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-rw-r--r--tensorflow/python/platform/__init__.py6
-rw-r--r--tensorflow/python/platform/app.py13
-rw-r--r--tensorflow/python/platform/base.i176
-rw-r--r--tensorflow/python/platform/control_imports.py13
-rwxr-xr-xtensorflow/python/platform/default/__init__.py0
-rw-r--r--tensorflow/python/platform/default/_app.py11
-rw-r--r--tensorflow/python/platform/default/_flags.py92
-rw-r--r--tensorflow/python/platform/default/_gfile.py404
-rw-r--r--tensorflow/python/platform/default/_googletest.py68
-rw-r--r--tensorflow/python/platform/default/_init.py1
-rw-r--r--tensorflow/python/platform/default/_logging.py182
-rw-r--r--tensorflow/python/platform/default/_parameterized.py2
-rw-r--r--tensorflow/python/platform/default/_resource_loader.py26
-rw-r--r--tensorflow/python/platform/default/_status_bar.py5
-rw-r--r--tensorflow/python/platform/default/flags_test.py53
-rw-r--r--tensorflow/python/platform/default/gfile_test.py147
-rw-r--r--tensorflow/python/platform/default/logging_test.py13
-rw-r--r--tensorflow/python/platform/flags.py10
-rw-r--r--tensorflow/python/platform/gfile.py10
-rw-r--r--tensorflow/python/platform/googletest.py10
-rw-r--r--tensorflow/python/platform/logging.py10
-rw-r--r--tensorflow/python/platform/numpy.i3085
-rw-r--r--tensorflow/python/platform/parameterized.py10
-rw-r--r--tensorflow/python/platform/resource_loader.py10
-rw-r--r--tensorflow/python/platform/status_bar.py10
-rw-r--r--tensorflow/python/platform/test.py6
26 files changed, 4373 insertions, 0 deletions
diff --git a/tensorflow/python/platform/__init__.py b/tensorflow/python/platform/__init__.py
new file mode 100644
index 0000000000..b545bac907
--- /dev/null
+++ b/tensorflow/python/platform/__init__.py
@@ -0,0 +1,6 @@
+"""Setup system-specific platform environment for TensorFlow."""
+import control_imports
+if control_imports.USE_OSS:
+ from tensorflow.python.platform.default._init import *
+else:
+ from tensorflow.python.platform.google._init import *
diff --git a/tensorflow/python/platform/app.py b/tensorflow/python/platform/app.py
new file mode 100644
index 0000000000..3d51bc74b2
--- /dev/null
+++ b/tensorflow/python/platform/app.py
@@ -0,0 +1,13 @@
+"""Switch between depending on pyglib.app or an OSS replacement."""
+# pylint: disable=unused-import
+# pylint: disable=g-import-not-at-top
+# pylint: disable=wildcard-import
+import tensorflow.python.platform
+import control_imports
+if control_imports.USE_OSS and control_imports.OSS_APP:
+ from tensorflow.python.platform.default._app import *
+else:
+ from tensorflow.python.platform.google._app import *
+
+# Import 'flags' into this module
+from tensorflow.python.platform import flags
diff --git a/tensorflow/python/platform/base.i b/tensorflow/python/platform/base.i
new file mode 100644
index 0000000000..85fa3968a1
--- /dev/null
+++ b/tensorflow/python/platform/base.i
@@ -0,0 +1,176 @@
+// Helper macros and typemaps for use in Tensorflow swig files.
+//
+%{
+ #include <memory>
+ #include "tensorflow/core/platform/port.h"
+ using tensorflow::uint64;
+ using tensorflow::string;
+
+ template<class T>
+ bool _PyObjAs(PyObject *pystr, T* cstr) {
+ T::undefined; // You need to define specialization _PyObjAs<T>
+ }
+
+ template<class T>
+ PyObject *_PyObjFrom(const T& c) {
+ T::undefined; // You need to define specialization _PyObjFrom<T>
+ }
+
+#ifdef HAS_GLOBAL_STRING
+ template<>
+ bool _PyObjAs(PyObject *pystr, ::string* cstr) {
+ char *buf;
+ Py_ssize_t len;
+#if PY_VERSION_HEX >= 0x03030000
+ if (PyUnicode_Check(pystr)) {
+ buf = PyUnicode_AsUTF8AndSize(pystr, &len);
+ if (!buf) return false;
+ } else // NOLINT
+#endif
+ if (PyBytes_AsStringAndSize(pystr, &buf, &len) == -1) return false;
+ if (cstr) cstr->assign(buf, len);
+ return true;
+ }
+#endif
+ template<>
+ bool _PyObjAs(PyObject *pystr, std::string* cstr) {
+ char *buf;
+ Py_ssize_t len;
+#if PY_VERSION_HEX >= 0x03030000
+ if (PyUnicode_Check(pystr)) {
+ buf = PyUnicode_AsUTF8AndSize(pystr, &len);
+ if (!buf) return false;
+ } else // NOLINT
+#endif
+ if (PyBytes_AsStringAndSize(pystr, &buf, &len) == -1) return false;
+ if (cstr) cstr->assign(buf, len);
+ return true;
+ }
+#ifdef HAS_GLOBAL_STRING
+ template<>
+ PyObject* _PyObjFrom(const ::string& c) {
+ return PyString_FromStringAndSize(c.data(), c.size());
+ }
+#endif
+ template<>
+ PyObject* _PyObjFrom(const std::string& c) {
+ return PyString_FromStringAndSize(c.data(), c.size());
+ }
+
+ PyObject* _SwigString_FromString(const string& s) {
+ return PyUnicode_FromStringAndSize(s.data(), s.size());
+ }
+%}
+
+%typemap(in) string {
+ if (!_PyObjAs<string>($input, &$1)) return NULL;
+}
+
+%typemap(in) const string& (string temp) {
+ if (!_PyObjAs<string>($input, &temp)) return NULL;
+ $1 = &temp;
+}
+
+%typemap(out) string {
+ $result = PyString_FromStringAndSize($1.data(), $1.size());
+}
+
+%typemap(out) const string& {
+ $result = PyString_FromStringAndSize($1->data(), $1->size());
+}
+
+%typemap(in, numinputs = 0) string* OUTPUT (string temp) {
+ $1 = &temp;
+}
+
+%typemap(argout) string * OUTPUT {
+ PyObject *str = PyString_FromStringAndSize($1->data(), $1->length());
+ if (!str) SWIG_fail;
+ %append_output(str);
+}
+
+%typemap(argout) string* INOUT = string* OUTPUT;
+
+%typemap(varout) string {
+ $result = PyString_FromStringAndSize($1.data(), $1.size());
+}
+
+%define _LIST_OUTPUT_TYPEMAP(type, py_converter)
+ %typemap(in) std::vector<type>(std::vector<type> temp) {
+ if (!vector_input_helper($input, &temp, _PyObjAs<type>)) {
+ if (!PyErr_Occurred())
+ PyErr_SetString(PyExc_TypeError, "sequence(type) expected");
+ return NULL;
+ }
+ $1 = temp;
+}
+%typemap(in) const std::vector<type>& (std::vector<type> temp),
+ const std::vector<type>* (std::vector<type> temp) {
+ if (!vector_input_helper($input, &temp, _PyObjAs<type>)) {
+ if (!PyErr_Occurred())
+ PyErr_SetString(PyExc_TypeError, "sequence(type) expected");
+ return NULL;
+ }
+ $1 = &temp;
+}
+%typemap(in,numinputs=0)
+std::vector<type>* OUTPUT (std::vector<type> temp),
+ hash_set<type>* OUTPUT (hash_set<type> temp),
+ set<type>* OUTPUT (set<type> temp) {
+ $1 = &temp;
+}
+%typemap(argout) std::vector<type>* OUTPUT, set<type>* OUTPUT, hash_set<type>* OUTPUT {
+ %append_output(list_output_helper($1, &py_converter));
+}
+%typemap(out) std::vector<type> {
+ $result = vector_output_helper(&$1, &py_converter);
+}
+%typemap(out) std::vector<type>*, const std::vector<type>& {
+ $result = vector_output_helper($1, &py_converter);
+}
+%enddef
+
+_LIST_OUTPUT_TYPEMAP(string, _SwigString_FromString);
+_LIST_OUTPUT_TYPEMAP(unsigned long long, PyLong_FromUnsignedLongLong);
+
+%typemap(in) uint64 {
+ // TODO(gps): Check if another implementation
+ // from hosting/images/util/image-hosting-utils.swig is better. May be not.
+%#if PY_MAJOR_VERSION < 3
+ if (PyInt_Check($input)) {
+ $1 = static_cast<uint64>(PyInt_AsLong($input));
+ } else
+%#endif
+ if (PyLong_Check($input)) {
+ $1 = static_cast<uint64>(PyLong_AsUnsignedLongLong($input));
+ } else {
+ PyErr_SetString(PyExc_TypeError,
+ "int or long value expected for argument \"$1_name\"");
+ }
+ // TODO(mrovner): Make consistent use of SWIG_fail vs. return NULL.
+ if (PyErr_Occurred()) return NULL;
+}
+
+%define _COPY_TYPEMAPS(oldtype, newtype)
+ typedef oldtype newtype;
+%apply oldtype * OUTPUT { newtype * OUTPUT };
+%apply oldtype & OUTPUT { newtype & OUTPUT };
+%apply oldtype * INPUT { newtype * INPUT };
+%apply oldtype & INPUT { newtype & INPUT };
+%apply oldtype * INOUT { newtype * INOUT };
+%apply oldtype & INOUT { newtype & INOUT };
+%apply std::vector<oldtype> * OUTPUT { std::vector<newtype> * OUTPUT };
+%enddef
+
+_COPY_TYPEMAPS(unsigned long long, uint64);
+
+// SWIG macros for explicit API declaration.
+// Usage:
+//
+// %ignoreall
+// %unignore SomeName; // namespace / class / method
+// %include "somelib.h"
+// %unignoreall // mandatory closing "bracket"
+%define %ignoreall %ignore ""; %enddef
+%define %unignore %rename("%s") %enddef
+%define %unignoreall %rename("%s") ""; %enddef
diff --git a/tensorflow/python/platform/control_imports.py b/tensorflow/python/platform/control_imports.py
new file mode 100644
index 0000000000..713caf3f4f
--- /dev/null
+++ b/tensorflow/python/platform/control_imports.py
@@ -0,0 +1,13 @@
+"""Switch between Google or open source dependencies."""
+# Switch between Google and OSS dependencies
+USE_OSS = True
+
+# Per-dependency switches determining whether each dependency is ready
+# to be replaced by its OSS equivalence.
+# TODO(danmane,mrry,opensource): Flip these switches, then remove them
+OSS_APP = True
+OSS_FLAGS = True
+OSS_GFILE = True
+OSS_GOOGLETEST = True
+OSS_LOGGING = True
+OSS_PARAMETERIZED = True
diff --git a/tensorflow/python/platform/default/__init__.py b/tensorflow/python/platform/default/__init__.py
new file mode 100755
index 0000000000..e69de29bb2
--- /dev/null
+++ b/tensorflow/python/platform/default/__init__.py
diff --git a/tensorflow/python/platform/default/_app.py b/tensorflow/python/platform/default/_app.py
new file mode 100644
index 0000000000..5917d00ce3
--- /dev/null
+++ b/tensorflow/python/platform/default/_app.py
@@ -0,0 +1,11 @@
+"""Generic entry point script."""
+import sys
+
+from tensorflow.python.platform import flags
+
+
+def run():
+ f = flags.FLAGS
+ f._parse_flags()
+ main = sys.modules['__main__'].main
+ sys.exit(main(sys.argv))
diff --git a/tensorflow/python/platform/default/_flags.py b/tensorflow/python/platform/default/_flags.py
new file mode 100644
index 0000000000..ceccda6e5c
--- /dev/null
+++ b/tensorflow/python/platform/default/_flags.py
@@ -0,0 +1,92 @@
+"""Implementation of the flags interface."""
+import tensorflow.python.platform
+
+import argparse
+
+_global_parser = argparse.ArgumentParser()
+
+class _FlagValues(object):
+
+ def __init__(self):
+ """Global container and accessor for flags and their values."""
+ self.__dict__['__flags'] = {}
+ self.__dict__['__parsed'] = False
+
+ def _parse_flags(self):
+ result = _global_parser.parse_args()
+ for flag_name, val in vars(result).items():
+ self.__dict__['__flags'][flag_name] = val
+ self.__dict__['__parsed'] = True
+
+ def __getattr__(self, name):
+ """Retrieves the 'value' attribute of the flag --name."""
+ if not self.__dict__['__parsed']:
+ self._parse_flags()
+ if name not in self.__dict__['__flags']:
+ raise AttributeError(name)
+ return self.__dict__['__flags'][name]
+
+ def __setattr__(self, name, value):
+ """Sets the 'value' attribute of the flag --name."""
+ if not self.__dict__['__parsed']:
+ self._parse_flags()
+ self.__dict__['__flags'][name] = value
+
+
+def _define_helper(flag_name, default_value, docstring, flagtype):
+ """Registers 'flag_name' with 'default_value' and 'docstring'."""
+ _global_parser.add_argument("--" + flag_name,
+ default=default_value,
+ help=docstring,
+ type=flagtype)
+
+
+# Provides the global object that can be used to access flags.
+FLAGS = _FlagValues()
+
+
+def DEFINE_string(flag_name, default_value, docstring):
+ """Defines a flag of type 'string'.
+
+ Args:
+ flag_name: The name of the flag as a string.
+ default_value: The default value the flag should take as a string.
+ docstring: A helpful message explaining the use of the flag.
+ """
+ _define_helper(flag_name, default_value, docstring, str)
+
+
+def DEFINE_integer(flag_name, default_value, docstring):
+ """Defines a flag of type 'int'.
+
+ Args:
+ flag_name: The name of the flag as a string.
+ default_value: The default value the flag should take as an int.
+ docstring: A helpful message explaining the use of the flag.
+ """
+ _define_helper(flag_name, default_value, docstring, int)
+
+
+def DEFINE_boolean(flag_name, default_value, docstring):
+ """Defines a flag of type 'boolean'.
+
+ Args:
+ flag_name: The name of the flag as a string.
+ default_value: The default value the flag should take as a boolean.
+ docstring: A helpful message explaining the use of the flag.
