weka.core package¶
weka.core.capabilities module¶
- class weka.core.capabilities.Capabilities(jobject=None, owner=None)¶
Bases:
weka.core.classes.JavaObject
Wrapper for Capabilities.
- attribute_capabilities()¶
Returns all the attribute capabilities.
- Returns
attribute capabilities
- Return type
- capabilities()¶
Returns all the capabilities.
- Returns
all capabilities
- Return type
list
- class_capabilities()¶
Returns all the class capabilities.
- Returns
class capabilities
- Return type
- dependencies()¶
Returns all the dependencies.
- Returns
the dependency list
- Return type
list
- disable(capability)¶
Disables the specified capability.
- Parameters
capability (Capability) – the capability to disable
- disable_all()¶
Disables all capabilities.
- disable_all_attribute_dependencies()¶
Disables all attribute dependencies.
- disable_all_attributes()¶
Disables all attributes.
- disable_all_class_dependencies()¶
Disables all class dependencies.
- disable_all_classes()¶
Disables all classes.
- disable_dependency(capability)¶
Disables the dependency of the given capability Disabling NOMINAL_ATTRIBUTES also disables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
- Parameters
capability (Capability) – the dependency to disable
- enable(capability)¶
enables the specified capability.
- Parameters
capability (Capability) – the capability to enable
- enable_all()¶
enables all capabilities.
- enable_all_attribute_dependencies()¶
enables all attribute dependencies.
- enable_all_attributes()¶
enables all attributes.
- enable_all_class_dependencies()¶
enables all class dependencies.
- enable_all_classes()¶
enables all classes.
- enable_dependency(capability)¶
enables the dependency of the given capability enabling NOMINAL_ATTRIBUTES also enables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
- Parameters
capability (Capability) – the dependency to enable
- classmethod for_instances(data, multi=None)¶
returns a Capabilities object specific for this data. The minimum number of instances is not set, the check for multi-instance data is optional.
- Parameters
data (Instances) – the data to generate the capabilities for
multi (bool) – whether to check the structure, too
- Returns
the generated capabilities
- Return type
- handles(capability)¶
Returns whether the specified capability is set.
- Parameters
capability (Capability) – the capability to check
- Returns
whether the capability is set
- Return type
bool
- has_dependencies()¶
Returns whether any dependencies are set.
- Returns
whether any dependecies are set
- Return type
bool
- has_dependency(capability)¶
Returns whether the specified dependency is set.
- Parameters
capability (Capability) – the capability to check
- Returns
whether the dependency is set
- Return type
bool
- property min_instances¶
Returns the minimum number of instances that must be supported.
- Returns
the minimum number
- Return type
int
- other_capabilities()¶
Returns all other capabilities.
- Returns
all other capabilities
- Return type
- property owner¶
Returns the owner of these capabilities, if any.
- Returns
the owner, can be None
- Return type
- supports(capabilities)¶
Returns true if the currently set capabilities support at least all of the capabiliites of the given Capabilities object (checks only the enum!)
- Parameters
capabilities (Capabilities) – the capabilities to check
- Returns
whether the current capabilities support at least the specified ones
- Return type
bool
- supports_maybe(capabilities)¶
Returns true if the currently set capabilities support (or have a dependency) at least all of the capabilities of the given Capabilities object (checks only the enum!)
- Parameters
capabilities (Capabilities) – the capabilities to check
- Returns
whether the current capabilities (potentially) support the specified ones
- Return type
bool
- test_attribute(att, is_class=None, fail=False)¶
Tests whether the attribute meets the conditions.
- Parameters
att (Attribute) – the Attribute to test
is_class (bool) – whether this attribute is the class attribute
fail (bool) – whether to fail with an exception in case the test fails
- Returns
whether the attribute meets the conditions
- Return type
bool
- test_instances(data, from_index=None, to_index=None, fail=False)¶
Tests whether the dataset meets the conditions.
- Parameters
data (Instances) – the Instances to test
from_index (int) – the first attribute to include
to_index (int) – the last attribute to include
- Returns
wether the dataset meets the requirements
- Return type
bool
- class weka.core.capabilities.Capability(jobject=None, member=None)¶
Bases:
weka.core.classes.Enum
Wrapper for a Capability.
- property is_attribute¶
Returns whether this capability is an attribute.
- Returns
whether it is an attribute
- Return type
bool
- property is_attribute_capability¶
Returns whether this capability is an attribute capability.
- Returns
whether it is an attribute capability
- Return type
bool
- property is_class¶
Returns whether this capability is a class.
- Returns
whether it is a class
- Return type
bool
- property is_class_capability¶
Returns whether this capability is a class capability.
- Returns
whether it is a class capability
- Return type
bool
- property is_other_capability¶
Returns whether this capability is an other capability.
- Returns
whether it is an other capability
- Return type
bool
weka.core.classes module¶
- class weka.core.classes.AbstractParameter(classname=None, jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Ancestor for all parameter classes used by SetupGenerator and MultiSearch.
- property prop¶
Returns the currently set property to apply the parameter to.
- Returns
the property
- Return type
str
- class weka.core.classes.Configurable(config=None)¶
Bases:
weka.core.classes.JSONObject
The ancestor for all actors.
- property config¶
Obtains the currently set options of the actor.
- Returns
the options
- Return type
dict
- description()¶
Returns a description of the object.
- Returns
the description
- Return type
str
- fix_config(options)¶
Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.
- Parameters
options (dict) – the options to fix
- Returns
the (potentially) fixed options
- Return type
dict
- classmethod from_dict(d)¶
Restores its state from a dictionary, used in de-JSONification.
- Parameters
d (dict) – the object dictionary
- generate_help()¶
Generates a help string for this actor.
- Returns
the help string
- Return type
str
- property help¶
Obtains the help information per option for this actor.
- Returns
the help
- Return type
dict
- property logger¶
Returns the logger object.
- Returns
the logger
- Return type
logger
- new_logger()¶
Returns a new logger instance.
- Returns
the logger instance
- Return type
logger
- print_help()¶
Prints a help string for this actor to stdout.
- to_dict()¶
Returns a dictionary that represents this object, to be used for JSONification.
- Returns
the object dictionary
- Return type
dict
- class weka.core.classes.Date(jobject=None, msecs=None)¶
Bases:
weka.core.classes.JavaObject
Wraps a java.util.Date object.
- property time¶
Returns the stored milli-seconds.
- Returns
the milli-seconds
- Return type
long
- class weka.core.classes.Enum(jobject=None, enum=None, member=None)¶
Bases:
weka.core.classes.JavaObject
Wrapper for Java enums.
- property name¶
Returns the name of the enum member.
- Returns
the name
- Return type
str
- property ordinal¶
Returns the ordinal of the enum member.
- Returns
the ordinal
- Return type
int
- property values¶
Returns list of all enum members.
- Returns
all enum members
- Return type
list
- class weka.core.classes.Environment(jobject=None)¶
Bases:
weka.core.classes.JavaObject
Wraps around weka.core.Environment
- add_variable(key, value, system_wide=False)¶
Adds the environment variable.
- Parameters
key (str) – the name of the variable
value (str) – the value
system_wide (bool) – whether to add the variable system wide
- remove_variable(key)¶
Adds the environment variable.
- Parameters
key (str) – the name of the variable
- classmethod system_wide()¶
Returns the system-wide environment.
;return: the environment :rtype: Environment
- variable_names()¶
Returns the names of all environment variables.
