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Top 10 Examples of "numexpr in functional component" in Python

Dive into secure and efficient coding practices with our curated list of the top 10 examples showcasing 'numexpr' in functional components in Python. Our advanced machine learning engine meticulously scans each line of code, cross-referencing millions of open source libraries to ensure your implementation is not just functional, but also robust and secure. Elevate your React applications to new heights by mastering the art of handling side effects, API calls, and asynchronous operations with confidence and precision.

def bench(N):
    print "*** array length:", N
    a = np.arange(N)
    t0 = time()
    ntimes = (1000*2**15) // N
    for i in xrange(ntimes):
        ne.evaluate('a>1000')
    print "numexpr--> %.3g" % ((time()-t0)/ntimes,)

    t0 = time()
    for i in xrange(ntimes):
        eval('a>1000')
    print "numpy--> %.3g" % ((time()-t0)/ntimes,)
import numpy as np
import numexpr as ne
import pandas as pd
from pandas import DataFrame, eval as pd_eval
import seamless.pandeval
from seamless.pandeval.core.computation.eval import eval
# Sample data
s = np.zeros(6, 'S5')
v = np.array([5,8,3,6,7,2])
s[:4] = "Test", "Test2", "Test", "Test"
s_u = np.array([ss.decode() for ss in s])  # s as unicode
dic = {"s": s, "v": v}
dic_u = {"s": s_u, "v": v}


print("Golden standard (numexpr with ugly syntax)\t", ne.compute("(s == 'Test') & (v > 3)", dic))

df = DataFrame(dic)
print("pandas DataFrame with bytes (error)\t\t", df.eval("s == 'Test' and v > 3").values)
try:  # ugly syntax AND does not work
    print(df.eval("s == b'Test' and v > 3").values)
except AttributeError:
    print("*" * 50)
    import traceback; traceback.print_exc(0)
    print("*" * 50)

df_u = DataFrame(dic_u)
print("pandas DataFrame with unicode (works)\t\t", df_u.eval("s == 'Test' and v > 3").values)


print("pandas eval with bytes (wrong)\t\t\t", pd_eval("s == 'Test' and v > 3", global_dict=dic))
print("pandas eval with unicode (wrong)\t\t", pd_eval("s == 'Test' and v > 3", global_dict=dic_u))
def compute():
    """Compute the polynomial."""
    if what == "numpy":
        y = eval(expr)
    else:
        y = ne.evaluate(expr)
    return len(y)


if __name__ == '__main__':
    if len(sys.argv) > 1:  # first arg is the package to use
        what = sys.argv[1]
    if len(sys.argv) > 2:  # second arg is the number of threads to use
        nthreads = int(sys.argv[2])
        if "ncores" in dir(ne):
            ne.set_num_threads(nthreads)
    if what not in ("numpy", "numexpr"):
        print "Unrecognized module:", what
        sys.exit(0)
    print "Computing: '%s' using %s with %d points" % (expr, what, N)
    t0 = time()
    result = compute()
    ts = round(time() - t0, 3)
    print "*** Time elapsed:", ts
"""

import os
import sys
sys.setrecursionlimit(8192)
import time
import re
import shutil
import zlib

import numpy as np
import bcolz
import numexpr as ne
bcolz.blosc_set_nthreads(2)
ne.set_num_threads(2)
import sqlalchemy as sql
import database

import compression
from gemini_utils import get_gt_cols

def get_samples(metadata):
    return [x['name'] for x in metadata.tables['samples'].select().order_by("sample_id").execute()]

def get_n_variants(cur):
    return next(iter(cur.execute(sql.text("select count(*) from variants"))))[0]

def get_bcolz_dir(db):
    if not "://" in db:
        return db + ".gts"
    else:
if expression:
        compare_times(expression, 1)
        sys.exit(0)
    nexpr = 0
    for expr in expressions:
        nexpr += 1
        compare_times(expr, nexpr)
    print

if __name__ == '__main__':
    import numexpr
    numexpr.print_versions()

    numpy.seterr(all='ignore')

    numexpr.set_vml_accuracy_mode('low')
    numexpr.set_vml_num_threads(2)

    if len(sys.argv) > 1:
        expression = sys.argv[1]
        print "expression-->", expression
        compare(expression)
    else:
        compare()

