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pahaz/sshtunnel
sshtunnel.py
SSHTunnelForwarder._check_tunnel
def _check_tunnel(self, _srv): """ Check if tunnel is already established """ if self.skip_tunnel_checkup: self.tunnel_is_up[_srv.local_address] = True return self.logger.info('Checking tunnel to: {0}'.format(_srv.remote_address)) if isinstance(_srv.local_address, string_types): # UNIX stream s = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM) else: s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.settimeout(TUNNEL_TIMEOUT) try: # Windows raises WinError 10049 if trying to connect to 0.0.0.0 connect_to = ('127.0.0.1', _srv.local_port) \ if _srv.local_host == '0.0.0.0' else _srv.local_address s.connect(connect_to) self.tunnel_is_up[_srv.local_address] = _srv.tunnel_ok.get( timeout=TUNNEL_TIMEOUT * 1.1 ) self.logger.debug( 'Tunnel to {0} is DOWN'.format(_srv.remote_address) ) except socket.error: self.logger.debug( 'Tunnel to {0} is DOWN'.format(_srv.remote_address) ) self.tunnel_is_up[_srv.local_address] = False except queue.Empty: self.logger.debug( 'Tunnel to {0} is UP'.format(_srv.remote_address) ) self.tunnel_is_up[_srv.local_address] = True finally: s.close()
python
def _check_tunnel(self, _srv): """ Check if tunnel is already established """ if self.skip_tunnel_checkup: self.tunnel_is_up[_srv.local_address] = True return self.logger.info('Checking tunnel to: {0}'.format(_srv.remote_address)) if isinstance(_srv.local_address, string_types): # UNIX stream s = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM) else: s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.settimeout(TUNNEL_TIMEOUT) try: # Windows raises WinError 10049 if trying to connect to 0.0.0.0 connect_to = ('127.0.0.1', _srv.local_port) \ if _srv.local_host == '0.0.0.0' else _srv.local_address s.connect(connect_to) self.tunnel_is_up[_srv.local_address] = _srv.tunnel_ok.get( timeout=TUNNEL_TIMEOUT * 1.1 ) self.logger.debug( 'Tunnel to {0} is DOWN'.format(_srv.remote_address) ) except socket.error: self.logger.debug( 'Tunnel to {0} is DOWN'.format(_srv.remote_address) ) self.tunnel_is_up[_srv.local_address] = False except queue.Empty: self.logger.debug( 'Tunnel to {0} is UP'.format(_srv.remote_address) ) self.tunnel_is_up[_srv.local_address] = True finally: s.close()
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Check if tunnel is already established
[ "Check", "if", "tunnel", "is", "already", "established" ]
66a923e4c6c8e41b8348420523fbf5ddfd53176c
https://github.com/pahaz/sshtunnel/blob/66a923e4c6c8e41b8348420523fbf5ddfd53176c/sshtunnel.py#L1243-L1277
3,901
pahaz/sshtunnel
sshtunnel.py
SSHTunnelForwarder.start
def start(self): """ Start the SSH tunnels """ if self.is_alive: self.logger.warning('Already started!') return self._create_tunnels() if not self.is_active: self._raise(BaseSSHTunnelForwarderError, reason='Could not establish session to SSH gateway') for _srv in self._server_list: thread = threading.Thread( target=self._serve_forever_wrapper, args=(_srv, ), name='Srv-{0}'.format(address_to_str(_srv.local_port)) ) thread.daemon = self.daemon_forward_servers thread.start() self._check_tunnel(_srv) self.is_alive = any(self.tunnel_is_up.values()) if not self.is_alive: self._raise(HandlerSSHTunnelForwarderError, 'An error occurred while opening tunnels.')
python
def start(self): """ Start the SSH tunnels """ if self.is_alive: self.logger.warning('Already started!') return self._create_tunnels() if not self.is_active: self._raise(BaseSSHTunnelForwarderError, reason='Could not establish session to SSH gateway') for _srv in self._server_list: thread = threading.Thread( target=self._serve_forever_wrapper, args=(_srv, ), name='Srv-{0}'.format(address_to_str(_srv.local_port)) ) thread.daemon = self.daemon_forward_servers thread.start() self._check_tunnel(_srv) self.is_alive = any(self.tunnel_is_up.values()) if not self.is_alive: self._raise(HandlerSSHTunnelForwarderError, 'An error occurred while opening tunnels.')
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Start the SSH tunnels
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66a923e4c6c8e41b8348420523fbf5ddfd53176c
https://github.com/pahaz/sshtunnel/blob/66a923e4c6c8e41b8348420523fbf5ddfd53176c/sshtunnel.py#L1287-L1308
3,902
pahaz/sshtunnel
sshtunnel.py
SSHTunnelForwarder.stop
def stop(self): """ Shut the tunnel down. .. note:: This **had** to be handled with care before ``0.1.0``: - if a port redirection is opened - the destination is not reachable - we attempt a connection to that tunnel (``SYN`` is sent and acknowledged, then a ``FIN`` packet is sent and never acknowledged... weird) - we try to shutdown: it will not succeed until ``FIN_WAIT_2`` and ``CLOSE_WAIT`` time out. .. note:: Handle these scenarios with :attr:`.tunnel_is_up`: if False, server ``shutdown()`` will be skipped on that tunnel """ self.logger.info('Closing all open connections...') opened_address_text = ', '.join( (address_to_str(k.local_address) for k in self._server_list) ) or 'None' self.logger.debug('Listening tunnels: ' + opened_address_text) self._stop_transport() self._server_list = [] # reset server list self.tunnel_is_up = {}
python
def stop(self): """ Shut the tunnel down. .. note:: This **had** to be handled with care before ``0.1.0``: - if a port redirection is opened - the destination is not reachable - we attempt a connection to that tunnel (``SYN`` is sent and acknowledged, then a ``FIN`` packet is sent and never acknowledged... weird) - we try to shutdown: it will not succeed until ``FIN_WAIT_2`` and ``CLOSE_WAIT`` time out. .. note:: Handle these scenarios with :attr:`.tunnel_is_up`: if False, server ``shutdown()`` will be skipped on that tunnel """ self.logger.info('Closing all open connections...') opened_address_text = ', '.join( (address_to_str(k.local_address) for k in self._server_list) ) or 'None' self.logger.debug('Listening tunnels: ' + opened_address_text) self._stop_transport() self._server_list = [] # reset server list self.tunnel_is_up = {}
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Shut the tunnel down. .. note:: This **had** to be handled with care before ``0.1.0``: - if a port redirection is opened - the destination is not reachable - we attempt a connection to that tunnel (``SYN`` is sent and acknowledged, then a ``FIN`` packet is sent and never acknowledged... weird) - we try to shutdown: it will not succeed until ``FIN_WAIT_2`` and ``CLOSE_WAIT`` time out. .. note:: Handle these scenarios with :attr:`.tunnel_is_up`: if False, server ``shutdown()`` will be skipped on that tunnel
[ "Shut", "the", "tunnel", "down", "." ]
66a923e4c6c8e41b8348420523fbf5ddfd53176c
https://github.com/pahaz/sshtunnel/blob/66a923e4c6c8e41b8348420523fbf5ddfd53176c/sshtunnel.py#L1310-L1335
3,903
pahaz/sshtunnel
sshtunnel.py
SSHTunnelForwarder._serve_forever_wrapper
def _serve_forever_wrapper(self, _srv, poll_interval=0.1): """ Wrapper for the server created for a SSH forward """ self.logger.info('Opening tunnel: {0} <> {1}'.format( address_to_str(_srv.local_address), address_to_str(_srv.remote_address)) ) _srv.serve_forever(poll_interval) # blocks until finished self.logger.info('Tunnel: {0} <> {1} released'.format( address_to_str(_srv.local_address), address_to_str(_srv.remote_address)) )
python
def _serve_forever_wrapper(self, _srv, poll_interval=0.1): """ Wrapper for the server created for a SSH forward """ self.logger.info('Opening tunnel: {0} <> {1}'.format( address_to_str(_srv.local_address), address_to_str(_srv.remote_address)) ) _srv.serve_forever(poll_interval) # blocks until finished self.logger.info('Tunnel: {0} <> {1} released'.format( address_to_str(_srv.local_address), address_to_str(_srv.remote_address)) )
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Wrapper for the server created for a SSH forward
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66a923e4c6c8e41b8348420523fbf5ddfd53176c
https://github.com/pahaz/sshtunnel/blob/66a923e4c6c8e41b8348420523fbf5ddfd53176c/sshtunnel.py#L1383-L1396
3,904
pahaz/sshtunnel
sshtunnel.py
SSHTunnelForwarder._stop_transport
def _stop_transport(self): """ Close the underlying transport when nothing more is needed """ try: self._check_is_started() except (BaseSSHTunnelForwarderError, HandlerSSHTunnelForwarderError) as e: self.logger.warning(e) for _srv in self._server_list: tunnel = _srv.local_address if self.tunnel_is_up[tunnel]: self.logger.info('Shutting down tunnel {0}'.format(tunnel)) _srv.shutdown() _srv.server_close() # clean up the UNIX domain socket if we're using one if isinstance(_srv, _UnixStreamForwardServer): try: os.unlink(_srv.local_address) except Exception as e: self.logger.error('Unable to unlink socket {0}: {1}' .format(self.local_address, repr(e))) self.is_alive = False if self.is_active: self._transport.close() self._transport.stop_thread() self.logger.debug('Transport is closed')
python
def _stop_transport(self): """ Close the underlying transport when nothing more is needed """ try: self._check_is_started() except (BaseSSHTunnelForwarderError, HandlerSSHTunnelForwarderError) as e: self.logger.warning(e) for _srv in self._server_list: tunnel = _srv.local_address if self.tunnel_is_up[tunnel]: self.logger.info('Shutting down tunnel {0}'.format(tunnel)) _srv.shutdown() _srv.server_close() # clean up the UNIX domain socket if we're using one if isinstance(_srv, _UnixStreamForwardServer): try: os.unlink(_srv.local_address) except Exception as e: self.logger.error('Unable to unlink socket {0}: {1}' .format(self.local_address, repr(e))) self.is_alive = False if self.is_active: self._transport.close() self._transport.stop_thread() self.logger.debug('Transport is closed')
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Close the underlying transport when nothing more is needed
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66a923e4c6c8e41b8348420523fbf5ddfd53176c
https://github.com/pahaz/sshtunnel/blob/66a923e4c6c8e41b8348420523fbf5ddfd53176c/sshtunnel.py#L1398-L1422
3,905
pahaz/sshtunnel
sshtunnel.py
SSHTunnelForwarder.local_bind_ports
def local_bind_ports(self): """ Return a list containing the ports of local side of the TCP tunnels """ self._check_is_started() return [_server.local_port for _server in self._server_list if _server.local_port is not None]
python
def local_bind_ports(self): """ Return a list containing the ports of local side of the TCP tunnels """ self._check_is_started() return [_server.local_port for _server in self._server_list if _server.local_port is not None]
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Return a list containing the ports of local side of the TCP tunnels
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66a923e4c6c8e41b8348420523fbf5ddfd53176c
https://github.com/pahaz/sshtunnel/blob/66a923e4c6c8e41b8348420523fbf5ddfd53176c/sshtunnel.py#L1455-L1461
3,906
pahaz/sshtunnel
sshtunnel.py
SSHTunnelForwarder.local_bind_hosts
def local_bind_hosts(self): """ Return a list containing the IP addresses listening for the tunnels """ self._check_is_started() return [_server.local_host for _server in self._server_list if _server.local_host is not None]
python
def local_bind_hosts(self): """ Return a list containing the IP addresses listening for the tunnels """ self._check_is_started() return [_server.local_host for _server in self._server_list if _server.local_host is not None]
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Return a list containing the IP addresses listening for the tunnels
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66a923e4c6c8e41b8348420523fbf5ddfd53176c
https://github.com/pahaz/sshtunnel/blob/66a923e4c6c8e41b8348420523fbf5ddfd53176c/sshtunnel.py#L1464-L1470
3,907
DMSC-Instrument-Data/lewis
src/lewis/core/utils.py
get_submodules
def get_submodules(module): """ This function imports all sub-modules of the supplied module and returns a dictionary with module names as keys and the sub-module objects as values. If the supplied parameter is not a module object, a RuntimeError is raised. :param module: Module object from which to import sub-modules. :return: Dict with name-module pairs. """ if not inspect.ismodule(module): raise RuntimeError( 'Can only extract submodules from a module object, ' 'for example imported via importlib.import_module') submodules = get_members(module, inspect.ismodule) module_path = list(getattr(module, '__path__', [None]))[0] if module_path is not None: for item in listdir(module_path): module_name = extract_module_name(osp.join(module_path, item)) if module_name is not None: try: submodules[module_name] = importlib.import_module( '.{}'.format(module_name), package=module.__name__) except ImportError: # This is necessary in case random directories are in the path or things can # just not be imported due to other ImportErrors. pass return submodules
python
def get_submodules(module): """ This function imports all sub-modules of the supplied module and returns a dictionary with module names as keys and the sub-module objects as values. If the supplied parameter is not a module object, a RuntimeError is raised. :param module: Module object from which to import sub-modules. :return: Dict with name-module pairs. """ if not inspect.ismodule(module): raise RuntimeError( 'Can only extract submodules from a module object, ' 'for example imported via importlib.import_module') submodules = get_members(module, inspect.ismodule) module_path = list(getattr(module, '__path__', [None]))[0] if module_path is not None: for item in listdir(module_path): module_name = extract_module_name(osp.join(module_path, item)) if module_name is not None: try: submodules[module_name] = importlib.import_module( '.{}'.format(module_name), package=module.__name__) except ImportError: # This is necessary in case random directories are in the path or things can # just not be imported due to other ImportErrors. pass return submodules
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This function imports all sub-modules of the supplied module and returns a dictionary with module names as keys and the sub-module objects as values. If the supplied parameter is not a module object, a RuntimeError is raised. :param module: Module object from which to import sub-modules. :return: Dict with name-module pairs.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/utils.py#L42-L73
3,908
DMSC-Instrument-Data/lewis
src/lewis/core/utils.py
extract_module_name
def extract_module_name(absolute_path): """ This function tries to extract a valid module name from the basename of the supplied path. If it's a directory, the directory name is returned, if it's a file, the file name without extension is returned. If the basename starts with _ or . or it's a file with an ending different from .py, the function returns None :param absolute_path: Absolute path of something that might be a module. :return: Module name or None. """ base_name = osp.basename(osp.normpath(absolute_path)) # If the basename starts with _ it's probably __init__.py or __pycache__ or something internal. # At the moment there seems to be no use case for those if base_name[0] in ('.', '_'): return None # If it's a directory, there's nothing else to check, so it can be returned directly if osp.isdir(absolute_path): return base_name module_name, extension = osp.splitext(base_name) # If it's a file, it must have a .py ending if extension == '.py': return module_name return None
python
def extract_module_name(absolute_path): """ This function tries to extract a valid module name from the basename of the supplied path. If it's a directory, the directory name is returned, if it's a file, the file name without extension is returned. If the basename starts with _ or . or it's a file with an ending different from .py, the function returns None :param absolute_path: Absolute path of something that might be a module. :return: Module name or None. """ base_name = osp.basename(osp.normpath(absolute_path)) # If the basename starts with _ it's probably __init__.py or __pycache__ or something internal. # At the moment there seems to be no use case for those if base_name[0] in ('.', '_'): return None # If it's a directory, there's nothing else to check, so it can be returned directly if osp.isdir(absolute_path): return base_name module_name, extension = osp.splitext(base_name) # If it's a file, it must have a .py ending if extension == '.py': return module_name return None
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This function tries to extract a valid module name from the basename of the supplied path. If it's a directory, the directory name is returned, if it's a file, the file name without extension is returned. If the basename starts with _ or . or it's a file with an ending different from .py, the function returns None :param absolute_path: Absolute path of something that might be a module. :return: Module name or None.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/utils.py#L97-L124
3,909
DMSC-Instrument-Data/lewis
src/lewis/core/utils.py
dict_strict_update
def dict_strict_update(base_dict, update_dict): """ This function updates base_dict with update_dict if and only if update_dict does not contain keys that are not already in base_dict. It is essentially a more strict interpretation of the term "updating" the dict. If update_dict contains keys that are not in base_dict, a RuntimeError is raised. :param base_dict: The dict that is to be updated. This dict is modified. :param update_dict: The dict containing the new values. """ additional_keys = set(update_dict.keys()) - set(base_dict.keys()) if len(additional_keys) > 0: raise RuntimeError( 'The update dictionary contains keys that are not part of ' 'the base dictionary: {}'.format(str(additional_keys)), additional_keys) base_dict.update(update_dict)
python
def dict_strict_update(base_dict, update_dict): """ This function updates base_dict with update_dict if and only if update_dict does not contain keys that are not already in base_dict. It is essentially a more strict interpretation of the term "updating" the dict. If update_dict contains keys that are not in base_dict, a RuntimeError is raised. :param base_dict: The dict that is to be updated. This dict is modified. :param update_dict: The dict containing the new values. """ additional_keys = set(update_dict.keys()) - set(base_dict.keys()) if len(additional_keys) > 0: raise RuntimeError( 'The update dictionary contains keys that are not part of ' 'the base dictionary: {}'.format(str(additional_keys)), additional_keys) base_dict.update(update_dict)
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This function updates base_dict with update_dict if and only if update_dict does not contain keys that are not already in base_dict. It is essentially a more strict interpretation of the term "updating" the dict. If update_dict contains keys that are not in base_dict, a RuntimeError is raised. :param base_dict: The dict that is to be updated. This dict is modified. :param update_dict: The dict containing the new values.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/utils.py#L127-L145