+ """
+ _define_helper(flag_name, default_value, docstring, bool)
+ _global_parser.add_argument('--no' + flag_name,
+ action='store_false',
+ dest=flag_name)
+
+
+def DEFINE_float(flag_name, default_value, docstring):
+ """Defines a flag of type 'float'.
+
+ Args:
+ flag_name: The name of the flag as a string.
+ default_value: The default value the flag should take as a float.
+ docstring: A helpful message explaining the use of the flag.
+ """
+ _define_helper(flag_name, default_value, docstring, float)
diff --git a/tensorflow/python/platform/default/_gfile.py b/tensorflow/python/platform/default/_gfile.py
new file mode 100644
index 0000000000..cfd25bdf90
--- /dev/null
+++ b/tensorflow/python/platform/default/_gfile.py
@@ -0,0 +1,404 @@
+"""File processing utilities."""
+
+import errno
+import functools
+import glob as _glob
+import os
+import shutil
+import threading
+
+
+class FileError(IOError):
+ """An error occurred while reading or writing a file."""
+
+
+class GOSError(OSError):
+ """An error occurred while finding a file or in handling pathnames."""
+
+
+class _GFileBase(object):
+ """Base I/O wrapper class. Similar semantics to Python's file object."""
+
+ # pylint: disable=protected-access
+ def _error_wrapper(fn):
+ """Decorator wrapping GFileBase class method errors."""
+ @functools.wraps(fn) # Preserve methods' __doc__
+ def wrap(self, *args, **kwargs):
+ try:
+ return fn(self, *args, **kwargs)
+ except ValueError, e:
+ # Sometimes a ValueError is raised, e.g., a read() on a closed file.
+ raise FileError(errno.EIO, e.message, self._name)
+ except IOError, e:
+ e.filename = self._name
+ raise FileError(e)
+ except OSError, e:
+ raise GOSError(e)
+ return wrap
+
+ def _synchronized(fn):
+ """Synchronizes file I/O for methods in GFileBase."""
+ @functools.wraps(fn)
+ def sync(self, *args, **kwargs):
+ # Sometimes a GFileBase method is called before the instance
+ # has been properly initialized. Check that _locker is available.
+ if hasattr(self, '_locker'): self._locker.lock()
+ try:
+ return fn(self, *args, **kwargs)
+ finally:
+ if hasattr(self, '_locker'): self._locker.unlock()
+ return sync
+ # pylint: enable=protected-access
+
+ @_error_wrapper
+ def __init__(self, name, mode, locker):
+ """Create the GFileBase object with the given filename, mode, and locker.
+
+ Args:
+ name: string, the filename.
+ mode: string, the mode to open the file with (e.g. "r", "w", "a+").
+ locker: the thread locking object (e.g. _PythonLocker) for controlling
+ thread access to the I/O methods of this class.
+ """
+ self._name = name
+ self._mode = mode
+ self._locker = locker
+ self._fp = open(name, mode)
+
+ def __enter__(self):
+ """Make GFileBase usable with "with" statement."""
+ return self
+
+ def __exit__(self, unused_type, unused_value, unused_traceback):
+ """Make GFileBase usable with "with" statement."""
+ self.close()
+
+ @_error_wrapper
+ @_synchronized
+ def __del__(self):
+ # __del__ is sometimes called before initialization, in which
+ # case the object is not fully constructed. Check for this here
+ # before trying to close the file handle.
+ if hasattr(self, '_fp'): self._fp.close()
+
+ @_error_wrapper
+ @_synchronized
+ def flush(self):
+ """Flush the underlying file handle."""
+ return self._fp.flush()
+
+ @property
+ @_error_wrapper
+ @_synchronized
+ def closed(self):
+ """Returns "True" if the file handle is closed. Otherwise False."""
+ return self._fp.closed
+
+ @_error_wrapper
+ @_synchronized
+ def write(self, data):
+ """Write data to the underlying file handle.
+
+ Args:
+ data: The string to write to the file handle.
+ """
+ self._fp.write(data)
+
+ @_error_wrapper
+ @_synchronized
+ def writelines(self, seq):
+ """Write a sequence of strings to the underlying file handle."""
+ self._fp.writelines(seq)
+
+ @_error_wrapper
+ @_synchronized
+ def tell(self):
+ """Return the location from the underlying file handle.
+
+ Returns:
+ An integer location (which can be used in e.g., seek).
+ """
+ return self._fp.tell()
+
+ @_error_wrapper
+ @_synchronized
+ def seek(self, offset, whence=0):
+ """Seek to offset (conditioned on whence) in the underlying file handle.
+
+ Args:
+ offset: int, the offset within the file to seek to.
+ whence: 0, 1, or 2. See python's seek() documentation for details.
+ """
+ self._fp.seek(offset, whence)
+
+ @_error_wrapper
+ @_synchronized
+ def truncate(self, new_size=None):
+ """Truncate the underlying file handle to new_size.
+
+ Args:
+ new_size: Size after truncation. If None, the file handle is truncated
+ to 0 bytes.
+ """
+ self._fp.truncate(new_size)
+
+ @_error_wrapper
+ @_synchronized
+ def readline(self, max_length=-1):
+ """Read a single line (up to max_length) from the underlying file handle.
+
+ Args:
+ max_length: The maximum number of chsaracters to read.
+
+ Returns:
+ A string, including any newline at the end, or empty string if at EOF.
+ """
+ return self._fp.readline(max_length)
+
+ @_error_wrapper
+ @_synchronized
+ def readlines(self, sizehint=None):
+ """Read lines from the underlying file handle.
+
+ Args:
+ sizehint: See the python file.readlines() documentation.
+
+ Returns:
+ A list of strings from the underlying file handle.
+ """
+ if sizehint is not None:
+ return self._fp.readlines(sizehint)
+ else:
+ return self._fp.readlines()
+
+ def __iter__(self):
+ """Enable line iteration on the underlying handle (not synchronized)."""
+ return self
+
+ # Not synchronized
+ @_error_wrapper
+ def next(self):
+ """Enable line iteration on the underlying handle (not synchronized).
+
+ Returns:
+ An line iterator from the underlying handle.
+
+ Example:
+ # read a file's lines by consuming the iterator with a list
+ with open("filename", "r") as fp: lines = list(fp)
+ """
+ return self._fp.next()
+
+ @_error_wrapper
+ @_synchronized
+ def Size(self): # pylint: disable=invalid-name
+ """Get byte size of the file from the underlying file handle."""
+ cur = self.tell()
+ try:
+ self.seek(0, 2)
+ size = self.tell()
+ finally:
+ self.seek(cur)
+ return size
+
+ @_error_wrapper
+ @_synchronized
+ def read(self, n=-1):
+ """Read n bytes from the underlying file handle.
+
+ Args:
+ n: Number of bytes to read (if negative, read to end of file handle.)
+
+ Returns:
+ A string of the bytes read, up to the end of file.
+ """
+ return self._fp.read(n)
+
+ @_error_wrapper
+ @_synchronized
+ def close(self):
+ """Close the underlying file handle."""
+ self._fp.close()
+
+ # Declare wrappers as staticmethods at the end so that we can
+ # use them as decorators.
+ _error_wrapper = staticmethod(_error_wrapper)
+ _synchronized = staticmethod(_synchronized)
+
+
+class GFile(_GFileBase):
+ """File I/O wrappers with thread locking."""
+
+ def __init__(self, name, mode='r'):
+ super(GFile, self).__init__(name, mode, _Pythonlocker())
+
+
+class FastGFile(_GFileBase):
+ """File I/O wrappers without thread locking."""
+
+ def __init__(self, name, mode='r'):
+ super(FastGFile, self).__init__(name, mode, _Nulllocker())
+
+
+# locker classes. Note that locks must be reentrant, so that multiple
+# lock() calls by the owning thread will not block.
+class _Pythonlocker(object):
+ """A locking strategy that uses standard locks from the thread module."""
+
+ def __init__(self):
+ self._lock = threading.RLock()
+
+ def lock(self):
+ self._lock.acquire()
+
+ def unlock(self):
+ self._lock.release()
+
+
+class _Nulllocker(object):
+ """A locking strategy where lock() and unlock() methods are no-ops."""
+
+ def lock(self):
+ pass
+
+ def unlock(self):
+ pass
+
+
+def _func_error_wrapper(fn):
+ """Decorator wrapping function errors."""
+ @functools.wraps(fn) # Preserve methods' __doc__
+ def wrap(*args, **kwargs):
+ try:
+ return fn(*args, **kwargs)
+ except ValueError, e:
+ raise FileError(errno.EIO, e.message)
+ except IOError, e:
+ raise FileError(e)
+ except OSError, e:
+ raise GOSError(e)
+ return wrap
+
+
+@_func_error_wrapper
+def Exists(path): # pylint: disable=invalid-name
+ """Retruns True iff "path" exists (as a dir, file, non-broken symlink)."""
+ return os.path.exists(path)
+
+
+@_func_error_wrapper
+def IsDirectory(path): # pylint: disable=invalid-name
+ """Return True iff "path" exists and is a directory."""
+ return os.path.isdir(path)
+
+
+@_func_error_wrapper
+def Glob(glob): # pylint: disable=invalid-name
+ """Return a list of filenames matching the glob "glob"."""
+ return _glob.glob(glob)
+
+
+@_func_error_wrapper
+def MkDir(path, mode=0755): # pylint: disable=invalid-name
+ """Create the directory "path" with the given mode.
+
+ Args:
+ path: The directory path
+ mode: The file mode for the directory
+
+ Returns:
+ None
+
+ Raises:
+ GOSError: if the path already exists
+ """
+ os.mkdir(path, mode)
+
+
+@_func_error_wrapper
+def MakeDirs(path, mode=0755): # pylint: disable=invalid-name
+ """Recursively create the directory "path" with the given mode.
+
+ Args:
+ path: The directory path
+ mode: The file mode for the created directories
+
+ Returns:
+ None
+
+
+ Raises:
+ GOSError: if the path already exists
+ """
+ os.makedirs(path, mode)
+
+
+@_func_error_wrapper
+def RmDir(directory): # pylint: disable=invalid-name
+ """Removes the directory "directory" iff the directory is empty.
+
+ Args:
+ directory: The directory to remove.
+
+ Raises:
+ GOSError: If the directory does not exist or is not empty.
+ """
+ os.rmdir(directory)
+
+
+@_func_error_wrapper
+def Remove(path): # pylint: disable=invalid-name
+ """Delete the (non-directory) file "path".
+
+ Args:
+ path: The file to remove.
+
+ Raises:
+ GOSError: If "path" does not exist, is a directory, or cannot be deleted.
+ """
+ os.remove(path)
+
+
+@_func_error_wrapper
+def DeleteRecursively(path): # pylint: disable=invalid-name
+ """Delete the file or directory "path" recursively.
+
+ Args:
+ path: The path to remove (may be a non-empty directory).
+
+ Raises:
+ GOSError: If the path does not exist or cannot be deleted.
+ """
+ if IsDirectory(path):
+ shutil.rmtree(path)
+ else:
+ Remove(path)
+
+
+@_func_error_wrapper
+def ListDirectory(directory, return_dotfiles=False): # pylint: disable=invalid-name
+ """Returns a list of files in dir.
+
+ As with the standard os.listdir(), the filenames in the returned list will be
+ the basenames of the files in dir (not absolute paths). To get a list of
+ absolute paths of files in a directory, a client could do:
+ file_list = gfile.ListDir(my_dir)
+ file_list = [os.path.join(my_dir, f) for f in file_list]
+ (assuming that my_dir itself specified an absolute path to a directory).
+
+ Args:
+ directory: the directory to list
+ return_dotfiles: if True, dotfiles will be returned as well. Even if
+ this arg is True, '.' and '..' will not be returned.
+
+ Returns:
+ ['list', 'of', 'files']. The entries '.' and '..' are never returned.
+ Other entries starting with a dot will only be returned if return_dotfiles
+ is True.
+ Raises:
+ GOSError: if there is an error retrieving the directory listing.
+ """
+ files = os.listdir(directory)
+ if not return_dotfiles:
+ files = [f for f in files if not f.startswith('.')]
+ return files
diff --git a/tensorflow/python/platform/default/_googletest.py b/tensorflow/python/platform/default/_googletest.py
new file mode 100644
index 0000000000..d2686565a0
--- /dev/null
+++ b/tensorflow/python/platform/default/_googletest.py
@@ -0,0 +1,68 @@
+"""Imports unittest as a replacement for testing.pybase.googletest."""
+import inspect
+import itertools
+import os
+import tempfile
+
+# pylint: disable=wildcard-import
+from unittest import *
+
+
+unittest_main = main
+
+
+# pylint: disable=invalid-name
+# pylint: disable=undefined-variable
+def main(*args, **kwargs):
+ """Delegate to unittest.main after redefining testLoader."""
+ if 'TEST_SHARD_STATUS_FILE' in os.environ:
+ try:
+ f = None
+ try:
+ f = open(os.environ['TEST_SHARD_STATUS_FILE'], 'w')
+ f.write('')
+ except IOError:
+ sys.stderr.write('Error opening TEST_SHARD_STATUS_FILE (%s). Exiting.'
+ % os.environ['TEST_SHARD_STATUS_FILE'])
+ sys.exit(1)
+ finally:
+ if f is not None: f.close()
+
+ if ('TEST_TOTAL_SHARDS' not in os.environ or
+ 'TEST_SHARD_INDEX' not in os.environ):
+ return unittest_main(*args, **kwargs)
+
+ total_shards = int(os.environ['TEST_TOTAL_SHARDS'])
+ shard_index = int(os.environ['TEST_SHARD_INDEX'])
+ base_loader = TestLoader()
+
+ delegate_get_names = base_loader.getTestCaseNames
+ bucket_iterator = itertools.cycle(range(total_shards))
+
+ def getShardedTestCaseNames(testCaseClass):
+ filtered_names = []
+ for testcase in sorted(delegate_get_names(testCaseClass)):
+ bucket = bucket_iterator.next()
+ if bucket == shard_index:
+ filtered_names.append(testcase)
+ return filtered_names
+
+ # Override getTestCaseNames
+ base_loader.getTestCaseNames = getShardedTestCaseNames
+
+ kwargs['testLoader'] = base_loader
+ unittest_main(*args, **kwargs)
+
+
+def GetTempDir():
+ first_frame = inspect.stack()[-1][0]
+ temp_dir = os.path.join(
+ tempfile.gettempdir(), os.path.basename(inspect.getfile(first_frame)))
+ temp_dir = temp_dir.rstrip('.py')
+ if not os.path.isdir(temp_dir):
+ os.mkdir(temp_dir, 0755)
+ return temp_dir
+
+
+def StatefulSessionAvailable():
+ return False
diff --git a/tensorflow/python/platform/default/_init.py b/tensorflow/python/platform/default/_init.py
new file mode 100644
index 0000000000..916d598856
--- /dev/null
+++ b/tensorflow/python/platform/default/_init.py
@@ -0,0 +1 @@
+# Nothing to do for default platform
diff --git a/tensorflow/python/platform/default/_logging.py b/tensorflow/python/platform/default/_logging.py
new file mode 100644
index 0000000000..2e289b1abe
--- /dev/null
+++ b/tensorflow/python/platform/default/_logging.py
@@ -0,0 +1,182 @@
+"""Logging utilities."""
