def w_theta(data,rand,bins):
ra=data['ra']
dec=data['dec']
rar=rand['ra']
decr=rand['dec']
nbins = len(bins)-1
DD_counts = DDtheta_mocks(autocorr=1, nthreads=2, binfile=bins, RA1=ra, DEC1=dec)
DR_counts = DDtheta_mocks(autocorr=0, nthreads=2, binfile=bins, RA1=ra, DEC1=dec, RA2=rar, DEC2=decr)
#RR_counts = DDtheta_mocks(autocorr=1, nthreads=2, binfile=bins, RA1=rar, DEC1=decr)
N=len(data)
N_rand=len(rand)
cf = np.zeros(nbins)
cf[:] = np.nan
DR = DR_counts['npairs'] / (N*N_rand)
DD = DD_counts['npairs'] / (N*(N-1))
th = DD_counts['thetamax']
nonzero = DR > 0
cf[nonzero] = (DD[nonzero] / DR[nonzero] ) - 1.
return th,cf
def benchmark_mocks_threads_all(numpart_frac=[
0.001, 0.005, 0.01, 0.05, 0.1, 0.2, 0.25, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
],
nrepeats=3,
keys=None,
isa=None):
from Corrfunc.mocks import DDrppi_mocks, DDtheta_mocks
allkeys = [ #'DDrppi (DD)',
#'DDtheta (DD)',
'DDrppi (DR)',
'DDtheta (DR)'
]
allisa = ['avx512f', 'avx', 'sse42', 'fallback']
if keys is None:
keys = allkeys
else:
for k in keys:
if k not in allkeys:
msg = "Valid routines to benchmark are: {0}\nFound routine"\
" = {1}".format(allkeys, k)
raise ValueError(msg)
if isa is None:
isa = allisa
else:
for i in isa:
if i not in allisa:
msg = "Valid instructions sets benchmark are: {0}\n"\
"Found routine = {1}".format(allisa, i)
raise ValueError(msg)
print("Benchmarking mocks routines = {0} with isa = {1}".format(keys, isa))
mocks_file = pjoin(dirname(abspath(Corrfunc.__file__)),
"../mocks/tests/data", "Mr19_mock_northonly.rdcz.ff")
allra, alldec, allcz = read_catalog(mocks_file)
rand_file = pjoin(dirname(abspath(Corrfunc.__file__)),
"../mocks/tests/data", "Mr19_randoms_northonly.rdcz.ff")
allrand_ra, allrand_dec, allrand_cz = read_catalog(rand_file)
cosmology = 1
rmin = 0.1
rmax = 84.0
angmax = 10.0
nbins = 20
rbins = np.logspace(np.log10(rmin), np.log10(rmax), nbins)
# set to rmax for easier handling of
# scaling with number of particles
pimax = rmax
angbins = np.logspace(np.log10(rmin), np.log10(angmax), nbins)
nthreads = max_threads
dtype = np.dtype([('repeat', np.int), ('name', 'U16'), ('isa', 'U16'),
('rmax', np.float), ('ndata', np.int), ('nrand', np.int),
('nthreads', np.int), ('runtime', np.float),
('serial_time', np.float), ('pair_time', np.float),
('api_time', np.float)])
totN = len(numpart_frac) * len(keys) * len(isa) * nrepeats
runtimes = np.empty(totN, dtype=dtype)
runtimes['nthreads'][:] = nthreads
runtimes['rmax'][:] = rmax
index = 0
stderr_filename = 'stderr.txt'
for run_isa in isa:
for frac in numpart_frac:
npts = np.int(frac * len(allra))
npts_rand = np.int(frac * len(allrand_ra))
print("Working with (N, nrand) = {0} {1}".format(npts, npts_rand),
file=sys.stderr)
ra = np.random.choice(allra, npts, replace=False)
dec = np.random.choice(alldec, npts, replace=False)
cz = np.random.choice(allcz, npts, replace=False)
rand_ra = np.random.choice(allrand_ra, npts_rand, replace=False)
rand_dec = np.random.choice(allrand_dec, npts_rand, replace=False)
rand_cz = np.random.choice(allrand_cz, npts_rand, replace=False)
start_thread_index = index
if 'DDtheta (DD)' in keys:
for repeat in range(nrepeats):
runtimes['repeat'][index] = repeat
with stderr_redirected(to=stderr_filename):
autocorr = 1
t0 = time.time()
_, api_time = DDtheta_mocks(autocorr,
nthreads,
angbins,
ra,
dec,
verbose=True,
c_api_timer=True,
isa=run_isa)
t1 = time.time()
runtimes['name'][index] = 'DDtheta (DD)'
runtimes['isa'][index] = run_isa
runtimes['ndata'][index] = npts
runtimes['nrand'][index] = npts
runtimes['nthreads'][index] = nthreads
runtimes['runtime'][index] = t1 - t0
serial_time, pair_time = _get_times(stderr_filename)
