def work(i):
with pool.critical:
print 'doing chunk', i, Nchunks
Qchunk = correlate.points(qpos[qchunks[i]],
extra=Qfull.extra[qchunks[i]])
Rchunk = correlate.points(rpos[rchunks[i]],
extra=Rfull.extra[rchunks[i]])
Fchunk = correlate.field(fpos[fchunks[i]],
value=fdelta[fchunks[i]],
extra=objectid[fchunks[i]]
)
#Q-Q
DQDQ[i, ...] = correlate.paircount(Qchunk, Qfull, binning, np=0).fullsum1
RQDQ[i, ...] = correlate.paircount(Rchunk, Qfull, binning, np=0).fullsum1
RQRQ[i, ...] = correlate.paircount(Rchunk, Rfull, binning, np=0).fullsum1
#Q-F
DQDF = correlate.paircount(Qchunk, Ffull, binning, np=0)
DQDFsum1[:, i, ...] = DQDF.fullsum1
DQDFsum2[i, ...] = DQDF.fullsum2
RQDF = correlate.paircount(Rchunk, Ffull, binning, np=0)
RQDFsum1[:, i, ...] = RQDF.fullsum1
RQDFsum2[i, ...] = RQDF.fullsum2
#F-F
DFDF = correlate.paircount(Fchunk, Ffull, binning, np=0)
DFDFsum1[:, i, ...] = DFDF.fullsum1
DFDFsum2[i, ...] = DFDF.fullsum2
with pool.critical:
print 'done chunk', i, Nchunks, len(fchunks[i])
def main(A):
delta, pos, id = getforest(A,
Zmin=2.0, Zmax=2.2, RfLamMin=1040, RfLamMax=1185, combine=4)
print len(pos)
print pos, delta
data = correlate.field(pos, value=delta)
DD = correlate.paircount(data, data, correlate.RBinning(160000, 40))
r = DD.centers
xi = DD.sum1 / DD.sum2
print r.shape, xi.shape
numpy.savez(os.path.join(A.datadir, 'delta-corr1d-both.npz'), r=r, xi=xi)
figure = Figure(figsize=(4, 5), dpi=200)
ax = figure.add_subplot(311)
ax.plot(r / 1000, (r / 1000) ** 2 * xi[0], 'o ', label='$dF$ RSD')
ax.set_ylim(-0.4, 1.0)
ax.legend()
ax = figure.add_subplot(312)
ax.plot(r / 1000, (r / 1000) ** 2 * xi[1], 'o ', label='$dF$ Real')
ax.set_ylim(-0.4, 1.0)
ax.legend()
ax = figure.add_subplot(313)
ax.plot(r / 1000, (r / 1000) ** 2 * xi[2], 'o ', label=r'$dF$ Broadband')
ax.set_ylim(-20, 60)
ax.legend()
canvas = FigureCanvasAgg(figure)
figure.savefig(os.path.join(A.datadir, 'delta-corr-both.svg'))
def test_field():
numpy.random.seed(1234)
pos = numpy.random.uniform(size=(1000, 3))
dataset = correlate.field(pos, value=numpy.ones(len(pos)),
boxsize=1.0, weights=numpy.ones(len(pos)))
binning = correlate.RBinning(numpy.linspace(0, 0.5, 10))
r = correlate.paircount(dataset, dataset, binning, np=0)
assert_allclose(r.sum1, r.sum2)
def test_field():
numpy.random.seed(1234)
pos = numpy.random.uniform(size=(1000, 3))
dataset = correlate.field(pos, value=numpy.ones(len(pos)),
boxsize=1.0, weights=numpy.ones(len(pos)))
binning = correlate.RBinning(numpy.linspace(0, 0.5, 10))
r = correlate.paircount(dataset, dataset, binning, np=0)
assert_allclose(r.sum1, r.sum2)
def main(A):
delta, pos, id = getforest(A,
Zmin=2.0, Zmax=2.2, RfLamMin=1040, RfLamMax=1185, combine=4)
print len(pos)
print pos.min(), pos.max()
data = correlate.field(pos, value=delta)
DD = correlate.paircount(data, data,
correlate.RmuBinning(80000, Nbins=20, Nmubins=48, observer=0))
numpy.savez(os.path.join(A.datadir, 'pixcorr-Rmu.npz'),
center=DD.centers, sum1=DD.sum1, sum2=DD.sum2)