+# pylint: disable=unused-import
+# pylint: disable=g-bad-import-order
+# pylint: disable=invalid-name
+import os
+import sys
+import time
+import thread
+from logging import getLogger
+from logging import log
+from logging import debug
+from logging import error
+from logging import fatal
+from logging import info
+from logging import warn
+from logging import warning
+from logging import DEBUG
+from logging import ERROR
+from logging import FATAL
+from logging import INFO
+from logging import WARN
+
+# Controls which methods from pyglib.logging are available within the project
+# Do not add methods here without also adding to platform/default/_logging.py
+__all__ = ['log', 'debug', 'error', 'fatal', 'info', 'warn', 'warning',
+ 'DEBUG', 'ERROR', 'FATAL', 'INFO', 'WARN',
+ 'flush', 'log_every_n', 'log_first_n', 'vlog',
+ 'TaskLevelStatusMessage', 'get_verbosity', 'set_verbosity']
+
+warning = warn
+
+_level_names = {
+ FATAL: 'FATAL',
+ ERROR: 'ERROR',
+ WARN: 'WARN',
+ INFO: 'INFO',
+ DEBUG: 'DEBUG',
+}
+
+# Mask to convert integer thread ids to unsigned quantities for logging
+# purposes
+_THREAD_ID_MASK = 2 * sys.maxint + 1
+
+_log_prefix = None # later set to google2_log_prefix
+
+# Counter to keep track of number of log entries per token.
+_log_counter_per_token = {}
+
+
+def TaskLevelStatusMessage(msg):
+ error(msg)
+
+
+def flush():
+ raise NotImplementedError()
+
+
+# Code below is taken from pyglib/logging
+def vlog(level, msg, *args, **kwargs):
+ log(level, msg, *args, **kwargs)
+
+
+def _GetNextLogCountPerToken(token):
+ """Wrapper for _log_counter_per_token.
+
+ Args:
+ token: The token for which to look up the count.
+
+ Returns:
+ The number of times this function has been called with
+ *token* as an argument (starting at 0)
+ """
+ global _log_counter_per_token # pylint: disable=global-variable-not-assigned
+ _log_counter_per_token[token] = 1 + _log_counter_per_token.get(token, -1)
+ return _log_counter_per_token[token]
+
+
+def log_every_n(level, msg, n, *args):
+ """Log 'msg % args' at level 'level' once per 'n' times.
+
+ Logs the 1st call, (N+1)st call, (2N+1)st call, etc.
+ Not threadsafe.
+
+ Args:
+ level: The level at which to log.
+ msg: The message to be logged.
+ n: The number of times this should be called before it is logged.
+ *args: The args to be substituted into the msg.
+ """
+ count = _GetNextLogCountPerToken(_GetFileAndLine())
+ log_if(level, msg, not (count % n), *args)
+
+
+def log_first_n(level, msg, n, *args): # pylint: disable=g-bad-name
+ """Log 'msg % args' at level 'level' only first 'n' times.
+
+ Not threadsafe.
+
+ Args:
+ level: The level at which to log.
+ msg: The message to be logged.
+ n: The number of times this should be called before it is logged.
+ *args: The args to be substituted into the msg.
+ """
+ count = _GetNextLogCountPerToken(_GetFileAndLine())
+ log_if(level, msg, count < n, *args)
+
+
+def log_if(level, msg, condition, *args):
+ """Log 'msg % args' at level 'level' only if condition is fulfilled."""
+ if condition:
+ vlog(level, msg, *args)
+
+
+def _GetFileAndLine():
+ """Returns (filename, linenumber) for the stack frame."""
+ # Use sys._getframe(). This avoids creating a traceback object.
+ # pylint: disable=protected-access
+ f = sys._getframe()
+ # pylint: enable=protected-access
+ our_file = f.f_code.co_filename
+ f = f.f_back
+ while f:
+ code = f.f_code
+ if code.co_filename != our_file:
+ return (code.co_filename, f.f_lineno)
+ f = f.f_back
+ return ('<unknown>', 0)
+
+
+def google2_log_prefix(level, timestamp=None, file_and_line=None):
+ """Assemble a logline prefix using the google2 format."""
+ # pylint: disable=global-variable-not-assigned
+ global _level_names
+ global _logfile_map, _logfile_map_mutex
+ # pylint: enable=global-variable-not-assigned
+
+ # Record current time
+ now = timestamp or time.time()
+ now_tuple = time.localtime(now)
+ now_microsecond = int(1e6 * (now % 1.0))
+
+ (filename, line) = file_and_line or _GetFileAndLine()
+ basename = os.path.basename(filename)
+
+ # Severity string
+ severity = 'I'
+ if level in _level_names:
+ severity = _level_names[level][0]
+
+ s = '%c%02d%02d %02d:%02d:%02d.%06d %5d %s:%d] ' % (
+ severity,
+ now_tuple[1], # month
+ now_tuple[2], # day
+ now_tuple[3], # hour
+ now_tuple[4], # min
+ now_tuple[5], # sec
+ now_microsecond,
+ _get_thread_id(),
+ basename,
+ line)
+
+ return s
+
+
+def get_verbosity():
+ """Return how much logging output will be produced."""
+ return getLogger().getEffectiveLevel()
+
+
+def set_verbosity(verbosity):
+ """Sets the threshold for what messages will be logged."""
+ getLogger().setLevel(verbosity)
+
+
+def _get_thread_id():
+ """Get id of current thread, suitable for logging as an unsigned quantity."""
+ thread_id = thread.get_ident()
+ return thread_id & _THREAD_ID_MASK
+
+
+_log_prefix = google2_log_prefix
diff --git a/tensorflow/python/platform/default/_parameterized.py b/tensorflow/python/platform/default/_parameterized.py
new file mode 100644
index 0000000000..5d141568ed
--- /dev/null
+++ b/tensorflow/python/platform/default/_parameterized.py
@@ -0,0 +1,2 @@
+"""Extension to unittest to run parameterized tests."""
+raise ImportError("Not implemented yet.")
diff --git a/tensorflow/python/platform/default/_resource_loader.py b/tensorflow/python/platform/default/_resource_loader.py
new file mode 100644
index 0000000000..69f425072f
--- /dev/null
+++ b/tensorflow/python/platform/default/_resource_loader.py
@@ -0,0 +1,26 @@
+"""Read a file and return its contents."""
+
+import os.path
+
+from tensorflow.python.platform import logging
+
+
+def load_resource(path):
+ """Load the resource at given path, where path is relative to tensorflow/.
+
+ Args:
+ path: a string resource path relative to tensorflow/.
+
+ Returns:
+ The contents of that resource.
+
+ Raises:
+ IOError: If the path is not found, or the resource can't be opened.
+ """
+ path = os.path.join('tensorflow', path)
+ path = os.path.abspath(path)
+ try:
+ with open(path, 'rb') as f:
+ return f.read()
+ except IOError as e:
+ logging.warning('IOError %s on path %s' % (e, path))
diff --git a/tensorflow/python/platform/default/_status_bar.py b/tensorflow/python/platform/default/_status_bar.py
new file mode 100644
index 0000000000..2953908724
--- /dev/null
+++ b/tensorflow/python/platform/default/_status_bar.py
@@ -0,0 +1,5 @@
+"""A no-op implementation of status bar functions."""
+
+
+def SetupStatusBarInsideGoogle(unused_link_text, unused_port):
+ pass
diff --git a/tensorflow/python/platform/default/flags_test.py b/tensorflow/python/platform/default/flags_test.py
new file mode 100644
index 0000000000..1b15ca138a
--- /dev/null
+++ b/tensorflow/python/platform/default/flags_test.py
@@ -0,0 +1,53 @@
+"""Tests for our flags implementation."""
+import sys
+
+from tensorflow.python.platform.default import _googletest as googletest
+
+from tensorflow.python.platform.default import _flags as flags
+
+
+flags.DEFINE_string("string_foo", "default_val", "HelpString")
+flags.DEFINE_boolean("bool_foo", True, "HelpString")
+flags.DEFINE_integer("int_foo", 42, "HelpString")
+flags.DEFINE_float("float_foo", 42.0, "HelpString")
+
+FLAGS = flags.FLAGS
+
+class FlagsTest(googletest.TestCase):
+
+ def testString(self):
+ res = FLAGS.string_foo
+ self.assertEqual(res, "default_val")
+ FLAGS.string_foo = "bar"
+ self.assertEqual("bar", FLAGS.string_foo)
+
+ def testBool(self):
+ res = FLAGS.bool_foo
+ self.assertTrue(res)
+ FLAGS.bool_foo = False
+ self.assertFalse(FLAGS.bool_foo)
+
+ def testNoBool(self):
+ FLAGS.bool_foo = True
+ try:
+ sys.argv.append("--nobool_foo")
+ FLAGS._parse_flags()
+ self.assertFalse(FLAGS.bool_foo)
+ finally:
+ sys.argv.pop()
+
+ def testInt(self):
+ res = FLAGS.int_foo
+ self.assertEquals(res, 42)
+ FLAGS.int_foo = -1
+ self.assertEqual(-1, FLAGS.int_foo)
+
+ def testFloat(self):
+ res = FLAGS.float_foo
+ self.assertEquals(42.0, res)
+ FLAGS.float_foo = -1.0
+ self.assertEqual(-1.0, FLAGS.float_foo)
+
+
+if __name__ == "__main__":
+ googletest.main()
diff --git a/tensorflow/python/platform/default/gfile_test.py b/tensorflow/python/platform/default/gfile_test.py
new file mode 100644
index 0000000000..9eec952e95
--- /dev/null
+++ b/tensorflow/python/platform/default/gfile_test.py
@@ -0,0 +1,147 @@
+import os
+import shutil
+
+from tensorflow.python.platform.default import _gfile as gfile
+from tensorflow.python.platform.default import _googletest as googletest
+from tensorflow.python.platform.default import _logging as logging
+
+
+class _BaseTest(object):
+
+ @property
+ def tmp(self):
+ return self._tmp_dir
+
+ def setUp(self):
+ self._orig_dir = os.getcwd()
+ self._tmp_dir = googletest.GetTempDir() + "/"
+ try:
+ os.makedirs(self._tmp_dir)
+ except OSError:
+ pass # Directory already exists
+
+ def tearDown(self):
+ try:
+ shutil.rmtree(self._tmp_dir)
+ except OSError:
+ logging.warn("[%s] Post-test directory cleanup failed: %s"
+ % (self, self._tmp_dir))
+
+
+class _GFileBaseTest(_BaseTest):
+
+ @property
+ def gfile(self):
+ raise NotImplementedError("Do not use _GFileBaseTest directly.")
+
+ def testWith(self):
+ with self.gfile(self.tmp + "test_with", "w") as fh:
+ fh.write("hi")
+ with self.gfile(self.tmp + "test_with", "r") as fh:
+ self.assertEquals(fh.read(), "hi")
+
+ def testSizeAndTellAndSeek(self):
+ with self.gfile(self.tmp + "test_tell", "w") as fh:
+ fh.write("".join(["0"] * 1000))
+ with self.gfile(self.tmp + "test_tell", "r") as fh:
+ self.assertEqual(1000, fh.Size())
+ self.assertEqual(0, fh.tell())
+ fh.seek(0, 2)
+ self.assertEqual(1000, fh.tell())
+ fh.seek(0)
+ self.assertEqual(0, fh.tell())
+
+ def testReadAndWritelines(self):
+ with self.gfile(self.tmp + "test_writelines", "w") as fh:
+ fh.writelines(["%d\n" % d for d in range(10)])
+ with self.gfile(self.tmp + "test_writelines", "r") as fh:
+ self.assertEqual(["%d\n" % x for x in range(10)], fh.readlines())
+
+ def testWriteAndTruncate(self):
+ with self.gfile(self.tmp + "test_truncate", "w") as fh:
+ fh.write("ababab")
+ with self.gfile(self.tmp + "test_truncate", "a+") as fh:
+ fh.seek(0, 2)
+ fh.write("hjhjhj")
+ with self.gfile(self.tmp + "test_truncate", "a+") as fh:
+ self.assertEqual(fh.Size(), 12)
+ fh.truncate(6)
+ with self.gfile(self.tmp + "test_truncate", "r") as fh:
+ self.assertEqual(fh.read(), "ababab")
+
+ def testErrors(self):
+ self.assertRaises(
+ gfile.FileError, lambda: self.gfile(self.tmp + "doesnt_exist", "r"))
+ with self.gfile(self.tmp + "test_error", "w") as fh:
+ self.assertRaises(gfile.FileError, lambda: fh.seek(-1))
+ # test_error now exists, we can read from it:
+ with self.gfile(self.tmp + "test_error", "r") as fh:
+ self.assertRaises(gfile.FileError, lambda: fh.write("ack"))
+ fh = self.gfile(self.tmp + "test_error", "w")
+ self.assertFalse(fh.closed)
+ fh.close()
+ self.assertTrue(fh.closed)
+ self.assertRaises(gfile.FileError, lambda: fh.write("ack"))
+
+ def testIteration(self):
+ with self.gfile(self.tmp + "test_iter", "w") as fh:
+ fh.writelines(["a\n", "b\n", "c\n"])
+ with self.gfile(self.tmp + "test_iter", "r") as fh:
+ lines = list(fh)
+ self.assertEqual(["a\n", "b\n", "c\n"], lines)
+
+
+class GFileTest(_GFileBaseTest, googletest.TestCase):
+
+ @property
+ def gfile(self):
+ return gfile.GFile
+
+
+class FastGFileTest(_GFileBaseTest, googletest.TestCase):
+
+ @property
+ def gfile(self):
+ return gfile.FastGFile
+
+
+class FunctionTests(_BaseTest, googletest.TestCase):
+
+ def testExists(self):
+ self.assertFalse(gfile.Exists(self.tmp + "test_exists"))
+ with gfile.GFile(self.tmp + "test_exists", "w"):
+ pass
+ self.assertTrue(gfile.Exists(self.tmp + "test_exists"))
+
+ def testMkDirsGlobAndRmDirs(self):
+ self.assertFalse(gfile.Exists(self.tmp + "test_dir"))
+ gfile.MkDir(self.tmp + "test_dir")
+ self.assertTrue(gfile.Exists(self.tmp + "test_dir"))
+ gfile.RmDir(self.tmp + "test_dir")
+ self.assertFalse(gfile.Exists(self.tmp + "test_dir"))
+ gfile.MakeDirs(self.tmp + "test_dir/blah0")
+ gfile.MakeDirs(self.tmp + "test_dir/blah1")
+ self.assertEqual([self.tmp + "test_dir/blah0", self.tmp + "test_dir/blah1"],
+ sorted(gfile.Glob(self.tmp + "test_dir/*")))
+ gfile.DeleteRecursively(self.tmp + "test_dir")
+ self.assertFalse(gfile.Exists(self.tmp + "test_dir"))
+
+ def testErrors(self):
+ self.assertRaises(
+ gfile.GOSError, lambda: gfile.RmDir(self.tmp + "dir_doesnt_exist"))
+ self.assertRaises(
+ gfile.GOSError, lambda: gfile.Remove(self.tmp + "file_doesnt_exist"))
+ gfile.MkDir(self.tmp + "error_dir")
+ with gfile.GFile(self.tmp + "error_dir/file", "w"):
+ pass # Create file
+ self.assertRaises(
+ gfile.GOSError, lambda: gfile.Remove(self.tmp + "error_dir"))
+ self.assertRaises(
+ gfile.GOSError, lambda: gfile.RmDir(self.tmp + "error_dir"))
+ self.assertTrue(gfile.Exists(self.tmp + "error_dir"))
+ gfile.DeleteRecursively(self.tmp + "error_dir")
+ self.assertFalse(gfile.Exists(self.tmp + "error_dir"))
+
+
+if __name__ == "__main__":
+ googletest.main()
diff --git a/tensorflow/python/platform/default/logging_test.py b/tensorflow/python/platform/default/logging_test.py
new file mode 100644
index 0000000000..fd492bc384
--- /dev/null
+++ b/tensorflow/python/platform/default/logging_test.py
@@ -0,0 +1,13 @@
+from tensorflow.python.platform.default import _googletest as googletest
+from tensorflow.python.platform.default import _logging as logging
+
+
+class EventLoaderTest(googletest.TestCase):
+
+ def test_log(self):
+ # Just check that logging works without raising an exception.