3,910
DMSC-Instrument-Data/lewis
src/lewis/core/utils.py
format_doc_text
def format_doc_text(text): """ A very thin wrapper around textwrap.fill to consistently wrap documentation text for display in a command line environment. The text is wrapped to 99 characters with an indentation depth of 4 spaces. Each line is wrapped independently in order to preserve manually added line breaks. :param text: The text to format, it is cleaned by inspect.cleandoc. :return: The formatted doc text. """ return '\n'.join( textwrap.fill(line, width=99, initial_indent=' ', subsequent_indent=' ') for line in inspect.cleandoc(text).splitlines())
python
def format_doc_text(text): """ A very thin wrapper around textwrap.fill to consistently wrap documentation text for display in a command line environment. The text is wrapped to 99 characters with an indentation depth of 4 spaces. Each line is wrapped independently in order to preserve manually added line breaks. :param text: The text to format, it is cleaned by inspect.cleandoc. :return: The formatted doc text. """ return '\n'.join( textwrap.fill(line, width=99, initial_indent=' ', subsequent_indent=' ') for line in inspect.cleandoc(text).splitlines())
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A very thin wrapper around textwrap.fill to consistently wrap documentation text for display in a command line environment. The text is wrapped to 99 characters with an indentation depth of 4 spaces. Each line is wrapped independently in order to preserve manually added line breaks. :param text: The text to format, it is cleaned by inspect.cleandoc. :return: The formatted doc text.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/utils.py#L250-L263
3,911
DMSC-Instrument-Data/lewis
src/lewis/core/utils.py
FromOptionalDependency.do_import
def do_import(self, *names): """ Tries to import names from the module specified on initialization of the FromOptionalDependency-object. In case an ImportError occurs, the requested names are replaced with stub objects. :param names: List of strings that are used as type names. :return: Tuple of actual symbols or stub types with provided names. If there is only one element in the tuple, that element is returned. """ try: module_object = importlib.import_module(self._module) objects = tuple(getattr(module_object, name) for name in names) except ImportError: def failing_init(obj, *args, **kwargs): raise self._exception objects = tuple(type(name, (object,), {'__init__': failing_init}) for name in names) return objects if len(objects) != 1 else objects[0]
python
def do_import(self, *names): """ Tries to import names from the module specified on initialization of the FromOptionalDependency-object. In case an ImportError occurs, the requested names are replaced with stub objects. :param names: List of strings that are used as type names. :return: Tuple of actual symbols or stub types with provided names. If there is only one element in the tuple, that element is returned. """ try: module_object = importlib.import_module(self._module) objects = tuple(getattr(module_object, name) for name in names) except ImportError: def failing_init(obj, *args, **kwargs): raise self._exception objects = tuple(type(name, (object,), {'__init__': failing_init}) for name in names) return objects if len(objects) != 1 else objects[0]
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Tries to import names from the module specified on initialization of the FromOptionalDependency-object. In case an ImportError occurs, the requested names are replaced with stub objects. :param names: List of strings that are used as type names. :return: Tuple of actual symbols or stub types with provided names. If there is only one element in the tuple, that element is returned.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/utils.py#L226-L247
3,912
DMSC-Instrument-Data/lewis
src/lewis/core/control_server.py
ExposedObject.get_api
def get_api(self): """ This method returns the class name and a list of exposed methods. It is exposed to RPC-clients by an instance of ExposedObjectCollection. :return: A dictionary describing the exposed API (consisting of a class name and methods). """ return {'class': type(self._object).__name__, 'methods': list(self._function_map.keys())}
python
def get_api(self): """ This method returns the class name and a list of exposed methods. It is exposed to RPC-clients by an instance of ExposedObjectCollection. :return: A dictionary describing the exposed API (consisting of a class name and methods). """ return {'class': type(self._object).__name__, 'methods': list(self._function_map.keys())}
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This method returns the class name and a list of exposed methods. It is exposed to RPC-clients by an instance of ExposedObjectCollection. :return: A dictionary describing the exposed API (consisting of a class name and methods).
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/control_server.py#L121-L128
3,913
DMSC-Instrument-Data/lewis
src/lewis/core/control_server.py
ExposedObjectCollection.remove_object
def remove_object(self, name): """ Remove the object exposed under that name. If no object is registered under the supplied name, a RuntimeError is raised. :param name: Name of object to be removed. """ if name not in self._object_map: raise RuntimeError('No object with name {} is registered.'.format(name)) for fn_name in list(self._function_map.keys()): if fn_name.startswith(name + '.') or fn_name.startswith(name + ':'): self._remove_function(fn_name) del self._object_map[name]
python
def remove_object(self, name): """ Remove the object exposed under that name. If no object is registered under the supplied name, a RuntimeError is raised. :param name: Name of object to be removed. """ if name not in self._object_map: raise RuntimeError('No object with name {} is registered.'.format(name)) for fn_name in list(self._function_map.keys()): if fn_name.startswith(name + '.') or fn_name.startswith(name + ':'): self._remove_function(fn_name) del self._object_map[name]
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Remove the object exposed under that name. If no object is registered under the supplied name, a RuntimeError is raised. :param name: Name of object to be removed.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/control_server.py#L219-L233
3,914
DMSC-Instrument-Data/lewis
src/lewis/devices/julabo/devices/device.py
SimulatedJulabo.set_set_point
def set_set_point(self, param): """ Sets the target temperature. :param param: The new temperature in C. Must be positive. :return: Empty string. """ if self.temperature_low_limit <= param <= self.temperature_high_limit: self.set_point_temperature = param return ""
python
def set_set_point(self, param): """ Sets the target temperature. :param param: The new temperature in C. Must be positive. :return: Empty string. """ if self.temperature_low_limit <= param <= self.temperature_high_limit: self.set_point_temperature = param return ""
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Sets the target temperature. :param param: The new temperature in C. Must be positive. :return: Empty string.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/devices/julabo/devices/device.py#L73-L82
3,915
DMSC-Instrument-Data/lewis
src/lewis/devices/julabo/devices/device.py
SimulatedJulabo.set_circulating
def set_circulating(self, param): """ Sets whether to circulate - in effect whether the heater is on. :param param: The mode to set, must be 0 or 1. :return: Empty string. """ if param == 0: self.is_circulating = param self.circulate_commanded = False elif param == 1: self.is_circulating = param self.circulate_commanded = True return ""
python
def set_circulating(self, param): """ Sets whether to circulate - in effect whether the heater is on. :param param: The mode to set, must be 0 or 1. :return: Empty string. """ if param == 0: self.is_circulating = param self.circulate_commanded = False elif param == 1: self.is_circulating = param self.circulate_commanded = True return ""
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Sets whether to circulate - in effect whether the heater is on. :param param: The mode to set, must be 0 or 1. :return: Empty string.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/devices/julabo/devices/device.py#L84-L97
3,916
DMSC-Instrument-Data/lewis
src/lewis/core/simulation.py
SimulationFactory.get_protocols
def get_protocols(self, device): """Returns a list of available protocols for the specified device.""" return self._reg.device_builder(device, self._rv).protocols
python
def get_protocols(self, device): """Returns a list of available protocols for the specified device.""" return self._reg.device_builder(device, self._rv).protocols
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Returns a list of available protocols for the specified device.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/simulation.py#L433-L435
3,917
DMSC-Instrument-Data/lewis
src/lewis/core/approaches.py
linear
def linear(current, target, rate, dt): """ This function returns the new value after moving towards target at the given speed constantly for the time dt. If for example the current position is 10 and the target is -20, the returned value will be less than 10 if rate and dt are greater than 0: .. sourcecode:: Python new_pos = linear(10, -20, 10, 0.1) # new_pos = 9 The function makes sure that the returned value never overshoots: .. sourcecode:: Python new_pos = linear(10, -20, 10, 100) # new_pos = -20 :param current: The current value of the variable to be changed. :param target: The target value to approach. :param rate: The rate at which the parameter should move towards target. :param dt: The time for which to calculate the change. :return: The new variable value. """ sign = (target > current) - (target < current) if not sign: return current new_value = current + sign * rate * dt if sign * new_value > sign * target: return target return new_value
python
def linear(current, target, rate, dt): """ This function returns the new value after moving towards target at the given speed constantly for the time dt. If for example the current position is 10 and the target is -20, the returned value will be less than 10 if rate and dt are greater than 0: .. sourcecode:: Python new_pos = linear(10, -20, 10, 0.1) # new_pos = 9 The function makes sure that the returned value never overshoots: .. sourcecode:: Python new_pos = linear(10, -20, 10, 100) # new_pos = -20 :param current: The current value of the variable to be changed. :param target: The target value to approach. :param rate: The rate at which the parameter should move towards target. :param dt: The time for which to calculate the change. :return: The new variable value. """ sign = (target > current) - (target < current) if not sign: return current new_value = current + sign * rate * dt if sign * new_value > sign * target: return target return new_value
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This function returns the new value after moving towards target at the given speed constantly for the time dt. If for example the current position is 10 and the target is -20, the returned value will be less than 10 if rate and dt are greater than 0: .. sourcecode:: Python new_pos = linear(10, -20, 10, 0.1) # new_pos = 9 The function makes sure that the returned value never overshoots: .. sourcecode:: Python new_pos = linear(10, -20, 10, 100) # new_pos = -20 :param current: The current value of the variable to be changed. :param target: The target value to approach. :param rate: The rate at which the parameter should move towards target. :param dt: The time for which to calculate the change. :return: The new variable value.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/approaches.py#L26-L61
3,918
DMSC-Instrument-Data/lewis
src/lewis/adapters/epics.py
BoundPV.meta
def meta(self): """Value of the bound meta-property on the target.""" if not self._pv.meta_data_property or not self._meta_target: return {} return getattr(self._meta_target, self._pv.meta_data_property)
python
def meta(self): """Value of the bound meta-property on the target.""" if not self._pv.meta_data_property or not self._meta_target: return {} return getattr(self._meta_target, self._pv.meta_data_property)
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Value of the bound meta-property on the target.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/epics.py#L93-L98
3,919
DMSC-Instrument-Data/lewis
src/lewis/adapters/epics.py
BoundPV.doc
def doc(self): """Docstring of property on target or override specified on PV-object.""" return self._pv.doc or inspect.getdoc( getattr(type(self._target), self._pv.property, None)) or ''
python
def doc(self): """Docstring of property on target or override specified on PV-object.""" return self._pv.doc or inspect.getdoc( getattr(type(self._target), self._pv.property, None)) or ''
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Docstring of property on target or override specified on PV-object.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/epics.py#L116-L119
3,920
DMSC-Instrument-Data/lewis
src/lewis/adapters/epics.py
PV.bind
def bind(self, *targets): """ Tries to bind the PV to one of the supplied targets. Targets are inspected according to the order in which they are supplied. :param targets: Objects to inspect from. :return: BoundPV instance with the PV bound to the target property. """ self.property = 'value' self.meta_data_property = 'meta' return BoundPV(self, self._get_target(self.property, *targets), self._get_target(self.meta_data_property, *targets))
python
def bind(self, *targets): """ Tries to bind the PV to one of the supplied targets. Targets are inspected according to the order in which they are supplied. :param targets: Objects to inspect from. :return: BoundPV instance with the PV bound to the target property. """ self.property = 'value' self.meta_data_property = 'meta' return BoundPV(self, self._get_target(self.property, *targets), self._get_target(self.meta_data_property, *targets))
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Tries to bind the PV to one of the supplied targets. Targets are inspected according to the order in which they are supplied. :param targets: Objects to inspect from. :return: BoundPV instance with the PV bound to the target property.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/epics.py#L224-L237
3,921
DMSC-Instrument-Data/lewis
src/lewis/adapters/epics.py
PV._get_callable
def _get_callable(self, func, *targets): """ If func is already a callable, it is returned directly. If it's a string, it is assumed to be a method on one of the objects supplied in targets and that is returned. If no method with the specified name is found, an AttributeError is raised. :param func: Callable or name of method on one object in targets. :param targets: List of targets with decreasing priority for finding func. :return: Callable. """ if not callable(func): func_name = func func = next((getattr(obj, func, None) for obj in targets if func in dir(obj)), None) if not func: raise AttributeError( 'No method with the name \'{}\' could be found on any of the target objects ' '(device, interface). Please check the spelling.'.format(func_name)) return func
python
def _get_callable(self, func, *targets): """ If func is already a callable, it is returned directly. If it's a string, it is assumed to be a method on one of the objects supplied in targets and that is returned. If no method with the specified name is found, an AttributeError is raised. :param func: Callable or name of method on one object in targets. :param targets: List of targets with decreasing priority for finding func. :return: Callable. """ if not callable(func): func_name = func func = next((getattr(obj, func, None) for obj in targets if func in dir(obj)), None) if not func: raise AttributeError( 'No method with the name \'{}\' could be found on any of the target objects ' '(device, interface). Please check the spelling.'.format(func_name)) return func
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If func is already a callable, it is returned directly. If it's a string, it is assumed to be a method on one of the objects supplied in targets and that is returned. If no method with the specified name is found, an AttributeError is raised. :param func: Callable or name of method on one object in targets. :param targets: List of targets with decreasing priority for finding func. :return: Callable.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/epics.py#L361-L381
3,922
DMSC-Instrument-Data/lewis
src/lewis/adapters/epics.py
PV._function_has_n_args
def _function_has_n_args(self, func, n): """ Returns true if func has n arguments. Arguments with default and self for methods are not considered. """ if inspect.ismethod(func): n += 1 argspec = inspect.getargspec(func) defaults = argspec.defaults or () return len(argspec.args) - len(defaults) == n
python
def _function_has_n_args(self, func, n): """ Returns true if func has n arguments. Arguments with default and self for methods are not considered. """ if inspect.ismethod(func): n += 1 argspec = inspect.getargspec(func) defaults = argspec.defaults or () return len(argspec.args) - len(defaults) == n
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Returns true if func has n arguments. Arguments with default and self for methods are not considered.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/epics.py#L383-L394
3,923
DMSC-Instrument-Data/lewis
src/lewis/adapters/epics.py
EpicsAdapter.start_server
def start_server(self): """ Creates a pcaspy-server. .. note:: The server does not process requests unless :meth:`handle` is called regularly. """ if self._server is None: self._server = SimpleServer() self._server.createPV(prefix=self._options.prefix, pvdb={k: v.config for k, v in self.interface.bound_pvs.items()}) self._driver = PropertyExposingDriver(interface=self.interface, device_lock=self.device_lock) self._driver.process_pv_updates(force=True) self.log.info('Started serving PVs: %s', ', '.join((self._options.prefix + pv for pv in self.interface.bound_pvs.keys())))
python
def start_server(self): """ Creates a pcaspy-server. .. note:: The server does not process requests unless :meth:`handle` is called regularly. """ if self._server is None: self._server = SimpleServer() self._server.createPV(prefix=self._options.prefix, pvdb={k: v.config for k, v in self.interface.bound_pvs.items()}) self._driver = PropertyExposingDriver(interface=self.interface, device_lock=self.device_lock) self._driver.process_pv_updates(force=True) self.log.info('Started serving PVs: %s', ', '.join((self._options.prefix + pv for pv in self.interface.bound_pvs.keys())))
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Creates a pcaspy-server. .. note:: The server does not process requests unless :meth:`handle` is called regularly.
