import numpy as np
from likelihood import Likelihood
data = np.load('data.npy')
L = Likelihood(data)
print(
L.pseudoplanck([
3.20090859e-01, 2.21224104e-02, 6.69496793e-01, 2.09219606e-09,
9.63266374e-01, 5.24779614e-02, 8.12628423e-01
]))
# print( L.rosenbrock2d([1,1]) )
# print( L.rosenbrock2d([1,2]) )
# print( L.rosenbrock2d([2,1]) )
# print(L.lnL([5,3]))
# print(L.lnL([5,2]))
# print(L.lnL([15,13]))
# print(L.lnL([3,3]))
# integrate it over entire parameter space
# x = np.linspace(0,10,1000)
# y = np.linspace(0,10,1000)
# grid = np.zeros((1000,1000))
# for i,xi in enumerate(x):
# print( i )
# for j,yj in enumerate(y):
# grid[i,j] = L.lnL([xi,yj])
# grid = np.exp(grid)
# ix = np.zeros(1000)
