# tag: numpy
# cannot be named "numpy" in order to not clash with the numpy module!

cimport numpy as np

def little_endian():
    cdef int endian_detector = 1
    return (<char*>&endian_detector)[0] != 0

if little_endian():
    my_endian = '<'
    other_endian = '>'
else:
    my_endian = '>'
    other_endian = '<'

try:
    import numpy as np
    __doc__ = u"""

    >>> assert_dtype_sizes()

    >>> basic()
    [[0 1 2 3 4]
     [5 6 7 8 9]]
    2 0 9 5

    >>> three_dim()
    [[[  0.   1.   2.   3.]
      [  4.   5.   6.   7.]]
    <_BLANKLINE_>
     [[  8.   9.  10.  11.]
      [ 12.  13.  14.  15.]]
    <_BLANKLINE_>
     [[ 16.  17.  18.  19.]
      [ 20.  21.  22.  23.]]]
    6.0 0.0 13.0 8.0
    
    >>> obj_array()
    [a 1 {}]
    a 1 {}

    Test various forms of slicing, picking etc.
    >>> a = np.arange(10, dtype='l').reshape(2, 5)
    >>> print_long_2d(a)
    0 1 2 3 4
    5 6 7 8 9
    >>> print_long_2d(a[::-1, ::-1])
    9 8 7 6 5
    4 3 2 1 0
    >>> print_long_2d(a[1:2, 1:3])
    6 7
    >>> print_long_2d(a[::2, ::2])
    0 2 4
    >>> print_long_2d(a[::4, :])
    0 1 2 3 4
    >>> print_long_2d(a[:, 1:5:2])
    1 3
    6 8
    >>> print_long_2d(a[:, 5:1:-2])
    4 2
    9 7
    >>> print_long_2d(a[:, [3, 1]])
    3 1
    8 6
    >>> print_long_2d(a.T)
    0 5
    1 6
    2 7
    3 8
    4 9

    Write to slices
    >>> b = a.copy()
    >>> put_range_long_1d(b[:, 3])
    >>> print (b)
    [[0 1 2 0 4]
     [5 6 7 1 9]]
    >>> put_range_long_1d(b[::-1, 3])
    >>> print (b)
    [[0 1 2 1 4]
     [5 6 7 0 9]]
    >>> a = np.zeros(9, dtype='l')
    >>> put_range_long_1d(a[1::3])
    >>> print (a)
    [0 0 0 0 1 0 0 2 0]

    Write to picked subarrays. This should NOT change the original
    array as picking creates a new mutable copy.
    >>> a = np.zeros(10, dtype='l').reshape(2, 5)
    >>> put_range_long_1d(a[[0, 0, 1, 1, 0], [0, 1, 2, 4, 3]])
    >>> print (a)
    [[0 0 0 0 0]
     [0 0 0 0 0]]

    Test contiguous access modes:
    >>> c_arr = np.array(np.arange(12, dtype='i').reshape(3,4), order='C')
    >>> f_arr = np.array(np.arange(12, dtype='i').reshape(3,4), order='F')
    >>> test_c_contig(c_arr)
    0 1 2 3
    4 5 6 7
    8 9 10 11
    >>> test_f_contig(f_arr)
    0 1 2 3
    4 5 6 7
    8 9 10 11
    >>> test_c_contig(f_arr) #doctest: +ELLIPSIS
    Traceback (most recent call last):
       ...
    ValueError: ndarray is not C...contiguous
    >>> test_f_contig(c_arr) #doctest: +ELLIPSIS
    Traceback (most recent call last):
       ...
    ValueError: ndarray is not Fortran contiguous
    >>> test_c_contig(c_arr[::2,::2]) #doctest: +ELLIPSIS
    Traceback (most recent call last):
       ...
    ValueError: ndarray is not C...contiguous
    
