def testMetadataLoading( self ) : os.environ["ARNOLD_PLUGIN_PATH"] = os.path.join( os.path.dirname( __file__ ), "metadata" ) with IECoreArnold.UniverseBlock( writable = True ) : pass with IECoreArnold.UniverseBlock( writable = False ) : e = arnold.AiNodeEntryLookUp( "options" ) s = arnold.AtStringReturn() i = ctypes.c_int() arnold.AiMetaDataGetStr( e, "", "cortex.testString", s ) self.assertEqual( arnold.AtStringToStr( s ), "test" ) arnold.AiMetaDataGetInt( e, "", "cortex.testInt", i ) self.assertEqual( i.value, 25 ) arnold.AiMetaDataGetStr( e, "AA_samples", "cortex.testString", s ) self.assertEqual( arnold.AtStringToStr( s ), "test2" ) arnold.AiMetaDataGetInt( e, "AA_samples", "cortex.testInt", i ) self.assertEqual( i.value, 12 )
def testMetadataLoading(self):
metadataPath = os.path.join(os.path.dirname(__file__), "metadata")
if metadataPath not in os.environ["ARNOLD_PLUGIN_PATH"].split(":"):
# Relaunch test in subprocess with our metadata on the plugin path.
env = os.environ.copy()
env["ARNOLD_PLUGIN_PATH"] = env[
"ARNOLD_PLUGIN_PATH"] + ":" + metadataPath
try:
subprocess.check_output([
"gaffer", "test",
"IECoreArnoldTest.UniverseBlockTest.testMetadataLoading"
],
env=env,
stderr=subprocess.STDOUT)
except subprocess.CalledProcessError as e:
self.fail(e.output)
else:
# Our metadata is on the plugin path. Check that it has been loaded.
with IECoreArnold.UniverseBlock(writable=False):
e = arnold.AiNodeEntryLookUp("options")
s = arnold.AtStringReturn()
i = ctypes.c_int()
arnold.AiMetaDataGetStr(e, "", "cortex.testString", s)
self.assertEqual(arnold.AtStringToStr(s), "test")
arnold.AiMetaDataGetInt(e, "", "cortex.testInt", i)
self.assertEqual(i.value, 25)
arnold.AiMetaDataGetStr(e, "AA_samples", "cortex.testString",
s)
self.assertEqual(arnold.AtStringToStr(s), "test2")
arnold.AiMetaDataGetInt(e, "AA_samples", "cortex.testInt", i)
self.assertEqual(i.value, 12)
def testMetadataLoading(self):
with IECoreArnold.UniverseBlock(writable=False):
e = arnold.AiNodeEntryLookUp("options")
s = arnold.AtStringReturn()
i = ctypes.c_int()
arnold.AiMetaDataGetStr(e, "", "cortex.testString", s)
self.assertEqual(arnold.AtStringToStr(s), "test")
arnold.AiMetaDataGetInt(e, "", "cortex.testInt", i)
self.assertEqual(i.value, 25)
arnold.AiMetaDataGetStr(e, "AA_samples", "cortex.testString", s)
self.assertEqual(arnold.AtStringToStr(s), "test2")
arnold.AiMetaDataGetInt(e, "AA_samples", "cortex.testInt", i)
self.assertEqual(i.value, 12)
ignoreCameraAttributes + ['focus_distance']
}
'''
Now let's create a new class for each "type", let it inherit from a meaningful schema, and let's add its parameters based on the existing dictionary
'''
for key, paramList in typeParams.iteritems():
if key == 'override':
continue
entryNames = entryByType[key] # list of entry names for this type
if entryNames == None or len(entryNames) == 0:
print 'This script is not working...no entries found for type {}'.format(
key)
entryName = entryNames[0] # using the first entry found here
nentry = ai.AiNodeEntryLookUp(entryName)
if nentry == None:
print 'Hey I could not find any AtNodeEntry called {}'.format(
entryName)
continue
# these "base" arnold classes are typed but can't be instantiated
createArnoldClass(key, 'Typed', paramList, nentry, None, False, False)
# For the API schemas of arnold common types, we want to remove the attributes from the USD builtin
if key in nativeUsdList:
createArnoldClass(key, 'APISchemaBase', paramList, nentry,
nativeUsdList[key], True)
for entry in entryList:
entryName = entry[0]
