def main(args):
"""
Trains Apriori on the specified dataset (uses vote UCI dataset if no dataset specified).
:param args: the commandline arguments
:type args: list
"""
# load a dataset
if len(args) <= 1:
data_file = helper.get_data_dir() + os.sep + "vote.arff"
else:
data_file = args[1]
helper.print_info("Loading dataset: " + data_file)
loader = Loader("weka.core.converters.ArffLoader")
data = loader.load_file(data_file)
data.class_is_last()
# build Apriori, using last attribute as class attribute
apriori = Associator(classname="weka.associations.Apriori", options=["-c", "-1"])
apriori.build_associations(data)
print(str(apriori))
# iterate association rules (low-level)
helper.print_info("Rules (low-level)")
# make the underlying rules list object iterable in Python
rules = javabridge.iterate_collection(apriori.jwrapper.getAssociationRules().getRules().o)
for i, r in enumerate(rules):
# wrap the Java object to make its methods accessible
rule = JWrapper(r)
print(str(i+1) + ". " + str(rule))
# output some details on rule
print(" - consequence support: " + str(rule.getConsequenceSupport()))
print(" - premise support: " + str(rule.getPremiseSupport()))
print(" - total support: " + str(rule.getTotalSupport()))
print(" - total transactions: " + str(rule.getTotalTransactions()))
# iterate association rules (high-level)
helper.print_info("Rules (high-level)")
print("can produce rules? " + str(apriori.can_produce_rules()))
print("rule metric names: " + str(apriori.rule_metric_names))
rules = apriori.association_rules()
if rules is not None:
print("producer: " + rules.producer)
print("# rules: " + str(len(rules)))
for i, rule in enumerate(rules):
print(str(i+1) + ". " + str(rule))
# output some details on rule
print(" - consequence support: " + str(rule.consequence_support))
print(" - consequence: " + str(rule.consequence))
print(" - premise support: " + str(rule.premise_support))
print(" - premise: " + str(rule.premise))
print(" - total support: " + str(rule.total_support))
print(" - total transactions: " + str(rule.total_transactions))
print(" - metric names: " + str(rule.metric_names))
print(" - metric values: " + str(rule.metric_values))
print(" - metric value 'Confidence': " + str(rule.metric_value('Confidence')))
print(" - primary metric name: " + str(rule.primary_metric_name))
print(" - primary metric value: " + str(rule.primary_metric_value))
class ModuleInfo(object):
def __init__(self):
self.o = instance
getInput = J.make_method(
"getInput",
"(Ljava/lang/String;)Lorg/scijava/module/ModuleItem;",
doc = "Gets the input item with the given name.",
fn_post_process=wrap_module_item)
getOutput = J.make_method(
"getOutput",
"(Ljava/lang/String;)Lorg/scijava/module/ModuleItem;",
doc = "Gets the output item with the given name.",
fn_post_process=wrap_module_item)
getInputs = J.make_method(
"inputs", "()Ljava/lang/Iterable;",
"""Get the module info's input module items""",
fn_post_process=lambda iterator:
map(wrap_module_item, J.iterate_collection(iterator)))
getOutputs = J.make_method(
"outputs", "()Ljava/lang/Iterable;",
"""Get the module info's output module items""",
fn_post_process=lambda iterator:
map(wrap_module_item, J.iterate_collection(iterator)))
getTitle = J.make_method(
"getTitle",
"()Ljava/lang/String;")
createModule = J.make_method(
"createModule",
"()Lorg/scijava/module/Module;",
fn_post_process=wrap_module)
getMenuPath = J.make_method(
"getMenuPath", "()Lorg/scijava/MenuPath;")
getMenuRoot = J.make_method(
"getMenuRoot", "()Ljava/lang/String;")
getName = J.make_method("getName", "()Ljava/lang/String;")
getClassName = J.make_method("getClassName", "()Ljava/lang/String;")
def get_pixel_data(self, axes=None):
imgplus = self.getImgPlus()
pixel_data = get_pixel_data(imgplus)
script = """
var result = java.util.ArrayList();
for (i=0;i<imgplus.numDimensions();i++)
result.add(imgplus.axis(i).type());
result"""
inv_axes = J.run_script(script, dict(imgplus=imgplus))
inv_axes = list(J.iterate_collection(inv_axes))
transpose = calculate_transpose(inv_axes, axes)
return pixel_data.transpose(transpose)
def get_pixel_data(self, axes = None):
imgplus = self.getImgPlus()
