 = PyTuple_Pack(1, __pyx_kp_s_unsupported_time_units); if (unlikely(!__pyx_tuple__111)) __PYX_ERR(0, 5343, __pyx_L1_error)
+ __pyx_tuple__111 = PyTuple_Pack(1, __pyx_kp_s_unsupported_time_units); if (unlikely(!__pyx_tuple__111)) __PYX_ERR(0, 5352, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__111);
__Pyx_GIVEREF(__pyx_tuple__111);
- /* "netCDF4/_netCDF4.pyx":5395
+ /* "netCDF4/_netCDF4.pyx":5404
* nctime.units
* except AttributeError:
* raise AttributeError("netcdf time variable is missing a 'units' attribute") # <<<<<<<<<<<<<<
* if calendar == None:
* calendar = getattr(nctime, 'calendar', 'standard')
*/
- __pyx_tuple__112 = PyTuple_Pack(1, __pyx_kp_s_netcdf_time_variable_is_missing); if (unlikely(!__pyx_tuple__112)) __PYX_ERR(0, 5395, __pyx_L1_error)
+ __pyx_tuple__112 = PyTuple_Pack(1, __pyx_kp_s_netcdf_time_variable_is_missing); if (unlikely(!__pyx_tuple__112)) __PYX_ERR(0, 5404, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__112);
__Pyx_GIVEREF(__pyx_tuple__112);
- /* "netCDF4/_netCDF4.pyx":5481
+ /* "netCDF4/_netCDF4.pyx":5490
* # can be used like a CDF instance.
* if isinstance(files, str):
* if files.startswith('http'): # <<<<<<<<<<<<<<
* msg='cannot using file globbing for remote (OPeNDAP) datasets'
* raise ValueError(msg)
*/
- __pyx_tuple__113 = PyTuple_Pack(1, __pyx_n_s_http); if (unlikely(!__pyx_tuple__113)) __PYX_ERR(0, 5481, __pyx_L1_error)
+ __pyx_tuple__113 = PyTuple_Pack(1, __pyx_n_s_http); if (unlikely(!__pyx_tuple__113)) __PYX_ERR(0, 5490, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__113);
__Pyx_GIVEREF(__pyx_tuple__113);
- /* "netCDF4/_netCDF4.pyx":5543
+ /* "netCDF4/_netCDF4.pyx":5552
* # Make sure each file defines the same aggregation variables as the master
* # and that the variables are defined in the same way (name, shape and type)
* for f in files[1:]: # <<<<<<<<<<<<<<
* part = Dataset(f)
* varInfo = part.variables
*/
- __pyx_slice__114 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__114)) __PYX_ERR(0, 5543, __pyx_L1_error)
+ __pyx_slice__114 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__114)) __PYX_ERR(0, 5552, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__114);
__Pyx_GIVEREF(__pyx_slice__114);
- /* "netCDF4/_netCDF4.pyx":5554
+ /* "netCDF4/_netCDF4.pyx":5563
* #if not vInst.dimensions[0] != aggDimName:
*
* masterDims, masterShape, masterType = masterRecVar[v][:3] # <<<<<<<<<<<<<<
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*/
- __pyx_slice__115 = PySlice_New(Py_None, __pyx_int_3, Py_None); if (unlikely(!__pyx_slice__115)) __PYX_ERR(0, 5554, __pyx_L1_error)
+ __pyx_slice__115 = PySlice_New(Py_None, __pyx_int_3, Py_None); if (unlikely(!__pyx_slice__115)) __PYX_ERR(0, 5563, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__115);
__Pyx_GIVEREF(__pyx_slice__115);
- /* "netCDF4/_netCDF4.pyx":5571
+ /* "netCDF4/_netCDF4.pyx":5580
* "master %s (%s) and extension %s (%s)" %
* (v, master, len(masterShape), f, len(extShape)))
* if masterShape[1:] != extShape[1:]: # <<<<<<<<<<<<<<
* raise IOError("variable %s : shape mismatch between "
* "master %s (%s) and extension %s (%s)" %
*/
