def grade5():
print '=' * 20 + ' TASK 5 ' + '=' * 20
testcases = {
'read_image':
[(['testcases/test_image.pgm'],
[map(lambda x: i * x, range(15)) for i in range(1, 19)]),
(['testcases/test_image2.ppm'], [
map(lambda x: [i * x, i * x + 1, i * x + 2], range(15))
for i in range(1, 19)
])],
'preprocess_image': [([[
map(lambda x: [i * x, i * x + 1, i * x + 2], range(15))
for i in range(19, 1, -1)
]], cluster.readfile('testcases/test_data.csv')),
([[
map(lambda x: [i * x, i * x + 1, i * x + 2],
range(15)) for i in range(1, 19)
]], cluster.readfile('testcases/test_data2.csv'))]
}
grade = 0
for function in testcases:
passed = True
for inp, out in testcases[function]:
try:
ret = getattr(image, function)(*inp)
except Exception:
ret = None
if ret != out:
print 'Function {} failed a testcase.\n\tInput: {}\n\tExpected return: {}\n\tRecieved return: {}\n'.format(
function,
str(inp)[1:-1], out, ret)
passed = False
print ' {} Function {}'.format([u'\u2718',
u'\u2713'][passed].encode('utf8'),
function)
print '-' * 30
grade += passed
grade *= 0.5
print 'grade: {}'.format(grade)
print ''
return grade
def grade8():
print '=' * 20 + ' TASK 8 ' + '=' * 20
with open('testcases/test_labels', 'r') as f:
labels = map(lambda x: map(int, x.split()), f.readlines())
with open('testcases/test_labels2', 'r') as f:
labels2 = map(lambda x: map(int, x.split()), f.readlines())
with open('testcases/test_decomp', 'r') as f:
img = [[map(int, j.split(', ')) for j in i.split('], [')]
for i in f.read()[3:-3].split(']], [[')]
with open('testcases/test_decomp2', 'r') as f:
img2 = [[map(int, j.split(', ')) for j in i.split('], [')]
for i in f.read()[3:-3].split(']], [[')]
testcases = {
'decompress_image':
[([labels, cluster.readfile('testcases/test_centroids.csv')], img),
([labels2, cluster.readfile('testcases/test_centroids2.csv')], img2)]
}
grade = 0
function = 'decompress_image'
passed = True
for inp, out in testcases[function]:
try:
ret = getattr(image, function)(*inp)
except Exception:
ret = None
if ret != out:
print 'Function {} failed a testcase.\n\tInput: {}\n\tExpected return: {}\n\tRecieved return: {}\n'.format(
function,
str(inp)[1:-1], out, ret)
passed = False
print ' {} Function {}'.format([u'\u2718',
u'\u2713'][passed].encode('utf8'),
function)
print '-' * 30
grade += passed
grade *= 0.5
print 'grade: {}'.format(grade)
print ''
return grade
__author__ = 'esauali'
import cluster
# blognames, words, data = cluster.readfile('blogdata.txt')
# clust = cluster.hcluster(data)
# # Print cluster
# cluster.printclust(clust, labels=blognames)
# # Generate cluster tree image
# cluster.drawdendrogram(clust, blognames, jpeg='blogclust.jpg')
#
# clust_k_means = cluster.kcluster(data, k = 10)
# print(clust_k_means)
# wants, people, data=cluster.readfile('zebo.txt')
# clust = cluster.hcluster(data, distance=cluster.tanimoto)
# cluster.drawdendrogram(clust, wants, jpeg='zeboclust.jpg')
blognames,words,data=cluster.readfile('blogdata.txt')
coords=cluster.scaledown(data)
cluster.draw2d(coords,blognames,jpeg='blogs2d.jpg')
import PIL
from PIL import Image, ImageDraw
from cluster import readfile, dendrogram, rotatematrix, hierarchical_cluster, printcluster
blognames, words, data = readfile('database.txt')
cluster = hierarchical_cluster(data)
printcluster(cluster, labels=blognames)
dendrogram(cluster, labels=blognames, jpeg='blogoutput.jpg')
rdata = rotatematrix(data)
wordcluster = hierarchical_cluster(rdata)
dendrogram(wordcluster, labels=words, jpeg='wordoutput.jpg')
def grade7():
print '=' * 20 + ' TASK 7 ' + '=' * 20
with open('testcases/test_labels', 'r') as f:
labels = map(lambda x: map(int, x.split()), f.readlines())
with open('testcases/test_labels2', 'r') as f:
labels2 = map(lambda x: map(int, x.split()), f.readlines())
with open('testcases/test_image.pgm', 'r') as f:
img = f.read()
img = img.split(None, 4)
with open('testcases/test_image2.ppm', 'r') as f:
img2 = f.read()
img2 = img2.split(None, 4)
testcases = {
'label_image':
[([[
map(lambda x: [i * x, i * x + 1, i * x + 2], range(15))
for i in range(19, 1, -1)
],
cluster.readfile('testcases/test_centroids.csv')], labels),
([[
map(lambda x: [i * x, i * x + 1, i * x + 2], range(15))
for i in range(1, 19)
],
cluster.readfile('testcases/test_centroids2.csv')], labels2)],
'write_image':
[(['t1.pgm',
[map(lambda x: i * x, range(15)) for i in range(1, 19)]], img),
([
't2.ppm',
[
map(lambda x: [i * x, i * x + 1, i * x + 2], range(15))
for i in range(1, 19)
]
], img2)]
}
grade = 0
function = 'label_image'
passed = True
for inp, out in testcases[function]:
try:
ret = getattr(image, function)(*inp)
except Exception:
ret = None
if ret != out:
print 'Function {} failed a testcase.\n\tInput: {}\n\tExpected return: {}\n\tRecieved return: {}\n'.format(
function,
str(inp)[1:-1], out, ret)
passed = False
print ' {} Function {}'.format([u'\u2718',
u'\u2713'][passed].encode('utf8'),
function)
print '-' * 30
grade += passed
function = 'write_image'
passed = True
for inp, out in testcases[function]:
try:
getattr(image, function)(*inp)
with open(inp[0], 'r') as f:
ret = f.read()
ret = ret.split(None, 4)
except Exception:
ret = None
if ret != out:
print 'Function {} failed a testcase.\n\tInput: {}\n'.format(
function,
str(inp)[1:-1])
passed = False
print ' {} Function {}'.format([u'\u2718',
u'\u2713'][passed].encode('utf8'),
function)
print '-' * 30
grade += passed
grade *= 0.5
print 'grade: {}'.format(grade)
print ''
return grade
# clusterTest.py
import cluster
blognames, words, data = cluster.readfile('blogdata.txt')
'''
clust = cluster.hcluster(data)
# cluster.printclust(clust, labels = blognames)
cluster.drawdendrogram(clust, blognames, jpeg = 'blogclust.jpg')
'''
'''
kclust = cluster.kcluster(data, k = 10)
print([blognames[r] for r in kclust[2]])
'''
'''
wants, people, data = cluster.readfile('zebo.txt')
clust = cluster.hcluster(data, distance = cluster.tanimoto)
cluster.drawdendrogram(clust, wants)
'''
coords = cluster.scaledown(data)
cluster.draw2d(coords, blognames, jpeg='blogs2d.jpg')
import cluster
sBlogNames, sWords, sData = cluster.readfile('blogdata.txt')
sClust = cluster.hcluster(sData)
cluster.printclust(sClust, aLabels=sBlogNames)
cluster.drawdendrogram(sClust, sBlogNames, 'blogclust.jpg')