def main():
p = argparse.ArgumentParser(usage=__doc__.strip())
p.add_argument('test_mode', metavar='TEST_MODE')
p.add_argument('pytest_args', metavar='PYTEST_ARGS', nargs='*')
args = p.parse_args()
import scipy
print("Scipy: {} {}".format(scipy.__version__, scipy.__path__))
ret = scipy.test(args.test_mode, extra_argv=args.pytest_args)
if hasattr(ret, 'wasSuccessful'):
# Nosetests version
ret = ret.wasSuccessful()
sys.exit(not ret)
def main():
p = argparse.ArgumentParser(usage=__doc__.strip())
p.add_argument('test_mode', metavar='TEST_MODE')
p.add_argument('pytest_args', metavar='PYTEST_ARGS', nargs='*')
args = p.parse_args()
import scipy
print("Scipy: {} {}".format(scipy.__version__, scipy.__path__))
ret = scipy.test(args.test_mode, extra_argv=args.pytest_args)
if hasattr(ret, 'wasSuccessful'):
# Nosetests version
ret = ret.wasSuccessful()
sys.exit(not ret)
import sys
from scipy import test
from gpaw.mpi import rank
_stdout = sys.stdout
_stderr = sys.stderr
# scipy tests write to stderr
sys.stderr = open("scipy_test%02d.out" % rank, "w")
result = test(verbose=10)
sys.stdout = _stdout
sys.stderr = _stderr
if not result.wasSuccessful():
print >> sys.stderr, "scipy_test%02d.out" % rank, result.errors, result.failures
assert result.wasSuccessful()
def runScipyTest(self):
import scipy
scipy.test()
from __future__ import print_function
import sys
from distutils.version import LooseVersion
import numpy
import scipy
EXCLUDE_TESTS = []
if (LooseVersion(numpy.__version__) >= '1.9' and
LooseVersion(scipy.__version__) <= '1.4.0'):
EXCLUDE_TESTS += [
# https://github.com/scipy/scipy/issues/3853
'test_no_64',
'test_resiliency_all_32',
'test_resiliency_all_64',
'test_resiliency_limit_10',
'test_resiliency_random',
'test_ufunc_object_array',
'test_unary_ufunc_overrides',
'test_binary_ufunc_overrides',
]
extra_argv = ['--exclude=' + regex for regex in EXCLUDE_TESTS]
res = scipy.test(extra_argv = extra_argv)
sys.exit(not res.wasSuccessful())
import scipy.special._ufuncs
import scipy.special._ufuncs_cxx
import scipy.special.specfun
import scipy.stats.mvn
import scipy.stats.statlib
import scipy.stats
import scipy.special
import numpy
try:
print('MKL: %r' % numpy.__mkl_version__)
have_mkl = True
except AttributeError:
print('NO MKL')
have_mkl = False
# We have some test-case failures on 32-bit platforms:
#
# Ran 24221 tests in 389.466s
#
# FAILED (KNOWNFAIL=91, SKIP=1948, failures=4)
#
# .. maybe related to:
#
# TODO :: Investigate this properly.
if sys.maxsize > 2**32:
result = scipy.test(verbose=2)
sys.exit(0 if result else 1)
import scipy
print 'Initialize enviroment for scipy, please wait'
scipy.test('f**k')
origin_vec = []
f_origin = open('RG.csv','r')
for l_origin in f_origin:
origin_str = l_origin.split(',')
origin_vec.append(float(origin_str[2]))
#print 'f_origin length is:'
#print len(origin_vec)
#raw_input('Press any key to continue')
max_sim = 0;
max_sim_file = '';
F_NAME1 = ['100']
F_NAME2 = ['3']
for name1 in F_NAME1:
for name2 in F_NAME2:
f_name = 'exp50.res'
f_input = open(f_name,'r')
input_vec = []
for l_input in f_input:
input_str = l_input.split(',')
# print input_str
del(input_str[0]) #del the word-pair
# print float(input_str[0])
input_vec.append(float(input_str[0]))
# print 'input vec length is:',len(input_vec)
# raw_input('Press anykey to continue')
f_input.close()
print f_name
p = scipy.stats.pearsonr(origin_vec,input_vec)