- __pyx_slice__116 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__116)) __PYX_ERR(0, 5571, __pyx_L1_error)
+ __pyx_slice__116 = PySlice_New(__pyx_int_1, Py_None, Py_None); if (unlikely(!__pyx_slice__116)) __PYX_ERR(0, 5580, __pyx_L1_error)
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__Pyx_GIVEREF(__pyx_slice__116);
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__Pyx_GOTREF(__pyx_slice__117);
__Pyx_GIVEREF(__pyx_slice__117);
- /* "netCDF4/_netCDF4.pyx":5614
+ /* "netCDF4/_netCDF4.pyx":5623
* for dset in self._cdf:
* if dset.file_format == 'NETCDF4' or dset.data_model == 'NETCDF4':
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* self._file_format.append(dset.file_format)
* self._data_model.append(dset.data_model)
*/
- __pyx_tuple__118 = PyTuple_Pack(1, __pyx_kp_s_MFNetCDF4_only_works_with_NETCDF); if (unlikely(!__pyx_tuple__118)) __PYX_ERR(0, 5614, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__118);
__Pyx_GIVEREF(__pyx_tuple__118);
- /* "netCDF4/_netCDF4.pyx":5714
+ /* "netCDF4/_netCDF4.pyx":5683
* def __reduce__(self):
* # raise error is user tries to pickle a MFDataset object.
* raise NotImplementedError('MFDataset is not picklable') # <<<<<<<<<<<<<<
*
* class _Dimension(object):
*/
- __pyx_tuple__119 = PyTuple_Pack(1, __pyx_kp_s_MFDataset_is_not_picklable); if (unlikely(!__pyx_tuple__119)) __PYX_ERR(0, 5714, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_tuple__119);
__Pyx_GIVEREF(__pyx_tuple__119);
- /* "netCDF4/_netCDF4.pyx":5774
+ /* "netCDF4/_netCDF4.pyx":5743
* def __len__(self):
* if not self._shape:
* raise TypeError('len() of unsized object') # <<<<<<<<<<<<<<
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* return self._shape()[0]
*/
- __pyx_tuple__120 = PyTuple_Pack(1, __pyx_kp_s_len_of_unsized_object); if (unlikely(!__pyx_tuple__120)) __PYX_ERR(0, 5774, __pyx_L1_error)
+ __pyx_tuple__120 = PyTuple_Pack(1, __pyx_kp_s_len_of_unsized_object); if (unlikely(!__pyx_tuple__120)) __PYX_ERR(0, 5743, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__120);
__Pyx_GIVEREF(__pyx_tuple__120);
- /* "netCDF4/_netCDF4.pyx":5779
+ /* "netCDF4/_netCDF4.pyx":5748
* def _shape(self):
* recdimlen = len(self._dset.dimensions[self._recdimname])
* return (recdimlen,) + self._mastervar.shape[1:] # <<<<<<<<<<<<<<
* def set_auto_maskandscale(self,val):
* for v in self._recVar:
*/
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__Pyx_GOTREF(__pyx_slice__121);
__Pyx_GIVEREF(__pyx_slice__121);
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+ /* "netCDF4/_netCDF4.pyx":5775
* # The convention used is that for those cases,
* # put_ind for this dimension is set to -1 by _StartCountStride.
* squeeze = data.ndim * [slice(None),] # <<<<<<<<<<<<<<
* for i,n in enumerate(put_ind.shape[:-1]):
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*/
- __pyx_slice__122 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_slice__122)) __PYX_ERR(0, 5806, __pyx_L1_error)
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__Pyx_GOTREF(__pyx_slice__122);
__Pyx_GIVEREF(__pyx_slice__122);
- /* "netCDF4/_netCDF4.pyx":5807
+ /* "netCDF4/_netCDF4.pyx":5776
* # put_ind for this dimension is set to -1 by _StartCountStride.
