def TD_to_1D(pk_or_kr):
if pk_or_kr[0] == 0: #Normal plot
partition = range(number / 2)
block = len(partition)
y = [0] * block
y_n = [0] * block
for i in range(number):
for j in range(number):
for k in range(number):
distance = math.sqrt(i**2 + j**2 + k**2)
distance = math.sqrt((i - number / 2)**2 +
(j - number / 2)**2 +
(k - number / 2)**2)
if distance < number / 2:
y[int(distance)] += pk_or_kr[1][i][j][k]
y_n[int(distance)] += 1
for i in range(block):
if y_n[i] <> 0:
y[i] = y[i] / y_n[i]
return partition, y
elif pk_or_kr[0] == 1: #Log plot
partition = ml.Create_Partition(number / 2, 0)
block = len(partition) - 1
y = [0] * block
y_n = [0] * block
for i in range(number):
for j in range(number):
for k in range(number):
distance = math.sqrt((i - number / 2)**2 +
(j - number / 2)**2 +
(k - number / 2)**2)
for l in range(block):
if distance >= partition[l] and distance < partition[
l + 1]:
y_n[l] += 1
y[l] += pk_or_kr[1][i][j][k]
del partition[-1]
for i in range(block):
if y_n[i] <> 0:
y[i] = y[i] / y_n[i]
return partition, y