+ logging.error("test log message")
+
+
+if __name__ == "__main__":
+ googletest.main()
diff --git a/tensorflow/python/platform/flags.py b/tensorflow/python/platform/flags.py
new file mode 100644
index 0000000000..d5b12d26df
--- /dev/null
+++ b/tensorflow/python/platform/flags.py
@@ -0,0 +1,10 @@
+"""Switch between depending on pyglib.flags or open-source gflags."""
+# pylint: disable=unused-import
+# pylint: disable=g-import-not-at-top
+# pylint: disable=wildcard-import
+import tensorflow.python.platform
+import control_imports
+if control_imports.USE_OSS and control_imports.OSS_FLAGS:
+ from tensorflow.python.platform.default._flags import *
+else:
+ from tensorflow.python.platform.google._flags import *
diff --git a/tensorflow/python/platform/gfile.py b/tensorflow/python/platform/gfile.py
new file mode 100644
index 0000000000..fc28811821
--- /dev/null
+++ b/tensorflow/python/platform/gfile.py
@@ -0,0 +1,10 @@
+"""Switch between depending on pyglib.gfile or an OSS replacement."""
+# pylint: disable=unused-import
+# pylint: disable=g-import-not-at-top
+# pylint: disable=wildcard-import
+import tensorflow.python.platform
+import control_imports
+if control_imports.USE_OSS and control_imports.OSS_GFILE:
+ from tensorflow.python.platform.default._gfile import *
+else:
+ from tensorflow.python.platform.google._gfile import *
diff --git a/tensorflow/python/platform/googletest.py b/tensorflow/python/platform/googletest.py
new file mode 100644
index 0000000000..ca22ec6e6b
--- /dev/null
+++ b/tensorflow/python/platform/googletest.py
@@ -0,0 +1,10 @@
+"""Switch between depending on googletest or unittest."""
+# pylint: disable=unused-import
+# pylint: disable=g-import-not-at-top
+# pylint: disable=wildcard-import
+import tensorflow.python.platform
+import control_imports
+if control_imports.USE_OSS and control_imports.OSS_GOOGLETEST:
+ from tensorflow.python.platform.default._googletest import *
+else:
+ from tensorflow.python.platform.google._googletest import *
diff --git a/tensorflow/python/platform/logging.py b/tensorflow/python/platform/logging.py
new file mode 100644
index 0000000000..b6d2e53dd4
--- /dev/null
+++ b/tensorflow/python/platform/logging.py
@@ -0,0 +1,10 @@
+"""Switch between depending on pyglib.logging or regular logging."""
+# pylint: disable=unused-import
+# pylint: disable=g-import-not-at-top
+# pylint: disable=wildcard-import
+import tensorflow.python.platform
+import control_imports
+if control_imports.USE_OSS and control_imports.OSS_LOGGING:
+ from tensorflow.python.platform.default._logging import *
+else:
+ from tensorflow.python.platform.google._logging import *
diff --git a/tensorflow/python/platform/numpy.i b/tensorflow/python/platform/numpy.i
new file mode 100644
index 0000000000..217acd5bff
--- /dev/null
+++ b/tensorflow/python/platform/numpy.i
@@ -0,0 +1,3085 @@
+/* -*- C -*- (not really, but good for syntax highlighting) */
+#ifdef SWIGPYTHON
+
+%{
+#ifndef SWIG_FILE_WITH_INIT
+#define NO_IMPORT_ARRAY
+#endif
+#include "stdio.h"
+#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
+#include <numpy/arrayobject.h>
+%}
+
+/**********************************************************************/
+
+%fragment("NumPy_Backward_Compatibility", "header")
+{
+%#if NPY_API_VERSION < 0x00000007
+%#define NPY_ARRAY_DEFAULT NPY_DEFAULT
+%#define NPY_ARRAY_FARRAY NPY_FARRAY
+%#define NPY_FORTRANORDER NPY_FORTRAN
+%#endif
+}
+
+/**********************************************************************/
+
+/* The following code originally appeared in
+ * enthought/kiva/agg/src/numeric.i written by Eric Jones. It was
+ * translated from C++ to C by John Hunter. Bill Spotz has modified
+ * it to fix some minor bugs, upgrade from Numeric to numpy (all
+ * versions), add some comments and functionality, and convert from
+ * direct code insertion to SWIG fragments.
+ */
+
+%fragment("NumPy_Macros", "header")
+{
+/* Macros to extract array attributes.
+ */
+%#if NPY_API_VERSION < 0x00000007
+%#define is_array(a) ((a) && PyArray_Check((PyArrayObject*)a))
+%#define array_type(a) (int)(PyArray_TYPE((PyArrayObject*)a))
+%#define array_numdims(a) (((PyArrayObject*)a)->nd)
+%#define array_dimensions(a) (((PyArrayObject*)a)->dimensions)
+%#define array_size(a,i) (((PyArrayObject*)a)->dimensions[i])
+%#define array_strides(a) (((PyArrayObject*)a)->strides)
+%#define array_stride(a,i) (((PyArrayObject*)a)->strides[i])
+%#define array_data(a) (((PyArrayObject*)a)->data)
+%#define array_descr(a) (((PyArrayObject*)a)->descr)
+%#define array_flags(a) (((PyArrayObject*)a)->flags)
+%#define array_enableflags(a,f) (((PyArrayObject*)a)->flags) = f
+%#else
+%#define is_array(a) ((a) && PyArray_Check(a))
+%#define array_type(a) PyArray_TYPE((PyArrayObject*)a)
+%#define array_numdims(a) PyArray_NDIM((PyArrayObject*)a)
+%#define array_dimensions(a) PyArray_DIMS((PyArrayObject*)a)
+%#define array_strides(a) PyArray_STRIDES((PyArrayObject*)a)
+%#define array_stride(a,i) PyArray_STRIDE((PyArrayObject*)a,i)
+%#define array_size(a,i) PyArray_DIM((PyArrayObject*)a,i)
+%#define array_data(a) PyArray_DATA((PyArrayObject*)a)
+%#define array_descr(a) PyArray_DESCR((PyArrayObject*)a)
+%#define array_flags(a) PyArray_FLAGS((PyArrayObject*)a)
+%#define array_enableflags(a,f) PyArray_ENABLEFLAGS((PyArrayObject*)a,f)
+%#endif
+%#define array_is_contiguous(a) (PyArray_ISCONTIGUOUS((PyArrayObject*)a))
+%#define array_is_native(a) (PyArray_ISNOTSWAPPED((PyArrayObject*)a))
+%#define array_is_fortran(a) (PyArray_ISFORTRAN((PyArrayObject*)a))
+}
+
+/**********************************************************************/
+
+%fragment("NumPy_Utilities",
+ "header")
+{
+ /* Given a PyObject, return a string describing its type.
+ */
+ const char* pytype_string(PyObject* py_obj)
+ {
+ if (py_obj == NULL ) return "C NULL value";
+ if (py_obj == Py_None ) return "Python None" ;
+ if (PyCallable_Check(py_obj)) return "callable" ;
+ if (PyString_Check( py_obj)) return "string" ;
+ if (PyInt_Check( py_obj)) return "int" ;
+ if (PyFloat_Check( py_obj)) return "float" ;
+ if (PyDict_Check( py_obj)) return "dict" ;
+ if (PyList_Check( py_obj)) return "list" ;
+ if (PyTuple_Check( py_obj)) return "tuple" ;
+%#if PY_MAJOR_VERSION < 3
+ if (PyFile_Check( py_obj)) return "file" ;
+ if (PyModule_Check( py_obj)) return "module" ;
+ if (PyInstance_Check(py_obj)) return "instance" ;
+%#endif
+
+ return "unkown type";
+ }
+
+ /* Given a NumPy typecode, return a string describing the type.
+ */
+ const char* typecode_string(int typecode)
+ {
+ static const char* type_names[25] = {"bool",
+ "byte",
+ "unsigned byte",
+ "short",
+ "unsigned short",
+ "int",
+ "unsigned int",
+ "long",
+ "unsigned long",
+ "long long",
+ "unsigned long long",
+ "float",
+ "double",
+ "long double",
+ "complex float",
+ "complex double",
+ "complex long double",
+ "object",
+ "string",
+ "unicode",
+ "void",
+ "ntypes",
+ "notype",
+ "char",
+ "unknown"};
+ return typecode < 24 ? type_names[typecode] : type_names[24];
+ }
+
+ /* Make sure input has correct numpy type. This now just calls
+ PyArray_EquivTypenums().
+ */
+ int type_match(int actual_type,
+ int desired_type)
+ {
+ return PyArray_EquivTypenums(actual_type, desired_type);
+ }
+
+%#ifdef SWIGPY_USE_CAPSULE
+ void free_cap(PyObject * cap)
+ {
+ void* array = (void*) PyCapsule_GetPointer(cap,SWIGPY_CAPSULE_NAME);
+ if (array != NULL) free(array);
+ }
+%#endif
+
+
+}
+
+/**********************************************************************/
+
+%fragment("NumPy_Object_to_Array",
+ "header",
+ fragment="NumPy_Backward_Compatibility",
+ fragment="NumPy_Macros",
+ fragment="NumPy_Utilities")
+{
+ /* Given a PyObject pointer, cast it to a PyArrayObject pointer if
+ * legal. If not, set the python error string appropriately and
+ * return NULL.
+ */
+ PyArrayObject* obj_to_array_no_conversion(PyObject* input,
+ int typecode)
+ {
+ PyArrayObject* ary = NULL;
+ if (is_array(input) && (typecode == NPY_NOTYPE ||
+ PyArray_EquivTypenums(array_type(input), typecode)))
+ {
+ ary = (PyArrayObject*) input;
+ }
+ else if is_array(input)
+ {
+ const char* desired_type = typecode_string(typecode);
+ const char* actual_type = typecode_string(array_type(input));
+ PyErr_Format(PyExc_TypeError,
+ "Array of type '%s' required. Array of type '%s' given",
+ desired_type, actual_type);
+ ary = NULL;
+ }
+ else
+ {
+ const char* desired_type = typecode_string(typecode);
+ const char* actual_type = pytype_string(input);
+ PyErr_Format(PyExc_TypeError,
+ "Array of type '%s' required. A '%s' was given",
+ desired_type,
+ actual_type);
+ ary = NULL;
+ }
+ return ary;
+ }
+
+ /* Convert the given PyObject to a NumPy array with the given
+ * typecode. On success, return a valid PyArrayObject* with the
+ * correct type. On failure, the python error string will be set and
+ * the routine returns NULL.
+ */
+ PyArrayObject* obj_to_array_allow_conversion(PyObject* input,
+ int typecode,
+ int* is_new_object)
+ {
+ PyArrayObject* ary = NULL;
+ PyObject* py_obj;
+ if (is_array(input) && (typecode == NPY_NOTYPE ||
+ PyArray_EquivTypenums(array_type(input),typecode)))
+ {
+ ary = (PyArrayObject*) input;
+ *is_new_object = 0;
+ }
+ else
+ {
+ py_obj = PyArray_FROMANY(input, typecode, 0, 0, NPY_ARRAY_DEFAULT);
+ /* If NULL, PyArray_FromObject will have set python error value.*/
+ ary = (PyArrayObject*) py_obj;
+ *is_new_object = 1;
+ }
+ return ary;
+ }
+
+ /* Given a PyArrayObject, check to see if it is contiguous. If so,
+ * return the input pointer and flag it as not a new object. If it is
+ * not contiguous, create a new PyArrayObject using the original data,
+ * flag it as a new object and return the pointer.