[ "Creates", "a", "pcaspy", "-", "server", "." ]
931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/epics.py#L550-L568
3,924
DMSC-Instrument-Data/lewis
src/lewis/adapters/epics.py
EpicsAdapter.handle
def handle(self, cycle_delay=0.1): """ Call this method to spend about ``cycle_delay`` seconds processing requests in the pcaspy server. Under load, for example when running ``caget`` at a high frequency, the actual time spent in the method may be much shorter. This effect is not corrected for. :param cycle_delay: Approximate time to be spent processing requests in pcaspy server. """ if self._server is not None: self._server.process(cycle_delay) self._driver.process_pv_updates()
python
def handle(self, cycle_delay=0.1): """ Call this method to spend about ``cycle_delay`` seconds processing requests in the pcaspy server. Under load, for example when running ``caget`` at a high frequency, the actual time spent in the method may be much shorter. This effect is not corrected for. :param cycle_delay: Approximate time to be spent processing requests in pcaspy server. """ if self._server is not None: self._server.process(cycle_delay) self._driver.process_pv_updates()
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Call this method to spend about ``cycle_delay`` seconds processing requests in the pcaspy server. Under load, for example when running ``caget`` at a high frequency, the actual time spent in the method may be much shorter. This effect is not corrected for. :param cycle_delay: Approximate time to be spent processing requests in pcaspy server.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/epics.py#L578-L589
3,925
DMSC-Instrument-Data/lewis
src/lewis/core/control_client.py
ObjectProxy._make_request
def _make_request(self, method, *args): """ This method performs a JSON-RPC request via the object's ZMQ socket. If successful, the result is returned, otherwise exceptions are raised. Server side exceptions are raised using the same type as on the server if they are part of the exceptions-module. Otherwise, a RemoteException is raised. :param method: Method of the object to call on the remote. :param args: Positional arguments to the method call. :return: Result of the remote call if successful. """ response, request_id = self._connection.json_rpc(self._prefix + method, *args) if 'id' not in response: raise ProtocolException('JSON-RPC response does not contain ID field.') if response['id'] != request_id: raise ProtocolException( 'ID of JSON-RPC request ({}) did not match response ({}).'.format( request_id, response['id'])) if 'result' in response: return response['result'] if 'error' in response: if 'data' in response['error']: exception_type = response['error']['data']['type'] exception_message = response['error']['data']['message'] if not hasattr(exceptions, exception_type): raise RemoteException(exception_type, exception_message) else: exception = getattr(exceptions, exception_type) raise exception(exception_message) else: raise ProtocolException(response['error']['message'])
python
def _make_request(self, method, *args): """ This method performs a JSON-RPC request via the object's ZMQ socket. If successful, the result is returned, otherwise exceptions are raised. Server side exceptions are raised using the same type as on the server if they are part of the exceptions-module. Otherwise, a RemoteException is raised. :param method: Method of the object to call on the remote. :param args: Positional arguments to the method call. :return: Result of the remote call if successful. """ response, request_id = self._connection.json_rpc(self._prefix + method, *args) if 'id' not in response: raise ProtocolException('JSON-RPC response does not contain ID field.') if response['id'] != request_id: raise ProtocolException( 'ID of JSON-RPC request ({}) did not match response ({}).'.format( request_id, response['id'])) if 'result' in response: return response['result'] if 'error' in response: if 'data' in response['error']: exception_type = response['error']['data']['type'] exception_message = response['error']['data']['message'] if not hasattr(exceptions, exception_type): raise RemoteException(exception_type, exception_message) else: exception = getattr(exceptions, exception_type) raise exception(exception_message) else: raise ProtocolException(response['error']['message'])
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This method performs a JSON-RPC request via the object's ZMQ socket. If successful, the result is returned, otherwise exceptions are raised. Server side exceptions are raised using the same type as on the server if they are part of the exceptions-module. Otherwise, a RemoteException is raised. :param method: Method of the object to call on the remote. :param args: Positional arguments to the method call. :return: Result of the remote call if successful.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/control_client.py#L194-L229
3,926
DMSC-Instrument-Data/lewis
src/lewis/devices/linkam_t95/interfaces/stream_interface.py
LinkamT95StreamInterface.get_status
def get_status(self): """ Models "T Command" functionality of device. Returns all available status information about the device as single byte array. :return: Byte array consisting of 10 status bytes. """ # "The first command sent must be a 'T' command" from T95 manual self.device.serial_command_mode = True Tarray = [0x80] * 10 # Status byte (SB1) Tarray[0] = { 'stopped': 0x01, 'heat': 0x10, 'cool': 0x20, 'hold': 0x30, }.get(self.device._csm.state, 0x01) if Tarray[0] == 0x30 and self.device.hold_commanded: Tarray[0] = 0x50 # Error status byte (EB1) if self.device.pump_overspeed: Tarray[1] |= 0x01 # TODO: Add support for other error conditions? # Pump status byte (PB1) Tarray[2] = 0x80 + self.device.pump_speed # Temperature Tarray[6:10] = [ord(x) for x in "%04x" % (int(self.device.temperature * 10) & 0xFFFF)] return ''.join(chr(c) for c in Tarray)
python
def get_status(self): """ Models "T Command" functionality of device. Returns all available status information about the device as single byte array. :return: Byte array consisting of 10 status bytes. """ # "The first command sent must be a 'T' command" from T95 manual self.device.serial_command_mode = True Tarray = [0x80] * 10 # Status byte (SB1) Tarray[0] = { 'stopped': 0x01, 'heat': 0x10, 'cool': 0x20, 'hold': 0x30, }.get(self.device._csm.state, 0x01) if Tarray[0] == 0x30 and self.device.hold_commanded: Tarray[0] = 0x50 # Error status byte (EB1) if self.device.pump_overspeed: Tarray[1] |= 0x01 # TODO: Add support for other error conditions? # Pump status byte (PB1) Tarray[2] = 0x80 + self.device.pump_speed # Temperature Tarray[6:10] = [ord(x) for x in "%04x" % (int(self.device.temperature * 10) & 0xFFFF)] return ''.join(chr(c) for c in Tarray)
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Models "T Command" functionality of device. Returns all available status information about the device as single byte array. :return: Byte array consisting of 10 status bytes.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/devices/linkam_t95/interfaces/stream_interface.py#L49-L85
3,927
DMSC-Instrument-Data/lewis
src/lewis/devices/linkam_t95/interfaces/stream_interface.py
LinkamT95StreamInterface.set_rate
def set_rate(self, param): """ Models "Rate Command" functionality of device. Sets the target rate of temperature change. :param param: Rate of temperature change in C/min, multiplied by 100, as a string. Must be positive. :return: Empty string. """ # TODO: Is not having leading zeroes / 4 digits an error? rate = int(param) if 1 <= rate <= 15000: self.device.temperature_rate = rate / 100.0 return ""
python
def set_rate(self, param): """ Models "Rate Command" functionality of device. Sets the target rate of temperature change. :param param: Rate of temperature change in C/min, multiplied by 100, as a string. Must be positive. :return: Empty string. """ # TODO: Is not having leading zeroes / 4 digits an error? rate = int(param) if 1 <= rate <= 15000: self.device.temperature_rate = rate / 100.0 return ""
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Models "Rate Command" functionality of device. Sets the target rate of temperature change. :param param: Rate of temperature change in C/min, multiplied by 100, as a string. Must be positive. :return: Empty string.
[ "Models", "Rate", "Command", "functionality", "of", "device", "." ]
931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/devices/linkam_t95/interfaces/stream_interface.py#L87-L101
3,928
DMSC-Instrument-Data/lewis
src/lewis/devices/linkam_t95/interfaces/stream_interface.py
LinkamT95StreamInterface.set_limit
def set_limit(self, param): """ Models "Limit Command" functionality of device. Sets the target temperate to be reached. :param param: Target temperature in C, multiplied by 10, as a string. Can be negative. :return: Empty string. """ # TODO: Is not having leading zeroes / 4 digits an error? limit = int(param) if -2000 <= limit <= 6000: self.device.temperature_limit = limit / 10.0 return ""
python
def set_limit(self, param): """ Models "Limit Command" functionality of device. Sets the target temperate to be reached. :param param: Target temperature in C, multiplied by 10, as a string. Can be negative. :return: Empty string. """ # TODO: Is not having leading zeroes / 4 digits an error? limit = int(param) if -2000 <= limit <= 6000: self.device.temperature_limit = limit / 10.0 return ""
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Models "Limit Command" functionality of device. Sets the target temperate to be reached. :param param: Target temperature in C, multiplied by 10, as a string. Can be negative. :return: Empty string.
[ "Models", "Limit", "Command", "functionality", "of", "device", "." ]
931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/devices/linkam_t95/interfaces/stream_interface.py#L103-L116
3,929
DMSC-Instrument-Data/lewis
src/lewis/devices/linkam_t95/interfaces/stream_interface.py
LinkamT95StreamInterface.pump_command
def pump_command(self, param): """ Models "LNP Pump Commands" functionality of device. Switches between automatic or manual pump mode, and adjusts speed when in manual mode. :param param: 'a0' for auto, 'm0' for manual, [0-N] for speed. :return: """ lookup = [c for c in "0123456789:;<=>?@ABCDEFGHIJKLMN"] if param == "a0": self.device.pump_manual_mode = False elif param == "m0": self.device.pump_manual_mode = True elif param in lookup: self.device.manual_target_speed = lookup.index(param) return ""
python
def pump_command(self, param): """ Models "LNP Pump Commands" functionality of device. Switches between automatic or manual pump mode, and adjusts speed when in manual mode. :param param: 'a0' for auto, 'm0' for manual, [0-N] for speed. :return: """ lookup = [c for c in "0123456789:;<=>?@ABCDEFGHIJKLMN"] if param == "a0": self.device.pump_manual_mode = False elif param == "m0": self.device.pump_manual_mode = True elif param in lookup: self.device.manual_target_speed = lookup.index(param) return ""
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Models "LNP Pump Commands" functionality of device. Switches between automatic or manual pump mode, and adjusts speed when in manual mode. :param param: 'a0' for auto, 'm0' for manual, [0-N] for speed. :return:
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/devices/linkam_t95/interfaces/stream_interface.py#L172-L190
3,930
DMSC-Instrument-Data/lewis
src/lewis/core/statemachine.py
HasContext.set_context
def set_context(self, new_context): """Assigns the new context to the member variable ``_context``.""" self._context = new_context if hasattr(self, '_set_logging_context'): self._set_logging_context(self._context)
python
def set_context(self, new_context): """Assigns the new context to the member variable ``_context``.""" self._context = new_context if hasattr(self, '_set_logging_context'): self._set_logging_context(self._context)
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Assigns the new context to the member variable ``_context``.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/statemachine.py#L56-L61
3,931
DMSC-Instrument-Data/lewis
src/lewis/devices/linkam_t95/devices/device.py
SimulatedLinkamT95._initialize_data
def _initialize_data(self): """ This method is called once on construction. After that, it may be manually called again to reset the device to its default state. After the first call during construction, the class is frozen. This means that attempting to define a new member variable will raise an exception. This is to prevent typos from inadvertently and silently adding new members instead of accessing existing ones. """ self.serial_command_mode = False self.pump_overspeed = False self.start_commanded = False self.stop_commanded = False self.hold_commanded = False # Real device remembers values from last run, we use arbitrary defaults self.temperature_rate = 5.0 # Rate of change of temperature in C/min self.temperature_limit = 0.0 # Target temperature in C self.pump_speed = 0 # Pump speed in arbitrary unit, ranging 0 to 30 self.temperature = 24.0 # Current temperature in C self.pump_manual_mode = False self.manual_target_speed = 0
python
def _initialize_data(self): """ This method is called once on construction. After that, it may be manually called again to reset the device to its default state. After the first call during construction, the class is frozen. This means that attempting to define a new member variable will raise an exception. This is to prevent typos from inadvertently and silently adding new members instead of accessing existing ones. """ self.serial_command_mode = False self.pump_overspeed = False self.start_commanded = False self.stop_commanded = False self.hold_commanded = False # Real device remembers values from last run, we use arbitrary defaults self.temperature_rate = 5.0 # Rate of change of temperature in C/min self.temperature_limit = 0.0 # Target temperature in C self.pump_speed = 0 # Pump speed in arbitrary unit, ranging 0 to 30 self.temperature = 24.0 # Current temperature in C self.pump_manual_mode = False self.manual_target_speed = 0
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This method is called once on construction. After that, it may be manually called again to reset the device to its default state. After the first call during construction, the class is frozen. This means that attempting to define a new member variable will raise an exception. This is to prevent typos from inadvertently and silently adding new members instead of accessing existing ones.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/devices/linkam_t95/devices/device.py#L28-L54
3,932
DMSC-Instrument-Data/lewis
src/lewis/core/logging.py
has_log
def has_log(target): """ This is a decorator to add logging functionality to a class or function. Applying this decorator to a class or function will add two new members: - ``log`` is an instance of ``logging.Logger``. The name of the logger is set to ``lewis.Foo`` for a class named Foo. - ``_set_logging_context`` is a method that modifies the name of the logger when the class is used in a certain context. If ``context`` is a string, that string is directly inserted between ``lewis`` and ``Foo``, so that the logger name would be ``lewis.bar.Foo`` if context was ``'bar'``. The more common case is probably ``context`` being an object of some class, in which case the class name is inserted. If ``context`` is an object of type ``Bar``, the logger name of ``Foo`` would be ``lewis.Bar.Foo``. To provide a more concrete example in terms of Lewis, this is used for the state machine logger in a device. So the logs of the state machine belonging to a certain device appear in the log as originating from ``lewis.DeviceName.StateMachine``, which makes it possible to distinguish between messages from different state machines. Example for how to use logging in a class: .. sourcecode:: Python from lewis.core.logging import has_log @has_log class Foo(Base): def __init__(self): super(Foo, self).__init__() def bar(self, baz): self.log.debug('Called bar with parameter baz=%s', baz) return baz is not None It works similarly for free functions, although the actual logging calls are a bit different: .. sourcecode:: Python from lewis.core.logging import has_log @has_log def foo(bar): foo.log.info('Called with argument bar=%s', bar) return bar The name of the logger is ``lewis.foo``, the context could also be modified by calling ``foo._set_logging_context``. :param target: Target to decorate with logging functionality. """ logger_name = target.__name__ def get_logger_name(context=None): log_names = [root_logger_name, logger_name] if context is not None: log_names.insert(1, context if isinstance(context, string_types) else context.__class__.__name__) return '.'.join(log_names) def _set_logging_context(obj, context): """ Changes the logger name of this class using the supplied context according to the rules described in the documentation of :func:`has_log`. To clear the context of a class logger, supply ``None`` as the argument. :param context: String or object, ``None`` to clear context. """ obj.log.name = get_logger_name(context) target.log = logging.getLogger(get_logger_name()) target._set_logging_context = _set_logging_context return target
python
def has_log(target): """ This is a decorator to add logging functionality to a class or function. Applying this decorator to a class or function will add two new members: - ``log`` is an instance of ``logging.Logger``. The name of the logger is set to ``lewis.Foo`` for a class named Foo. - ``_set_logging_context`` is a method that modifies the name of the logger when the class is used in a certain context. If ``context`` is a string, that string is directly inserted between ``lewis`` and ``Foo``, so that the logger name would be ``lewis.bar.Foo`` if context was ``'bar'``. The more common case is probably ``context`` being an object of some class, in which case the class name is inserted. If ``context`` is an object of type ``Bar``, the logger name of ``Foo`` would be ``lewis.Bar.Foo``. To provide a more concrete example in terms of Lewis, this is used for the state machine logger in a device. So the logs of the state machine belonging to a certain device appear in the log as originating from ``lewis.DeviceName.StateMachine``, which makes it possible to distinguish between messages from different state machines. Example for how to use logging in a class: .. sourcecode:: Python from lewis.core.logging import has_log @has_log class Foo(Base): def __init__(self): super(Foo, self).__init__() def bar(self, baz): self.log.debug('Called bar with parameter baz=%s', baz) return baz is not None It works similarly for free functions, although the actual logging calls are a bit different: .. sourcecode:: Python from lewis.core.logging import has_log @has_log def foo(bar): foo.log.info('Called with argument bar=%s', bar) return bar The name of the logger is ``lewis.foo``, the context could also be modified by calling ``foo._set_logging_context``. :param target: Target to decorate with logging functionality. """ logger_name = target.__name__ def get_logger_name(context=None): log_names = [root_logger_name, logger_name] if context is not None: log_names.insert(1, context if isinstance(context, string_types) else context.__class__.__name__) return '.'.join(log_names) def _set_logging_context(obj, context): """ Changes the logger name of this class using the supplied context according to the rules described in the documentation of :func:`has_log`. To clear the context of a class logger, supply ``None`` as the argument. :param context: String or object, ``None`` to clear context. """ obj.log.name = get_logger_name(context) target.log = logging.getLogger(get_logger_name()) target._set_logging_context = _set_logging_context return target
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This is a decorator to add logging functionality to a class or function. Applying this decorator to a class or function will add two new members: - ``log`` is an instance of ``logging.Logger``. The name of the logger is set to ``lewis.Foo`` for a class named Foo. - ``_set_logging_context`` is a method that modifies the name of the logger when the class is used in a certain context. If ``context`` is a string, that string is directly inserted between ``lewis`` and ``Foo``, so that the logger name would be ``lewis.bar.Foo`` if context was ``'bar'``. The more common case is probably ``context`` being an object of some class, in which case the class name is inserted. If ``context`` is an object of type ``Bar``, the logger name of ``Foo`` would be ``lewis.Bar.Foo``. To provide a more concrete example in terms of Lewis, this is used for the state machine logger in a device. So the logs of the state machine belonging to a certain device appear in the log as originating from ``lewis.DeviceName.StateMachine``, which makes it possible to distinguish between messages from different state machines. Example for how to use logging in a class: .. sourcecode:: Python from lewis.core.logging import has_log @has_log class Foo(Base): def __init__(self): super(Foo, self).__init__() def bar(self, baz): self.log.debug('Called bar with parameter baz=%s', baz) return baz is not None It works similarly for free functions, although the actual logging calls are a bit different: .. sourcecode:: Python from lewis.core.logging import has_log @has_log def foo(bar): foo.log.info('Called with argument bar=%s', bar) return bar The name of the logger is ``lewis.foo``, the context could also be modified by calling ``foo._set_logging_context``. :param target: Target to decorate with logging functionality.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/core/logging.py#L44-L122
