def test_load_rb_com_11():
data = load_rb_com_11(num_instances=1)
known = {
'_guid': 'ea022d3d-5c9e-46d7-be23-8ea718fe7816',
'_human_cluster_label': '0',
'component0': {
'b': 1.0,
'l': 0.0,
'r': 1.0,
't': 2.0,
'type': 'cube0'
},
'component1': {
'b': 3.0,
'l': 2.0,
'r': 3.0,
't': 4.0,
'type': 'cube0'
},
'component14': {
'b': 4.0,
'l': 1.0,
'r': 4.0,
't': 5.0,
'type': 'ufoo0'
},
'component2': {
'b': 1.0,
'l': 1.0,
'r': 4.0,
't': 2.0,
'type': 'plat0'
},
'component3': {
'b': 2.0,
'l': 1.0,
'r': 4.0,
't': 3.0,
'type': 'plat0'
},
'component4': {
'b': 0.0,
'l': 0.0,
'r': 5.0,
't': 1.0,
'type': 'rect0'
}
}
assert known == data[0]
def output_json(file="forest", size=100, prune=True, seed=50, burn=1):
random.seed(seed)
if file == "forest":
instances = ds.load_forest_fires()
variables = False
elif file == "voting":
instances = ds.load_congressional_voting()
variables = False
elif file == "iris":
instances = ds.load_iris()
variables = False
elif file == "mushroom":
instances = ds.load_mushroom()
variables = False
elif file == "rb_com_11":
instances = ds.load_rb_com_11()
variables = True
elif file == "rb_s_07":
instances = ds.load_rb_s_07()
variables = True
elif file == "rb_s_13":
instances = ds.load_rb_s_13()
variables = True
elif file == "rb_wb_03":
instances = ds.load_rb_wb_03()
variables = True
else:
instances = ds.load_forest_fires()
variables = False
random.shuffle(instances)
pprint.pprint(instances[0])
instances = instances[:size]
print(len(instances))
if variables:
variablizer = ObjectVariablizer()
instances = [variablizer.transform(t) for t in instances]
tree = TrestleTree()
tree.fit(instances, iterations=burn)
pprint.pprint(tree.root.output_json())
with open('output.js', 'w') as out:
out.write("var trestle_output = ")
out.write(json.dumps(tree.root.output_json()))
out.write(";")
x = np.arange(len(hueristics))
width = 0.3
hueristic_names = ['AIC', 'BIC', 'CU', 'AICc']
# for i in range(len(clusters)):
# hueristic_names[i] += '\nClusters='+str(len(set(clusters[i])))
b1 = plt.bar(x - width,
calculate_aris(load_rb_wb_03()),
width,
color='r',
alpha=.8,
align='center')
b2 = plt.bar(x,
calculate_aris(load_rb_com_11()),
width,
color='b',
alpha=.8,
align='center')
b3 = plt.bar(x + width,
calculate_aris(load_rb_s_13()),
width,
color='g',
alpha=.8,
align='center')
plt.legend((b1[0], b2[0], b3[0]), ('wb_03', 'com_11', 's_13'))
plt.title(
"TRESTLE Clustering Accuracy of Best Clustering by Different Hueristics")
plt.ylabel("Adjusted Rand Index (Agreement Correcting for Chance)")
plt.ylim(0, 1)