# 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) Traceback (most recent call last): ... ValueError: ndarray is not C contiguous >>> test_f_contig(c_arr) Traceback (most recent call last): ... ValueError: ndarray is not Fortran contiguous >>> test_c_contig(c_arr[::2,::2]) 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.long, inc1_long_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) Traceback (most recent call last): ... ValueError: Non-native byte order not supported >>> 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)))) Traceback (most recent call last): ... ValueError: Buffer dtype mismatch; next field is at offset 4 but 1 expected >>> print(test_unpacked_align(np.zeros((1,), dtype=np.dtype('b,i', align=False)))) Traceback (most recent call last): ... ValueError: Buffer dtype mismatch; next field is at offset 1 but 4 expected >>> 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')]) """ 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=b'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=b'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([b"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=b'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=b'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_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 (b'F', b'D', b'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(b'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=b'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'b') cdef packed struct PackedStruct: char a int b cdef struct UnpackedStruct: char a int b 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_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"