import warnings

from numpy.testing import *
import numpy.lib
from numpy.lib import *
from numpy.core import *

class TestAny(TestCase):
    def test_basic(self):
        y1 = [0,0,1,0]
        y2 = [0,0,0,0]
        y3 = [1,0,1,0]
        assert(any(y1))
        assert(any(y3))
        assert(not any(y2))

    def test_nd(self):
        y1 = [[0,0,0],[0,1,0],[1,1,0]]
        assert(any(y1))
        assert_array_equal(sometrue(y1,axis=0),[1,1,0])
        assert_array_equal(sometrue(y1,axis=1),[0,1,1])

class TestAll(TestCase):
    def test_basic(self):
        y1 = [0,1,1,0]
        y2 = [0,0,0,0]
        y3 = [1,1,1,1]
        assert(not all(y1))
        assert(all(y3))
        assert(not all(y2))
        assert(all(~array(y2)))

    def test_nd(self):
        y1 = [[0,0,1],[0,1,1],[1,1,1]]
        assert(not all(y1))
        assert_array_equal(alltrue(y1,axis=0),[0,0,1])
        assert_array_equal(alltrue(y1,axis=1),[0,0,1])

class TestAverage(TestCase):
    def test_basic(self):
        y1 = array([1,2,3])
        assert(average(y1,axis=0) == 2.)
        y2 = array([1.,2.,3.])
        assert(average(y2,axis=0) == 2.)
        y3 = [0.,0.,0.]
        assert(average(y3,axis=0) == 0.)

        y4 = ones((4,4))
        y4[0,1] = 0
        y4[1,0] = 2
        assert_almost_equal(y4.mean(0), average(y4, 0))
        assert_almost_equal(y4.mean(1), average(y4, 1))

        y5 = rand(5,5)
        assert_almost_equal(y5.mean(0), average(y5, 0))
        assert_almost_equal(y5.mean(1), average(y5, 1))

        y6 = matrix(rand(5,5))
        assert_array_equal(y6.mean(0), average(y6,0))

    def test_weights(self):
        y = arange(10)
        w = arange(10)
        assert_almost_equal(average(y, weights=w), (arange(10)**2).sum()*1./arange(10).sum())

        y1 = array([[1,2,3],[4,5,6]])
        w0 = [1,2]
        actual = average(y1,weights=w0,axis=0)
        desired = array([3.,4.,5.])
        assert_almost_equal(actual, desired)


        w1 = [0,0,1]
        desired = array([3., 6.])
        assert_almost_equal(average(y1, weights=w1, axis=1), desired)

        # This should raise an error. Can we test for that ?
        # assert_equal(average(y1, weights=w1), 9./2.)


        # 2D Case
        w2 = [[0,0,1],[0,0,2]]
        desired = array([3., 6.])
        assert_array_equal(average(y1, weights=w2, axis=1), desired)

        assert_equal(average(y1, weights=w2), 5.)


    def test_returned(self):
        y = array([[1,2,3],[4,5,6]])

        # No weights
        avg, scl = average(y, returned=True)
        assert_equal(scl, 6.)

        avg, scl = average(y, 0, returned=True)
        assert_array_equal(scl, array([2.,2.,2.]))

        avg, scl = average(y, 1, returned=True)
        assert_array_equal(scl, array([3.,3.]))

        # With weights
        w0 = [1,2]
        avg, scl = average(y, weights=w0, axis=0, returned=True)
        assert_array_equal(scl, array([3., 3., 3.]))

        w1 = [1,2,3]
        avg, scl = average(y, weights=w1, axis=1, returned=True)
        assert_array_equal(scl, array([6., 6.]))

        w2 = [[0,0,1],[1,2,3]]
        avg, scl = average(y, weights=w2, axis=1, returned=True)
        assert_array_equal(scl, array([1.,6.]))


class TestSelect(TestCase):
    def _select(self,cond,values,default=0):
        output = []
        for m in range(len(cond)):
            output += [V[m] for V,C in zip(values,cond) if C[m]] or [default]
        return output

    def test_basic(self):
        choices = [array([1,2,3]),
                   array([4,5,6]),
                   array([7,8,9])]
        conditions = [array([0,0,0]),
                      array([0,1,0]),
                      array([0,0,1])]
        assert_array_equal(select(conditions,choices,default=15),
                           self._select(conditions,choices,default=15))

        assert_equal(len(choices),3)
        assert_equal(len(conditions),3)

