https://github.com/JoeMcEwen/FAST-PT
Tip revision: 68c2df21063d59bb39d5a1e5f1747e463ba00d29 authored by Jonathan Blazek on 21 September 2016, 01:19:09 UTC
updated arxiv number
updated arxiv number
Tip revision: 68c2df2
kPol.py
import numpy as np
from J_table import J_table
import sys
# The ordering is \alpha, \beta, l_1, l_2, l, A coefficient.
l_mat1= np.array([[-2,-2,0,0,0,2.],\
[-2,-2,2,0,0,6.],\
[-2,-2,0,0,2,1.],\
[-2,-2,2,2,0,6.],\
[-2,-2,1,1,1,-9.]], dtype=float)
l_mat2 = np.array([[-2,-2,0,0,0,1.],\
[-2,-2,2,0,0,-2.],\
[-2,-2,1,1,1,9.],\
[-2,-2,2,2,0,-8.]], dtype=float)
l_mat3= np.array([[-2,-2,0,0,0,1.],\
[-2,-2,2,0,0,-2.],
[-2,-2,2,2,0,1.]], dtype=float)
def kPol():
table1=np.zeros(10,dtype=float)
for i in range(l_mat1.shape[0]):
x=J_table(l_mat1[i])
table1=np.row_stack((table1,x))
table2=np.zeros(10,dtype=float)
for i in range(l_mat2.shape[0]):
x=J_table(l_mat2[i])
table2=np.row_stack((table2,x))
table3=np.zeros(10,dtype=float)
for i in range(l_mat3.shape[0]):
x=J_table(l_mat3[i])
table3=np.row_stack((table3,x))
return table1[1:,:], table2[1:,:], table3[1:,:]