3,933
DMSC-Instrument-Data/lewis
src/lewis/scripts/__init__.py
get_usage_text
def get_usage_text(parser, indent=None): """ This small helper function extracts the help information from an ArgumentParser instance and indents the text by the number of spaces supplied in the indent-argument. :param parser: ArgumentParser object. :param indent: Number of spaces to put before each line or None. :return: Formatted help string of the supplied parser. """ usage_text = StringIO() parser.print_help(usage_text) usage_string = usage_text.getvalue() if indent is None: return usage_string return '\n'.join([' ' * indent + line for line in usage_string.split('\n')])
python
def get_usage_text(parser, indent=None): """ This small helper function extracts the help information from an ArgumentParser instance and indents the text by the number of spaces supplied in the indent-argument. :param parser: ArgumentParser object. :param indent: Number of spaces to put before each line or None. :return: Formatted help string of the supplied parser. """ usage_text = StringIO() parser.print_help(usage_text) usage_string = usage_text.getvalue() if indent is None: return usage_string return '\n'.join([' ' * indent + line for line in usage_string.split('\n')])
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This small helper function extracts the help information from an ArgumentParser instance and indents the text by the number of spaces supplied in the indent-argument. :param parser: ArgumentParser object. :param indent: Number of spaces to put before each line or None. :return: Formatted help string of the supplied parser.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/scripts/__init__.py#L23-L40
3,934
DMSC-Instrument-Data/lewis
src/lewis/examples/example_motor/__init__.py
SimulatedExampleMotor.stop
def stop(self): """Stops the motor and returns the new target and position, which are equal""" self._target = self.position self.log.info('Stopping movement after user request.') return self.target, self.position
python
def stop(self): """Stops the motor and returns the new target and position, which are equal""" self._target = self.position self.log.info('Stopping movement after user request.') return self.target, self.position
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Stops the motor and returns the new target and position, which are equal
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/examples/example_motor/__init__.py#L75-L82
3,935
DMSC-Instrument-Data/lewis
src/lewis/scripts/run.py
run_simulation
def run_simulation(argument_list=None): # noqa: C901 """ This is effectively the main function of a typical simulation run. Arguments passed in are parsed and used to construct and run the simulation. This function only exits when the program has completed or is interrupted. :param argument_list: Argument list to pass to the argument parser declared in this module. """ try: arguments = parser.parse_args(argument_list or sys.argv[1:]) if arguments.version: print(__version__) return if arguments.relaxed_versions: print('Unknown option --relaxed-versions. Did you mean --ignore-versions?') return loglevel = 'debug' if arguments.verify else arguments.output_level if loglevel != 'none': logging.basicConfig( level=getattr(logging, loglevel.upper()), format=default_log_format) if arguments.add_path is not None: additional_path = os.path.abspath(arguments.add_path) logging.getLogger().debug('Extending path with: %s', additional_path) sys.path.append(additional_path) strict_versions = use_strict_versions(arguments.strict_versions, arguments.ignore_versions) simulation_factory = SimulationFactory(arguments.device_package, strict_versions) if not arguments.device: devices = ['Please specify a device to simulate. The following devices are available:'] for dev in simulation_factory.devices: devices.append(' ' + dev) print('\n'.join(devices)) return if arguments.list_protocols: print('\n'.join(simulation_factory.get_protocols(arguments.device))) return protocols = parse_adapter_options(arguments.adapter_options) \ if not arguments.no_interface else {} simulation = simulation_factory.create( arguments.device, arguments.setup, protocols, arguments.rpc_host) if arguments.show_interface: print(simulation._adapters.documentation()) return if arguments.list_adapter_options: configurations = simulation._adapters.configuration() for protocol, options in configurations.items(): print('{}:'.format(protocol)) for opt, val in options.items(): print(' {} = {}'.format(opt, val)) return simulation.cycle_delay = arguments.cycle_delay simulation.speed = arguments.speed if not arguments.verify: try: simulation.start() except KeyboardInterrupt: print('\nInterrupt received; shutting down. Goodbye, cruel world!') simulation.log.critical('Simulation aborted by user interaction') finally: simulation.stop() except LewisException as e: print('\n'.join(('An error occurred:', str(e))))
python
def run_simulation(argument_list=None): # noqa: C901 """ This is effectively the main function of a typical simulation run. Arguments passed in are parsed and used to construct and run the simulation. This function only exits when the program has completed or is interrupted. :param argument_list: Argument list to pass to the argument parser declared in this module. """ try: arguments = parser.parse_args(argument_list or sys.argv[1:]) if arguments.version: print(__version__) return if arguments.relaxed_versions: print('Unknown option --relaxed-versions. Did you mean --ignore-versions?') return loglevel = 'debug' if arguments.verify else arguments.output_level if loglevel != 'none': logging.basicConfig( level=getattr(logging, loglevel.upper()), format=default_log_format) if arguments.add_path is not None: additional_path = os.path.abspath(arguments.add_path) logging.getLogger().debug('Extending path with: %s', additional_path) sys.path.append(additional_path) strict_versions = use_strict_versions(arguments.strict_versions, arguments.ignore_versions) simulation_factory = SimulationFactory(arguments.device_package, strict_versions) if not arguments.device: devices = ['Please specify a device to simulate. The following devices are available:'] for dev in simulation_factory.devices: devices.append(' ' + dev) print('\n'.join(devices)) return if arguments.list_protocols: print('\n'.join(simulation_factory.get_protocols(arguments.device))) return protocols = parse_adapter_options(arguments.adapter_options) \ if not arguments.no_interface else {} simulation = simulation_factory.create( arguments.device, arguments.setup, protocols, arguments.rpc_host) if arguments.show_interface: print(simulation._adapters.documentation()) return if arguments.list_adapter_options: configurations = simulation._adapters.configuration() for protocol, options in configurations.items(): print('{}:'.format(protocol)) for opt, val in options.items(): print(' {} = {}'.format(opt, val)) return simulation.cycle_delay = arguments.cycle_delay simulation.speed = arguments.speed if not arguments.verify: try: simulation.start() except KeyboardInterrupt: print('\nInterrupt received; shutting down. Goodbye, cruel world!') simulation.log.critical('Simulation aborted by user interaction') finally: simulation.stop() except LewisException as e: print('\n'.join(('An error occurred:', str(e))))
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This is effectively the main function of a typical simulation run. Arguments passed in are parsed and used to construct and run the simulation. This function only exits when the program has completed or is interrupted. :param argument_list: Argument list to pass to the argument parser declared in this module.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/scripts/run.py#L172-L253
3,936
DMSC-Instrument-Data/lewis
src/lewis/adapters/stream.py
Func.map_arguments
def map_arguments(self, arguments): """ Returns the mapped function arguments. If no mapping functions are defined, the arguments are returned as they were supplied. :param arguments: List of arguments for bound function as strings. :return: Mapped arguments. """ if self.argument_mappings is None: return arguments return [f(a) for f, a in zip(self.argument_mappings, arguments)]
python
def map_arguments(self, arguments): """ Returns the mapped function arguments. If no mapping functions are defined, the arguments are returned as they were supplied. :param arguments: List of arguments for bound function as strings. :return: Mapped arguments. """ if self.argument_mappings is None: return arguments return [f(a) for f, a in zip(self.argument_mappings, arguments)]
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Returns the mapped function arguments. If no mapping functions are defined, the arguments are returned as they were supplied. :param arguments: List of arguments for bound function as strings. :return: Mapped arguments.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/stream.py#L368-L379
3,937
DMSC-Instrument-Data/lewis
src/lewis/adapters/stream.py
Func.map_return_value
def map_return_value(self, return_value): """ Returns the mapped return_value of a processed request. If no return_mapping has been defined, the value is returned as is. If return_mapping is a static value, that value is returned, ignoring return_value completely. :param return_value: Value to map. :return: Mapped return value. """ if callable(self.return_mapping): return self.return_mapping(return_value) if self.return_mapping is not None: return self.return_mapping return return_value
python
def map_return_value(self, return_value): """ Returns the mapped return_value of a processed request. If no return_mapping has been defined, the value is returned as is. If return_mapping is a static value, that value is returned, ignoring return_value completely. :param return_value: Value to map. :return: Mapped return value. """ if callable(self.return_mapping): return self.return_mapping(return_value) if self.return_mapping is not None: return self.return_mapping return return_value
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Returns the mapped return_value of a processed request. If no return_mapping has been defined, the value is returned as is. If return_mapping is a static value, that value is returned, ignoring return_value completely. :param return_value: Value to map. :return: Mapped return value.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/stream.py#L381-L396
3,938
DMSC-Instrument-Data/lewis
src/lewis/adapters/stream.py
StreamAdapter.start_server
def start_server(self): """ Starts the TCP stream server, binding to the configured host and port. Host and port are configured via the command line arguments. .. note:: The server does not process requests unless :meth:`handle` is called in regular intervals. """ if self._server is None: if self._options.telnet_mode: self.interface.in_terminator = '\r\n' self.interface.out_terminator = '\r\n' self._server = StreamServer(self._options.bind_address, self._options.port, self.interface, self.device_lock)
python
def start_server(self): """ Starts the TCP stream server, binding to the configured host and port. Host and port are configured via the command line arguments. .. note:: The server does not process requests unless :meth:`handle` is called in regular intervals. """ if self._server is None: if self._options.telnet_mode: self.interface.in_terminator = '\r\n' self.interface.out_terminator = '\r\n' self._server = StreamServer(self._options.bind_address, self._options.port, self.interface, self.device_lock)
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Starts the TCP stream server, binding to the configured host and port. Host and port are configured via the command line arguments. .. note:: The server does not process requests unless :meth:`handle` is called in regular intervals.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/stream.py#L632-L647
3,939
DMSC-Instrument-Data/lewis
src/lewis/adapters/stream.py
StreamAdapter.handle
def handle(self, cycle_delay=0.1): """ Spend approximately ``cycle_delay`` seconds to process requests to the server. :param cycle_delay: S """ asyncore.loop(cycle_delay, count=1) self._server.process(int(cycle_delay * 1000))
python
def handle(self, cycle_delay=0.1): """ Spend approximately ``cycle_delay`` seconds to process requests to the server. :param cycle_delay: S """ asyncore.loop(cycle_delay, count=1) self._server.process(int(cycle_delay * 1000))
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Spend approximately ``cycle_delay`` seconds to process requests to the server. :param cycle_delay: S
[ "Spend", "approximately", "cycle_delay", "seconds", "to", "process", "requests", "to", "the", "server", "." ]
931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/stream.py#L658-L665
3,940
DMSC-Instrument-Data/lewis
src/lewis/devices/__init__.py
StateMachineDevice._override_data
def _override_data(self, overrides): """ This method overrides data members of the class, but does not allow for adding new members. :param overrides: Dict with data overrides. """ if overrides is not None: for name, val in overrides.items(): self.log.debug('Trying to override initial data (%s=%s)', name, val) if name not in dir(self): raise AttributeError( 'Can not override non-existing attribute' '\'{}\' of class \'{}\'.'.format(name, type(self).__name__)) setattr(self, name, val)
python
def _override_data(self, overrides): """ This method overrides data members of the class, but does not allow for adding new members. :param overrides: Dict with data overrides. """ if overrides is not None: for name, val in overrides.items(): self.log.debug('Trying to override initial data (%s=%s)', name, val) if name not in dir(self): raise AttributeError( 'Can not override non-existing attribute' '\'{}\' of class \'{}\'.'.format(name, type(self).__name__)) setattr(self, name, val)
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This method overrides data members of the class, but does not allow for adding new members. :param overrides: Dict with data overrides.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/devices/__init__.py#L177-L191
3,941
DMSC-Instrument-Data/lewis
src/lewis/adapters/modbus.py
ModbusDataBank.get
def get(self, addr, count): """ Read list of ``count`` values at ``addr`` memory location in DataBank. :param addr: Address to read from :param count: Number of entries to retrieve :return: list of entry values :except IndexError: Raised if address range falls outside valid range """ addr -= self._start_addr data = self._data[addr:addr + count] if len(data) != count: addr += self._start_addr raise IndexError("Invalid address range [{:#06x} - {:#06x}]" .format(addr, addr + count)) return data
python
def get(self, addr, count): """ Read list of ``count`` values at ``addr`` memory location in DataBank. :param addr: Address to read from :param count: Number of entries to retrieve :return: list of entry values :except IndexError: Raised if address range falls outside valid range """ addr -= self._start_addr data = self._data[addr:addr + count] if len(data) != count: addr += self._start_addr raise IndexError("Invalid address range [{:#06x} - {:#06x}]" .format(addr, addr + count)) return data
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Read list of ``count`` values at ``addr`` memory location in DataBank. :param addr: Address to read from :param count: Number of entries to retrieve :return: list of entry values :except IndexError: Raised if address range falls outside valid range
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/modbus.py#L64-L79
3,942
DMSC-Instrument-Data/lewis
src/lewis/adapters/modbus.py
ModbusDataBank.set
def set(self, addr, values): """ Write list ``values`` to ``addr`` memory location in DataBank. :param addr: Address to write to :param values: list of values to write :except IndexError: Raised if address range falls outside valid range """ addr -= self._start_addr end = addr + len(values) if not 0 <= addr <= end <= len(self._data): addr += self._start_addr raise IndexError("Invalid address range [{:#06x} - {:#06x}]" .format(addr, addr + len(values))) self._data[addr:end] = values
python
def set(self, addr, values): """ Write list ``values`` to ``addr`` memory location in DataBank. :param addr: Address to write to :param values: list of values to write :except IndexError: Raised if address range falls outside valid range """ addr -= self._start_addr end = addr + len(values) if not 0 <= addr <= end <= len(self._data): addr += self._start_addr raise IndexError("Invalid address range [{:#06x} - {:#06x}]" .format(addr, addr + len(values))) self._data[addr:end] = values
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Write list ``values`` to ``addr`` memory location in DataBank. :param addr: Address to write to :param values: list of values to write :except IndexError: Raised if address range falls outside valid range
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/modbus.py#L81-L95
3,943
DMSC-Instrument-Data/lewis
src/lewis/adapters/modbus.py
ModbusTCPFrame.from_bytearray
def from_bytearray(self, stream): """ Constructs this frame from input data stream, consuming as many bytes as necessary from the beginning of the stream. If stream does not contain enough data to construct a complete modbus frame, an EOFError is raised and no data is consumed. :param stream: bytearray to consume data from to construct this frame. :except EOFError: Not enough data for complete frame; no data consumed. """ fmt = '>HHHBB' size_header = struct.calcsize(fmt) if len(stream) < size_header: raise EOFError ( self.transaction_id, self.protocol_id, self.length, self.unit_id, self.fcode ) = struct.unpack(fmt, bytes(stream[:size_header])) size_total = size_header + self.length - 2 if len(stream) < size_total: raise EOFError self.data = stream[size_header:size_total] del stream[:size_total]
python
def from_bytearray(self, stream): """ Constructs this frame from input data stream, consuming as many bytes as necessary from the beginning of the stream. If stream does not contain enough data to construct a complete modbus frame, an EOFError is raised and no data is consumed. :param stream: bytearray to consume data from to construct this frame. :except EOFError: Not enough data for complete frame; no data consumed. """ fmt = '>HHHBB' size_header = struct.calcsize(fmt) if len(stream) < size_header: raise EOFError ( self.transaction_id, self.protocol_id, self.length, self.unit_id, self.fcode ) = struct.unpack(fmt, bytes(stream[:size_header])) size_total = size_header + self.length - 2 if len(stream) < size_total: raise EOFError self.data = stream[size_header:size_total] del stream[:size_total]
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Constructs this frame from input data stream, consuming as many bytes as necessary from the beginning of the stream. If stream does not contain enough data to construct a complete modbus frame, an EOFError is raised and no data is consumed. :param stream: bytearray to consume data from to construct this frame. :except EOFError: Not enough data for complete frame; no data consumed.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/modbus.py#L171-L200
3,944
DMSC-Instrument-Data/lewis
src/lewis/adapters/modbus.py
ModbusTCPFrame.to_bytearray
def to_bytearray(self): """ Convert this frame into its bytearray representation. :return: bytearray representation of this frame. """ header = bytearray(struct.pack( '>HHHBB', self.transaction_id, self.protocol_id, self.length, self.unit_id, self.fcode )) return header + self.data
python
def to_bytearray(self): """ Convert this frame into its bytearray representation. :return: bytearray representation of this frame. """ header = bytearray(struct.pack( '>HHHBB', self.transaction_id, self.protocol_id, self.length, self.unit_id, self.fcode )) return header + self.data
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Convert this frame into its bytearray representation. :return: bytearray representation of this frame.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/modbus.py#L202-L216
3,945
DMSC-Instrument-Data/lewis
src/lewis/adapters/modbus.py
ModbusTCPFrame.is_valid
def is_valid(self): """ Check integrity and validity of this frame. :return: bool True if this frame is structurally valid. """ conditions = [ self.protocol_id == 0, # Modbus always uses protocol 0 2 <= self.length <= 260, # Absolute length limits len(self.data) == self.length - 2, # Total length matches data length ] return all(conditions)
python
def is_valid(self): """ Check integrity and validity of this frame. :return: bool True if this frame is structurally valid. """ conditions = [ self.protocol_id == 0, # Modbus always uses protocol 0 2 <= self.length <= 260, # Absolute length limits len(self.data) == self.length - 2, # Total length matches data length ] return all(conditions)
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Check integrity and validity of this frame. :return: bool True if this frame is structurally valid.
