def __init__(self, toolRootDir, libFileName='hdllib.cfg', toolFileName='hdltool_<toolset>.cfg'):
"""Get tool dictionary info from toolRootDir and all HDL library dictionary info for it
- self.tool.dicts = single dictionary that contains the tool info (only one tool dict in dicts list)
- self.libs.dicts = list of dictionaries that contains the info of the HDL libraries.
The libRootDir parameter is defined in the hdltool_<toolset>.cfg file and is the root directory from where the hdllib.cfg
files are searched for.
The technologyNames parameter is defined in the hdltool_<toolset>.cfg file. All generic HDL libraries and these
technology specific libraries are kept. If technologyNames is:
[] : Keep all HDL libraries that were found.
['ip_stratixiv', 'ip_arria10'] : The HDL libraries with a hdl_lib_technology that is not '' or does not match one of the technologies
in technologyNames are removed from the list of HDL library dictionaries.
"""
self.toolRootDir = toolRootDir
# HDL tool config file
self.tool = common_dict_file.CommonDictFile(toolRootDir, toolFileName) # tool dict file
if self.tool.nof_dicts==0: sys.exit('Error : No HDL tool config file found')
if self.tool.nof_dicts >1: sys.exit('Error : Multiple HDL tool config files found')
self.tool_dict = self.tool.dicts[0] # there is only one tool dict in dicts list so for convenience make it also accessible as self.tool_dict
# HDL library config files
self.libRootDir = os.path.expandvars(self.tool_dict['lib_root_dir'])
self.libs = common_dict_file.CommonDictFile(self.libRootDir, libFileName) # library dict files
if self.libs.nof_dicts==0: sys.exit('Error : No HDL library config file found')
# Keep the generic HDL libraries and remove those that do not match the specified IP technologies
self.technologyNames = os.path.expandvars(self.tool_dict['technology_names'])
self.removed_dicts = []
print 'self.technologyNames=',self.technologyNames
if len(self.technologyNames)>0:
for d in self.libs.dicts:
#if not(d['hdl_lib_technology']=='' or d['hdl_lib_technology'] in self.technologyNames):
#print 'd[hdl_lib_technology]=',d['hdl_lib_technology']
if not(d['hdl_lib_technology']=='' or d['hdl_lib_technology'] == self.technologyNames):
self.removed_dicts.append(d)
#print 'remove=',d
for d in self.removed_dicts:
self.libs.remove_dict_from_list(d)
# Keep list of HDL library names
self.lib_names = self.libs.get_key_values('hdl_lib_name')
# Check that there are no duplicate library names (eg. due to copying a hdlib.cfg without modifying the hdl_lib_name value)
duplicate_lib_names = cm.list_duplicates(self.lib_names)
if len(duplicate_lib_names)>0: sys.exit('Error : Duplicate HDL library config file found %s' % duplicate_lib_names)
def MaxDecodingNonUniq ( F ):
""" F is a list of max marginal factors passed in. We don't assume that there is a unique
max value. So we get the indices of the non-uniq max value as a tuple and add it to """
ASSIGNMENTS=[]
for f in F:
values=f.getVal().tolist()
maxvalue=max(values)
""" if the maxvalue is duplicated, we get the indices of where it resides in the value array """
if common.isMaxDuplicated(values):
dup_indices_list=[dup for dup in sorted(common.list_duplicates(values)) ]
dup_values= [ x for (x, y) in dup_indices_list ]
dup_indices= [ y for (x, y) in dup_indices_list ]
non_uniq_max_indices=tuple(dup_indices [ dup_values.index(maxvalue) ])
ASSIGNMENTS.append ( non_uniq_max_indices )
else:
ASSIGNMENTS.append( values.index(maxvalue))
return ASSIGNMENTS
def MaxDecodingNonUniq(F):
""" F is a list of max marginal factors passed in. We don't assume that there is a unique
max value. So we get the indices of the non-uniq max value as a tuple and add it to """
ASSIGNMENTS = []
for f in F:
values = f.getVal().tolist()
maxvalue = max(values)
""" if the maxvalue is duplicated, we get the indices of where it resides in the value array """
if common.isMaxDuplicated(values):
dup_indices_list = [
dup for dup in sorted(common.list_duplicates(values))
]
dup_values = [x for (x, y) in dup_indices_list]
dup_indices = [y for (x, y) in dup_indices_list]
non_uniq_max_indices = tuple(
dup_indices[dup_values.index(maxvalue)])
ASSIGNMENTS.append(non_uniq_max_indices)
else:
ASSIGNMENTS.append(values.index(maxvalue))
return ASSIGNMENTS
