def get_ppv(self, axis, prefix='ppv_1', ppv_args={}):
self.get_fits_name('density', axis)
ds = yt.load(self.enzo_dataset)
ppv_name_vel = '%s/%s_vel.fits' % (self.fits_dir, prefix)
ppv_name_yt = '%s/%s_yt.fits' % (self.fits_dir, prefix)
normal = axis
if len(glob.glob(ppv_name_yt)) == 0:
field = ppv_args.get('field', 'density')
velocity_bounds = ppv_args.get('velocity_bounds',
(-35, 35, 14, 'code_velocity'))
dims = ppv_args.get('dims', 256)
cube = PPVCube(ds,
normal,
"density",
velocity_bounds,
dims=dims,
method='sum')
cube.write_fits(ppv_name_yt)
hdu = pyfits.PrimaryHDU(cube.vbins)
hdulist = pyfits.HDUList([hdu])
hdulist.writeto(ppv_name_vel, clobber=True)
print "Wrote", ppv_name_yt
print "Wrote", ppv_name_vel
print "Reading", ppv_name_yt
#self.ppv_name = ppv_name
self.ppv_name_yt = ppv_name_yt
ds_cube = yt.load(ppv_name_yt)
cube_only = np.rot90(
pyfits.open(ppv_name_yt)[0].data.swapaxes(0, 2), 3)
vel = pyfits.open(ppv_name_vel)[0].data
return cube_only, ds_cube, vel
def test_ppv():
np.random.seed(seed=0x4d3d3d3)
dims = (8, 8, 1024)
v_shift = 1.0e7 * u.cm / u.s
sigma_v = 2.0e7 * u.cm / u.s
T_0 = 1.0e8 * u.Kelvin
data = {
"density": (np.ones(dims), "g/cm**3"),
"temperature": (T_0.v * np.ones(dims), "K"),
"velocity_x": (np.zeros(dims), "cm/s"),
"velocity_y": (np.zeros(dims), "cm/s"),
"velocity_z": (np.random.normal(loc=v_shift.v,
scale=sigma_v.v,
size=dims), "cm/s")
}
ds = load_uniform_grid(data, dims)
cube = PPVCube(ds,
"z",
"density", (-300., 300., 1024, "km/s"),
dims=8,
thermal_broad=True)
dv = cube.dv
v_th = np.sqrt(2. * kboltz * T_0 / (56. * mh) +
2. * sigma_v**2).in_units("km/s")
a = cube.data.mean(axis=(0, 1)).v
b = dv * np.exp(-(
(cube.vmid + v_shift) / v_th)**2) / (np.sqrt(np.pi) * v_th)
yield assert_allclose_units, a, b, 1.0e-2
E_0 = 6.8 * u.keV
cube.transform_spectral_axis(E_0.v, str(E_0.units))
dE = -cube.dv
delta_E = E_0 * v_th.in_cgs() / clight
E_shift = E_0 * (1. + v_shift / clight)
c = dE * np.exp(-(
(cube.vmid - E_shift) / delta_E)**2) / (np.sqrt(np.pi) * delta_E)
yield assert_allclose_units, a, c, 1.0e-2
def test_ppv():
np.random.seed(seed=0x4d3d3d3)
dims = (8,8,1024)
v_shift = 1.0e7*u.cm/u.s
sigma_v = 2.0e7*u.cm/u.s
T_0 = 1.0e8*u.Kelvin
data = {"density":(np.ones(dims),"g/cm**3"),
"temperature":(T_0.v*np.ones(dims), "K"),
"velocity_x":(np.zeros(dims),"cm/s"),
"velocity_y":(np.zeros(dims),"cm/s"),
"velocity_z":(np.random.normal(loc=v_shift.v,scale=sigma_v.v,size=dims), "cm/s")}
ds = load_uniform_grid(data, dims)
cube = PPVCube(ds, "z", "density", (-300., 300., 1024, "km/s"),
dims=8, thermal_broad=True)
dv = cube.dv
v_th = np.sqrt(2.*kboltz*T_0/(56.*mh) + 2.*sigma_v**2).in_units("km/s")
a = cube.data.mean(axis=(0,1)).v
b = dv*np.exp(-((cube.vmid+v_shift)/v_th)**2)/(np.sqrt(np.pi)*v_th)
yield assert_allclose_units, a, b, 1.0e-2
E_0 = 6.8*u.keV
cube.transform_spectral_axis(E_0.v, str(E_0.units))
dE = -cube.dv
delta_E = E_0*v_th.in_cgs()/clight
E_shift = E_0*(1.+v_shift/clight)
c = dE*np.exp(-((cube.vmid-E_shift)/delta_E)**2)/(np.sqrt(np.pi)*delta_E)
yield assert_allclose_units, a, c, 1.0e-2
def test_ppv_nothermalbroad():
np.random.seed(seed=0x4d3d3d3)
dims = (16, 16, 128)
v_shift = 1.0e6*u.cm/u.s
sigma_v = 2.0e6*u.cm/u.s
data = {"density":(np.ones(dims),"g/cm**3"),
"velocity_x":(np.zeros(dims),"cm/s"),
"velocity_y":(np.zeros(dims),"cm/s"),
"velocity_z":(np.random.normal(loc=v_shift.v,scale=sigma_v.v,size=dims), "cm/s")}
ds = load_uniform_grid(data, dims)
cube = PPVCube(ds, "z", "density", (-100., 100., 128, "km/s"),
dims=16, thermal_broad=False)
dv = cube.dv
v_noth = np.sqrt(2)*(sigma_v).in_units("km/s")
a = cube.data.mean(axis=(0,1)).v
b = dv*np.exp(-((cube.vmid+v_shift)/v_noth)**2)/(np.sqrt(np.pi)*v_noth)
assert_allclose_units(a, b, atol=5.0e-3)
execfile('go')
def fake_temp(field,data):
return data.ds.arr(np.ones_like(data['density'].v)*10,'K')
yt.add_field('temperature',function=fake_temp,units='K')
from yt.analysis_modules.ppv_cube.api import PPVCube
velocity_bounds = (-70,70,128,'code_velocity')
dims = 256
normal = [0,0,-1]
normal = 'x'
ds = yt.load('/scratch1/dcollins/Paper08/B02/256/RS0050/restart0050')
cube = PPVCube(ds, normal, "density", velocity_bounds,dims=dims, method='sum')
print "nans", np.isnan(cube[:]).sum()
def fake_temp(field,data):
return data.ds.arr(np.ones_like(data['density'].v)*10,'K')
yt.add_field('temperature',function=fake_temp,units='K')
if 0:
simname = 'B02'
resolution = 256
frame = 30
dirname = '/scratch1/dcollins/Paper08/%s/%d/RS%04d/restart%04d'%(simname,resolution,frame,frame)
ds = yt.load(dirname)
ds.index.grids[0]['temperature']
L = [0,0,1]
cube = PPVCube(ds, L, "density", (-150.,150.,50,"code_velocity"), dims=200, method="sum")
if 0:
for n,v in enumerate(cube.vmid):
# if n not in [20,21]:
# continue
plt.clf()
plt.imshow(np.log10(cube[:,:,n].v),cmap='jet',origin='lower',interpolation='nearest')
plt.text(0,0,r'$%0.2f \rm{km}/\rm{s}$'%v)
cb=plt.colorbar()
cb.cmap.set_under('w')
cb.cmap.set_bad('w')
outname = 'p14b_tmp_slice%04d.png'%n
plt.savefig(outname)
print outname