def phase_by_region(filename,
params=None,
out_dir='',
region='midplane',
overwrite=False):
'''
phase_by_region(filename,out_dir='',region='midplane)
calculate 2D joint PDFs from TIGRESS vtk dump.
Inputs
------
filename: string
file name of vtk dump
Parameters
----------
params: class (phase_parameters)
out_dir: string
directory name for the output hdf5 file
region: string
setting the region for joint PDFs to be calculated
'midplane' -- cubic region near the midplane
'upper' or 'lower' -- region upper or lower than 512 pc
'full' -- entire domain
'''
if params is None: params = phase_parameters()
tigress_unit_system = params.unit_system
ds = yt.load(filename,
units_override=ya.unit_base,
unit_system=tigress_unit_system)
ya.add_yt_fields(ds, cooling=True, mhd=True, rotation=False)
le = ds.domain_left_edge
re = ds.domain_right_edge
if region == 'midplane':
le[2] = le[1]
re[2] = re[1]
elif region == 'upper':
le[2] = yt.YTQuantity(512, 'pc')
elif region == 'lower':
re[2] = yt.YTQuantity(-512, 'pc')
elif region == 'full':
pass
else:
print('{} is unsupported region type.')
print('region = [midplane, upper, lower, full]'.format(region))
raise ValueError
print('Joint PDFs to be calculated for quantities in')
print('x = {} ~ {}'.format(le[0], re[0]))
print('y = {} ~ {}'.format(le[1], re[1]))
print('z = {} ~ {}'.format(le[2], re[2]))
region = ds.box(le, re)
phase_part(ds, region, out_dir, params=params, overwrite=overwrite)
def FG_model(ds, center, size, height, mP):
try:
box = cell_patch(ds, center, size, height)
# gal_center = ds.arr([0.5, 0.5, 0.6], 'code_length')
# mP = massProfile(gal_center, ds)
size = yt.YTQuantity(size, 'pc')
Q = Qpatch(box, size, mP)
phi = 1./Q
F = 1.
retMomentum = yt.YTQuantity(3000., 'km/s')
SigmaG = GasDensity(ds,center, size, height, temp = 'all')
SigmaSF = (2.*np.sqrt(2.)*np.pi*G*Q*phi/F)*((retMomentum)**-1)*(SigmaG**2)
# SigmaSF = yt.YTQuantity(13., 'Msun/yr/kpc**2')*(Q*phi/F)*((retMomentum/yt.YTQuantity(3000., 'km/s'))**-1)*(SigmaG/yt.YTQuantity(10**3, 'Msun/pc**2'))**2
print('SigmaG: ', SigmaG)
print('SigmaSFR: ', SigmaSF)
return SigmaSF.in_units('Msun/yr/kpc**2')
except:
pass
def SFDensity_age_cut(ds, center, size, height, age_range):
#define center, establish YT Quantities
x, y, z = center
size = yt.YTQuantity(size,'pc')
height = yt.YTQuantity(height, 'pc')
min_age, max_age = age_range
min_age = yt.YTQuantity(min_age, 'Myr')
max_age = yt.YTQuantity(max_age, 'Myr')
#Create spatial patch
box = cell_patch(ds, center, size, height)
#Select new star particles in patch
formed_star_birth = box['formed_star', 'creation_time'].in_units('Myr')
formed_star_ages = (ds.current_time.in_units('Myr') - formed_star_birth).in_units('Myr')
formed_star_mass = box['formed_star', 'particle_mass']
#Select stars between min and max age
low_filter = formed_star_ages > min_age
high_filter = formed_star_ages < max_age
filtered_mass = formed_star_mass[low_filter & high_filter]
#Find total mass of stars, then SD
total_star_mass = np.sum(filtered_mass)
sfrDen = (total_star_mass/((size**2)*max_age)).in_units('Msun/yr/kpc**2')
return sfrDen
def nonlinear_fH2(fH2, G0):
Sigma_H2 = (fH2*SigmaG).in_units('Msun/pc**2').in_cgs()
Sigma_HI = ((1-fH2)*SigmaG).in_units('Msun/pc**2').in_cgs()
RH2 = Sigma_H2/Sigma_HI
#Plug values into system of equations
nCNM_min = 31*G0*(1+3.1*(Z)**0.365)**-1
nCNM_2p = yt.YTQuantity(23*G0*((1+3.1*Z**0.365)/4.1)**-1, 'cm**-3')
Pth = ((np.pi*G*Sigma_HI**2)/(4.*alpha))*(1+2*RH2+np.sqrt(((1+2*RH2)**2)+(32*zd*alpha*fw*rhoSD*cw**2)/(np.pi*G*Sigma_HI**2)))
nCNM_hydro = Pth/(1.1*kB*tCNM)
nCNM = max([nCNM_hydro.in_units('cm**-3'), nCNM_2p.in_units('cm**-3')])
n1 = nCNM/yt.YTQuantity(10., 'cm**-3')
Chi = (7.2*G0/n1).in_units('')
Tc = (0.066*fc*Z*SigmaG_0).in_units('')
S = np.log(1 + 0.6*Chi + 0.01*Chi**2)/(0.6*Tc)
if S < 2.:
fH2_inferred = 1 - (3/4)*S/(1+0.25*S)
else:
fH2_inferred = 0
return fH2 - fH2_inferred
def _MicroTurb(field, data):
turb = data[inputs.velocityX_field]
turb[turb>=0] = yt.YTQuantity(inputs.microturbulence_speed, "cm/s")
turb[turb<=0] = yt.YTQuantity(inputs.microturbulence_speed, "cm/s")
#print(turb.min())
#print(turb.max())
return turb
def _entr(field, data):
"""