class TestLogspace(TestCase):
    def test_basic(self):
        y = logspace(0,6)
        assert(len(y)==50)
        y = logspace(0,6,num=100)
        assert(y[-1] == 10**6)
        y = logspace(0,6,endpoint=0)
        assert(y[-1] < 10**6)
        y = logspace(0,6,num=7)
        assert_array_equal(y,[1,10,100,1e3,1e4,1e5,1e6])

class TestLinspace(TestCase):
    def test_basic(self):
        y = linspace(0,10)
        assert(len(y)==50)
        y = linspace(2,10,num=100)
        assert(y[-1] == 10)
        y = linspace(2,10,endpoint=0)
        assert(y[-1] < 10)
        y,st = linspace(2,10,retstep=1)
        assert_almost_equal(st,8/49.0)
        assert_array_almost_equal(y,mgrid[2:10:50j],13)

    def test_corner(self):
        y = list(linspace(0,1,1))
        assert y == [0.0], y
        y = list(linspace(0,1,2.5))
        assert y == [0.0, 1.0]

    def test_type(self):
        t1 = linspace(0,1,0).dtype
        t2 = linspace(0,1,1).dtype
        t3 = linspace(0,1,2).dtype
        assert_equal(t1, t2)
        assert_equal(t2, t3)

class TestInsert(TestCase):
    def test_basic(self):
        a = [1,2,3]
        assert_equal(insert(a,0,1), [1,1,2,3])
        assert_equal(insert(a,3,1), [1,2,3,1])
        assert_equal(insert(a,[1,1,1],[1,2,3]), [1,1,2,3,2,3])

class TestAmax(TestCase):
    def test_basic(self):
        a = [3,4,5,10,-3,-5,6.0]
        assert_equal(amax(a),10.0)
        b = [[3,6.0, 9.0],
             [4,10.0,5.0],
             [8,3.0,2.0]]
        assert_equal(amax(b,axis=0),[8.0,10.0,9.0])
        assert_equal(amax(b,axis=1),[9.0,10.0,8.0])

class TestAmin(TestCase):
    def test_basic(self):
        a = [3,4,5,10,-3,-5,6.0]
        assert_equal(amin(a),-5.0)
        b = [[3,6.0, 9.0],
             [4,10.0,5.0],
             [8,3.0,2.0]]
        assert_equal(amin(b,axis=0),[3.0,3.0,2.0])
        assert_equal(amin(b,axis=1),[3.0,4.0,2.0])

class TestPtp(TestCase):
    def test_basic(self):
        a = [3,4,5,10,-3,-5,6.0]
        assert_equal(ptp(a,axis=0),15.0)
        b = [[3,6.0, 9.0],
             [4,10.0,5.0],
             [8,3.0,2.0]]
        assert_equal(ptp(b,axis=0),[5.0,7.0,7.0])
        assert_equal(ptp(b,axis=-1),[6.0,6.0,6.0])

class TestCumsum(TestCase):
    def test_basic(self):
        ba = [1,2,10,11,6,5,4]
        ba2 = [[1,2,3,4],[5,6,7,9],[10,3,4,5]]
        for ctype in [int8,uint8,int16,uint16,int32,uint32,
                      float32,float64,complex64,complex128]:
            a = array(ba,ctype)
            a2 = array(ba2,ctype)
            assert_array_equal(cumsum(a,axis=0), array([1,3,13,24,30,35,39],ctype))
            assert_array_equal(cumsum(a2,axis=0), array([[1,2,3,4],[6,8,10,13],
                                                         [16,11,14,18]],ctype))
            assert_array_equal(cumsum(a2,axis=1),
                               array([[1,3,6,10],
                                      [5,11,18,27],
                                      [10,13,17,22]],ctype))

class TestProd(TestCase):
    def test_basic(self):
        ba = [1,2,10,11,6,5,4]
        ba2 = [[1,2,3,4],[5,6,7,9],[10,3,4,5]]
        for ctype in [int16,uint16,int32,uint32,
                      float32,float64,complex64,complex128]:
            a = array(ba,ctype)
            a2 = array(ba2,ctype)
            if ctype in ['1', 'b']:
                self.failUnlessRaises(ArithmeticError, prod, a)
                self.failUnlessRaises(ArithmeticError, prod, a2, 1)
                self.failUnlessRaises(ArithmeticError, prod, a)
            else:
                assert_equal(prod(a,axis=0),26400)
                assert_array_equal(prod(a2,axis=0),
                                   array([50,36,84,180],ctype))
                assert_array_equal(prod(a2,axis=-1),array([24, 1890, 600],ctype))

