#!/usr/bin/env python

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# Author: Mark Moll

import sys
from os.path import abspath, dirname, join
sys.path.insert(0, join(dirname(dirname(dirname(abspath(__file__)))),'py-bindings') )
from functools import partial
from os.path import dirname
from time import clock
from math import fabs
import unittest
import copy
import ompl.util as ou
import ompl.base as ob
import ompl.geometric as og
from ompl.util import setLogLevel, LogLevel

SOLUTION_TIME = 5.0

class Environment(object):
    def __init__(self, fname):
        fp = open(fname, 'r')
        lines = fp.readlines()
        fp.close()
        self.width, self.height = [int(i) for i in lines[0].split(' ')[1:3]]
        self.grid = []
        self.start = [int(i) for i in lines[1].split(' ')[1:3]]
        self.goal = [int(i) for i in lines[2].split(' ')[1:3]]
        for i in range(self.width):
            self.grid.append(
                [int(i) for i in lines[4+i].split(' ')[0:self.height]])
        self.char_mapping = ['__', '##', 'oo', 'XX']

    def __str__(self):
        result = ''
        for line in self.grid:
            result = result + ''.join([self.char_mapping[c] for c in line]) + '\n'
        return result

def isValid(grid, state):
    # planning is done in a continuous space, but our collision space
    # representation is discrete
    x = int(state[0][0])
    y = int(state[1][0])
    return grid[x][y] == 0 # 0 means valid state

class mySpace1(ob.RealVectorStateSpace):
    def __init__(self):
        super(mySpace1, self).__init__(1)

    def distance(self, state1, state2):
        x1 = int(state1[0])
        x2 = int(state2[0])
        return fabs(x1-x2)

class mySetup(object):
    def __init__(self, env):
        self.space = ob.CompoundStateSpace()
        self.setup = og.SimpleSetup(self.space)
        bounds = ob.RealVectorBounds(1)
        bounds.setLow(0)
        bounds.setHigh(float(env.width) - 0.000000001)
        self.m1 = mySpace1()
        self.m1.setBounds(bounds)

        bounds.setHigh(float(env.height) - 0.000000001)
        self.m2 = mySpace1()
        self.m2.setBounds(bounds)

        self.space.addSubspace(self.m1, 1.0)
        self.space.addSubspace(self.m2, 1.0)

        isValidFn = ob.StateValidityCheckerFn(partial(isValid, env.grid))
        self.setup.setStateValidityChecker(isValidFn)

        state = ob.CompoundState(self.space)
        state()[0][0] = env.start[0]
        state()[1][0] = env.start[1]
        self.start = ob.State(state)

        gstate = ob.CompoundState(self.space)
        gstate()[0][0] = env.goal[0]
        gstate()[1][0] = env.goal[1]
        self.goal = ob.State(gstate)

        self.setup.setStartAndGoalStates(self.start, self.goal)


def testPlanner(env, time, pathLength, show = False):
    result = True
    setup = mySetup(env)
    startTime = clock()
    if setup.setup.solve(SOLUTION_TIME):
        elapsed = clock() - startTime
        time = time + elapsed
        if show:
            print('Found solution in %f seconds!' % elapsed)

        startTime = clock()
        setup.setup.simplifySolution()
        elapsed = clock() - startTime
        time = time + elapsed
        if show:
            print('Simplified solution in %f seconds!' % elapsed)

        path = setup.setup.getSolutionPath()
        path.interpolate(100)
        pathLength = pathLength + path.length()
        if show:
            print(env, '\n')
            temp = copy.deepcopy(env)
            for i in range(len(path.states)):
                x = int(path.states[i][0][0])
                y = int(path.states[i][1][0])
                if temp.grid[x][y] in [0,2]:
                    temp.grid[x][y] = 2
                else:
                    temp.grid[x][y] = 3
            print(temp, '\n')
    else:
        result = False

    return (result, time, pathLength)


class PlanTest(unittest.TestCase):
    def setUp(self):
        self.env = Environment(dirname(abspath(__file__))+'/../../tests/resources/env1.txt')
        if self.env.width * self.env.height == 0:
            self.fail('The environment has a 0 dimension. Cannot continue')
        self.verbose = True

    def testRunPlanner(self):
        time = 0.0
        length = 0.0
        good = 0
        N = 25

        for i in range(N):
            (result, time, length) = testPlanner(self.env, time, length, False)
            if result: good = good + 1

        success = 100.0 * float(good) / float(N)
        avgruntime = time / float(N)
        avglength = length / float(N)

        if self.verbose:
            print('    Success rate: %f%%' % success)
            print('    Average runtime: %f' % avgruntime)
            print('    Average path length: %f' % avglength)

        self.assertTrue(success >= 99.0)
        self.assertTrue(avgruntime < 2.5)
        self.assertTrue(avglength < 70.0)


def suite():
    suites = ( unittest.makeSuite(PlanTest) )
    return unittest.TestSuite(suites)

if __name__ == '__main__':
    setLogLevel(LogLevel.LOG_ERROR)
    unittest.main()