* squeeze = data.ndim * [slice(None),]
* for i,n in enumerate(put_ind.shape[:-1]): # <<<<<<<<<<<<<<
* if n == 1 and put_ind[...,i].ravel()[0] == -1:
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*/
- __pyx_slice__123 = PySlice_New(Py_None, __pyx_int_neg_1, Py_None); if (unlikely(!__pyx_slice__123)) __PYX_ERR(0, 5807, __pyx_L1_error)
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__Pyx_GIVEREF(__pyx_slice__123);
- /* "netCDF4/_netCDF4.pyx":5824
+ /* "netCDF4/_netCDF4.pyx":5793
* count = [abs(cnt) for cnt in count]
* if (numpy.array(stride) < 0).any():
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*/
- __pyx_tuple__124 = PyTuple_Pack(1, __pyx_kp_s_negative_strides_not_allowed_whe); if (unlikely(!__pyx_tuple__124)) __PYX_ERR(0, 5824, __pyx_L1_error)
+ __pyx_tuple__124 = PyTuple_Pack(1, __pyx_kp_s_negative_strides_not_allowed_whe); if (unlikely(!__pyx_tuple__124)) __PYX_ERR(0, 5793, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__124);
__Pyx_GIVEREF(__pyx_tuple__124);
- /* "netCDF4/_netCDF4.pyx":5848
+ /* "netCDF4/_netCDF4.pyx":5817
*
* # Rebuild the slicing expression for dimensions 1 and ssq.
* newSlice = [slice(None, None, None)] # <<<<<<<<<<<<<<
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*/
- __pyx_slice__125 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_slice__125)) __PYX_ERR(0, 5848, __pyx_L1_error)
+ __pyx_slice__125 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_slice__125)) __PYX_ERR(0, 5817, __pyx_L1_error)
__Pyx_GOTREF(__pyx_slice__125);
__Pyx_GIVEREF(__pyx_slice__125);
- /* "netCDF4/_netCDF4.pyx":5950
+ /* "netCDF4/_netCDF4.pyx":5919
* for t in self._recVar:
* if not hasattr(t,'calendar'):
* raise ValueError('MFTime requires that the time variable in all files have a calendar attribute') # <<<<<<<<<<<<<<
*
* # Check that calendar is the same in all files.
*/
- __pyx_tuple__126 = PyTuple_Pack(1, __pyx_kp_s_MFTime_requires_that_the_time_va); if (unlikely(!__pyx_tuple__126)) __PYX_ERR(0, 5950, __pyx_L1_error)
+ __pyx_tuple__126 = PyTuple_Pack(1, __pyx_kp_s_MFTime_requires_that_the_time_va); if (unlikely(!__pyx_tuple__126)) __PYX_ERR(0, 5919, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__126);
__Pyx_GIVEREF(__pyx_tuple__126);
- /* "netCDF4/_netCDF4.pyx":5954
+ /* "netCDF4/_netCDF4.pyx":5923
* # Check that calendar is the same in all files.
* if len(set([t.calendar for t in self._recVar])) > 1:
* raise ValueError('MFTime requires that the same time calendar is used by all files.') # <<<<<<<<<<<<<<
*
* # Override units if units is specified.
*/
- __pyx_tuple__127 = PyTuple_Pack(1, __pyx_kp_s_MFTime_requires_that_the_same_ti); if (unlikely(!__pyx_tuple__127)) __PYX_ERR(0, 5954, __pyx_L1_error)
+ __pyx_tuple__127 = PyTuple_Pack(1, __pyx_kp_s_MFTime_requires_that_the_same_ti); if (unlikely(!__pyx_tuple__127)) __PYX_ERR(0, 5923, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__127);
__Pyx_GIVEREF(__pyx_tuple__127);
- /* "netCDF4/_netCDF4.pyx":5960
+ /* "netCDF4/_netCDF4.pyx":5929
*
* # Reference date to compute the difference between different time units.