+ */
+ PyArrayObject* make_contiguous(PyArrayObject* ary,
+ int* is_new_object,
+ int min_dims,
+ int max_dims)
+ {
+ PyArrayObject* result;
+ if (array_is_contiguous(ary))
+ {
+ result = ary;
+ *is_new_object = 0;
+ }
+ else
+ {
+ result = (PyArrayObject*) PyArray_ContiguousFromObject((PyObject*)ary,
+ array_type(ary),
+ min_dims,
+ max_dims);
+ *is_new_object = 1;
+ }
+ return result;
+ }
+
+ /* Given a PyArrayObject, check to see if it is Fortran-contiguous.
+ * If so, return the input pointer, but do not flag it as not a new
+ * object. If it is not Fortran-contiguous, create a new
+ * PyArrayObject using the original data, flag it as a new object
+ * and return the pointer.
+ */
+ PyArrayObject* make_fortran(PyArrayObject* ary,
+ int* is_new_object)
+ {
+ PyArrayObject* result;
+ if (array_is_fortran(ary))
+ {
+ result = ary;
+ *is_new_object = 0;
+ }
+ else
+ {
+ Py_INCREF(array_descr(ary));
+ result = (PyArrayObject*) PyArray_FromArray(ary,
+ array_descr(ary),
+ NPY_FORTRANORDER);
+ *is_new_object = 1;
+ }
+ return result;
+ }
+
+ /* Convert a given PyObject to a contiguous PyArrayObject of the
+ * specified type. If the input object is not a contiguous
+ * PyArrayObject, a new one will be created and the new object flag
+ * will be set.
+ */
+ PyArrayObject* obj_to_array_contiguous_allow_conversion(PyObject* input,
+ int typecode,
+ int* is_new_object)
+ {
+ int is_new1 = 0;
+ int is_new2 = 0;
+ PyArrayObject* ary2;
+ PyArrayObject* ary1 = obj_to_array_allow_conversion(input,
+ typecode,
+ &is_new1);
+ if (ary1)
+ {
+ ary2 = make_contiguous(ary1, &is_new2, 0, 0);
+ if ( is_new1 && is_new2)
+ {
+ Py_DECREF(ary1);
+ }
+ ary1 = ary2;
+ }
+ *is_new_object = is_new1 || is_new2;
+ return ary1;
+ }
+
+ /* Convert a given PyObject to a Fortran-ordered PyArrayObject of the
+ * specified type. If the input object is not a Fortran-ordered
+ * PyArrayObject, a new one will be created and the new object flag
+ * will be set.
+ */
+ PyArrayObject* obj_to_array_fortran_allow_conversion(PyObject* input,
+ int typecode,
+ int* is_new_object)
+ {
+ int is_new1 = 0;
+ int is_new2 = 0;
+ PyArrayObject* ary2;
+ PyArrayObject* ary1 = obj_to_array_allow_conversion(input,
+ typecode,
+ &is_new1);
+ if (ary1)
+ {
+ ary2 = make_fortran(ary1, &is_new2);
+ if (is_new1 && is_new2)
+ {
+ Py_DECREF(ary1);
+ }
+ ary1 = ary2;
+ }
+ *is_new_object = is_new1 || is_new2;
+ return ary1;
+ }
+} /* end fragment */
+
+/**********************************************************************/
+
+%fragment("NumPy_Array_Requirements",
+ "header",
+ fragment="NumPy_Backward_Compatibility",
+ fragment="NumPy_Macros")
+{
+ /* Test whether a python object is contiguous. If array is
+ * contiguous, return 1. Otherwise, set the python error string and
+ * return 0.
+ */
+ int require_contiguous(PyArrayObject* ary)
+ {
+ int contiguous = 1;
+ if (!array_is_contiguous(ary))
+ {
+ PyErr_SetString(PyExc_TypeError,
+ "Array must be contiguous. A non-contiguous array was given");
+ contiguous = 0;
+ }
+ return contiguous;
+ }
+
+ /* Require that a numpy array is not byte-swapped. If the array is
+ * not byte-swapped, return 1. Otherwise, set the python error string
+ * and return 0.
+ */
+ int require_native(PyArrayObject* ary)
+ {
+ int native = 1;
+ if (!array_is_native(ary))
+ {
+ PyErr_SetString(PyExc_TypeError,
+ "Array must have native byteorder. "
+ "A byte-swapped array was given");
+ native = 0;
+ }
+ return native;
+ }
+
+ /* Require the given PyArrayObject to have a specified number of
+ * dimensions. If the array has the specified number of dimensions,
+ * return 1. Otherwise, set the python error string and return 0.
+ */
+ int require_dimensions(PyArrayObject* ary,
+ int exact_dimensions)
+ {
+ int success = 1;
+ if (array_numdims(ary) != exact_dimensions)
+ {
+ PyErr_Format(PyExc_TypeError,
+ "Array must have %d dimensions. Given array has %d dimensions",
+ exact_dimensions,
+ array_numdims(ary));
+ success = 0;
+ }
+ return success;
+ }
+
+ /* Require the given PyArrayObject to have one of a list of specified
+ * number of dimensions. If the array has one of the specified number
+ * of dimensions, return 1. Otherwise, set the python error string
+ * and return 0.
+ */
+ int require_dimensions_n(PyArrayObject* ary,
+ int* exact_dimensions,
+ int n)
+ {
+ int success = 0;
+ int i;
+ char dims_str[255] = "";
+ char s[255];
+ for (i = 0; i < n && !success; i++)
+ {
+ if (array_numdims(ary) == exact_dimensions[i])
+ {
+ success = 1;
+ }
+ }
+ if (!success)
+ {
+ for (i = 0; i < n-1; i++)
+ {
+ sprintf(s, "%d, ", exact_dimensions[i]);
+ strcat(dims_str,s);
+ }
+ sprintf(s, " or %d", exact_dimensions[n-1]);
+ strcat(dims_str,s);
+ PyErr_Format(PyExc_TypeError,
+ "Array must have %s dimensions. Given array has %d dimensions",
+ dims_str,
+ array_numdims(ary));
+ }
+ return success;
+ }
+
+ /* Require the given PyArrayObject to have a specified shape. If the
+ * array has the specified shape, return 1. Otherwise, set the python
+ * error string and return 0.
+ */
+ int require_size(PyArrayObject* ary,
+ npy_intp* size,
+ int n)
+ {
+ int i;
+ int success = 1;
+ int len;
+ char desired_dims[255] = "[";
+ char s[255];
+ char actual_dims[255] = "[";
+ for(i=0; i < n;i++)
+ {
+ if (size[i] != -1 && size[i] != array_size(ary,i))
+ {
+ success = 0;
+ }
+ }
+ if (!success)
+ {
+ for (i = 0; i < n; i++)
+ {
+ if (size[i] == -1)
+ {
+ sprintf(s, "*,");
+ }
+ else
+ {
+ sprintf(s, "%ld,", (long int)size[i]);
+ }
+ strcat(desired_dims,s);
+ }
+ len = strlen(desired_dims);
+ desired_dims[len-1] = ']';
+ for (i = 0; i < n; i++)
+ {
+ sprintf(s, "%ld,", (long int)array_size(ary,i));
+ strcat(actual_dims,s);
+ }
+ len = strlen(actual_dims);
+ actual_dims[len-1] = ']';
+ PyErr_Format(PyExc_TypeError,
+ "Array must have shape of %s. Given array has shape of %s",
+ desired_dims,
+ actual_dims);
+ }
+ return success;
+ }
+
+ /* Require the given PyArrayObject to to be Fortran ordered. If the
+ * the PyArrayObject is already Fortran ordered, do nothing. Else,
+ * set the Fortran ordering flag and recompute the strides.
+ */
+ int require_fortran(PyArrayObject* ary)
+ {
+ int success = 1;
+ int nd = array_numdims(ary);
+ int i;
+ npy_intp * strides = array_strides(ary);
+ if (array_is_fortran(ary)) return success;
+ /* Set the Fortran ordered flag */
+ array_enableflags(ary,NPY_ARRAY_FARRAY);
+ /* Recompute the strides */
+ strides[0] = strides[nd-1];
+ for (i=1; i < nd; ++i)
+ strides[i] = strides[i-1] * array_size(ary,i-1);
+ return success;
+ }
+}
+
+/* Combine all NumPy fragments into one for convenience */
+%fragment("NumPy_Fragments",
+ "header",
+ fragment="NumPy_Backward_Compatibility",
+ fragment="NumPy_Macros",
+ fragment="NumPy_Utilities",
+ fragment="NumPy_Object_to_Array",
+ fragment="NumPy_Array_Requirements")
+{
+}
+
+/* End John Hunter translation (with modifications by Bill Spotz)
+ */
+
+/* %numpy_typemaps() macro
+ *
+ * This macro defines a family of 74 typemaps that allow C arguments
+ * of the form
+ *
+ * 1. (DATA_TYPE IN_ARRAY1[ANY])
+ * 2. (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
+ * 3. (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
+ *
+ * 4. (DATA_TYPE IN_ARRAY2[ANY][ANY])
+ * 5. (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ * 6. (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
+ * 7. (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ * 8. (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
+ *
+ * 9. (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
+ * 10. (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ * 11. (DATA_TYPE** IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ * 12. (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_ARRAY3)
+ * 13. (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ * 14. (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_FARRAY3)
+ *
+ * 15. (DATA_TYPE IN_ARRAY4[ANY][ANY][ANY][ANY])
+ * 16. (DATA_TYPE* IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ * 17. (DATA_TYPE** IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ * 18. (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, , DIM_TYPE DIM4, DATA_TYPE* IN_ARRAY4)
+ * 19. (DATA_TYPE* IN_FARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ * 20. (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* IN_FARRAY4)
+ *
+ * 21. (DATA_TYPE INPLACE_ARRAY1[ANY])
+ * 22. (DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1)
+ * 23. (DIM_TYPE DIM1, DATA_TYPE* INPLACE_ARRAY1)
+ *
+ * 24. (DATA_TYPE INPLACE_ARRAY2[ANY][ANY])
+ * 25. (DATA_TYPE* INPLACE_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ * 26. (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_ARRAY2)
+ * 27. (DATA_TYPE* INPLACE_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ * 28. (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_FARRAY2)
+ *
+ * 29. (DATA_TYPE INPLACE_ARRAY3[ANY][ANY][ANY])
+ * 30. (DATA_TYPE* INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ * 31. (DATA_TYPE** INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ * 32. (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_ARRAY3)
+ * 33. (DATA_TYPE* INPLACE_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ * 34. (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_FARRAY3)
+ *
+ * 35. (DATA_TYPE INPLACE_ARRAY4[ANY][ANY][ANY][ANY])
+ * 36. (DATA_TYPE* INPLACE_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ * 37. (DATA_TYPE** INPLACE_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ * 38. (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* INPLACE_ARRAY4)
+ * 39. (DATA_TYPE* INPLACE_FARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ * 40. (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* INPLACE_FARRAY4)
+ *
+ * 41. (DATA_TYPE ARGOUT_ARRAY1[ANY])
+ * 42. (DATA_TYPE* ARGOUT_ARRAY1, DIM_TYPE DIM1)
+ * 43. (DIM_TYPE DIM1, DATA_TYPE* ARGOUT_ARRAY1)
+ *
+ * 44. (DATA_TYPE ARGOUT_ARRAY2[ANY][ANY])
+ *
+ * 45. (DATA_TYPE ARGOUT_ARRAY3[ANY][ANY][ANY])
+ *
+ * 46. (DATA_TYPE ARGOUT_ARRAY4[ANY][ANY][ANY][ANY])
+ *
+ * 47. (DATA_TYPE** ARGOUTVIEW_ARRAY1, DIM_TYPE* DIM1)
+ * 48. (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEW_ARRAY1)
+ *
+ * 49. (DATA_TYPE** ARGOUTVIEW_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+ * 50. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_ARRAY2)
+ * 51. (DATA_TYPE** ARGOUTVIEW_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+ * 52. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_FARRAY2)
+ *
+ * 53. (DATA_TYPE** ARGOUTVIEW_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
+ * 54. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_ARRAY3)
+ * 55. (DATA_TYPE** ARGOUTVIEW_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
+ * 56. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_FARRAY3)
+ *
+ * 57. (DATA_TYPE** ARGOUTVIEW_ARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ * 58. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEW_ARRAY4)
+ * 59. (DATA_TYPE** ARGOUTVIEW_FARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ * 60. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEW_FARRAY4)
+ *
+ * 61. (DATA_TYPE** ARGOUTVIEWM_ARRAY1, DIM_TYPE* DIM1)
+ * 62. (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEWM_ARRAY1)
+ *
+ * 63. (DATA_TYPE** ARGOUTVIEWM_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+ * 64. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEWM_ARRAY2)
+ * 65. (DATA_TYPE** ARGOUTVIEWM_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+ * 66. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEWM_FARRAY2)
+ *
+ * 67. (DATA_TYPE** ARGOUTVIEWM_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
+ * 68. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEWM_ARRAY3)
+ * 69. (DATA_TYPE** ARGOUTVIEWM_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
+ * 70. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEWM_FARRAY3)
+ *
+ * 71. (DATA_TYPE** ARGOUTVIEWM_ARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ * 72. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEWM_ARRAY4)
+ * 73. (DATA_TYPE** ARGOUTVIEWM_FARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ * 74. (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEWM_FARRAY4)
+ *
+ * where "DATA_TYPE" is any type supported by the NumPy module, and
+ * "DIM_TYPE" is any int-like type suitable for specifying dimensions.
+ * The difference between "ARRAY" typemaps and "FARRAY" typemaps is
+ * that the "FARRAY" typemaps expect Fortran ordering of
+ * multidimensional arrays. In python, the dimensions will not need
+ * to be specified (except for the "DATA_TYPE* ARGOUT_ARRAY1"
+ * typemaps). The IN_ARRAYs can be a numpy array or any sequence that
+ * can be converted to a numpy array of the specified type. The
+ * INPLACE_ARRAYs must be numpy arrays of the appropriate type. The
+ * ARGOUT_ARRAYs will be returned as new numpy arrays of the
+ * appropriate type.
