move 3rd-party librarys into libs/ and add built-in honeysuckle

1 files changed, 283 insertions, 0 deletions

diff --git a/libs/assimp/port/PyAssimp/pyassimp/helper.py b/libs/assimp/port/PyAssimp/pyassimp/helper.py
new file mode 100644
index 0000000..7c14f60
--- /dev/null
+++ b/libs/assimp/port/PyAssimp/pyassimp/helper.py
@@ -0,0 +1,283 @@
+#-*- coding: UTF-8 -*-
+
+"""
+Some fancy helper functions.
+"""
+
+import os
+import ctypes
+import operator
+
+from distutils.sysconfig import get_python_lib
+import re
+import sys
+
+try: import numpy
+except ImportError: numpy = None
+
+import logging;logger = logging.getLogger("pyassimp")
+
+from .errors import AssimpError
+
+additional_dirs, ext_whitelist = [],[]
+
+# populate search directories and lists of allowed file extensions
+# depending on the platform we're running on.
+if os.name=='posix':
+    additional_dirs.append('./')
+    additional_dirs.append('/usr/lib/')
+    additional_dirs.append('/usr/lib/x86_64-linux-gnu/')
+    additional_dirs.append('/usr/lib/aarch64-linux-gnu/')
+    additional_dirs.append('/usr/local/lib/')
+
+    if 'LD_LIBRARY_PATH' in os.environ:
+        additional_dirs.extend([item for item in os.environ['LD_LIBRARY_PATH'].split(':') if item])
+
+    # check if running from anaconda.
+    anaconda_keywords = ("conda", "continuum")
+    if any(k in sys.version.lower() for k in anaconda_keywords):
+      cur_path = get_python_lib()
+      pattern = re.compile('.*\/lib\/')
+      conda_lib = pattern.match(cur_path).group()
+      logger.info("Adding Anaconda lib path:"+ conda_lib)
+      additional_dirs.append(conda_lib)
+
+    # note - this won't catch libassimp.so.N.n, but
+    # currently there's always a symlink called
+    # libassimp.so in /usr/local/lib.
+    ext_whitelist.append('.so')
+    # libassimp.dylib in /usr/local/lib
+    ext_whitelist.append('.dylib')
+
+elif os.name=='nt':
+    ext_whitelist.append('.dll')
+    path_dirs = os.environ['PATH'].split(';')
+    additional_dirs.extend(path_dirs)
+
+def vec2tuple(x):
+    """ Converts a VECTOR3D to a Tuple """
+    return (x.x, x.y, x.z)
+
+def transform(vector3, matrix4x4):
+    """ Apply a transformation matrix on a 3D vector.
+
+    :param vector3: array with 3 elements
+    :param matrix4x4: 4x4 matrix
+    """
+    if numpy:
+        return numpy.dot(matrix4x4, numpy.append(vector3, 1.))
+    else:
+        m0,m1,m2,m3 = matrix4x4; x,y,z = vector3
+        return [
+            m0[0]*x + m0[1]*y + m0[2]*z + m0[3],
+            m1[0]*x + m1[1]*y + m1[2]*z + m1[3],
+            m2[0]*x + m2[1]*y + m2[2]*z + m2[3],
+            m3[0]*x + m3[1]*y + m3[2]*z + m3[3]
+            ]
+
+def _inv(matrix4x4):
+    m0,m1,m2,m3 = matrix4x4
+
+    det  =  m0[3]*m1[2]*m2[1]*m3[0] - m0[2]*m1[3]*m2[1]*m3[0] - \
+            m0[3]*m1[1]*m2[2]*m3[0] + m0[1]*m1[3]*m2[2]*m3[0] + \
+            m0[2]*m1[1]*m2[3]*m3[0] - m0[1]*m1[2]*m2[3]*m3[0] - \
+            m0[3]*m1[2]*m2[0]*m3[1] + m0[2]*m1[3]*m2[0]*m3[1] + \
+            m0[3]*m1[0]*m2[2]*m3[1] - m0[0]*m1[3]*m2[2]*m3[1] - \
+            m0[2]*m1[0]*m2[3]*m3[1] + m0[0]*m1[2]*m2[3]*m3[1] + \