class TestCumprod(TestCase):
    def test_basic(self):
        ba = [1,2,10,11,6,5,4]
        ba2 = [[1,2,3,4],[5,6,7,9],[10,3,4,5]]
        for ctype in [int16,uint16,int32,uint32,
                      float32,float64,complex64,complex128]:
            a = array(ba,ctype)
            a2 = array(ba2,ctype)
            if ctype in ['1', 'b']:
                self.failUnlessRaises(ArithmeticError, cumprod, a)
                self.failUnlessRaises(ArithmeticError, cumprod, a2, 1)
                self.failUnlessRaises(ArithmeticError, cumprod, a)
            else:
                assert_array_equal(cumprod(a,axis=-1),
                                   array([1, 2, 20, 220,
                                          1320, 6600, 26400],ctype))
                assert_array_equal(cumprod(a2,axis=0),
                                   array([[ 1,  2,  3,   4],
                                          [ 5, 12, 21,  36],
                                          [50, 36, 84, 180]],ctype))
                assert_array_equal(cumprod(a2,axis=-1),
                                   array([[ 1,  2,   6,   24],
                                          [ 5, 30, 210, 1890],
                                          [10, 30, 120,  600]],ctype))

class TestDiff(TestCase):
    def test_basic(self):
        x = [1,4,6,7,12]
        out = array([3,2,1,5])
        out2 = array([-1,-1,4])
        out3 = array([0,5])
        assert_array_equal(diff(x),out)
        assert_array_equal(diff(x,n=2),out2)
        assert_array_equal(diff(x,n=3),out3)

    def test_nd(self):
        x = 20*rand(10,20,30)
        out1 = x[:,:,1:] - x[:,:,:-1]
        out2 = out1[:,:,1:] - out1[:,:,:-1]
        out3 = x[1:,:,:] - x[:-1,:,:]
        out4 = out3[1:,:,:] - out3[:-1,:,:]
        assert_array_equal(diff(x),out1)
        assert_array_equal(diff(x,n=2),out2)
        assert_array_equal(diff(x,axis=0),out3)
        assert_array_equal(diff(x,n=2,axis=0),out4)

class TestGradient(TestCase):
    def test_basic(self):
        x = array([[1,1],[3,4]])
        dx = [array([[2.,3.],[2.,3.]]),
              array([[0.,0.],[1.,1.]])]
        assert_array_equal(gradient(x), dx)

    def test_badargs(self):
        # for 2D array, gradient can take 0,1, or 2 extra args
        x = array([[1,1],[3,4]])
        assert_raises(SyntaxError, gradient, x, array([1.,1.]),
                      array([1.,1.]), array([1.,1.]))

class TestAngle(TestCase):
    def test_basic(self):
        x = [1+3j,sqrt(2)/2.0+1j*sqrt(2)/2,1,1j,-1,-1j,1-3j,-1+3j]
        y = angle(x)
        yo = [arctan(3.0/1.0),arctan(1.0),0,pi/2,pi,-pi/2.0,
              -arctan(3.0/1.0),pi-arctan(3.0/1.0)]
        z = angle(x,deg=1)
        zo = array(yo)*180/pi
        assert_array_almost_equal(y,yo,11)
        assert_array_almost_equal(z,zo,11)

class TestTrimZeros(TestCase):
    """ only testing for integer splits.
    """
    def test_basic(self):
        a= array([0,0,1,2,3,4,0])
        res = trim_zeros(a)
        assert_array_equal(res,array([1,2,3,4]))
    def test_leading_skip(self):
        a= array([0,0,1,0,2,3,4,0])
        res = trim_zeros(a)
        assert_array_equal(res,array([1,0,2,3,4]))
    def test_trailing_skip(self):
        a= array([0,0,1,0,2,3,0,4,0])
        res = trim_zeros(a)
        assert_array_equal(res,array([1,0,2,3,0,4]))


class TestExtins(TestCase):
    def test_basic(self):
        a = array([1,3,2,1,2,3,3])
        b = extract(a>1,a)
        assert_array_equal(b,[3,2,2,3,3])
    def test_place(self):
        a = array([1,4,3,2,5,8,7])
        place(a,[0,1,0,1,0,1,0],[2,4,6])
        assert_array_equal(a,[1,2,3,4,5,6,7])
    def test_both(self):
        a = rand(10)
        mask = a > 0.5
        ac = a.copy()
        c = extract(mask, a)
        place(a,mask,0)
        place(a,mask,c)
        assert_array_equal(a,ac)

