In [4]:
from pangloss import BackgroundCatalog, ForegroundCatalog, \
TrueHaloMassDistribution, Kappamap, Shearmap
ITERATIONS = 4
RADIUS = 2.0
# initialize background and foreground
B = BackgroundCatalog(N=10.0, domain=[1.5, 1.4, -1.5, -1.4], field=[0, 0, 0, 0])
F = ForegroundCatalog.guo()
F.set_mass_prior(TrueHaloMassDistribution())
# initialize maps from Hilbert et al 2009
K = Kappamap.example()
S = Shearmap.example()
# run monte carlo samples
def pangloss_benchmark():
for _ in xrange(ITERATIONS):
F.draw_halo_masses()
B.drill_lightcones(radius=RADIUS, foreground=F, smooth_corr=False)
B.lens_by_map(K, S)
B.lens_by_halos(lookup_table=False, smooth_corr=False, relevance_lim=0)
B.halo_mass_log_likelihood()
['$PANGLOSS_DIR/calib/Millennium/catalog_example.txt']
['$PANGLOSS_DIR/calib/Millennium/GGL_los*.fits']
45253159 function calls (44562463 primitive calls) in 164.629 seconds
Ordered by: standard name
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In [2]:
from massinference.angle import Angle
from massinference.catalog import SourceCatalogFactory, FastSampleHaloCatalogFactory, \
MutableHaloMassCatalog, SourceCatalog, HaloCatalog
from massinference.distribution import MassPrior
from massinference.inference import log_likelihood
from massinference.lenser import MapLenser
from massinference.lightcone import LightconeManager
from massinference.map import KappaMap, ShearMap
from massinference.plot import Limits
import cProfile
ITERATIONS = 4
RADIUS = 2.0
# run parameters
sigma_e = 0.2
random_seed = 1
source_density = 10.0
limits = Limits(Angle.from_degree(1.5), Angle.from_degree(1.4),
Angle.from_degree(-1.5), Angle.from_degree(-1.4))
limits_with_perimeter = limits.add_perimeter(Angle.from_arcmin(RADIUS))
# make a mock WL catalog, of observed, lensed, galaxy ellipticities:
source_factory = SourceCatalogFactory(limits, source_density, sigma_e)
source_catalog = source_factory.generate()
max_z = source_catalog.dataframe[SourceCatalog.Z].max()
e1, e2 = MapLenser(KappaMap.default(), ShearMap.default()).lens(source_catalog)
base_halo_catalog = MutableHaloMassCatalog.default(limits, max_z)
mass_prior = MassPrior(base_halo_catalog.dataframe[HaloCatalog.HALO_MASS].as_matrix())
halo_catalog_factory = FastSampleHaloCatalogFactory(base_halo_catalog,
mass_prior, random_seed)
lightcone_manager = LightconeManager(source_catalog, halo_catalog_factory, RADIUS)
def mass_inference_benchmark():
predictions = lightcone_manager.run(ITERATIONS)
log_likelihood(predictions, e1, e2, sigma_e)
cProfile.run('mass_inference_benchmark()')
52642 function calls (52626 primitive calls) in 0.568 seconds
Ordered by: standard name
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4 0.000 0.000 0.000 0.000 internals.py:3613(set)
4 0.000 0.000 0.000 0.000 internals.py:3637(value_getitem)
8 0.000 0.000 0.000 0.000 internals.py:4640(_get_blkno_placements)
1440 0.095 0.000 0.229 0.000 lensing.py:12(bmo_f)
1440 0.096 0.000 0.215 0.000 lensing.py:36(bmo_g)
2880 0.046 0.000 0.046 0.000 lensing.py:50(l_f)
4 0.000 0.000 0.000 0.000 lensing.py:54(delta_c)
2880 0.167 0.000 0.199 0.000 lensing.py:58(f_f)
1440 0.082 0.000 0.557 0.000 lightcone.py:36(compute_shear)
1 0.008 0.008 0.567 0.567 lightcone.py:78(run)
2880 0.004 0.000 0.015 0.000 numeric.py:148(ones)
4 0.000 0.000 0.000 0.000 numeric.py:414(asarray)
9 0.000 0.000 0.000 0.000 numeric.py:484(asanyarray)
20 0.000 0.000 0.000 0.000 range.py:455(__len__)
4 0.000 0.000 0.000 0.000 series.py:2789(_sanitize_index)
4 0.000 0.000 0.000 0.000 shape_base.py:61(atleast_2d)
4 0.000 0.000 0.000 0.000 {callable}
32 0.000 0.000 0.000 0.000 {getattr}
21 0.000 0.000 0.000 0.000 {hasattr}
8 0.000 0.000 0.000 0.000 {hash}
4462 0.003 0.000 0.003 0.000 {isinstance}
13 0.000 0.000 0.000 0.000 {issubclass}
4 0.000 0.000 0.000 0.000 {iter}
76/60 0.000 0.000 0.000 0.000 {len}
22 0.000 0.000 0.000 0.000 {max}
4320 0.003 0.000 0.022 0.000 {method 'any' of 'numpy.ndarray' objects}
4 0.000 0.000 0.000 0.000 {method 'append' of 'list' objects}
4 0.000 0.000 0.000 0.000 {method 'clear' of 'dict' objects}
8 0.000 0.000 0.000 0.000 {method 'copy' of 'numpy.ndarray' objects}
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
8 0.000 0.000 0.000 0.000 {method 'get_loc' of 'pandas.index.IndexEngine' objects}
4 0.000 0.000 0.000 0.000 {method 'permutation' of 'mtrand.RandomState' objects}
8653 0.031 0.000 0.031 0.000 {method 'reduce' of 'numpy.ufunc' objects}
2 0.000 0.000 0.000 0.000 {method 'std' of 'numpy.ndarray' objects}
16 0.000 0.000 0.000 0.000 {method 'view' of 'numpy.ndarray' objects}
13 0.000 0.000 0.000 0.000 {numpy.core.multiarray.array}
2880 0.007 0.000 0.007 0.000 {numpy.core.multiarray.copyto}
2880 0.004 0.000 0.004 0.000 {numpy.core.multiarray.empty}
2 0.000 0.000 0.000 0.000 {numpy.core.multiarray.zeros}
4 0.000 0.000 0.000 0.000 {pandas.algos.ensure_int64}
4 0.000 0.000 0.000 0.000 {pandas.lib.get_blkno_indexers}
8 0.000 0.000 0.000 0.000 {pandas.lib.values_from_object}
3 0.000 0.000 0.000 0.000 {range}
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Content source: davidthomas5412/PanglossNotebooks
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