* ref_date = datetime.datetime(1900,1,1) # <<<<<<<<<<<<<<
* ref_num = date2num(ref_date, self.units, self.calendar)
*
*/
- __pyx_tuple__128 = PyTuple_Pack(3, __pyx_int_1900, __pyx_int_1, __pyx_int_1); if (unlikely(!__pyx_tuple__128)) __PYX_ERR(0, 5960, __pyx_L1_error)
+ __pyx_tuple__128 = PyTuple_Pack(3, __pyx_int_1900, __pyx_int_1, __pyx_int_1); if (unlikely(!__pyx_tuple__128)) __PYX_ERR(0, 5929, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__128);
__Pyx_GIVEREF(__pyx_tuple__128);
- /* "netCDF4/_netCDF4.pyx":933
+ /* "netCDF4/_netCDF4.pyx":932
* from ordereddict import OrderedDict
* except ImportError:
* raise ImportError('please install ordereddict (https://pypi.python.org/pypi/ordereddict)') # <<<<<<<<<<<<<<
* try:
* from itertools import izip as zip
*/
- __pyx_tuple__129 = PyTuple_Pack(1, __pyx_kp_s_please_install_ordereddict_https); if (unlikely(!__pyx_tuple__129)) __PYX_ERR(0, 933, __pyx_L1_error)
+ __pyx_tuple__129 = PyTuple_Pack(1, __pyx_kp_s_please_install_ordereddict_https); if (unlikely(!__pyx_tuple__129)) __PYX_ERR(0, 932, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__129);
__Pyx_GIVEREF(__pyx_tuple__129);
- /* "netCDF4/_netCDF4.pyx":959
+ /* "netCDF4/_netCDF4.pyx":958
* # check for required version of netcdf-4 and hdf5.
*
* def _gethdf5libversion(): # <<<<<<<<<<<<<<
* majorvers = H5_VERS_MAJOR
* minorvers = H5_VERS_MINOR
*/
- __pyx_tuple__130 = PyTuple_Pack(4, __pyx_n_s_majorvers, __pyx_n_s_minorvers, __pyx_n_s_releasevers, __pyx_n_s_patchstring); if (unlikely(!__pyx_tuple__130)) __PYX_ERR(0, 959, __pyx_L1_error)
+ __pyx_tuple__130 = PyTuple_Pack(4, __pyx_n_s_majorvers, __pyx_n_s_minorvers, __pyx_n_s_releasevers, __pyx_n_s_patchstring); if (unlikely(!__pyx_tuple__130)) __PYX_ERR(0, 958, __pyx_L1_error)
__Pyx_GOTREF(__pyx_tuple__130);
__Pyx_GIVEREF(__pyx_tuple__130);
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__Pyx_XGOTREF(__pyx_t_5);
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@@ -83128,28 +82217,28 @@ PyMODINIT_FUNC PyInit__netCDF4(void)
__Pyx_XGOTREF(__pyx_t_10);
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@@ -83166,7 +82255,7 @@ PyMODINIT_FUNC PyInit__netCDF4(void)
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__pyx_L9_try_end:;
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goto __pyx_L24_except_error;
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__pyx_L29_try_end:;
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@@ -85749,7 +84833,7 @@ PyMODINIT_FUNC PyInit__netCDF4(void)
/* "netCDF4/_netCDF4.pyx":1
* """ # <<<<<<<<<<<<<<
- * Version 1.2.5
+ * Version 1.2.6
* -------------
*/
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diff --git a/netCDF4/_netCDF4.pyx b/netCDF4/_netCDF4.pyx
index 5176f3b..6f294d5 100644
--- a/netCDF4/_netCDF4.pyx
+++ b/netCDF4/_netCDF4.pyx
@@ -1,5 +1,5 @@
"""
-Version 1.2.5
+Version 1.2.6
-------------
- - -
@@ -36,7 +36,7 @@ Download
Requires
========
- - Python 2.6 or later (python 3 works too).
+ - Python 2.7 or later (python 3 works too).
- [numpy array module](http://numpy.scipy.org), version 1.7.0 or later.
- [Cython](http://cython.org), version 0.19 or later, is optional - if it is installed setup.py will
use it to recompile the Cython source code into C, using conditional compilation
@@ -44,7 +44,6 @@ Requires
Cython is not installed, these features (such as the ability to rename Group objects)
will be disabled to preserve backward compatibility with older versions of the netCDF
library.
- - For python < 2.7, the [ordereddict module](http://python.org/pypi/ordereddict).
