Merge branch 'master' of bitbucket.org:glavaux/cosmotool

This commit is contained in:
Guilhem Lavaux 2014-06-14 17:26:26 +02:00
commit e698201f38
5 changed files with 149 additions and 164 deletions

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@ -1,11 +1,12 @@
from cpython cimport bool
from cython cimport view
from cython.parallel import prange, parallel
from openmp cimport omp_get_max_threads, omp_get_thread_num
from libc.math cimport sin, cos, abs, floor, sqrt
import numpy as np
cimport numpy as npx
cimport cython
from copy cimport *
from openmp cimport omp_get_max_threads, omp_get_thread_num
ctypedef npx.float64_t DTYPE_t
DTYPE=np.float64
@ -297,8 +298,7 @@ cdef void INTERNAL_project_cic_no_mass(npx.ndarray[DTYPE_t, ndim=3] g,
cdef double half_Box = 0.5*Lbox
cdef double delta_Box = Ngrid/Lbox
cdef int i
cdef double a[3]
cdef double c[3]
cdef double a[3], c[3]
cdef int b[3]
cdef int do_not_put
@ -334,10 +334,8 @@ cdef void INTERNAL_project_cic_no_mass_periodic(npx.ndarray[DTYPE_t, ndim=3] g,
cdef double half_Box = 0.5*Lbox
cdef double delta_Box = Ngrid/Lbox
cdef int i
cdef double a[3]
cdef double c[3]
cdef int b[3]
cdef int b1[3]
cdef double a[3], c[3]
cdef int b[3], b1[3]
cdef int do_not_put
for i in range(x.shape[0]):
@ -375,8 +373,7 @@ cdef void INTERNAL_project_cic_with_mass(npx.ndarray[DTYPE_t, ndim=3] g,
cdef double half_Box = 0.5*Lbox
cdef double delta_Box = Ngrid/Lbox
cdef int i
cdef double a[3]
cdef double c[3]
cdef double a[3], c[3]
cdef DTYPE_t m0
cdef int b[3]
@ -413,10 +410,8 @@ cdef void INTERNAL_project_cic_with_mass_periodic(npx.ndarray[DTYPE_t, ndim=3] g
cdef double half_Box = 0.5*Lbox, m0
cdef double delta_Box = Ngrid/Lbox
cdef int i
cdef double a[3]
cdef double c[3]
cdef int b[3]
cdef int b1[3]
cdef double a[3], c[3]
cdef int b[3], b1[3]
for i in range(x.shape[0]):
@ -537,23 +532,10 @@ cdef DTYPE_t cube_integral(DTYPE_t u[3], DTYPE_t u0[3], int r[1]) nogil:
@cython.boundscheck(False)
@cython.cdivision(True)
cdef DTYPE_t mysum(DTYPE_t *v, int q) nogil:
cdef int i
cdef DTYPE_t s
s = 0
for i in xrange(q):
s += v[i]
return s
@cython.boundscheck(False)
@cython.cdivision(True)
cdef DTYPE_t cube_integral_trilin(DTYPE_t u[3], DTYPE_t u0[3], int r[1], DTYPE_t vertex_value[8], int err[1]) nogil:
cdef DTYPE_t cube_integral_trilin(DTYPE_t u[3], DTYPE_t u0[3], int r[1], DTYPE_t vertex_value[8]) nogil:
cdef DTYPE_t alpha_max
cdef DTYPE_t I, tmp_a
cdef DTYPE_t v[3]
cdef DTYPE_t term[4]
cdef DTYPE_t v[3], term[4]
cdef int i, j, q
alpha_max = 10.0 # A big number
@ -571,11 +553,7 @@ cdef DTYPE_t cube_integral_trilin(DTYPE_t u[3], DTYPE_t u0[3], int r[1], DTYPE_t
if tmp_a < alpha_max:
alpha_max = tmp_a
j = i
if (u0[i] >= 0 || u0[i] <= 1)
err[0] = 1
return 0
I = compute_projection(vertex_value, u, u0, alpha_max)
for i in xrange(3):
@ -589,7 +567,7 @@ cdef DTYPE_t cube_integral_trilin(DTYPE_t u[3], DTYPE_t u0[3], int r[1], DTYPE_t
@cython.boundscheck(False)
cdef DTYPE_t integrator0(DTYPE_t[:,:,:] density,
DTYPE_t u[3], DTYPE_t u0[3], int u_delta[3], int iu0[3], int jumper[1], int err[1]) nogil:
DTYPE_t u[3], DTYPE_t u0[3], int u_delta[3], int iu0[3], int jumper[1]) nogil:
cdef DTYPE_t d
d = density[iu0[0], iu0[1], iu0[2]]
@ -598,24 +576,15 @@ cdef DTYPE_t integrator0(DTYPE_t[:,:,:] density,