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/modbus.py#L218-L229
3,946
DMSC-Instrument-Data/lewis
src/lewis/adapters/modbus.py
ModbusTCPFrame.create_exception
def create_exception(self, code): """ Create an exception frame based on this frame. :param code: Modbus exception code to use for this exception :return: ModbusTCPFrame instance that represents an exception """ frame = deepcopy(self) frame.length = 3 frame.fcode += 0x80 frame.data = bytearray(chr(code)) return frame
python
def create_exception(self, code): """ Create an exception frame based on this frame. :param code: Modbus exception code to use for this exception :return: ModbusTCPFrame instance that represents an exception """ frame = deepcopy(self) frame.length = 3 frame.fcode += 0x80 frame.data = bytearray(chr(code)) return frame
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Create an exception frame based on this frame. :param code: Modbus exception code to use for this exception :return: ModbusTCPFrame instance that represents an exception
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931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/modbus.py#L231-L242
3,947
DMSC-Instrument-Data/lewis
src/lewis/adapters/modbus.py
ModbusTCPFrame.create_response
def create_response(self, data=None): """ Create a response frame based on this frame. :param data: Data section of response as bytearray. If None, request data section is kept. :return: ModbusTCPFrame instance that represents a response """ frame = deepcopy(self) if data is not None: frame.data = data frame.length = 2 + len(frame.data) return frame
python
def create_response(self, data=None): """ Create a response frame based on this frame. :param data: Data section of response as bytearray. If None, request data section is kept. :return: ModbusTCPFrame instance that represents a response """ frame = deepcopy(self) if data is not None: frame.data = data frame.length = 2 + len(frame.data) return frame
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Create a response frame based on this frame. :param data: Data section of response as bytearray. If None, request data section is kept. :return: ModbusTCPFrame instance that represents a response
[ "Create", "a", "response", "frame", "based", "on", "this", "frame", "." ]
931d96b8c761550a6a58f6e61e202690db04233a
https://github.com/DMSC-Instrument-Data/lewis/blob/931d96b8c761550a6a58f6e61e202690db04233a/src/lewis/adapters/modbus.py#L244-L255
3,948
simpleai-team/simpleai
simpleai/search/local.py
_all_expander
def _all_expander(fringe, iteration, viewer): ''' Expander that expands all nodes on the fringe. ''' expanded_neighbors = [node.expand(local_search=True) for node in fringe] if viewer: viewer.event('expanded', list(fringe), expanded_neighbors) list(map(fringe.extend, expanded_neighbors))
python
def _all_expander(fringe, iteration, viewer): ''' Expander that expands all nodes on the fringe. ''' expanded_neighbors = [node.expand(local_search=True) for node in fringe] if viewer: viewer.event('expanded', list(fringe), expanded_neighbors) list(map(fringe.extend, expanded_neighbors))
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Expander that expands all nodes on the fringe.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L8-L18
3,949
simpleai-team/simpleai
simpleai/search/local.py
beam
def beam(problem, beam_size=100, iterations_limit=0, viewer=None): ''' Beam search. beam_size is the size of the beam. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.value, and SearchProblem.generate_random_state. ''' return _local_search(problem, _all_expander, iterations_limit=iterations_limit, fringe_size=beam_size, random_initial_states=True, stop_when_no_better=iterations_limit==0, viewer=viewer)
python
def beam(problem, beam_size=100, iterations_limit=0, viewer=None): ''' Beam search. beam_size is the size of the beam. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.value, and SearchProblem.generate_random_state. ''' return _local_search(problem, _all_expander, iterations_limit=iterations_limit, fringe_size=beam_size, random_initial_states=True, stop_when_no_better=iterations_limit==0, viewer=viewer)
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Beam search. beam_size is the size of the beam. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.value, and SearchProblem.generate_random_state.
[ "Beam", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L21-L38
3,950
simpleai-team/simpleai
simpleai/search/local.py
_first_expander
def _first_expander(fringe, iteration, viewer): ''' Expander that expands only the first node on the fringe. ''' current = fringe[0] neighbors = current.expand(local_search=True) if viewer: viewer.event('expanded', [current], [neighbors]) fringe.extend(neighbors)
python
def _first_expander(fringe, iteration, viewer): ''' Expander that expands only the first node on the fringe. ''' current = fringe[0] neighbors = current.expand(local_search=True) if viewer: viewer.event('expanded', [current], [neighbors]) fringe.extend(neighbors)
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Expander that expands only the first node on the fringe.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L41-L51
3,951
simpleai-team/simpleai
simpleai/search/local.py
beam_best_first
def beam_best_first(problem, beam_size=100, iterations_limit=0, viewer=None): ''' Beam search best first. beam_size is the size of the beam. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value. ''' return _local_search(problem, _first_expander, iterations_limit=iterations_limit, fringe_size=beam_size, random_initial_states=True, stop_when_no_better=iterations_limit==0, viewer=viewer)
python
def beam_best_first(problem, beam_size=100, iterations_limit=0, viewer=None): ''' Beam search best first. beam_size is the size of the beam. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value. ''' return _local_search(problem, _first_expander, iterations_limit=iterations_limit, fringe_size=beam_size, random_initial_states=True, stop_when_no_better=iterations_limit==0, viewer=viewer)
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Beam search best first. beam_size is the size of the beam. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value.
[ "Beam", "search", "best", "first", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L55-L72
3,952
simpleai-team/simpleai
simpleai/search/local.py
hill_climbing
def hill_climbing(problem, iterations_limit=0, viewer=None): ''' Hill climbing search. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value. ''' return _local_search(problem, _first_expander, iterations_limit=iterations_limit, fringe_size=1, stop_when_no_better=True, viewer=viewer)
python
def hill_climbing(problem, iterations_limit=0, viewer=None): ''' Hill climbing search. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value. ''' return _local_search(problem, _first_expander, iterations_limit=iterations_limit, fringe_size=1, stop_when_no_better=True, viewer=viewer)
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Hill climbing search. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value.
[ "Hill", "climbing", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L75-L90
3,953
simpleai-team/simpleai
simpleai/search/local.py
hill_climbing_stochastic
def hill_climbing_stochastic(problem, iterations_limit=0, viewer=None): ''' Stochastic hill climbing. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value. ''' return _local_search(problem, _random_best_expander, iterations_limit=iterations_limit, fringe_size=1, stop_when_no_better=iterations_limit==0, viewer=viewer)
python
def hill_climbing_stochastic(problem, iterations_limit=0, viewer=None): ''' Stochastic hill climbing. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value. ''' return _local_search(problem, _random_best_expander, iterations_limit=iterations_limit, fringe_size=1, stop_when_no_better=iterations_limit==0, viewer=viewer)
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Stochastic hill climbing. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value.
[ "Stochastic", "hill", "climbing", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L112-L127
3,954
simpleai-team/simpleai
simpleai/search/local.py
hill_climbing_random_restarts
def hill_climbing_random_restarts(problem, restarts_limit, iterations_limit=0, viewer=None): ''' Hill climbing with random restarts. restarts_limit specifies the number of times hill_climbing will be runned. If iterations_limit is specified, each hill_climbing will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.value, and SearchProblem.generate_random_state. ''' restarts = 0 best = None while restarts < restarts_limit: new = _local_search(problem, _first_expander, iterations_limit=iterations_limit, fringe_size=1, random_initial_states=True, stop_when_no_better=True, viewer=viewer) if not best or best.value < new.value: best = new restarts += 1 if viewer: viewer.event('no_more_runs', best, 'returned after %i runs' % restarts_limit) return best
python
def hill_climbing_random_restarts(problem, restarts_limit, iterations_limit=0, viewer=None): ''' Hill climbing with random restarts. restarts_limit specifies the number of times hill_climbing will be runned. If iterations_limit is specified, each hill_climbing will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.value, and SearchProblem.generate_random_state. ''' restarts = 0 best = None while restarts < restarts_limit: new = _local_search(problem, _first_expander, iterations_limit=iterations_limit, fringe_size=1, random_initial_states=True, stop_when_no_better=True, viewer=viewer) if not best or best.value < new.value: best = new restarts += 1 if viewer: viewer.event('no_more_runs', best, 'returned after %i runs' % restarts_limit) return best
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Hill climbing with random restarts. restarts_limit specifies the number of times hill_climbing will be runned. If iterations_limit is specified, each hill_climbing will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.value, and SearchProblem.generate_random_state.
[ "Hill", "climbing", "with", "random", "restarts", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L130-L161
3,955
simpleai-team/simpleai
simpleai/search/local.py
_exp_schedule
def _exp_schedule(iteration, k=20, lam=0.005, limit=100): ''' Possible scheduler for simulated_annealing, based on the aima example. ''' return k * math.exp(-lam * iteration)
python
def _exp_schedule(iteration, k=20, lam=0.005, limit=100): ''' Possible scheduler for simulated_annealing, based on the aima example. ''' return k * math.exp(-lam * iteration)
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Possible scheduler for simulated_annealing, based on the aima example.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L165-L169
3,956
simpleai-team/simpleai
simpleai/search/local.py
simulated_annealing
def simulated_annealing(problem, schedule=_exp_schedule, iterations_limit=0, viewer=None): ''' Simulated annealing. schedule is the scheduling function that decides the chance to choose worst nodes depending on the time. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value. ''' return _local_search(problem, _create_simulated_annealing_expander(schedule), iterations_limit=iterations_limit, fringe_size=1, stop_when_no_better=iterations_limit==0, viewer=viewer)
python
def simulated_annealing(problem, schedule=_exp_schedule, iterations_limit=0, viewer=None): ''' Simulated annealing. schedule is the scheduling function that decides the chance to choose worst nodes depending on the time. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value. ''' return _local_search(problem, _create_simulated_annealing_expander(schedule), iterations_limit=iterations_limit, fringe_size=1, stop_when_no_better=iterations_limit==0, viewer=viewer)
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Simulated annealing. schedule is the scheduling function that decides the chance to choose worst nodes depending on the time. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.value.
[ "Simulated", "annealing", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L198-L215
3,957
simpleai-team/simpleai
simpleai/search/local.py
_create_genetic_expander
def _create_genetic_expander(problem, mutation_chance): ''' Creates an expander that expands the bests nodes of the population, crossing over them. ''' def _expander(fringe, iteration, viewer): fitness = [x.value for x in fringe] sampler = InverseTransformSampler(fitness, fringe) new_generation = [] expanded_nodes = [] expanded_neighbors = [] for _ in fringe: node1 = sampler.sample() node2 = sampler.sample() child = problem.crossover(node1.state, node2.state) action = 'crossover' if random.random() < mutation_chance: # Noooouuu! she is... he is... *IT* is a mutant! child = problem.mutate(child) action += '+mutation' child_node = SearchNodeValueOrdered(state=child, problem=problem, action=action) new_generation.append(child_node) expanded_nodes.append(node1) expanded_neighbors.append([child_node]) expanded_nodes.append(node2) expanded_neighbors.append([child_node]) if viewer: viewer.event('expanded', expanded_nodes, expanded_neighbors) fringe.clear() for node in new_generation: fringe.append(node) return _expander
python
def _create_genetic_expander(problem, mutation_chance): ''' Creates an expander that expands the bests nodes of the population, crossing over them. ''' def _expander(fringe, iteration, viewer): fitness = [x.value for x in fringe] sampler = InverseTransformSampler(fitness, fringe) new_generation = [] expanded_nodes = [] expanded_neighbors = [] for _ in fringe: node1 = sampler.sample() node2 = sampler.sample() child = problem.crossover(node1.state, node2.state) action = 'crossover' if random.random() < mutation_chance: # Noooouuu! she is... he is... *IT* is a mutant! child = problem.mutate(child) action += '+mutation' child_node = SearchNodeValueOrdered(state=child, problem=problem, action=action) new_generation.append(child_node) expanded_nodes.append(node1) expanded_neighbors.append([child_node]) expanded_nodes.append(node2) expanded_neighbors.append([child_node]) if viewer: viewer.event('expanded', expanded_nodes, expanded_neighbors) fringe.clear() for node in new_generation: fringe.append(node) return _expander
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Creates an expander that expands the bests nodes of the population, crossing over them.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L218-L256
3,958
simpleai-team/simpleai
simpleai/search/local.py
genetic
def genetic(problem, population_size=100, mutation_chance=0.1, iterations_limit=0, viewer=None): ''' Genetic search. population_size specifies the size of the population (ORLY). mutation_chance specifies the probability of a mutation on a child, varying from 0 to 1. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.generate_random_state, SearchProblem.crossover, SearchProblem.mutate and SearchProblem.value. ''' return _local_search(problem, _create_genetic_expander(problem, mutation_chance), iterations_limit=iterations_limit, fringe_size=population_size, random_initial_states=True, stop_when_no_better=iterations_limit==0, viewer=viewer)
python
def genetic(problem, population_size=100, mutation_chance=0.1, iterations_limit=0, viewer=None): ''' Genetic search. population_size specifies the size of the population (ORLY). mutation_chance specifies the probability of a mutation on a child, varying from 0 to 1. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.generate_random_state, SearchProblem.crossover, SearchProblem.mutate and SearchProblem.value. ''' return _local_search(problem, _create_genetic_expander(problem, mutation_chance), iterations_limit=iterations_limit, fringe_size=population_size, random_initial_states=True, stop_when_no_better=iterations_limit==0, viewer=viewer)
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Genetic search. population_size specifies the size of the population (ORLY). mutation_chance specifies the probability of a mutation on a child, varying from 0 to 1. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until it can't find a better node than the current one. Requires: SearchProblem.generate_random_state, SearchProblem.crossover, SearchProblem.mutate and SearchProblem.value.
