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Updates to make util_AMRgrid.py run #63

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Updates to make util_AMRgrid.py run #63

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acf95ac
Python 2 to 3
spfanning Nov 21, 2021
34afc69
lsctables requires parameters to be named mass1, mass2, spin1z, etc.
spfanning Nov 21, 2021
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27 changes: 14 additions & 13 deletions MonteCarloMarginalizeCode/Code/RIFT/misc/amrlib.py
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Original file line number Diff line number Diff line change
Expand Up @@ -301,7 +301,8 @@ def create_regular_grid_from_cell(cell, side_pts=5, return_cells=False):
# This produces a representation of the points, but not in a tuple form
grid_pts = numpy.mgrid[grid_pts]
# This tuplizes them
grid_pts = numpy.array(zip(*[grid.flatten() for grid in grid_pts]))
#grid_pts = numpy.array(zip(*[grid.flatten() for grid in grid_pts])) # python2
grid_pts = grid_pts.reshape(grid_pts.shape[0],-1).T.copy()

# useful knowledge for later
grid_spacing = numpy.array([(rb - lb) / (side_pts - 1) for lb, rb in cell._bounds])
Expand Down Expand Up @@ -377,7 +378,7 @@ def save_grid_cells_hdf(base_grp, cells, crd_sys, intr_prms=None, check=True):
assert grids.attrs["distance_coordinates"] == crd_sys

levels = []
for name, ds in grids.iteritems():
for name, ds in grids.items():
levels.append((ds.attrs["level"], name))

grid_res = numpy.diff(cells[0]._bounds).flatten()
Expand Down Expand Up @@ -429,9 +430,9 @@ def load_grid_level(h5file, level, return_labels= False, base_grp="rapidpe_grids

grids = hfile[base_grp]["grids"]
if level == -1:
level = sorted(dat.attrs["level"] for name, dat in grids.iteritems())[-1]
level = sorted(dat.attrs["level"] for name, dat in grids.items())[-1]

for name, dat in grids.iteritems():
for name, dat in grids.items():
if dat.attrs["level"] == level:
grid_res = dat.attrs["resolution"][numpy.newaxis,:]
if return_labels:
Expand Down Expand Up @@ -559,19 +560,19 @@ def check_grid(grid, intr_prms, distance_coordinates):
"""
Check the validity of points in various coordinate spaces to ensure they are physical.
"""
m1_axis, m2_axis = intr_prms.index("m1"), intr_prms.index("m2")
m1_axis, m2_axis = intr_prms.index("mass1"), intr_prms.index("mass2")
grid_check = numpy.array(grid).T
if distance_coordinates == "tau0_tau3":
bounds_mask = check_tau0tau3(grid_check[m1_axis], grid_check[m2_axis])
elif distance_coordinates == "mchirp_eta":
bounds_mask = check_mchirpeta(grid_check[m1_axis], grid_check[m2_axis])

# FIXME: Needs general spin
if "s1z" in intr_prms:
s1_axis = intr_prms.index("s1z")
if "spin1z" in intr_prms:
s1_axis = intr_prms.index("spin1z")
bounds_mask &= check_spins(grid_check[s1_axis])
if "s2z" in intr_prms:
s2_axis = intr_prms.index("s2z")
if "spin2z" in intr_prms:
s2_axis = intr_prms.index("spin2z")
bounds_mask &= check_spins(grid_check[s2_axis])
if "chi_z" in intr_prms:
chi_axis = intr_prms.index("chi_z")
Expand Down Expand Up @@ -605,10 +606,10 @@ def apply_transform(pts, intr_prms, mass_transform=None, spin_transform=None):
# You know what... recarrays are dumb, and so's your face.
# FIXME: Why does numpy want me to repack this into tuples!?
#tpts = numpy.array([tuple(pt) for pt in pts.T], dtype = numpy.dtype([(a ,"float64") for a in intr_prms]))
m1_idx, m2_idx = intr_prms.index("m1"), intr_prms.index("m2")
m1_idx, m2_idx = intr_prms.index("mass1"), intr_prms.index("mass2")
if spin_transform:
if spin_transform == "chi_z":
s1z_idx, s2z_idx = intr_prms.index("s1z"), intr_prms.index("s2z")
s1z_idx, s2z_idx = intr_prms.index("spin1z"), intr_prms.index("spin2z")
# chi_z = transform_s1zs2z_chi(pts[:,m1_idx], pts[:,m2_idx], pts[:,s1z_idx], pts[:,s2z_idx])
#The grid is converted from m1 m2 s1 s2 to mc eta chi_eff because it's better to choose the closest grid points in mc eta chi_eff space.
#chi_a is not considered when choosing the closes grid points, but we do need it to transform back to s1 s2
Expand All @@ -625,13 +626,13 @@ def apply_transform(pts, intr_prms, mass_transform=None, spin_transform=None):
return pts

def apply_inv_transform(pts, intr_prms, mass_transform=None,spin_transform=None):
m1_idx, m2_idx = intr_prms.index("m1"), intr_prms.index("m2")
m1_idx, m2_idx = intr_prms.index("mass1"), intr_prms.index("mass2")
if mass_transform:
pts[:,m1_idx], pts[:,m2_idx] = INVERSE_TRANSFORMS_MASS[VALID_TRANSFORMS_MASS[mass_transform]](pts[:,m1_idx], pts[:,m2_idx])

if spin_transform:
if spin_transform == "chi_z":
s1z_idx, s2z_idx = intr_prms.index("s1z"), intr_prms.index("s2z")
s1z_idx, s2z_idx = intr_prms.index("spin1z"), intr_prms.index("spin2z")
pts[:,s1z_idx],pts[:,s2z_idx] =transform_chi_eff_chi_a_s1zs2z(pts[:,m1_idx], pts[:,m2_idx], pts[:,s1z_idx], pts[:,s2z_idx])


Expand Down
14 changes: 7 additions & 7 deletions MonteCarloMarginalizeCode/Code/bin/util_AMRGrid.py
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Original file line number Diff line number Diff line change
Expand Up @@ -155,7 +155,7 @@ def write_to_xml(cells, intr_prms, pin_prms={}, fvals=None, fname=None, verbose=
sim_insp.alpha1 = fvals[itr]
for p, v in zip(intr_prms, intr_prm._center):
setattr(sim_insp, p, v)
for p, v in pin_prms.iteritems():
for p, v in pin_prms.items():
setattr(sim_insp, p, v)
sim_insp_tbl.append(sim_insp)

Expand Down Expand Up @@ -276,12 +276,12 @@ def parse_param(popts):

#If spin 1 and 2 are not specified, they are pinned. This means the spin columns still appear in the output grid.
spin_transform=None
if not "s1z" in intr_prms or not "s2z" in intr_prms:
if not "s1z" in intr_prms and not "s2z" in intr_prms:
if not "s1z" in pin_prms:
pin_prms["s1z"] = 0.0
if not "s2z" in pin_prms:
pin_prms["s2z"] = 0.0
if not "spin1z" in intr_prms or not "spin2z" in intr_prms:
if not "spin1z" in intr_prms and not "spin2z" in intr_prms:
if not "spin1z" in pin_prms:
pin_prms["spin1z"] = 0.0
if not "spin2z" in pin_prms:
pin_prms["spin2z"] = 0.0
else:
sys.exit("spin1z or spin2z is specified but not the other spin. compute intrinsic grid is not setup to search just one")
else:
Expand Down