Example #1
2
"""
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
Example #3
0
"""
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