+            m0[3]*m1[1]*m2[0]*m3[2] - m0[1]*m1[3]*m2[0]*m3[2] - \
+            m0[3]*m1[0]*m2[1]*m3[2] + m0[0]*m1[3]*m2[1]*m3[2] + \
+            m0[1]*m1[0]*m2[3]*m3[2] - m0[0]*m1[1]*m2[3]*m3[2] - \
+            m0[2]*m1[1]*m2[0]*m3[3] + m0[1]*m1[2]*m2[0]*m3[3] + \
+            m0[2]*m1[0]*m2[1]*m3[3] - m0[0]*m1[2]*m2[1]*m3[3] - \
+            m0[1]*m1[0]*m2[2]*m3[3] + m0[0]*m1[1]*m2[2]*m3[3]
+
+    return[[( m1[2]*m2[3]*m3[1] - m1[3]*m2[2]*m3[1] + m1[3]*m2[1]*m3[2] - m1[1]*m2[3]*m3[2] - m1[2]*m2[1]*m3[3] + m1[1]*m2[2]*m3[3]) /det,
+            ( m0[3]*m2[2]*m3[1] - m0[2]*m2[3]*m3[1] - m0[3]*m2[1]*m3[2] + m0[1]*m2[3]*m3[2] + m0[2]*m2[1]*m3[3] - m0[1]*m2[2]*m3[3]) /det,
+            ( m0[2]*m1[3]*m3[1] - m0[3]*m1[2]*m3[1] + m0[3]*m1[1]*m3[2] - m0[1]*m1[3]*m3[2] - m0[2]*m1[1]*m3[3] + m0[1]*m1[2]*m3[3]) /det,
+            ( m0[3]*m1[2]*m2[1] - m0[2]*m1[3]*m2[1] - m0[3]*m1[1]*m2[2] + m0[1]*m1[3]*m2[2] + m0[2]*m1[1]*m2[3] - m0[1]*m1[2]*m2[3]) /det],
+           [( m1[3]*m2[2]*m3[0] - m1[2]*m2[3]*m3[0] - m1[3]*m2[0]*m3[2] + m1[0]*m2[3]*m3[2] + m1[2]*m2[0]*m3[3] - m1[0]*m2[2]*m3[3]) /det,
+            ( m0[2]*m2[3]*m3[0] - m0[3]*m2[2]*m3[0] + m0[3]*m2[0]*m3[2] - m0[0]*m2[3]*m3[2] - m0[2]*m2[0]*m3[3] + m0[0]*m2[2]*m3[3]) /det,
+            ( m0[3]*m1[2]*m3[0] - m0[2]*m1[3]*m3[0] - m0[3]*m1[0]*m3[2] + m0[0]*m1[3]*m3[2] + m0[2]*m1[0]*m3[3] - m0[0]*m1[2]*m3[3]) /det,
+            ( m0[2]*m1[3]*m2[0] - m0[3]*m1[2]*m2[0] + m0[3]*m1[0]*m2[2] - m0[0]*m1[3]*m2[2] - m0[2]*m1[0]*m2[3] + m0[0]*m1[2]*m2[3]) /det],
+           [( m1[1]*m2[3]*m3[0] - m1[3]*m2[1]*m3[0] + m1[3]*m2[0]*m3[1] - m1[0]*m2[3]*m3[1] - m1[1]*m2[0]*m3[3] + m1[0]*m2[1]*m3[3]) /det,
+            ( m0[3]*m2[1]*m3[0] - m0[1]*m2[3]*m3[0] - m0[3]*m2[0]*m3[1] + m0[0]*m2[3]*m3[1] + m0[1]*m2[0]*m3[3] - m0[0]*m2[1]*m3[3]) /det,
+            ( m0[1]*m1[3]*m3[0] - m0[3]*m1[1]*m3[0] + m0[3]*m1[0]*m3[1] - m0[0]*m1[3]*m3[1] - m0[1]*m1[0]*m3[3] + m0[0]*m1[1]*m3[3]) /det,
+            ( m0[3]*m1[1]*m2[0] - m0[1]*m1[3]*m2[0] - m0[3]*m1[0]*m2[1] + m0[0]*m1[3]*m2[1] + m0[1]*m1[0]*m2[3] - m0[0]*m1[1]*m2[3]) /det],
+           [( m1[2]*m2[1]*m3[0] - m1[1]*m2[2]*m3[0] - m1[2]*m2[0]*m3[1] + m1[0]*m2[2]*m3[1] + m1[1]*m2[0]*m3[2] - m1[0]*m2[1]*m3[2]) /det,
+            ( m0[1]*m2[2]*m3[0] - m0[2]*m2[1]*m3[0] + m0[2]*m2[0]*m3[1] - m0[0]*m2[2]*m3[1] - m0[1]*m2[0]*m3[2] + m0[0]*m2[1]*m3[2]) /det,
+            ( m0[2]*m1[1]*m3[0] - m0[1]*m1[2]*m3[0] - m0[2]*m1[0]*m3[1] + m0[0]*m1[2]*m3[1] + m0[1]*m1[0]*m3[2] - m0[0]*m1[1]*m3[2]) /det,
+            ( m0[1]*m1[2]*m2[0] - m0[2]*m1[1]*m2[0] + m0[2]*m1[0]*m2[1] - m0[0]*m1[2]*m2[1] - m0[1]*m1[0]*m2[2] + m0[0]*m1[1]*m2[2]) /det]]
+
+def get_bounding_box(scene):
+    bb_min = [1e10, 1e10, 1e10] # x,y,z
+    bb_max = [-1e10, -1e10, -1e10] # x,y,z
+    inv = numpy.linalg.inv if numpy else _inv
+    return get_bounding_box_for_node(scene.rootnode, bb_min, bb_max, inv(scene.rootnode.transformation))
+
+def get_bounding_box_for_node(node, bb_min, bb_max, transformation):
+
+    if numpy:
+        transformation = numpy.dot(transformation, node.transformation)
+    else:
