def run_parallel(self,f,npoints,distribution,expected_value,expected_variance,**kwargs):
res,sd = mcimport(f,npoints,distribution,nprocs=2,**kwargs)
error = np.sqrt(expected_variance/float(npoints))
assert_within_tol(res,expected_value,3.*max(error,1e-10),
"Error in <f> in parallel run.")
assert_within_tol(sd,error,0.1*max(error,1e-10),
"Error in expected error in parallel run.")
def run_parallel(self, f, npoints, distribution, expected_value,
expected_variance, **kwargs):
res, sd = mcimport(f, npoints, distribution, nprocs=2, **kwargs)
error = np.sqrt(expected_variance / float(npoints))
assert_within_tol(res, expected_value, 3. * max(error, 1e-10),
"Error in <f> in parallel run.")
assert_within_tol(sd, error, 0.1 * max(error, 1e-10),
"Error in expected error in parallel run.")
def run_serial(self,f,npoints,expected_value,expected_variance,**kwargs):
res, sd = mcquad(f,npoints,nprocs=1,**kwargs)
volume = self.calc_volume(kwargs["xl"],kwargs["xu"])
error = volume*np.sqrt(expected_variance/float(npoints))
assert_within_tol(res,expected_value,3.*max(error,1e-10),
"Error in <f> in serial run.")
assert_within_tol(sd,error,0.1*max(error,1e-10),
"Error in expected error in serial run.")
def run_serial(self, f, npoints, expected_value, expected_variance,
**kwargs):
res, sd = mcquad(f, npoints, nprocs=1, **kwargs)
volume = self.calc_volume(kwargs["xl"], kwargs["xu"])
error = volume * np.sqrt(expected_variance / float(npoints))
assert_within_tol(res, expected_value, 3. * max(error, 1e-10),
"Error in <f> in serial run.")
assert_within_tol(sd, error, 0.1 * max(error, 1e-10),
"Error in expected error in serial run.")
def run_all(self,f,points,serial_only=False,**kwargs):
expected_res,expected_err = self.calc_res_err(f,points)
# serial run
res, err = integrate_from_points(f,points,nprocs=1,**kwargs)
assert_within_tol(res,expected_res,1e-10)
assert_within_tol(err,expected_err,1e-10)
# parallel run
if not serial_only:
res, err = integrate_from_points(f,points,
nprocs=2,batch_size=len(points)/10,**kwargs)
assert_within_tol(res,expected_res,1e-10)
assert_within_tol(err,expected_err,1e-10)
def test_args(self):
""" x**2 + a*y**2, passing a as an argument. """
npoints = 1000
points = numpy.random.ranf(size=2*npoints).reshape(npoints,2)
aval = 3.0
f = lambda xs,a: xs[0]**2 + a*xs[1]**2
expected_res, expected_err = self.calc_res_err(
lambda xs:xs[0]**2 + aval*xs[1]**2,points)
res_serial, err_serial = integrate_from_points(f,points,
args=(aval,),nprocs=1)
assert_within_tol(res_serial,expected_res,1e-10)
assert_within_tol(err_serial,expected_err,1e-10)
res_parallel, err_parallel = integrate_from_points(f,points,
args=(aval,),nprocs=2,batch_size=npoints/2)
assert_within_tol(res_parallel,expected_res,1e-10)
assert_within_tol(err_parallel,expected_err,1e-10)
def test_weight(self):
""" a*x**2, using a weight. """
npoints = 1000
points = numpy.random.ranf(size=npoints).reshape(npoints,1)
aval = 3.0
f = lambda x: x**2
expected_res, expected_err = self.calc_res_err(
lambda x:aval*x**2,points)
res_serial, err_serial = integrate_from_points(f,points,
nprocs=1,weight=aval)
assert_within_tol(res_serial,expected_res,1e-10)
assert_within_tol(err_serial,expected_err,1e-10)
res_parallel, err_parallel = integrate_from_points(f,points,
nprocs=2,batch_size=npoints/2,weight=aval)
assert_within_tol(res_parallel,expected_res,1e-10)
assert_within_tol(err_parallel,expected_err,1e-10)
