def pairwise_entropy_comp(filenames):
x = []
y = []
l = []
for filename in filenames:
# open the spreadsheet
try:
workbook = xlrd.open_workbook(filename)
quipu = workbook.sheet_by_name('Pendant Detail')
except Exception:
continue
primary = parse_to_pendant_tree(quipu)
collect = empty_collect()
primary.as_raw(collect)
x+=[entropy.calc(collect["ply"])]
y+=[entropy.calc(collect["knot_type"])]
l+=[os.path.basename(filename)[:-4]]
plt.xlabel('pendant ply entropy (bits)')
plt.ylabel('knot type entropy (bits)')
plt.scatter(x, y)
for i, txt in enumerate(l):
plt.annotate(txt, (x[i],y[i]), fontsize=6)
plt.show()
def calculate_entropy(filename,encode_fn):
print filename
# open the spreadsheet
try:
workbook = xlrd.open_workbook(filename)
quipu = workbook.sheet_by_name('Pendant Detail')
except Exception:
print "problem"
return False
print(encode_fn(quipu))
return entropy.calc(encode_fn(quipu))
def calc_entropy(self):
collect=empty_collect()
self.as_raw(collect)
self.entropy=0
for i in collect.values():
self.entropy += entropy.calc(i)
global _min_entropy
global _max_entropy
if self.entropy<_min_entropy: _min_entropy=self.entropy
if self.entropy>_max_entropy: _max_entropy=self.entropy
for p in self.children:
p.calc_entropy()
def global_entropy_sliced(filenames):
collect={
"ply":[],
"attach":[],
"length":[],
"colours":[],
"knot_value":[],
"knot_type":[],
"knot_position":[],
"knot_spin":[]
}
for filename in filenames:
# open the spreadsheet
try:
workbook = xlrd.open_workbook(filename)
quipu = workbook.sheet_by_name('Pendant Detail')
primary = parse_to_pendant_tree(quipu)
primary.as_raw(collect)
except Exception:
pass
for key,value in collect.items():
print(key+" "+str(entropy.calc(value)))
try:
workbook = xlrd.open_workbook(filename)
quipu = workbook.sheet_by_name('Pendant Detail')
except Exception:
print "problem"
return False
print(encode_fn(quipu))
return entropy.calc(encode_fn(quipu))
def batch_generate_entropy(filenames):
cache = {}
for filename in filenames:
e = calculate_entropy(filename, parse_to_raw)
if e!=False:
cache[filename]=e
sorted_cache = sorted(cache.items(), key=operator.itemgetter(1))
for item in sorted_cache:
print(item)
# are we the script that's being run?
if __name__ == "__main__":
if sys.argv[1]=="test":
print entropy.calc(sys.argv[2])
exit(1)
if sys.argv[1]=="batch":
batch_generate_entropy(generate_quipu_list())
else:
print("entropy is: "+str(calculate_entropy(sys.argv[1], parse_to_raw)))
"""Demo."""
import argparse
import entropy
if __name__ == '__main__':
"""Run demo."""
parser = argparse.ArgumentParser(description='Set window size.')
parser.add_argument('-w', '--window', type=int, default=2)
parser.add_argument('-f', '--file', type=str, default="signal.dat")
args = parser.parse_args()
with open(args.file) as f:
signal = f.readline()
exact = 0.99999922015194587997155654610165791488976968896093062603
s = entropy.calc(signal, window=args.window)
print('Entropy:', s)
print('Error:', abs(s-exact))
def test_mixed(self):
"""Test signal with zero enropy."""
signal = [0, 0, 1, 1, 1]
expected = -(2 * math.log2(2. / 5.) + 3 * math.log2(3. / 5.)) / 5
expected = -(2 * math.log2(2) + 3 * math.log2(3)) / 5 + math.log2(5)
self.assertAlmostEqual(entropy.calc(signal, window=1), expected, 15)
def test_one2(self):
"""Test signal with one enropy."""
signal = [0, 0, 0, 1, 1, 0, 1, 1]
self.assertEqual(entropy.calc(signal, window=2), 1)
def test_zero2(self):
"""Test signal with zero enropy."""
signal = [0, 1, 0, 1, 0, 1, 0, 1]
self.assertEqual(entropy.calc(signal, window=2), 0)