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250,000
trailofbits/protofuzz
protofuzz/pbimport.py
_load_module
def _load_module(path): 'Helper to load a Python file at path and return as a module' module_name = os.path.splitext(os.path.basename(path))[0] module = None if sys.version_info.minor < 5: loader = importlib.machinery.SourceFileLoader(module_name, path) module = loader.load_module() else: spec = importlib.util.spec_from_file_location(module_name, path) module = importlib.util.module_from_spec(spec) spec.loader.exec_module(module) return module
python
def _load_module(path): 'Helper to load a Python file at path and return as a module' module_name = os.path.splitext(os.path.basename(path))[0] module = None if sys.version_info.minor < 5: loader = importlib.machinery.SourceFileLoader(module_name, path) module = loader.load_module() else: spec = importlib.util.spec_from_file_location(module_name, path) module = importlib.util.module_from_spec(spec) spec.loader.exec_module(module) return module
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Helper to load a Python file at path and return as a module
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/pbimport.py#L63-L77
250,001
trailofbits/protofuzz
protofuzz/pbimport.py
_compile_proto
def _compile_proto(full_path, dest): 'Helper to compile protobuf files' proto_path = os.path.dirname(full_path) protoc_args = [find_protoc(), '--python_out={}'.format(dest), '--proto_path={}'.format(proto_path), full_path] proc = subprocess.Popen(protoc_args, stdout=subprocess.PIPE, stderr=subprocess.PIPE) try: outs, errs = proc.communicate(timeout=5) except subprocess.TimeoutExpired: proc.kill() outs, errs = proc.communicate() return False if proc.returncode != 0: msg = 'Failed compiling "{}": \n\nstderr: {}\nstdout: {}'.format( full_path, errs.decode('utf-8'), outs.decode('utf-8')) raise BadProtobuf(msg) return True
python
def _compile_proto(full_path, dest): 'Helper to compile protobuf files' proto_path = os.path.dirname(full_path) protoc_args = [find_protoc(), '--python_out={}'.format(dest), '--proto_path={}'.format(proto_path), full_path] proc = subprocess.Popen(protoc_args, stdout=subprocess.PIPE, stderr=subprocess.PIPE) try: outs, errs = proc.communicate(timeout=5) except subprocess.TimeoutExpired: proc.kill() outs, errs = proc.communicate() return False if proc.returncode != 0: msg = 'Failed compiling "{}": \n\nstderr: {}\nstdout: {}'.format( full_path, errs.decode('utf-8'), outs.decode('utf-8')) raise BadProtobuf(msg) return True
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Helper to compile protobuf files
[ "Helper", "to", "compile", "protobuf", "files" ]
589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/pbimport.py#L80-L101
250,002
trailofbits/protofuzz
protofuzz/pbimport.py
from_file
def from_file(proto_file): ''' Take a filename |protoc_file|, compile it via the Protobuf compiler, and import the module. Return the module if successfully compiled, otherwise raise either a ProtocNotFound or BadProtobuf exception. ''' if not proto_file.endswith('.proto'): raise BadProtobuf() dest = tempfile.mkdtemp() full_path = os.path.abspath(proto_file) _compile_proto(full_path, dest) filename = os.path.split(full_path)[-1] name = re.search(r'^(.*)\.proto$', filename).group(1) target = os.path.join(dest, name+'_pb2.py') return _load_module(target)
python
def from_file(proto_file): ''' Take a filename |protoc_file|, compile it via the Protobuf compiler, and import the module. Return the module if successfully compiled, otherwise raise either a ProtocNotFound or BadProtobuf exception. ''' if not proto_file.endswith('.proto'): raise BadProtobuf() dest = tempfile.mkdtemp() full_path = os.path.abspath(proto_file) _compile_proto(full_path, dest) filename = os.path.split(full_path)[-1] name = re.search(r'^(.*)\.proto$', filename).group(1) target = os.path.join(dest, name+'_pb2.py') return _load_module(target)
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Take a filename |protoc_file|, compile it via the Protobuf compiler, and import the module. Return the module if successfully compiled, otherwise raise either a ProtocNotFound or BadProtobuf exception.
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/pbimport.py#L104-L123
250,003
trailofbits/protofuzz
protofuzz/pbimport.py
types_from_module
def types_from_module(pb_module): ''' Return protobuf class types from an imported generated module. ''' types = pb_module.DESCRIPTOR.message_types_by_name return [getattr(pb_module, name) for name in types]
python
def types_from_module(pb_module): ''' Return protobuf class types from an imported generated module. ''' types = pb_module.DESCRIPTOR.message_types_by_name return [getattr(pb_module, name) for name in types]
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Return protobuf class types from an imported generated module.
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/pbimport.py#L126-L131
250,004
trailofbits/protofuzz
protofuzz/gen.py
Permuter._resolve_child
def _resolve_child(self, path): 'Return a member generator by a dot-delimited path' obj = self for component in path.split('.'): ptr = obj if not isinstance(ptr, Permuter): raise self.MessageNotFound("Bad element path [wrong type]") # pylint: disable=protected-access found_gen = (_ for _ in ptr._generators if _.name() == component) obj = next(found_gen, None) if not obj: raise self.MessageNotFound("Path '{}' unresolved to member." .format(path)) return ptr, obj
python
def _resolve_child(self, path): 'Return a member generator by a dot-delimited path' obj = self for component in path.split('.'): ptr = obj if not isinstance(ptr, Permuter): raise self.MessageNotFound("Bad element path [wrong type]") # pylint: disable=protected-access found_gen = (_ for _ in ptr._generators if _.name() == component) obj = next(found_gen, None) if not obj: raise self.MessageNotFound("Path '{}' unresolved to member." .format(path)) return ptr, obj
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Return a member generator by a dot-delimited path
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/gen.py#L111-L128
250,005
trailofbits/protofuzz
protofuzz/gen.py
Permuter.make_dependent
def make_dependent(self, source, target, action): ''' Create a dependency between path 'source' and path 'target' via the callable 'action'. >>> permuter._generators [IterValueGenerator(one), IterValueGenerator(two)] >>> permuter.make_dependent('one', 'two', lambda x: x + 1) Going forward, 'two' will only contain values that are (one+1) ''' if not self._generators: return src_permuter, src = self._resolve_child(source) dest = self._resolve_child(target)[1] # pylint: disable=protected-access container = src_permuter._generators idx = container.index(src) container[idx] = DependentValueGenerator(src.name(), dest, action) self._update_independent_generators()
python
def make_dependent(self, source, target, action): ''' Create a dependency between path 'source' and path 'target' via the callable 'action'. >>> permuter._generators [IterValueGenerator(one), IterValueGenerator(two)] >>> permuter.make_dependent('one', 'two', lambda x: x + 1) Going forward, 'two' will only contain values that are (one+1) ''' if not self._generators: return src_permuter, src = self._resolve_child(source) dest = self._resolve_child(target)[1] # pylint: disable=protected-access container = src_permuter._generators idx = container.index(src) container[idx] = DependentValueGenerator(src.name(), dest, action) self._update_independent_generators()
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Create a dependency between path 'source' and path 'target' via the callable 'action'. >>> permuter._generators [IterValueGenerator(one), IterValueGenerator(two)] >>> permuter.make_dependent('one', 'two', lambda x: x + 1) Going forward, 'two' will only contain values that are (one+1)
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/gen.py#L130-L152
250,006
trailofbits/protofuzz
protofuzz/gen.py
Permuter.get
def get(self): 'Retrieve the most recent value generated' # If you attempt to use a generator comprehension below, it will # consume the StopIteration exception and just return an empty tuple, # instead of stopping iteration normally return tuple([(x.name(), x.get()) for x in self._generators])
python
def get(self): 'Retrieve the most recent value generated' # If you attempt to use a generator comprehension below, it will # consume the StopIteration exception and just return an empty tuple, # instead of stopping iteration normally return tuple([(x.name(), x.get()) for x in self._generators])
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Retrieve the most recent value generated
[ "Retrieve", "the", "most", "recent", "value", "generated" ]
589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/gen.py#L154-L159
250,007
trailofbits/protofuzz
protofuzz/values.py
_fuzzdb_integers
def _fuzzdb_integers(limit=0): 'Helper to grab some integers from fuzzdb' path = os.path.join(BASE_PATH, 'integer-overflow/integer-overflows.txt') stream = _open_fuzzdb_file(path) for line in _limit_helper(stream, limit): yield int(line.decode('utf-8'), 0)
python
def _fuzzdb_integers(limit=0): 'Helper to grab some integers from fuzzdb' path = os.path.join(BASE_PATH, 'integer-overflow/integer-overflows.txt') stream = _open_fuzzdb_file(path) for line in _limit_helper(stream, limit): yield int(line.decode('utf-8'), 0)
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Helper to grab some integers from fuzzdb
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/values.py#L31-L36
250,008
trailofbits/protofuzz
protofuzz/values.py
_fuzzdb_get_strings
def _fuzzdb_get_strings(max_len=0): 'Helper to get all the strings from fuzzdb' ignored = ['integer-overflow'] for subdir in pkg_resources.resource_listdir('protofuzz', BASE_PATH): if subdir in ignored: continue path = '{}/{}'.format(BASE_PATH, subdir) listing = pkg_resources.resource_listdir('protofuzz', path) for filename in listing: if not filename.endswith('.txt'): continue path = '{}/{}/{}'.format(BASE_PATH, subdir, filename) source = _open_fuzzdb_file(path) for line in source: string = line.decode('utf-8').strip() if not string or string.startswith('#'): continue if max_len != 0 and len(line) > max_len: continue yield string
python
def _fuzzdb_get_strings(max_len=0): 'Helper to get all the strings from fuzzdb' ignored = ['integer-overflow'] for subdir in pkg_resources.resource_listdir('protofuzz', BASE_PATH): if subdir in ignored: continue path = '{}/{}'.format(BASE_PATH, subdir) listing = pkg_resources.resource_listdir('protofuzz', path) for filename in listing: if not filename.endswith('.txt'): continue path = '{}/{}/{}'.format(BASE_PATH, subdir, filename) source = _open_fuzzdb_file(path) for line in source: string = line.decode('utf-8').strip() if not string or string.startswith('#'): continue if max_len != 0 and len(line) > max_len: continue yield string
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Helper to get all the strings from fuzzdb
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/values.py#L39-L63
250,009
trailofbits/protofuzz
protofuzz/values.py
get_integers
def get_integers(bitwidth, unsigned, limit=0): ''' Get integers from fuzzdb database bitwidth - The bitwidth that has to contain the integer unsigned - Whether the type is unsigned limit - Limit to |limit| results ''' if unsigned: start, stop = 0, ((1 << bitwidth) - 1) else: start, stop = (-(1 << bitwidth-1)), (1 << (bitwidth-1)-1) for num in _fuzzdb_integers(limit): if num >= start and num <= stop: yield num
python
def get_integers(bitwidth, unsigned, limit=0): ''' Get integers from fuzzdb database bitwidth - The bitwidth that has to contain the integer unsigned - Whether the type is unsigned limit - Limit to |limit| results ''' if unsigned: start, stop = 0, ((1 << bitwidth) - 1) else: start, stop = (-(1 << bitwidth-1)), (1 << (bitwidth-1)-1) for num in _fuzzdb_integers(limit): if num >= start and num <= stop: yield num
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Get integers from fuzzdb database bitwidth - The bitwidth that has to contain the integer unsigned - Whether the type is unsigned limit - Limit to |limit| results
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/values.py#L76-L91
250,010
trailofbits/protofuzz
protofuzz/values.py
get_floats
def get_floats(bitwidth, limit=0): ''' Return a number of interesting floating point values ''' assert bitwidth in (32, 64, 80) values = [0.0, -1.0, 1.0, -1231231231231.0123, 123123123123123.123] for val in _limit_helper(values, limit): yield val
python
def get_floats(bitwidth, limit=0): ''' Return a number of interesting floating point values ''' assert bitwidth in (32, 64, 80) values = [0.0, -1.0, 1.0, -1231231231231.0123, 123123123123123.123] for val in _limit_helper(values, limit): yield val
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Return a number of interesting floating point values
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/values.py#L94-L102
250,011
trailofbits/protofuzz
protofuzz/protofuzz.py
_int_generator
def _int_generator(descriptor, bitwidth, unsigned): 'Helper to create a basic integer value generator' vals = list(values.get_integers(bitwidth, unsigned)) return gen.IterValueGenerator(descriptor.name, vals)
python
def _int_generator(descriptor, bitwidth, unsigned): 'Helper to create a basic integer value generator' vals = list(values.get_integers(bitwidth, unsigned)) return gen.IterValueGenerator(descriptor.name, vals)
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Helper to create a basic integer value generator
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L41-L44
250,012
trailofbits/protofuzz
protofuzz/protofuzz.py
_string_generator
def _string_generator(descriptor, max_length=0, limit=0): 'Helper to create a string generator' vals = list(values.get_strings(max_length, limit)) return gen.IterValueGenerator(descriptor.name, vals)
python
def _string_generator(descriptor, max_length=0, limit=0): 'Helper to create a string generator' vals = list(values.get_strings(max_length, limit)) return gen.IterValueGenerator(descriptor.name, vals)
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Helper to create a string generator
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L47-L50
250,013
trailofbits/protofuzz
protofuzz/protofuzz.py
_float_generator
def _float_generator(descriptor, bitwidth): 'Helper to create floating point values' return gen.IterValueGenerator(descriptor.name, values.get_floats(bitwidth))
python
def _float_generator(descriptor, bitwidth): 'Helper to create floating point values' return gen.IterValueGenerator(descriptor.name, values.get_floats(bitwidth))
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Helper to create floating point values
[ "Helper", "to", "create", "floating", "point", "values" ]
589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L60-L62
250,014
trailofbits/protofuzz
protofuzz/protofuzz.py
_enum_generator
def _enum_generator(descriptor): 'Helper to create protobuf enums' vals = descriptor.enum_type.values_by_number.keys() return gen.IterValueGenerator(descriptor.name, vals)
python
def _enum_generator(descriptor): 'Helper to create protobuf enums' vals = descriptor.enum_type.values_by_number.keys() return gen.IterValueGenerator(descriptor.name, vals)
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Helper to create protobuf enums
[ "Helper", "to", "create", "protobuf", "enums" ]
589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L65-L68
250,015
trailofbits/protofuzz
protofuzz/protofuzz.py
_prototype_to_generator
def _prototype_to_generator(descriptor, cls): 'Helper to map a descriptor to a protofuzz generator' _fd = D.FieldDescriptor generator = None ints32 = [_fd.TYPE_INT32, _fd.TYPE_UINT32, _fd.TYPE_FIXED32, _fd.TYPE_SFIXED32, _fd.TYPE_SINT32] ints64 = [_fd.TYPE_INT64, _fd.TYPE_UINT64, _fd.TYPE_FIXED64, _fd.TYPE_SFIXED64, _fd.TYPE_SINT64] ints_signed = [_fd.TYPE_INT32, _fd.TYPE_SFIXED32, _fd.TYPE_SINT32, _fd.TYPE_INT64, _fd.TYPE_SFIXED64, _fd.TYPE_SINT64] if descriptor.type in ints32+ints64: bitwidth = [32, 64][descriptor.type in ints64] unsigned = descriptor.type not in ints_signed generator = _int_generator(descriptor, bitwidth, unsigned) elif descriptor.type == _fd.TYPE_DOUBLE: generator = _float_generator(descriptor, 64) elif descriptor.type == _fd.TYPE_FLOAT: generator = _float_generator(descriptor, 32) elif descriptor.type == _fd.TYPE_STRING: generator = _string_generator(descriptor) elif descriptor.type == _fd.TYPE_BYTES: generator = _bytes_generator(descriptor) elif descriptor.type == _fd.TYPE_BOOL: generator = gen.IterValueGenerator(descriptor.name, [True, False]) elif descriptor.type == _fd.TYPE_ENUM: generator = _enum_generator(descriptor) elif descriptor.type == _fd.TYPE_MESSAGE: generator = descriptor_to_generator(descriptor.message_type, cls) generator.set_name(descriptor.name) else: raise RuntimeError("type {} unsupported".format(descriptor.type)) return generator