+        t0,t1,t2,t3 = transformation
+        T0,T1,T2,T3 = node.transformation
+        transformation = [ [
+                t0[0]*T0[0] + t0[1]*T1[0] + t0[2]*T2[0] + t0[3]*T3[0],
+                t0[0]*T0[1] + t0[1]*T1[1] + t0[2]*T2[1] + t0[3]*T3[1],
+                t0[0]*T0[2] + t0[1]*T1[2] + t0[2]*T2[2] + t0[3]*T3[2],
+                t0[0]*T0[3] + t0[1]*T1[3] + t0[2]*T2[3] + t0[3]*T3[3]
+            ],[
+                t1[0]*T0[0] + t1[1]*T1[0] + t1[2]*T2[0] + t1[3]*T3[0],
+                t1[0]*T0[1] + t1[1]*T1[1] + t1[2]*T2[1] + t1[3]*T3[1],
+                t1[0]*T0[2] + t1[1]*T1[2] + t1[2]*T2[2] + t1[3]*T3[2],
+                t1[0]*T0[3] + t1[1]*T1[3] + t1[2]*T2[3] + t1[3]*T3[3]
+            ],[
+                t2[0]*T0[0] + t2[1]*T1[0] + t2[2]*T2[0] + t2[3]*T3[0],
+                t2[0]*T0[1] + t2[1]*T1[1] + t2[2]*T2[1] + t2[3]*T3[1],
+                t2[0]*T0[2] + t2[1]*T1[2] + t2[2]*T2[2] + t2[3]*T3[2],
+                t2[0]*T0[3] + t2[1]*T1[3] + t2[2]*T2[3] + t2[3]*T3[3]
+            ],[
+                t3[0]*T0[0] + t3[1]*T1[0] + t3[2]*T2[0] + t3[3]*T3[0],
+                t3[0]*T0[1] + t3[1]*T1[1] + t3[2]*T2[1] + t3[3]*T3[1],
+                t3[0]*T0[2] + t3[1]*T1[2] + t3[2]*T2[2] + t3[3]*T3[2],
+                t3[0]*T0[3] + t3[1]*T1[3] + t3[2]*T2[3] + t3[3]*T3[3]
+            ] ]
+
+    for mesh in node.meshes:
+        for v in mesh.vertices:
+            v = transform(v, transformation)
+            bb_min[0] = min(bb_min[0], v[0])
+            bb_min[1] = min(bb_min[1], v[1])
+            bb_min[2] = min(bb_min[2], v[2])
+            bb_max[0] = max(bb_max[0], v[0])
+            bb_max[1] = max(bb_max[1], v[1])
+            bb_max[2] = max(bb_max[2], v[2])
+
+
+    for child in node.children:
+        bb_min, bb_max = get_bounding_box_for_node(child, bb_min, bb_max, transformation)
+
+    return bb_min, bb_max
+
+def try_load_functions(library_path, dll):
+    '''
+    Try to bind to aiImportFile and aiReleaseImport
+
+    Arguments
+    ---------
+    library_path: path to current lib
+    dll:          ctypes handle to library
+
+    Returns
+    ---------
+    If unsuccessful:
+        None
+    If successful:
+        Tuple containing (library_path,
+                          load from filename function,
+                          load from memory function,
+                          export to filename function,
+                          export to blob function,
+                          release function,
+                          ctypes handle to assimp library)
+    '''
+
+    try:
+        load     = dll.aiImportFile
+        release  = dll.aiReleaseImport
+        load_mem = dll.aiImportFileFromMemory
+        export   = dll.aiExportScene
+        export2blob = dll.aiExportSceneToBlob
+    except AttributeError:
+        #OK, this is a library, but it doesn't have the functions we need
+        return None
+
+    # library found!
+    from .structs import Scene, ExportDataBlob
+    load.restype = ctypes.POINTER(Scene)
+    load_mem.restype = ctypes.POINTER(Scene)
+    export2blob.restype = ctypes.POINTER(ExportDataBlob)
