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))