python
def _prototype_to_generator(descriptor, cls): 'Helper to map a descriptor to a protofuzz generator' _fd = D.FieldDescriptor generator = None ints32 = [_fd.TYPE_INT32, _fd.TYPE_UINT32, _fd.TYPE_FIXED32, _fd.TYPE_SFIXED32, _fd.TYPE_SINT32] ints64 = [_fd.TYPE_INT64, _fd.TYPE_UINT64, _fd.TYPE_FIXED64, _fd.TYPE_SFIXED64, _fd.TYPE_SINT64] ints_signed = [_fd.TYPE_INT32, _fd.TYPE_SFIXED32, _fd.TYPE_SINT32, _fd.TYPE_INT64, _fd.TYPE_SFIXED64, _fd.TYPE_SINT64] if descriptor.type in ints32+ints64: bitwidth = [32, 64][descriptor.type in ints64] unsigned = descriptor.type not in ints_signed generator = _int_generator(descriptor, bitwidth, unsigned) elif descriptor.type == _fd.TYPE_DOUBLE: generator = _float_generator(descriptor, 64) elif descriptor.type == _fd.TYPE_FLOAT: generator = _float_generator(descriptor, 32) elif descriptor.type == _fd.TYPE_STRING: generator = _string_generator(descriptor) elif descriptor.type == _fd.TYPE_BYTES: generator = _bytes_generator(descriptor) elif descriptor.type == _fd.TYPE_BOOL: generator = gen.IterValueGenerator(descriptor.name, [True, False]) elif descriptor.type == _fd.TYPE_ENUM: generator = _enum_generator(descriptor) elif descriptor.type == _fd.TYPE_MESSAGE: generator = descriptor_to_generator(descriptor.message_type, cls) generator.set_name(descriptor.name) else: raise RuntimeError("type {} unsupported".format(descriptor.type)) return generator
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Helper to map a descriptor to a protofuzz generator
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L71-L105
250,016
trailofbits/protofuzz
protofuzz/protofuzz.py
descriptor_to_generator
def descriptor_to_generator(cls_descriptor, cls, limit=0): 'Convert a protobuf descriptor to a protofuzz generator for same type' generators = [] for descriptor in cls_descriptor.fields_by_name.values(): generator = _prototype_to_generator(descriptor, cls) if limit != 0: generator.set_limit(limit) generators.append(generator) obj = cls(cls_descriptor.name, *generators) return obj
python
def descriptor_to_generator(cls_descriptor, cls, limit=0): 'Convert a protobuf descriptor to a protofuzz generator for same type' generators = [] for descriptor in cls_descriptor.fields_by_name.values(): generator = _prototype_to_generator(descriptor, cls) if limit != 0: generator.set_limit(limit) generators.append(generator) obj = cls(cls_descriptor.name, *generators) return obj
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Convert a protobuf descriptor to a protofuzz generator for same type
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L108-L121
250,017
trailofbits/protofuzz
protofuzz/protofuzz.py
_assign_to_field
def _assign_to_field(obj, name, val): 'Helper to assign an arbitrary value to a protobuf field' target = getattr(obj, name) if isinstance(target, containers.RepeatedScalarFieldContainer): target.append(val) elif isinstance(target, containers.RepeatedCompositeFieldContainer): target = target.add() target.CopyFrom(val) elif isinstance(target, (int, float, bool, str, bytes)): setattr(obj, name, val) elif isinstance(target, message.Message): target.CopyFrom(val) else: raise RuntimeError("Unsupported type: {}".format(type(target)))
python
def _assign_to_field(obj, name, val): 'Helper to assign an arbitrary value to a protobuf field' target = getattr(obj, name) if isinstance(target, containers.RepeatedScalarFieldContainer): target.append(val) elif isinstance(target, containers.RepeatedCompositeFieldContainer): target = target.add() target.CopyFrom(val) elif isinstance(target, (int, float, bool, str, bytes)): setattr(obj, name, val) elif isinstance(target, message.Message): target.CopyFrom(val) else: raise RuntimeError("Unsupported type: {}".format(type(target)))
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Helper to assign an arbitrary value to a protobuf field
[ "Helper", "to", "assign", "an", "arbitrary", "value", "to", "a", "protobuf", "field" ]
589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L124-L138
250,018
trailofbits/protofuzz
protofuzz/protofuzz.py
_fields_to_object
def _fields_to_object(descriptor, fields): 'Helper to convert a descriptor and a set of fields to a Protobuf instance' # pylint: disable=protected-access obj = descriptor._concrete_class() for name, value in fields: if isinstance(value, tuple): subtype = descriptor.fields_by_name[name].message_type value = _fields_to_object(subtype, value) _assign_to_field(obj, name, value) return obj
python
def _fields_to_object(descriptor, fields): 'Helper to convert a descriptor and a set of fields to a Protobuf instance' # pylint: disable=protected-access obj = descriptor._concrete_class() for name, value in fields: if isinstance(value, tuple): subtype = descriptor.fields_by_name[name].message_type value = _fields_to_object(subtype, value) _assign_to_field(obj, name, value) return obj
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Helper to convert a descriptor and a set of fields to a Protobuf instance
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L141-L152
250,019
trailofbits/protofuzz
protofuzz/protofuzz.py
_module_to_generators
def _module_to_generators(pb_module): ''' Convert a protobuf module to a dict of generators. This is typically used with modules that contain multiple type definitions. ''' if not pb_module: return None message_types = pb_module.DESCRIPTOR.message_types_by_name return {k: ProtobufGenerator(v) for k, v in message_types.items()}
python
def _module_to_generators(pb_module): ''' Convert a protobuf module to a dict of generators. This is typically used with modules that contain multiple type definitions. ''' if not pb_module: return None message_types = pb_module.DESCRIPTOR.message_types_by_name return {k: ProtobufGenerator(v) for k, v in message_types.items()}
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Convert a protobuf module to a dict of generators. This is typically used with modules that contain multiple type definitions.
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L224-L233
250,020
trailofbits/protofuzz
protofuzz/protofuzz.py
ProtobufGenerator.add_dependency
def add_dependency(self, source, target, action): ''' Create a dependency between fields source and target via callable action. >>> permuter = protofuzz.from_description_string(""" ... message Address { ... required uint32 one = 1; ... required uint32 two = 2; ... }""")['Address'] >>> permuter.add_dependency('one', 'two', lambda val: max(0,val-1)) >>> for obj in permuter.linear(): ... print("obj = {}".format(obj)) ... obj = one: 0 two: 1 obj = one: 256 two: 257 obj = one: 4096 two: 4097 obj = one: 1073741823 two: 1073741824 ''' self._dependencies.append((source, target, action))
python
def add_dependency(self, source, target, action): ''' Create a dependency between fields source and target via callable action. >>> permuter = protofuzz.from_description_string(""" ... message Address { ... required uint32 one = 1; ... required uint32 two = 2; ... }""")['Address'] >>> permuter.add_dependency('one', 'two', lambda val: max(0,val-1)) >>> for obj in permuter.linear(): ... print("obj = {}".format(obj)) ... obj = one: 0 two: 1 obj = one: 256 two: 257 obj = one: 4096 two: 4097 obj = one: 1073741823 two: 1073741824 ''' self._dependencies.append((source, target, action))
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Create a dependency between fields source and target via callable action. >>> permuter = protofuzz.from_description_string(""" ... message Address { ... required uint32 one = 1; ... required uint32 two = 2; ... }""")['Address'] >>> permuter.add_dependency('one', 'two', lambda val: max(0,val-1)) >>> for obj in permuter.linear(): ... print("obj = {}".format(obj)) ... obj = one: 0 two: 1 obj = one: 256 two: 257 obj = one: 4096 two: 4097 obj = one: 1073741823 two: 1073741824
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589492d34de9a0da6cc5554094e2588b893b2fd8
https://github.com/trailofbits/protofuzz/blob/589492d34de9a0da6cc5554094e2588b893b2fd8/protofuzz/protofuzz.py#L185-L213
250,021
sepandhaghighi/pycm
pycm/pycm_compare.py
Compare.print_report
def print_report(self): """ Print Compare report. :return: None """ report = compare_report_print( self.sorted, self.scores, self.best_name) print(report)
python
def print_report(self): report = compare_report_print( self.sorted, self.scores, self.best_name) print(report)
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Print Compare report. :return: None
[ "Print", "Compare", "report", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_compare.py#L98-L106
250,022
sepandhaghighi/pycm
pycm/pycm_class_func.py
F_calc
def F_calc(TP, FP, FN, beta): """ Calculate F-score. :param TP: true positive :type TP : int :param FP: false positive :type FP : int :param FN: false negative :type FN : int :param beta : beta coefficient :type beta : float :return: F score as float """ try: result = ((1 + (beta)**2) * TP) / \ ((1 + (beta)**2) * TP + FP + (beta**2) * FN) return result except ZeroDivisionError: return "None"
python
def F_calc(TP, FP, FN, beta): try: result = ((1 + (beta)**2) * TP) / \ ((1 + (beta)**2) * TP + FP + (beta**2) * FN) return result except ZeroDivisionError: return "None"
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Calculate F-score. :param TP: true positive :type TP : int :param FP: false positive :type FP : int :param FN: false negative :type FN : int :param beta : beta coefficient :type beta : float :return: F score as float
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_class_func.py#L61-L80
250,023
sepandhaghighi/pycm
pycm/pycm_class_func.py
G_calc
def G_calc(item1, item2): """ Calculate G-measure & G-mean. :param item1: PPV or TPR or TNR :type item1 : float :param item2: PPV or TPR or TNR :type item2 : float :return: G-measure or G-mean as float """ try: result = math.sqrt(item1 * item2) return result except Exception: return "None"
python
def G_calc(item1, item2): try: result = math.sqrt(item1 * item2) return result except Exception: return "None"
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Calculate G-measure & G-mean. :param item1: PPV or TPR or TNR :type item1 : float :param item2: PPV or TPR or TNR :type item2 : float :return: G-measure or G-mean as float
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_class_func.py#L156-L170
250,024
sepandhaghighi/pycm
pycm/pycm_class_func.py
RACC_calc
def RACC_calc(TOP, P, POP): """ Calculate random accuracy. :param TOP: test outcome positive :type TOP : int :param P: condition positive :type P : int :param POP: population :type POP:int :return: RACC as float """ try: result = (TOP * P) / ((POP) ** 2) return result except Exception: return "None"
python
def RACC_calc(TOP, P, POP): try: result = (TOP * P) / ((POP) ** 2) return result except Exception: return "None"
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Calculate random accuracy. :param TOP: test outcome positive :type TOP : int :param P: condition positive :type P : int :param POP: population :type POP:int :return: RACC as float
[ "Calculate", "random", "accuracy", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_class_func.py#L173-L189
250,025
sepandhaghighi/pycm
pycm/pycm_class_func.py
CEN_misclassification_calc
def CEN_misclassification_calc( table, TOP, P, i, j, subject_class, modified=False): """ Calculate misclassification probability of classifying. :param table: input matrix :type table : dict :param TOP: test outcome positive :type TOP : int :param P: condition positive :type P : int :param i: table row index (class name) :type i : any valid type :param j: table col index (class name) :type j : any valid type :param subject_class: subject to class (class name) :type subject_class: any valid type :param modified : modified mode flag :type modified : bool :return: misclassification probability of classifying as float """ try: result = TOP + P if modified: result -= table[subject_class][subject_class] result = table[i][j] / result return result except Exception: return "None"
python
def CEN_misclassification_calc( table, TOP, P, i, j, subject_class, modified=False): try: result = TOP + P if modified: result -= table[subject_class][subject_class] result = table[i][j] / result return result except Exception: return "None"
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Calculate misclassification probability of classifying. :param table: input matrix :type table : dict :param TOP: test outcome positive :type TOP : int :param P: condition positive :type P : int :param i: table row index (class name) :type i : any valid type :param j: table col index (class name) :type j : any valid type :param subject_class: subject to class (class name) :type subject_class: any valid type :param modified : modified mode flag :type modified : bool :return: misclassification probability of classifying as float
[ "Calculate", "misclassification", "probability", "of", "classifying", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_class_func.py#L265-L299
250,026
sepandhaghighi/pycm
pycm/pycm_output.py
html_init
def html_init(name): """ Return HTML report file first lines. :param name: name of file :type name : str :return: html_init as str """ result = "" result += "<html>\n" result += "<head>\n" result += "<title>" + str(name) + "</title>\n" result += "</head>\n" result += "<body>\n" result += '<h1 style="border-bottom:1px solid ' \ 'black;text-align:center;">PyCM Report</h1>' return result
python
def html_init(name): result = "" result += "<html>\n" result += "<head>\n" result += "<title>" + str(name) + "</title>\n" result += "</head>\n" result += "<body>\n" result += '<h1 style="border-bottom:1px solid ' \ 'black;text-align:center;">PyCM Report</h1>' return result
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Return HTML report file first lines. :param name: name of file :type name : str :return: html_init as str
[ "Return", "HTML", "report", "file", "first", "lines", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L10-L26
250,027
sepandhaghighi/pycm
pycm/pycm_output.py
html_dataset_type
def html_dataset_type(is_binary, is_imbalanced): """ Return HTML report file dataset type. :param is_binary: is_binary flag (binary : True , multi-class : False) :type is_binary: bool :param is_imbalanced: is_imbalanced flag (imbalance : True , balance : False) :type is_imbalanced: bool :return: dataset_type as str """ result = "<h2>Dataset Type : </h2>\n" balance_type = "Balanced" class_type = "Binary Classification" if is_imbalanced: balance_type = "Imbalanced" if not is_binary: class_type = "Multi-Class Classification" result += "<ul>\n\n<li>{0}</li>\n\n<li>{1}</li>\n</ul>\n".format( class_type, balance_type) result += "<p>{0}</p>\n".format(RECOMMEND_HTML_MESSAGE) result += "<p>{0}</p>\n".format(RECOMMEND_HTML_MESSAGE2) return result
python
def html_dataset_type(is_binary, is_imbalanced): result = "<h2>Dataset Type : </h2>\n" balance_type = "Balanced" class_type = "Binary Classification" if is_imbalanced: balance_type = "Imbalanced" if not is_binary: class_type = "Multi-Class Classification" result += "<ul>\n\n<li>{0}</li>\n\n<li>{1}</li>\n</ul>\n".format( class_type, balance_type) result += "<p>{0}</p>\n".format(RECOMMEND_HTML_MESSAGE) result += "<p>{0}</p>\n".format(RECOMMEND_HTML_MESSAGE2) return result
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Return HTML report file dataset type. :param is_binary: is_binary flag (binary : True , multi-class : False) :type is_binary: bool :param is_imbalanced: is_imbalanced flag (imbalance : True , balance : False) :type is_imbalanced: bool :return: dataset_type as str
[ "Return", "HTML", "report", "file", "dataset", "type", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L29-L51
250,028
sepandhaghighi/pycm
pycm/pycm_output.py
color_check
def color_check(color): """ Check input color format. :param color: input color :type color : tuple :return: color as list """ if isinstance(color, (tuple, list)): if all(map(lambda x: isinstance(x, int), color)): if all(map(lambda x: x < 256, color)): return list(color) if isinstance(color, str): color_lower = color.lower() if color_lower in TABLE_COLOR.keys(): return TABLE_COLOR[color_lower] return [0, 0, 0]
python