- The HDF5 C library version 1.8.4-patch1 or higher (1.8.x recommended)
from [](ftp://ftp.hdfgroup.org/HDF5/current/src).
***netCDF version 4.4.1 or higher is recommended if using HDF5 1.10.x -
@@ -55,8 +54,8 @@ Requires
[OPeNDAP](http://opendap.org) support.
- [HDF4](http://www.hdfgroup.org/products/hdf4), if you want
to be able to read HDF4 "Scientific Dataset" (SD) files.
- - The netCDF-4 C library from
- [ftp://ftp.unidata.ucar.edu/pub/netcdf](ftp://ftp.unidata.ucar.edu/pub/netcdf).
+ - The netCDF-4 C library from the [github releases
+ page](https://github.com/Unidata/netcdf-c/releases).
Version 4.1.1 or higher is required (4.2 or higher recommended).
Be sure to build with `--enable-netcdf-4 --enable-shared`, and set
`CPPFLAGS="-I $HDF5_DIR/include"` and `LDFLAGS="-L $HDF5_DIR/lib"`,
@@ -937,7 +936,7 @@ except ImportError:
# python3: zip is already python2's itertools.izip
pass
-__version__ = "1.2.5"
+__version__ = "1.2.6"
# Initialize numpy
import posixpath
@@ -1066,6 +1065,8 @@ default_encoding = 'utf-8'
# can be set to 'strict' or 'ignore'.
unicode_error = 'replace'
python3 = sys.version_info[0] > 2
+if python3:
+ buffer = memoryview
_nctonptype = {}
for _key,_value in _nptonctype.items():
@@ -2485,7 +2486,11 @@ and variable scaling shall be applied for all variables.
after calling this function will follow the default behaviour.
"""
- for var in self.variables.values():
+ # this is a hack to make inheritance work in MFDataset
+ # (which stores variables in _vars)
+ _vars = self.variables
+ if _vars is None: _vars = self._vars
+ for var in _vars.values():
var.set_auto_maskandscale(value)
for groups in _walk_grps(self):
@@ -2530,7 +2535,11 @@ shall be applied for all variables.
after calling this function will follow the default behaviour.
"""
- for var in self.variables.values():
+ # this is a hack to make inheritance work in MFDataset
+ # (which stores variables in _vars)
+ _vars = self.variables
+ if _vars is None: _vars = self._vars
+ for var in _vars.values():
var.set_auto_scale(value)
for groups in _walk_grps(self):
@@ -2569,8 +2578,12 @@ attribute does not exist on the variable. For example,
vs = []
has_value_flag = False
- for vname in self.variables:
- var = self.variables[vname]
+ # this is a hack to make inheritance work in MFDataset
+ # (which stores variables in _vars)
+ _vars = self.variables
+ if _vars is None: _vars = self._vars
+ for vname in _vars:
+ var = _vars[vname]
for k, v in kwargs.items():
if callable(v):
has_value_flag = v(getattr(var, k, None))
@@ -2583,7 +2596,7 @@ attribute does not exist on the variable. For example,
break
if has_value_flag is True:
- vs.append(self.variables[vname])
+ vs.append(_vars[vname])
return vs
@@ -3252,12 +3265,12 @@ behavior is similar to Fortran or Matlab, but different than numpy.
if grp.data_model != 'NETCDF4': grp._enddef()
raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
else:
- # cast fill_value to type/endian-ness of variable.
+ # cast fill_value to type of variable.
+ # also make sure it is written in native byte order
+ # (the same as the data)
if self._isprimitive or self._isenum:
fillval = numpy.array(fill_value, self.dtype)
- if (is_native_little and self.endian() == 'big') or\
- (is_native_big and self.endian() == 'little'):
- fillval = fillval.byteswap(True)
+ if not fillval.dtype.isnative: fillval.byteswap(True)
_set_att(self._grp, self._varid, '_FillValue',\
fillval, xtype=xtype)
else:
@@ -3660,11 +3673,11 @@ details."""