+    return (library_path, load, load_mem, export, export2blob, release, dll)
+
+def search_library():
+    '''
+    Loads the assimp library.
+    Throws exception AssimpError if no library_path is found
+
+    Returns: tuple, (load from filename function,
+                     load from memory function,
+                     export to filename function,
+                     export to blob function,
+                     release function,
+                     dll)
+    '''
+    #this path
+    folder = os.path.dirname(__file__)
+
+    # silence 'DLL not found' message boxes on win
+    try:
+        ctypes.windll.kernel32.SetErrorMode(0x8007)
+    except AttributeError:
+        pass
+
+    candidates = []
+    # test every file
+    for curfolder in [folder]+additional_dirs:
+        if os.path.isdir(curfolder):
+            for filename in os.listdir(curfolder):
+                # our minimum requirement for candidates is that
+                # they should contain 'assimp' somewhere in
+                # their name                                  
+                if filename.lower().find('assimp')==-1 : 
+                    continue
+                is_out=1
+                for et in ext_whitelist:
+                  if et in filename.lower():
+                    is_out=0
+                    break
+                if is_out:
+                  continue
+                
+                library_path = os.path.join(curfolder, filename)
+                logger.debug('Try ' + library_path)
+                try:
+                    dll = ctypes.cdll.LoadLibrary(library_path)
+                except Exception as e:
+                    logger.warning(str(e))
+                    # OK, this except is evil. But different OSs will throw different
+                    # errors. So just ignore any errors.
+                    continue
+                # see if the functions we need are in the dll
+                loaded = try_load_functions(library_path, dll)
+                if loaded: candidates.append(loaded)
+
+    if not candidates:
+        # no library found
+        raise AssimpError("assimp library not found")
+    else:
+        # get the newest library_path
+        candidates = map(lambda x: (os.lstat(x[0])[-2], x), candidates)
+        res = max(candidates, key=operator.itemgetter(0))[1]
+        logger.debug('Using assimp library located at ' + res[0])
+
+        # XXX: if there are 1000 dll/so files containing 'assimp'
+        # in their name, do we have all of them in our address
+        # space now until gc kicks in?
+
+        # XXX: take version postfix of the .so on linux?
+        return res[1:]
+
+def hasattr_silent(object, name):
+    """
+        Calls hasttr() with the given parameters and preserves the legacy (pre-Python 3.2)
+        functionality of silently catching exceptions.
+
+        Returns the result of hasatter() or False if an exception was raised.
+    """
+
+    try:
+        if not object:
+            return False
+        return hasattr(object, name)
+    except AttributeError:
+        return False