import pyopencl as cl
mf = cl.mem_flags

import numpy
import time

import matplotlib
import matplotlib.pyplot as plt
matplotlib.use('AGG')

import sympy
import lbm_d2q9 as D2Q9

from mako.template import Template

class D2Q9_BGK_Lattice:
    def idx(self, x, y):
        return y * self.nX + x;

    def __init__(self, nX, nY):
        self.nX = nX
        self.nY = nY
        self.nCells = nX * nY
        self.tick = True

        self.platform = cl.get_platforms()[0]
        self.context  = cl.Context(properties=[(cl.context_properties.PLATFORM, self.platform)])
        self.queue = cl.CommandQueue(self.context)

        self.np_moments = []
        self.np_material = numpy.ndarray(shape=(self.nCells, 1), dtype=numpy.int32)

        self.setup_geometry()

        self.cl_pop_a = cl.Buffer(self.context, mf.READ_WRITE, size=9*self.nCells*numpy.float32(0).nbytes)
        self.cl_pop_b = cl.Buffer(self.context, mf.READ_WRITE, size=9*self.nCells*numpy.float32(0).nbytes)

        self.cl_moments  = cl.Buffer(self.context, mf.WRITE_ONLY, size=3*self.nCells*numpy.float32(0).nbytes)
        self.cl_material = cl.Buffer(self.context, mf.READ_ONLY  | mf.USE_HOST_PTR, hostbuf=self.np_material)

        self.build_kernel()

        self.program.equilibrilize(self.queue, (self.nX,self.nY), (32,1), self.cl_pop_a, self.cl_pop_b).wait()

    def setup_geometry(self):
        self.np_material[:] = 0
        for x in range(1,self.nX-1):
            for y in range(1,self.nY-1):
                if x == 1 or y == 1 or x == self.nX-2 or y == self.nY-2:
                    self.np_material[self.idx(x,y)] = 2
                else:
                    self.np_material[self.idx(x,y)] = 1

    def build_kernel(self):
        program_src = Template(filename = './template/kernel.mako').render(
            nX     = self.nX,
            nY     = self.nY,
            nCells = self.nCells,
            tau    = '0.8f',
            moments_helper     = D2Q9.moments_opt[0],
            moments_assignment = D2Q9.moments_opt[1],
            collide_helper     = D2Q9.collide_opt[0],
            collide_assignment = D2Q9.collide_opt[1],
            c     = D2Q9.c,
            w     = D2Q9.w,
            ccode = sympy.ccode
        )
        self.program = cl.Program(self.context, program_src).build()

    def collect_moments(self):
        moments = numpy.ndarray(shape=(3, self.nCells), dtype=numpy.float32)

        if self.tick:
            self.program.collect_moments(self.queue, (self.nX,self.nY), (32,1), self.cl_pop_b, self.cl_moments)
        else:
            self.program.collect_moments(self.queue, (self.nX,self.nY), (32,1), self.cl_pop_a, self.cl_moments)

        cl.enqueue_copy(LBM.queue, moments, LBM.cl_moments).wait();
        self.np_moments.append(moments)

    def evolve(self):
        if self.tick:
            self.tick = False
            self.program.collide_and_stream(self.queue, (self.nX,self.nY), (32,1), self.cl_pop_a, self.cl_pop_b, self.cl_material)
        else:
            self.tick = True
            self.program.collide_and_stream(self.queue, (self.nX,self.nY), (32,1), self.cl_pop_b, self.cl_pop_a, self.cl_material)

    def sync(self):
        self.queue.finish()

    def generate_moment_plots(self):
        for i, moments in enumerate(self.np_moments):
            print("Generating plot %d of %d." % (i+1, len(self.np_moments)))

            density = numpy.ndarray(shape=(self.nY-2, self.nX-2))
            for y in range(1,self.nY-1):
                for x in range(1,self.nX-1):
                    density[y-1,x-1] = moments[0,self.idx(x,y)]

            plt.figure(figsize=(10, 10))
            plt.imshow(density, origin='lower', vmin=0.2, vmax=2.0, cmap=plt.get_cmap('seismic'))
            plt.savefig("result/density_" + str(i) + ".png", bbox_inches='tight', pad_inches=0)

        self.np_moments = []


def MLUPS(cells, steps, time):
    return cells * steps / time * 1e-6

nUpdates = 1000
nStat = 100

print("Initializing simulation...\n")

LBM = D2Q9_BGK_Lattice(1024, 1024)

print("Starting simulation using %d cells...\n" % LBM.nCells)

lastStat = time.time()

for i in range(1,nUpdates+1):
    LBM.evolve()

    if i % nStat == 0:
        LBM.sync()
        print("i = %4d; %3.0f MLUPS" % (i, MLUPS(LBM.nCells, nStat, time.time() - lastStat)))
        LBM.collect_moments()
        lastStat = time.time()

print("\nConcluded simulation.\n")

LBM.generate_moment_plots()