"""
Numexpr is a fast numerical expression evaluator for NumPy. With it,
expressions that operate on arrays (like "3*a+4*b") are accelerated
and use less memory than doing the same calculation in Python.
See:
https://github.com/pydata/numexpr
for more info about it.
"""
from __config__ import show as show_config, get_info
if get_info('mkl'):
use_vml = True
else:
use_vml = False
is_cpu_amd_intel = False # DEPRECATION WARNING: WILL BE REMOVED IN FUTURE RELEASE
# cpuinfo imports were moved into the test submodule function that calls them
# to improve import times.
import os, os.path
import platform
from numexpr.expressions import E
from numexpr.necompiler import NumExpr, disassemble, evaluate, re_evaluate
# from numexpr.tests import test, print_versions
from numexpr.interpreter import MAX_THREADS
"""
Numexpr is a fast numerical expression evaluator for NumPy. With it,
expressions that operate on arrays (like "3*a+4*b") are accelerated
and use less memory than doing the same calculation in Python.
See:
https://github.com/pydata/numexpr
for more info about it.
"""
from __config__ import show as show_config, get_info
if get_info('mkl'):
use_vml = True
else:
use_vml = False
from cpuinfo import cpu
if cpu.is_AMD() or cpu.is_Intel():
is_cpu_amd_intel = True
else:
is_cpu_amd_intel = False
import os, os.path
import platform
from numexpr.expressions import E
from numexpr.necompiler import NumExpr, disassemble, evaluate, re_evaluate
"""
Numexpr is a fast numerical expression evaluator for NumPy. With it,
expressions that operate on arrays (like "3*a+4*b") are accelerated
and use less memory than doing the same calculation in Python.
See:
http://code.google.com/p/numexpr/
for more info about it.
"""
from __config__ import show as show_config, get_info
if get_info("mkl"):
use_vml = True
else:
use_vml = False
from cpuinfo import cpu
if cpu.is_AMD() or cpu.is_Intel():
is_cpu_amd_intel = True
else:
is_cpu_amd_intel = False
import os.path
from numexpr.expressions import E
from numexpr.necompiler import NumExpr, disassemble, evaluate
from numexpr.tests import test, print_versions