[ "Genetic", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L259-L279
3,959
simpleai-team/simpleai
simpleai/search/local.py
_local_search
def _local_search(problem, fringe_expander, iterations_limit=0, fringe_size=1, random_initial_states=False, stop_when_no_better=True, viewer=None): ''' Basic algorithm for all local search algorithms. ''' if viewer: viewer.event('started') fringe = BoundedPriorityQueue(fringe_size) if random_initial_states: for _ in range(fringe_size): s = problem.generate_random_state() fringe.append(SearchNodeValueOrdered(state=s, problem=problem)) else: fringe.append(SearchNodeValueOrdered(state=problem.initial_state, problem=problem)) finish_reason = '' iteration = 0 run = True best = None while run: if viewer: viewer.event('new_iteration', list(fringe)) old_best = fringe[0] fringe_expander(fringe, iteration, viewer) best = fringe[0] iteration += 1 if iterations_limit and iteration >= iterations_limit: run = False finish_reason = 'reaching iteration limit' elif old_best.value >= best.value and stop_when_no_better: run = False finish_reason = 'not being able to improve solution' if viewer: viewer.event('finished', fringe, best, 'returned after %s' % finish_reason) return best
python
def _local_search(problem, fringe_expander, iterations_limit=0, fringe_size=1, random_initial_states=False, stop_when_no_better=True, viewer=None): ''' Basic algorithm for all local search algorithms. ''' if viewer: viewer.event('started') fringe = BoundedPriorityQueue(fringe_size) if random_initial_states: for _ in range(fringe_size): s = problem.generate_random_state() fringe.append(SearchNodeValueOrdered(state=s, problem=problem)) else: fringe.append(SearchNodeValueOrdered(state=problem.initial_state, problem=problem)) finish_reason = '' iteration = 0 run = True best = None while run: if viewer: viewer.event('new_iteration', list(fringe)) old_best = fringe[0] fringe_expander(fringe, iteration, viewer) best = fringe[0] iteration += 1 if iterations_limit and iteration >= iterations_limit: run = False finish_reason = 'reaching iteration limit' elif old_best.value >= best.value and stop_when_no_better: run = False finish_reason = 'not being able to improve solution' if viewer: viewer.event('finished', fringe, best, 'returned after %s' % finish_reason) return best
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Basic algorithm for all local search algorithms.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/local.py#L282-L325
3,960
simpleai-team/simpleai
samples/search/eight_puzzle.py
EigthPuzzleProblem.actions
def actions(self, state): '''Returns a list of the pieces we can move to the empty space.''' rows = string_to_list(state) row_e, col_e = find_location(rows, 'e') actions = [] if row_e > 0: actions.append(rows[row_e - 1][col_e]) if row_e < 2: actions.append(rows[row_e + 1][col_e]) if col_e > 0: actions.append(rows[row_e][col_e - 1]) if col_e < 2: actions.append(rows[row_e][col_e + 1]) return actions
python
def actions(self, state): '''Returns a list of the pieces we can move to the empty space.''' rows = string_to_list(state) row_e, col_e = find_location(rows, 'e') actions = [] if row_e > 0: actions.append(rows[row_e - 1][col_e]) if row_e < 2: actions.append(rows[row_e + 1][col_e]) if col_e > 0: actions.append(rows[row_e][col_e - 1]) if col_e < 2: actions.append(rows[row_e][col_e + 1]) return actions
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Returns a list of the pieces we can move to the empty space.
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2836befa7e970013f62e0ee75562652aacac6f65
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simpleai-team/simpleai
simpleai/machine_learning/models.py
is_attribute
def is_attribute(method, name=None): """ Decorator for methods that are attributes. """ if name is None: name = method.__name__ method.is_attribute = True method.name = name return method
python
def is_attribute(method, name=None): """ Decorator for methods that are attributes. """ if name is None: name = method.__name__ method.is_attribute = True method.name = name return method
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Decorator for methods that are attributes.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/machine_learning/models.py#L230-L238
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simpleai-team/simpleai
simpleai/machine_learning/models.py
Classifier.load
def load(cls, filepath): """ Loads a pickled version of the classifier saved in `filepath` """ with open(filepath, "rb") as filehandler: classifier = pickle.load(filehandler) if not isinstance(classifier, Classifier): raise ValueError("Pickled object is not a Classifier") return classifier
python
def load(cls, filepath): """ Loads a pickled version of the classifier saved in `filepath` """ with open(filepath, "rb") as filehandler: classifier = pickle.load(filehandler) if not isinstance(classifier, Classifier): raise ValueError("Pickled object is not a Classifier") return classifier
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Loads a pickled version of the classifier saved in `filepath`
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/machine_learning/models.py#L76-L86
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simpleai-team/simpleai
simpleai/machine_learning/classifiers.py
tree_to_str
def tree_to_str(root): """ Returns a string representation of a decision tree with root node `root`. """ xs = [] for value, node, depth in iter_tree(root): template = "{indent}" if node is not root: template += "case={value}\t" if node.attribute is None: template += "result={result} -- P={prob:.2}" else: template += "split by {split}:\t" +\ "(partial result={result} -- P={prob:.2})" line = template.format(indent=" " * depth, value=value, result=node.result[0], prob=node.result[1], split=str(node.attribute)) xs.append(line) return "\n".join(xs)
python
def tree_to_str(root): """ Returns a string representation of a decision tree with root node `root`. """ xs = [] for value, node, depth in iter_tree(root): template = "{indent}" if node is not root: template += "case={value}\t" if node.attribute is None: template += "result={result} -- P={prob:.2}" else: template += "split by {split}:\t" +\ "(partial result={result} -- P={prob:.2})" line = template.format(indent=" " * depth, value=value, result=node.result[0], prob=node.result[1], split=str(node.attribute)) xs.append(line) return "\n".join(xs)
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Returns a string representation of a decision tree with root node `root`.
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2836befa7e970013f62e0ee75562652aacac6f65
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3,964
simpleai-team/simpleai
simpleai/machine_learning/classifiers.py
KNearestNeighbors.save
def save(self, filepath): """ Saves the classifier to `filepath`. Because this classifier needs to save the dataset, it must be something that can be pickled and not something like an iterator. """ if not filepath or not isinstance(filepath, str): raise ValueError("Invalid filepath") with open(filepath, "wb") as filehandler: pickle.dump(self, filehandler)
python
def save(self, filepath): """ Saves the classifier to `filepath`. Because this classifier needs to save the dataset, it must be something that can be pickled and not something like an iterator. """ if not filepath or not isinstance(filepath, str): raise ValueError("Invalid filepath") with open(filepath, "wb") as filehandler: pickle.dump(self, filehandler)
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Saves the classifier to `filepath`. Because this classifier needs to save the dataset, it must be something that can be pickled and not something like an iterator.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/machine_learning/classifiers.py#L180-L192
3,965
simpleai-team/simpleai
simpleai/machine_learning/classifiers.py
DecisionTreeLearner_Queued._max_gain_split
def _max_gain_split(self, examples): """ Returns an OnlineInformationGain of the attribute with max gain based on `examples`. """ gains = self._new_set_of_gain_counters() for example in examples: for gain in gains: gain.add(example) winner = max(gains, key=lambda gain: gain.get_gain()) if not winner.get_target_class_counts(): raise ValueError("Dataset is empty") return winner
python
def _max_gain_split(self, examples): """ Returns an OnlineInformationGain of the attribute with max gain based on `examples`. """ gains = self._new_set_of_gain_counters() for example in examples: for gain in gains: gain.add(example) winner = max(gains, key=lambda gain: gain.get_gain()) if not winner.get_target_class_counts(): raise ValueError("Dataset is empty") return winner
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Returns an OnlineInformationGain of the attribute with max gain based on `examples`.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/machine_learning/classifiers.py#L322-L334
3,966
simpleai-team/simpleai
simpleai/search/csp.py
backtrack
def backtrack(problem, variable_heuristic='', value_heuristic='', inference=True): ''' Backtracking search. variable_heuristic is the heuristic for variable choosing, can be MOST_CONSTRAINED_VARIABLE, HIGHEST_DEGREE_VARIABLE, or blank for simple ordered choosing. value_heuristic is the heuristic for value choosing, can be LEAST_CONSTRAINING_VALUE or blank for simple ordered choosing. ''' assignment = {} domains = deepcopy(problem.domains) if variable_heuristic == MOST_CONSTRAINED_VARIABLE: variable_chooser = _most_constrained_variable_chooser elif variable_heuristic == HIGHEST_DEGREE_VARIABLE: variable_chooser = _highest_degree_variable_chooser else: variable_chooser = _basic_variable_chooser if value_heuristic == LEAST_CONSTRAINING_VALUE: values_sorter = _least_constraining_values_sorter else: values_sorter = _basic_values_sorter return _backtracking(problem, assignment, domains, variable_chooser, values_sorter, inference=inference)
python
def backtrack(problem, variable_heuristic='', value_heuristic='', inference=True): ''' Backtracking search. variable_heuristic is the heuristic for variable choosing, can be MOST_CONSTRAINED_VARIABLE, HIGHEST_DEGREE_VARIABLE, or blank for simple ordered choosing. value_heuristic is the heuristic for value choosing, can be LEAST_CONSTRAINING_VALUE or blank for simple ordered choosing. ''' assignment = {} domains = deepcopy(problem.domains) if variable_heuristic == MOST_CONSTRAINED_VARIABLE: variable_chooser = _most_constrained_variable_chooser elif variable_heuristic == HIGHEST_DEGREE_VARIABLE: variable_chooser = _highest_degree_variable_chooser else: variable_chooser = _basic_variable_chooser if value_heuristic == LEAST_CONSTRAINING_VALUE: values_sorter = _least_constraining_values_sorter else: values_sorter = _basic_values_sorter return _backtracking(problem, assignment, domains, variable_chooser, values_sorter, inference=inference)
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Backtracking search. variable_heuristic is the heuristic for variable choosing, can be MOST_CONSTRAINED_VARIABLE, HIGHEST_DEGREE_VARIABLE, or blank for simple ordered choosing. value_heuristic is the heuristic for value choosing, can be LEAST_CONSTRAINING_VALUE or blank for simple ordered choosing.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/csp.py#L12-L41
3,967
simpleai-team/simpleai
simpleai/search/csp.py
_most_constrained_variable_chooser
def _most_constrained_variable_chooser(problem, variables, domains): ''' Choose the variable that has less available values. ''' # the variable with fewer values available return sorted(variables, key=lambda v: len(domains[v]))[0]
python
def _most_constrained_variable_chooser(problem, variables, domains): ''' Choose the variable that has less available values. ''' # the variable with fewer values available return sorted(variables, key=lambda v: len(domains[v]))[0]
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Choose the variable that has less available values.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/csp.py#L51-L56
3,968
simpleai-team/simpleai
simpleai/search/csp.py
_highest_degree_variable_chooser
def _highest_degree_variable_chooser(problem, variables, domains): ''' Choose the variable that is involved on more constraints. ''' # the variable involved in more constraints return sorted(variables, key=lambda v: problem.var_degrees[v], reverse=True)[0]
python
def _highest_degree_variable_chooser(problem, variables, domains): ''' Choose the variable that is involved on more constraints. ''' # the variable involved in more constraints return sorted(variables, key=lambda v: problem.var_degrees[v], reverse=True)[0]
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Choose the variable that is involved on more constraints.
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2836befa7e970013f62e0ee75562652aacac6f65
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3,969
simpleai-team/simpleai
simpleai/search/csp.py
_count_conflicts
def _count_conflicts(problem, assignment, variable=None, value=None): ''' Count the number of violated constraints on a given assignment. ''' return len(_find_conflicts(problem, assignment, variable, value))
python
def _count_conflicts(problem, assignment, variable=None, value=None): ''' Count the number of violated constraints on a given assignment. ''' return len(_find_conflicts(problem, assignment, variable, value))
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Count the number of violated constraints on a given assignment.
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2836befa7e970013f62e0ee75562652aacac6f65
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3,970
simpleai-team/simpleai
simpleai/search/csp.py
_find_conflicts
def _find_conflicts(problem, assignment, variable=None, value=None): ''' Find violated constraints on a given assignment, with the possibility of specifying a new variable and value to add to the assignment before checking. ''' if variable is not None and value is not None: assignment = deepcopy(assignment) assignment[variable] = value conflicts = [] for neighbors, constraint in problem.constraints: # if all the neighbors on the constraint have values, check if conflict if all(n in assignment for n in neighbors): if not _call_constraint(assignment, neighbors, constraint): conflicts.append((neighbors, constraint)) return conflicts
python
def _find_conflicts(problem, assignment, variable=None, value=None): ''' Find violated constraints on a given assignment, with the possibility of specifying a new variable and value to add to the assignment before checking. ''' if variable is not None and value is not None: assignment = deepcopy(assignment) assignment[variable] = value conflicts = [] for neighbors, constraint in problem.constraints: # if all the neighbors on the constraint have values, check if conflict if all(n in assignment for n in neighbors): if not _call_constraint(assignment, neighbors, constraint): conflicts.append((neighbors, constraint)) return conflicts
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Find violated constraints on a given assignment, with the possibility of specifying a new variable and value to add to the assignment before checking.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/csp.py#L80-L97
3,971
simpleai-team/simpleai
simpleai/search/csp.py
_least_constraining_values_sorter
def _least_constraining_values_sorter(problem, assignment, variable, domains): ''' Sort values based on how many conflicts they generate if assigned. ''' # the value that generates less conflicts def update_assignment(value): new_assignment = deepcopy(assignment) new_assignment[variable] = value return new_assignment values = sorted(domains[variable][:], key=lambda v: _count_conflicts(problem, assignment, variable, v)) return values
python
def _least_constraining_values_sorter(problem, assignment, variable, domains): ''' Sort values based on how many conflicts they generate if assigned. ''' # the value that generates less conflicts def update_assignment(value): new_assignment = deepcopy(assignment) new_assignment[variable] = value return new_assignment values = sorted(domains[variable][:], key=lambda v: _count_conflicts(problem, assignment, variable, v)) return values
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Sort values based on how many conflicts they generate if assigned.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/csp.py#L107-L120
3,972
simpleai-team/simpleai
simpleai/search/csp.py
_backtracking
def _backtracking(problem, assignment, domains, variable_chooser, values_sorter, inference=True): ''' Internal recursive backtracking algorithm. ''' from simpleai.search.arc import arc_consistency_3 if len(assignment) == len(problem.variables): return assignment pending = [v for v in problem.variables if v not in assignment] variable = variable_chooser(problem, pending, domains) values = values_sorter(problem, assignment, variable, domains) for value in values: new_assignment = deepcopy(assignment) new_assignment[variable] = value if not _count_conflicts(problem, new_assignment): # TODO on aima also checks if using fc new_domains = deepcopy(domains) new_domains[variable] = [value] if not inference or arc_consistency_3(new_domains, problem.constraints): result = _backtracking(problem, new_assignment, new_domains, variable_chooser, values_sorter, inference=inference) if result: return result return None
python
def _backtracking(problem, assignment, domains, variable_chooser, values_sorter, inference=True): ''' Internal recursive backtracking algorithm. ''' from simpleai.search.arc import arc_consistency_3 if len(assignment) == len(problem.variables): return assignment pending = [v for v in problem.variables if v not in assignment] variable = variable_chooser(problem, pending, domains) values = values_sorter(problem, assignment, variable, domains) for value in values: new_assignment = deepcopy(assignment) new_assignment[variable] = value if not _count_conflicts(problem, new_assignment): # TODO on aima also checks if using fc new_domains = deepcopy(domains) new_domains[variable] = [value] if not inference or arc_consistency_3(new_domains, problem.constraints): result = _backtracking(problem, new_assignment, new_domains, variable_chooser, values_sorter, inference=inference) if result: return result return None
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Internal recursive backtracking algorithm.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/csp.py#L123-L155
3,973
simpleai-team/simpleai
simpleai/search/csp.py
_min_conflicts_value
def _min_conflicts_value(problem, assignment, variable): ''' Return the value generate the less number of conflicts. In case of tie, a random value is selected among this values subset. ''' return argmin(problem.domains[variable], lambda x: _count_conflicts(problem, assignment, variable, x))
python
def _min_conflicts_value(problem, assignment, variable): ''' Return the value generate the less number of conflicts. In case of tie, a random value is selected among this values subset. ''' return argmin(problem.domains[variable], lambda x: _count_conflicts(problem, assignment, variable, x))
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Return the value generate the less number of conflicts. In case of tie, a random value is selected among this values subset.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/csp.py#L158-L163
3,974
simpleai-team/simpleai
simpleai/search/csp.py
min_conflicts
def min_conflicts(problem, initial_assignment=None, iterations_limit=0): """ Min conflicts search. initial_assignment the initial assignment, or None to generate a random one. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until if finds an assignment that doesn't generate conflicts (a solution). """ assignment = {} if initial_assignment: assignment.update(initial_assignment) else: for variable in problem.variables: value = _min_conflicts_value(problem, assignment, variable) assignment[variable] = value iteration = 0 run = True while run: conflicts = _find_conflicts(problem, assignment) conflict_variables = [v for v in problem.variables if any(v in conflict[0] for conflict in conflicts)] if conflict_variables: variable = random.choice(conflict_variables) value = _min_conflicts_value(problem, assignment, variable) assignment[variable] = value iteration += 1 if iterations_limit and iteration >= iterations_limit: run = False elif not _count_conflicts(problem, assignment): run = False return assignment
python
def min_conflicts(problem, initial_assignment=None, iterations_limit=0): """ Min conflicts search. initial_assignment the initial assignment, or None to generate a random one. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until if finds an assignment that doesn't generate conflicts (a solution). """ assignment = {} if initial_assignment: assignment.update(initial_assignment) else: for variable in problem.variables: value = _min_conflicts_value(problem, assignment, variable) assignment[variable] = value iteration = 0 run = True while run: conflicts = _find_conflicts(problem, assignment) conflict_variables = [v for v in problem.variables if any(v in conflict[0] for conflict in conflicts)] if conflict_variables: variable = random.choice(conflict_variables) value = _min_conflicts_value(problem, assignment, variable) assignment[variable] = value iteration += 1 if iterations_limit and iteration >= iterations_limit: run = False elif not _count_conflicts(problem, assignment): run = False return assignment
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Min conflicts search. initial_assignment the initial assignment, or None to generate a random one. If iterations_limit is specified, the algorithm will end after that number of iterations. Else, it will continue until if finds an assignment that doesn't generate conflicts (a solution).