+ *
+ * These typemaps can be applied to existing functions using the
+ * %apply directive. For example:
+ *
+ * %apply (double* IN_ARRAY1, int DIM1) {(double* series, int length)};
+ * double prod(double* series, int length);
+ *
+ * %apply (int DIM1, int DIM2, double* INPLACE_ARRAY2)
+ * {(int rows, int cols, double* matrix )};
+ * void floor(int rows, int cols, double* matrix, double f);
+ *
+ * %apply (double IN_ARRAY3[ANY][ANY][ANY])
+ * {(double tensor[2][2][2] )};
+ * %apply (double ARGOUT_ARRAY3[ANY][ANY][ANY])
+ * {(double low[2][2][2] )};
+ * %apply (double ARGOUT_ARRAY3[ANY][ANY][ANY])
+ * {(double upp[2][2][2] )};
+ * void luSplit(double tensor[2][2][2],
+ * double low[2][2][2],
+ * double upp[2][2][2] );
+ *
+ * or directly with
+ *
+ * double prod(double* IN_ARRAY1, int DIM1);
+ *
+ * void floor(int DIM1, int DIM2, double* INPLACE_ARRAY2, double f);
+ *
+ * void luSplit(double IN_ARRAY3[ANY][ANY][ANY],
+ * double ARGOUT_ARRAY3[ANY][ANY][ANY],
+ * double ARGOUT_ARRAY3[ANY][ANY][ANY]);
+ */
+
+%define %numpy_typemaps(DATA_TYPE, DATA_TYPECODE, DIM_TYPE)
+
+/************************/
+/* Input Array Typemaps */
+/************************/
+
+/* Typemap suite for (DATA_TYPE IN_ARRAY1[ANY])
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE IN_ARRAY1[ANY])
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE IN_ARRAY1[ANY])
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[1] = { $1_dim0 };
+ array = obj_to_array_contiguous_allow_conversion($input,
+ DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 1) ||
+ !require_size(array, size, 1)) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+%typemap(freearg)
+ (DATA_TYPE IN_ARRAY1[ANY])
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[1] = { -1 };
+ array = obj_to_array_contiguous_allow_conversion($input,
+ DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 1) ||
+ !require_size(array, size, 1)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+}
+%typemap(freearg)
+ (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[1] = {-1};
+ array = obj_to_array_contiguous_allow_conversion($input,
+ DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 1) ||
+ !require_size(array, size, 1)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DATA_TYPE*) array_data(array);
+}
+%typemap(freearg)
+ (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE IN_ARRAY2[ANY][ANY])
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE IN_ARRAY2[ANY][ANY])
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE IN_ARRAY2[ANY][ANY])
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[2] = { $1_dim0, $1_dim1 };
+ array = obj_to_array_contiguous_allow_conversion($input,
+ DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 2) ||
+ !require_size(array, size, 2)) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+%typemap(freearg)
+ (DATA_TYPE IN_ARRAY2[ANY][ANY])
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[2] = { -1, -1 };
+ array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 2) ||
+ !require_size(array, size, 2)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+}
+%typemap(freearg)
+ (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[2] = { -1, -1 };
+ array = obj_to_array_contiguous_allow_conversion($input,
+ DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 2) ||
+ !require_size(array, size, 2)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DATA_TYPE*) array_data(array);
+}
+%typemap(freearg)
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[2] = { -1, -1 };
+ array = obj_to_array_fortran_allow_conversion($input,
+ DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 2) ||
+ !require_size(array, size, 2) || !require_fortran(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+}
+%typemap(freearg)
+ (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[2] = { -1, -1 };
+ array = obj_to_array_fortran_allow_conversion($input,
+ DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 2) ||
+ !require_size(array, size, 2) || !require_fortran(array)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DATA_TYPE*) array_data(array);
+}
+%typemap(freearg)
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[3] = { $1_dim0, $1_dim1, $1_dim2 };
+ array = obj_to_array_contiguous_allow_conversion($input,
+ DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 3) ||
+ !require_size(array, size, 3)) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+%typemap(freearg)
+ (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[3] = { -1, -1, -1 };
+ array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 3) ||
+ !require_size(array, size, 3)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+ $4 = (DIM_TYPE) array_size(array,2);
+}
+%typemap(freearg)
+ (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE** IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE** IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ /* for now, only concerned with lists */
+ $1 = PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE** IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ (DATA_TYPE** array=NULL, PyArrayObject** object_array=NULL, int* is_new_object_array=NULL)
+{
+ npy_intp size[2] = { -1, -1 };
+ PyArrayObject* temp_array;
+ Py_ssize_t i;
+ int is_new_object;
+
+ /* length of the list */
+ $2 = PyList_Size($input);
+
+ /* the arrays */
+ array = (DATA_TYPE **)malloc($2*sizeof(DATA_TYPE *));
+ object_array = (PyArrayObject **)calloc($2,sizeof(PyArrayObject *));
+ is_new_object_array = (int *)calloc($2,sizeof(int));
+
+ if (array == NULL || object_array == NULL || is_new_object_array == NULL)
+ {
+ SWIG_fail;
+ }
+
+ for (i=0; i<$2; i++)
+ {
+ temp_array = obj_to_array_contiguous_allow_conversion(PySequence_GetItem($input,i), DATA_TYPECODE, &is_new_object);
+
+ /* the new array must be stored so that it can be destroyed in freearg */
+ object_array[i] = temp_array;
+ is_new_object_array[i] = is_new_object;
+
+ if (!temp_array || !require_dimensions(temp_array, 2)) SWIG_fail;
+
+ /* store the size of the first array in the list, then use that for comparison. */
+ if (i == 0)
+ {
+ size[0] = array_size(temp_array,0);
+ size[1] = array_size(temp_array,1);
+ }
+
+ if (!require_size(temp_array, size, 2)) SWIG_fail;
+
+ array[i] = (DATA_TYPE*) array_data(temp_array);
+ }
+
+ $1 = (DATA_TYPE**) array;
+ $3 = (DIM_TYPE) size[0];
+ $4 = (DIM_TYPE) size[1];
+}
+%typemap(freearg)
+ (DATA_TYPE** IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ Py_ssize_t i;
+
+ if (array$argnum!=NULL) free(array$argnum);
+
+ /*freeing the individual arrays if needed */
+ if (object_array$argnum!=NULL)
+ {
+ if (is_new_object_array$argnum!=NULL)
+ {
+ for (i=0; i<$2; i++)
+ {
+ if (object_array$argnum[i] != NULL && is_new_object_array$argnum[i])
+ { Py_DECREF(object_array$argnum[i]); }
+ }
+ free(is_new_object_array$argnum);
+ }
+ free(object_array$argnum);
+ }
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3,
+ * DATA_TYPE* IN_ARRAY3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_ARRAY3)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_ARRAY3)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[3] = { -1, -1, -1 };
+ array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 3) ||
+ !require_size(array, size, 3)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DIM_TYPE) array_size(array,2);
+ $4 = (DATA_TYPE*) array_data(array);
+}
+%typemap(freearg)
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_ARRAY3)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[3] = { -1, -1, -1 };
+ array = obj_to_array_fortran_allow_conversion($input, DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 3) ||
+ !require_size(array, size, 3) | !require_fortran(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+ $4 = (DIM_TYPE) array_size(array,2);
+}
+%typemap(freearg)
+ (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3,
+ * DATA_TYPE* IN_FARRAY3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_FARRAY3)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_FARRAY3)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[3] = { -1, -1, -1 };
+ array = obj_to_array_fortran_allow_conversion($input,
+ DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 3) ||
+ !require_size(array, size, 3) || !require_fortran(array)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DIM_TYPE) array_size(array,2);
+ $4 = (DATA_TYPE*) array_data(array);
+}
+%typemap(freearg)
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_FARRAY3)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE IN_ARRAY4[ANY][ANY][ANY][ANY])
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE IN_ARRAY4[ANY][ANY][ANY][ANY])
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE IN_ARRAY4[ANY][ANY][ANY][ANY])
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[4] = { $1_dim0, $1_dim1, $1_dim2 , $1_dim3};
+ array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 4) ||
+ !require_size(array, size, 4)) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+%typemap(freearg)
+ (DATA_TYPE IN_ARRAY4[ANY][ANY][ANY][ANY])
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE* IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3, DIM_TYPE DIM4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[4] = { -1, -1, -1, -1 };
+ array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 4) ||
+ !require_size(array, size, 4)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+ $4 = (DIM_TYPE) array_size(array,2);
+ $5 = (DIM_TYPE) array_size(array,3);
+}
+%typemap(freearg)
+ (DATA_TYPE* IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE** IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3, DIM_TYPE DIM4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE** IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ /* for now, only concerned with lists */
+ $1 = PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE** IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ (DATA_TYPE** array=NULL, PyArrayObject** object_array=NULL, int* is_new_object_array=NULL)
+{
+ npy_intp size[3] = { -1, -1, -1 };
+ PyArrayObject* temp_array;
+ Py_ssize_t i;
+ int is_new_object;
+
+ /* length of the list */
+ $2 = PyList_Size($input);
+
+ /* the arrays */
+ array = (DATA_TYPE **)malloc($2*sizeof(DATA_TYPE *));
+ object_array = (PyArrayObject **)calloc($2,sizeof(PyArrayObject *));
+ is_new_object_array = (int *)calloc($2,sizeof(int));
+
+ if (array == NULL || object_array == NULL || is_new_object_array == NULL)
+ {
+ SWIG_fail;
+ }
+
+ for (i=0; i<$2; i++)
+ {
+ temp_array = obj_to_array_contiguous_allow_conversion(PySequence_GetItem($input,i), DATA_TYPECODE, &is_new_object);
+
+ /* the new array must be stored so that it can be destroyed in freearg */
+ object_array[i] = temp_array;
+ is_new_object_array[i] = is_new_object;
+
+ if (!temp_array || !require_dimensions(temp_array, 3)) SWIG_fail;
+
+ /* store the size of the first array in the list, then use that for comparison. */
+ if (i == 0)
+ {
+ size[0] = array_size(temp_array,0);
+ size[1] = array_size(temp_array,1);
+ size[2] = array_size(temp_array,2);
+ }
+
+ if (!require_size(temp_array, size, 3)) SWIG_fail;
+
+ array[i] = (DATA_TYPE*) array_data(temp_array);
+ }
+
+ $1 = (DATA_TYPE**) array;
+ $3 = (DIM_TYPE) size[0];
+ $4 = (DIM_TYPE) size[1];
+ $5 = (DIM_TYPE) size[2];
+}
+%typemap(freearg)
+ (DATA_TYPE** IN_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ Py_ssize_t i;
+
+ if (array$argnum!=NULL) free(array$argnum);
+
+ /*freeing the individual arrays if needed */
+ if (object_array$argnum!=NULL)
+ {
+ if (is_new_object_array$argnum!=NULL)
+ {
+ for (i=0; i<$2; i++)
+ {
+ if (object_array$argnum[i] != NULL && is_new_object_array$argnum[i])
+ { Py_DECREF(object_array$argnum[i]); }
+ }
+ free(is_new_object_array$argnum);
+ }
+ free(object_array$argnum);
+ }
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4,
+ * DATA_TYPE* IN_ARRAY4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* IN_ARRAY4)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* IN_ARRAY4)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[4] = { -1, -1, -1 , -1};
+ array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 4) ||
+ !require_size(array, size, 4)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DIM_TYPE) array_size(array,2);
+ $4 = (DIM_TYPE) array_size(array,3);
+ $5 = (DATA_TYPE*) array_data(array);
+}
+%typemap(freearg)
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* IN_ARRAY4)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DATA_TYPE* IN_FARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3, DIM_TYPE DIM4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* IN_FARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* IN_FARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[4] = { -1, -1, -1, -1 };
+ array = obj_to_array_fortran_allow_conversion($input, DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 4) ||
+ !require_size(array, size, 4) | !require_fortran(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+ $4 = (DIM_TYPE) array_size(array,2);
+ $5 = (DIM_TYPE) array_size(array,3);
+}
+%typemap(freearg)
+ (DATA_TYPE* IN_FARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4,
+ * DATA_TYPE* IN_FARRAY4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* IN_FARRAY4)
+{
+ $1 = is_array($input) || PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* IN_FARRAY4)
+ (PyArrayObject* array=NULL, int is_new_object=0)
+{
+ npy_intp size[4] = { -1, -1, -1 , -1 };
+ array = obj_to_array_fortran_allow_conversion($input, DATA_TYPECODE,
+ &is_new_object);
+ if (!array || !require_dimensions(array, 4) ||
+ !require_size(array, size, 4) || !require_fortran(array)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DIM_TYPE) array_size(array,2);
+ $4 = (DIM_TYPE) array_size(array,3);
+ $5 = (DATA_TYPE*) array_data(array);
+}
+%typemap(freearg)
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* IN_FARRAY4)
+{
+ if (is_new_object$argnum && array$argnum)
+ { Py_DECREF(array$argnum); }
+}
+
+/***************************/
+/* In-Place Array Typemaps */
+/***************************/
+
+/* Typemap suite for (DATA_TYPE INPLACE_ARRAY1[ANY])
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE INPLACE_ARRAY1[ANY])
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE INPLACE_ARRAY1[ANY])
+ (PyArrayObject* array=NULL)
+{
+ npy_intp size[1] = { $1_dim0 };
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,1) || !require_size(array, size, 1) ||
+ !require_contiguous(array) || !require_native(array)) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1)
+ (PyArrayObject* array=NULL, int i=1)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,1) || !require_contiguous(array)
+ || !require_native(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = 1;
+ for (i=0; i < array_numdims(array); ++i) $2 *= array_size(array,i);
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DATA_TYPE* INPLACE_ARRAY1)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DATA_TYPE* INPLACE_ARRAY1)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DATA_TYPE* INPLACE_ARRAY1)
+ (PyArrayObject* array=NULL, int i=0)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,1) || !require_contiguous(array)
+ || !require_native(array)) SWIG_fail;
+ $1 = 1;
+ for (i=0; i < array_numdims(array); ++i) $1 *= array_size(array,i);
+ $2 = (DATA_TYPE*) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE INPLACE_ARRAY2[ANY][ANY])
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE INPLACE_ARRAY2[ANY][ANY])