# "VLEN or compound variable"
# raise AttributeError(msg)
elif name in ['valid_min','valid_max','valid_range','missing_value'] and self._isprimitive:
- if (is_native_little and self.endian() == 'big') or\
- (is_native_big and self.endian() == 'little'):
- value = numpy.array(value, self.dtype).byteswap(True)
- else:
- value = numpy.array(value, self.dtype)
+ # make sure these attributes written in same data type as variable.
+ # also make sure it is written in native byte order
+ # (the same as the data)
+ value = numpy.array(value, self.dtype)
+ if not value.dtype.isnative: value.byteswap(True)
self.setncattr(name, value)
elif not name.endswith('__'):
if hasattr(self,name):
@@ -3795,8 +3808,6 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
totalmask = numpy.zeros(data.shape, numpy.bool)
fill_value = None
if hasattr(self, 'missing_value'):
- # note: missing_value has to have same endian-ness as variable
- # or this won't work.
mval = numpy.array(self.missing_value, self.dtype)
# create mask from missing values.
mvalmask = numpy.zeros(data.shape, numpy.bool)
@@ -4002,7 +4013,7 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
# for string vars, if data is not an array
# assume it is a python string and raise an error
# if it is an array, but not an object array.
- if not hasattr(data,'ndim'):
+ if not isinstance(data, numpy.ndarray):
# issue 458, allow Ellipsis to be used for scalar var
if type(elem) == type(Ellipsis) and not\
len(self.dimensions): elem = 0
@@ -4021,16 +4032,16 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
# for non-string vlen arrays, if data is not multi-dim, or
# not an object array, assume it represents a single element
# of the vlen var.
- if not hasattr(data,'ndim') or data.dtype.kind != 'O':
+ if not isinstance(data, numpy.ndarray) or data.dtype.kind != 'O':
# issue 458, allow Ellipsis to be used for scalar var
if type(elem) == type(Ellipsis) and not\
len(self.dimensions): elem = 0
self._assign_vlen(elem, data)
return
- # A numpy array is needed. Convert if necessary.
- # assume it's a numpy or masked array if it has an 'ndim' attribute.
- if not hasattr(data,'ndim'):
+ # A numpy or masked array (or an object supporting the buffer interface) is needed.
+ # Convert if necessary.
+ if not ma.isMA(data) and not (hasattr(data,'data') and isinstance(data.data,buffer)):
# if auto scaling is to be done, don't cast to an integer yet.
if self.scale and self.dtype.kind in 'iu' and \
hasattr(self, 'scale_factor') or hasattr(self, 'add_offset'):
@@ -4330,9 +4341,8 @@ The default value of `mask` is `True`
# byte-swap data in numpy array so that is has native
# endian byte order (this is what netcdf-c expects -
# issue #554, pull request #555)
- if (is_native_little and data.dtype.byteorder == '>') or\
- (is_native_big and data.dtype.byteorder == '<'):
- data = data.byteswap() # don't do in-place, make a copy
+ if not data.dtype.isnative:
+ data = data.byteswap()
# strides all 1 or scalar variable, use put_vara (faster)
if sum(stride) == ndims or ndims == 0:
ierr = nc_put_vara(self._grpid, self._varid,
@@ -4539,9 +4549,8 @@ The default value of `mask` is `True`
# bytes if the variable dtype is not native endian, so the
# dtype of the returned numpy array matches the variable dtype.
# (pull request #555, issue #554).
- if (self.endian() == 'big' and is_native_little) or\
- (self.endian() == 'little' and is_native_big):
- data.byteswap(True) # in-place byteswap
+ if not data.dtype.isnative:
+ data.byteswap(True) # in-place byteswap
if not self.dimensions:
return data[0] # a scalar
elif squeeze_out:
@@ -4990,8 +4999,9 @@ cdef _def_enum(grp, object dt, object dtype_name, object enum_dict):
# private function used to construct a netCDF Enum data type
# from a numpy dtype object or python str object by EnumType.__init__.
cdef nc_type xtype, xtype_tmp
- cdef int ierr, val
+ cdef int ierr
cdef char *namstring
+ cdef ndarray value_arr
bytestr = _strencode(dtype_name)
namstring = bytestr
dt = numpy.dtype(dt) # convert to numpy datatype.