    tratios = numpy.array(numpy_ttime) / numpy.array(numexpr_ttime)
    stratios = numpy.array(numpy_sttime) / numpy.array(numexpr_sttime)
    ntratios = numpy.array(numpy_nttime) / numpy.array(numexpr_nttime)


    print "eval method: %s" % eval_method
    print "*************** Numexpr vs NumPy speed-ups *******************"
# we do not include PyQt because it is an indirect dependency. It might
        # be a good idea to include those too, but the list will get long in
        # that case.
        print("""
python {py}
larray {la}
numexpr {ne}
numpy {np}
pandas {pd}
pytables {pt}
pyyaml {yml}
bcolz {bc}
bottleneck {bn}
matplotlib {mpl}
vitables {vt}
""".format(py=py_version, la=la.__version__, ne=ne.__version__,
           np=np.__version__, pd=pd.__version__, pt=pt.__version__,
           yml=yaml.__version__,
           bc=bcolz_version, bn=bn_version, mpl=mpl_version, vt=vt_version,
           ))
        parser.exit()
pass

# Check for NumPy
check_import('numpy', min_numpy_version)

# Check for Numexpr
numexpr_here = False
try:
    import numexpr
except ImportError:
    print_warning("Numexpr not detected.  Disabling support for it.")
else:
    if numexpr.__version__ >= min_numexpr_version:
        numexpr_here = True
        print ( "* Found %(pkgname)s %(pkgver)s package installed."
                % {'pkgname': 'numexpr', 'pkgver': numexpr.__version__} )
    else:
        print_warning(
            "Numexpr %s detected, but version is not >= %s.  "
            "Disabling support for it." % (
            numexpr.__version__, min_numexpr_version))

########### End of version checks ##########

# carray version
VERSION = open('VERSION').read().strip()
# Create the version.py file
open('carray/version.py', 'w').write('__version__ = "%s"\n' % VERSION)


# Global variables
CFLAGS = os.environ.get('CFLAGS', '').split()
compare_times(expression, 1)
        sys.exit(0)
    nexpr = 0
    for expr in expressions:
        nexpr += 1
        compare_times(expr, nexpr)
    print

if __name__ == '__main__':
    import numexpr
    numexpr.print_versions()

    numpy.seterr(all='ignore')

    numexpr.set_vml_accuracy_mode('low')
    numexpr.set_vml_num_threads(2)

    if len(sys.argv) > 1:
        expression = sys.argv[1]
        print "expression-->", expression
        compare(expression)
    else:
        compare()

    tratios = numpy.array(numpy_ttime) / numpy.array(numexpr_ttime)
    stratios = numpy.array(numpy_sttime) / numpy.array(numexpr_sttime)
    ntratios = numpy.array(numpy_nttime) / numpy.array(numexpr_nttime)


    print "eval method: %s" % eval_method
    print "*************** Numexpr vs NumPy speed-ups *******************"
#     print "numpy total:", sum(numpy_ttime)/iterations
def _getNCPUs(self):
        return 1

    def __get_nbits(self):
        abits = platform.architecture()[0]
        nbits = re.compile('(\d+)bit').search(abits).group(1)
        return nbits

    def _is_32bit(self):
        return self.__get_nbits() == '32'

    def _is_64bit(self):
        return self.__get_nbits() == '64'


class LinuxCPUInfo(CPUInfoBase):
    info = None

    def __init__(self):
        if self.info is not None:
            return
        info = [{}]
        ok, output = getoutput(['uname', '-m'])
        if ok:
            info[0]['uname_m'] = output.strip()
        try:
            fo = open('/proc/cpuinfo')
        except EnvironmentError as e:
            warnings.warn(str(e), UserWarning)
        else:
            for line in fo:
                name_value = [s.strip() for s in line.split(':', 1)]
import warnings

try:
    from collections.abc import Mapping
except ImportError:
    from collections import Mapping

import numexpr as ne

__all__ = ['ScalarProperty']


class ScalarProperty(object):

    _evaluate = staticmethod(ne.evaluate)

    def __init__(self, expr, name=None, unit=None, symbol=None):
        '''
        Represents a scalar particle property.

        expr - The expression how to calcualte the value (string).
        name - the name the property can be accessed by.
        unit - unit of property.
        symbol - symbol used in formulas. Defaults to 'name' if omitted.
        '''
        self._expr = expr
        self._name = name
        self._unit = unit
        self._symbol = symbol
        self._func_cache = None  # Optimized numexpr function if available

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