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE INPLACE_ARRAY2[ANY][ANY])
+ (PyArrayObject* array=NULL)
+{
+ npy_intp size[2] = { $1_dim0, $1_dim1 };
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,2) || !require_size(array, size, 2) ||
+ !require_contiguous(array) || !require_native(array)) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE* INPLACE_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* INPLACE_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* INPLACE_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,2) || !require_contiguous(array)
+ || !require_native(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_ARRAY2)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_ARRAY2)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_ARRAY2)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,2) || !require_contiguous(array) ||
+ !require_native(array)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DATA_TYPE*) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE* INPLACE_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* INPLACE_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* INPLACE_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,2) || !require_contiguous(array)
+ || !require_native(array) || !require_fortran(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_FARRAY2)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_FARRAY2)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_FARRAY2)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,2) || !require_contiguous(array) ||
+ !require_native(array) || !require_fortran(array)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DATA_TYPE*) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE INPLACE_ARRAY3[ANY][ANY][ANY])
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE INPLACE_ARRAY3[ANY][ANY][ANY])
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE INPLACE_ARRAY3[ANY][ANY][ANY])
+ (PyArrayObject* array=NULL)
+{
+ npy_intp size[3] = { $1_dim0, $1_dim1, $1_dim2 };
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,3) || !require_size(array, size, 3) ||
+ !require_contiguous(array) || !require_native(array)) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE* INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,3) || !require_contiguous(array) ||
+ !require_native(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+ $4 = (DIM_TYPE) array_size(array,2);
+}
+
+/* Typemap suite for (DATA_TYPE** INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE** INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ $1 = PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE** INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ (DATA_TYPE** array=NULL, PyArrayObject** object_array=NULL)
+{
+ npy_intp size[2] = { -1, -1 };
+ PyArrayObject* temp_array;
+ Py_ssize_t i;
+
+ /* length of the list */
+ $2 = PyList_Size($input);
+
+ /* the arrays */
+ array = (DATA_TYPE **)malloc($2*sizeof(DATA_TYPE *));
+ object_array = (PyArrayObject **)calloc($2,sizeof(PyArrayObject *));
+
+ if (array == NULL || object_array == NULL)
+ {
+ SWIG_fail;
+ }
+
+ for (i=0; i<$2; i++)
+ {
+ temp_array = obj_to_array_no_conversion(PySequence_GetItem($input,i), DATA_TYPECODE);
+
+ /* the new array must be stored so that it can be destroyed in freearg */
+ object_array[i] = temp_array;
+
+ if ( !temp_array || !require_dimensions(temp_array, 2) ||
+ !require_contiguous(temp_array) ||
+ !require_native(temp_array) ||
+ !PyArray_EquivTypenums(array_type(temp_array), DATA_TYPECODE)
+ ) SWIG_fail;
+
+ /* store the size of the first array in the list, then use that for comparison. */
+ if (i == 0)
+ {
+ size[0] = array_size(temp_array,0);
+ size[1] = array_size(temp_array,1);
+ }
+
+ if (!require_size(temp_array, size, 2)) SWIG_fail;
+
+ array[i] = (DATA_TYPE*) array_data(temp_array);
+ }
+
+ $1 = (DATA_TYPE**) array;
+ $3 = (DIM_TYPE) size[0];
+ $4 = (DIM_TYPE) size[1];
+}
+%typemap(freearg)
+ (DATA_TYPE** INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ if (array$argnum!=NULL) free(array$argnum);
+ if (object_array$argnum!=NULL) free(object_array$argnum);
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3,
+ * DATA_TYPE* INPLACE_ARRAY3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_ARRAY3)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_ARRAY3)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,3) || !require_contiguous(array)
+ || !require_native(array)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DIM_TYPE) array_size(array,2);
+ $4 = (DATA_TYPE*) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE* INPLACE_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* INPLACE_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* INPLACE_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,3) || !require_contiguous(array) ||
+ !require_native(array) || !require_fortran(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+ $4 = (DIM_TYPE) array_size(array,2);
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3,
+ * DATA_TYPE* INPLACE_FARRAY3)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_FARRAY3)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_FARRAY3)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,3) || !require_contiguous(array)
+ || !require_native(array) || !require_fortran(array)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DIM_TYPE) array_size(array,2);
+ $4 = (DATA_TYPE*) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE INPLACE_ARRAY4[ANY][ANY][ANY][ANY])
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE INPLACE_ARRAY4[ANY][ANY][ANY][ANY])
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE INPLACE_ARRAY4[ANY][ANY][ANY][ANY])
+ (PyArrayObject* array=NULL)
+{
+ npy_intp size[4] = { $1_dim0, $1_dim1, $1_dim2 , $1_dim3 };
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,4) || !require_size(array, size, 4) ||
+ !require_contiguous(array) || !require_native(array)) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE* INPLACE_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3, DIM_TYPE DIM4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* INPLACE_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* INPLACE_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,4) || !require_contiguous(array) ||
+ !require_native(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+ $4 = (DIM_TYPE) array_size(array,2);
+ $5 = (DIM_TYPE) array_size(array,3);
+}
+
+/* Typemap suite for (DATA_TYPE** INPLACE_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3, DIM_TYPE DIM4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE** INPLACE_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ $1 = PySequence_Check($input);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE** INPLACE_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ (DATA_TYPE** array=NULL, PyArrayObject** object_array=NULL)
+{
+ npy_intp size[3] = { -1, -1, -1 };
+ PyArrayObject* temp_array;
+ Py_ssize_t i;
+
+ /* length of the list */
+ $2 = PyList_Size($input);
+
+ /* the arrays */
+ array = (DATA_TYPE **)malloc($2*sizeof(DATA_TYPE *));
+ object_array = (PyArrayObject **)calloc($2,sizeof(PyArrayObject *));
+
+ if (array == NULL || object_array == NULL)
+ {
+ SWIG_fail;
+ }
+
+ for (i=0; i<$2; i++)
+ {
+ temp_array = obj_to_array_no_conversion(PySequence_GetItem($input,i), DATA_TYPECODE);
+
+ /* the new array must be stored so that it can be destroyed in freearg */
+ object_array[i] = temp_array;
+
+ if ( !temp_array || !require_dimensions(temp_array, 3) ||
+ !require_contiguous(temp_array) ||
+ !require_native(temp_array) ||
+ !PyArray_EquivTypenums(array_type(temp_array), DATA_TYPECODE)
+ ) SWIG_fail;
+
+ /* store the size of the first array in the list, then use that for comparison. */
+ if (i == 0)
+ {
+ size[0] = array_size(temp_array,0);
+ size[1] = array_size(temp_array,1);
+ size[2] = array_size(temp_array,2);
+ }
+
+ if (!require_size(temp_array, size, 3)) SWIG_fail;
+
+ array[i] = (DATA_TYPE*) array_data(temp_array);
+ }
+
+ $1 = (DATA_TYPE**) array;
+ $3 = (DIM_TYPE) size[0];
+ $4 = (DIM_TYPE) size[1];
+ $5 = (DIM_TYPE) size[2];
+}
+%typemap(freearg)
+ (DATA_TYPE** INPLACE_ARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ if (array$argnum!=NULL) free(array$argnum);
+ if (object_array$argnum!=NULL) free(object_array$argnum);
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4,
+ * DATA_TYPE* INPLACE_ARRAY4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* INPLACE_ARRAY4)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* INPLACE_ARRAY4)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,4) || !require_contiguous(array)
+ || !require_native(array)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DIM_TYPE) array_size(array,2);
+ $4 = (DIM_TYPE) array_size(array,3);
+ $5 = (DATA_TYPE*) array_data(array);
+}
+
+/* Typemap suite for (DATA_TYPE* INPLACE_FARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2,
+ * DIM_TYPE DIM3, DIM_TYPE DIM4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DATA_TYPE* INPLACE_FARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* INPLACE_FARRAY4, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,4) || !require_contiguous(array) ||
+ !require_native(array) || !require_fortran(array)) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+ $2 = (DIM_TYPE) array_size(array,0);
+ $3 = (DIM_TYPE) array_size(array,1);
+ $4 = (DIM_TYPE) array_size(array,2);
+ $5 = (DIM_TYPE) array_size(array,3);
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3,
+ * DATA_TYPE* INPLACE_FARRAY4)
+ */
+%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
+ fragment="NumPy_Macros")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* INPLACE_FARRAY4)
+{
+ $1 = is_array($input) && PyArray_EquivTypenums(array_type($input),
+ DATA_TYPECODE);
+}
+%typemap(in,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DIM_TYPE DIM4, DATA_TYPE* INPLACE_FARRAY4)
+ (PyArrayObject* array=NULL)
+{
+ array = obj_to_array_no_conversion($input, DATA_TYPECODE);
+ if (!array || !require_dimensions(array,4) || !require_contiguous(array)
+ || !require_native(array) || !require_fortran(array)) SWIG_fail;
+ $1 = (DIM_TYPE) array_size(array,0);
+ $2 = (DIM_TYPE) array_size(array,1);
+ $3 = (DIM_TYPE) array_size(array,2);
+ $4 = (DIM_TYPE) array_size(array,3);
+ $5 = (DATA_TYPE*) array_data(array);
+}
+
+/*************************/
+/* Argout Array Typemaps */
+/*************************/
+
+/* Typemap suite for (DATA_TYPE ARGOUT_ARRAY1[ANY])
+ */
+%typemap(in,numinputs=0,
+ fragment="NumPy_Backward_Compatibility,NumPy_Macros")
+ (DATA_TYPE ARGOUT_ARRAY1[ANY])
+ (PyObject* array = NULL)
+{
+ npy_intp dims[1] = { $1_dim0 };
+ array = PyArray_SimpleNew(1, dims, DATA_TYPECODE);
+ if (!array) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+%typemap(argout)
+ (DATA_TYPE ARGOUT_ARRAY1[ANY])
+{
+ $result = SWIG_Python_AppendOutput($result,(PyObject*)array$argnum);
+}
+
+/* Typemap suite for (DATA_TYPE* ARGOUT_ARRAY1, DIM_TYPE DIM1)
+ */
+%typemap(in,numinputs=1,
+ fragment="NumPy_Fragments")
+ (DATA_TYPE* ARGOUT_ARRAY1, DIM_TYPE DIM1)
+ (PyObject* array = NULL)
+{
+ npy_intp dims[1];
+ if (!PyInt_Check($input))
+ {
+ const char* typestring = pytype_string($input);
+ PyErr_Format(PyExc_TypeError,
+ "Int dimension expected. '%s' given.",
+ typestring);
+ SWIG_fail;
+ }
+ $2 = (DIM_TYPE) PyInt_AsLong($input);
+ dims[0] = (npy_intp) $2;
+ array = PyArray_SimpleNew(1, dims, DATA_TYPECODE);
+ if (!array) SWIG_fail;
+ $1 = (DATA_TYPE*) array_data(array);
+}
+%typemap(argout)
+ (DATA_TYPE* ARGOUT_ARRAY1, DIM_TYPE DIM1)
+{
+ $result = SWIG_Python_AppendOutput($result,(PyObject*)array$argnum);
+}
+
+/* Typemap suite for (DIM_TYPE DIM1, DATA_TYPE* ARGOUT_ARRAY1)
+ */
+%typemap(in,numinputs=1,
+ fragment="NumPy_Fragments")
+ (DIM_TYPE DIM1, DATA_TYPE* ARGOUT_ARRAY1)
+ (PyObject* array = NULL)
+{
+ npy_intp dims[1];
+ if (!PyInt_Check($input))
+ {
+ const char* typestring = pytype_string($input);
+ PyErr_Format(PyExc_TypeError,
+ "Int dimension expected. '%s' given.",
+ typestring);
+ SWIG_fail;
+ }
+ $1 = (DIM_TYPE) PyInt_AsLong($input);
+ dims[0] = (npy_intp) $1;
+ array = PyArray_SimpleNew(1, dims, DATA_TYPECODE);
+ if (!array) SWIG_fail;
+ $2 = (DATA_TYPE*) array_data(array);
+}
+%typemap(argout)
+ (DIM_TYPE DIM1, DATA_TYPE* ARGOUT_ARRAY1)
+{
+ $result = SWIG_Python_AppendOutput($result,(PyObject*)array$argnum);
+}
+
+/* Typemap suite for (DATA_TYPE ARGOUT_ARRAY2[ANY][ANY])
+ */
+%typemap(in,numinputs=0,
+ fragment="NumPy_Backward_Compatibility,NumPy_Macros")
+ (DATA_TYPE ARGOUT_ARRAY2[ANY][ANY])
+ (PyObject* array = NULL)
+{
+ npy_intp dims[2] = { $1_dim0, $1_dim1 };
+ array = PyArray_SimpleNew(2, dims, DATA_TYPECODE);
+ if (!array) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+%typemap(argout)
+ (DATA_TYPE ARGOUT_ARRAY2[ANY][ANY])
+{
+ $result = SWIG_Python_AppendOutput($result,(PyObject*)array$argnum);
+}
+
+/* Typemap suite for (DATA_TYPE ARGOUT_ARRAY3[ANY][ANY][ANY])
+ */
+%typemap(in,numinputs=0,
+ fragment="NumPy_Backward_Compatibility,NumPy_Macros")
+ (DATA_TYPE ARGOUT_ARRAY3[ANY][ANY][ANY])
+ (PyObject* array = NULL)
+{
+ npy_intp dims[3] = { $1_dim0, $1_dim1, $1_dim2 };
+ array = PyArray_SimpleNew(3, dims, DATA_TYPECODE);
+ if (!array) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+%typemap(argout)
+ (DATA_TYPE ARGOUT_ARRAY3[ANY][ANY][ANY])
+{
+ $result = SWIG_Python_AppendOutput($result,(PyObject*)array$argnum);
+}
+
+/* Typemap suite for (DATA_TYPE ARGOUT_ARRAY4[ANY][ANY][ANY][ANY])
+ */
+%typemap(in,numinputs=0,
+ fragment="NumPy_Backward_Compatibility,NumPy_Macros")
+ (DATA_TYPE ARGOUT_ARRAY4[ANY][ANY][ANY][ANY])
+ (PyObject* array = NULL)
+{
+ npy_intp dims[4] = { $1_dim0, $1_dim1, $1_dim2, $1_dim3 };
+ array = PyArray_SimpleNew(4, dims, DATA_TYPECODE);
+ if (!array) SWIG_fail;
+ $1 = ($1_ltype) array_data(array);
+}
+%typemap(argout)
+ (DATA_TYPE ARGOUT_ARRAY4[ANY][ANY][ANY][ANY])
+{
+ $result = SWIG_Python_AppendOutput($result,(PyObject*)array$argnum);
+}
+
+/*****************************/
+/* Argoutview Array Typemaps */
+/*****************************/
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_ARRAY1, DIM_TYPE* DIM1)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEW_ARRAY1, DIM_TYPE* DIM1 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility")
+ (DATA_TYPE** ARGOUTVIEW_ARRAY1, DIM_TYPE* DIM1)
+{
+ npy_intp dims[1] = { *$2 };
+ PyObject* obj = PyArray_SimpleNewFromData(1, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEW_ARRAY1)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DATA_TYPE** ARGOUTVIEW_ARRAY1)
+ (DIM_TYPE dim_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim_temp;
+ $2 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility")
+ (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEW_ARRAY1)
+{
+ npy_intp dims[1] = { *$1 };
+ PyObject* obj = PyArray_SimpleNewFromData(1, dims, DATA_TYPECODE, (void*)(*$2));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEW_ARRAY2, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility")
+ (DATA_TYPE** ARGOUTVIEW_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+{
+ npy_intp dims[2] = { *$2, *$3 };
+ PyObject* obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_ARRAY2)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DATA_TYPE** ARGOUTVIEW_ARRAY2)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_ARRAY2)
+{
+ npy_intp dims[2] = { *$1, *$2 };