class TestVectorize(TestCase):
    def test_simple(self):
        def addsubtract(a,b):
            if a > b:
                return a - b
            else:
                return a + b
        f = vectorize(addsubtract)
        r = f([0,3,6,9],[1,3,5,7])
        assert_array_equal(r,[1,6,1,2])
    def test_scalar(self):
        def addsubtract(a,b):
            if a > b:
                return a - b
            else:
                return a + b
        f = vectorize(addsubtract)
        r = f([0,3,6,9],5)
        assert_array_equal(r,[5,8,1,4])
    def test_large(self):
        x = linspace(-3,2,10000)
        f = vectorize(lambda x: x)
        y = f(x)
        assert_array_equal(y, x)

class TestDigitize(TestCase):
    def test_forward(self):
        x = arange(-6,5)
        bins = arange(-5,5)
        assert_array_equal(digitize(x,bins),arange(11))

    def test_reverse(self):
        x = arange(5,-6,-1)
        bins = arange(5,-5,-1)
        assert_array_equal(digitize(x,bins),arange(11))

    def test_random(self):
        x = rand(10)
        bin = linspace(x.min(), x.max(), 10)
        assert all(digitize(x,bin) != 0)

class TestUnwrap(TestCase):
    def test_simple(self):
                #check that unwrap removes jumps greather that 2*pi
        assert_array_equal(unwrap([1,1+2*pi]),[1,1])
        #check that unwrap maintans continuity
        assert(all(diff(unwrap(rand(10)*100))<pi))


class TestFilterwindows(TestCase):
    def test_hanning(self):
        #check symmetry
        w=hanning(10)
        assert_array_almost_equal(w,flipud(w),7)
        #check known value
        assert_almost_equal(sum(w,axis=0),4.500,4)

    def test_hamming(self):
        #check symmetry
        w=hamming(10)
        assert_array_almost_equal(w,flipud(w),7)
        #check known value
        assert_almost_equal(sum(w,axis=0),4.9400,4)

    def test_bartlett(self):
        #check symmetry
        w=bartlett(10)
        assert_array_almost_equal(w,flipud(w),7)
        #check known value
        assert_almost_equal(sum(w,axis=0),4.4444,4)

    def test_blackman(self):
        #check symmetry
        w=blackman(10)
        assert_array_almost_equal(w,flipud(w),7)
        #check known value
        assert_almost_equal(sum(w,axis=0),3.7800,4)


class TestTrapz(TestCase):
    def test_simple(self):
        r=trapz(exp(-1.0/2*(arange(-10,10,.1))**2)/sqrt(2*pi),dx=0.1)
        #check integral of normal equals 1
        assert_almost_equal(sum(r,axis=0),1,7)

    def test_ndim(self):
        x = linspace(0, 1, 3)
        y = linspace(0, 2, 8)
        z = linspace(0, 3, 13)

        wx = ones_like(x) * (x[1]-x[0])
        wx[0] /= 2
        wx[-1] /= 2
        wy = ones_like(y) * (y[1]-y[0])
        wy[0] /= 2
        wy[-1] /= 2
        wz = ones_like(z) * (z[1]-z[0])
        wz[0] /= 2
        wz[-1] /= 2

        q = x[:,None,None] + y[None,:,None] + z[None,None,:]

        qx = (q*wx[:,None,None]).sum(axis=0)
        qy = (q*wy[None,:,None]).sum(axis=1)
        qz = (q*wz[None,None,:]).sum(axis=2)

        # n-d `x`
        r = trapz(q, x=x[:,None,None], axis=0)
        assert_almost_equal(r, qx)
        r = trapz(q, x=y[None,:,None], axis=1)
        assert_almost_equal(r, qy)
        r = trapz(q, x=z[None,None,:], axis=2)
        assert_almost_equal(r, qz)

        # 1-d `x`
        r = trapz(q, x=x, axis=0)
        assert_almost_equal(r, qx)
        r = trapz(q, x=y, axis=1)
        assert_almost_equal(r, qy)
        r = trapz(q, x=z, axis=2)
        assert_almost_equal(r, qz)


class TestSinc(TestCase):
    def test_simple(self):
        assert(sinc(0)==1)
        w=sinc(linspace(-1,1,100))
        #check symmetry
        assert_array_almost_equal(w,flipud(w),7)

class TestHistogram(TestCase):
    def setUp(self):
        warnings.simplefilter('ignore', DeprecationWarning)

    def tearDown(self):
        warnings.resetwarnings()