import scipy.optimize.minpack2 import scipy.optimize.moduleTNC import scipy.signal._max_len_seq_inner import scipy.signal._spectral import scipy.signal.sigtools import scipy.signal.spline import scipy.sparse._csparsetools import scipy.sparse._sparsetools import scipy.sparse.csgraph._min_spanning_tree import scipy.sparse.csgraph._reordering import scipy.sparse.csgraph._shortest_path import scipy.sparse.csgraph._tools import scipy.sparse.csgraph._traversal import scipy.sparse.linalg.dsolve._superlu import scipy.sparse.linalg.eigen.arpack._arpack import scipy.sparse.linalg.isolve._iterative import scipy.spatial._distance_wrap import scipy.spatial.ckdtree import scipy.spatial.qhull import scipy.special._ellip_harm_2 import scipy.special._ufuncs import scipy.special._ufuncs_cxx import scipy.special.specfun import scipy.stats.mvn import scipy.stats.statlib import scipy.stats import scipy.special sys.exit(not scipy.test().wasSuccessful())
import scipy.special._ufuncs_cxx
import scipy.special.specfun
import scipy.stats.mvn
import scipy.stats.statlib
import scipy.stats
import scipy.special
import numpy
try:
print('MKL: %r' % numpy.__mkl_version__)
have_mkl = True
except AttributeError:
print('NO MKL')
have_mkl = False
# We have some test-case failures on 32-bit platforms:
#
# Ran 24221 tests in 389.466s
#
# FAILED (KNOWNFAIL=91, SKIP=1948, failures=4)
#
# .. maybe related to:
#
# TODO :: Investigate this properly.
if sys.maxsize > 2**32:
result = scipy.test(verbose=2, extra_argv=['-k not test_parallel'])
sys.exit(0 if result else 1)
# -*- coding: utf-8 -*-
import scipy as sc
output = sc.test('all', raise_warnings='release')
import pylab as gr
gr.ion()
# Importar los datos en archivos para matlab
import scipy.io as sio
def bellCurve(x, A=1.0, mu=0.0, sigma=1.0):
aa = ((x - mu)**2)
bb = 2 * (sigma**2)
cc = sc.exp(-aa / bb)
return A * cc
def trainGauss(samplingTimes, pulseTimes, bellSpread=0.5):
"""
train= trainGauss(samplingTimes, pulseTimes,bellSpread=1.0)
"""
#nPts= len(samplingTimes)
train = 0 #sc.zeros(nPts)
for n in range(len(pulseTimes)):
amp = 1 / (bellSpread * sc.sqrt(2 * sc.pi))
train = train + bellCurve(samplingTimes,
A=amp,
mu=pulseTimes[n] + 3 * bellSpread,
sigma=bellSpread)
return train
action="store_true",
dest="doctests",
default=False,
help="Run doctests in module")
parser.add_option(
"--coverage",
action="store_true",
dest="coverage",
default=False,
help="report coverage of Scipy code (requires 'coverage' module")
parser.add_option("-m",
"--mode",
action="store",
dest="mode",
default="fast",
help="'fast', 'full', or something that could be "
"passed to nosetests -A [default: %default]")
(options, args) = parser.parse_args()
import scipy
result = scipy.test(options.mode,
verbose=options.verbose,
extra_argv=args,
doctests=options.doctests,
coverage=options.coverage)
if result.wasSuccessful():
sys.exit(0)
else:
sys.exit(1)
import numpy as np import scipy import matplotlib.pyplot as plt import matplotlib import sklearn # print(np.test()) print(scipy.test()) # print(matplotlib.test())
from numpy.testing import assert_
__author__ = 'han'
import numpy as np
print (type(np.array([1.,2,3,4])))
print (np.zeros((3,4)))
print (np.ones((3,4)))
print (np.eye(3))
for x in np.linspace(1,3,3):
print (x)
a = np.ones((2,2))
b = np.eye(2)
print (a)
print (b)
print (a+b)
import scipy
scipy.test("fast")
def run_scipy_tests(*args, **kwargs):
import scipy
scipy.show_config()
scipy.test()
import numpy
try:
print('MKL: %r' % numpy.__mkl_version__)
have_mkl = True
except AttributeError:
print('NO MKL')
have_mkl = False
# Unset conda's $OPT environment variable, or numpy will think it's getting
# additional compiler flags. This would cause the test_compile* tests to fail,
# as the compiler would try to compile a non-existent file named '0' or '1'.
if 'OPT' in os.environ:
del os.environ['OPT']