def color_check(color): if isinstance(color, (tuple, list)): if all(map(lambda x: isinstance(x, int), color)): if all(map(lambda x: x < 256, color)): return list(color) if isinstance(color, str): color_lower = color.lower() if color_lower in TABLE_COLOR.keys(): return TABLE_COLOR[color_lower] return [0, 0, 0]
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Check input color format. :param color: input color :type color : tuple :return: color as list
[ "Check", "input", "color", "format", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L54-L70
250,029
sepandhaghighi/pycm
pycm/pycm_output.py
html_table_color
def html_table_color(row, item, color=(0, 0, 0)): """ Return background color of each cell of table. :param row: row dictionary :type row : dict :param item: cell number :type item : int :param color : input color :type color : tuple :return: background color as list [R,G,B] """ result = [0, 0, 0] color_list = color_check(color) max_color = max(color_list) back_color_index = 255 - int((item / (sum(list(row.values())) + 1)) * 255) for i in range(3): result[i] = back_color_index - (max_color - color_list[i]) if result[i] < 0: result[i] = 0 return result
python
def html_table_color(row, item, color=(0, 0, 0)): result = [0, 0, 0] color_list = color_check(color) max_color = max(color_list) back_color_index = 255 - int((item / (sum(list(row.values())) + 1)) * 255) for i in range(3): result[i] = back_color_index - (max_color - color_list[i]) if result[i] < 0: result[i] = 0 return result
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Return background color of each cell of table. :param row: row dictionary :type row : dict :param item: cell number :type item : int :param color : input color :type color : tuple :return: background color as list [R,G,B]
[ "Return", "background", "color", "of", "each", "cell", "of", "table", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L73-L93
250,030
sepandhaghighi/pycm
pycm/pycm_output.py
html_table
def html_table(classes, table, rgb_color, normalize=False): """ Return HTML report file confusion matrix. :param classes: matrix classes :type classes: list :param table: matrix :type table : dict :param rgb_color : input color :type rgb_color : tuple :param normalize : save normalize matrix flag :type normalize : bool :return: html_table as str """ result = "" result += "<h2>Confusion Matrix " if normalize: result += "(Normalized)" result += ": </h2>\n" result += '<table>\n' result += '<tr align="center">' + "\n" result += '<td>Actual</td>\n' result += '<td>Predict\n' table_size = str((len(classes) + 1) * 7) + "em" result += '<table style="border:1px solid black;border-collapse: collapse;height:{0};width:{0};">\n'\ .format(table_size) classes.sort() result += '<tr align="center">\n<td></td>\n' part_2 = "" for i in classes: class_name = str(i) if len(class_name) > 6: class_name = class_name[:4] + "..." result += '<td style="border:1px solid ' \ 'black;padding:10px;height:7em;width:7em;">' + \ class_name + '</td>\n' part_2 += '<tr align="center">\n' part_2 += '<td style="border:1px solid ' \ 'black;padding:10px;height:7em;width:7em;">' + \ class_name + '</td>\n' for j in classes: item = table[i][j] color = "black;" back_color = html_table_color(table[i], item, rgb_color) if min(back_color) < 128: color = "white" part_2 += '<td style="background-color: rgb({0},{1},{2});color:{3};padding:10px;height:7em;width:7em;">'.format( str(back_color[0]), str(back_color[1]), str(back_color[2]), color) + str(item) + '</td>\n' part_2 += "</tr>\n" result += '</tr>\n' part_2 += "</table>\n</td>\n</tr>\n</table>\n" result += part_2 return result
python
def html_table(classes, table, rgb_color, normalize=False): result = "" result += "<h2>Confusion Matrix " if normalize: result += "(Normalized)" result += ": </h2>\n" result += '<table>\n' result += '<tr align="center">' + "\n" result += '<td>Actual</td>\n' result += '<td>Predict\n' table_size = str((len(classes) + 1) * 7) + "em" result += '<table style="border:1px solid black;border-collapse: collapse;height:{0};width:{0};">\n'\ .format(table_size) classes.sort() result += '<tr align="center">\n<td></td>\n' part_2 = "" for i in classes: class_name = str(i) if len(class_name) > 6: class_name = class_name[:4] + "..." result += '<td style="border:1px solid ' \ 'black;padding:10px;height:7em;width:7em;">' + \ class_name + '</td>\n' part_2 += '<tr align="center">\n' part_2 += '<td style="border:1px solid ' \ 'black;padding:10px;height:7em;width:7em;">' + \ class_name + '</td>\n' for j in classes: item = table[i][j] color = "black;" back_color = html_table_color(table[i], item, rgb_color) if min(back_color) < 128: color = "white" part_2 += '<td style="background-color: rgb({0},{1},{2});color:{3};padding:10px;height:7em;width:7em;">'.format( str(back_color[0]), str(back_color[1]), str(back_color[2]), color) + str(item) + '</td>\n' part_2 += "</tr>\n" result += '</tr>\n' part_2 += "</table>\n</td>\n</tr>\n</table>\n" result += part_2 return result
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Return HTML report file confusion matrix. :param classes: matrix classes :type classes: list :param table: matrix :type table : dict :param rgb_color : input color :type rgb_color : tuple :param normalize : save normalize matrix flag :type normalize : bool :return: html_table as str
[ "Return", "HTML", "report", "file", "confusion", "matrix", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L96-L148
250,031
sepandhaghighi/pycm
pycm/pycm_output.py
html_overall_stat
def html_overall_stat( overall_stat, digit=5, overall_param=None, recommended_list=()): """ Return HTML report file overall stat. :param overall_stat: overall stat :type overall_stat : dict :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :param overall_param : Overall parameters list for print, Example : ["Kappa","Scott PI] :type overall_param : list :param recommended_list: recommended statistics list :type recommended_list : list or tuple :return: html_overall_stat as str """ result = "" result += "<h2>Overall Statistics : </h2>\n" result += '<table style="border:1px solid black;border-collapse: collapse;">\n' overall_stat_keys = sorted(overall_stat.keys()) if isinstance(overall_param, list): if set(overall_param) <= set(overall_stat_keys): overall_stat_keys = sorted(overall_param) if len(overall_stat_keys) < 1: return "" for i in overall_stat_keys: background_color = DEFAULT_BACKGROUND_COLOR if i in recommended_list: background_color = RECOMMEND_BACKGROUND_COLOR result += '<tr align="center">\n' result += '<td style="border:1px solid black;padding:4px;text-align:left;background-color:{};"><a href="'.format( background_color) + DOCUMENT_ADR + PARAMS_LINK[i] + '" style="text-decoration:None;">' + str(i) + '</a></td>\n' if i in BENCHMARK_LIST: background_color = BENCHMARK_COLOR[overall_stat[i]] result += '<td style="border:1px solid black;padding:4px;background-color:{};">'.format( background_color) else: result += '<td style="border:1px solid black;padding:4px;">' result += rounder(overall_stat[i], digit) + '</td>\n' result += "</tr>\n" result += "</table>\n" return result
python
def html_overall_stat( overall_stat, digit=5, overall_param=None, recommended_list=()): result = "" result += "<h2>Overall Statistics : </h2>\n" result += '<table style="border:1px solid black;border-collapse: collapse;">\n' overall_stat_keys = sorted(overall_stat.keys()) if isinstance(overall_param, list): if set(overall_param) <= set(overall_stat_keys): overall_stat_keys = sorted(overall_param) if len(overall_stat_keys) < 1: return "" for i in overall_stat_keys: background_color = DEFAULT_BACKGROUND_COLOR if i in recommended_list: background_color = RECOMMEND_BACKGROUND_COLOR result += '<tr align="center">\n' result += '<td style="border:1px solid black;padding:4px;text-align:left;background-color:{};"><a href="'.format( background_color) + DOCUMENT_ADR + PARAMS_LINK[i] + '" style="text-decoration:None;">' + str(i) + '</a></td>\n' if i in BENCHMARK_LIST: background_color = BENCHMARK_COLOR[overall_stat[i]] result += '<td style="border:1px solid black;padding:4px;background-color:{};">'.format( background_color) else: result += '<td style="border:1px solid black;padding:4px;">' result += rounder(overall_stat[i], digit) + '</td>\n' result += "</tr>\n" result += "</table>\n" return result
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Return HTML report file overall stat. :param overall_stat: overall stat :type overall_stat : dict :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :param overall_param : Overall parameters list for print, Example : ["Kappa","Scott PI] :type overall_param : list :param recommended_list: recommended statistics list :type recommended_list : list or tuple :return: html_overall_stat as str
[ "Return", "HTML", "report", "file", "overall", "stat", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L151-L194
250,032
sepandhaghighi/pycm
pycm/pycm_output.py
html_class_stat
def html_class_stat( classes, class_stat, digit=5, class_param=None, recommended_list=()): """ Return HTML report file class_stat. :param classes: matrix classes :type classes: list :param class_stat: class stat :type class_stat:dict :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :param class_param : Class parameters list for print, Example : ["TPR","TNR","AUC"] :type class_param : list :param recommended_list: recommended statistics list :type recommended_list : list or tuple :return: html_class_stat as str """ result = "" result += "<h2>Class Statistics : </h2>\n" result += '<table style="border:1px solid black;border-collapse: collapse;">\n' result += '<tr align="center">\n<td>Class</td>\n' for i in classes: result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;">' + \ str(i) + '</td>\n' result += '<td>Description</td>\n' result += '</tr>\n' class_stat_keys = sorted(class_stat.keys()) if isinstance(class_param, list): if set(class_param) <= set(class_stat_keys): class_stat_keys = class_param classes.sort() if len(classes) < 1 or len(class_stat_keys) < 1: return "" for i in class_stat_keys: background_color = DEFAULT_BACKGROUND_COLOR if i in recommended_list: background_color = RECOMMEND_BACKGROUND_COLOR result += '<tr align="center" style="border:1px solid black;border-collapse: collapse;">\n' result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;background-color:{};"><a href="'.format( background_color) + DOCUMENT_ADR + PARAMS_LINK[i] + '" style="text-decoration:None;">' + str(i) + '</a></td>\n' for j in classes: if i in BENCHMARK_LIST: background_color = BENCHMARK_COLOR[class_stat[i][j]] result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;background-color:{};">'.format( background_color) else: result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;">' result += rounder(class_stat[i][j], digit) + '</td>\n' params_text = PARAMS_DESCRIPTION[i] if i not in CAPITALIZE_FILTER: params_text = params_text.capitalize() result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;text-align:left;">' + \ params_text + '</td>\n' result += "</tr>\n" result += "</table>\n" return result
python
def html_class_stat( classes, class_stat, digit=5, class_param=None, recommended_list=()): result = "" result += "<h2>Class Statistics : </h2>\n" result += '<table style="border:1px solid black;border-collapse: collapse;">\n' result += '<tr align="center">\n<td>Class</td>\n' for i in classes: result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;">' + \ str(i) + '</td>\n' result += '<td>Description</td>\n' result += '</tr>\n' class_stat_keys = sorted(class_stat.keys()) if isinstance(class_param, list): if set(class_param) <= set(class_stat_keys): class_stat_keys = class_param classes.sort() if len(classes) < 1 or len(class_stat_keys) < 1: return "" for i in class_stat_keys: background_color = DEFAULT_BACKGROUND_COLOR if i in recommended_list: background_color = RECOMMEND_BACKGROUND_COLOR result += '<tr align="center" style="border:1px solid black;border-collapse: collapse;">\n' result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;background-color:{};"><a href="'.format( background_color) + DOCUMENT_ADR + PARAMS_LINK[i] + '" style="text-decoration:None;">' + str(i) + '</a></td>\n' for j in classes: if i in BENCHMARK_LIST: background_color = BENCHMARK_COLOR[class_stat[i][j]] result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;background-color:{};">'.format( background_color) else: result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;">' result += rounder(class_stat[i][j], digit) + '</td>\n' params_text = PARAMS_DESCRIPTION[i] if i not in CAPITALIZE_FILTER: params_text = params_text.capitalize() result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;text-align:left;">' + \ params_text + '</td>\n' result += "</tr>\n" result += "</table>\n" return result
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Return HTML report file class_stat. :param classes: matrix classes :type classes: list :param class_stat: class stat :type class_stat:dict :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :param class_param : Class parameters list for print, Example : ["TPR","TNR","AUC"] :type class_param : list :param recommended_list: recommended statistics list :type recommended_list : list or tuple :return: html_class_stat as str
[ "Return", "HTML", "report", "file", "class_stat", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L197-L256
250,033
sepandhaghighi/pycm
pycm/pycm_output.py
table_print
def table_print(classes, table): """ Return printable confusion matrix. :param classes: classes list :type classes:list :param table: table :type table:dict :return: printable table as str """ classes_len = len(classes) table_list = [] for key in classes: table_list.extend(list(table[key].values())) table_list.extend(classes) table_max_length = max(map(len, map(str, table_list))) shift = "%-" + str(7 + table_max_length) + "s" result = shift % "Predict" + shift * \ classes_len % tuple(map(str, classes)) + "\n" result = result + "Actual\n" classes.sort() for key in classes: row = [table[key][i] for i in classes] result += shift % str(key) + \ shift * classes_len % tuple(map(str, row)) + "\n\n" if classes_len >= CLASS_NUMBER_THRESHOLD: result += "\n" + "Warning : " + CLASS_NUMBER_WARNING + "\n" return result
python
def table_print(classes, table): classes_len = len(classes) table_list = [] for key in classes: table_list.extend(list(table[key].values())) table_list.extend(classes) table_max_length = max(map(len, map(str, table_list))) shift = "%-" + str(7 + table_max_length) + "s" result = shift % "Predict" + shift * \ classes_len % tuple(map(str, classes)) + "\n" result = result + "Actual\n" classes.sort() for key in classes: row = [table[key][i] for i in classes] result += shift % str(key) + \ shift * classes_len % tuple(map(str, row)) + "\n\n" if classes_len >= CLASS_NUMBER_THRESHOLD: result += "\n" + "Warning : " + CLASS_NUMBER_WARNING + "\n" return result
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Return printable confusion matrix. :param classes: classes list :type classes:list :param table: table :type table:dict :return: printable table as str
[ "Return", "printable", "confusion", "matrix", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L286-L313
250,034
sepandhaghighi/pycm
pycm/pycm_output.py
csv_matrix_print
def csv_matrix_print(classes, table): """ Return matrix as csv data. :param classes: classes list :type classes:list :param table: table :type table:dict :return: """ result = "" classes.sort() for i in classes: for j in classes: result += str(table[i][j]) + "," result = result[:-1] + "\n" return result[:-1]
python
def csv_matrix_print(classes, table): result = "" classes.sort() for i in classes: for j in classes: result += str(table[i][j]) + "," result = result[:-1] + "\n" return result[:-1]
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Return matrix as csv data. :param classes: classes list :type classes:list :param table: table :type table:dict :return:
[ "Return", "matrix", "as", "csv", "data", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L316-L332
250,035
sepandhaghighi/pycm
pycm/pycm_output.py
csv_print
def csv_print(classes, class_stat, digit=5, class_param=None): """ Return csv file data. :param classes: classes list :type classes:list :param class_stat: statistic result for each class :type class_stat:dict :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :param class_param : class parameters list for print, Example : ["TPR","TNR","AUC"] :type class_param : list :return: csv file data as str """ result = "Class" classes.sort() for item in classes: result += ',"' + str(item) + '"' result += "\n" class_stat_keys = sorted(class_stat.keys()) if isinstance(class_param, list): if set(class_param) <= set(class_stat_keys): class_stat_keys = class_param if len(class_stat_keys) < 1 or len(classes) < 1: return "" for key in class_stat_keys: row = [rounder(class_stat[key][i], digit) for i in classes] result += key + "," + ",".join(row) result += "\n" return result