pixel_data = get_pixel_data(imgplus)
script = """
var result = java.util.ArrayList();
for (i=0;i<imgplus.numDimensions();i++)
result.add(imgplus.axis(i).type());
result"""
inv_axes = J.run_script(script, dict(imgplus=imgplus))
inv_axes = list(J.iterate_collection(inv_axes))
transpose = calculate_transpose(inv_axes, axes)
return pixel_data.transpose(transpose)
class DisplayService(object):
def __init__(self):
self.o = o
def createDisplay(self, name, dataset):
"""Create a display that contains the given dataset
:param dataset:
:param name:
"""
return wrap_display(
J.call(
o, "createDisplay",
"(Ljava/lang/String;Ljava/lang/Object;)Lorg/scijava/display/Display;",
name, dataset))
def getActiveDisplay(self, klass=None):
"""Get the first display, optionally of the given type from the list
klass - if not None, return the first display of this type,
otherwise return the first display
:param klass:
"""
if klass is None:
return wrap_display(
J.call(self.o, "getActiveDisplay",
"()Lorg/scijava/display/Display;"))
else:
return wrap_display(
J.call(self.o, "getActiveDisplay",
"(Ljava/lang/Class;)Lorg/scijava/display/Display;",
klass))
def getActiveImageDisplay(self):
"""Get the active imagej.data.display.ImageDisplay"""
return wrap_display(
J.call(self.o, "getActiveDisplay",
"()Lorg/scijava/display/Display;",
J.class_for_name("net.imagej.display.ImageDisplay")))
setActiveDisplay = J.make_method("setActiveDisplay",
"(Lorg/scijava/display/Display;)V")
getDisplays = J.make_method("getDisplays",
"()Ljava/util/List;",
fn_post_process=lambda x: map(
wrap_display, J.iterate_collection(x)))
getDisplay = J.make_method(
"getDisplay",
"(Ljava/lang/String;)Lorg/scijava/display/Display;",
fn_post_process=wrap_display)
isUniqueName = J.make_method("isUniqueName", "(Ljava/lang/String;)Z")
class ScriptService(object):
def __init__(self, o=o):
self.o = o
getPluginService = J.make_method(
"getPluginService", "()Lorg/scijava/plugin/PluginService;")
getIndex = J.make_method(
"getIndex", "()Lorg/scijava/script/ScriptLanguageIndex;")
getLanguages = J.make_method(
"getLanguages", "()Ljava/util/List;",
doc = "Return the script engine factories supported by this service",
fn_post_process = lambda jlangs: [
wrap_script_engine_factory(o)
for o in J.iterate_collection(jlangs)])
getByFileExtension = J.make_method(
"getLanguageByExtension",
"(Ljava/lang/String;)Lorg/scijava/script/ScriptLanguage;",
fn_post_process=wrap_script_engine_factory)
getByName = J.make_method(
"getLanguageByName",
"(Ljava/lang/String;)Lorg/scijava/script/ScriptLanguage;",
fn_post_process=wrap_script_engine_factory)
def test_02_06_menu_entry(self):
svc = ij2.get_module_service(self.context)
module_infos = svc.getModules()
for module_info in module_infos:
if module_info.getClassName() == \
'net.imagej.plugins.commands.assign.AddSpecifiedNoiseToDataValues':
menu_path = module_info.getMenuPath()
for item in J.iterate_collection(menu_path):
menu_entry = ij2.wrap_menu_entry(item)
menu_entry.getName()
menu_entry.setName("Foo")
menu_entry.getWeight()
menu_entry.setWeight(5)
menu_entry.getMnemonic()
menu_entry.setMnemonic("X")
menu_entry.getAccelerator()
menu_entry.setAccelerator(None)
menu_entry.getIconPath()
menu_entry.setIconPath(None)
break
else:
raise AssertionError("Could not find target module")
def test_02_06_menu_entry(self):
svc = ij2.get_module_service(self.context)
module_infos = svc.getModules()
for module_info in module_infos:
if module_info.getClassName() == \
'net.imagej.plugins.commands.assign.AddSpecifiedNoiseToDataValues':
menu_path = module_info.getMenuPath()
for item in J.iterate_collection(menu_path):
menu_entry = ij2.wrap_menu_entry(item)
menu_entry.getName()
menu_entry.setName("Foo")
menu_entry.getWeight()
menu_entry.setWeight(5)
menu_entry.getMnemonic()
menu_entry.setMnemonic("X")
menu_entry.getAccelerator()
menu_entry.setAccelerator(None)
menu_entry.getIconPath()
menu_entry.setIconPath(None)
break
else:
raise AssertionError("Could not find target module")
def __iter__(self):
return J.iterate_collection(self.o)
class DisplayService(object):
def __init__(self):
self.o = o
def createDisplay(self, name, dataset):
'''Create a display that contains the given dataset'''
