def test_voxels(self):
#return
# load a mesh, make a grid, and voxelize
print()
ngrid = 3 * (64, )
snap = 'data/snapshot_010'
mesh = psi.Mesh(filename=snap, loader='gadget2')
grid = psi.Grid(type='cart',
n=ngrid,
window=(mesh.boxmin, mesh.boxmax))
psi.voxels(grid=grid, mesh=mesh, mode='density')
#psi.voxels(grid=grid, mesh=mesh, mode='annihilation')
# check the total mass
# show a picture
elemmass = np.sum(mesh.mass)
voxmass = np.sum(grid.fields["m"])
err = np.abs(1.0 - voxmass / elemmass)
print(' - total mass =', voxmass)
print(" - mass error = ", err)
#plt.imshow(np.log10(grid.fields["m"][:,:,32]))
#plt.show()
self.assertAlmostEqual(err, 0.0, delta=errtol)
def test_powerspec(self):
# loads, voxelizes, and computes the potential field
print()
dim = 3
box = 128
win = 13.0
grid = psi.Grid(type='cart',
n=dim * (box, ),
window=(dim * (0., ), dim * (win, )))
# set phi min, max such that phi min/max = -+1
#rho0 = -(np.pi*nk**2)/(G*win**2)
grid.fields['m'][:, :, :] = np.sin(2 * np.pi * 13 * np.arange(box) /
box)
grid.fields['m'][:, :, :] += 0.7 * np.sin(
2 * np.pi * 31 * np.arange(box) / box)
grid.fields['m'][:, :, :] += 1.2 * np.sin(
2 * np.pi * 45 * np.arange(box) / box)
P, k = psi.powerSpectrum(grid)
#plt.plot(k, P)
#plt.show()
# test that the max error is small
ptot_x = np.sum(grid.fields['m']**2)
ptot_k = np.sum(P)
maxerr = np.abs((ptot_x - ptot_k) / ptot_x)
print(' - max relative err (checking Parseval) =', maxerr)
self.assertAlmostEqual(maxerr, 0.0, delta=errtol)
def test_annihilation(self):
return
print()
mesh = psi.Mesh(filename='data/snapshot_010', loader='gadget2')
#mesh = psi.Mesh(filename='', loader='hacky_test')
#mesh = psi.Mesh(filename='data/box128_010', loader='gadget2')
#print mesh.pos[mesh.connectivity][12475]
grid = psi.Grid(type='hpring', n=128)
psi.skymap(grid=grid, mesh=mesh, bstep=1, mode=1)
err = 1.0 - np.sum(grid.fields["m"])
print("mass = ", np.sum(grid.fields["m"]), 'err =', err)
print(" - min = ", np.min(grid.fields["m"]))
print(" - max = ", np.max(grid.fields["m"]))
grid.fields["m"].tofile('data/annihilation128_shell.np')
# show the pixel area plot
#hp.mollview(np.log10(grid.fields['m']), title='Mass map, err = %.5e'%err)
hp.mollview(np.log10(grid.fields['m'])
) #, title='Mass map, err = %.5e'%err)#, min = -4)
plt.show()
def test_vdf(self):
#return
# load a mesh, make a grid, and voxelize
print()
snap = 'data/snapshot_010'
mesh = psi.Mesh(filename=snap, loader='gadget2')
rst = psi.RStarTree(mesh)
for sample_pos in [(10., 10., 13.), (19., 23., 29.), (10., 12., 13.)]:
rho, vel = psi.VDF(mesh, sample_pos, tree=rst)
print('Sampled %d streams' % len(rho))
print('rho[0] =', rho[0])
print('vel[0] =', vel[0])
def test_mesh_init(self):
print()
mesh = psi.Mesh(filename='data/snapshot_010', loader='gadget2')
print(' - pos =', mesh.pos.dtype, mesh.pos.shape)
print(' - vel =', mesh.vel.dtype, mesh.vel.shape)
print(' - conn =', mesh.connectivity.dtype, mesh.connectivity.shape)
print(' - box =', mesh.boxmin, mesh.boxmax)
def test_grid_hpring(self):
print()
grid = psi.Grid(type='hpring')
print(' - type =', grid.type)
print(' - fields =', grid.fields['m'].dtype, grid.fields['m'].shape)
print(' - window =', grid.winmin, grid.winmax)
print(' - n =', grid.n)
print(' - d =', grid.d)
# get a pixel boundary
center, boundary, vol = grid.getCellGeometry(cell=None, bstep=2)
def test_grid_cart(self):
print()
grid = psi.Grid(type='cart',
n=(10, 10, 10)) # default is 64^3 unit box
print(' - type =', grid.type)
print(' - fields =', grid.fields['m'].dtype, grid.fields['m'].shape)
print(' - window =', grid.winmin, grid.winmax)
print(' - n =', grid.n)
print(' - d =', grid.d)
center, boundary, vol = grid.getCellGeometry(cell=[123])
def test_skymap(self):
return
print()
snap = 'data/snapshot_010'
nside = 64 # 16 # 32
mesh = psi.Mesh(filename=snap, loader='gadget2')
#mesh = psi.Mesh(filename='', loader='hacky_test')
grid = psi.Grid(type='hpring', n=nside)
psi.skymap(grid=grid, mesh=mesh, bstep=2, mode=0)
# show the mass map and error
elemmass = np.sum(mesh.mass)
voxmass = np.sum(grid.fields["m"])
err = np.abs(1.0 - voxmass / elemmass)
print(' - total mass =', voxmass)
print(" - mass error = ", err)
hp.mollview(np.log10(grid.fields['m']), title='Mass map')
plt.show()
self.assertAlmostEqual(err, 0.0, delta=errtol)
def test_rtree(self):
#return
# load a mesh, make a grid, and voxelize
print()
snap = 'data/snapshot_010'
mesh = psi.Mesh(filename=snap, loader='gadget2')
rst = psi.RStarTree(mesh, initial_capacity=12)
qinds = rst.query(box=((
10.,
10.,
10.,
), (11., 11.2, 11.3)))
print('Queried indices from the tree!')