- Returns
the names of the variables
- Return type
list
- variable_value(key)¶
Returns the value of the environment variable.
- Parameters
key (str) – the name of the variable
- Returns
the variable value
- Return type
str
- class weka.core.classes.JSONObject¶
Bases:
object
Ancestor for classes that can be represented as JSON and restored from JSON.
- classmethod from_dict(d)¶
Restores an object state from a dictionary, used in de-JSONification.
- Parameters
d (dict) – the object dictionary
- Returns
the object
- Return type
object
- classmethod from_json(s)¶
Restores the object from the given JSON.
- Parameters
s (str) – the JSON string to parse
- Returns
the
- shallow_copy()¶
Returns a shallow copy of itself.
- Returns
the copy
- Return type
object
- to_dict()¶
Returns a dictionary that represents this object, to be used for JSONification.
- Returns
the object dictionary
- Return type
dict
- to_json()¶
Returns the options as JSON.
- Returns
the object as string
- Return type
str
- class weka.core.classes.JavaArray(jobject)¶
Bases:
weka.core.classes.JavaObject
Convenience wrapper around Java arrays.
- component_type()¶
Returns the classname of the elements.
- Returns
the class of the elements
- Return type
str
- classmethod new_instance(classname, length)¶
Creates a new array with the given classname and length; initial values are null.
- Parameters
classname (str) – the classname in Java notation (eg “weka.core.DenseInstance”)
length (int) – the length of the array
- Returns
the Java array
- Return type
JB_Object
- class weka.core.classes.JavaArrayIterator(data)¶
Bases:
object
Iterator for elements in a Java array.
- class weka.core.classes.JavaObject(jobject)¶
Bases:
weka.core.classes.JSONObject
Basic Java object.
- classmethod check_type(jobject, intf_or_class)¶
Returns whether the object implements the specified interface or is a subclass.
- Parameters
jobject (JB_Object) – the Java object to check
intf_or_class (str) – the classname in Java notation (eg “weka.core.DenseInstance;”)
- Returns
whether object implements interface or is subclass
- Return type
bool
- property classname¶
Returns the Java classname in dot-notation.
- Returns
the Java classname
- Return type
str
- classmethod enforce_type(jobject, intf_or_class)¶
Raises an exception if the object does not implement the specified interface or is not a subclass.
- Parameters
jobject (JB_Object) – the Java object to check
intf_or_class (str) – the classname in Java notation (eg “weka.core.DenseInstance”)
- classmethod from_dict(d)¶
Restores an object state from a dictionary, used in de-JSONification.
- Parameters
d (dict) – the object dictionary
- Returns
the object
- Return type
object
- get_property(path)¶
Attempts to get the value (jobject, a Java object) of the provided (bean) property path.
- Parameters
path (str) – the property path, e.g., “filter” for a setFilter(…)/getFilter() method pair
- Returns
the wrapped Java object
- Return type
- property is_serializable¶
Returns true if the object is serialiable.
- Returns
true if serializable
- Return type
bool
- property jclass¶
Returns the Java class object of the underlying Java object.
- Returns
the Java class
- Return type
JB_Object
- property jclasswrapper¶
Returns a JClassWrapper instance of the class for the encapsulated Java object, giving access to the class methods using dot notation.
http://pythonhosted.org//javabridge/highlevel.html#wrapping-java-objects-using-reflection
- Returns
the wrapper
- Return type
JClassWrapper
- property jwrapper¶
Returns a JWrapper instance of the encapsulated Java object, giving access to methods using dot notation.
http://pythonhosted.org//javabridge/highlevel.html#wrapping-java-objects-using-reflection
- Returns
the wrapper
- Return type
JWrapper
- classmethod new_instance(classname, options=None)¶
Creates a new object from the given classname using the default constructor, None in case of error.
- Parameters
classname (str) – the classname in Java notation (eg “weka.core.DenseInstance”)
options (list) – the list of options to use, ignored if None
- Returns
the Java object
- Return type
JB_Object
- set_property(path, jobject)¶
Attempts to set the value (jobject, a Java object) of the provided (bean) property path.
- Parameters
path (str) – the property path, e.g., “filter” for a setFilter(…)/getFilter() method pair
jobject (JB_Object) – the Java object to set; if instance of JavaObject class, the jobject member is automatically used
- to_dict()¶
Returns a dictionary that represents this object, to be used for JSONification.
- Returns
the object dictionary
- Return type
dict
- class weka.core.classes.ListParameter(jobject=None, options=None)¶
Bases:
weka.core.classes.AbstractParameter
Parameter using a predefined list of values, used by SetupGenerator and MultiSearch.
- property values¶
Returns the currently set values.
- Returns
the list of values (strings)
- Return type
list
- class weka.core.classes.MathParameter(jobject=None, options=None)¶
Bases:
weka.core.classes.AbstractParameter
Parameter using a math expression for generating values, used by SetupGenerator and MultiSearch.
- property base¶
Returns the currently set base value.
- Returns
the base
- Return type
float
- property expression¶
Returns the currently set expression.
- Returns
the expression
- Return type
str
- property maximum¶
Returns the currently set maximum value.
- Returns
the maximum
- Return type
float
- property minimum¶
Returns the currently set minimum value.
- Returns
the minimum
- Return type
float
- property step¶
Returns the currently set step value.
- Returns
the step
- Return type
float
- class weka.core.classes.Option(jobject)¶
Bases:
weka.core.classes.JavaObject
Wrapper for the weka.core.Option class.
- property description¶
Returns the description of the option.
- Returns
the description
- Return type
str
- property name¶
Returns the name of the option.
- Returns
the name
- Return type
str
- property num_arguments¶
Returns the synopsis of the option.
- Returns
the synopsis
- Return type
str
- property synopsis¶
Returns the synopsis of the option.
- Returns
the synopsis
- Return type
str
- class weka.core.classes.OptionHandler(jobject, options=None)¶
Bases:
weka.core.classes.JavaObject
,weka.core.classes.Configurable
Ancestor for option-handling classes. Classes should implement the weka.core.OptionHandler interface to have any effect.
- description()¶
Returns a description of the object.
- Returns
the description
- Return type
str
- classmethod from_dict(d)¶
Restores an object state from a dictionary, used in de-JSONification.
- Parameters
d (dict) – the object dictionary
- Returns
the object
- Return type
object
- global_info()¶
Returns the globalInfo() result, None if not available.
- Rtypes
str
- property options¶
Obtains the currently set options as list.
- Returns
the list of options
- Return type
list
- to_commandline()¶
Generates a commandline string from the JavaObject instance.
- Returns
the commandline string
- Return type
str
- to_dict()¶
Returns a dictionary that represents this object, to be used for JSONification.
- Returns
the object dictionary
- Return type
dict
- to_help(title=True, description=True, options=True, use_headers=True, separator='')¶
Returns a string that contains the ‘global_info’ text and the options.
- Parameters
title (bool) – whether to output a title
description (bool) – whether to output the description
options (bool) – whether to output the options
use_headers (bool) – whether to output headers, describing the sections
separator (str) – the separator line to use between sections
- Returns
the generated help string
- Return type
str
- class weka.core.classes.Random(seed)¶
Bases:
weka.core.classes.JavaObject
Wrapper for the java.util.Random class.
- next_double()¶
Next random double.
- Returns
the next random double
- Return type
double
- next_int(n=None)¶
Next random integer. if n is provided, then between 0 and n-1.