    def test_simple_old(self):
        n=100
        v=rand(n)
        (a,b)=histogram(v,  new=False)
        #check if the sum of the bins equals the number of samples
        assert_equal(sum(a,axis=0), n)
        #check that the bin counts are evenly spaced when the data is from a
        # linear function
        (a,b)=histogram(linspace(0,10,100),  new=False)
        assert_array_equal(a, 10)

    def test_simple(self):
        n=100
        v=rand(n)
        (a,b)=histogram(v)
        #check if the sum of the bins equals the number of samples
        assert_equal(sum(a,axis=0), n)
        #check that the bin counts are evenly spaced when the data is from a
        # linear function
        (a,b)=histogram(linspace(0,10,100))
        assert_array_equal(a, 10)

    def test_one_bin(self):
        # Ticket 632
        hist,edges = histogram([1,2,3,4],[1,2])
        assert_array_equal(hist,[2, ])
        assert_array_equal(edges,[1,2])

    def test_normed(self):
        # Check that the integral of the density equals 1.
        n = 100
        v = rand(n)
        a,b = histogram(v, normed=True)
        area = sum(a*diff(b))
        assert_almost_equal(area, 1)

        # Check with non constant bin width
        v = rand(n)*10
        bins = [0,1,5, 9, 10]
        a,b = histogram(v, bins, normed=True)
        area = sum(a*diff(b))
        assert_almost_equal(area, 1)


    def test_outliers(self):
        # Check that outliers are not tallied
        a = arange(10)+.5

        # Lower outliers
        h,b = histogram(a, range=[0,9])
        assert_equal(h.sum(),9)

        # Upper outliers
        h,b = histogram(a, range=[1,10])
        assert_equal(h.sum(),9)

        # Normalization
        h,b = histogram(a, range=[1,9], normed=True)
        assert_equal((h*diff(b)).sum(),1)

        # Weights
        w = arange(10)+.5
        h,b = histogram(a, range=[1,9], weights=w, normed=True)
        assert_equal((h*diff(b)).sum(),1)

        h,b = histogram(a, bins=8, range=[1,9], weights=w)
        assert_equal(h, w[1:-1])


    def test_type(self):
        # Check the type of the returned histogram
        a = arange(10)+.5
        h,b = histogram(a)
        assert(issubdtype(h.dtype, int))

        h,b = histogram(a, normed=True)
        assert(issubdtype(h.dtype, float))

        h,b = histogram(a, weights=ones(10, int))
        assert(issubdtype(h.dtype, int))

        h,b = histogram(a, weights=ones(10, float))
        assert(issubdtype(h.dtype, float))


    def test_weights(self):
        v = rand(100)
        w = ones(100)*5
        a,b = histogram(v)
        na,nb = histogram(v, normed=True)
        wa,wb = histogram(v, weights=w)
        nwa,nwb = histogram(v, weights=w, normed=True)
        assert_array_almost_equal(a*5, wa)
        assert_array_almost_equal(na, nwa)

        # Check weights are properly applied.
        v = linspace(0,10,10)
        w = concatenate((zeros(5), ones(5)))
        wa,wb = histogram(v, bins=arange(11),weights=w)
        assert_array_almost_equal(wa, w)

        # Check with integer weights
        wa, wb = histogram([1,2,2,4], bins=4, weights=[4,3,2,1])
        assert_array_equal(wa, [4,5,0,1])
        wa, wb = histogram([1,2,2,4], bins=4, weights=[4,3,2,1], normed=True)
        assert_array_equal(wa, array([4,5,0,1])/10./3.*4)

class TestHistogramdd(TestCase):
    def test_simple(self):
        x = array([[-.5, .5, 1.5], [-.5, 1.5, 2.5], [-.5, 2.5, .5], \
        [.5, .5, 1.5], [.5, 1.5, 2.5], [.5, 2.5, 2.5]])
        H, edges = histogramdd(x, (2,3,3), range = [[-1,1], [0,3], [0,3]])
        answer = asarray([[[0,1,0], [0,0,1], [1,0,0]], [[0,1,0], [0,0,1],
            [0,0,1]]])
        assert_array_equal(H,answer)
        # Check normalization
        ed = [[-2,0,2], [0,1,2,3], [0,1,2,3]]
        H, edges = histogramdd(x, bins = ed, normed = True)
        assert(all(H == answer/12.))
        # Check that H has the correct shape.
        H, edges = histogramdd(x, (2,3,4), range = [[-1,1], [0,3], [0,4]],
            normed=True)
        answer = asarray([[[0,1,0,0], [0,0,1,0], [1,0,0,0]], [[0,1,0,0],
            [0,0,1,0], [0,0,1,0]]])
        assert_array_almost_equal(H, answer/6., 4)
        # Check that a sequence of arrays is accepted and H has the correct
        # shape.
        z = [squeeze(y) for y in split(x,3,axis=1)]
        H, edges = histogramdd(z, bins=(4,3,2),range=[[-2,2], [0,3], [0,2]])
        answer = asarray([[[0,0],[0,0],[0,0]],
                          [[0,1], [0,0], [1,0]],
                          [[0,1], [0,0],[0,0]],
                          [[0,0],[0,0],[0,0]]])
        assert_array_equal(H, answer)