#
# Must be run on the gui thread
#
jcallable = J.run_script(
"""new java.util.concurrent.Callable() {
call:function() {
return displayService.createDisplay(name, dataset);
}
};
""", dict(displayService=self.o, name=name, dataset=dataset.o))
future = J.make_future_task(jcallable,
fn_post_process=wrap_display)
return J.execute_future_in_main_thread(future)
def getActiveDisplay(self, klass=None):
'''Get the first display, optionally of the given type from the list
klass - if not None, return the first display of this type,
otherwise return the first display
'''
if klass is None:
return wrap_display(
J.call(self.o, "getActiveDisplay",
"()Lorg/scijava/display/Display;"))
else:
return wrap_display(
J.call(self.o, "getActiveDisplay",
"(Ljava/lang/Class;)Lorg/scijava/display/Display;",
klass))
def getActiveImageDisplay(self):
'''Get the active imagej.data.display.ImageDisplay'''
return wrap_display(
J.call(self.o, "getActiveDisplay",
"()Lorg/scijava/display/Display;",
J.class_for_name("net.imagej.display.ImageDisplay")))
def setActiveDisplay(self, display):
'''Make this the active display'''
# Note: has to be run in GUI thread on mac
r = J.run_script(
"""new java.lang.Runnable() {
run:function() { displayService.setActiveDisplay(display); }
}
""", dict(displayService=self.o, display=display.o))
J.execute_runnable_in_main_thread(r, True)
getDisplays = J.make_method("getDisplays",
"()Ljava/util/List;",
fn_post_process=lambda x: map(
wrap_display, J.iterate_collection(x)))
getDisplay = J.make_method(
"getDisplay",
"(Ljava/lang/String;)Lorg/scijava/display/Display;",
fn_post_process=wrap_display)
isUniqueName = J.make_method("isUniqueName", "(Ljava/lang/String;)Z")
def __iter__(self):
return J.iterate_collection(self.o)
def main(args):
"""
Trains Apriori on the specified dataset (uses vote UCI dataset if no dataset specified).
:param args: the commandline arguments
:type args: list
"""
# load a dataset
if len(args) <= 1:
data_file = helper.get_data_dir() + os.sep + "vote.arff"
else:
data_file = args[1]
helper.print_info("Loading dataset: " + data_file)
loader = Loader("weka.core.converters.ArffLoader")
data = loader.load_file(data_file)
data.class_is_last()
# build Apriori, using last attribute as class attribute
apriori = Associator(classname="weka.associations.Apriori",
options=["-c", "-1"])
apriori.build_associations(data)
print(str(apriori))
# iterate association rules (low-level)
helper.print_info("Rules (low-level)")
# make the underlying rules list object iterable in Python
rules = javabridge.iterate_collection(
apriori.jwrapper.getAssociationRules().getRules().o)
for i, r in enumerate(rules):
# wrap the Java object to make its methods accessible
rule = JWrapper(r)
print(str(i + 1) + ". " + str(rule))
# output some details on rule
print(" - consequence support: " + str(rule.getConsequenceSupport()))
print(" - premise support: " + str(rule.getPremiseSupport()))
print(" - total support: " + str(rule.getTotalSupport()))
print(" - total transactions: " + str(rule.getTotalTransactions()))
# iterate association rules (high-level)
helper.print_info("Rules (high-level)")
print("can produce rules? " + str(apriori.can_produce_rules()))
print("rule metric names: " + str(apriori.rule_metric_names))
rules = apriori.association_rules()
if rules is not None:
print("producer: " + rules.producer)
print("# rules: " + str(len(rules)))
for i, rule in enumerate(rules):
print(str(i + 1) + ". " + str(rule))
# output some details on rule
print(" - consequence support: " + str(rule.consequence_support))
print(" - consequence: " + str(rule.consequence))
print(" - premise support: " + str(rule.premise_support))
print(" - premise: " + str(rule.premise))
print(" - total support: " + str(rule.total_support))
print(" - total transactions: " + str(rule.total_transactions))
print(" - metric names: " + str(rule.metric_names))
print(" - metric values: " + str(rule.metric_values))
print(" - metric value 'Confidence': " +
str(rule.metric_value('Confidence')))
print(" - primary metric name: " + str(rule.primary_metric_name))
print(" - primary metric value: " +
str(rule.primary_metric_value))