    >>> test_dtype('b', inc1_byte)
    >>> test_dtype('B', inc1_ubyte)
    >>> test_dtype('h', inc1_short)
    >>> test_dtype('H', inc1_ushort)
    >>> test_dtype('i', inc1_int)
    >>> test_dtype('I', inc1_uint)
    >>> test_dtype('l', inc1_long)
    >>> test_dtype('L', inc1_ulong)
    
    >>> test_dtype('f', inc1_float)
    >>> test_dtype('d', inc1_double)
    >>> test_dtype('g', inc1_longdouble)
    >>> test_dtype('O', inc1_object)
    >>> test_dtype('F', inc1_cfloat) # numpy format codes differ from buffer ones here
    >>> test_dtype('D', inc1_cdouble)
    >>> test_dtype('G', inc1_clongdouble)
    >>> test_dtype('F', inc1_cfloat_struct)
    >>> test_dtype('D', inc1_cdouble_struct)
    >>> test_dtype('G', inc1_clongdouble_struct)

    >>> test_dtype(np.int, inc1_int_t)
    >>> test_dtype(np.longlong, inc1_longlong_t)
    >>> test_dtype(np.float, inc1_float_t)
    >>> test_dtype(np.double, inc1_double_t)
    >>> test_dtype(np.intp, inc1_intp_t)
    >>> test_dtype(np.uintp, inc1_uintp_t)

    >>> test_dtype(np.longdouble, inc1_longdouble_t)

    >>> test_dtype(np.int32, inc1_int32_t)
    >>> test_dtype(np.float64, inc1_float64_t)

    Endian tests:
    >>> test_dtype('%si' % my_endian, inc1_int)
    >>> test_dtype('%si' % other_endian, inc1_int)  #doctest: +ELLIPSIS
    Traceback (most recent call last):
       ...
    ValueError: ...
    


    >>> test_recordarray()
    
    >>> print(test_nested_dtypes(np.zeros((3,), dtype=np.dtype([\
            ('a', np.dtype('i,i')),\
            ('b', np.dtype('i,i'))\
        ]))))
    array([((0, 0), (0, 0)), ((1, 2), (1, 4)), ((1, 2), (1, 4))], 
          dtype=[('a', [('f0', '!i4'), ('f1', '!i4')]), ('b', [('f0', '!i4'), ('f1', '!i4')])])

    >>> print(test_nested_dtypes(np.zeros((3,), dtype=np.dtype([\
            ('a', np.dtype('i,f')),\
            ('b', np.dtype('i,i'))\
        ]))))
    Traceback (most recent call last):
        ...
    ValueError: Buffer dtype mismatch, expected 'int' but got 'float' in 'DoubleInt.y'

    >>> print(test_packed_align(np.zeros((1,), dtype=np.dtype('b,i', align=False))))
    array([(22, 23)], 
          dtype=[('f0', '|i1'), ('f1', '!i4')])
    >>> print(test_unpacked_align(np.zeros((1,), dtype=np.dtype('b,i', align=True))))
    array([(22, 23)], 
          dtype=[('f0', '|i1'), ('', '|V3'), ('f1', '!i4')])

    >>> print(test_packed_align(np.zeros((1,), dtype=np.dtype('b,i', align=True)))) #doctest: +ELLIPSIS
    Traceback (most recent call last):
        ...
    ValueError: ...

    >>> print(test_unpacked_align(np.zeros((1,), dtype=np.dtype('b,i', align=False)))) #doctest: +ELLIPSIS
    Traceback (most recent call last):
        ...
    ValueError: ...