python
def csv_print(classes, class_stat, digit=5, class_param=None): result = "Class" classes.sort() for item in classes: result += ',"' + str(item) + '"' result += "\n" class_stat_keys = sorted(class_stat.keys()) if isinstance(class_param, list): if set(class_param) <= set(class_stat_keys): class_stat_keys = class_param if len(class_stat_keys) < 1 or len(classes) < 1: return "" for key in class_stat_keys: row = [rounder(class_stat[key][i], digit) for i in classes] result += key + "," + ",".join(row) result += "\n" return result
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Return csv file data. :param classes: classes list :type classes:list :param class_stat: statistic result for each class :type class_stat:dict :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :param class_param : class parameters list for print, Example : ["TPR","TNR","AUC"] :type class_param : list :return: csv file data as str
[ "Return", "csv", "file", "data", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L335-L364
250,036
sepandhaghighi/pycm
pycm/pycm_output.py
stat_print
def stat_print( classes, class_stat, overall_stat, digit=5, overall_param=None, class_param=None): """ Return printable statistics table. :param classes: classes list :type classes:list :param class_stat: statistic result for each class :type class_stat:dict :param overall_stat : overall statistic result :type overall_stat:dict :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :param overall_param : overall parameters list for print, Example : ["Kappa","Scott PI] :type overall_param : list :param class_param : class parameters list for print, Example : ["TPR","TNR","AUC"] :type class_param : list :return: printable result as str """ shift = max(map(len, PARAMS_DESCRIPTION.values())) + 5 classes_len = len(classes) overall_stat_keys = sorted(overall_stat.keys()) result = "" if isinstance(overall_param, list): if set(overall_param) <= set(overall_stat_keys): overall_stat_keys = sorted(overall_param) if len(overall_stat_keys) > 0: result = "Overall Statistics : " + "\n\n" for key in overall_stat_keys: result += key + " " * (shift - len(key) + 7) + \ rounder(overall_stat[key], digit) + "\n" class_stat_keys = sorted(class_stat.keys()) if isinstance(class_param, list): if set(class_param) <= set(class_stat_keys): class_stat_keys = sorted(class_param) classes.sort() if len(class_stat_keys) > 0 and len(classes) > 0: class_shift = max( max(map(lambda x: len(str(x)), classes)) + 5, digit + 6, 14) class_shift_format = "%-" + str(class_shift) + "s" result += "\nClass Statistics :\n\n" result += "Classes" + shift * " " + class_shift_format * \ classes_len % tuple(map(str, classes)) + "\n" rounder_map = partial(rounder, digit=digit) for key in class_stat_keys: row = [class_stat[key][i] for i in classes] params_text = PARAMS_DESCRIPTION[key] if key not in CAPITALIZE_FILTER: params_text = params_text.capitalize() result += key + "(" + params_text + ")" + " " * ( shift - len(key) - len(PARAMS_DESCRIPTION[key]) + 5) + class_shift_format * classes_len % tuple( map(rounder_map, row)) + "\n" if classes_len >= CLASS_NUMBER_THRESHOLD: result += "\n" + "Warning : " + CLASS_NUMBER_WARNING + "\n" return result
python
def stat_print( classes, class_stat, overall_stat, digit=5, overall_param=None, class_param=None): shift = max(map(len, PARAMS_DESCRIPTION.values())) + 5 classes_len = len(classes) overall_stat_keys = sorted(overall_stat.keys()) result = "" if isinstance(overall_param, list): if set(overall_param) <= set(overall_stat_keys): overall_stat_keys = sorted(overall_param) if len(overall_stat_keys) > 0: result = "Overall Statistics : " + "\n\n" for key in overall_stat_keys: result += key + " " * (shift - len(key) + 7) + \ rounder(overall_stat[key], digit) + "\n" class_stat_keys = sorted(class_stat.keys()) if isinstance(class_param, list): if set(class_param) <= set(class_stat_keys): class_stat_keys = sorted(class_param) classes.sort() if len(class_stat_keys) > 0 and len(classes) > 0: class_shift = max( max(map(lambda x: len(str(x)), classes)) + 5, digit + 6, 14) class_shift_format = "%-" + str(class_shift) + "s" result += "\nClass Statistics :\n\n" result += "Classes" + shift * " " + class_shift_format * \ classes_len % tuple(map(str, classes)) + "\n" rounder_map = partial(rounder, digit=digit) for key in class_stat_keys: row = [class_stat[key][i] for i in classes] params_text = PARAMS_DESCRIPTION[key] if key not in CAPITALIZE_FILTER: params_text = params_text.capitalize() result += key + "(" + params_text + ")" + " " * ( shift - len(key) - len(PARAMS_DESCRIPTION[key]) + 5) + class_shift_format * classes_len % tuple( map(rounder_map, row)) + "\n" if classes_len >= CLASS_NUMBER_THRESHOLD: result += "\n" + "Warning : " + CLASS_NUMBER_WARNING + "\n" return result
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Return printable statistics table. :param classes: classes list :type classes:list :param class_stat: statistic result for each class :type class_stat:dict :param overall_stat : overall statistic result :type overall_stat:dict :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :param overall_param : overall parameters list for print, Example : ["Kappa","Scott PI] :type overall_param : list :param class_param : class parameters list for print, Example : ["TPR","TNR","AUC"] :type class_param : list :return: printable result as str
[ "Return", "printable", "statistics", "table", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L367-L426
250,037
sepandhaghighi/pycm
pycm/pycm_output.py
compare_report_print
def compare_report_print(sorted_list, scores, best_name): """ Return compare report. :param sorted_list: sorted list of cm's :type sorted_list: list :param scores: scores of cm's :type scores: dict :param best_name: best cm name :type best_name: str :return: printable result as str """ title_items = ["Rank", "Name", "Class-Score", "Overall-Score"] class_scores_len = map(lambda x: len( str(x["class"])), list(scores.values())) shifts = ["%-" + str(len(sorted_list) + 4) + "s", "%-" + str(max(map(lambda x: len(str(x)), sorted_list)) + 4) + "s", "%-" + str(max(class_scores_len) + 11) + "s"] result = "" result += "Best : " + str(best_name) + "\n\n" result += ("".join(shifts) ) % tuple(title_items[:-1]) + title_items[-1] + "\n" prev_rank = 0 for index, cm in enumerate(sorted_list): rank = index if scores[sorted_list[rank]] == scores[sorted_list[prev_rank]]: rank = prev_rank result += ("".join(shifts)) % (str(rank + 1), str(cm), str(scores[cm]["class"])) + str(scores[cm]["overall"]) + "\n" prev_rank = rank if best_name is None: result += "\nWarning: " + COMPARE_RESULT_WARNING return result
python
def compare_report_print(sorted_list, scores, best_name): title_items = ["Rank", "Name", "Class-Score", "Overall-Score"] class_scores_len = map(lambda x: len( str(x["class"])), list(scores.values())) shifts = ["%-" + str(len(sorted_list) + 4) + "s", "%-" + str(max(map(lambda x: len(str(x)), sorted_list)) + 4) + "s", "%-" + str(max(class_scores_len) + 11) + "s"] result = "" result += "Best : " + str(best_name) + "\n\n" result += ("".join(shifts) ) % tuple(title_items[:-1]) + title_items[-1] + "\n" prev_rank = 0 for index, cm in enumerate(sorted_list): rank = index if scores[sorted_list[rank]] == scores[sorted_list[prev_rank]]: rank = prev_rank result += ("".join(shifts)) % (str(rank + 1), str(cm), str(scores[cm]["class"])) + str(scores[cm]["overall"]) + "\n" prev_rank = rank if best_name is None: result += "\nWarning: " + COMPARE_RESULT_WARNING return result
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Return compare report. :param sorted_list: sorted list of cm's :type sorted_list: list :param scores: scores of cm's :type scores: dict :param best_name: best cm name :type best_name: str :return: printable result as str
[ "Return", "compare", "report", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L429-L466
250,038
sepandhaghighi/pycm
pycm/pycm_output.py
online_help
def online_help(param=None): """ Open online document in web browser. :param param: input parameter :type param : int or str :return: None """ try: PARAMS_LINK_KEYS = sorted(PARAMS_LINK.keys()) if param in PARAMS_LINK_KEYS: webbrowser.open_new_tab(DOCUMENT_ADR + PARAMS_LINK[param]) elif param in range(1, len(PARAMS_LINK_KEYS) + 1): webbrowser.open_new_tab( DOCUMENT_ADR + PARAMS_LINK[PARAMS_LINK_KEYS[param - 1]]) else: print("Please choose one parameter : \n") print('Example : online_help("J") or online_help(2)\n') for index, item in enumerate(PARAMS_LINK_KEYS): print(str(index + 1) + "-" + item) except Exception: print("Error in online help")
python
def online_help(param=None): try: PARAMS_LINK_KEYS = sorted(PARAMS_LINK.keys()) if param in PARAMS_LINK_KEYS: webbrowser.open_new_tab(DOCUMENT_ADR + PARAMS_LINK[param]) elif param in range(1, len(PARAMS_LINK_KEYS) + 1): webbrowser.open_new_tab( DOCUMENT_ADR + PARAMS_LINK[PARAMS_LINK_KEYS[param - 1]]) else: print("Please choose one parameter : \n") print('Example : online_help("J") or online_help(2)\n') for index, item in enumerate(PARAMS_LINK_KEYS): print(str(index + 1) + "-" + item) except Exception: print("Error in online help")
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Open online document in web browser. :param param: input parameter :type param : int or str :return: None
[ "Open", "online", "document", "in", "web", "browser", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_output.py#L469-L490
250,039
sepandhaghighi/pycm
pycm/pycm_util.py
rounder
def rounder(input_number, digit=5): """ Round input number and convert to str. :param input_number: input number :type input_number : anything :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :return: round number as str """ if isinstance(input_number, tuple): tuple_list = list(input_number) tuple_str = [] for i in tuple_list: if isfloat(i): tuple_str.append(str(numpy.around(i, digit))) else: tuple_str.append(str(i)) return "(" + ",".join(tuple_str) + ")" if isfloat(input_number): return str(numpy.around(input_number, digit)) return str(input_number)
python
def rounder(input_number, digit=5): if isinstance(input_number, tuple): tuple_list = list(input_number) tuple_str = [] for i in tuple_list: if isfloat(i): tuple_str.append(str(numpy.around(i, digit))) else: tuple_str.append(str(i)) return "(" + ",".join(tuple_str) + ")" if isfloat(input_number): return str(numpy.around(input_number, digit)) return str(input_number)
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Round input number and convert to str. :param input_number: input number :type input_number : anything :param digit: scale (the number of digits to the right of the decimal point in a number.) :type digit : int :return: round number as str
[ "Round", "input", "number", "and", "convert", "to", "str", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L35-L56
250,040
sepandhaghighi/pycm
pycm/pycm_util.py
class_filter
def class_filter(classes, class_name): """ Filter classes by comparing two lists. :param classes: matrix classes :type classes: list :param class_name: sub set of classes :type class_name : list :return: filtered classes as list """ result_classes = classes if isinstance(class_name, list): if set(class_name) <= set(classes): result_classes = class_name return result_classes
python
def class_filter(classes, class_name): result_classes = classes if isinstance(class_name, list): if set(class_name) <= set(classes): result_classes = class_name return result_classes
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Filter classes by comparing two lists. :param classes: matrix classes :type classes: list :param class_name: sub set of classes :type class_name : list :return: filtered classes as list
[ "Filter", "classes", "by", "comparing", "two", "lists", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L59-L73
250,041
sepandhaghighi/pycm
pycm/pycm_util.py
vector_check
def vector_check(vector): """ Check input vector items type. :param vector: input vector :type vector : list :return: bool """ for i in vector: if isinstance(i, int) is False: return False if i < 0: return False return True
python
def vector_check(vector): for i in vector: if isinstance(i, int) is False: return False if i < 0: return False return True
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Check input vector items type. :param vector: input vector :type vector : list :return: bool
[ "Check", "input", "vector", "items", "type", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L76-L89
250,042
sepandhaghighi/pycm
pycm/pycm_util.py
matrix_check
def matrix_check(table): """ Check input matrix format. :param table: input matrix :type table : dict :return: bool """ try: if len(table.keys()) == 0: return False for i in table.keys(): if table.keys() != table[i].keys() or vector_check( list(table[i].values())) is False: return False return True except Exception: return False
python
def matrix_check(table): try: if len(table.keys()) == 0: return False for i in table.keys(): if table.keys() != table[i].keys() or vector_check( list(table[i].values())) is False: return False return True except Exception: return False
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Check input matrix format. :param table: input matrix :type table : dict :return: bool
[ "Check", "input", "matrix", "format", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L92-L109
250,043
sepandhaghighi/pycm
pycm/pycm_util.py
vector_filter
def vector_filter(actual_vector, predict_vector): """ Convert different type of items in vectors to str. :param actual_vector: actual values :type actual_vector : list :param predict_vector: predict value :type predict_vector : list :return: new actual and predict vector """ temp = [] temp.extend(actual_vector) temp.extend(predict_vector) types = set(map(type, temp)) if len(types) > 1: return [list(map(str, actual_vector)), list(map(str, predict_vector))] return [actual_vector, predict_vector]
python
def vector_filter(actual_vector, predict_vector): temp = [] temp.extend(actual_vector) temp.extend(predict_vector) types = set(map(type, temp)) if len(types) > 1: return [list(map(str, actual_vector)), list(map(str, predict_vector))] return [actual_vector, predict_vector]
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Convert different type of items in vectors to str. :param actual_vector: actual values :type actual_vector : list :param predict_vector: predict value :type predict_vector : list :return: new actual and predict vector
[ "Convert", "different", "type", "of", "items", "in", "vectors", "to", "str", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L112-L128
250,044
sepandhaghighi/pycm
pycm/pycm_util.py
class_check
def class_check(vector): """ Check different items in matrix classes. :param vector: input vector :type vector : list :return: bool """ for i in vector: if not isinstance(i, type(vector[0])): return False return True
python
def class_check(vector): for i in vector: if not isinstance(i, type(vector[0])): return False return True
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Check different items in matrix classes. :param vector: input vector :type vector : list :return: bool
[ "Check", "different", "items", "in", "matrix", "classes", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L131-L142
250,045
sepandhaghighi/pycm
pycm/pycm_util.py
one_vs_all_func
def one_vs_all_func(classes, table, TP, TN, FP, FN, class_name): """ One-Vs-All mode handler. :param classes: classes :type classes : list :param table: input matrix :type table : dict :param TP: true positive dict for all classes :type TP : dict :param TN: true negative dict for all classes :type TN : dict :param FP: false positive dict for all classes :type FP : dict :param FN: false negative dict for all classes :type FN : dict :param class_name : target class name for One-Vs-All mode :type class_name : any valid type :return: [classes , table ] as list """ try: report_classes = [str(class_name), "~"] report_table = {str(class_name): {str(class_name): TP[class_name], "~": FN[class_name]}, "~": {str(class_name): FP[class_name], "~": TN[class_name]}} return [report_classes, report_table] except Exception: return [classes, table]
python
