from gputhread import *
from Queue import Queue
from detectors import LBNE
from photon import uniform_sphere
import numpy as np
from pycuda import gpuarray
import pycuda.driver as cuda
from uncertainties import ufloat, umath
from histogram import Histogram

jobs = Queue()
output = Queue()

lbne = LBNE()
lbne.build(bits=8)

cuda.init()

gputhreads = []
for i in range(cuda.Device.count()):
    gputhreads.append(GPUThread(i, lbne, jobs, output))
    gputhreads[-1].start()

def generate_event(pos=(0,0,0), nphotons=1000):
    origins_float3 = np.tile(gpuarray.vec.make_float3(*pos), (nphotons,1))
    directions = uniform_sphere(nphotons)
    directions_float3 = np.empty(nphotons, dtype=gpuarray.vec.float3)
    directions_float3['x'] = directions[:,0]
    directions_float3['y'] = directions[:,1]
    directions_float3['z'] = directions[:,2]

    jobs.put(Job(origins_float3, directions_float3))

    jobs.join()

    return output.get()

def likelihood(event_bincount, pos=(0,0,0), nphotons=1000, neval=1000):
    for i in range(neval):
        origins_float3 = np.tile(gpuarray.vec.make_float3(*pos), (nphotons,1))
        directions = uniform_sphere(nphotons)
        directions_float3 = np.empty(nphotons, dtype=gpuarray.vec.float3)
        directions_float3['x'] = directions[:,0]
        directions_float3['y'] = directions[:,1]
        directions_float3['z'] = directions[:,2]

        jobs.put(Job(origins_float3, directions_float3))

    jobs.join()

    bincount = np.zeros((neval, len(lbne.solids)))
    for i in range(neval):
        bincount[i] = output.get()

    log_likelihood = ufloat((0,0))
    for i in range(len(lbne.solids)):
        h = Histogram(100, (-0.5, 99.5))
        h.fill(bincount[:,i])
        h.normalize()

        probability = h.ueval(event_bincount[i])

        if probability.nominal_value == 0.0:
            probability = ufloat((0.5/h.nentries, 0.5/h.nentries))

        log_likelihood += umath.log(probability)

    return -log_likelihood

def stop():
    for gputhread in gputhreads:
        gputhread.stop()

    for gputhread in gputhreads:
        gputhread.join()

if __name__ == '__main__':
    event_bincount = generate_event()

    for z in np.linspace(-1.0, 1.0, 100):
        log_likelihood = likelihood(event_bincount, (z,0,0))
        print 'z = %f, likelihood = %s' % (z, log_likelihood)

    stop()