@cython.boundscheck(False)
cdef DTYPE_t integrator1(DTYPE_t[:,:,:] density,
DTYPE_t u[3], DTYPE_t u0[3], int u_delta[3], int iu0[3], int jumper[1], int err[1]) nogil:
DTYPE_t u[3], DTYPE_t u0[3], int u_delta[3], int iu0[3], int jumper[1]) nogil:
cdef DTYPE_t vertex_value[8]
cdef DTYPE_t d
cdef int a[3][2]
cdef int i
cdef int a[3][2], i
for i in xrange(3):
# if u[i] < 0:
# a[i][0] = iu0[i]-1
# a[i][1] = iu0[i]
# else:
a[i][0] = iu0[i]
a[i][1] = iu0[i]+1
with gil:
assert a[i][0] >= 0
assert a[i][1] < density.shape[i]
vertex_value[0 + 2*0 + 4*0] = density[a[0][0], a[1][0], a[2][0]]
vertex_value[1 + 2*0 + 4*0] = density[a[0][1], a[1][0], a[2][0]]
vertex_value[0 + 2*1 + 4*0] = density[a[0][0], a[1][1], a[2][0]]
@ -626,8 +595,7 @@ cdef DTYPE_t integrator1(DTYPE_t[:,:,:] density,
vertex_value[0 + 2*1 + 4*1] = density[a[0][0], a[1][1], a[2][1]]
vertex_value[1 + 2*1 + 4*1] = density[a[0][1], a[1][1], a[2][1]]
# return cube_integral(u, u0, jumper)*d
return cube_integral_trilin(u, u0, jumper, vertex_value, err)
return cube_integral_trilin(u, u0, jumper, vertex_value)
@ -635,15 +603,11 @@ cdef DTYPE_t integrator1(DTYPE_t[:,:,:] density,
cdef DTYPE_t C_line_of_sight_projection(DTYPE_t[:,:,:] density,
DTYPE_t a_u[3],
DTYPE_t min_distance,
DTYPE_t max_distance, DTYPE_t[:] shifter, int integrator_id, int out_err[1]) nogil:
DTYPE_t max_distance, DTYPE_t[:] shifter, int integrator_id) nogil except? 0:
cdef DTYPE_t u[3]
cdef DTYPE_t ifu0[3]
cdef DTYPE_t u0[3]
cdef DTYPE_t utot[3]
cdef DTYPE_t u[3], ifu0[3], u0[3], utot[3]
cdef int u_delta[3]
cdef int iu0[3]
cdef int err[1]
cdef int i
cdef int N = density.shape[0]
cdef int half_N = density.shape[0]/2
@ -652,10 +616,8 @@ cdef DTYPE_t C_line_of_sight_projection(DTYPE_t[:,:,:] density,
cdef int jumper[1]
cdef DTYPE_t (*integrator)(DTYPE_t[:,:,:],
DTYPE_t u[3], DTYPE_t u0[3], int u_delta[3], int iu0[3], int jumper[1], int err[1]) nogil
DTYPE_t u[3], DTYPE_t u0[3], int u_delta[3], int iu0[3], int jumper[1]) nogil
out_err[0] = 0
if integrator_id == 0:
integrator = integrator0
else:
@ -673,12 +635,12 @@ cdef DTYPE_t C_line_of_sight_projection(DTYPE_t[:,:,:] density,
u0[i] = ifu0[i]-iu0[i]
u_delta[i] = 1 if iu0[i] > 0 else -1
if (not ((iu0[i]>= 0) and (iu0[i] < N))):
out_err[0] = 1
return 0
with gil:
raise RuntimeError("iu0[%d] = %d !!" % (i,iu0[i]))
if (not (u0[i]>=0 and u0[i]<=1)):
out_err[0] = 1
return 0
with gil:
raise RuntimeError("u0[%d] = %g !" % (i,u0[i]))
completed = 0
if ((iu0[0] >= N) or (iu0[0] <= 0) or
@ -689,12 +651,8 @@ cdef DTYPE_t C_line_of_sight_projection(DTYPE_t[:,:,:] density,
I0 = 0
jumper[0] = 0
while completed == 0:
err[0] = 0
I0 += integrator(density, u, u0, u_delta, iu0, jumper, err)
if err[0] == 1:
out_err[0] = 1
return 0
I0 += integrator(density, u, u0, u_delta, iu0, jumper)
if u[jumper[0]] < 0:
iu0[jumper[0]] -= 1
@ -711,7 +669,7 @@ cdef DTYPE_t C_line_of_sight_projection(DTYPE_t[:,:,:] density,
else:
dist2 = 0
for i in range(3):
delta = iu0[i]+u0[i]-half_N
delta = iu0[i]+u0[i]-half_N-shifter[i]
dist2 += delta*delta
if (dist2 > max_distance2):
@ -727,24 +685,19 @@ def line_of_sight_projection(DTYPE_t[:,:,:] density not None,
DTYPE_t min_distance,
DTYPE_t max_distance, DTYPE_t[:] shifter not None, int integrator_id=0):