def one_vs_all_func(classes, table, TP, TN, FP, FN, class_name): try: report_classes = [str(class_name), "~"] report_table = {str(class_name): {str(class_name): TP[class_name], "~": FN[class_name]}, "~": {str(class_name): FP[class_name], "~": TN[class_name]}} return [report_classes, report_table] except Exception: return [classes, table]
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One-Vs-All mode handler. :param classes: classes :type classes : list :param table: input matrix :type table : dict :param TP: true positive dict for all classes :type TP : dict :param TN: true negative dict for all classes :type TN : dict :param FP: false positive dict for all classes :type FP : dict :param FN: false negative dict for all classes :type FN : dict :param class_name : target class name for One-Vs-All mode :type class_name : any valid type :return: [classes , table ] as list
[ "One", "-", "Vs", "-", "All", "mode", "handler", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L158-L186
250,046
sepandhaghighi/pycm
pycm/pycm_util.py
normalized_table_calc
def normalized_table_calc(classes, table): """ Return normalized confusion matrix. :param classes: classes list :type classes:list :param table: table :type table:dict :return: normalized table as dict """ map_dict = {k: 0 for k in classes} new_table = {k: map_dict.copy() for k in classes} for key in classes: div = sum(table[key].values()) if div == 0: div = 1 for item in classes: new_table[key][item] = numpy.around(table[key][item] / div, 5) return new_table
python
def normalized_table_calc(classes, table): map_dict = {k: 0 for k in classes} new_table = {k: map_dict.copy() for k in classes} for key in classes: div = sum(table[key].values()) if div == 0: div = 1 for item in classes: new_table[key][item] = numpy.around(table[key][item] / div, 5) return new_table
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Return normalized confusion matrix. :param classes: classes list :type classes:list :param table: table :type table:dict :return: normalized table as dict
[ "Return", "normalized", "confusion", "matrix", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L189-L207
250,047
sepandhaghighi/pycm
pycm/pycm_util.py
transpose_func
def transpose_func(classes, table): """ Transpose table. :param classes: classes :type classes : list :param table: input matrix :type table : dict :return: transposed table as dict """ transposed_table = table for i, item1 in enumerate(classes): for j, item2 in enumerate(classes): if i > j: temp = transposed_table[item1][item2] transposed_table[item1][item2] = transposed_table[item2][item1] transposed_table[item2][item1] = temp return transposed_table
python
def transpose_func(classes, table): transposed_table = table for i, item1 in enumerate(classes): for j, item2 in enumerate(classes): if i > j: temp = transposed_table[item1][item2] transposed_table[item1][item2] = transposed_table[item2][item1] transposed_table[item2][item1] = temp return transposed_table
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Transpose table. :param classes: classes :type classes : list :param table: input matrix :type table : dict :return: transposed table as dict
[ "Transpose", "table", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L210-L227
250,048
sepandhaghighi/pycm
pycm/pycm_util.py
matrix_params_from_table
def matrix_params_from_table(table, transpose=False): """ Calculate TP,TN,FP,FN from confusion matrix. :param table: input matrix :type table : dict :param transpose : transpose flag :type transpose : bool :return: [classes_list,table,TP,TN,FP,FN] """ classes = sorted(table.keys()) map_dict = {k: 0 for k in classes} TP_dict = map_dict.copy() TN_dict = map_dict.copy() FP_dict = map_dict.copy() FN_dict = map_dict.copy() for i in classes: TP_dict[i] = table[i][i] sum_row = sum(list(table[i].values())) for j in classes: if j != i: FN_dict[i] += table[i][j] FP_dict[j] += table[i][j] TN_dict[j] += sum_row - table[i][j] if transpose: temp = FN_dict FN_dict = FP_dict FP_dict = temp table = transpose_func(classes, table) return [classes, table, TP_dict, TN_dict, FP_dict, FN_dict]
python
def matrix_params_from_table(table, transpose=False): classes = sorted(table.keys()) map_dict = {k: 0 for k in classes} TP_dict = map_dict.copy() TN_dict = map_dict.copy() FP_dict = map_dict.copy() FN_dict = map_dict.copy() for i in classes: TP_dict[i] = table[i][i] sum_row = sum(list(table[i].values())) for j in classes: if j != i: FN_dict[i] += table[i][j] FP_dict[j] += table[i][j] TN_dict[j] += sum_row - table[i][j] if transpose: temp = FN_dict FN_dict = FP_dict FP_dict = temp table = transpose_func(classes, table) return [classes, table, TP_dict, TN_dict, FP_dict, FN_dict]
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Calculate TP,TN,FP,FN from confusion matrix. :param table: input matrix :type table : dict :param transpose : transpose flag :type transpose : bool :return: [classes_list,table,TP,TN,FP,FN]
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L230-L259
250,049
sepandhaghighi/pycm
pycm/pycm_util.py
matrix_params_calc
def matrix_params_calc(actual_vector, predict_vector, sample_weight): """ Calculate TP,TN,FP,FN for each class. :param actual_vector: actual values :type actual_vector : list :param predict_vector: predict value :type predict_vector : list :param sample_weight : sample weights list :type sample_weight : list :return: [classes_list,table,TP,TN,FP,FN] """ if isinstance(actual_vector, numpy.ndarray): actual_vector = actual_vector.tolist() if isinstance(predict_vector, numpy.ndarray): predict_vector = predict_vector.tolist() classes = set(actual_vector).union(set(predict_vector)) classes = sorted(classes) map_dict = {k: 0 for k in classes} table = {k: map_dict.copy() for k in classes} weight_vector = [1] * len(actual_vector) if isinstance(sample_weight, (list, numpy.ndarray)): if len(sample_weight) == len(actual_vector): weight_vector = sample_weight for index, item in enumerate(actual_vector): table[item][predict_vector[index]] += 1 * weight_vector[index] [classes, table, TP_dict, TN_dict, FP_dict, FN_dict] = matrix_params_from_table(table) return [classes, table, TP_dict, TN_dict, FP_dict, FN_dict]
python
def matrix_params_calc(actual_vector, predict_vector, sample_weight): if isinstance(actual_vector, numpy.ndarray): actual_vector = actual_vector.tolist() if isinstance(predict_vector, numpy.ndarray): predict_vector = predict_vector.tolist() classes = set(actual_vector).union(set(predict_vector)) classes = sorted(classes) map_dict = {k: 0 for k in classes} table = {k: map_dict.copy() for k in classes} weight_vector = [1] * len(actual_vector) if isinstance(sample_weight, (list, numpy.ndarray)): if len(sample_weight) == len(actual_vector): weight_vector = sample_weight for index, item in enumerate(actual_vector): table[item][predict_vector[index]] += 1 * weight_vector[index] [classes, table, TP_dict, TN_dict, FP_dict, FN_dict] = matrix_params_from_table(table) return [classes, table, TP_dict, TN_dict, FP_dict, FN_dict]
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Calculate TP,TN,FP,FN for each class. :param actual_vector: actual values :type actual_vector : list :param predict_vector: predict value :type predict_vector : list :param sample_weight : sample weights list :type sample_weight : list :return: [classes_list,table,TP,TN,FP,FN]
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L262-L290
250,050
sepandhaghighi/pycm
pycm/pycm_util.py
imbalance_check
def imbalance_check(P): """ Check if the dataset is imbalanced. :param P: condition positive :type P : dict :return: is_imbalanced as bool """ p_list = list(P.values()) max_value = max(p_list) min_value = min(p_list) if min_value > 0: balance_ratio = max_value / min_value else: balance_ratio = max_value is_imbalanced = False if balance_ratio > BALANCE_RATIO_THRESHOLD: is_imbalanced = True return is_imbalanced
python
def imbalance_check(P): p_list = list(P.values()) max_value = max(p_list) min_value = min(p_list) if min_value > 0: balance_ratio = max_value / min_value else: balance_ratio = max_value is_imbalanced = False if balance_ratio > BALANCE_RATIO_THRESHOLD: is_imbalanced = True return is_imbalanced
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Check if the dataset is imbalanced. :param P: condition positive :type P : dict :return: is_imbalanced as bool
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L293-L311
250,051
sepandhaghighi/pycm
pycm/pycm_util.py
binary_check
def binary_check(classes): """ Check if the problem is a binary classification. :param classes: all classes name :type classes : list :return: is_binary as bool """ num_classes = len(classes) is_binary = False if num_classes == 2: is_binary = True return is_binary
python
def binary_check(classes): num_classes = len(classes) is_binary = False if num_classes == 2: is_binary = True return is_binary
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Check if the problem is a binary classification. :param classes: all classes name :type classes : list :return: is_binary as bool
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L314-L326
250,052
sepandhaghighi/pycm
pycm/pycm_util.py
statistic_recommend
def statistic_recommend(classes, P): """ Return recommend parameters which are more suitable due to the input dataset characteristics. :param classes: all classes name :type classes : list :param P: condition positive :type P : dict :return: recommendation_list as list """ if imbalance_check(P): return IMBALANCED_RECOMMEND if binary_check(classes): return BINARY_RECOMMEND return MULTICLASS_RECOMMEND
python
def statistic_recommend(classes, P): if imbalance_check(P): return IMBALANCED_RECOMMEND if binary_check(classes): return BINARY_RECOMMEND return MULTICLASS_RECOMMEND
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Return recommend parameters which are more suitable due to the input dataset characteristics. :param classes: all classes name :type classes : list :param P: condition positive :type P : dict :return: recommendation_list as list
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_util.py#L329-L343
250,053
sepandhaghighi/pycm
Otherfiles/version_check.py
print_result
def print_result(failed=False): """ Print final result. :param failed: failed flag :type failed: bool :return: None """ message = "Version tag tests " if not failed: print("\n" + message + "passed!") else: print("\n" + message + "failed!") print("Passed : " + str(TEST_NUMBER - Failed) + "/" + str(TEST_NUMBER))
python
def print_result(failed=False): message = "Version tag tests " if not failed: print("\n" + message + "passed!") else: print("\n" + message + "failed!") print("Passed : " + str(TEST_NUMBER - Failed) + "/" + str(TEST_NUMBER))
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Print final result. :param failed: failed flag :type failed: bool :return: None
[ "Print", "final", "result", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/Otherfiles/version_check.py#L40-L53
250,054
sepandhaghighi/pycm
pycm/pycm_overall_func.py
AUNP_calc
def AUNP_calc(classes, P, POP, AUC_dict): """ Calculate AUNP. :param classes: classes :type classes : list :param P: condition positive :type P : dict :param POP: population :type POP : dict :param AUC_dict: AUC (Area under the ROC curve) for each class :type AUC_dict : dict :return: AUNP as float """ try: result = 0 for i in classes: result += (P[i] / POP[i]) * AUC_dict[i] return result except Exception: return "None"
python
def AUNP_calc(classes, P, POP, AUC_dict): try: result = 0 for i in classes: result += (P[i] / POP[i]) * AUC_dict[i] return result except Exception: return "None"
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Calculate AUNP. :param classes: classes :type classes : list :param P: condition positive :type P : dict :param POP: population :type POP : dict :param AUC_dict: AUC (Area under the ROC curve) for each class :type AUC_dict : dict :return: AUNP as float
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L43-L63
250,055
sepandhaghighi/pycm
pycm/pycm_overall_func.py
overall_MCC_calc
def overall_MCC_calc(classes, table, TOP, P): """ Calculate Overall_MCC. :param classes: classes :type classes : list :param table: input matrix :type table : dict :param TOP: test outcome positive :type TOP : dict :param P: condition positive :type P : dict :return: Overall_MCC as float """ try: cov_x_y = 0 cov_x_x = 0 cov_y_y = 0 matrix_sum = sum(list(TOP.values())) for i in classes: cov_x_x += TOP[i] * (matrix_sum - TOP[i]) cov_y_y += P[i] * (matrix_sum - P[i]) cov_x_y += (table[i][i] * matrix_sum - P[i] * TOP[i]) return cov_x_y / (math.sqrt(cov_y_y * cov_x_x)) except Exception: return "None"
python
def overall_MCC_calc(classes, table, TOP, P): try: cov_x_y = 0 cov_x_x = 0 cov_y_y = 0 matrix_sum = sum(list(TOP.values())) for i in classes: cov_x_x += TOP[i] * (matrix_sum - TOP[i]) cov_y_y += P[i] * (matrix_sum - P[i]) cov_x_y += (table[i][i] * matrix_sum - P[i] * TOP[i]) return cov_x_y / (math.sqrt(cov_y_y * cov_x_x)) except Exception: return "None"
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Calculate Overall_MCC. :param classes: classes :type classes : list :param table: input matrix :type table : dict :param TOP: test outcome positive :type TOP : dict :param P: condition positive :type P : dict :return: Overall_MCC as float
[ "Calculate", "Overall_MCC", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L108-L133
250,056
sepandhaghighi/pycm
pycm/pycm_overall_func.py
convex_combination
def convex_combination(classes, TP, TOP, P, class_name, modified=False): """ Calculate Overall_CEN coefficient. :param classes: classes :type classes : list :param TP: true Positive Dict For All Classes :type TP : dict :param TOP: test outcome positive :type TOP : dict :param P: condition positive :type P : dict :param class_name: reviewed class name :type class_name : any valid type :param modified : modified mode flag :type modified : bool :return: coefficient as float """ try: class_number = len(classes) alpha = 1 if class_number == 2: alpha = 0 matrix_sum = sum(list(TOP.values())) TP_sum = sum(list(TP.values())) up = TOP[class_name] + P[class_name] down = 2 * matrix_sum if modified: down -= (alpha * TP_sum) up -= TP[class_name] return up / down except Exception: return "None"
python
def convex_combination(classes, TP, TOP, P, class_name, modified=False): try: class_number = len(classes) alpha = 1 if class_number == 2: alpha = 0 matrix_sum = sum(list(TOP.values())) TP_sum = sum(list(TP.values())) up = TOP[class_name] + P[class_name] down = 2 * matrix_sum if modified: down -= (alpha * TP_sum) up -= TP[class_name] return up / down except Exception: return "None"
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Calculate Overall_CEN coefficient. :param classes: classes :type classes : list :param TP: true Positive Dict For All Classes :type TP : dict :param TOP: test outcome positive :type TOP : dict :param P: condition positive :type P : dict :param class_name: reviewed class name :type class_name : any valid type :param modified : modified mode flag :type modified : bool :return: coefficient as float
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L136-L168
250,057
sepandhaghighi/pycm
pycm/pycm_overall_func.py
ncr
def ncr(n, r): """ Calculate n choose r. :param n: n :type n : int :param r: r :type r :int :return: n choose r as int """ r = min(r, n - r) numer = reduce(op.mul, range(n, n - r, -1), 1) denom = reduce(op.mul, range(1, r + 1), 1) return numer // denom
python
def ncr(n, r): r = min(r, n - r) numer = reduce(op.mul, range(n, n - r, -1), 1) denom = reduce(op.mul, range(1, r + 1), 1) return numer // denom
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Calculate n choose r. :param n: n :type n : int :param r: r :type r :int :return: n choose r as int
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L199-L212
250,058
sepandhaghighi/pycm
pycm/pycm_overall_func.py
p_value_calc
def p_value_calc(TP, POP, NIR): """ Calculate p_value. :param TP: true positive :type TP : dict :param POP: population :type POP : int :param NIR: no information rate :type NIR : float :return: p_value as float """ try: n = POP x = sum(list(TP.values())) p = NIR result = 0 for j in range(x): result += ncr(n, j) * (p ** j) * ((1 - p) ** (n - j)) return 1 - result except Exception: return "None"
python
def p_value_calc(TP, POP, NIR): try: n = POP x = sum(list(TP.values())) p = NIR result = 0 for j in range(x): result += ncr(n, j) * (p ** j) * ((1 - p) ** (n - j)) return 1 - result except Exception: return "None"
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Calculate p_value. :param TP: true positive :type TP : dict :param POP: population :type POP : int :param NIR: no information rate :type NIR : float :return: p_value as float