print('Indices =', qinds.shape)
print('Connectivity =', mesh.connectivity[qinds].shape)
print('Elems =', mesh.pos[mesh.connectivity[qinds]].shape)
print(' = Indices =', qinds[0])
print(' = Connectivity =', mesh.connectivity[qinds][0])
print(' = Elems =', mesh.pos[mesh.connectivity[qinds]][0])
def test_phi_simple(self):
# loads, voxelizes, and computes the potential field
print()
dim = 3
box = 128
win = 21.0
G = 21.12131
nk = 2
grid = psi.Grid(type='cart',
n=dim * (box, ),
window=(dim * (0., ), dim * (win, )))
# set phi min, max such that phi min/max = -+1
rho0 = -(np.pi * nk**2) / (G * win**2)
grid.fields['m'][:, :, :] = rho0 * np.sin(
2 * np.pi * nk * np.arange(box) / box)
phi = psi.phi(grid, Gn=G)
analytic = np.sin(2 * np.pi * nk * np.arange(box) / box)
maxerr = np.max(np.abs(phi - analytic))
print(' - max absolute err in phi =', maxerr)
# test that the max error is small
self.assertAlmostEqual(maxerr, 0.0, delta=errtol)
'''
Example 5: VDF sampling
Demonstrates how to use PSI.VDF() and PSI.crossStreams()
'''
import PSI as psi
import helpers as hlp
import numpy as np
# load the mesh
snap = '../data/snapshot_010'
mesh = psi.Mesh(filename=snap, loader='gadget2')
# make an RStarTree out of the mesh
rst = psi.RStarTree(mesh)
# define the velocity-dependent rate coefficient
def xsn(v):
return 1.0
# loop over all sample locations
for sample_pos in hlp.sampleSphere(r=0.2, center=[10.,10.,13.], nsamp=5):
print('Next sample...')
# sample the multi-streaming region
rho, vel = psi.VDF(mesh, tuple(sample_pos), tree=rst)
'''
Example 2: Voxelization of a cosmological density field
'''
import PSI as psi
import helpers as hlp
import numpy as np
# load the mesh from a Gadget snapshot
snap = '../data/snapshot_010'
mesh = psi.Mesh(filename=snap, loader='gadget2')
# create the Grid, specifying the resolution and projection window
ngrid = 3 * (128, )
win = (mesh.boxmin, mesh.boxmax)
grid = psi.Grid(type='cart', n=ngrid, window=win)
# call PSI.voxels()
psi.voxels(grid=grid, mesh=mesh, mode='density')
#psi.voxels(grid=grid, mesh=mesh, mode='annihilation')
# check the total mass
# show a picture
elemmass = np.sum(mesh.mass)
voxmass = np.sum(grid.fields["m"])
err = np.abs(1.0 - voxmass / elemmass)
# print the error and show the figure
print('Global error = %.10e' % err)
# perturb the position randomly, keeping it within the unit box
pos -= 0.5
pos *= 0.5 + 0.4 * np.random.sample(pos.shape)
pos += 0.5
# make a mesh, using the direct array input mode
# NOTE: connectivity must be 32-bit ints
conn = np.array([list(range(pos.shape[0]))],
dtype=np.int32) # TODO: connectivity array must be 2D
pbox = (
None, None
) # TODO: this is still necessary to pass, even if the mesh is not periodic
print(' - Connectivity =', conn)
mesh = psi.Mesh(loader='array',
posar=pos,
velar=vel,
massar=mass,
connar=conn,
box=pbox)
print('Connectivity done')
# create the Grid, specifying the resolution and projection window
ngrid = 3 * (128, )
win = ((0., 0., 0.), (1., 1., 1.))