- Parameters
n (int) – the upper limit (minus 1) for the random integer
- Returns
the next random integer
- Return type
int
- class weka.core.classes.Range(jobject=None, ranges=None)¶
Bases:
weka.core.classes.JavaObject
Wrapper for a Weka Range object.
- property invert¶
Returns whether the range is inverted.
- Returns
true if inverted
- Return type
bool
- property ranges¶
Returns the string range.
- Returns
the string range of 1-based indices
- Return type
str
- selection()¶
Returns the selection list.
- Returns
the list of 0-based integer indices
- Return type
list
- upper(upper)¶
Sets the upper limit.
- Parameters
upper (int) – the upper limit
- class weka.core.classes.SelectedTag(jobject=None, tag_id=None, tag_text=None, tags=None)¶
Bases:
weka.core.classes.JavaObject
Wrapper for the weka.core.SelectedTag class.
- property tags¶
Returns the associated tags.
- Returns
the list of Tag objects
- Return type
list
- class weka.core.classes.SetupGenerator(jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Allows generation of large number of setups using parameter setups.
- property base_object¶
Returns the base object to apply the setups to.
- Returns
the base object
- Return type
- property parameters¶
Returns the list of currently set search parameters.
- Returns
the list of AbstractSearchParameter objects
- Return type
list
- setups()¶
Generates and returns all the setups according to the parameter search space.
- Returns
the list of configured objects (of type JavaObject)
- Return type
list
- class weka.core.classes.SingleIndex(jobject=None, index=None)¶
Bases:
weka.core.classes.JavaObject
Wrapper for a Weka SingleIndex object.
- index()¶
Returns the integer index.
- Returns
the 0-based integer index
- Return type
int
- property single_index¶
Returns the string index.
- Returns
the 1-based string index
- Return type
str
- upper(upper)¶
Sets the upper limit.
- Parameters
upper (int) – the upper limit
- class weka.core.classes.Stoppable¶
Bases:
object
Classes that can be stopped.
- is_stopped()¶
Returns whether the object has been stopped.
- Returns
whether stopped
- Return type
bool
- stop_execution()¶
Triggers the stopping of the object.
- class weka.core.classes.Tag(jobject=None, ident=None, ident_str='', readable='', uppercase=True)¶
Bases:
weka.core.classes.JavaObject
Wrapper for the weka.core.Tag class.
- property ident¶
Returns the current integer ID of the tag.
- Returns
the integer ID
- Return type
int
- property identstr¶
Returns the current ID string.
- Returns
the ID string
- Return type
str
- property readable¶
Returns the ‘human readable’ string.
- Returns
the readable string
- Return type
str
- class weka.core.classes.Tags(jobject=None, tags=None)¶
Bases:
weka.core.classes.JavaObject
Wrapper for an array of weka.core.Tag objects.
- find(name)¶
Returns the Tag that matches the name.
- Parameters
name (str) – the string representation of the tag
- Returns
the tag, None if not found
- Return type
- classmethod get_object_tags(javaobject, methodname)¶
Instantiates the Tag array obtained from the object using the specified method name.
Example: cls = Classifier(classname=”weka.classifiers.meta.MultiSearch”) tags = Tags.get_object_tags(cls, “getMetricsTags”)
- Parameters
javaobject (JavaObject) – the javaobject to obtain the tags from
methodname (str) – the method name returning the Tag array
- Returns
the Tags objects
- Return type
- classmethod get_tags(classname, field)¶
Instantiates the Tag array located in the specified class with the given field name.
Example: tags = Tags.get_tags(“weka.classifiers.functions.SMO”, “TAGS_FILTER”)
- Parameters
classname (str) – the classname in which the tags reside
field (str) – the field name of the Tag array
- Returns
the Tags objects
- Return type
- weka.core.classes.backquote(s)¶
Backquotes the string.
- Parameters
s (str) – the string to process
- Returns
the backquoted string
- Return type
str
- weka.core.classes.complete_classname(classname)¶
Attempts to complete a partial classname like ‘.J48’ and returns the full classname if a single match was found, otherwise an exception is raised.
- Parameters
classname (str) – the partial classname to expand
- Returns
the full classname
- Return type
str
- weka.core.classes.deepcopy(obj)¶
Creates a deep copy of the JavaObject (or derived class) or JB_Object.
- Parameters
obj (object) – the object to create a copy of
- Returns
the copy, None if failed to copy
- Return type
object
- weka.core.classes.deregister_dict_handler(typestr)¶
Deregisters a handler for restoring an object from a JSON dictionary.
- Parameters
typestr (str) – the type of the object
- weka.core.classes.from_byte_array(array)¶
Deserializes Java objects from the numpy array.
- Parameters
array (ndarray) – the numpy array to deserialize the Java objects from
- Returns
the list of deserialized JB_Object instances
- Return type
list
- weka.core.classes.from_commandline(cmdline, classname=None)¶
Creates an OptionHandler based on the provided commandline string.
- Parameters
cmdline (str) – the commandline string to use
classname (str) – the classname of the wrapper to return other than OptionHandler (in dot-notation)
- Returns
the generated option handler instance
- Return type
object
- weka.core.classes.from_dict_handlers = {}¶
The methods that handle the restoration from a JSON dictionary, stored under their ‘type’.
- weka.core.classes.get_class(classname)¶
Returns the class object associated with the dot-notation classname.
Taken from here: http://stackoverflow.com/a/452981
- Parameters
classname (str) – the classname
- Returns
the class object
- Return type
object
- weka.core.classes.get_classname(obj)¶
Returns the classname of the JB_Object, Python class or object.
- Parameters
obj (object) – the java object or Python class/object to get the classname for
- Returns
the classname
- Return type
str
- weka.core.classes.get_dict_handler(typestr)¶
Returns the handler for restoring an object from a JSON dictionary.
- Parameters
typestr (str) – the type of the object
- Returns
the handler, None if not available
- weka.core.classes.get_enum(classname, enm)¶
Returns the instance of the enum.
- Parameters
classname (str) – the classname of the enum
enm (str) – the name of the enum element to return
- Returns
the enum instance
- Return type
JB_Object
- weka.core.classes.get_jclass(classname)¶
Returns the Java class object associated with the dot-notation classname.
- Parameters
classname (str) – the classname
- Returns
the class object
- Return type
JB_Object
- weka.core.classes.get_static_field(classname, fieldname, signature)¶
Returns the Java object associated with the static field of the specified class.
- Parameters
classname (str) – the classname of the class to get the field from
fieldname (str) – the name of the field to retriev
- Returns
the object
- Return type
JB_Object
- weka.core.classes.has_dict_handler(typestr)¶
Returns the handler for restoring an object from a JSON dictionary.
- Parameters
typestr (str) – the type of the object
- Returns
the handler, None if not available
- weka.core.classes.help_for(classname, title=True, description=True, options=True, use_headers=True, separator='')¶
Generates a help screen for the specified class.
- Parameters
classname (str) – the class to get the help screen for, must implement the OptionHandler interface
title (bool) – whether to output a title
description (bool) – whether to output the description
options (bool) – whether to output the options
use_headers (bool) – whether to output headers, describing the sections
separator (str) – the separator line to use between sections
- Returns
the help screen, None if not available
- Return type
str
- weka.core.classes.is_array(obj)¶
Checks whether the Java object is an array.