[ "Calculate", "p_value", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L215-L236
250,059
sepandhaghighi/pycm
pycm/pycm_overall_func.py
hamming_calc
def hamming_calc(TP, POP): """ Calculate hamming loss. :param TP: true positive :type TP : dict :param POP: population :type POP : int :return: hamming loss as float """ try: length = POP return (1 / length) * (length - sum(TP.values())) except Exception: return "None"
python
def hamming_calc(TP, POP): try: length = POP return (1 / length) * (length - sum(TP.values())) except Exception: return "None"
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Calculate hamming loss. :param TP: true positive :type TP : dict :param POP: population :type POP : int :return: hamming loss as float
[ "Calculate", "hamming", "loss", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L257-L271
250,060
sepandhaghighi/pycm
pycm/pycm_overall_func.py
zero_one_loss_calc
def zero_one_loss_calc(TP, POP): """ Calculate zero-one loss. :param TP: true Positive :type TP : dict :param POP: population :type POP : int :return: zero_one loss as integer """ try: length = POP return (length - sum(TP.values())) except Exception: return "None"
python
def zero_one_loss_calc(TP, POP): try: length = POP return (length - sum(TP.values())) except Exception: return "None"
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Calculate zero-one loss. :param TP: true Positive :type TP : dict :param POP: population :type POP : int :return: zero_one loss as integer
[ "Calculate", "zero", "-", "one", "loss", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L274-L288
250,061
sepandhaghighi/pycm
pycm/pycm_overall_func.py
entropy_calc
def entropy_calc(item, POP): """ Calculate reference and response likelihood. :param item : TOP or P :type item : dict :param POP: population :type POP : dict :return: reference or response likelihood as float """ try: result = 0 for i in item.keys(): likelihood = item[i] / POP[i] if likelihood != 0: result += likelihood * math.log(likelihood, 2) return -result except Exception: return "None"
python
def entropy_calc(item, POP): try: result = 0 for i in item.keys(): likelihood = item[i] / POP[i] if likelihood != 0: result += likelihood * math.log(likelihood, 2) return -result except Exception: return "None"
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Calculate reference and response likelihood. :param item : TOP or P :type item : dict :param POP: population :type POP : dict :return: reference or response likelihood as float
[ "Calculate", "reference", "and", "response", "likelihood", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L291-L309
250,062
sepandhaghighi/pycm
pycm/pycm_overall_func.py
cross_entropy_calc
def cross_entropy_calc(TOP, P, POP): """ Calculate cross entropy. :param TOP: test outcome positive :type TOP : dict :param P: condition positive :type P : dict :param POP: population :type POP : dict :return: cross entropy as float """ try: result = 0 for i in TOP.keys(): reference_likelihood = P[i] / POP[i] response_likelihood = TOP[i] / POP[i] if response_likelihood != 0 and reference_likelihood != 0: result += reference_likelihood * \ math.log(response_likelihood, 2) return -result except Exception: return "None"
python
def cross_entropy_calc(TOP, P, POP): try: result = 0 for i in TOP.keys(): reference_likelihood = P[i] / POP[i] response_likelihood = TOP[i] / POP[i] if response_likelihood != 0 and reference_likelihood != 0: result += reference_likelihood * \ math.log(response_likelihood, 2) return -result except Exception: return "None"
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Calculate cross entropy. :param TOP: test outcome positive :type TOP : dict :param P: condition positive :type P : dict :param POP: population :type POP : dict :return: cross entropy as float
[ "Calculate", "cross", "entropy", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L327-L349
250,063
sepandhaghighi/pycm
pycm/pycm_overall_func.py
joint_entropy_calc
def joint_entropy_calc(classes, table, POP): """ Calculate joint entropy. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param POP: population :type POP : dict :return: joint entropy as float """ try: result = 0 for i in classes: for index, j in enumerate(classes): p_prime = table[i][j] / POP[i] if p_prime != 0: result += p_prime * math.log(p_prime, 2) return -result except Exception: return "None"
python
def joint_entropy_calc(classes, table, POP): try: result = 0 for i in classes: for index, j in enumerate(classes): p_prime = table[i][j] / POP[i] if p_prime != 0: result += p_prime * math.log(p_prime, 2) return -result except Exception: return "None"
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Calculate joint entropy. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param POP: population :type POP : dict :return: joint entropy as float
[ "Calculate", "joint", "entropy", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L352-L373
250,064
sepandhaghighi/pycm
pycm/pycm_overall_func.py
conditional_entropy_calc
def conditional_entropy_calc(classes, table, P, POP): """ Calculate conditional entropy. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param P: condition positive :type P : dict :param POP: population :type POP : dict :return: conditional entropy as float """ try: result = 0 for i in classes: temp = 0 for index, j in enumerate(classes): p_prime = 0 if P[i] != 0: p_prime = table[i][j] / P[i] if p_prime != 0: temp += p_prime * math.log(p_prime, 2) result += temp * (P[i] / POP[i]) return -result except Exception: return "None"
python
def conditional_entropy_calc(classes, table, P, POP): try: result = 0 for i in classes: temp = 0 for index, j in enumerate(classes): p_prime = 0 if P[i] != 0: p_prime = table[i][j] / P[i] if p_prime != 0: temp += p_prime * math.log(p_prime, 2) result += temp * (P[i] / POP[i]) return -result except Exception: return "None"
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Calculate conditional entropy. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param P: condition positive :type P : dict :param POP: population :type POP : dict :return: conditional entropy as float
[ "Calculate", "conditional", "entropy", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L376-L403
250,065
sepandhaghighi/pycm
pycm/pycm_overall_func.py
lambda_B_calc
def lambda_B_calc(classes, table, TOP, POP): """ Calculate Goodman and Kruskal's lambda B. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param TOP: test outcome positive :type TOP : dict :param POP: population :type POP : int :return: Goodman and Kruskal's lambda B as float """ try: result = 0 length = POP maxresponse = max(list(TOP.values())) for i in classes: result += max(list(table[i].values())) result = (result - maxresponse) / (length - maxresponse) return result except Exception: return "None"
python
def lambda_B_calc(classes, table, TOP, POP): try: result = 0 length = POP maxresponse = max(list(TOP.values())) for i in classes: result += max(list(table[i].values())) result = (result - maxresponse) / (length - maxresponse) return result except Exception: return "None"
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Calculate Goodman and Kruskal's lambda B. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param TOP: test outcome positive :type TOP : dict :param POP: population :type POP : int :return: Goodman and Kruskal's lambda B as float
[ "Calculate", "Goodman", "and", "Kruskal", "s", "lambda", "B", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L446-L469
250,066
sepandhaghighi/pycm
pycm/pycm_overall_func.py
lambda_A_calc
def lambda_A_calc(classes, table, P, POP): """ Calculate Goodman and Kruskal's lambda A. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param P: condition positive :type P : dict :param POP: population :type POP : int :return: Goodman and Kruskal's lambda A as float """ try: result = 0 maxreference = max(list(P.values())) length = POP for i in classes: col = [] for col_item in table.values(): col.append(col_item[i]) result += max(col) result = (result - maxreference) / (length - maxreference) return result except Exception: return "None"
python
def lambda_A_calc(classes, table, P, POP): try: result = 0 maxreference = max(list(P.values())) length = POP for i in classes: col = [] for col_item in table.values(): col.append(col_item[i]) result += max(col) result = (result - maxreference) / (length - maxreference) return result except Exception: return "None"
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Calculate Goodman and Kruskal's lambda A. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param P: condition positive :type P : dict :param POP: population :type POP : int :return: Goodman and Kruskal's lambda A as float
[ "Calculate", "Goodman", "and", "Kruskal", "s", "lambda", "A", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L472-L498
250,067
sepandhaghighi/pycm
pycm/pycm_overall_func.py
chi_square_calc
def chi_square_calc(classes, table, TOP, P, POP): """ Calculate chi-squared. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param TOP: test outcome positive :type TOP : dict :param P: condition positive :type P : dict :param POP: population :type POP : dict :return: chi-squared as float """ try: result = 0 for i in classes: for index, j in enumerate(classes): expected = (TOP[j] * P[i]) / (POP[i]) result += ((table[i][j] - expected)**2) / expected return result except Exception: return "None"
python
def chi_square_calc(classes, table, TOP, P, POP): try: result = 0 for i in classes: for index, j in enumerate(classes): expected = (TOP[j] * P[i]) / (POP[i]) result += ((table[i][j] - expected)**2) / expected return result except Exception: return "None"
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Calculate chi-squared. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param TOP: test outcome positive :type TOP : dict :param P: condition positive :type P : dict :param POP: population :type POP : dict :return: chi-squared as float
[ "Calculate", "chi", "-", "squared", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L501-L525
250,068
sepandhaghighi/pycm
pycm/pycm_overall_func.py
kappa_se_calc
def kappa_se_calc(PA, PE, POP): """ Calculate kappa standard error. :param PA: observed agreement among raters (overall accuracy) :type PA : float :param PE: hypothetical probability of chance agreement (random accuracy) :type PE : float :param POP: population :type POP:int :return: kappa standard error as float """ try: result = math.sqrt((PA * (1 - PA)) / (POP * ((1 - PE)**2))) return result except Exception: return "None"
python
def kappa_se_calc(PA, PE, POP): try: result = math.sqrt((PA * (1 - PA)) / (POP * ((1 - PE)**2))) return result except Exception: return "None"
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Calculate kappa standard error. :param PA: observed agreement among raters (overall accuracy) :type PA : float :param PE: hypothetical probability of chance agreement (random accuracy) :type PE : float :param POP: population :type POP:int :return: kappa standard error as float
[ "Calculate", "kappa", "standard", "error", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L591-L607
250,069
sepandhaghighi/pycm
pycm/pycm_overall_func.py
micro_calc
def micro_calc(TP, item): """ Calculate PPV_Micro and TPR_Micro. :param TP: true positive :type TP:dict :param item: FN or FP :type item : dict :return: PPV_Micro or TPR_Micro as float """ try: TP_sum = sum(TP.values()) item_sum = sum(item.values()) return TP_sum / (TP_sum + item_sum) except Exception: return "None"
python
def micro_calc(TP, item): try: TP_sum = sum(TP.values()) item_sum = sum(item.values()) return TP_sum / (TP_sum + item_sum) except Exception: return "None"
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Calculate PPV_Micro and TPR_Micro. :param TP: true positive :type TP:dict :param item: FN or FP :type item : dict :return: PPV_Micro or TPR_Micro as float
[ "Calculate", "PPV_Micro", "and", "TPR_Micro", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L648-L663
250,070
sepandhaghighi/pycm
pycm/pycm_overall_func.py
macro_calc
def macro_calc(item): """ Calculate PPV_Macro and TPR_Macro. :param item: PPV or TPR :type item:dict :return: PPV_Macro or TPR_Macro as float """ try: item_sum = sum(item.values()) item_len = len(item.values()) return item_sum / item_len except Exception: return "None"
python
def macro_calc(item): try: item_sum = sum(item.values()) item_len = len(item.values()) return item_sum / item_len except Exception: return "None"
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Calculate PPV_Macro and TPR_Macro. :param item: PPV or TPR :type item:dict :return: PPV_Macro or TPR_Macro as float
[ "Calculate", "PPV_Macro", "and", "TPR_Macro", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L666-L679
250,071
sepandhaghighi/pycm
pycm/pycm_overall_func.py
PC_PI_calc
def PC_PI_calc(P, TOP, POP): """ Calculate percent chance agreement for Scott's Pi. :param P: condition positive :type P : dict :param TOP: test outcome positive :type TOP : dict :param POP: population :type POP:dict :return: percent chance agreement as float """ try: result = 0 for i in P.keys(): result += ((P[i] + TOP[i]) / (2 * POP[i]))**2 return result except Exception: return "None"
python
def PC_PI_calc(P, TOP, POP): try: result = 0 for i in P.keys(): result += ((P[i] + TOP[i]) / (2 * POP[i]))**2 return result except Exception: return "None"
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Calculate percent chance agreement for Scott's Pi. :param P: condition positive :type P : dict :param TOP: test outcome positive :type TOP : dict :param POP: population :type POP:dict :return: percent chance agreement as float
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L682-L700
250,072
sepandhaghighi/pycm
pycm/pycm_overall_func.py
PC_AC1_calc
def PC_AC1_calc(P, TOP, POP): """ Calculate percent chance agreement for Gwet's AC1. :param P: condition positive :type P : dict :param TOP: test outcome positive :type TOP : dict :param POP: population :type POP:dict :return: percent chance agreement as float """ try: result = 0 classes = list(P.keys()) for i in classes: pi = ((P[i] + TOP[i]) / (2 * POP[i])) result += pi * (1 - pi) result = result / (len(classes) - 1) return result except Exception: return "None"
python
def PC_AC1_calc(P, TOP, POP): try: result = 0 classes = list(P.keys()) for i in classes: pi = ((P[i] + TOP[i]) / (2 * POP[i])) result += pi * (1 - pi) result = result / (len(classes) - 1) return result except Exception: return "None"
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Calculate percent chance agreement for Gwet's AC1. :param P: condition positive :type P : dict :param TOP: test outcome positive :type TOP : dict :param POP: population :type POP:dict :return: percent chance agreement as float
[ "Calculate", "percent", "chance", "agreement", "for", "Gwet", "s", "AC1", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L703-L724
250,073
sepandhaghighi/pycm
pycm/pycm_overall_func.py
overall_jaccard_index_calc
def overall_jaccard_index_calc(jaccard_list): """ Calculate overall jaccard index. :param jaccard_list : list of jaccard index for each class :type jaccard_list : list :return: (jaccard_sum , jaccard_mean) as tuple """ try: jaccard_sum = sum(jaccard_list) jaccard_mean = jaccard_sum / len(jaccard_list) return (jaccard_sum, jaccard_mean) except Exception: return "None"
python
def overall_jaccard_index_calc(jaccard_list): try: jaccard_sum = sum(jaccard_list) jaccard_mean = jaccard_sum / len(jaccard_list) return (jaccard_sum, jaccard_mean) except Exception: return "None"
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Calculate overall jaccard index. :param jaccard_list : list of jaccard index for each class :type jaccard_list : list :return: (jaccard_sum , jaccard_mean) as tuple
[ "Calculate", "overall", "jaccard", "index", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L741-L754
250,074
sepandhaghighi/pycm
pycm/pycm_overall_func.py
overall_accuracy_calc
def overall_accuracy_calc(TP, POP): """ Calculate overall accuracy. :param TP: true positive :type TP : dict :param POP: population :type POP:int :return: overall_accuracy as float """ try: overall_accuracy = sum(TP.values()) / POP return overall_accuracy except Exception: return "None"
python
def overall_accuracy_calc(TP, POP): try: overall_accuracy = sum(TP.values()) / POP return overall_accuracy except Exception: return "None"
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Calculate overall accuracy. :param TP: true positive :type TP : dict :param POP: population :type POP:int :return: overall_accuracy as float
