135 lines
2.9 KiB
Python
135 lines
2.9 KiB
Python
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import cmath
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import numpy as np
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from numba import float32
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from numba.types import unicode_type, i8
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from numba.pycc import CC, exportmany, export
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from numba.tests.support import has_blas
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from numba import typed
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#
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# New API
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#
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cc = CC('pycc_test_simple')
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cc.use_nrt = False
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# Note the first signature omits the return type
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@cc.export('multf', (float32, float32))
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@cc.export('multi', 'i4(i4, i4)')
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def mult(a, b):
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return a * b
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# Test imported C globals such as Py_None, PyExc_ZeroDivisionError
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@cc.export('get_none', 'none()')
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def get_none():
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return None
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@cc.export('div', 'f8(f8, f8)')
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def div(x, y):
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return x / y
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_two = 2
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# This one can't be compiled by the legacy API as it doesn't execute
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# the script in a proper module.
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@cc.export('square', 'i8(i8)')
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def square(u):
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return u ** _two
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# These ones need helperlib
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cc_helperlib = CC('pycc_test_helperlib')
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cc_helperlib.use_nrt = False
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@cc_helperlib.export('power', 'i8(i8, i8)')
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def power(u, v):
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return u ** v
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@cc_helperlib.export('sqrt', 'c16(c16)')
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def sqrt(u):
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return cmath.sqrt(u)
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@cc_helperlib.export('size', 'i8(f8[:])')
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def size(arr):
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return arr.size
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# Exercise linking to Numpy math functions
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@cc_helperlib.export('np_sqrt', 'f8(f8)')
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def np_sqrt(u):
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return np.sqrt(u)
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@cc_helperlib.export('spacing', 'f8(f8)')
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def np_spacing(u):
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return np.spacing(u)
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# This one clashes with libc random() unless pycc is careful with naming.
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@cc_helperlib.export('random', 'f8(i4)')
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def random_impl(seed):
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if seed != -1:
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np.random.seed(seed)
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return np.random.random()
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# These ones need NRT
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cc_nrt = CC('pycc_test_nrt')
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@cc_nrt.export('zero_scalar', 'f8(i4)')
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def zero_scalar(n):
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arr = np.zeros(n)
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return arr[-1]
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if has_blas:
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# This one also needs BLAS
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@cc_nrt.export('vector_dot', 'f8(i4)')
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def vector_dot(n):
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a = np.linspace(1, n, n)
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return np.dot(a, a)
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# This one needs an environment
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@cc_nrt.export('zeros', 'f8[:](i4)')
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def zeros(n):
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return np.zeros(n)
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# requires list dtor, #issue3535
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@cc_nrt.export('np_argsort', 'intp[:](float64[:])')
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def np_argsort(arr):
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return np.argsort(arr)
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#
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# Legacy API
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#
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exportmany(['multf f4(f4,f4)', 'multi i4(i4,i4)'])(mult)
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# Needs to link to helperlib to due with complex arguments
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# export('multc c16(c16,c16)')(mult)
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export('mult f8(f8, f8)')(mult)
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@cc_nrt.export('dict_usecase', 'intp[:](intp[:])')
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def dict_usecase(arr):
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d = typed.Dict()
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for i in range(arr.size):
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d[i] = arr[i]
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out = np.zeros_like(arr)
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for k, v in d.items():
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out[k] = k * v
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return out
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# checks for issue #6386
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@cc_nrt.export('internal_str_dict', i8(unicode_type))
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def internal_str_dict(x):
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d = typed.Dict.empty(unicode_type,i8)
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if(x not in d):
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d[x] = len(d)
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return len(d)
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@cc_nrt.export('hash_str', i8(unicode_type))
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def internal_str_dict(x):
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return hash(x)
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@cc_nrt.export('hash_literal_str_A', i8())
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def internal_str_dict():
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return hash("A")
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