- Parameters
obj (JB_Object) – the Java object to check
- Returns
whether the object is an array
- Return type
bool
- weka.core.classes.is_instance_of(obj, class_or_intf_name)¶
Checks whether the Java object implements the specified interface or is a subclass of the superclass.
- Parameters
obj (JB_Object) – the Java object to check
class_or_intf_name (str) – the superclass or interface to check, dot notation or with forward slashes
- Returns
true if either implements interface or subclass of superclass
- Return type
bool
- weka.core.classes.join_options(options)¶
Turns the list of options back into a single commandline string.
- Parameters
options (list) – the list of options to process
- Returns
the combined options
- Return type
str
- weka.core.classes.list_property_names(obj)¶
Lists the property names (Bean properties, ie read/write method pair) of the Java object.
- Parameters
obj (JB_Object or JavaObject) – the object to inspect
- Returns
the list of property names
- Return type
list
- weka.core.classes.load_suggestions()¶
Loads the class/package suggestions, if necessary.
- weka.core.classes.main()¶
Runs a classifier from the command-line. Calls JVM start/stop automatically. Use -h to see all options.
- weka.core.classes.new_instance(classname)¶
Instantiates an object of the specified class. Does not raise an Exception if it fails to do so (opposed to JavaObject.new_instance).
- Parameters
classname (str) – the name of the class to instantiate
- Returns
the object, None if failed to instantiate
- Return type
JB_Object
- weka.core.classes.quote(s)¶
Quotes the string if necessary.
- Parameters
s (str) – the string to process
- Returns
the quoted string
- Return type
str
- weka.core.classes.register_dict_handler(typestr, handler)¶
Registers a handler for restoring an object from a JSON dictionary.
- Parameters
typestr (str) – the type of the object
handler – the method
- weka.core.classes.serialization_read(filename)¶
Reads the serialized object from disk. Caller must wrap object in appropriate Python wrapper class.
- Parameters
filename (str) – the file with the serialized object
- Returns
the JB_Object
- Return type
JB_Object
- weka.core.classes.serialization_read_all(filename)¶
Reads the serialized objects from disk. Caller must wrap objects in appropriate Python wrapper classes.
- Parameters
filename (str) – the file with the serialized objects
- Returns
the list of JB_OBjects
- Return type
list
- weka.core.classes.serialization_write(filename, jobject)¶
Serializes the object to disk. JavaObject instances get automatically unwrapped.
- Parameters
filename (str) – the file to serialize the object to
jobject (JB_Object or JavaObject) – the object to serialize
- weka.core.classes.serialization_write_all(filename, jobjects)¶
Serializes the list of objects to disk. JavaObject instances get automatically unwrapped.
- Parameters
filename (str) – the file to serialize the object to
jobjects (list) – the list of objects to serialize
- weka.core.classes.split_options(cmdline)¶
Splits the commandline into a list of options.
- Parameters
cmdline (str) – the commandline string to split into individual options
- Returns
the split list of commandline options
- Return type
list
- weka.core.classes.suggest_package(name, exact=False)¶
Suggests package(s) for the given name (classname, package name). Matching can be either exact or just a substring.
- Parameters
name (str) – the name to look for
exact (bool) – whether to perform exact matching or substring matching
- Returns
list of matching package names
- Return type
list
- weka.core.classes.suggestions = None¶
dictionary for class -> package relation
- weka.core.classes.to_byte_array(jobjects)¶
Serializes the list of objects into a numpy array.
- Parameters
jobjects (list) – the list of objects to serialize
- Returns
the numpy array
- Return type
ndarray
- weka.core.classes.to_commandline(optionhandler)¶
Generates a commandline string from the OptionHandler instance.
- Parameters
optionhandler (OptionHandler) – the OptionHandler instance to turn into a commandline
- Returns
the commandline string
- Return type
str
- weka.core.classes.unbackquote(s)¶
Un-backquotes the string.
- Parameters
s (str) – the string to process
- Returns
the un-backquoted string
- Return type
str
- weka.core.classes.unquote(s)¶
Un-quotes the string.
- Parameters
s (str) – the string to process
- Returns
the un-quoted string
- Return type
str
weka.core.converters module¶
- class weka.core.converters.IncrementalLoaderIterator(loader, structure)¶
Bases:
object
Iterator for dataset rows when loarding incrementally.
- class weka.core.converters.Loader(classname='weka.core.converters.ArffLoader', jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Wrapper class for Loaders.
- load_file(dfile, incremental=False, class_index=None)¶
Loads the specified file and returns the Instances object. In case of incremental loading, only the structure.
- Parameters
dfile (str) – the file to load
incremental (bool) – whether to load the dataset incrementally
class_index (str) – the class index string to use (‘first’, ‘second’, ‘third’, ‘last-2’, ‘last-1’, ‘last’ or 1-based index)
- Returns
the full dataset or the header (if incremental)
- Return type
- Raises
Exception – if the file does not exist
- load_url(url, incremental=False)¶
Loads the specified URL and returns the Instances object. In case of incremental loading, only the structure.
- Parameters
url (str) – the URL to load the data from
incremental (bool) – whether to load the dataset incrementally
- Returns
the full dataset or the header (if incremental)
- Return type
- class weka.core.converters.Saver(classname='weka.core.converters.ArffSaver', jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Wrapper class for Savers.
- capabilities()¶
Returns the capabilities of the saver.
- Returns
the capabilities
- Return type
- class weka.core.converters.TextDirectoryLoader(jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Wrapper class for TextDirectoryLoader.
- weka.core.converters.load_any_file(filename, class_index=None)¶
Determines a Loader based on the the file extension. If successful, loads the full dataset and returns it.
- Parameters
filename (str) – the name of the file to load
class_index (str) – the class index string to use (‘first’, ‘second’, ‘third’, ‘last-2’, ‘last-1’, ‘last’ or 1-based index)
- Returns
the
- Return type
- weka.core.converters.loader_for_file(filename)¶
Returns a Loader that can load the specified file, based on the file extension. None if failed to determine.
- Parameters
filename (str) – the filename to get the loader for
- Returns
the assoicated loader instance or None if none found
- Return type
- weka.core.converters.ndarray_to_instances(array, relation, att_template='Att-#', att_list=None)¶
Converts the numpy matrix into an Instances object and returns it.
- Parameters
array (numpy.darray) – the numpy ndarray to convert
relation (str) – the name of the dataset
att_template (str) – the prefix to use for the attribute names, “#” is the 1-based index, “!” is the 0-based index, “@” the relation name
att_list (list) – the list of attribute names to use
- Returns
the generated instances object
- Return type
weka.core.database module¶
- class weka.core.database.DatabaseUtils(jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Wrapper class for weka.experiment.DatabaseUtils.
- property db_url¶
Obtains the currently set database URL.
- Returns
the database URL
- Return type
str
- property password¶
Obtains the currently set database password.
- Returns
the database password
- Return type
str
- property user¶
Obtains the currently set database user.
- Returns
the database user
- Return type
str
- class weka.core.database.InstanceQuery(jobject=None, options=None)¶
Bases:
weka.core.database.DatabaseUtils
Wrapper class for weka.experiment.InstanceQuery.
- property custom_properties¶
Obtains the currently set custom properties file.
- Returns
the custom properties file
- Return type
str
- property query¶
Obtains the current SQL query to execute.
- Returns
the SQL query
- Return type
str
- retrieve_instances(query=None)¶
Executes either the supplied query or the one set via options (or the ‘query’ property).