        Z = zeros((5,5,5))
        Z[range(5), range(5), range(5)] = 1.
        H,edges = histogramdd([arange(5), arange(5), arange(5)], 5)
        assert_array_equal(H, Z)

    def test_shape_3d(self):
        # All possible permutations for bins of different lengths in 3D.
        bins = ((5, 4, 6), (6, 4, 5), (5, 6, 4), (4, 6, 5), (6, 5, 4),
            (4, 5, 6))
        r = rand(10,3)
        for b in bins:
            H, edges = histogramdd(r, b)
            assert(H.shape == b)

    def test_shape_4d(self):
        # All possible permutations for bins of different lengths in 4D.
        bins = ((7, 4, 5, 6), (4, 5, 7, 6), (5, 6, 4, 7), (7, 6, 5, 4),
            (5, 7, 6, 4), (4, 6, 7, 5), (6, 5, 7, 4), (7, 5, 4, 6),
            (7, 4, 6, 5), (6, 4, 7, 5), (6, 7, 5, 4), (4, 6, 5, 7),
            (4, 7, 5, 6), (5, 4, 6, 7), (5, 7, 4, 6), (6, 7, 4, 5),
            (6, 5, 4, 7), (4, 7, 6, 5), (4, 5, 6, 7), (7, 6, 4, 5),
            (5, 4, 7, 6), (5, 6, 7, 4), (6, 4, 5, 7), (7, 5, 6, 4))

        r = rand(10,4)
        for b in bins:
            H, edges = histogramdd(r, b)
            assert(H.shape == b)

    def test_weights(self):
        v = rand(100,2)
        hist, edges = histogramdd(v)
        n_hist, edges = histogramdd(v, normed=True)
        w_hist, edges = histogramdd(v, weights=ones(100))
        assert_array_equal(w_hist, hist)
        w_hist, edges = histogramdd(v, weights=ones(100)*2, normed=True)
        assert_array_equal(w_hist, n_hist)
        w_hist, edges = histogramdd(v, weights=ones(100, int)*2)
        assert_array_equal(w_hist, 2*hist)

    def test_identical_samples(self):
        x = zeros((10,2),int)
        hist, edges = histogramdd(x, bins=2)
        assert_array_equal(edges[0],array([-0.5,  0. ,  0.5]))

class TestUnique(TestCase):
    def test_simple(self):
        x = array([4,3,2,1,1,2,3,4, 0])
        assert(all(unique(x) == [0,1,2,3,4]))
        assert(unique(array([1,1,1,1,1])) == array([1]))
        x = ['widget', 'ham', 'foo', 'bar', 'foo', 'ham']
        assert(all(unique(x) ==  ['bar', 'foo', 'ham', 'widget']))
        x = array([5+6j, 1+1j, 1+10j, 10, 5+6j])
        assert(all(unique(x) == [1+1j, 1+10j, 5+6j, 10]))


class TestCheckFinite(TestCase):
    def test_simple(self):
        a = [1,2,3]
        b = [1,2,inf]
        c = [1,2,nan]
        numpy.lib.asarray_chkfinite(a)
        assert_raises(ValueError, numpy.lib.asarray_chkfinite, b)
        assert_raises(ValueError, numpy.lib.asarray_chkfinite, c)

class TestNaNFuncts(TestCase):
    def setUp(self):
        self.A = array([[[ nan,         0.01319214,  0.01620964],
                         [ 0.11704017,  nan,         0.75157887],
                         [ 0.28333658,  0.1630199 ,  nan       ]],
                        [[ 0.59541557,  nan,         0.37910852],
                         [ nan,         0.87964135,  nan       ],
                         [ 0.70543747,  nan,         0.34306596]],
                        [[ 0.72687499,  0.91084584,  nan       ],
                         [ 0.84386844,  0.38944762,  0.23913896],
                         [ nan,         0.37068164,  0.33850425]]])

