def build_executor(py_ufunc, pyast_function, operands,
aterm_subgraph_root, strategy='chunked'):
""" Build a ufunc and an wrapping executor from a Python AST """
result_dtype = unannotate_dtype(aterm_subgraph_root)
operand_dtypes = map(unannotate_dtype, operands)
vectorizer = Vectorize(py_ufunc)
vectorizer.add(restype=minitype(result_dtype),
argtypes=map(minitype, operand_dtypes))
ufunc = vectorizer.build_ufunc()
# Get a string of the operation for debugging
return_stat = pyast_function.body[0]
operation = getsource(return_stat.value)
# TODO: build an executor tree and substitute where we can evaluate
executor = executors.ElementwiseLLVMExecutor(
strategy,
ufunc,
operand_dtypes,
result_dtype,
operation=operation,
)
return executor
def build_executor(py_ufunc,
pyast_function,
operands,
aterm_subgraph_root,
strategy='chunked'):
""" Build a ufunc and an wrapping executor from a Python AST """
result_dtype = unannotate_dtype(aterm_subgraph_root)
operand_dtypes = map(unannotate_dtype, operands)
vectorizer = Vectorize(py_ufunc)
vectorizer.add(restype=minitype(result_dtype),
argtypes=map(minitype, operand_dtypes))
ufunc = vectorizer.build_ufunc()
# Get a string of the operation for debugging
return_stat = pyast_function.body[0]
operation = getsource(return_stat.value)
# TODO: build an executor tree and substitute where we can evaluate
executor = executors.ElementwiseLLVMExecutor(
strategy,
ufunc,
operand_dtypes,
result_dtype,
operation=operation,
)
return executor
def build_executor(py_ufunc, operands, aterm_subgraph_root):
""" Build a ufunc and an wrapping executor from a Python AST """
result_dtype = unannotate_dtype(aterm_subgraph_root)
operand_dtypes = map(unannotate_dtype, operands)
vectorizer = Vectorize(py_ufunc)
vectorizer.add(restype=minitype(result_dtype),
argtypes=map(minitype, operand_dtypes))
ufunc = vectorizer.build_ufunc()
# TODO: build an executor tree and substitute where we can evaluate
executor = executors.ElementwiseLLVMExecutor(
ufunc,
operand_dtypes,
result_dtype,
)
return executor
from numba.decorators import jit
from numba import *
from numpy import sqrt
from numpy import log
from numpy import exp
f, d = f4, f8
import pyfits
def logThreshold(img_mat):
return 10*log(img_mat+10)+10
bv = Vectorize(logThreshold, backend='bytecode')
bv.add(restype=f, argtypes=[f])
b_poly_d = bv.build_ufunc()
pv = Vectorize(logThreshold, target='parallel', backend='bytecode')
pv.add(restype=f, argtypes=[f])
p_poly_d = pv.build_ufunc()
f1 = pyfits.getdata('fpC-003836-r3-0254.fit')
iterNum = 10