- Parameters
query (str) – query to execute if not the currently set one
- Returns
the generated dataq
- Return type
- property sparse_data¶
Obtains the whether sparse data is returned or not.
- Returns
whether sparse data is generated
- Return type
bool
weka.core.dataset module¶
- class weka.core.dataset.Attribute(jobject)¶
Bases:
weka.core.classes.JavaObject
Wrapper class for weka.core.Attribute.
- add_relation(instances)¶
Adds the relation value, returns the index.
- Parameters
instances (Instances) – the Instances object to add
- Returns
the index
- Return type
int
- add_string_value(s)¶
Adds the string value, returns the index.
- Parameters
s (str) – the string to add
- Returns
the index
- Return type
int
- copy(name=None)¶
Creates a copy of this attribute.
- Parameters
name (str) – the new name, uses the old one if None
- Returns
the copy of the attribute
- Return type
- classmethod create_date(name, formt="yyyy-MM-dd'T'HH:mm:ss")¶
Creates a date attribute.
- Parameters
name (str) – the name of the attribute
formt (str) – the date format, see Javadoc for java.text.SimpleDateFormat
- classmethod create_nominal(name, labels)¶
Creates a nominal attribute.
- Parameters
name (str) – the name of the attribute
labels (list) – the list of string labels to use
- classmethod create_numeric(name)¶
Creates a numeric attribute.
- Parameters
name (str) – the name of the attribute
- classmethod create_relational(name, inst)¶
Creates a relational attribute.
- Parameters
name (str) – the name of the attribute
inst (Instances) – the structure of the relational attribute
- classmethod create_string(name)¶
Creates a string attribute.
- Parameters
name (str) – the name of the attribute
- property date_format¶
Returns the format of this data attribute. See java.text.SimpleDateFormat Javadoc.
- Returns
the format string
- Return type
str
- equals(att)¶
Checks whether this attributes is the same as the provided one.
- Parameters
att (Attribute) – the Attribute to check against
- Returns
whether the same
- Return type
bool
- equals_msg(att)¶
Checks whether this attributes is the same as the provided one. Returns None if the same, otherwise error message.
- Parameters
att (Attribute) – the Attribute to check against
- Returns
None if the same, otherwise error message
- Return type
str
- property index¶
Returns the index of this attribute.
- Returns
the index
- Return type
int
- index_of(label)¶
Returns the index of the label in this attribute.
- Parameters
label (str) – the string label to get the index for
- Returns
the 0-based index
- Return type
int
- property is_averagable¶
Returns whether the attribute is averagable.
- Returns
whether averagable
- Return type
bool
- property is_date¶
Returns whether the attribute is a date one.
- Returns
whether date attribute
- Return type
bool
- is_in_range(value)¶
Checks whether the value is within the bounds of the numeric attribute.
- Parameters
value (float) – the numeric value to check
- Returns
whether between lower and upper bound
- Return type
bool
- property is_nominal¶
Returns whether the attribute is a nominal one.
- Returns
whether nominal attribute
- Return type
bool
- property is_numeric¶
Returns whether the attribute is a numeric one (date or numeric).
- Returns
whether numeric attribute
- Return type
bool
- property is_relation_valued¶
Returns whether the attribute is a relation valued one.
- Returns
whether relation valued attribute
- Return type
bool
- property is_string¶
Returns whether the attribute is a string attribute.
- Returns
whether string attribute
- Return type
bool
- property lower_numeric_bound¶
Returns the lower numeric bound of the numeric attribute.
- Returns
the lower bound
- Return type
float
- property name¶
Returns the name of the attribute.
- Returns
the name
- Return type
str
- property num_values¶
Returns the number of labels.
- Returns
the number of labels
- Return type
int
- property ordering¶
Returns the ordering of the attribute.
- Returns
the ordering (ORDERING_SYMBOLIC, ORDERING_ORDERED, ORDERING_MODULO)
- Return type
int
- parse_date(s)¶
Parses the date string and returns the internal format value.
- Parameters
s (str) – the date string
- Returns
the internal format
- Return type
float
- property type¶
Returns the type of the attribute. See weka.core.Attribute Javadoc.
- Returns
the type
- Return type
int
- type_str(short=False)¶
Returns the type of the attribute as string.
- Returns
the type
- Return type
str
- property upper_numeric_bound¶
Returns the upper numeric bound of the numeric attribute.
- Returns
the upper bound
- Return type
float
- value(index)¶
Returns the label for the index.
- Parameters
index (int) – the 0-based index of the label to return
- Returns
the label
- Return type
str
- property values¶
Returns the labels, strings or relation-values.
- Returns
all the values, None if not NOMINAL, STRING, or RELATION
- Return type
list
- property weight¶
Returns the weight of the attribute.
- Returns
the weight
- Return type
float
- class weka.core.dataset.AttributeIterator(data)¶
Bases:
object
Iterator for attributes in an Instances object.
- class weka.core.dataset.AttributeStats(jobject)¶
Bases:
weka.core.classes.JavaObject
Container for attribute statistics.
- property distinct_count¶
The number of distinct values.
- Returns
The number of distinct values
- Return type
int
- property int_count¶
The number of int-like values.
- Returns
The number of int-like values
- Return type
int
- property missing_count¶
The number of missing values.
- Returns
The number of missing values
- Return type
int
- property nominal_counts¶
Counts of each nominal value.
- Returns
Counts of each nominal value
- Return type
ndarray
- property nominal_weights¶
Weight mass for each nominal value.
- Returns
Weight mass for each nominal value
- Return type
ndarray
- property numeric_stats¶
Stats on numeric value distributions.
- Returns
Stats on numeric value distributions
- Return type
NumericStats
- property total_count¶
The total number of values.
- Returns
The total number of values
- Return type
int
- property unique_count¶
The number of values that only appear once.
- Returns
The number of values that only appear once
- Return type
int
- class weka.core.dataset.Instance(jobject)¶
Bases:
weka.core.classes.JavaObject
Wrapper class for weka.core.Instance.
- property class_attribute¶
Returns the currently set class attribute.
- Returns
the class attribute
- Return type
- property class_index¶
Returns the currently set class index.
- Returns
the class index, -1 if not set
- Return type
int
- classmethod create_instance(values, classname='weka.core.DenseInstance', weight=1.0)¶
Creates a new instance.
- Parameters
values (ndarray or list) – the float values (internal format) to use, numpy array or list.
classname (str) – the classname of the instance (eg weka.core.DenseInstance).
weight (float) – the weight of the instance
- classmethod create_sparse_instance(values, max_values, classname='weka.core.SparseInstance', weight=1.0)¶
Creates a new sparse instance.
- Parameters
values (list) – the list of tuples (0-based index and internal format float). The indices of the tuples must be in ascending order and “max_values” must be set to the maximum number of attributes in the dataset.
max_values (int) – the maximum number of attributes
classname (str) – the classname of the instance (eg weka.core.SparseInstance).
weight (float) – the weight of the instance
- property dataset¶
Returns the dataset that this instance belongs to.
- Returns
the dataset or None if no dataset set
- Return type
- get_relational_value(index)¶
Returns the relational value at the specified position (0-based).
- Parameters
index (int) – the 0-based index of the inernal value
- Returns
the relational value
- Return type
- get_string_value(index)¶
Returns the string value at the specified position (0-based).