# ---------- Comment from "defaults" recipe (CHL) ----------
# We have some test-case failures on 32-bit platforms:
#
# Ran 24221 tests in 389.466s
#
# FAILED (KNOWNFAIL=91, SKIP=1948, failures=4)
#
# .. maybe related to:
#
# TODO :: Investigate this properly.
# ----------------------------------------------------------
if sys.maxsize > 2**32:
result = scipy.test('full')
sys.exit(0 if result else 1)
import scipy
import sys
if sys.platform.startswith('linux'):
scipy.test('full')
# Find the package and build abspath to it
pkg = None
filelist = os.listdir(distdir)
for fn in filelist:
if fn.endswith('mpkg'):
pkg = fn
break
if pkg is None:
raise IOError('Package is not found in directory %s' % distdir)
pkgpath = os.path.abspath(os.path.join(SRC_DIR, DIST_DIR, pkg))
color_print('Installing package: %s' % pkgpath)
# Run the installer
print("")
color_print('Installer requires admin rights, you will be prompted for sudo')
print("")
cmd = 'sudo installer -verbose -package %s -target /' % pkgpath
#color_print(cmd)
shellcmd(cmd)
# Null out the PYTHONPATH so we're sure to test the Installed version of scipy
os.environ['PYTHONPATH'] = '0'
print("")
color_print('Install successful!')
color_print('Running scipy test suite!')
print("")
import scipy
scipy.test()
extra_argv = []
kwargs = dict(extra_argv=extra_argv)
if os.getenv("CI") != "travis":
extra_argv.append('-n%s' % os.environ['CPU_COUNT'])
elif is_pypy:
extra_argv.append('-n4')
if sys.platform.startswith("linux"):
extra_argv.append('-k')
extra_argv.append('not test_curvefit_covariance')
if os.getenv("CI") == "drone":
extra_argv.append('-k')
extra_argv.append('not (test_krandinit or test_heequb)')
# Run only linalg tests on drone as drone timeouts
kwargs['tests'] = ["scipy.linalg", "scipy.fft"]
if os.getenv("CI") == "travis" and is_pypy:
# Run only linalg, fft tests on travis with pypy as it timeouts
kwargs['tests'] = ["scipy.linalg", "scipy.fft"]
if os.getenv("CI") != "travis":
kwargs['verbose'] = 2
sys.exit(not scipy.test(**kwargs))
# --- run_test.py (end) ---
print('===== scipy-1.6.2-py38h7b17777_0 OK =====')
import scipy.optimize.minpack2 import scipy.optimize.moduleTNC import scipy.signal._max_len_seq_inner import scipy.signal._spectral import scipy.signal.sigtools import scipy.signal.spline import scipy.sparse._csparsetools import scipy.sparse._sparsetools import scipy.sparse.csgraph._min_spanning_tree import scipy.sparse.csgraph._reordering import scipy.sparse.csgraph._shortest_path import scipy.sparse.csgraph._tools import scipy.sparse.csgraph._traversal import scipy.sparse.linalg.dsolve._superlu import scipy.sparse.linalg.eigen.arpack._arpack import scipy.sparse.linalg.isolve._iterative import scipy.spatial._distance_wrap import scipy.spatial.ckdtree import scipy.spatial.qhull import scipy.special._ellip_harm_2 import scipy.special._ufuncs import scipy.special._ufuncs_cxx import scipy.special.specfun import scipy.stats.mvn import scipy.stats.statlib import scipy.stats import scipy.special sys.exit(not scipy.test(verbose=2))
import scipy.stats.mvn
import scipy.stats.statlib
import scipy.stats
import scipy.special
import numpy
try:
print('MKL: %r' % numpy.__mkl_version__)
have_mkl = True
except AttributeError:
print('NO MKL')