    >>> test_good_cast()
    True
    >>> test_bad_cast()
    Traceback (most recent call last):
        ...
    ValueError: Item size of buffer (1 byte) does not match size of 'int' (4 bytes)

    >>> test_complextypes()
    1,1
    1,1
    8,16

    >>> test_point_record()
    array([(0.0, 0.0), (1.0, -1.0), (2.0, -2.0)], 
          dtype=[('x', '!f8'), ('y', '!f8')])
    
"""

    if np.__version__ >= '1.6':
        __doc__ += u"""
        The following expose bugs in Numpy (versions prior to 2011-04-02):
        
        >>> print(test_partially_packed_align(np.zeros((1,), dtype=np.dtype([('a', 'b'), ('b', 'i'), ('sub', np.dtype('b,i')), ('c', 'i')], align=True))))
        array([(22, 23, (24, 25), 26)], 
              dtype=[('a', '|i1'), ('', '|V3'), ('b', '!i4'), ('sub', [('f0', '|i1'), ('f1', '!i4')]), ('', '|V3'), ('c', '!i4')])
    
        >>> print(test_partially_packed_align_2(np.zeros((1,), dtype=np.dtype([('a', 'b'), ('b', 'i'), ('c', 'b'), ('sub', np.dtype('b,i', align=True))]))))
        array([(22, 23, 24, (27, 28))], 
              dtype=[('a', '|i1'), ('b', '!i4'), ('c', '|i1'), ('sub', [('f0', '|i1'), ('', '|V3'), ('f1', '!i4')])])
    
        >>> print(test_partially_packed_align(np.zeros((1,), dtype=np.dtype([('a', 'b'), ('b', 'i'), ('sub', np.dtype('b,i')), ('c', 'i')], align=False)))) #doctest: +ELLIPSIS
        Traceback (most recent call last):
            ...
        ValueError: ...
    
        >>> print(test_partially_packed_align_2(np.zeros((1,), dtype=np.dtype([('a', 'b'), ('b', 'i'), ('c', 'b'), ('sub', np.dtype('b,i', align=False))])))) #doctest: +ELLIPSIS
        Traceback (most recent call last):
            ...
        ValueError: ...
        """

except:
    __doc__ = u""


def assert_dtype_sizes():
    assert sizeof(np.int8_t) == 1
    assert sizeof(np.int16_t) == 2
    assert sizeof(np.int32_t) == 4
    assert sizeof(np.int64_t) == 8
    assert sizeof(np.uint8_t) == 1
    assert sizeof(np.uint16_t) == 2
    assert sizeof(np.uint32_t) == 4
    assert sizeof(np.uint64_t) == 8
    assert sizeof(np.float32_t) == 4
    assert sizeof(np.float64_t) == 8
    assert sizeof(np.complex64_t) == 8
    assert sizeof(np.complex128_t) == 16

def ndarray_str(arr):
    u"""
    Since Py2.3 doctest don't support <BLANKLINE>, manually replace blank lines
    with <_BLANKLINE_>
    """
    return unicode(arr).replace(u'\n\n', u'\n<_BLANKLINE_>\n')    

def basic():
    cdef object[int, ndim=2] buf = np.arange(10, dtype='i').reshape((2, 5))
    print buf
    print buf[0, 2], buf[0, 0], buf[1, 4], buf[1, 0]

def three_dim():
    cdef object[double, ndim=3] buf = np.arange(24, dtype='d').reshape((3,2,4))
    print ndarray_str(buf)
    print buf[0, 1, 2], buf[0, 0, 0], buf[1, 1, 1], buf[1, 0, 0]

def obj_array():
    cdef object[object, ndim=1] buf = np.array(["a", 1, {}])
    print buf
    print buf[0], buf[1], buf[2]


def print_long_2d(np.ndarray[long, ndim=2] arr):
    cdef int i, j
    for i in range(arr.shape[0]):
        print u" ".join([unicode(arr[i, j]) for j in range(arr.shape[1])])

def put_range_long_1d(np.ndarray[long] arr):
    u"""Writes 0,1,2,... to array and returns array"""
    cdef int value = 0, i
    for i in range(arr.shape[0]):
        arr[i] = value
        value += 1

def test_c_contig(np.ndarray[int, ndim=2, mode='c'] arr):
    cdef int i, j
    for i in range(arr.shape[0]):
        print u" ".join([unicode(arr[i, j]) for j in range(arr.shape[1])])

def test_f_contig(np.ndarray[int, ndim=2, mode='fortran'] arr):
    cdef int i, j
    for i in range(arr.shape[0]):
        print u" ".join([unicode(arr[i, j]) for j in range(arr.shape[1])])