- Parameters
index (int) – the 0-based index of the inernal value
- Returns
the string value
- Return type
str
- get_value(index)¶
Returns the internal value at the specified position (0-based).
- Parameters
index (int) – the 0-based index of the inernal value
- Returns
the internal value
- Return type
float
- has_class()¶
Returns whether a class attribute is set (convenience method).
- Returns
whether a class attribute is currently set
- Return type
bool
- has_missing()¶
Returns whether at least one attribute has a missing value.
- Returns
whether at least one value is missing
- Return type
bool
- is_missing(index)¶
Returns whether the attribute at the specified index is missing.
- Parameters
index (int) – the 0-based index of the attribute
- Returns
whether the value is missing
- Return type
bool
- classmethod missing_value()¶
Returns the numeric value that represents a missing value in Weka (NaN).
- Returns
missing value
- Return type
float
- property num_attributes¶
Returns the number of attributes.
- Returns
the numer of attributes
- Return type
int
- property num_classes¶
Returns the number of class labels.
- Returns
the numer of class labels
- Return type
int
- set_missing(index)¶
Sets the attribute at the specified index to missing.
- Parameters
index (int) – the 0-based index of the attribute
- set_string_value(index, s)¶
Sets the string value at the specified position (0-based).
- Parameters
index (int) – the 0-based index of the inernal value
s (str) – the string value
- set_value(index, value)¶
Sets the internal value at the specified position (0-based).
- Parameters
index (int) – the 0-based index of the attribute
value (float) – the internal float value to set
- to_numpy(internal=False)¶
Turns the instance into a numpy matrix.
- Parameters
internal (bool) – whether to return the internal format
- Returns
the dataset as matrix with single row
- Return type
np.ndarray
- property values¶
Returns the internal values of this instance.
- Returns
the values as numpy array
- Return type
ndarray
- property weight¶
Returns the currently set weight.
- Returns
the weight
- Return type
float
- class weka.core.dataset.InstanceIterator(data)¶
Bases:
object
Iterator for rows in an Instances object.
- class weka.core.dataset.InstanceValueIterator(data)¶
Bases:
object
Iterator for values in an Instance object.
- class weka.core.dataset.Instances(jobject)¶
Bases:
weka.core.classes.JavaObject
Wrapper class for weka.core.Instances.
- add_instance(inst, index=None)¶
Adds the specified instance to the dataset.
- Parameters
inst (Instance) – the Instance to add
index (int) – the 0-based index where to add the Instance
- classmethod append_instances(inst1, inst2)¶
Merges the two datasets (one-after-the-other). Throws an exception if the datasets aren’t compatible.
- attribute(index)¶
Returns the specified attribute.
- Parameters
index (int) – the 0-based index of the attribute
- Returns
the attribute
- Return type
- attribute_by_name(name)¶
Returns the specified attribute, None if not found.
- Parameters
name (str) – the name of the attribute
- Returns
the attribute or None
- Return type
- attribute_names()¶
Returns a list of all the attribute names.
- Returns
list of attribute names
- Return type
list
- attribute_stats(index)¶
Returns the specified attribute statistics.
- Parameters
index (int) – the 0-based index of the attribute
- Returns
the attribute statistics
- Return type
- attributes()¶
Returns an iterator over the attributes.
- property class_attribute¶
Returns the currently set class attribute.
- Returns
the class attribute
- Return type
- property class_index¶
Returns the currently set class index (0-based).
- Returns
the class index, -1 if not set
- Return type
int
- class_is_first()¶
Sets the first attribute as class attribute (convenience method).
- class_is_last()¶
Sets the last attribute as class attribute (convenience method).
- compactify()¶
Compactifies the set of instances.
- classmethod copy_instances(dataset, from_row=None, num_rows=None)¶
Creates a copy of the Instances. If either from_row or num_rows are None, then all of the data is being copied.
- copy_structure()¶
Returns a copy of the dataset structure.
- Returns
the structure of the dataset
- Return type
- classmethod create_instances(name, atts, capacity)¶
Creates a new Instances.
- Parameters
name (str) – the relation name
atts (list of Attribute) – the list of attributes to use for the dataset
capacity (int) – how many data rows to reserve initially (see compactify)
- Returns
the dataset
- Return type
- cv_splits(folds=10, rnd=None, stratify=True)¶
Generates a list of train/test pairs used in cross-validation. Creates a copy of the dataset beforehand when randomizing.
- Parameters
folds (int) – the number of folds to use, >= 2
rnd (Random) – the random number generator to use for randomization, skips randomization if None
stratify (bool) – whether to stratify the data after randomization
- Returns
the list of train/test split tuples
- Return type
list
- delete(index=None)¶
Removes either the specified Instance or all Instance objects.
- Parameters
index (int) – the 0-based index of the instance to remove
- delete_attribute(index)¶
Deletes an attribute at the given position.
- Parameters
index (int) – the 0-based index of the attribute to remove
- delete_attribute_type(typ)¶
Deletes all attributes of the given type in the dataset.
- Parameters
typ (int) – the attribute type to remove, see weka.core.Attribute Javadoc
- delete_first_attribute()¶
Deletes the first attribute.
- delete_last_attribute()¶
Deletes the last attribute.
- delete_with_missing(index)¶
Deletes all rows that have a missing value at the specified attribute index.
- Parameters
index (int) – the attribute index to check for missing attributes
- equal_headers(inst)¶
Compares this dataset against the given one in terms of attributes.
- Parameters
inst (Instances) – the dataset to compare against
- Returns
None if the same, otherwise an error message
- Return type
str
- get_instance(index)¶
Returns the Instance object at the specified location.
- Parameters
index (int) – the 0-based index of the instance
- Returns
the instance
- Return type
- has_class()¶
Returns whether a class attribute is set (convenience method).
- Returns
whether a class attribute is currently set
- Return type
bool
- insert_attribute(att, index)¶
Inserts the attribute at the specified location.
- Parameters
att (Attribute) – the attribute to insert
index (int) – the index to insert the attribute at
- classmethod merge_instances(inst1, inst2)¶
Merges the two datasets (side-by-side).
- no_class()¶
Unsets the class attribute (convenience method).
- property num_attributes¶
Returns the number of attributes.
- Returns
the number of attributes
- Return type
int
- property num_instances¶
Returns the number of instances.
- Returns
the number of instances
- Return type
int
- randomize(random)¶
Randomizes the dataset using the random number generator.
- Parameters
random (Random) – the random number generator to use
- property relationname¶
Returns the name of the dataset.
- Returns
the name
- Return type
str
- set_instance(index, inst)¶
Sets the Instance at the specified location in the dataset.
- sort(index)¶
Sorts the dataset using the specified attribute index.
- Parameters
index (int) – the index of the attribute
- stratify(folds)¶
Stratifies the data after randomization for nominal class attributes.
- Parameters
folds (int) – the number of folds to perform the stratification for
- subset(col_range=None, col_names=None, invert_cols=False, row_range=None, invert_rows=False, keep_relationame=False)¶
Returns a subset of attributes/rows of the Instances object. If neither attributes nor rows have been specified a copy of the dataset gets returned. The invers of the specified cols/rows can be returned by setting invert_cols and/or invert_rows to True. The method uses the weka.filters.unsupervised.attribute.Remove and weka.filters.unsupervised.instance.RemoveRange filters under the hood.