    def test_nansum(self):
        assert_almost_equal(nansum(self.A), 8.0664079100000006)
        assert_almost_equal(nansum(self.A,0),
                            array([[ 1.32229056,  0.92403798,  0.39531816],
                                   [ 0.96090861,  1.26908897,  0.99071783],
                                   [ 0.98877405,  0.53370154,  0.68157021]]))
        assert_almost_equal(nansum(self.A,1),
                            array([[ 0.40037675,  0.17621204,  0.76778851],
                                   [ 1.30085304,  0.87964135,  0.72217448],
                                   [ 1.57074343,  1.6709751 ,  0.57764321]]))
        assert_almost_equal(nansum(self.A,2),
                            array([[ 0.02940178,  0.86861904,  0.44635648],
                                   [ 0.97452409,  0.87964135,  1.04850343],
                                   [ 1.63772083,  1.47245502,  0.70918589]]))

    def test_nanmin(self):
        assert_almost_equal(nanmin(self.A), 0.01319214)
        assert_almost_equal(nanmin(self.A,0),
                            array([[ 0.59541557,  0.01319214,  0.01620964],
                                   [ 0.11704017,  0.38944762,  0.23913896],
                                   [ 0.28333658,  0.1630199 ,  0.33850425]]))
        assert_almost_equal(nanmin(self.A,1),
                            array([[ 0.11704017,  0.01319214,  0.01620964],
                                   [ 0.59541557,  0.87964135,  0.34306596],
                                   [ 0.72687499,  0.37068164,  0.23913896]]))
        assert_almost_equal(nanmin(self.A,2),
                            array([[ 0.01319214,  0.11704017,  0.1630199 ],
                                   [ 0.37910852,  0.87964135,  0.34306596],
                                   [ 0.72687499,  0.23913896,  0.33850425]]))
        assert nanmin([nan, nan]) is nan

    def test_nanargmin(self):
        assert_almost_equal(nanargmin(self.A), 1)
        assert_almost_equal(nanargmin(self.A,0),
                            array([[1, 0, 0],
                                   [0, 2, 2],
                                   [0, 0, 2]]))
        assert_almost_equal(nanargmin(self.A,1),
                            array([[1, 0, 0],
                                   [0, 1, 2],
                                   [0, 2, 1]]))
        assert_almost_equal(nanargmin(self.A,2),
                            array([[1, 0, 1],
                                   [2, 1, 2],
                                   [0, 2, 2]]))

    def test_nanmax(self):
        assert_almost_equal(nanmax(self.A), 0.91084584000000002)
        assert_almost_equal(nanmax(self.A,0),
                            array([[ 0.72687499,  0.91084584,  0.37910852],
                                   [ 0.84386844,  0.87964135,  0.75157887],
                                   [ 0.70543747,  0.37068164,  0.34306596]]))
        assert_almost_equal(nanmax(self.A,1),
                            array([[ 0.28333658,  0.1630199 ,  0.75157887],
                                   [ 0.70543747,  0.87964135,  0.37910852],
                                   [ 0.84386844,  0.91084584,  0.33850425]]))
        assert_almost_equal(nanmax(self.A,2),
                            array([[ 0.01620964,  0.75157887,  0.28333658],
                                   [ 0.59541557,  0.87964135,  0.70543747],
                                   [ 0.91084584,  0.84386844,  0.37068164]]))

    def test_nanmin_allnan_on_axis(self):
        assert_array_equal(isnan(nanmin([[nan]*2]*3, axis=1)),
                     [True, True, True])


class TestCorrCoef(TestCase):
    def test_simple(self):
        A = array([[ 0.15391142,  0.18045767,  0.14197213],
                   [ 0.70461506,  0.96474128,  0.27906989],
                   [ 0.9297531 ,  0.32296769,  0.19267156]])
        B = array([[ 0.10377691,  0.5417086 ,  0.49807457],
                   [ 0.82872117,  0.77801674,  0.39226705],
                   [ 0.9314666 ,  0.66800209,  0.03538394]])
        assert_almost_equal(corrcoef(A),
                            array([[ 1.        ,  0.9379533 , -0.04931983],
                                   [ 0.9379533 ,  1.        ,  0.30007991],
                                   [-0.04931983,  0.30007991,  1.        ]]))
        assert_almost_equal(corrcoef(A,B),
                            array([[ 1.        ,  0.9379533 , -0.04931983,
                                     0.30151751,  0.66318558, 0.51532523],
                                   [ 0.9379533 ,  1.        , 0.30007991,
                                     -0.04781421,  0.88157256, 0.78052386],
                                   [-0.04931983,  0.30007991,  1.        ,
                                     -0.96717111,  0.71483595, 0.83053601],
                                   [ 0.30151751, -0.04781421, -0.96717111,
                                     1.        , -0.51366032, -0.66173113],
                                   [ 0.66318558,  0.88157256,  0.71483595,
                                     -0.51366032,  1.        , 0.98317823],
                                   [ 0.51532523,  0.78052386,  0.83053601,
                                     -0.66173113,  0.98317823, 1.        ]]))