# Exhaustive dtype tests -- increments element [1] by 1 (or 1+1j) for all dtypes
def inc1_byte(np.ndarray[char] arr):                    arr[1] += 1
def inc1_ubyte(np.ndarray[unsigned char] arr):          arr[1] += 1
def inc1_short(np.ndarray[short] arr):                  arr[1] += 1
def inc1_ushort(np.ndarray[unsigned short] arr):        arr[1] += 1
def inc1_int(np.ndarray[int] arr):                      arr[1] += 1
def inc1_uint(np.ndarray[unsigned int] arr):            arr[1] += 1
def inc1_long(np.ndarray[long] arr):                    arr[1] += 1
def inc1_ulong(np.ndarray[unsigned long] arr):          arr[1] += 1
def inc1_longlong(np.ndarray[long long] arr):           arr[1] += 1
def inc1_ulonglong(np.ndarray[unsigned long long] arr): arr[1] += 1

def inc1_float(np.ndarray[float] arr):                  arr[1] += 1
def inc1_double(np.ndarray[double] arr):                arr[1] += 1
def inc1_longdouble(np.ndarray[long double] arr):       arr[1] += 1

def inc1_cfloat(np.ndarray[float complex] arr):            arr[1] = arr[1] + 1 + 1j
def inc1_cdouble(np.ndarray[double complex] arr):          arr[1] = (arr[1] + 1) + 1j
def inc1_clongdouble(np.ndarray[long double complex] arr): arr[1] = arr[1] + (1 + 1j)

def inc1_cfloat_struct(np.ndarray[np.cfloat_t] arr):
    arr[1].real += 1
    arr[1].imag += 1
    
def inc1_cdouble_struct(np.ndarray[np.cdouble_t] arr):
    arr[1].real += 1
    arr[1].imag += 1

def inc1_clongdouble_struct(np.ndarray[np.clongdouble_t] arr):
    cdef long double x
    x = arr[1].real + 1
    arr[1].real = x
    arr[1].imag = arr[1].imag + 1

def inc1_object(np.ndarray[object] arr):
    o = arr[1]
    o += 1
    arr[1] = o # unfortunately, += segfaults for objects


def inc1_int_t(np.ndarray[np.int_t] arr):               arr[1] += 1
def inc1_long_t(np.ndarray[np.long_t] arr):             arr[1] += 1
def inc1_longlong_t(np.ndarray[np.longlong_t] arr):     arr[1] += 1
def inc1_float_t(np.ndarray[np.float_t] arr):           arr[1] += 1
def inc1_double_t(np.ndarray[np.double_t] arr):         arr[1] += 1
def inc1_longdouble_t(np.ndarray[np.longdouble_t] arr): arr[1] += 1
def inc1_intp_t(np.ndarray[np.intp_t] arr):             arr[1] += 1
def inc1_uintp_t(np.ndarray[np.uintp_t] arr):           arr[1] += 1

# The tests below only work on platforms that has the given types
def inc1_int32_t(np.ndarray[np.int32_t] arr):           arr[1] += 1
def inc1_float64_t(np.ndarray[np.float64_t] arr):       arr[1] += 1

    
def test_dtype(dtype, inc1):
    if dtype in ("g", np.longdouble,
                 "G", np.clongdouble):
        if sizeof(double) == sizeof(long double): # MSVC
            return
    if dtype in ('F', 'D', 'G'):
        a = np.array([0, 10+10j], dtype=dtype)
        inc1(a)
        if a[1] != (11 + 11j): print u"failed!", a[1]
    else:
        a = np.array([0, 10], dtype=dtype)
        inc1(a)
        if a[1] != 11: print u"failed!"