- Parameters
col_range (str) – the subset of attributes to return (eg ‘1-3,7-12,67-last’), None for all
col_names (list) – the list of attributes to return (list of names; case-sensitive), takes precedence over col_range
invert_cols (bool) – whether to invert the returned attributes
row_range (str) – the subset of rows to return (eg ‘1-3,7-12,67-last’), None for all
invert_rows (bool) – whether to invert the returned rows
keep_relationame (bool) – whether to keep the original relation name
- Returns
the subset
- Return type
- classmethod summary(inst)¶
Generates a summary of the dataset.
- Parameters
inst (Instances) – the dataset
- Returns
the summary
- Return type
str
- classmethod template_instances(dataset, capacity=0)¶
Uses the Instances as template to create an empty dataset.
- test_cv(num_folds, fold)¶
Generates a test fold for cross-validation.
- Parameters
num_folds (int) – the number of folds of cross-validation, eg 10
fold (int) – the current fold (0-based)
- Returns
the training fold
- Return type
- to_numpy(internal=False)¶
Turns the dataset into a numpy matrix.
- Parameters
internal (bool) – whether to return the internal format
- Returns
the dataset as matrix
- Return type
np.ndarray
- train_cv(num_folds, fold, random=None)¶
Generates a training fold for cross-validation.
- train_test_split(percentage, rnd=None)¶
Generates a train/test split. Creates a copy of the dataset first before applying randomization.
- Parameters
percentage (double) – the percentage split to use (amount to use for training; 0-100)
rnd (Random) – the random number generator to use, if None the order gets preserved
- Returns
the train/test splits
- Return type
tuple
- values(index)¶
Returns the internal values of this attribute from all the instance objects.
- Returns
the values as numpy array
- Return type
list
- class weka.core.dataset.Stats(jobject)¶
Bases:
weka.core.classes.JavaObject
Container for numeric attribute stats.
- property count¶
The number of values seen.
- Returns
The number of values seen
- Return type
float
- property max¶
The maximum value seen, or Double.NaN if no values seen.
- Returns
The maximum value seen, or Double.NaN if no values seen
- Return type
float
- property mean¶
The mean of values at the last calculateDerived() call.
- Returns
The mean of values at the last calculateDerived() call
- Return type
float
- property min¶
The minimum value seen, or Double.NaN if no values seen.
- Returns
The minimum value seen, or Double.NaN if no values seen
- Return type
float
- property stddev¶
The std deviation of values at the last calculateDerived() call.
- Returns
The std deviation of values at the last calculateDerived() call
- Return type
float
- property sum¶
The sum of values seen.
- Returns
The sum of values seen
- Return type
float
- property sumsq¶
The sum of values squared seen.
- Returns
The sum of values squared seen
- Return type
float
- weka.core.dataset.check_col_names_unique(cols_x, col_y=None)¶
Checks whether the column names are unique (a requirement for Instances objects).
- Parameters
cols_x (list) – the column names for the input variables
col_y (str) – the optional name for the output variable
- Returns
None if check passed, otherwise error message
- Return type
str
- weka.core.dataset.create_instances_from_lists(x, y=None, name='data', cols_x=None, col_y=None)¶
Allows the generation of an Instances object from a list of lists for X and a list for Y (optional). Data can be numeric, string or bytes. Attributes can be converted to nominal with the weka.filters.unsupervised.attribute.NumericToNominal filter.
- Parameters
x (list of list) – the input variables (row wise)
y (list) – the output variable (optional)
name (str) – the name of the dataset
cols_x (list) – the column names to use
col_y (str) – the column name to use for the output variable (y)
- Returns
the generated dataset
- Return type
- weka.core.dataset.create_instances_from_matrices(x, y=None, name='data', cols_x=None, col_y=None)¶
Allows the generation of an Instances object from a 2-dimensional matrix for X and a 1-dimensional matrix for Y (optional). Data can be numeric, string or bytes. Attributes can be converted to nominal with the weka.filters.unsupervised.attribute.NumericToNominal filter.
- Parameters
x (ndarray) – the input variables
y (ndarray) – the output variable (optional)
name (str) – the name of the dataset
cols_x (list) – the column names to use
col_y (str) – the column name to use for the output variable (y)
- Returns
the generated dataset
- Return type
- weka.core.dataset.missing_value()¶
Returns the value that represents missing values in Weka (NaN).
- Returns
missing value
- Return type
float
weka.core.distances module¶
- class weka.core.distances.DistanceFunction(classname='weka.core.EuclideanDistance', jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Wrapper for Weka’s weka.core.DistanceFunction interface.
- property attribute_indices¶
Returns the attribute indices in use.
- Returns
the attribute indices
- Return type
str
- distance(first, second, cutoff=None)¶
Computes the distance between the two Instance objects.
weka.core.jvm module¶
- weka.core.jvm.add_bundled_jars()¶
Adds the bundled jars to the JVM’s classpath.
- weka.core.jvm.add_system_classpath()¶
Adds the system’s classpath to the JVM’s classpath.
- weka.core.jvm.automatically_install_packages = None¶
whether to automatically install missing packages
- weka.core.jvm.lib_dir()¶
Returns the “lib” directory path.
- Returns
the path to the “lib” directory
- Return type
str
- weka.core.jvm.start(class_path=None, bundled=True, packages=False, system_cp=False, max_heap_size=None, system_info=False, auto_install=False, logging_level=10)¶
Initializes the javabridge connection (starts up the JVM).
- Parameters
class_path (list) – the additional classpath elements to add
bundled (bool) – whether to add jars from the “lib” directory
packages (bool or str) – whether to add jars from Weka packages as well (bool) or an alternative Weka home directory (str)
system_cp (bool) – whether to add the system classpath as well
max_heap_size (str) – the maximum heap size (-Xmx parameter, eg 512m or 4g)
system_info (bool) – whether to print the system info (generated by weka.core.SystemInfo)
auto_install (bool) – whether to automatically install missing Weka packages (based on suggestions); in conjunction with package support
logging_level (int) – the logging level to use for this module, e.g., logging.DEBUG or logging.INFO
- weka.core.jvm.started = None¶
whether the JVM has been started
- weka.core.jvm.stop()¶
Kills the JVM.
- weka.core.jvm.with_package_support = None¶
whether JVM was started with package support
weka.core.packages module¶
- class weka.core.packages.Dependency(jobject)¶
Bases:
weka.core.classes.JavaObject
Wrapper for the weka.core.packageManagement.Dependency class.
- property target¶
Returns the target package constraint.
- Returns
the package constraint
- Return type
- weka.core.packages.LATEST = 'Latest'¶
Constant for the latest version of a package
- class weka.core.packages.Package(jobject)¶
Bases:
weka.core.classes.JavaObject
Wrapper for the weka.core.packageManagement.Package class.
- as_dict()¶
Turns the package information into a dictionary. Not to be confused with ‘to_dict’!
- Returns
the package information as dictionary
- Return type
dict
- property dependencies¶
Returns the dependencies of the package.
- Returns
the list of Dependency objects
- Return type
list of Dependency
- install()¶
Installs the package.
- property is_installed¶
Returns whether the package is installed.
- Returns
whether installed
- Return type
bool
- property metadata¶
Returns the meta-data.
- Returns
the meta-data dictionary
- Return type
dict
- property name¶
Returns the name of the package.
- Returns
the name
- Return type
str
- property url¶
Returns the URL of the package.
- Returns
the url
- Return type
str
- property version¶
Returns the version of the package.