grid = psi.Grid(type='cart', n=ngrid, window=win)
print('Grid done')
# call PSI.voxels()
psi.voxels(grid=grid,
mesh=mesh,
def test_beam_tracing(self):
return
#metric = psi.Metric(type='flrw', filepattern='/home/devon/HDD/PS-128-vm/geo/%04d')
metric = psi.Metric(type='kerr')
with open('/home/devon/HDD/PS-128-vm/geo/0137', 'rb') as f:
# read potential
f.seek(0)
phi = np.fromfile(f, count=128**3, dtype=np.float32).reshape(
(128, 128, 128))
print(phi.shape, np.min(phi), np.max(phi))
# read velocity
f.seek(128**3)
vel = np.fromfile(f, count=3 * 128**3, dtype=np.float32).reshape(
(128, 128, 128, 3))
# read potential
f.seek(4 * 128**3)
gradphi = np.fromfile(f, count=3 * 128**3,
dtype=np.float32).reshape((128, 128, 128, 3))
print(gradphi.shape, np.min(gradphi), np.max(gradphi))
f.close()
gradax = 2
mygrad = np.roll(phi, 1, axis=gradax) - np.roll(phi, -1, axis=gradax)
fig, ax = plt.subplots(1, 2, figsize=(20, 10))
#ax[0].imshow(phi[64,:,:])
ax[0].imshow(mygrad[64, :, :])
ax[1].imshow(gradphi[64, :, :, gradax])
#ax[1].contour(phi[64,:,:])
plt.show()
#return
#print
grid = psi.Grid(type='hpring', n=16)
rayinfo = psi.beamtrace(grid=grid,
metric=metric,
obspos=(10., 9., 8.),
obsvel=(0., 0., 0.))
print(rayinfo.shape)
print(rayinfo[0, :, :])
fig = plt.figure()
ax = fig.gca(projection='3d')
for tray in rayinfo:
ray = tray[tray[:, 0] > 0.0]
ax.plot(ray[:, 1],
ray[:, 2],
ray[:, 3],
'k-',
lw=0.2,
label='parametric curve')
#ax.set_xlim(-30,30)
#ax.set_ylim(-30,30)
#ax.set_zlim(-30,30)
plt.show()
# show the pixel area plot
hp.mollview((grid.fields['m']), title='minkowski')
plt.show()
Example 4: RStarTree
Demonstrates how to use the RStarTree class
Still somewhat rudimentary
RStarTree is used by PSI.VDF and PSI.voxels(mode='annihlation') so far.
'''
import PSI as psi
import helpers as hlp
import numpy as np
# load the mesh
snap = '../data/snapshot_010'
mesh = psi.Mesh(filename=snap, loader='gadget2')
# make an RStarTree out of the mesh
# Currently this is the only constructor;
# a mesh must be provided
rst = psi.RStarTree(mesh)
# set up the query box
query_box = ((10., 9., 8.), (10.3, 9.5, 8.2))
# query the tree
# this returns an index for each queried element!
qinds = rst.query(box=query_box)
print(' - element indices =', qinds)
# use fancy indexing to get the element connectivity back
import PSI as psi
import helpers as hlp
import numpy as np
# load the mesh from a Gadget snapshot
snap = '../data/snapshot_010'
mesh = psi.Mesh(filename=snap, loader='gadget2')
# create the Grid, specifying the resolution and projection window
ngrid = 3*(128,)
win = (mesh.boxmin, mesh.boxmax)
grid = psi.Grid(type='cart', n=ngrid, window=win)
# call PSI.voxels()
psi.voxels(grid=grid, mesh=mesh, mode='density')
#psi.voxels(grid=grid, mesh=mesh, mode='annihilation')
# check the total mass
# show a picture
elemmass = np.sum(mesh.mass)
voxmass = np.sum(grid.fields["m"])
err = np.abs(1.0-voxmass/elemmass)
# print the error and show the figure
print('Global error = %.10e' % err)
hlp.makeFigs(grid.fields['m'], log=True, title='Example 2: Voxelization of a cosmological density field')
pos *= 0.5 + 0.4*np.random.sample(pos.shape)
pos += 0.5
# make a mesh, using the direct array input mode
# NOTE: connectivity must be 32-bit ints
conn = np.array([list(range(pos.shape[0]))], dtype=np.int32)# TODO: connectivity array must be 2D
pbox = (None, None) # TODO: this is still necessary to pass, even if the mesh is not periodic
print(' - Connectivity =', conn)
mesh = psi.Mesh(loader='array', posar=pos, velar=vel, massar=mass, connar=conn, box=pbox)
print('Connectivity done')
# create the Grid, specifying the resolution and projection window
ngrid = 3*(128,)
win = ((0.,0.,0.),(1.,1.,1.))
grid = psi.Grid(type='cart', n=ngrid, window=win)
print('Grid done')
# call PSI.voxels()
psi.voxels(grid=grid, mesh=mesh, mode='density', refine_tolerance=reftol, refine_max_lvl=reflvlmax)
# print the error and show the figure
elemmass = np.sum(mesh.mass)
voxmass = np.sum(grid.fields["m"])
err = np.abs(1.0-voxmass/elemmass)
print('Global error = %.10e' % err)
hlp.makeFigs(grid.fields['m'], title='Example 2: Voxelization of a cosmological density field')