cdef DTYPE_t u[3]
cdef int out_err[1]
cdef DTYPE_t v
u[0] = a_u[0]
u[1] = a_u[1]
u[2] = a_u[2]
v = C_line_of_sight_projection(density,
C_line_of_sight_projection(density,
u,
min_distance,
max_distance, shifter, integrator_id, out_err)
if out_err[0] == 1:
raise RuntimeError("Error occured during integration")
return v
max_distance, shifter, integrator_id)
cdef double _spherical_projloop(double theta, double phi, DTYPE_t[:,:,:] density,
double min_distance, double max_distance,
DTYPE_t[:] shifter, int integrator_id, int out_err[1]) nogil:
DTYPE_t[:] shifter, int integrator_id) nogil:
cdef DTYPE_t u0[3]
stheta = sin(theta)
@ -752,19 +705,7 @@ cdef double _spherical_projloop(double theta, double phi, DTYPE_t[:,:,:] density
u0[1] = sin(phi)*stheta
u0[2] = cos(theta)
return C_line_of_sight_projection(density, u0, min_distance, max_distance, shifter, integrator_id, out_err)
@cython.boundscheck(False)
cdef npx.uint64_t _mysum(int[:] jobs) nogil:
cdef npx.uint64_t s
cdef npx.uint64_t N
cdef int i
s = 0
N = jobs.shape[0]
for i in xrange(N):
s += jobs[i]
return s
return C_line_of_sight_projection(density, u0, min_distance, max_distance, shifter, integrator_id)
@cython.boundscheck(False)
@ -781,9 +722,9 @@ def spherical_projection(int Nside,
cdef DTYPE_t[:] outm
cdef int[:] job_done
cdef npx.ndarray[DTYPE_t, ndim=1] outm_array
cdef long N
cdef long N, N0
cdef double stheta
cdef int out_err[1]
cdef int tid
if shifter is None:
shifter = view.array(shape=(3,), format=FORMAT_DTYPE, itemsize=sizeof(DTYPE_t))
@ -797,20 +738,22 @@ def spherical_projection(int Nside,
p = pb.ProgressBar(maxval=outm.size,widgets=[pb.Bar(), pb.ETA()]).start()
N = omp_get_max_threads()
N0 = outm.size
if booster < 0:
booster = 1000
job_done = view.array(shape=(N,), format="i", itemsize=sizeof(int))
job_done[:] = 0
theta,phi = hp.pix2ang(Nside, np.arange(outm.size))
if booster <= 0:
booster = density.size / 100 / N
theta,phi = hp.pix2ang(Nside, np.arange(N0))
with nogil, parallel():
for i in prange(N):
if omp_get_thread_num() == 0 and progress != 0 and (i%booster) == 0:
tid = omp_get_thread_num()
for i in prange(N0):
if progress != 0 and (i%booster) == 0:
with gil:
p.update(_mysum(job_done))
outm[i] = _spherical_projloop(theta[i], phi[i], density_view, min_distance, max_distance, shifter, integrator_id, out_err)
job_done[omp_get_thread_num()] = i
outm[i] = _spherical_projloop(theta[i], phi[i], density_view, min_distance, max_distance, shifter, integrator_id)
job_done[tid] += 1
if progress:
p.finish()

22
python/copy.pxd Normal file
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@ -0,0 +1,22 @@
cimport cython
cimport numpy as npx
ctypedef fused sum_type:
cython.int
cython.float
npx.uint64_t
npx.uint32_t
@cython.boundscheck(False)
cdef inline sum_type _mysum(sum_type[:] jobs) nogil:
cdef sum_type s
cdef npx.uint64_t N
cdef int i
s = 0
N = jobs.shape[0]
for i in xrange(N):
s += jobs[i]
return s

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@ -7,6 +7,8 @@
#include <H5Cpp.h>
#include "hdf5_array.hpp"
#include <iostream>
#include <boost/format.hpp>
#include <boost/bind.hpp>
using namespace std;
using namespace CosmoTool;
@ -17,8 +19,13 @@ struct VCoord{
float v[3];
};
