#!/usr/bin/env python2.6
# -*- coding: utf-8 -*-

"""
test the LANLstar module

Copyright 2011-2012 Los Alamos National Security, LLC.
"""

import os.path
import sys
import unittest

import spacepy_testing
import spacepy
if sys.version_info[:2] <= (3, 6):  # Skip tests on 3.7+
    import spacepy.LANLstar as sl
import numpy
from numpy import array, hstack

__all__ = ['LANLStarFunctionsTest', 'lanlstarTest']


@unittest.skipIf(sys.version_info[:2] > (3, 6),
                 "ffnet not supported on Python > 3.6")
class LANLStarFunctionsTest(unittest.TestCase):
    """Tests of simple support functions for LANLStar"""

    def testNetPath(self):
        """Get the path to a .net file"""
        #okay, this is stupid since it's really the same code,
        #but at least it checks for syntax errors....
        self.assertEqual(
            os.path.join(
            os.path.split(spacepy.__file__)[0], 'data', 'LANLstar', 'Lmax_T89.net'),
            sl._get_net_path('Lmax_T89.net'))
        try:
            q = sl._get_net_path('sample.net')
        except RuntimeError:
            self.assertEqual(
                'Could not find neural network file sample.net',
                str(sys.exc_info()[1]))


@unittest.skipIf(sys.version_info[:2] > (3, 6),
                 "ffnet not supported on Python > 3.6")
class lanlstarTest(unittest.TestCase):

    def setUp(self):
        self.dat = {
            'Kp'     : array([2.7    ]),
            'Dst'    : array([7.7777 ]),
            'dens'   : array([4.1011 ]),
            'velo'   : array([400.101]),
            'Pdyn'   : array([4.1011 ]),
            'ByIMF'  : array([3.7244 ]),
            'BzIMF'  : array([-0.1266]),
            'G1'     : array([1.02966]),
            'G2'     : array([0.54933]),
            'G3'     : array([0.81399]),
            'W1'     : array([0.12244]),
            'W2'     : array([0.2514 ]),
            'W3'     : array([0.0892 ]),
            'W4'     : array([0.0478 ]),
            'W5'     : array([0.2258 ]),
            'W6'     : array([1.0461 ]),
            'Year'   : array([1996   ]),
            'DOY'    : array([6      ]),
            'Hr'     : array([1.2444 ]),
            'Lm'     : array([4.9360 ]),
            'Bmirr'  : array([315.620]),
            'rGSM'   : array([4.8341 ]),
            'lonGSM' : array([-40.266]),
            'latGSM' : array([36.4469]),
            'PA'     : array([57.3875])}
                                                                                
    def test_get_lanlstar(self):
        expected_lstar = {'OPDYN'   : array([4.7171]),
                          'OPQUIET' : array([4.6673]),
                          'T01QUIET': array([4.8427]),
                          'T01STORM': array([4.8669]),
                          'T89'     : array([4.5187]),
                          'T96'     : array([4.6439]),
                          'T05'    : array([4.7174])}

        Bmodels = ['OPDYN','OPQUIET','T01QUIET','T01STORM','T89','T96','T05']
        actual = sl.LANLstar(self.dat, Bmodels)
        for key in Bmodels:
            numpy.testing.assert_almost_equal(expected_lstar[key], actual[key], decimal=4)

    def test_get_lanlmax(self):
        expected_lmax = {'OPDYN'   : array([10.6278]),
                          'OPQUIET' : array([9.3352]),
                          'T01QUIET': array([10.0538]),
                          'T01STORM': array([9.9300]),
                          'T89'     : array([8.2888]),
                          'T96'     : array([9.2410]),
                          'T05'    : array([9.9295])}

        Bmodels = ['OPDYN','OPQUIET','T01QUIET','T01STORM','T89','T96','T05']
        actual = sl.LANLmax(self.dat, Bmodels)
        for key in Bmodels:
            numpy.testing.assert_almost_equal(expected_lmax[key], actual[key], decimal=4)
            
    def test_get_lanlmax_G(self):
        self.dat['G'] = hstack([self.dat['G1'], self.dat['G2'], self.dat['G3']])
        self.dat['W'] = hstack([self.dat['W1'], self.dat['W2'], self.dat['W3'], self.dat['W4'], self.dat['W5'], self.dat['W6']])
        for i in range(1,4): del self.dat['G{0}'.format(i)]
        for i in range(1,7): del self.dat['W{0}'.format(i)]
        expected_lmax = {'T01QUIET' : array([10.0538]),
                          'T01STORM': array([9.9300]),
                          'T05'     : array([9.9295])}

        Bmodels = ['T01QUIET','T01STORM','T05']
        actual = sl.LANLmax(self.dat, Bmodels)
        for key in Bmodels:
            numpy.testing.assert_almost_equal(expected_lmax[key], actual[key], decimal=4)

if __name__=="__main__":
    unittest.main()