- Returns
the version
- Return type
str
- class weka.core.packages.PackageConstraint(jobject)¶
Bases:
weka.core.classes.JavaObject
Wrapper for the weka.core.packageManagement.PackageConstraint class.
- check_constraint(pkge=None, constr=None)¶
Checks the constraints.
- Parameters
pkge (Package) – the package to check
constr (PackageConstraint) – the package constraint to check
- weka.core.packages.all_package(name)¶
Returns Package object for the specified package (either installed or available). Returns None if not found.
- Parameters
name (str) – the name of the package to retrieve
- Returns
the package information, None if not available
- Return type
- weka.core.packages.all_packages()¶
Returns a list of all packages.
- Returns
the list of packages
- Return type
list
- weka.core.packages.available_package(name)¶
Returns Package object for the specified, available package. Returns None if not installed.
- Parameters
name (str) – the name of the available package to retrieve
- Returns
the package information
- Return type
- weka.core.packages.available_packages()¶
Returns a list of all packages that aren’t installed yet.
- Returns
the list of packages
- Return type
list
- weka.core.packages.establish_cache()¶
Establishes the package cache if necessary.
- weka.core.packages.install_missing_package(pkge, version='Latest', quiet=False, stop_jvm_and_exit=False)¶
Installs the package if not yet installed.
- Parameters
pkge (str) – the name of the repository package, a URL (http/https) or a zip file
version (str) – in case of the repository packages, the version
quiet (bool) – whether to suppress console output and only print error messages
stop_jvm_and_exit (bool) – whether to stop the JVM and exit if anything was installed
- Returns
tuple of (success, exit_required); “success” being True if either nothing to install or all successfully installed, False otherwise; “exit_required” being True if at least one package was installed and the JVM needs restarting
- Return type
tuple
- weka.core.packages.install_missing_packages(pkges, quiet=False, stop_jvm_and_exit=False)¶
Installs the missing packages.
- Parameters
pkges (the packages to install) – list of tuples (packagename, version), use “Latest” or LATEST constant to grab latest version
quiet (bool) – whether to suppress console output and only print error messages
stop_jvm_and_exit (bool) – whether to stop the JVM and exit if anything was installed
- Returns
tuple of (success, exit_required); “success” being True if either nothing to install or all successfully installed, False otherwise; “exit_required” being True if at least one package was installed and the JVM needs restarting
- Return type
tuple
- weka.core.packages.install_package(pkge, version='Latest')¶
Installs the specified package.
- Parameters
pkge (str) – the name of the repository package, a URL (http/https) or a zip file
version (str) – in case of the repository packages, the version
- Returns
whether successfully installed
- Return type
bool
- weka.core.packages.install_packages(pkges)¶
Installs the specified package.
- Parameters
pkge (str) – the name of the repository package, a URL (http/https) or a zip file
version (str) – in case of the repository packages, the version
- Returns
whether successfully installed
- Return type
bool
- weka.core.packages.installed_package(name)¶
Returns Package object for the specified, installed package. Returns None if not installed.
- Parameters
name (str) – the name of the installed package to retrieve
- Returns
the package information
- Return type
- weka.core.packages.installed_packages()¶
Returns a list of the installed packages.
- Returns
the list of packages
- Return type
list
- weka.core.packages.is_installed(name, version=None)¶
Checks whether a package with the name is already installed.
- Parameters
name (str) – the name of the package
version (str) – the version to check as well, ignored if None
- Returns
whether the package is installed
- Return type
bool
- weka.core.packages.main(args=None)¶
Performs the specified package operation from the command-line. Calls JVM start/stop automatically. Use -h to see all options.
- Parameters
args (list) – the command-line arguments to use, uses sys.argv if None
- weka.core.packages.refresh_cache()¶
Refreshes the cache.
- weka.core.packages.suggest_package(name, exact=False)¶
Suggests package(s) for the given name (classname, package name). Matching can be either exact or just a substring.
- Parameters
name (str) – the name to look for
exact (bool) – whether to perform exact matching or substring matching
- Returns
list of matching package names
- Return type
list
- weka.core.packages.sys_main()¶
Runs the main function using the system cli arguments, and returns a system error code.
- Returns
0 for success, 1 for failure.
- Return type
int
- weka.core.packages.uninstall_package(name)¶
Uninstalls a package.
- Parameters
name (str) – the name of the package
- weka.core.packages.uninstall_packages(names)¶
Uninstalls a package.
- Parameters
name (list) – the names of the package
weka.core.serialization module¶
weka.core.stemmers module¶
- class weka.core.stemmers.Stemmer(classname='weka.core.stemmers.NullStemmer', jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Wrapper class for stemmers.
- stem(s)¶
Performs stemming on the string.
- Parameters
s (str) – the string to stem
- Returns
the stemmed string
- Return type
str
weka.core.stopwords module¶
- class weka.core.stopwords.Stopwords(classname='weka.core.stopwords.Null', jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Wrapper class for stopwords handlers.
- is_stopword(s)¶
Checks a string whether it is a stopword.
- Parameters
s (str) – the string to check
- Returns
True if a stopword
- Return type
bool
weka.core.tokenizers module¶
- class weka.core.tokenizers.TokenIterator(tokenizer)¶
Bases:
object
Iterator for string tokens.
- class weka.core.tokenizers.Tokenizer(classname='weka.core.tokenizers.AlphabeticTokenizer', jobject=None, options=None)¶
Bases:
weka.core.classes.OptionHandler
Wrapper class for tokenizers.
- tokenize(s)¶
Tokenizes the string.
- Parameters
s (str) – the string to tokenize
- Returns
the iterator
- Return type
weka.core.typeconv module¶
- weka.core.typeconv.float_to_jfloat(d)¶
Turns the Python float into a Java java.lang.Float object.
- Parameters
d (float) – the Python float
- Returns
the Float object
- Return type
JB_Object
- weka.core.typeconv.jdouble_matrix_to_ndarray(m)¶
Turns the Java matrix (2-dim array) of doubles into a numpy 2-dim array.
- Parameters
m – the double matrix
- Type
JB_Object
- Returns
Numpy array
- Return type
numpy.darray
- weka.core.typeconv.jdouble_to_float(d)¶
Turns the Java java.lang.Double object into Python float object.
- Parameters
d (JB_Object) – the java.lang.Double
- Returns
the Float object
- Return type
float
- weka.core.typeconv.jenumeration_to_list(enm)¶
Turns the java.util.Enumeration into a list.
- Parameters
enm (JB_Object) – the enumeration to convert
- Returns
the list
- Return type
list
- weka.core.typeconv.jstring_array_to_list(a)¶
Turns the Java string array into Python unicode string list.
- Parameters
a (JB_Object) – the string array to convert
- Returns
the string list
- Return type
list
- weka.core.typeconv.jstring_list_to_string_list(l, return_empty_if_none=True)¶
Converts a Java java.util.List containing strings into a Python list.
- Parameters
l (JB_Object) – the list to convert
return_empty_if_none (bool) – whether to return an empty list or None when list object is None
- Returns
the list with UTF strings
- Return type
list
- weka.core.typeconv.string_list_to_jarray(l)¶
Turns a Python unicode string list into a Java String array.
- Parameters
l – the string list
- Type
list
- Return type
java string array
- Returns
JB_Object
weka.core.version module¶
- weka.core.version.weka_version()¶
Determines the version of Weka in use.
- Returns
the version
- Return type
str