template<int i>
ComputePrecision getVelocity(const VCoord& v)
using boost::format;
using boost::str;
typedef boost::multi_array<float, 2> array_type;
typedef boost::multi_array<float, 3> array3_type;
typedef boost::multi_array<float, 4> array4_type;
ComputePrecision getVelocity(const VCoord& v, int i)
{
return v.v[i];
}
@ -32,11 +39,51 @@ typedef SPHSmooth<VCoord> MySmooth;
typedef MySmooth::SPHTree MyTree;
typedef MyTree::Cell MyCell;
template<typename FuncT>
void computeInterpolatedField(MyTree *tree1, double boxsize, int Nres, double cx, double cy, double cz,
array3_type& bins, array3_type& arr, FuncT func, double rLimit2)
{
#pragma omp parallel
{
MySmooth smooth1(tree1, N_SPH);
#pragma omp for schedule(dynamic)
for (int rz = 0; rz < Nres; rz++)
{
double pz = (rz)*boxsize/Nres-cz;
cout << format("[%d] %d / %d") % omp_get_thread_num() % rz % Nres << endl;
for (int ry = 0; ry < Nres; ry++)
{
double py = (ry)*boxsize/Nres-cy;
for (int rx = 0; rx < Nres; rx++)
{
double px = (rx)*boxsize/Nres-cx;
MyTree::coords c = { px, py, pz };
double r2 = c[0]*c[0]+c[1]*c[1]+c[2]*c[2];
if (r2 > rLimit2)
{
arr[rx][ry][rz] = 0;
continue;
}
uint32_t numInCell = bins[rx][ry][rz];
if (numInCell > N_SPH)
smooth1.fetchNeighbours(c, numInCell);
else
smooth1.fetchNeighbours(c);
arr[rx][ry][rz] = smooth1.computeSmoothedValue(c, func);
}
}
}
}
}
int main(int argc, char **argv)
{
typedef boost::multi_array<float, 2> array_type;
typedef boost::multi_array<float, 3> array3_type;
typedef boost::multi_array<float, 4> array4_type;
char *fname1, *fname2;
double rLimit, boxsize, rLimit2, cx, cy, cz;
@ -105,8 +152,6 @@ int main(int argc, char **argv)
cout << "Creating smoothing filter..." << endl;
array3_type out_den_1(boost::extents[Nres][Nres][Nres]);
array4_type out_v3d_1(boost::extents[Nres][Nres][Nres][3]);
// array3_type out_rad_1(boost::extents[Nres][Nres][Nres]);
cout << "Weighing..." << endl;
@ -149,55 +194,18 @@ int main(int argc, char **argv)
}
cout << "Interpolating..." << endl;
#pragma omp parallel
{
MySmooth smooth1(&tree1, N_SPH);
#pragma omp for schedule(dynamic)
for (int rz = 0; rz < Nres; rz++)
{
double pz = (rz)*boxsize/Nres-cz;
cout << rz << " / " << Nres << endl;
for (int ry = 0; ry < Nres; ry++)
{
double py = (ry)*boxsize/Nres-cy;
for (int rx = 0; rx < Nres; rx++)
{
double px = (rx)*boxsize/Nres-cx;
MyTree::coords c = { px, py, pz };
double r2 = c[0]*c[0]+c[1]*c[1]+c[2]*c[2];
if (r2 > rLimit2)
{
out_v3d_1[rx][ry][rz][0] = 0;
out_v3d_1[rx][ry][rz][1] = 0;
out_v3d_1[rx][ry][rz][2] = 0;
out_den_1[rx][ry][rz] = 0;
//out_rad_1[rx][ry][rz] = -1;
continue;
}
uint32_t numInCell = bins[rx][ry][rz];
if (numInCell > N_SPH)
smooth1.fetchNeighbours(c, numInCell);
else
smooth1.fetchNeighbours(c);
//out_rad_1[rx][ry][rz] = smooth1.getSmoothingLen();
out_v3d_1[rx][ry][rz][0] = smooth1.computeSmoothedValue(c, getVelocity<0>);
out_v3d_1[rx][ry][rz][1] = smooth1.computeSmoothedValue(c, getVelocity<1>);
out_v3d_1[rx][ry][rz][2] = smooth1.computeSmoothedValue(c, getVelocity<2>);
out_den_1[rx][ry][rz] = smooth1.computeSmoothedValue(c, getUnity);
}
}
}
array3_type interpolated(boost::extents[Nres][Nres][Nres]);
computeInterpolatedField(&tree1, boxsize, Nres, cx, cy, cz,
bins, interpolated, getUnity, rLimit2);