[ "Calculate", "overall", "accuracy", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_overall_func.py#L757-L771
250,075
sepandhaghighi/pycm
pycm/pycm_interpret.py
AUC_analysis
def AUC_analysis(AUC): """ Analysis AUC with interpretation table. :param AUC: area under the ROC curve :type AUC : float :return: interpretation result as str """ try: if AUC == "None": return "None" if AUC < 0.6: return "Poor" if AUC >= 0.6 and AUC < 0.7: return "Fair" if AUC >= 0.7 and AUC < 0.8: return "Good" if AUC >= 0.8 and AUC < 0.9: return "Very Good" return "Excellent" except Exception: # pragma: no cover return "None"
python
def AUC_analysis(AUC): try: if AUC == "None": return "None" if AUC < 0.6: return "Poor" if AUC >= 0.6 and AUC < 0.7: return "Fair" if AUC >= 0.7 and AUC < 0.8: return "Good" if AUC >= 0.8 and AUC < 0.9: return "Very Good" return "Excellent" except Exception: # pragma: no cover return "None"
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Analysis AUC with interpretation table. :param AUC: area under the ROC curve :type AUC : float :return: interpretation result as str
[ "Analysis", "AUC", "with", "interpretation", "table", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_interpret.py#L50-L71
250,076
sepandhaghighi/pycm
pycm/pycm_interpret.py
kappa_analysis_cicchetti
def kappa_analysis_cicchetti(kappa): """ Analysis kappa number with Cicchetti benchmark. :param kappa: kappa number :type kappa : float :return: strength of agreement as str """ try: if kappa < 0.4: return "Poor" if kappa >= 0.4 and kappa < 0.59: return "Fair" if kappa >= 0.59 and kappa < 0.74: return "Good" if kappa >= 0.74 and kappa <= 1: return "Excellent" return "None" except Exception: # pragma: no cover return "None"
python
def kappa_analysis_cicchetti(kappa): try: if kappa < 0.4: return "Poor" if kappa >= 0.4 and kappa < 0.59: return "Fair" if kappa >= 0.59 and kappa < 0.74: return "Good" if kappa >= 0.74 and kappa <= 1: return "Excellent" return "None" except Exception: # pragma: no cover return "None"
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Analysis kappa number with Cicchetti benchmark. :param kappa: kappa number :type kappa : float :return: strength of agreement as str
[ "Analysis", "kappa", "number", "with", "Cicchetti", "benchmark", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_interpret.py#L74-L93
250,077
sepandhaghighi/pycm
pycm/pycm_interpret.py
kappa_analysis_koch
def kappa_analysis_koch(kappa): """ Analysis kappa number with Landis-Koch benchmark. :param kappa: kappa number :type kappa : float :return: strength of agreement as str """ try: if kappa < 0: return "Poor" if kappa >= 0 and kappa < 0.2: return "Slight" if kappa >= 0.20 and kappa < 0.4: return "Fair" if kappa >= 0.40 and kappa < 0.6: return "Moderate" if kappa >= 0.60 and kappa < 0.8: return "Substantial" if kappa >= 0.80 and kappa <= 1: return "Almost Perfect" return "None" except Exception: # pragma: no cover return "None"
python
def kappa_analysis_koch(kappa): try: if kappa < 0: return "Poor" if kappa >= 0 and kappa < 0.2: return "Slight" if kappa >= 0.20 and kappa < 0.4: return "Fair" if kappa >= 0.40 and kappa < 0.6: return "Moderate" if kappa >= 0.60 and kappa < 0.8: return "Substantial" if kappa >= 0.80 and kappa <= 1: return "Almost Perfect" return "None" except Exception: # pragma: no cover return "None"
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Analysis kappa number with Landis-Koch benchmark. :param kappa: kappa number :type kappa : float :return: strength of agreement as str
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_interpret.py#L96-L119
250,078
sepandhaghighi/pycm
pycm/pycm_interpret.py
kappa_analysis_altman
def kappa_analysis_altman(kappa): """ Analysis kappa number with Altman benchmark. :param kappa: kappa number :type kappa : float :return: strength of agreement as str """ try: if kappa < 0.2: return "Poor" if kappa >= 0.20 and kappa < 0.4: return "Fair" if kappa >= 0.40 and kappa < 0.6: return "Moderate" if kappa >= 0.60 and kappa < 0.8: return "Good" if kappa >= 0.80 and kappa <= 1: return "Very Good" return "None" except Exception: # pragma: no cover return "None"
python
def kappa_analysis_altman(kappa): try: if kappa < 0.2: return "Poor" if kappa >= 0.20 and kappa < 0.4: return "Fair" if kappa >= 0.40 and kappa < 0.6: return "Moderate" if kappa >= 0.60 and kappa < 0.8: return "Good" if kappa >= 0.80 and kappa <= 1: return "Very Good" return "None" except Exception: # pragma: no cover return "None"
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Analysis kappa number with Altman benchmark. :param kappa: kappa number :type kappa : float :return: strength of agreement as str
[ "Analysis", "kappa", "number", "with", "Altman", "benchmark", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_interpret.py#L141-L162
250,079
sepandhaghighi/pycm
setup.py
get_requires
def get_requires(): """Read requirements.txt.""" requirements = open("requirements.txt", "r").read() return list(filter(lambda x: x != "", requirements.split()))
python
def get_requires(): requirements = open("requirements.txt", "r").read() return list(filter(lambda x: x != "", requirements.split()))
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Read requirements.txt.
[ "Read", "requirements", ".", "txt", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/setup.py#L9-L12
250,080
sepandhaghighi/pycm
setup.py
read_description
def read_description(): """Read README.md and CHANGELOG.md.""" try: with open("README.md") as r: description = "\n" description += r.read() with open("CHANGELOG.md") as c: description += "\n" description += c.read() return description except Exception: return ''' PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters. PyCM is the swiss-army knife of confusion matrices, targeted mainly at data scientists that need a broad array of metrics for predictive models and an accurate evaluation of large variety of classifiers.'''
python
def read_description(): try: with open("README.md") as r: description = "\n" description += r.read() with open("CHANGELOG.md") as c: description += "\n" description += c.read() return description except Exception: return ''' PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters. PyCM is the swiss-army knife of confusion matrices, targeted mainly at data scientists that need a broad array of metrics for predictive models and an accurate evaluation of large variety of classifiers.'''
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Read README.md and CHANGELOG.md.
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/setup.py#L15-L33
250,081
sepandhaghighi/pycm
pycm/pycm_obj.py
ConfusionMatrix.print_matrix
def print_matrix(self, one_vs_all=False, class_name=None): """ Print confusion matrix. :param one_vs_all : One-Vs-All mode flag :type one_vs_all : bool :param class_name : target class name for One-Vs-All mode :type class_name : any valid type :return: None """ classes = self.classes table = self.table if one_vs_all: [classes, table] = one_vs_all_func( classes, table, self.TP, self.TN, self.FP, self.FN, class_name) print(table_print(classes, table))
python
def print_matrix(self, one_vs_all=False, class_name=None): classes = self.classes table = self.table if one_vs_all: [classes, table] = one_vs_all_func( classes, table, self.TP, self.TN, self.FP, self.FN, class_name) print(table_print(classes, table))
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Print confusion matrix. :param one_vs_all : One-Vs-All mode flag :type one_vs_all : bool :param class_name : target class name for One-Vs-All mode :type class_name : any valid type :return: None
[ "Print", "confusion", "matrix", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_obj.py#L94-L109
250,082
sepandhaghighi/pycm
pycm/pycm_obj.py
ConfusionMatrix.stat
def stat(self, overall_param=None, class_param=None, class_name=None): """ Print statistical measures table. :param overall_param : overall parameters list for print, Example : ["Kappa","Scott PI] :type overall_param : list :param class_param : class parameters list for print, Example : ["TPR","TNR","AUC"] :type class_param : list :param class_name : class name (sub set of classes), Example :[1,2,3] :type class_name : list :return: None """ classes = class_filter(self.classes, class_name) print( stat_print( classes, self.class_stat, self.overall_stat, self.digit, overall_param, class_param))
python
def stat(self, overall_param=None, class_param=None, class_name=None): classes = class_filter(self.classes, class_name) print( stat_print( classes, self.class_stat, self.overall_stat, self.digit, overall_param, class_param))
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Print statistical measures table. :param overall_param : overall parameters list for print, Example : ["Kappa","Scott PI] :type overall_param : list :param class_param : class parameters list for print, Example : ["TPR","TNR","AUC"] :type class_param : list :param class_name : class name (sub set of classes), Example :[1,2,3] :type class_name : list :return: None
[ "Print", "statistical", "measures", "table", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_obj.py#L129-L147
250,083
sepandhaghighi/pycm
pycm/pycm_obj.py
ConfusionMatrix.save_html
def save_html( self, name, address=True, overall_param=None, class_param=None, class_name=None, color=(0, 0, 0), normalize=False): """ Save ConfusionMatrix in HTML file. :param name: filename :type name : str :param address: flag for address return :type address : bool :param overall_param : overall parameters list for save, Example : ["Kappa","Scott PI] :type overall_param : list :param class_param : class parameters list for save, Example : ["TPR","TNR","AUC"] :type class_param : list :param class_name : class name (sub set of classes), Example :[1,2,3] :type class_name : list :param color : matrix color (R,G,B) :type color : tuple :param normalize : save normalize matrix flag :type normalize : bool :return: saving Status as dict {"Status":bool , "Message":str} """ try: message = None table = self.table if normalize: table = self.normalized_table html_file = open(name + ".html", "w") html_file.write(html_init(name)) html_file.write(html_dataset_type(self.binary, self.imbalance)) html_file.write(html_table(self.classes, table, color, normalize)) html_file.write( html_overall_stat( self.overall_stat, self.digit, overall_param, self.recommended_list)) class_stat_classes = class_filter(self.classes, class_name) html_file.write( html_class_stat( class_stat_classes, self.class_stat, self.digit, class_param, self.recommended_list)) html_file.write(html_end(VERSION)) html_file.close() if address: message = os.path.join(os.getcwd(), name + ".html") return {"Status": True, "Message": message} except Exception as e: return {"Status": False, "Message": str(e)}
python
def save_html( self, name, address=True, overall_param=None, class_param=None, class_name=None, color=(0, 0, 0), normalize=False): try: message = None table = self.table if normalize: table = self.normalized_table html_file = open(name + ".html", "w") html_file.write(html_init(name)) html_file.write(html_dataset_type(self.binary, self.imbalance)) html_file.write(html_table(self.classes, table, color, normalize)) html_file.write( html_overall_stat( self.overall_stat, self.digit, overall_param, self.recommended_list)) class_stat_classes = class_filter(self.classes, class_name) html_file.write( html_class_stat( class_stat_classes, self.class_stat, self.digit, class_param, self.recommended_list)) html_file.write(html_end(VERSION)) html_file.close() if address: message = os.path.join(os.getcwd(), name + ".html") return {"Status": True, "Message": message} except Exception as e: return {"Status": False, "Message": str(e)}
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Save ConfusionMatrix in HTML file. :param name: filename :type name : str :param address: flag for address return :type address : bool :param overall_param : overall parameters list for save, Example : ["Kappa","Scott PI] :type overall_param : list :param class_param : class parameters list for save, Example : ["TPR","TNR","AUC"] :type class_param : list :param class_name : class name (sub set of classes), Example :[1,2,3] :type class_name : list :param color : matrix color (R,G,B) :type color : tuple :param normalize : save normalize matrix flag :type normalize : bool :return: saving Status as dict {"Status":bool , "Message":str}
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cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_obj.py#L212-L267
250,084
sepandhaghighi/pycm
pycm/pycm_obj.py
ConfusionMatrix.save_csv
def save_csv( self, name, address=True, class_param=None, class_name=None, matrix_save=True, normalize=False): """ Save ConfusionMatrix in CSV file. :param name: filename :type name : str :param address: flag for address return :type address : bool :param class_param : class parameters list for save, Example : ["TPR","TNR","AUC"] :type class_param : list :param class_name : class name (sub set of classes), Example :[1,2,3] :type class_name : list :param matrix_save : save matrix flag :type matrix_save : bool :param normalize : save normalize matrix flag :type normalize : bool :return: saving Status as dict {"Status":bool , "Message":str} """ try: message = None classes = class_filter(self.classes, class_name) csv_file = open(name + ".csv", "w") csv_data = csv_print( classes, self.class_stat, self.digit, class_param) csv_file.write(csv_data) if matrix_save: matrix = self.table if normalize: matrix = self.normalized_table csv_matrix_file = open(name + "_matrix" + ".csv", "w") csv_matrix_data = csv_matrix_print(self.classes, matrix) csv_matrix_file.write(csv_matrix_data) if address: message = os.path.join(os.getcwd(), name + ".csv") return {"Status": True, "Message": message} except Exception as e: return {"Status": False, "Message": str(e)}
python
def save_csv( self, name, address=True, class_param=None, class_name=None, matrix_save=True, normalize=False): try: message = None classes = class_filter(self.classes, class_name) csv_file = open(name + ".csv", "w") csv_data = csv_print( classes, self.class_stat, self.digit, class_param) csv_file.write(csv_data) if matrix_save: matrix = self.table if normalize: matrix = self.normalized_table csv_matrix_file = open(name + "_matrix" + ".csv", "w") csv_matrix_data = csv_matrix_print(self.classes, matrix) csv_matrix_file.write(csv_matrix_data) if address: message = os.path.join(os.getcwd(), name + ".csv") return {"Status": True, "Message": message} except Exception as e: return {"Status": False, "Message": str(e)}
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Save ConfusionMatrix in CSV file. :param name: filename :type name : str :param address: flag for address return :type address : bool :param class_param : class parameters list for save, Example : ["TPR","TNR","AUC"] :type class_param : list :param class_name : class name (sub set of classes), Example :[1,2,3] :type class_name : list :param matrix_save : save matrix flag :type matrix_save : bool :param normalize : save normalize matrix flag :type normalize : bool :return: saving Status as dict {"Status":bool , "Message":str}
[ "Save", "ConfusionMatrix", "in", "CSV", "file", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_obj.py#L269-L315
250,085
sepandhaghighi/pycm
pycm/pycm_obj.py
ConfusionMatrix.save_obj
def save_obj(self, name, address=True): """ Save ConfusionMatrix in .obj file. :param name: filename :type name : str :param address: flag for address return :type address : bool :return: saving Status as dict {"Status":bool , "Message":str} """ try: message = None obj_file = open(name + ".obj", "w") actual_vector_temp = self.actual_vector predict_vector_temp = self.predict_vector matrix_temp = {k: self.table[k].copy() for k in self.classes} matrix_items = [] for i in self.classes: matrix_items.append((i, list(matrix_temp[i].items()))) if isinstance(actual_vector_temp, numpy.ndarray): actual_vector_temp = actual_vector_temp.tolist() if isinstance(predict_vector_temp, numpy.ndarray): predict_vector_temp = predict_vector_temp.tolist() json.dump({"Actual-Vector": actual_vector_temp, "Predict-Vector": predict_vector_temp, "Matrix": matrix_items, "Digit": self.digit, "Sample-Weight": self.weights, "Transpose": self.transpose}, obj_file) if address: message = os.path.join(os.getcwd(), name + ".obj") return {"Status": True, "Message": message} except Exception as e: return {"Status": False, "Message": str(e)}
python