have_mkl = False
# We have some test-case failures on 32-bit platforms:
#
# Ran 24221 tests in 389.466s
#
# FAILED (KNOWNFAIL=91, SKIP=1948, failures=4)
#
# .. maybe related to:
#
# TODO :: Investigate this properly.
if sys.maxsize > 2**32:
result = scipy.test()
sys.exit(0 if result else 1)
# --- run_test.py (end) ---
print('===== scipy-1.0.0-py36h1260518_0 OK =====')
import scipy.optimize.moduleTNC import scipy.signal._max_len_seq_inner import scipy.signal._spectral import scipy.signal.sigtools import scipy.signal.spline import scipy.sparse._csparsetools import scipy.sparse._sparsetools import scipy.sparse.csgraph._min_spanning_tree import scipy.sparse.csgraph._reordering import scipy.sparse.csgraph._shortest_path import scipy.sparse.csgraph._tools import scipy.sparse.csgraph._traversal import scipy.sparse.linalg.dsolve._superlu import scipy.sparse.linalg.eigen.arpack._arpack import scipy.sparse.linalg.isolve._iterative import scipy.spatial._distance_wrap import scipy.spatial.ckdtree import scipy.spatial.qhull import scipy.special._ellip_harm_2 import scipy.special._ufuncs import scipy.special._ufuncs_cxx import scipy.special.specfun import scipy.stats.mvn import scipy.stats.statlib import scipy.stats import scipy.special sys.exit(scipy.test())
import scipy.signal._max_len_seq_inner import scipy.signal._spectral import scipy.signal.sigtools import scipy.signal.spline import scipy.sparse._csparsetools import scipy.sparse._sparsetools import scipy.sparse.csgraph._min_spanning_tree import scipy.sparse.csgraph._reordering import scipy.sparse.csgraph._shortest_path import scipy.sparse.csgraph._tools import scipy.sparse.csgraph._traversal import scipy.sparse.linalg.dsolve._superlu import scipy.sparse.linalg.eigen.arpack._arpack import scipy.sparse.linalg.isolve._iterative import scipy.spatial._distance_wrap import scipy.spatial.ckdtree import scipy.spatial.qhull import scipy.special._ellip_harm_2 import scipy.special._ufuncs import scipy.special._ufuncs_cxx import scipy.special.specfun import scipy.stats._rank import scipy.stats.mvn import scipy.stats.statlib import scipy.stats import scipy.special sys.exit(not scipy.test().wasSuccessful())
sys.path.pop(0)
from optparse import OptionParser
parser = OptionParser("usage: %prog [options] -- [nosetests options]")
parser.add_option("-v", "--verbose",
action="count", dest="verbose", default=1,
help="increase verbosity")
parser.add_option("--doctests",
action="store_true", dest="doctests", default=False,
help="Run doctests in module")
parser.add_option("--coverage",
action="store_true", dest="coverage", default=False,
help="report coverage of Scipy code (requires 'coverage' module")
parser.add_option("-m", "--mode",
action="store", dest="mode", default="fast",
help="'fast', 'full', or something that could be "
"passed to nosetests -A [default: %default]")
(options, args) = parser.parse_args()
import scipy
result = scipy.test(options.mode,
verbose=options.verbose,
extra_argv=args,
doctests=options.doctests,
coverage=options.coverage)
if result.wasSuccessful():
sys.exit(0)
else:
sys.exit(1)
from __future__ import print_function
import sys
from scipy import test
from gpaw.mpi import rank
_stdout = sys.stdout
_stderr = sys.stderr
# scipy tests write to stderr
sys.stderr = open("scipy_test%02d.out" % rank, "w")
result = test(verbose=10)
sys.stdout = _stdout
sys.stderr = _stderr
if not result.wasSuccessful():
print("scipy_test%02d.out" % rank,
result.errors,
result.failures,
file=sys.stderr)
assert result.wasSuccessful()
print(str("Running some Numpy tests: "))
numpy.test()
print("\n")
print("\t Would you like to run the SCIPY basic test suite...")
ans = input("For yes, enter y and hit return: ")
if ans == 'y':
print(str("Running some Scipy tests: "))
scipy.test()
print("\n")
print("\t Would you like to run the MATPLOTLIB basic test suite...")
ans = input("For yes, enter y and hit return: ")
if ans == 'y':
print(str("Running some Matplotlib tests: "))
matplotlib.test()
print("\n")
import scipy.optimize.moduleTNC import scipy.signal._max_len_seq_inner import scipy.signal._spectral import scipy.signal.sigtools import scipy.signal.spline import scipy.sparse._csparsetools import scipy.sparse._sparsetools import scipy.sparse.csgraph._min_spanning_tree import scipy.sparse.csgraph._reordering import scipy.sparse.csgraph._shortest_path import scipy.sparse.csgraph._tools import scipy.sparse.csgraph._traversal import scipy.sparse.linalg.dsolve._superlu import scipy.sparse.linalg.eigen.arpack._arpack import scipy.sparse.linalg.isolve._iterative import scipy.spatial._distance_wrap import scipy.spatial.ckdtree import scipy.spatial.qhull import scipy.special._ellip_harm_2 import scipy.special._ufuncs import scipy.special._ufuncs_cxx import scipy.special.specfun import scipy.stats.mvn import scipy.stats.statlib import scipy.stats import scipy.special sys.exit(not scipy.test(verbose=2))
