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from __future__ import absolute_import, print_function
import parser
import sys
from . import ast_tools
from . import slice_handler
from . import size_check
from . import converters
import numpy
import copy
from . import inline_tools
from .inline_tools import attempt_function_call
function_catalog = inline_tools.function_catalog
function_cache = inline_tools.function_cache
def blitz(expr,local_dict=None, global_dict=None,check_size=1,verbose=0,**kw):
# this could call inline, but making a copy of the
# code here is more efficient for several reasons.
global function_catalog
# this grabs the local variables from the *previous* call
# frame -- that is the locals from the function that called
# inline.
call_frame = sys._getframe().f_back
if local_dict is None:
local_dict = call_frame.f_locals
if global_dict is None:
global_dict = call_frame.f_globals
# 1. Check the sizes of the arrays and make sure they are compatible.
# This is expensive, so unsetting the check_size flag can save a lot
# of time. It also can cause core-dumps if the sizes of the inputs
# aren't compatible.
if check_size and not size_check.check_expr(expr,local_dict,global_dict):
raise ValueError("inputs failed to pass size check.")
# 2. try local cache
results = apply(function_cache[expr],(local_dict,global_dict))
return results
results = attempt_function_call(expr,local_dict,global_dict)
# 3. build the function
except ValueError:
# This section is pretty much the only difference
# between blitz and inline
ast = parser.suite(expr)
ast_list = ast.tolist()
expr_code = ast_to_blitz_expr(ast_list)
arg_names = ast_tools.harvest_variables(ast_list)
module_dir = global_dict.get('__file__',None)
#func = inline_tools.compile_function(expr_code,arg_names,
# local_dict,global_dict,
# module_dir,auto_downcast = 1)
func = inline_tools.compile_function(expr_code,arg_names,local_dict,
results = attempt_function_call(expr,local_dict,global_dict)
except ValueError:
print('warning: compilation failed. Executing as python code')
exec(expr, global_dict, local_dict)
def ast_to_blitz_expr(ast_seq):
""" Convert an ast_sequence to a blitz expression.
# Don't overwrite orignal sequence in call to transform slices.
ast_seq = copy.deepcopy(ast_seq)
# Build the actual program statement from ast_seq
expr = ast_tools.ast_to_string(ast_seq)
# Now find and replace specific symbols to convert this to
# a blitz++ compatible statement.
# I'm doing this with string replacement here. It could
# also be done on the actual ast tree (and probably should from
# a purest standpoint...).
# this one isn't necessary but it helps code readability
# and compactness. It requires that
# Range _all = blitz::Range::all();
# be included in the generated code.
# These could all alternatively be done to the ast in
# build_slice_atom()
expr = expr.replace('slice(_beg,_end)', '_all')
expr = expr.replace('slice', 'blitz::Range')
expr = expr.replace('[','(')
expr = expr.replace(']', ')')
expr = expr.replace('_stp', '1')
# Instead of blitz::fromStart and blitz::toEnd. This requires
# the following in the generated code.
# Range _beg = blitz::fromStart;
# Range _end = blitz::toEnd;
#expr = expr.replace('_beg', 'blitz::fromStart' )
#expr = expr.replace('_end', 'blitz::toEnd' )
return expr + ';\n'
def test_function():
expr = "ex[:,1:,1:] = k + ca_x[:,1:,1:] * ex[:,1:,1:]" \
"+ cb_y_x[:,1:,1:] * (hz[:,1:,1:] - hz[:,:-1,1:])"\
"- cb_z_x[:,1:,1:] * (hy[:,1:,1:] - hy[:,1:,:-1])"
#ast = parser.suite('a = (b + c) * sin(d)')
ast = parser.suite(expr)
k = 1.
ex = numpy.ones((1,1,1),dtype=numpy.float32)
ca_x = numpy.ones((1,1,1),dtype=numpy.float32)
cb_y_x = numpy.ones((1,1,1),dtype=numpy.float32)
cb_z_x = numpy.ones((1,1,1),dtype=numpy.float32)
hz = numpy.ones((1,1,1),dtype=numpy.float32)
hy = numpy.ones((1,1,1),dtype=numpy.float32)
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