hdf5_write_array(out_f, "density", interpolated);
//out_f.flush();
for (int i = 0; i < 3; i++) {
computeInterpolatedField(&tree1, boxsize, Nres, cx, cy, cz,
bins, interpolated, boost::bind(getVelocity, _1, i), rLimit2);
hdf5_write_array(out_f, str(format("p%d") % i), interpolated);
}
//hdf5_write_array(out_f, "radii", out_rad_1);
hdf5_write_array(out_f, "velocity", out_v3d_1);
hdf5_write_array(out_f, "density", out_den_1);
return 0;
};

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@ -82,10 +82,14 @@ namespace CosmoTool
return internal.currentCenter;
}
template<typename FuncT>
ComputePrecision computeSmoothedValue(const typename SPHTree::coords& c,
computeParticleValue fun, SPHState *state = 0);
FuncT fun, SPHState *state = 0);
template<typename FuncT>
ComputePrecision computeInterpolatedValue(const typename SPHTree::coords& c,
computeParticleValue fun, SPHState *state = 0);
FuncT fun, SPHState *state = 0);
ComputePrecision getMaxDistance(const typename SPHTree::coords& c,
SPHNode *node) const;
@ -101,7 +105,8 @@ namespace CosmoTool
}
// END
void runForEachNeighbour(runParticleValue fun, SPHState *state = 0);
template<typename FuncT>
void runForEachNeighbour(FuncT fun, SPHState *state = 0);
void addGridSite(const typename SPHTree::coords& c);
bool hasNeighbours() const;
@ -127,12 +132,15 @@ namespace CosmoTool
uint32_t maxNgb;
SPHTree *tree;
template<typename FuncT>
ComputePrecision computeWValue(const typename SPHTree::coords & c,
SPHCell& cell,
CoordType d,
computeParticleValue fun, SPHState *state);
FuncT fun, SPHState *state);
template<typename FuncT>
void runUnrollNode(SPHNode *node,
runParticleValue fun);
FuncT fun);
};
template<class ValType1, class ValType2, int Ndims>

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@ -21,10 +21,11 @@ SPHSmooth<ValType,Ndims>::~SPHSmooth()
}
template<typename ValType, int Ndims>
template<typename FuncT>
ComputePrecision SPHSmooth<ValType,Ndims>::computeWValue(const typename SPHTree::coords& c,
SPHCell& cell,
CoordType d,
computeParticleValue fun, SPHState *state)
FuncT fun, SPHState *state)
{
CoordType weight;
@ -117,9 +118,10 @@ SPHSmooth<ValType,Ndims>::fetchNeighboursOnVolume(const typename SPHTree::coords
}
template<typename ValType, int Ndims>
template<typename FuncT>
ComputePrecision
SPHSmooth<ValType,Ndims>::computeSmoothedValue(const typename SPHTree::coords& c,
computeParticleValue fun, SPHState *state)
FuncT fun, SPHState *state)
{
if (state == 0)
state = &internal;
@ -144,8 +146,9 @@ ComputePrecision interpolateOne(const ValType& t)
// WARNING ! Cell's weight must be 1 !!!
template<typename ValType, int Ndims>
template<typename FuncT>
ComputePrecision SPHSmooth<ValType,Ndims>::computeInterpolatedValue(const typename SPHTree::coords& c,
computeParticleValue fun, SPHState *state)
FuncT fun, SPHState *state)
{
if (state == 0)
state = &internal;
@ -164,7 +167,8 @@ ComputePrecision SPHSmooth<ValType,Ndims>::computeInterpolatedValue(const typena
}
template<typename ValType, int Ndims>
void SPHSmooth<ValType,Ndims>::runForEachNeighbour(runParticleValue fun, SPHState *state)
template<typename FuncT>
void SPHSmooth<ValType,Ndims>::runForEachNeighbour(FuncT fun, SPHState *state)
{
if (state == 0)
state = &internal;