def save_obj(self, name, address=True): try: message = None obj_file = open(name + ".obj", "w") actual_vector_temp = self.actual_vector predict_vector_temp = self.predict_vector matrix_temp = {k: self.table[k].copy() for k in self.classes} matrix_items = [] for i in self.classes: matrix_items.append((i, list(matrix_temp[i].items()))) if isinstance(actual_vector_temp, numpy.ndarray): actual_vector_temp = actual_vector_temp.tolist() if isinstance(predict_vector_temp, numpy.ndarray): predict_vector_temp = predict_vector_temp.tolist() json.dump({"Actual-Vector": actual_vector_temp, "Predict-Vector": predict_vector_temp, "Matrix": matrix_items, "Digit": self.digit, "Sample-Weight": self.weights, "Transpose": self.transpose}, obj_file) if address: message = os.path.join(os.getcwd(), name + ".obj") return {"Status": True, "Message": message} except Exception as e: return {"Status": False, "Message": str(e)}
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Save ConfusionMatrix in .obj file. :param name: filename :type name : str :param address: flag for address return :type address : bool :return: saving Status as dict {"Status":bool , "Message":str}
[ "Save", "ConfusionMatrix", "in", ".", "obj", "file", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_obj.py#L317-L350
250,086
sepandhaghighi/pycm
pycm/pycm_obj.py
ConfusionMatrix.F_beta
def F_beta(self, beta): """ Calculate FBeta score. :param beta: beta parameter :type beta : float :return: FBeta score for classes as dict """ try: F_dict = {} for i in self.TP.keys(): F_dict[i] = F_calc( TP=self.TP[i], FP=self.FP[i], FN=self.FN[i], beta=beta) return F_dict except Exception: return {}
python
def F_beta(self, beta): try: F_dict = {} for i in self.TP.keys(): F_dict[i] = F_calc( TP=self.TP[i], FP=self.FP[i], FN=self.FN[i], beta=beta) return F_dict except Exception: return {}
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Calculate FBeta score. :param beta: beta parameter :type beta : float :return: FBeta score for classes as dict
[ "Calculate", "FBeta", "score", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_obj.py#L352-L370
250,087
sepandhaghighi/pycm
pycm/pycm_obj.py
ConfusionMatrix.IBA_alpha
def IBA_alpha(self, alpha): """ Calculate IBA_alpha score. :param alpha: alpha parameter :type alpha: float :return: IBA_alpha score for classes as dict """ try: IBA_dict = {} for i in self.classes: IBA_dict[i] = IBA_calc(self.TPR[i], self.TNR[i], alpha=alpha) return IBA_dict except Exception: return {}
python
def IBA_alpha(self, alpha): try: IBA_dict = {} for i in self.classes: IBA_dict[i] = IBA_calc(self.TPR[i], self.TNR[i], alpha=alpha) return IBA_dict except Exception: return {}
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Calculate IBA_alpha score. :param alpha: alpha parameter :type alpha: float :return: IBA_alpha score for classes as dict
[ "Calculate", "IBA_alpha", "score", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_obj.py#L372-L386
250,088
sepandhaghighi/pycm
pycm/pycm_obj.py
ConfusionMatrix.relabel
def relabel(self, mapping): """ Rename ConfusionMatrix classes. :param mapping: mapping dictionary :type mapping : dict :return: None """ if not isinstance(mapping, dict): raise pycmMatrixError(MAPPING_FORMAT_ERROR) if self.classes != list(mapping.keys()): raise pycmMatrixError(MAPPING_CLASS_NAME_ERROR) for row in self.classes: temp_dict = {} temp_dict_normalized = {} for col in self.classes: temp_dict[mapping[col]] = self.table[row][col] temp_dict_normalized[mapping[col] ] = self.normalized_table[row][col] del self.table[row] self.table[mapping[row]] = temp_dict del self.normalized_table[row] self.normalized_table[mapping[row]] = temp_dict_normalized self.matrix = self.table self.normalized_matrix = self.normalized_table for param in self.class_stat.keys(): temp_dict = {} for classname in self.classes: temp_dict[mapping[classname] ] = self.class_stat[param][classname] self.class_stat[param] = temp_dict self.classes = list(mapping.values()) self.TP = self.class_stat["TP"] self.TN = self.class_stat["TN"] self.FP = self.class_stat["FP"] self.FN = self.class_stat["FN"] __class_stat_init__(self)
python
def relabel(self, mapping): if not isinstance(mapping, dict): raise pycmMatrixError(MAPPING_FORMAT_ERROR) if self.classes != list(mapping.keys()): raise pycmMatrixError(MAPPING_CLASS_NAME_ERROR) for row in self.classes: temp_dict = {} temp_dict_normalized = {} for col in self.classes: temp_dict[mapping[col]] = self.table[row][col] temp_dict_normalized[mapping[col] ] = self.normalized_table[row][col] del self.table[row] self.table[mapping[row]] = temp_dict del self.normalized_table[row] self.normalized_table[mapping[row]] = temp_dict_normalized self.matrix = self.table self.normalized_matrix = self.normalized_table for param in self.class_stat.keys(): temp_dict = {} for classname in self.classes: temp_dict[mapping[classname] ] = self.class_stat[param][classname] self.class_stat[param] = temp_dict self.classes = list(mapping.values()) self.TP = self.class_stat["TP"] self.TN = self.class_stat["TN"] self.FP = self.class_stat["FP"] self.FN = self.class_stat["FN"] __class_stat_init__(self)
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Rename ConfusionMatrix classes. :param mapping: mapping dictionary :type mapping : dict :return: None
[ "Rename", "ConfusionMatrix", "classes", "." ]
cb03258afd6a821d10acba73c965aaac174bedcd
https://github.com/sepandhaghighi/pycm/blob/cb03258afd6a821d10acba73c965aaac174bedcd/pycm/pycm_obj.py#L426-L462
250,089
manns/pyspread
pyspread/src/gui/_toolbars.py
ToolbarBase.add_tools
def add_tools(self): """Adds tools from self.toolbardata to self""" for data in self.toolbardata: # tool type is in data[0] if data[0] == "T": # Simple tool _, msg_type, label, tool_tip = data icon = icons[label] self.label2id[label] = tool_id = wx.NewId() self.AddSimpleTool(tool_id, label, icon, short_help_string=tool_tip) self.ids_msgs[tool_id] = msg_type self.parent.Bind(wx.EVT_TOOL, self.OnTool, id=tool_id) elif data[0] == "S": # Separator self.AddSeparator() elif data[0] == "C": # Control _, control, tool_tip = data self.AddControl(control, label=tool_tip) elif data[0] == "O": # Check tool / option button _, label, tool_tip = data icon = icons[label] self.label2id[label] = tool_id = wx.NewId() self.AddCheckTool(tool_id, label, icon, icon, tool_tip) else: raise ValueError("Unknown tooltype " + str(data[0])) self.SetCustomOverflowItems([], []) self.Realize() # Adjust Toolbar size self.SetSize(self.DoGetBestSize())
python
def add_tools(self): for data in self.toolbardata: # tool type is in data[0] if data[0] == "T": # Simple tool _, msg_type, label, tool_tip = data icon = icons[label] self.label2id[label] = tool_id = wx.NewId() self.AddSimpleTool(tool_id, label, icon, short_help_string=tool_tip) self.ids_msgs[tool_id] = msg_type self.parent.Bind(wx.EVT_TOOL, self.OnTool, id=tool_id) elif data[0] == "S": # Separator self.AddSeparator() elif data[0] == "C": # Control _, control, tool_tip = data self.AddControl(control, label=tool_tip) elif data[0] == "O": # Check tool / option button _, label, tool_tip = data icon = icons[label] self.label2id[label] = tool_id = wx.NewId() self.AddCheckTool(tool_id, label, icon, icon, tool_tip) else: raise ValueError("Unknown tooltype " + str(data[0])) self.SetCustomOverflowItems([], []) self.Realize() # Adjust Toolbar size self.SetSize(self.DoGetBestSize())
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Adds tools from self.toolbardata to self
[ "Adds", "tools", "from", "self", ".", "toolbardata", "to", "self" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L96-L146
250,090
manns/pyspread
pyspread/src/gui/_toolbars.py
ToolbarBase.OnTool
def OnTool(self, event): """Toolbar event handler""" msgtype = self.ids_msgs[event.GetId()] post_command_event(self, msgtype)
python
def OnTool(self, event): msgtype = self.ids_msgs[event.GetId()] post_command_event(self, msgtype)
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Toolbar event handler
[ "Toolbar", "event", "handler" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L148-L152
250,091
manns/pyspread
pyspread/src/gui/_toolbars.py
MainToolbar.OnToggleTool
def OnToggleTool(self, event): """Tool event handler""" config["check_spelling"] = str(event.IsChecked()) toggle_id = self.parent.menubar.FindMenuItem(_("View"), _("Check spelling")) if toggle_id != -1: # Check may fail if translation is incomplete toggle_item = self.parent.menubar.FindItemById(toggle_id) toggle_item.Check(event.IsChecked()) self.parent.grid.grid_renderer.cell_cache.clear() self.parent.grid.ForceRefresh() event.Skip()
python
def OnToggleTool(self, event): config["check_spelling"] = str(event.IsChecked()) toggle_id = self.parent.menubar.FindMenuItem(_("View"), _("Check spelling")) if toggle_id != -1: # Check may fail if translation is incomplete toggle_item = self.parent.menubar.FindItemById(toggle_id) toggle_item.Check(event.IsChecked()) self.parent.grid.grid_renderer.cell_cache.clear() self.parent.grid.ForceRefresh() event.Skip()
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Tool event handler
[ "Tool", "event", "handler" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L209-L223
250,092
manns/pyspread
pyspread/src/gui/_toolbars.py
WidgetToolbar._get_button_label
def _get_button_label(self): """Gets Button label from user and returns string""" dlg = wx.TextEntryDialog(self, _('Button label:')) if dlg.ShowModal() == wx.ID_OK: label = dlg.GetValue() else: label = "" dlg.Destroy() return label
python
def _get_button_label(self): dlg = wx.TextEntryDialog(self, _('Button label:')) if dlg.ShowModal() == wx.ID_OK: label = dlg.GetValue() else: label = "" dlg.Destroy() return label
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Gets Button label from user and returns string
[ "Gets", "Button", "label", "from", "user", "and", "returns", "string" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L303-L315
250,093
manns/pyspread
pyspread/src/gui/_toolbars.py
WidgetToolbar.OnButtonCell
def OnButtonCell(self, event): """Event handler for cell button toggle button""" if self.button_cell_button_id == event.GetId(): if event.IsChecked(): label = self._get_button_label() post_command_event(self, self.ButtonCellMsg, text=label) else: post_command_event(self, self.ButtonCellMsg, text=False) event.Skip()
python
def OnButtonCell(self, event): if self.button_cell_button_id == event.GetId(): if event.IsChecked(): label = self._get_button_label() post_command_event(self, self.ButtonCellMsg, text=label) else: post_command_event(self, self.ButtonCellMsg, text=False) event.Skip()
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Event handler for cell button toggle button
[ "Event", "handler", "for", "cell", "button", "toggle", "button" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L317-L327
250,094
manns/pyspread
pyspread/src/gui/_toolbars.py
WidgetToolbar.OnVideoCell
def OnVideoCell(self, event): """Event handler for video cell toggle button""" if self.video_cell_button_id == event.GetId(): if event.IsChecked(): wildcard = _("Media files") + " (*.*)|*.*" videofile, __ = self.get_filepath_findex_from_user( wildcard, "Choose video or audio file", wx.OPEN) post_command_event(self, self.VideoCellMsg, videofile=videofile) else: post_command_event(self, self.VideoCellMsg, videofile=False) event.Skip()
python
def OnVideoCell(self, event): if self.video_cell_button_id == event.GetId(): if event.IsChecked(): wildcard = _("Media files") + " (*.*)|*.*" videofile, __ = self.get_filepath_findex_from_user( wildcard, "Choose video or audio file", wx.OPEN) post_command_event(self, self.VideoCellMsg, videofile=videofile) else: post_command_event(self, self.VideoCellMsg, videofile=False) event.Skip()
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Event handler for video cell toggle button
[ "Event", "handler", "for", "video", "cell", "toggle", "button" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L329-L342
250,095
manns/pyspread
pyspread/src/gui/_toolbars.py
FindToolbar.make_menu
def make_menu(self): """Creates the search menu""" menu = wx.Menu() item = menu.Append(-1, "Recent Searches") item.Enable(False) for __id, txt in enumerate(self.search_history): menu.Append(__id, txt) return menu
python
def make_menu(self): menu = wx.Menu() item = menu.Append(-1, "Recent Searches") item.Enable(False) for __id, txt in enumerate(self.search_history): menu.Append(__id, txt) return menu
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Creates the search menu
[ "Creates", "the", "search", "menu" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L427-L436
250,096
manns/pyspread
pyspread/src/gui/_toolbars.py
FindToolbar.OnMenu
def OnMenu(self, event): """Search history has been selected""" __id = event.GetId() try: menuitem = event.GetEventObject().FindItemById(__id) selected_text = menuitem.GetItemLabel() self.search.SetValue(selected_text) except AttributeError: # Not called by menu event.Skip()
python
def OnMenu(self, event): __id = event.GetId() try: menuitem = event.GetEventObject().FindItemById(__id) selected_text = menuitem.GetItemLabel() self.search.SetValue(selected_text) except AttributeError: # Not called by menu event.Skip()
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Search history has been selected
[ "Search", "history", "has", "been", "selected" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L438-L448
250,097
manns/pyspread
pyspread/src/gui/_toolbars.py
FindToolbar.OnSearch
def OnSearch(self, event): """Event handler for starting the search""" search_string = self.search.GetValue() if search_string not in self.search_history: self.search_history.append(search_string) if len(self.search_history) > 10: self.search_history.pop(0) self.menu = self.make_menu() self.search.SetMenu(self.menu) search_flags = self.search_options + ["FIND_NEXT"] post_command_event(self, self.FindMsg, text=search_string, flags=search_flags) self.search.SetFocus()
python
def OnSearch(self, event): search_string = self.search.GetValue() if search_string not in self.search_history: self.search_history.append(search_string) if len(self.search_history) > 10: self.search_history.pop(0) self.menu = self.make_menu() self.search.SetMenu(self.menu) search_flags = self.search_options + ["FIND_NEXT"] post_command_event(self, self.FindMsg, text=search_string, flags=search_flags) self.search.SetFocus()
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Event handler for starting the search
[ "Event", "handler", "for", "starting", "the", "search" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L450-L468
250,098
manns/pyspread
pyspread/src/gui/_toolbars.py
FindToolbar.OnSearchDirectionButton
def OnSearchDirectionButton(self, event): """Event handler for search direction toggle button""" if "DOWN" in self.search_options: flag_index = self.search_options.index("DOWN") self.search_options[flag_index] = "UP" elif "UP" in self.search_options: flag_index = self.search_options.index("UP") self.search_options[flag_index] = "DOWN" else: raise AttributeError(_("Neither UP nor DOWN in search_flags")) event.Skip()
python
def OnSearchDirectionButton(self, event): if "DOWN" in self.search_options: flag_index = self.search_options.index("DOWN") self.search_options[flag_index] = "UP" elif "UP" in self.search_options: flag_index = self.search_options.index("UP") self.search_options[flag_index] = "DOWN" else: raise AttributeError(_("Neither UP nor DOWN in search_flags")) event.Skip()
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Event handler for search direction toggle button
[ "Event", "handler", "for", "search", "direction", "toggle", "button" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L470-L482
250,099
manns/pyspread
pyspread/src/gui/_toolbars.py
FindToolbar.OnSearchFlag
def OnSearchFlag(self, event): """Event handler for search flag toggle buttons""" for label in self.search_options_buttons: button_id = self.label2id[label] if button_id == event.GetId(): if event.IsChecked(): self.search_options.append(label) else: flag_index = self.search_options.index(label) self.search_options.pop(flag_index) event.Skip()
python
def OnSearchFlag(self, event): for label in self.search_options_buttons: button_id = self.label2id[label] if button_id == event.GetId(): if event.IsChecked(): self.search_options.append(label) else: flag_index = self.search_options.index(label) self.search_options.pop(flag_index) event.Skip()
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Event handler for search flag toggle buttons
[ "Event", "handler", "for", "search", "flag", "toggle", "buttons" ]
0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/gui/_toolbars.py#L484-L496