@@ -5007,11 +5017,10 @@ cdef _def_enum(grp, object dt, object dtype_name, object enum_dict):
raise KeyError(msg)
# insert named members into enum type.
for field in enum_dict:
- value = enum_dict[field]
+ value_arr = numpy.array(enum_dict[field],dt)
bytestr = _strencode(field)
namstring = bytestr
- val = value
- ierr = nc_insert_enum(grp._grpid, xtype, namstring, &val)
+ ierr = nc_insert_enum(grp._grpid, xtype, namstring, value_arr.data)
if ierr != NC_NOERR:
raise RuntimeError((<char *>nc_strerror(ierr)).decode('ascii'))
return xtype, dt
@@ -5642,46 +5651,6 @@ Example usage (See `netCDF4.MFDataset.__init__` for more details):
"""
return self._cdf[0].__dict__.keys()
- def set_auto_maskandscale(self, value):
- """
- **`set_auto_maskandscale(self, True_or_False)`**
-
- Call `Variable.set_auto_maskandscale` for all variables contained in this
- `MFDataset`.
-
- **`True_or_False`**: Boolean determining if automatic conversion to masked arrays
- and variable scaling shall be applied for all variables.
- """
-
- for var in self.variables.values():
- var.set_auto_maskandscale(value)
-
- def set_auto_mask(self, value):
- """
- **`set_auto_mask(self, True_or_False)`**
-
- Call `Variable.set_auto_mask` for all variables contained in this `MFDataset`.
-
- **`True_or_False`**: Boolean determining if automatic conversion to masked arrays
- shall be applied for all variables.
- """
-
- for var in self.variables.values():
- var.set_auto_mask(value)
-
- def set_auto_scale(self, value):
- """
- **`set_auto_scale(self, True_or_False)`**
-
- Call `Variable.set_auto_scale` for all variables contained in this `MFDataset`.
-
- **`True_or_False`**: Boolean determining if automatic variable scaling
- shall be applied for all variables.
- """
-
- for var in self.variables.values():
- var.set_auto_scale(value)
-
def close(self):
"""
**`close(self)`**
diff --git a/setup.py b/setup.py
index b8496e2..6c3b0ef 100644
--- a/setup.py
+++ b/setup.py
@@ -449,7 +449,7 @@ else:
setup(name = "netCDF4",
cmdclass = cmdclass,
- version = "1.2.5",
+ version = "1.2.6",
long_description = "netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types. It is implemented on top of HDF5. This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library. The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project has a `Sub [...]
author = "Jeff Whitaker",
author_email = "jeffrey.s.whitaker at noaa.gov",
diff --git a/test/tst_compound_alignment.py b/test/tst_compound_alignment.py
index 23e670e..fa25495 100644
--- a/test/tst_compound_alignment.py
+++ b/test/tst_compound_alignment.py
@@ -101,11 +101,10 @@ class CompoundAlignTestCase(unittest.TestCase):
assert new_cells.shape == cells.shape
assert new_cells.dtype.names == cells.dtype.names
for name in cells.dtype.names:
- assert cells[name].dtype == new_cells[name].dtype
+ assert cells[name].dtype.name == new_cells[name].dtype.name
assert cells[name].shape == new_cells[name].shape
assert_array_equal(cells[name],new_cells[name])
f.close()
if __name__ == '__main__':
unittest.main()
-
diff --git a/test/tst_multifile.py b/test/tst_multifile.py
index 7096ce8..9fccbf5 100644
--- a/test/tst_multifile.py
+++ b/test/tst_multifile.py
@@ -62,6 +62,12 @@ class VariablesTestCase(unittest.TestCase):
assert getattr(varin,'nonexistantatt',None) == None
f.close()
+ def test_get_by_mfdataset(self):
+ """testing multi-file get_variables_by_attributes."""
+ f = MFDataset(self.files,check=True)
+ assert f.get_variables_by_attributes(axis='T') == []
+ f.get_variables_by_attributes(units='zlotys')[0] == f['x']
+ f.close()
class NonuniformTimeTestCase(unittest.TestCase):
ninc = 365
--
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