+ PyObject* obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$3));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEW_FARRAY2, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements")
+ (DATA_TYPE** ARGOUTVIEW_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+{
+ npy_intp dims[2] = { *$2, *$3 };
+ PyObject* obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_FARRAY2)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DATA_TYPE** ARGOUTVIEW_FARRAY2)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_FARRAY2)
+{
+ npy_intp dims[2] = { *$1, *$2 };
+ PyObject* obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$3));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEW_ARRAY3, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility")
+ (DATA_TYPE** ARGOUTVIEW_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
+{
+ npy_intp dims[3] = { *$2, *$3, *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3,
+ DATA_TYPE** ARGOUTVIEW_ARRAY3)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_ARRAY3)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DATA_TYPE* data_temp = NULL)
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_ARRAY3)
+{
+ npy_intp dims[3] = { *$1, *$2, *$3 };
+ PyObject* obj = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$4));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEW_FARRAY3, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements")
+ (DATA_TYPE** ARGOUTVIEW_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
+{
+ npy_intp dims[3] = { *$2, *$3, *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3,
+ DATA_TYPE** ARGOUTVIEW_FARRAY3)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DATA_TYPE** ARGOUTVIEW_FARRAY3)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_FARRAY3)
+{
+ npy_intp dims[3] = { *$1, *$2, *$3 };
+ PyObject* obj = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$4));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_ARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEW_ARRAY4, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+ $5 = &dim4_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility")
+ (DATA_TYPE** ARGOUTVIEW_ARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+{
+ npy_intp dims[4] = { *$2, *$3, *$4 , *$5 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4,
+ DATA_TYPE** ARGOUTVIEW_ARRAY4)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 , DATA_TYPE** ARGOUTVIEW_ARRAY4)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &dim4_temp;
+ $5 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEW_ARRAY4)
+{
+ npy_intp dims[4] = { *$1, *$2, *$3 , *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$5));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_FARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEW_FARRAY4, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+ $5 = &dim4_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements")
+ (DATA_TYPE** ARGOUTVIEW_FARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+{
+ npy_intp dims[4] = { *$2, *$3, *$4 , *$5 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4,
+ DATA_TYPE** ARGOUTVIEW_FARRAY4)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 , DATA_TYPE** ARGOUTVIEW_FARRAY4)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &dim4_temp;
+ $5 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEW_FARRAY4)
+{
+ npy_intp dims[4] = { *$1, *$2, *$3 , *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$5));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/*************************************/
+/* Managed Argoutview Array Typemaps */
+/*************************************/
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEWM_ARRAY1, DIM_TYPE* DIM1)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY1, DIM_TYPE* DIM1 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY1, DIM_TYPE* DIM1)
+{
+ npy_intp dims[1] = { *$2 };
+ PyObject* obj = PyArray_SimpleNewFromData(1, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEWM_ARRAY1)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DATA_TYPE** ARGOUTVIEWM_ARRAY1)
+ (DIM_TYPE dim_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim_temp;
+ $2 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEWM_ARRAY1)
+{
+ npy_intp dims[1] = { *$1 };
+ PyObject* obj = PyArray_SimpleNewFromData(1, dims, DATA_TYPECODE, (void*)(*$2));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEWM_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY2, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+{
+ npy_intp dims[2] = { *$2, *$3 };
+ PyObject* obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEWM_ARRAY2)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DATA_TYPE** ARGOUTVIEWM_ARRAY2)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEWM_ARRAY2)
+{
+ npy_intp dims[2] = { *$1, *$2 };
+ PyObject* obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$3));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEWM_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEWM_FARRAY2, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements,NumPy_Utilities")
+ (DATA_TYPE** ARGOUTVIEWM_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
+{
+ npy_intp dims[2] = { *$2, *$3 };
+ PyObject* obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEWM_FARRAY2)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DATA_TYPE** ARGOUTVIEWM_FARRAY2)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements,NumPy_Utilities")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEWM_FARRAY2)
+{
+ npy_intp dims[2] = { *$1, *$2 };
+ PyObject* obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$3));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEWM_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY3, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
+{
+ npy_intp dims[3] = { *$2, *$3, *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3,
+ DATA_TYPE** ARGOUTVIEWM_ARRAY3)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DATA_TYPE** ARGOUTVIEWM_ARRAY3)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEWM_ARRAY3)
+{
+ npy_intp dims[3] = { *$1, *$2, *$3 };
+ PyObject* obj= PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$4));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEWM_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEWM_FARRAY3, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements,NumPy_Utilities")
+ (DATA_TYPE** ARGOUTVIEWM_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
+{
+ npy_intp dims[3] = { *$2, *$3, *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3,
+ DATA_TYPE** ARGOUTVIEWM_FARRAY3)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DATA_TYPE** ARGOUTVIEWM_FARRAY3)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements,NumPy_Utilities")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEWM_FARRAY3)
+{
+ npy_intp dims[3] = { *$1, *$2, *$3 };
+ PyObject* obj = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$4));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEWM_ARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY4, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+ $5 = &dim4_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+{
+ npy_intp dims[4] = { *$2, *$3, *$4 , *$5 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4,
+ DATA_TYPE** ARGOUTVIEWM_ARRAY4)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 , DATA_TYPE** ARGOUTVIEWM_ARRAY4)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &dim4_temp;
+ $5 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEWM_ARRAY4)
+{
+ npy_intp dims[4] = { *$1, *$2, *$3 , *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$5));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEWM_FARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEWM_FARRAY4, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+ $5 = &dim4_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements,NumPy_Utilities")
+ (DATA_TYPE** ARGOUTVIEWM_FARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
+{
+ npy_intp dims[4] = { *$2, *$3, *$4 , *$5 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4,
+ DATA_TYPE** ARGOUTVIEWM_FARRAY4)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 , DATA_TYPE** ARGOUTVIEWM_FARRAY4)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &dim4_temp;
+ $5 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements,NumPy_Utilities")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEWM_FARRAY4)
+{
+ npy_intp dims[4] = { *$1, *$2, *$3 , *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$5));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEWM_ARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY4, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+ $5 = &dim4_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DATA_TYPE** ARGOUTVIEWM_ARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+{
+ npy_intp dims[4] = { *$2, *$3, *$4 , *$5 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4,
+ DATA_TYPE** ARGOUTVIEWM_ARRAY4)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 , DATA_TYPE** ARGOUTVIEWM_ARRAY4)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &dim4_temp;
+ $5 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Utilities")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEWM_ARRAY4)
+{
+ npy_intp dims[4] = { *$1, *$2, *$3 , *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$5));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DATA_TYPE** ARGOUTVIEWM_FARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2,
+ DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+ */
+%typemap(in,numinputs=0)
+ (DATA_TYPE** ARGOUTVIEWM_FARRAY4, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 )
+ (DATA_TYPE* data_temp = NULL , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp)
+{
+ $1 = &data_temp;
+ $2 = &dim1_temp;
+ $3 = &dim2_temp;
+ $4 = &dim3_temp;
+ $5 = &dim4_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements,NumPy_Utilities")
+ (DATA_TYPE** ARGOUTVIEWM_FARRAY4, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4)
+{
+ npy_intp dims[4] = { *$2, *$3, *$4 , *$5 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$1));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4,
+ DATA_TYPE** ARGOUTVIEWM_FARRAY4)
+ */
+%typemap(in,numinputs=0)
+ (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DIM_TYPE* DIM3 , DIM_TYPE* DIM4 , DATA_TYPE** ARGOUTVIEWM_FARRAY4)
+ (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DIM_TYPE dim4_temp, DATA_TYPE* data_temp = NULL )
+{
+ $1 = &dim1_temp;
+ $2 = &dim2_temp;
+ $3 = &dim3_temp;
+ $4 = &dim4_temp;
+ $5 = &data_temp;
+}
+%typemap(argout,
+ fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements,NumPy_Utilities")
+ (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DIM_TYPE* DIM4, DATA_TYPE** ARGOUTVIEWM_FARRAY4)
+{
+ npy_intp dims[4] = { *$1, *$2, *$3 , *$4 };
+ PyObject* obj = PyArray_SimpleNewFromData(4, dims, DATA_TYPECODE, (void*)(*$5));
+ PyArrayObject* array = (PyArrayObject*) obj;
+
+ if (!array || !require_fortran(array)) SWIG_fail;
+
+%#ifdef SWIGPY_USE_CAPSULE
+ PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, free_cap);
+%#else
+ PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free);
+%#endif
+
+%#if NPY_API_VERSION < 0x00000007
+ PyArray_BASE(array) = cap;
+%#else
+ PyArray_SetBaseObject(array,cap);
+%#endif
+
+ $result = SWIG_Python_AppendOutput($result,obj);
+}
+
+%enddef /* %numpy_typemaps() macro */
+/* *************************************************************** */
+
+/* Concrete instances of the %numpy_typemaps() macro: Each invocation
+ * below applies all of the typemaps above to the specified data type.
+ */
+%numpy_typemaps(signed char , NPY_BYTE , int)
+%numpy_typemaps(unsigned char , NPY_UBYTE , int)
+%numpy_typemaps(short , NPY_SHORT , int)
+%numpy_typemaps(unsigned short , NPY_USHORT , int)
+%numpy_typemaps(int , NPY_INT , int)
+%numpy_typemaps(unsigned int , NPY_UINT , int)
+%numpy_typemaps(long , NPY_LONG , int)
+%numpy_typemaps(unsigned long , NPY_ULONG , int)
+%numpy_typemaps(long long , NPY_LONGLONG , int)
+%numpy_typemaps(unsigned long long, NPY_ULONGLONG, int)
+%numpy_typemaps(float , NPY_FLOAT , int)
+%numpy_typemaps(double , NPY_DOUBLE , int)
+
+/* ***************************************************************
+ * The follow macro expansion does not work, because C++ bool is 4
+ * bytes and NPY_BOOL is 1 byte
+ *
+ * %numpy_typemaps(bool, NPY_BOOL, int)
+ */
+
+/* ***************************************************************
+ * On my Mac, I get the following warning for this macro expansion:
+ * 'swig/python detected a memory leak of type 'long double *', no destructor found.'
+ *
+ * %numpy_typemaps(long double, NPY_LONGDOUBLE, int)
+ */
+
+/* ***************************************************************
+ * Swig complains about a syntax error for the following macro
+ * expansions:
+ *
+ * %numpy_typemaps(complex float, NPY_CFLOAT , int)
+ *
+ * %numpy_typemaps(complex double, NPY_CDOUBLE, int)
+ *
+ * %numpy_typemaps(complex long double, NPY_CLONGDOUBLE, int)
+ */
+
+#endif /* SWIGPYTHON */
diff --git a/tensorflow/python/platform/parameterized.py b/tensorflow/python/platform/parameterized.py
new file mode 100644
index 0000000000..cf01512bc1
--- /dev/null
+++ b/tensorflow/python/platform/parameterized.py
@@ -0,0 +1,10 @@
+"""Switch between depending on pyglib.gfile or an OSS replacement."""
+# pylint: disable=unused-import
+# pylint: disable=g-import-not-at-top
+# pylint: disable=wildcard-import
+import tensorflow.python.platform
+import control_imports
+if control_imports.USE_OSS and control_imports.OSS_PARAMETERIZED:
+ from tensorflow.python.platform.default._parameterized import *
+else:
+ from tensorflow.python.platform.google._parameterized import *
diff --git a/tensorflow/python/platform/resource_loader.py b/tensorflow/python/platform/resource_loader.py
new file mode 100644
index 0000000000..a0e6546c28
--- /dev/null
+++ b/tensorflow/python/platform/resource_loader.py
@@ -0,0 +1,10 @@
+"""Load a file resource and return the contents."""
+# pylint: disable=unused-import
+# pylint: disable=g-import-not-at-top
+# pylint: disable=wildcard-import
+import control_imports
+import tensorflow.python.platform
+if control_imports.USE_OSS:
+ from tensorflow.python.platform.default._resource_loader import *
+else:
+ from tensorflow.python.platform.google._resource_loader import *
diff --git a/tensorflow/python/platform/status_bar.py b/tensorflow/python/platform/status_bar.py
new file mode 100644
index 0000000000..720b9d82c0
--- /dev/null
+++ b/tensorflow/python/platform/status_bar.py
@@ -0,0 +1,10 @@
+"""Switch between an internal status bar and a no-op version."""
+# pylint: disable=unused-import
+# pylint: disable=g-import-not-at-top
+# pylint: disable=wildcard-import
+import tensorflow.python.platform
+import control_imports
+if control_imports.USE_OSS:
+ from tensorflow.python.platform.default._status_bar import *
+else:
+ from tensorflow.python.platform.google._status_bar import *
diff --git a/tensorflow/python/platform/test.py b/tensorflow/python/platform/test.py
new file mode 100644
index 0000000000..7d46f9cbc2
--- /dev/null
+++ b/tensorflow/python/platform/test.py
@@ -0,0 +1,6 @@
+from tensorflow.python.platform.googletest import GetTempDir
+from tensorflow.python.platform.googletest import main
+from tensorflow.python.framework.test_util import TensorFlowTestCase as TestCase
+from tensorflow.python.framework.test_util import IsGoogleCudaEnabled as IsBuiltWithCuda
+
+get_temp_dir = GetTempDir