[ "Min", "conflicts", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/csp.py#L166-L204
3,975
simpleai-team/simpleai
simpleai/search/csp.py
convert_to_binary
def convert_to_binary(variables, domains, constraints): """ Returns new constraint list, all binary, using hidden variables. You can use it as previous step when creating a problem. """ def wdiff(vars_): def diff(variables, values): hidden, other = variables if hidden.startswith('hidden'): idx = vars_.index(other) return values[1] == values[0][idx] else: idx = vars_.index(hidden) return values[0] == values[1][idx] diff.no_wrap = True # so it's not wrapped to swap values return diff new_constraints = [] new_domains = copy(domains) new_variables = list(variables) last = 0 for vars_, const in constraints: if len(vars_) == 2: new_constraints.append((vars_, const)) continue hidden = 'hidden%d' % last new_variables.append(hidden) last += 1 new_domains[hidden] = [t for t in product(*map(domains.get, vars_)) if const(vars_, t)] for var in vars_: new_constraints.append(((hidden, var), wdiff(vars_))) return new_variables, new_domains, new_constraints
python
def convert_to_binary(variables, domains, constraints): """ Returns new constraint list, all binary, using hidden variables. You can use it as previous step when creating a problem. """ def wdiff(vars_): def diff(variables, values): hidden, other = variables if hidden.startswith('hidden'): idx = vars_.index(other) return values[1] == values[0][idx] else: idx = vars_.index(hidden) return values[0] == values[1][idx] diff.no_wrap = True # so it's not wrapped to swap values return diff new_constraints = [] new_domains = copy(domains) new_variables = list(variables) last = 0 for vars_, const in constraints: if len(vars_) == 2: new_constraints.append((vars_, const)) continue hidden = 'hidden%d' % last new_variables.append(hidden) last += 1 new_domains[hidden] = [t for t in product(*map(domains.get, vars_)) if const(vars_, t)] for var in vars_: new_constraints.append(((hidden, var), wdiff(vars_))) return new_variables, new_domains, new_constraints
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Returns new constraint list, all binary, using hidden variables. You can use it as previous step when creating a problem.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/csp.py#L207-L242
3,976
simpleai-team/simpleai
simpleai/machine_learning/reinforcement_learning.py
boltzmann_exploration
def boltzmann_exploration(actions, utilities, temperature, action_counter): '''returns an action with a probability depending on utilities and temperature''' utilities = [utilities[x] for x in actions] temperature = max(temperature, 0.01) _max = max(utilities) _min = min(utilities) if _max == _min: return random.choice(actions) utilities = [math.exp(((u - _min) / (_max - _min)) / temperature) for u in utilities] probs = [u / sum(utilities) for u in utilities] i = 0 tot = probs[i] r = random.random() while i < len(actions) and r >= tot: i += 1 tot += probs[i] return actions[i]
python
def boltzmann_exploration(actions, utilities, temperature, action_counter): '''returns an action with a probability depending on utilities and temperature''' utilities = [utilities[x] for x in actions] temperature = max(temperature, 0.01) _max = max(utilities) _min = min(utilities) if _max == _min: return random.choice(actions) utilities = [math.exp(((u - _min) / (_max - _min)) / temperature) for u in utilities] probs = [u / sum(utilities) for u in utilities] i = 0 tot = probs[i] r = random.random() while i < len(actions) and r >= tot: i += 1 tot += probs[i] return actions[i]
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returns an action with a probability depending on utilities and temperature
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/machine_learning/reinforcement_learning.py#L28-L45
3,977
simpleai-team/simpleai
samples/search/sudoku.py
mkconstraints
def mkconstraints(): """ Make constraint list for binary constraint problem. """ constraints = [] for j in range(1, 10): vars = ["%s%d" % (i, j) for i in uppercase[:9]] constraints.extend((c, const_different) for c in combinations(vars, 2)) for i in uppercase[:9]: vars = ["%s%d" % (i, j) for j in range(1, 10)] constraints.extend((c, const_different) for c in combinations(vars, 2)) for b0 in ['ABC', 'DEF', 'GHI']: for b1 in [[1, 2, 3], [4, 5, 6], [7, 8, 9]]: vars = ["%s%d" % (i, j) for i in b0 for j in b1] l = list((c, const_different) for c in combinations(vars, 2)) constraints.extend(l) return constraints
python
def mkconstraints(): """ Make constraint list for binary constraint problem. """ constraints = [] for j in range(1, 10): vars = ["%s%d" % (i, j) for i in uppercase[:9]] constraints.extend((c, const_different) for c in combinations(vars, 2)) for i in uppercase[:9]: vars = ["%s%d" % (i, j) for j in range(1, 10)] constraints.extend((c, const_different) for c in combinations(vars, 2)) for b0 in ['ABC', 'DEF', 'GHI']: for b1 in [[1, 2, 3], [4, 5, 6], [7, 8, 9]]: vars = ["%s%d" % (i, j) for i in b0 for j in b1] l = list((c, const_different) for c in combinations(vars, 2)) constraints.extend(l) return constraints
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Make constraint list for binary constraint problem.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/samples/search/sudoku.py#L57-L77
3,978
simpleai-team/simpleai
simpleai/machine_learning/evaluation.py
precision
def precision(classifier, testset): """ Runs the classifier for each example in `testset` and verifies that the classification is correct using the `target`. Returns a number between 0.0 and 1.0 with the precision of classification for this test set. """ hit = 0 total = 0 for example in testset: if classifier.classify(example)[0] == classifier.target(example): hit += 1 total += 1 if total == 0: raise ValueError("Empty testset!") return hit / float(total)
python
def precision(classifier, testset): """ Runs the classifier for each example in `testset` and verifies that the classification is correct using the `target`. Returns a number between 0.0 and 1.0 with the precision of classification for this test set. """ hit = 0 total = 0 for example in testset: if classifier.classify(example)[0] == classifier.target(example): hit += 1 total += 1 if total == 0: raise ValueError("Empty testset!") return hit / float(total)
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Runs the classifier for each example in `testset` and verifies that the classification is correct using the `target`. Returns a number between 0.0 and 1.0 with the precision of classification for this test set.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/machine_learning/evaluation.py#L12-L30
3,979
simpleai-team/simpleai
simpleai/machine_learning/evaluation.py
kfold
def kfold(dataset, problem, method, k=10): """ Does a k-fold on `dataset` with `method`. This is, it randomly creates k-partitions of the dataset, and k-times trains the method with k-1 parts and runs it with the partition left. After all this, returns the overall success ratio. """ if k <= 1: raise ValueError("k argument must be at least 2") dataset = list(dataset) random.shuffle(dataset) trials = 0 positive = 0 for i in range(k): train = [x for j, x in enumerate(dataset) if j % k != i] test = [x for j, x in enumerate(dataset) if j % k == i] classifier = method(train, problem) for data in test: trials += 1 result = classifier.classify(data) if result is not None and result[0] == problem.target(data): positive += 1 return float(positive) / float(trials)
python
def kfold(dataset, problem, method, k=10): """ Does a k-fold on `dataset` with `method`. This is, it randomly creates k-partitions of the dataset, and k-times trains the method with k-1 parts and runs it with the partition left. After all this, returns the overall success ratio. """ if k <= 1: raise ValueError("k argument must be at least 2") dataset = list(dataset) random.shuffle(dataset) trials = 0 positive = 0 for i in range(k): train = [x for j, x in enumerate(dataset) if j % k != i] test = [x for j, x in enumerate(dataset) if j % k == i] classifier = method(train, problem) for data in test: trials += 1 result = classifier.classify(data) if result is not None and result[0] == problem.target(data): positive += 1 return float(positive) / float(trials)
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Does a k-fold on `dataset` with `method`. This is, it randomly creates k-partitions of the dataset, and k-times trains the method with k-1 parts and runs it with the partition left. After all this, returns the overall success ratio.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/machine_learning/evaluation.py#L33-L59
3,980
simpleai-team/simpleai
samples/machine_learning/tic_tac_toe.py
TicTacToeProblem.actions
def actions(self, state): 'actions are index where we can make a move' actions = [] for index, char in enumerate(state): if char == '_': actions.append(index) return actions
python
def actions(self, state): 'actions are index where we can make a move' actions = [] for index, char in enumerate(state): if char == '_': actions.append(index) return actions
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actions are index where we can make a move
[ "actions", "are", "index", "where", "we", "can", "make", "a", "move" ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/samples/machine_learning/tic_tac_toe.py#L14-L20
3,981
simpleai-team/simpleai
samples/search/missioners.py
MissionersProblem.actions
def actions(self, s): '''Possible actions from a state.''' # we try to generate every possible state and then filter those # states that are valid return [a for a in self._actions if self._is_valid(self.result(s, a))]
python
def actions(self, s): '''Possible actions from a state.''' # we try to generate every possible state and then filter those # states that are valid return [a for a in self._actions if self._is_valid(self.result(s, a))]
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Possible actions from a state.
[ "Possible", "actions", "from", "a", "state", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/samples/search/missioners.py#L21-L25
3,982
simpleai-team/simpleai
samples/search/missioners.py
MissionersProblem._is_valid
def _is_valid(self, s): '''Check if a state is valid.''' # valid states: no more cannibals than missioners on each side, # and numbers between 0 and 3 return ((s[0] >= s[1] or s[0] == 0)) and \ ((3 - s[0]) >= (3 - s[1]) or s[0] == 3) and \ (0 <= s[0] <= 3) and \ (0 <= s[1] <= 3)
python
def _is_valid(self, s): '''Check if a state is valid.''' # valid states: no more cannibals than missioners on each side, # and numbers between 0 and 3 return ((s[0] >= s[1] or s[0] == 0)) and \ ((3 - s[0]) >= (3 - s[1]) or s[0] == 3) and \ (0 <= s[0] <= 3) and \ (0 <= s[1] <= 3)
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Check if a state is valid.
[ "Check", "if", "a", "state", "is", "valid", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/samples/search/missioners.py#L27-L34
3,983
simpleai-team/simpleai
samples/search/missioners.py
MissionersProblem.result
def result(self, s, a): '''Result of applying an action to a state.''' # result: boat on opposite side, and numbers of missioners and # cannibals updated according to the move if s[2] == 0: return (s[0] - a[1][0], s[1] - a[1][1], 1) else: return (s[0] + a[1][0], s[1] + a[1][1], 0)
python
def result(self, s, a): '''Result of applying an action to a state.''' # result: boat on opposite side, and numbers of missioners and # cannibals updated according to the move if s[2] == 0: return (s[0] - a[1][0], s[1] - a[1][1], 1) else: return (s[0] + a[1][0], s[1] + a[1][1], 0)
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Result of applying an action to a state.
[ "Result", "of", "applying", "an", "action", "to", "a", "state", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/samples/search/missioners.py#L36-L43
3,984
simpleai-team/simpleai
simpleai/search/arc.py
arc_consistency_3
def arc_consistency_3(domains, constraints): """ Makes a CSP problem arc consistent. Ignores any constraint that is not binary. """ arcs = list(all_arcs(constraints)) pending_arcs = set(arcs) while pending_arcs: x, y = pending_arcs.pop() if revise(domains, (x, y), constraints): if len(domains[x]) == 0: return False pending_arcs = pending_arcs.union((x2, y2) for x2, y2 in arcs if y2 == x) return True
python
def arc_consistency_3(domains, constraints): """ Makes a CSP problem arc consistent. Ignores any constraint that is not binary. """ arcs = list(all_arcs(constraints)) pending_arcs = set(arcs) while pending_arcs: x, y = pending_arcs.pop() if revise(domains, (x, y), constraints): if len(domains[x]) == 0: return False pending_arcs = pending_arcs.union((x2, y2) for x2, y2 in arcs if y2 == x) return True
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Makes a CSP problem arc consistent. Ignores any constraint that is not binary.
[ "Makes", "a", "CSP", "problem", "arc", "consistent", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/arc.py#L58-L74
3,985
simpleai-team/simpleai
simpleai/search/models.py
SearchNode.expand
def expand(self, local_search=False): '''Create successors.''' new_nodes = [] for action in self.problem.actions(self.state): new_state = self.problem.result(self.state, action) cost = self.problem.cost(self.state, action, new_state) nodefactory = self.__class__ new_nodes.append(nodefactory(state=new_state, parent=None if local_search else self, problem=self.problem, action=action, cost=self.cost + cost, depth=self.depth + 1)) return new_nodes
python
def expand(self, local_search=False): '''Create successors.''' new_nodes = [] for action in self.problem.actions(self.state): new_state = self.problem.result(self.state, action) cost = self.problem.cost(self.state, action, new_state) nodefactory = self.__class__ new_nodes.append(nodefactory(state=new_state, parent=None if local_search else self, problem=self.problem, action=action, cost=self.cost + cost, depth=self.depth + 1)) return new_nodes
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Create successors.
[ "Create", "successors", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/models.py#L102-L117
3,986
simpleai-team/simpleai
simpleai/environments.py
Environment.step
def step(self, viewer=None): "This method evolves one step in time" if not self.is_completed(self.state): for agent in self.agents: action = agent.program(self.percept(agent, self.state)) next_state = self.do_action(self.state, action, agent) if viewer: viewer.event(self.state, action, next_state, agent) self.state = next_state if self.is_completed(self.state): return
python
def step(self, viewer=None): "This method evolves one step in time" if not self.is_completed(self.state): for agent in self.agents: action = agent.program(self.percept(agent, self.state)) next_state = self.do_action(self.state, action, agent) if viewer: viewer.event(self.state, action, next_state, agent) self.state = next_state if self.is_completed(self.state): return
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This method evolves one step in time
[ "This", "method", "evolves", "one", "step", "in", "time" ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/environments.py#L18-L28
3,987
simpleai-team/simpleai
simpleai/search/traditional.py
breadth_first
def breadth_first(problem, graph_search=False, viewer=None): ''' Breadth first search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal. ''' return _search(problem, FifoList(), graph_search=graph_search, viewer=viewer)
python
def breadth_first(problem, graph_search=False, viewer=None): ''' Breadth first search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal. ''' return _search(problem, FifoList(), graph_search=graph_search, viewer=viewer)
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Breadth first search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal.