cdef struct DoubleInt:
    int x, y

def test_recordarray():
    cdef object[DoubleInt] arr
    arr = np.array([(5,5), (4, 6)], dtype=np.dtype('i,i'))
    cdef DoubleInt rec
    rec = arr[0]
    if rec.x != 5: print u"failed"
    if rec.y != 5: print u"failed"
    rec.y += 5
    arr[1] = rec
    arr[0].x -= 2
    arr[0].y += 3
    if arr[0].x != 3: print u"failed"
    if arr[0].y != 8: print u"failed"
    if arr[1].x != 5: print u"failed"
    if arr[1].y != 10: print u"failed"

cdef struct NestedStruct:
    DoubleInt a
    DoubleInt b

cdef struct BadDoubleInt:
    float x
    int y

cdef struct BadNestedStruct:
    DoubleInt a
    BadDoubleInt b

def test_nested_dtypes(obj):
    cdef object[NestedStruct] arr = obj
    arr[1].a.x = 1
    arr[1].a.y = 2
    arr[1].b.x = arr[0].a.y + 1
    arr[1].b.y = 4
    arr[2] = arr[1]
    return repr(arr).replace('<', '!').replace('>', '!')

def test_bad_nested_dtypes():
    cdef object[BadNestedStruct] arr

def test_good_cast():
    # Check that a signed int can round-trip through casted unsigned int access
    cdef np.ndarray[unsigned int, cast=True] arr = np.array([-100], dtype='i')
    cdef unsigned int data = arr[0]
    return -100 == <int>data

def test_bad_cast():
    # This should raise an exception
    cdef np.ndarray[int, cast=True] arr = np.array([1], dtype='b')

cdef packed struct PackedStruct:
    char a
    int b

cdef struct UnpackedStruct:
    char a
    int b

cdef struct PartiallyPackedStruct:
    char a
    int b
    PackedStruct sub
    int c

cdef packed struct PartiallyPackedStruct2:
    char a
    int b
    char c
    UnpackedStruct sub

def test_packed_align(np.ndarray[PackedStruct] arr):
    arr[0].a = 22
    arr[0].b = 23
    return repr(arr).replace('<', '!').replace('>', '!')

def test_unpacked_align(np.ndarray[UnpackedStruct] arr):
    arr[0].a = 22
    arr[0].b = 23    
    return repr(arr).replace('<', '!').replace('>', '!')

def test_partially_packed_align(np.ndarray[PartiallyPackedStruct] arr):
    arr[0].a = 22
    arr[0].b = 23
    arr[0].sub.a = 24
    arr[0].sub.b = 25
    arr[0].c = 26
    return repr(arr).replace('<', '!').replace('>', '!')

def test_partially_packed_align_2(np.ndarray[PartiallyPackedStruct2] arr):
    arr[0].a = 22
    arr[0].b = 23
    arr[0].c = 24
    arr[0].sub.a = 27
    arr[0].sub.b = 28
    return repr(arr).replace('<', '!').replace('>', '!')

def test_complextypes():
    cdef np.complex64_t x64 = 1, y64 = 1j
    cdef np.complex128_t x128 = 1, y128 = 1j
    x64 = x64 + y64
    print "%.0f,%.0f" % (x64.real, x64.imag)
    x128 = x128 + y128
    print "%.0f,%.0f" % (x128.real, x128.imag)
    print "%d,%d" % (sizeof(x64), sizeof(x128))


cdef struct Point:
    np.float64_t x, y

def test_point_record():
    cdef np.ndarray[Point] test
    Point_dtype = np.dtype([('x', np.float64), ('y', np.float64)])
    test = np.zeros(3, Point_dtype)
    cdef int i
    for i in range(3):
        test[i].x = i
        test[i].y = -i
    print repr(test).replace('<', '!').replace('>', '!')

include "numpy_common.pxi"