runtimes['serial_time'][index] = serial_time
runtimes['pair_time'][index] = pair_time
runtimes['api_time'][index] = api_time
index += 1
if 'DDtheta (DR)' in keys:
for repeat in range(nrepeats):
runtimes['repeat'][index] = repeat
with stderr_redirected(to=stderr_filename):
autocorr = 0
t0 = time.time()
_, api_time = DDtheta_mocks(autocorr,
nthreads,
angbins,
ra,
dec,
RA2=rand_ra,
DEC2=rand_dec,
verbose=True,
c_api_timer=True,
isa=run_isa)
t1 = time.time()
runtimes['name'][index] = 'DDtheta (DR)'
runtimes['isa'][index] = run_isa
runtimes['ndata'][index] = npts
runtimes['nrand'][index] = npts_rand
runtimes['nthreads'][index] = nthreads
runtimes['runtime'][index] = t1 - t0
serial_time, pair_time = _get_times(stderr_filename)
runtimes['serial_time'][index] = serial_time
runtimes['pair_time'][index] = pair_time
runtimes['api_time'][index] = api_time
index += 1
if 'DDrppi (DD)' in keys:
for repeat in range(nrepeats):
runtimes['repeat'][index] = repeat
with stderr_redirected(to=stderr_filename):
autocorr = 1
t0 = time.time()
_, api_time = DDrppi_mocks(autocorr,
cosmology,
nthreads,
pimax,
rbins,
ra,
dec,
cz,
verbose=True,
c_api_timer=True,
isa=run_isa)
t1 = time.time()
runtimes['name'][index] = 'DDrppi (DD)'
runtimes['isa'][index] = run_isa
runtimes['ndata'][index] = npts
runtimes['nrand'][index] = npts
runtimes['nthreads'][index] = nthreads
runtimes['runtime'][index] = t1 - t0
serial_time, pair_time = _get_times(stderr_filename)
runtimes['serial_time'][index] = serial_time
runtimes['pair_time'][index] = pair_time
runtimes['api_time'][index] = api_time
index += 1
if 'DDrppi (DR)' in keys:
for repeat in range(nrepeats):
runtimes['repeat'][index] = repeat
with stderr_redirected(to=stderr_filename):
autocorr = 0
t0 = time.time()
_, api_time = DDrppi_mocks(autocorr,
cosmology,
nthreads,
pimax,
rbins,
ra,
dec,
cz,
RA2=rand_ra,
DEC2=rand_dec,
CZ2=rand_cz,
verbose=True,
c_api_timer=True,
isa=run_isa)
t1 = time.time()
runtimes['name'][index] = 'DDrppi (DR)'
runtimes['isa'][index] = run_isa
runtimes['ndata'][index] = npts
runtimes['nrand'][index] = npts_rand
runtimes['nthreads'][index] = nthreads
runtimes['runtime'][index] = t1 - t0
serial_time, pair_time = _get_times(stderr_filename)
runtimes['serial_time'][index] = serial_time
runtimes['pair_time'][index] = pair_time
runtimes['api_time'][index] = api_time
index += 1
print("{0}".format(runtimes[start_thread_index:index]))
sys.stdout.flush()
print("index = {0} totN = {1}".format(index, totN))
return keys, isa, runtimes
def benchmark_mocks_threads_all(rmax_array=[10.0, 20.0, 40.0, 80.0, 100.0],
thetamax_array=[2., 4., 8., 16., 20.],
nrepeats=1,
keys=None,
isa=None):
from Corrfunc.mocks import DDrppi_mocks, DDtheta_mocks
allkeys = [ #'DDrppi (DD)',
#'DDtheta (DD)',
'DDrppi (DR)',
'DDtheta (DR)'
]
allisa = ['avx512f', 'avx', 'sse42', 'fallback']
if keys is None:
keys = allkeys
else:
for k in keys:
if k not in allkeys:
msg = "Valid routines to benchmark are: {0}\nFound routine"\
" = {1}".format(allkeys, k)
raise ValueError(msg)
if isa is None:
isa = allisa
else:
for i in isa:
if i not in allisa:
msg = "Valid instructions sets benchmark are: {0}\n"\
"Found routine = {1}".format(allisa, i)
raise ValueError(msg)
rmax_array = np.array(rmax_array)
thetamax_array = np.array(thetamax_array)
print("Benchmarking mocks routines = {0} with isa = {1}".format(keys, isa))
mocks_file = pjoin(dirname(abspath(Corrfunc.__file__)),
"../mocks/tests/data", "Mr19_mock_northonly.rdcz.ff")
ra, dec, cz = read_catalog(mocks_file)
rand_file = pjoin(dirname(abspath(Corrfunc.__file__)),
"../mocks/tests/data", "Mr19_randoms_northonly.rdcz.ff")
rand_ra, rand_dec, rand_cz = read_catalog(rand_file)
cosmology = 1
rmin = 0.1