def dobootstrap(binning, dir):
A = Config(dir + '/paramfile', dir)
r, mu = binning.centers
qpos = getqso(A)
rpos = getrandom(A)
fdelta, fpos, objectid = getforest(A, Zmin=2.0, Zmax=3.0, RfLamMin=1040,
RfLamMax=1216, combine=4)
# fdelta, fpos = numpy.empty((2, 1, 3))
# objectid = numpy.empty(1, dtype='i8')
qchunks = chop(4, qpos)
rchunks = chop(4, rpos)
fchunks = chop(4, fpos)
Nchunks = len(qchunks)
Nvars = fdelta.shape[-1]
print 'Nchunks', Nchunks, 'Num of variables in fdelta', Nvars
chunkshape = [Nchunks, binning.shape[0], binning.shape[1]]
# last index is the chunk
DQDQ, RQDQ, RQRQ = sharedmem.empty([3] + chunkshape)
DQDFsum1, RQDFsum1, DFDFsum1 = sharedmem.empty([3, Nvars] + chunkshape)
DQDFsum2, RQDFsum2, DFDFsum2 = sharedmem.empty([3] + chunkshape)
with sharedmem.MapReduce() as pool:
Qfull = correlate.points(qpos, extra=numpy.arange(len(qpos)))
print 'Qfull:', Qfull.tree.min, Qfull.tree.max
Rfull = correlate.points(rpos, extra=numpy.arange(len(rpos)))
print 'Rfull:', Rfull.tree.min, Rfull.tree.max
Ffull = correlate.field(fpos, value=fdelta, extra=objectid)
print 'Ffull:', Ffull.tree.min, Ffull.tree.max
def work(i):
with pool.critical:
print 'doing chunk', i, Nchunks
Qchunk = correlate.points(qpos[qchunks[i]],
extra=Qfull.extra[qchunks[i]])
Rchunk = correlate.points(rpos[rchunks[i]],
extra=Rfull.extra[rchunks[i]])
Fchunk = correlate.field(fpos[fchunks[i]],
value=fdelta[fchunks[i]],
extra=objectid[fchunks[i]]
)
#Q-Q
DQDQ[i, ...] = correlate.paircount(Qchunk, Qfull, binning, np=0).fullsum1
RQDQ[i, ...] = correlate.paircount(Rchunk, Qfull, binning, np=0).fullsum1
RQRQ[i, ...] = correlate.paircount(Rchunk, Rfull, binning, np=0).fullsum1
#Q-F
DQDF = correlate.paircount(Qchunk, Ffull, binning, np=0)
DQDFsum1[:, i, ...] = DQDF.fullsum1
DQDFsum2[i, ...] = DQDF.fullsum2
RQDF = correlate.paircount(Rchunk, Ffull, binning, np=0)
RQDFsum1[:, i, ...] = RQDF.fullsum1
RQDFsum2[i, ...] = RQDF.fullsum2
#F-F
DFDF = correlate.paircount(Fchunk, Ffull, binning, np=0)
DFDFsum1[:, i, ...] = DFDF.fullsum1
DFDFsum2[i, ...] = DFDF.fullsum2
with pool.critical:
print 'done chunk', i, Nchunks, len(fchunks[i])
pool.map(work, range(Nchunks))
red = MakeBootstrapSample(r, mu, DQDQ, RQDQ, RQRQ,
DQDFsum1[0], DQDFsum2, RQDFsum1[0], RQDFsum2,
DFDFsum1[0], DFDFsum2, len(qpos), len(rpos))
real = MakeBootstrapSample(r, mu, DQDQ, RQDQ, RQRQ,
DQDFsum1[1], DQDFsum2, RQDFsum1[1], RQDFsum2,
DFDFsum1[1], DFDFsum2, len(qpos), len(rpos))
delta = MakeBootstrapSample(r, mu, DQDQ, RQDQ, RQRQ,
DQDFsum1[2], DQDFsum2, RQDFsum1[2], RQDFsum2,
DFDFsum1[2], DFDFsum2, len(qpos), len(rpos))
numpy.savez(os.path.join(A.datadir, 'bootstrap.npz'),
r=r,
mu=mu,
DQDQ=DQDQ,
RQDQ=RQDQ,
RQRQ=RQRQ,
DQDFsum1=DQDFsum1,
DQDFsum2=DQDFsum2,
RQDFsum1=RQDFsum1,
RQDFsum2=RQDFsum2,
DFDFsum1=DFDFsum1,
DFDFsum2=DFDFsum2,
Qchunksize=qchunks.end - qchunks.start,
Rchunksize=rchunks.end - rchunks.start,
Fchunksize=fchunks.end - fchunks.start,
red=red,
real=real,
delta=delta
)