[ "Breadth", "first", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/traditional.py#L8-L19
3,988
simpleai-team/simpleai
simpleai/search/traditional.py
depth_first
def depth_first(problem, graph_search=False, viewer=None): ''' Depth first search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal. ''' return _search(problem, LifoList(), graph_search=graph_search, viewer=viewer)
python
def depth_first(problem, graph_search=False, viewer=None): ''' Depth first search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal. ''' return _search(problem, LifoList(), graph_search=graph_search, viewer=viewer)
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Depth first search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal.
[ "Depth", "first", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/traditional.py#L22-L33
3,989
simpleai-team/simpleai
simpleai/search/traditional.py
limited_depth_first
def limited_depth_first(problem, depth_limit, graph_search=False, viewer=None): ''' Limited depth first search. Depth_limit is the maximum depth allowed, being depth 0 the initial state. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal. ''' return _search(problem, LifoList(), graph_search=graph_search, depth_limit=depth_limit, viewer=viewer)
python
def limited_depth_first(problem, depth_limit, graph_search=False, viewer=None): ''' Limited depth first search. Depth_limit is the maximum depth allowed, being depth 0 the initial state. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal. ''' return _search(problem, LifoList(), graph_search=graph_search, depth_limit=depth_limit, viewer=viewer)
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Limited depth first search. Depth_limit is the maximum depth allowed, being depth 0 the initial state. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal.
[ "Limited", "depth", "first", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/traditional.py#L36-L49
3,990
simpleai-team/simpleai
simpleai/search/traditional.py
iterative_limited_depth_first
def iterative_limited_depth_first(problem, graph_search=False, viewer=None): ''' Iterative limited depth first search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal. ''' solution = None limit = 0 while not solution: solution = limited_depth_first(problem, depth_limit=limit, graph_search=graph_search, viewer=viewer) limit += 1 if viewer: viewer.event('no_more_runs', solution, 'returned after %i runs' % limit) return solution
python
def iterative_limited_depth_first(problem, graph_search=False, viewer=None): ''' Iterative limited depth first search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal. ''' solution = None limit = 0 while not solution: solution = limited_depth_first(problem, depth_limit=limit, graph_search=graph_search, viewer=viewer) limit += 1 if viewer: viewer.event('no_more_runs', solution, 'returned after %i runs' % limit) return solution
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Iterative limited depth first search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, and SearchProblem.is_goal.
[ "Iterative", "limited", "depth", "first", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/traditional.py#L52-L73
3,991
simpleai-team/simpleai
simpleai/search/traditional.py
uniform_cost
def uniform_cost(problem, graph_search=False, viewer=None): ''' Uniform cost search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.is_goal, and SearchProblem.cost. ''' return _search(problem, BoundedPriorityQueue(), graph_search=graph_search, node_factory=SearchNodeCostOrdered, graph_replace_when_better=True, viewer=viewer)
python
def uniform_cost(problem, graph_search=False, viewer=None): ''' Uniform cost search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.is_goal, and SearchProblem.cost. ''' return _search(problem, BoundedPriorityQueue(), graph_search=graph_search, node_factory=SearchNodeCostOrdered, graph_replace_when_better=True, viewer=viewer)
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Uniform cost search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.is_goal, and SearchProblem.cost.
[ "Uniform", "cost", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/traditional.py#L76-L89
3,992
simpleai-team/simpleai
simpleai/search/traditional.py
greedy
def greedy(problem, graph_search=False, viewer=None): ''' Greedy search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.is_goal, SearchProblem.cost, and SearchProblem.heuristic. ''' return _search(problem, BoundedPriorityQueue(), graph_search=graph_search, node_factory=SearchNodeHeuristicOrdered, graph_replace_when_better=True, viewer=viewer)
python
def greedy(problem, graph_search=False, viewer=None): ''' Greedy search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.is_goal, SearchProblem.cost, and SearchProblem.heuristic. ''' return _search(problem, BoundedPriorityQueue(), graph_search=graph_search, node_factory=SearchNodeHeuristicOrdered, graph_replace_when_better=True, viewer=viewer)
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Greedy search. If graph_search=True, will avoid exploring repeated states. Requires: SearchProblem.actions, SearchProblem.result, SearchProblem.is_goal, SearchProblem.cost, and SearchProblem.heuristic.
[ "Greedy", "search", "." ]
2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/traditional.py#L92-L105
3,993
simpleai-team/simpleai
simpleai/search/traditional.py
_search
def _search(problem, fringe, graph_search=False, depth_limit=None, node_factory=SearchNode, graph_replace_when_better=False, viewer=None): ''' Basic search algorithm, base of all the other search algorithms. ''' if viewer: viewer.event('started') memory = set() initial_node = node_factory(state=problem.initial_state, problem=problem) fringe.append(initial_node) while fringe: if viewer: viewer.event('new_iteration', fringe.sorted()) node = fringe.pop() if problem.is_goal(node.state): if viewer: viewer.event('chosen_node', node, True) viewer.event('finished', fringe.sorted(), node, 'goal found') return node else: if viewer: viewer.event('chosen_node', node, False) memory.add(node.state) if depth_limit is None or node.depth < depth_limit: expanded = node.expand() if viewer: viewer.event('expanded', [node], [expanded]) for n in expanded: if graph_search: others = [x for x in fringe if x.state == n.state] assert len(others) in (0, 1) if n.state not in memory and len(others) == 0: fringe.append(n) elif graph_replace_when_better and len(others) > 0 and n < others[0]: fringe.remove(others[0]) fringe.append(n) else: fringe.append(n) if viewer: viewer.event('finished', fringe.sorted(), None, 'goal not found')
python
def _search(problem, fringe, graph_search=False, depth_limit=None, node_factory=SearchNode, graph_replace_when_better=False, viewer=None): ''' Basic search algorithm, base of all the other search algorithms. ''' if viewer: viewer.event('started') memory = set() initial_node = node_factory(state=problem.initial_state, problem=problem) fringe.append(initial_node) while fringe: if viewer: viewer.event('new_iteration', fringe.sorted()) node = fringe.pop() if problem.is_goal(node.state): if viewer: viewer.event('chosen_node', node, True) viewer.event('finished', fringe.sorted(), node, 'goal found') return node else: if viewer: viewer.event('chosen_node', node, False) memory.add(node.state) if depth_limit is None or node.depth < depth_limit: expanded = node.expand() if viewer: viewer.event('expanded', [node], [expanded]) for n in expanded: if graph_search: others = [x for x in fringe if x.state == n.state] assert len(others) in (0, 1) if n.state not in memory and len(others) == 0: fringe.append(n) elif graph_replace_when_better and len(others) > 0 and n < others[0]: fringe.remove(others[0]) fringe.append(n) else: fringe.append(n) if viewer: viewer.event('finished', fringe.sorted(), None, 'goal not found')
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Basic search algorithm, base of all the other search algorithms.
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2836befa7e970013f62e0ee75562652aacac6f65
https://github.com/simpleai-team/simpleai/blob/2836befa7e970013f62e0ee75562652aacac6f65/simpleai/search/traditional.py#L124-L173
3,994
andosa/treeinterpreter
treeinterpreter/treeinterpreter.py
_get_tree_paths
def _get_tree_paths(tree, node_id, depth=0): """ Returns all paths through the tree as list of node_ids """ if node_id == _tree.TREE_LEAF: raise ValueError("Invalid node_id %s" % _tree.TREE_LEAF) left_child = tree.children_left[node_id] right_child = tree.children_right[node_id] if left_child != _tree.TREE_LEAF: left_paths = _get_tree_paths(tree, left_child, depth=depth + 1) right_paths = _get_tree_paths(tree, right_child, depth=depth + 1) for path in left_paths: path.append(node_id) for path in right_paths: path.append(node_id) paths = left_paths + right_paths else: paths = [[node_id]] return paths
python
def _get_tree_paths(tree, node_id, depth=0): """ Returns all paths through the tree as list of node_ids """ if node_id == _tree.TREE_LEAF: raise ValueError("Invalid node_id %s" % _tree.TREE_LEAF) left_child = tree.children_left[node_id] right_child = tree.children_right[node_id] if left_child != _tree.TREE_LEAF: left_paths = _get_tree_paths(tree, left_child, depth=depth + 1) right_paths = _get_tree_paths(tree, right_child, depth=depth + 1) for path in left_paths: path.append(node_id) for path in right_paths: path.append(node_id) paths = left_paths + right_paths else: paths = [[node_id]] return paths
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Returns all paths through the tree as list of node_ids
[ "Returns", "all", "paths", "through", "the", "tree", "as", "list", "of", "node_ids" ]
c4294ad6ad74ea574ca41aa81b6f7f1545da0186
https://github.com/andosa/treeinterpreter/blob/c4294ad6ad74ea574ca41aa81b6f7f1545da0186/treeinterpreter/treeinterpreter.py#L12-L33
3,995
csurfer/rake-nltk
rake_nltk/rake.py
Rake.extract_keywords_from_text
def extract_keywords_from_text(self, text): """Method to extract keywords from the text provided. :param text: Text to extract keywords from, provided as a string. """ sentences = nltk.tokenize.sent_tokenize(text) self.extract_keywords_from_sentences(sentences)
python
def extract_keywords_from_text(self, text): """Method to extract keywords from the text provided. :param text: Text to extract keywords from, provided as a string. """ sentences = nltk.tokenize.sent_tokenize(text) self.extract_keywords_from_sentences(sentences)
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Method to extract keywords from the text provided. :param text: Text to extract keywords from, provided as a string.
[ "Method", "to", "extract", "keywords", "from", "the", "text", "provided", "." ]
e36116d6074c5ddfbc69bce4440f0342355ceb2e
https://github.com/csurfer/rake-nltk/blob/e36116d6074c5ddfbc69bce4440f0342355ceb2e/rake_nltk/rake.py#L76-L82
3,996
csurfer/rake-nltk
rake_nltk/rake.py
Rake.extract_keywords_from_sentences
def extract_keywords_from_sentences(self, sentences): """Method to extract keywords from the list of sentences provided. :param sentences: Text to extraxt keywords from, provided as a list of strings, where each string is a sentence. """ phrase_list = self._generate_phrases(sentences) self._build_frequency_dist(phrase_list) self._build_word_co_occurance_graph(phrase_list) self._build_ranklist(phrase_list)
python
def extract_keywords_from_sentences(self, sentences): """Method to extract keywords from the list of sentences provided. :param sentences: Text to extraxt keywords from, provided as a list of strings, where each string is a sentence. """ phrase_list = self._generate_phrases(sentences) self._build_frequency_dist(phrase_list) self._build_word_co_occurance_graph(phrase_list) self._build_ranklist(phrase_list)
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Method to extract keywords from the list of sentences provided. :param sentences: Text to extraxt keywords from, provided as a list of strings, where each string is a sentence.
[ "Method", "to", "extract", "keywords", "from", "the", "list", "of", "sentences", "provided", "." ]
e36116d6074c5ddfbc69bce4440f0342355ceb2e
https://github.com/csurfer/rake-nltk/blob/e36116d6074c5ddfbc69bce4440f0342355ceb2e/rake_nltk/rake.py#L84-L93
3,997
csurfer/rake-nltk
rake_nltk/rake.py
Rake._build_word_co_occurance_graph
def _build_word_co_occurance_graph(self, phrase_list): """Builds the co-occurance graph of words in the given body of text to compute degree of each word. :param phrase_list: List of List of strings where each sublist is a collection of words which form a contender phrase. """ co_occurance_graph = defaultdict(lambda: defaultdict(lambda: 0)) for phrase in phrase_list: # For each phrase in the phrase list, count co-occurances of the # word with other words in the phrase. # # Note: Keep the co-occurances graph as is, to help facilitate its # use in other creative ways if required later. for (word, coword) in product(phrase, phrase): co_occurance_graph[word][coword] += 1 self.degree = defaultdict(lambda: 0) for key in co_occurance_graph: self.degree[key] = sum(co_occurance_graph[key].values())
python
def _build_word_co_occurance_graph(self, phrase_list): """Builds the co-occurance graph of words in the given body of text to compute degree of each word. :param phrase_list: List of List of strings where each sublist is a collection of words which form a contender phrase. """ co_occurance_graph = defaultdict(lambda: defaultdict(lambda: 0)) for phrase in phrase_list: # For each phrase in the phrase list, count co-occurances of the # word with other words in the phrase. # # Note: Keep the co-occurances graph as is, to help facilitate its # use in other creative ways if required later. for (word, coword) in product(phrase, phrase): co_occurance_graph[word][coword] += 1 self.degree = defaultdict(lambda: 0) for key in co_occurance_graph: self.degree[key] = sum(co_occurance_graph[key].values())
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Builds the co-occurance graph of words in the given body of text to compute degree of each word. :param phrase_list: List of List of strings where each sublist is a collection of words which form a contender phrase.
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e36116d6074c5ddfbc69bce4440f0342355ceb2e
https://github.com/csurfer/rake-nltk/blob/e36116d6074c5ddfbc69bce4440f0342355ceb2e/rake_nltk/rake.py#L135-L153
3,998
csurfer/rake-nltk
rake_nltk/rake.py
Rake._build_ranklist
def _build_ranklist(self, phrase_list): """Method to rank each contender phrase using the formula phrase_score = sum of scores of words in the phrase. word_score = d(w)/f(w) where d is degree and f is frequency. :param phrase_list: List of List of strings where each sublist is a collection of words which form a contender phrase. """ self.rank_list = [] for phrase in phrase_list: rank = 0.0 for word in phrase: if self.metric == Metric.DEGREE_TO_FREQUENCY_RATIO: rank += 1.0 * self.degree[word] / self.frequency_dist[word] elif self.metric == Metric.WORD_DEGREE: rank += 1.0 * self.degree[word] else: rank += 1.0 * self.frequency_dist[word] self.rank_list.append((rank, " ".join(phrase))) self.rank_list.sort(reverse=True) self.ranked_phrases = [ph[1] for ph in self.rank_list]
python
def _build_ranklist(self, phrase_list): """Method to rank each contender phrase using the formula phrase_score = sum of scores of words in the phrase. word_score = d(w)/f(w) where d is degree and f is frequency. :param phrase_list: List of List of strings where each sublist is a collection of words which form a contender phrase. """ self.rank_list = [] for phrase in phrase_list: rank = 0.0 for word in phrase: if self.metric == Metric.DEGREE_TO_FREQUENCY_RATIO: rank += 1.0 * self.degree[word] / self.frequency_dist[word] elif self.metric == Metric.WORD_DEGREE: rank += 1.0 * self.degree[word] else: rank += 1.0 * self.frequency_dist[word] self.rank_list.append((rank, " ".join(phrase))) self.rank_list.sort(reverse=True) self.ranked_phrases = [ph[1] for ph in self.rank_list]
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Method to rank each contender phrase using the formula phrase_score = sum of scores of words in the phrase. word_score = d(w)/f(w) where d is degree and f is frequency. :param phrase_list: List of List of strings where each sublist is a collection of words which form a contender phrase.
[ "Method", "to", "rank", "each", "contender", "phrase", "using", "the", "formula" ]
e36116d6074c5ddfbc69bce4440f0342355ceb2e
https://github.com/csurfer/rake-nltk/blob/e36116d6074c5ddfbc69bce4440f0342355ceb2e/rake_nltk/rake.py#L155-L176
3,999
csurfer/rake-nltk
rake_nltk/rake.py
Rake._generate_phrases
def _generate_phrases(self, sentences): """Method to generate contender phrases given the sentences of the text document. :param sentences: List of strings where each string represents a sentence which forms the text. :return: Set of string tuples where each tuple is a collection of words forming a contender phrase. """ phrase_list = set() # Create contender phrases from sentences. for sentence in sentences: word_list = [word.lower() for word in wordpunct_tokenize(sentence)] phrase_list.update(self._get_phrase_list_from_words(word_list)) return phrase_list
python
def _generate_phrases(self, sentences): """Method to generate contender phrases given the sentences of the text document. :param sentences: List of strings where each string represents a sentence which forms the text. :return: Set of string tuples where each tuple is a collection of words forming a contender phrase. """ phrase_list = set() # Create contender phrases from sentences. for sentence in sentences: word_list = [word.lower() for word in wordpunct_tokenize(sentence)] phrase_list.update(self._get_phrase_list_from_words(word_list)) return phrase_list
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Method to generate contender phrases given the sentences of the text document. :param sentences: List of strings where each string represents a sentence which forms the text. :return: Set of string tuples where each tuple is a collection of words forming a contender phrase.
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e36116d6074c5ddfbc69bce4440f0342355ceb2e
https://github.com/csurfer/rake-nltk/blob/e36116d6074c5ddfbc69bce4440f0342355ceb2e/rake_nltk/rake.py#L178-L192