nbins = 20
nthreads = max_threads
dtype = np.dtype([('repeat', np.int), ('name', 'U16'), ('isa', 'U16'),
('rmax', np.float), ('nthreads', np.int),
('runtime', np.float), ('serial_time', np.float),
('pair_time', np.float), ('api_time', np.float)])
totN = len(rmax_array) * len(keys) * len(isa) * nrepeats
runtimes = np.empty(totN, dtype=dtype)
index = 0
stderr_filename = 'stderr.txt'
for run_isa in isa:
for thetamax, rmax in zip(thetamax_array, rmax_array):
rbins = np.logspace(np.log10(rmin), np.log10(rmax), nbins)
thetabins = np.logspace(np.log10(rmin), np.log10(thetamax), nbins)
pimax = rmax # Set to rmax for comparisons between wp and xi
print("Working on rmax = {0}".format(rmax), file=sys.stderr)
start_thread_index = index
if 'DDtheta (DD)' in keys:
for repeat in range(nrepeats):
runtimes['repeat'][index] = repeat
with stderr_redirected(to=stderr_filename):
autocorr = 1
t0 = time.time()
_, api_time = DDtheta_mocks(autocorr,
nthreads,
thetabins,
ra,
dec,
verbose=True,
c_api_timer=True,
isa=run_isa)
t1 = time.time()
runtimes['name'][index] = 'DDtheta (DD)'
runtimes['isa'][index] = run_isa
runtimes['rmax'][index] = thetamax
runtimes['nthreads'][index] = nthreads
runtimes['runtime'][index] = t1 - t0
serial_time, pair_time = _get_times(stderr_filename)
runtimes['serial_time'][index] = serial_time
runtimes['pair_time'][index] = pair_time
runtimes['api_time'][index] = api_time
index += 1
if 'DDtheta (DR)' in keys:
for repeat in range(nrepeats):
runtimes['repeat'][index] = repeat
with stderr_redirected(to=stderr_filename):
autocorr = 0
t0 = time.time()
_, api_time = DDtheta_mocks(autocorr,
nthreads,
thetabins,
ra,
dec,
RA2=rand_ra,
DEC2=rand_dec,
verbose=True,
c_api_timer=True,
isa=run_isa)
t1 = time.time()
runtimes['name'][index] = 'DDtheta (DR)'
runtimes['isa'][index] = run_isa
runtimes['rmax'][index] = thetamax
runtimes['nthreads'][index] = nthreads
runtimes['runtime'][index] = t1 - t0
serial_time, pair_time = _get_times(stderr_filename)
runtimes['serial_time'][index] = serial_time
runtimes['pair_time'][index] = pair_time
runtimes['api_time'][index] = api_time
index += 1
if 'DDrppi (DD)' in keys:
for repeat in range(nrepeats):
runtimes['repeat'][index] = repeat
with stderr_redirected(to=stderr_filename):
autocorr = 1
t0 = time.time()
_, api_time = DDrppi_mocks(autocorr,
cosmology,
nthreads,
pimax,
rbins,
ra,
dec,
cz,
verbose=True,
c_api_timer=True,
isa=run_isa)
t1 = time.time()
runtimes['name'][index] = 'DDrppi (DD)'
runtimes['isa'][index] = run_isa
runtimes['rmax'][index] = rmax
runtimes['nthreads'][index] = nthreads
runtimes['runtime'][index] = t1 - t0
serial_time, pair_time = _get_times(stderr_filename)
runtimes['serial_time'][index] = serial_time
runtimes['pair_time'][index] = pair_time
runtimes['api_time'][index] = api_time
index += 1
if 'DDrppi (DR)' in keys:
for repeat in range(nrepeats):
runtimes['repeat'][index] = repeat
with stderr_redirected(to=stderr_filename):
autocorr = 0
t0 = time.time()
_, api_time = DDrppi_mocks(autocorr,
cosmology,
nthreads,
pimax,
rbins,
ra,
dec,
cz,
RA2=rand_ra,
DEC2=rand_dec,
CZ2=rand_cz,
verbose=True,
c_api_timer=True,
isa=run_isa)
t1 = time.time()
runtimes['name'][index] = 'DDrppi (DR)'
runtimes['isa'][index] = run_isa
runtimes['rmax'][index] = rmax
runtimes['nthreads'][index] = nthreads
runtimes['runtime'][index] = t1 - t0
serial_time, pair_time = _get_times(stderr_filename)
runtimes['serial_time'][index] = serial_time
runtimes['pair_time'][index] = pair_time
runtimes['api_time'][index] = api_time
index += 1
print("{0}".format(runtimes[start_thread_index:index]))
sys.stdout.flush()
print("index = {0} totN = {1}".format(index, totN))
return keys, isa, runtimes