class Test_i0(TestCase):
    def test_simple(self):
        assert_almost_equal(i0(0.5), array(1.0634833707413234))
        A = array([ 0.49842636,  0.6969809 ,  0.22011976,  0.0155549])
        assert_almost_equal(i0(A),
                            array([ 1.06307822,  1.12518299,  1.01214991,  1.00006049]))
        B = array([[ 0.827002  ,  0.99959078],
                   [ 0.89694769,  0.39298162],
                   [ 0.37954418,  0.05206293],
                   [ 0.36465447,  0.72446427],
                   [ 0.48164949,  0.50324519]])
        assert_almost_equal(i0(B),
                            array([[ 1.17843223,  1.26583466],
                                   [ 1.21147086,  1.0389829 ],
                                   [ 1.03633899,  1.00067775],
                                   [ 1.03352052,  1.13557954],
                                   [ 1.0588429 ,  1.06432317]]))

class TestKaiser(TestCase):
    def test_simple(self):
        assert_almost_equal(kaiser(0,1.0), array([]))
        assert isnan(kaiser(1,1.0))
        assert_almost_equal(kaiser(2,1.0), array([ 0.78984831,  0.78984831]))
        assert_almost_equal(kaiser(5,1.0),
                            array([ 0.78984831,  0.94503323,  1.        ,
                                    0.94503323,  0.78984831]))
        assert_almost_equal(kaiser(5,1.56789),
                            array([ 0.58285404,  0.88409679,  1.        ,
                                    0.88409679,  0.58285404]))

    def test_int_beta(self):
        kaiser(3, 4)

class TestMsort(TestCase):
    def test_simple(self):
        A = array([[ 0.44567325,  0.79115165,  0.5490053 ],
                   [ 0.36844147,  0.37325583,  0.96098397],
                   [ 0.64864341,  0.52929049,  0.39172155]])
        assert_almost_equal(msort(A),
                            array([[ 0.36844147,  0.37325583,  0.39172155],
                                   [ 0.44567325,  0.52929049,  0.5490053 ],
                                   [ 0.64864341,  0.79115165,  0.96098397]]))

class TestMeshgrid(TestCase):
    def test_simple(self):
        [X, Y] = meshgrid([1,2,3], [4,5,6,7])
        assert all(X == array([[1, 2, 3],
                               [1, 2, 3],
                               [1, 2, 3],
                               [1, 2, 3]]))
        assert all(Y == array([[4, 4, 4],
                               [5, 5, 5],
                               [6, 6, 6],
                               [7, 7, 7]]))


class TestPiecewise(TestCase):
    def test_simple(self):
        # Condition is single bool list
        x = piecewise([0, 0], [True, False], [1])
        assert_array_equal(x, [1, 0])

        # List of conditions: single bool list
        x = piecewise([0, 0], [[True, False]], [1])
        assert_array_equal(x, [1, 0])

        # Conditions is single bool array
        x = piecewise([0, 0], array([True, False]), [1])
        assert_array_equal(x, [1, 0])

        # Condition is single int array
        x = piecewise([0, 0], array([1, 0]), [1])
        assert_array_equal(x, [1, 0])

        # List of conditions: int array
        x = piecewise([0, 0], [array([1, 0])], [1])
        assert_array_equal(x, [1, 0])


        x = piecewise([0, 0], [[False, True]], [lambda x: -1])
        assert_array_equal(x, [0, -1])

        x = piecewise([1, 2], [[True, False], [False, True]], [3, 4])
        assert_array_equal(x, [3, 4])

    def test_default(self):
        # No value specified for x[1], should be 0
        x = piecewise([1, 2], [True, False], [2])
        assert_array_equal(x, [2, 0])

        # Should set x[1] to 3
        x = piecewise([1, 2], [True, False], [2, 3])
        assert_array_equal(x, [2, 3])

    def test_0d(self):
        x = array(3)
        y = piecewise(x, x>3, [4, 0])
        assert y.ndim == 0
        assert y == 0

def compare_results(res,desired):
    for i in range(len(desired)):
        assert_array_equal(res[i],desired[i])

if __name__ == "__main__":
    run_module_suite()