fixed the entropy units in flash
"""
entr = data["entr"]
kb_by = yt.YTQuantity(1, 'erg') / yt.YTQuantity(
1, 'K') / yt.YTQuantity(1, 'g') * (1.3806488e-16 / 1.674e-24)
return entr * kb_by
def _NumberDensityXYZ(field, data):
aw = yt.YTQuantity(inputs.gas_mmw*Csts.mp, 'g')
H2numDen = (inputs.x_H2/aw)*data[inputs.density_field]
XYZnumDen= (inputs.x_XYZ/aw)*data[inputs.density_field]
#print(H2numDen.min())
#print(H2numDen.max())
if(inputs.allow_freezeout):
XYZnumDen[H2numDen < inputs.freeze_minN] = yt.YTQuantity(0.0, "cm**-3")
XYZnumDen[H2numDen > inputs.freeze_maxN] = yt.YTQuantity(0.0, "cm**-3")
return XYZnumDen
def generate_sim_column_densities(sim, ion_list, res=800):
#cdens_file = h5.File('../../data/simulated_ion_column_densities_%s.h5'%(sim), 'w')
cdens_file = h5.File('test.h5', 'w')
ds, center, bv = spg.load_simulation_properties(sim)
print(center)
center = ds.arr(center, 'kpc')
trident.add_ion_fields(ds, ion_list)
field_list = ipd.generate_ion_field_list(ion_list,
'number_density',
model='P0')
width = yt.YTQuantity(110, 'kpc')
px, py = np.mgrid[-width / 2:width / 2:res * 1j,
-width / 2:width / 2:res * 1j]
radius = (px**2.0 + py**2.0)**0.5
if "radius" not in cdens_file.keys():
cdens_file.create_dataset("radius", data=radius.ravel())
# note: something weird going on in x-axis with P0
for axis in ['x', 'y', 'z']:
frb = ipd.make_projection(ds, axis, field_list, center, width)
for i, ion in enumerate(ion_list):
dset = "%s_%s" % (ion.replace(" ", ""), axis)
if dset not in cdens_file.keys():
cdens_file.create_dataset(dset,
data=frb[field_list[i]].ravel())
cdens_file.flush()
def test_unequal_bin_field_profile(self):
density = np.random.random(128)
temperature = np.random.random(127)
mass = np.random.random((128, 128))
my_data = {
("gas", "density"): density,
("gas", "temperature"): temperature,
("gas", "mass"): mass,
}
fake_ds_med = {"current_time": yt.YTQuantity(10, "Myr")}
field_types = {field: "gas" for field in my_data.keys()}
yt.save_as_dataset(fake_ds_med,
"mydata.h5",
my_data,
field_types=field_types)
ds = yt.load("mydata.h5")
with assert_raises(YTProfileDataShape):
yt.PhasePlot(
ds.data,
("gas", "temperature"),
("gas", "density"),
("gas", "mass"),
)
def massInterior(self, r):
if not self.cached:
self.cache()
# the interpolation function os for logr-logM
print('r: ', r.in_units('kpc'))
return yt.YTQuantity(
np.power(10.0, self.f(np.log10(r.in_units('kpc')))), 'msun')
def generate_sim_column_densities(sim, ion_list, res = 800):
cdens_file = h5.File('../../data/simulated_ion_column_densities_%s.h5'%(sim), 'a')
if sim == 'ad' or sim == 'stream':
ds = yt.load('/Users/irynabutsky/Work/galaxy/g160_torB_%s/DD2600'%(sim))
elif sim == 'P0':
ds = yt.load('/Users/irynabutsky/Work/galaxy/P0/P0.003195')
trident.add_ion_fields(ds, ion_list)
if sim == 'P0':
# center = YTArray([-1.693207e4, -1.201068e4, 5.303337e3], 'kpc')
center = [-0.42323229, -0.30021773, 0.13256167]
else:
v, center = ds.h.find_max(("gas", "density"))
print(center)
field_list = ipd.generate_ion_field_list(ion_list, 'number_density', model = 'P0')
width = yt.YTQuantity(1000, 'kpc')
px, py = np.mgrid[-width/2:width/2:res*1j, -width/2:width/2:res*1j]
radius = (px**2.0 + py**2.0)**0.5
if "radius" not in cdens_file.keys():
cdens_file.create_dataset("radius", data = radius.ravel())
# note: something weird going on in x-axis with P0
for axis in ['y', 'z']:
frb = ipd.make_projection(ds, axis, field_list, center, width)
for i, ion in enumerate(ion_list):
dset = "%s_%s" % (ion.replace(" ", ""), axis)
if dset not in cdens_file.keys():
cdens_file.create_dataset(dset, data=frb[field_list[i]].ravel())
cdens_file.flush()
def Ostriker_model(ds, center, size, height):
box = cell_patch(ds, center, size, height)
SigmaG = GasDensity(ds, center, size, height, temp='all')
print('SigmaG: ', SigmaG)
size = yt.YTQuantity(size, 'pc').in_cgs()
height = yt.YTQuantity(height, 'pc').in_cgs()
SigmaG_0 = (SigmaG / yt.YTQuantity(1., 'Msun/pc**2')).in_units('')
Z = 0.1
rhoSD = (np.sum(box['particle_mass'].in_units('g')) /
((size**2) * (2 * height))).in_cgs()
print('rhoSD: ', rhoSD)
Sigma_h = (2 * alpha * Pth_0) / (np.pi * G * SigmaSF_0 * t_SF)
S = (8. * zd * alpha * fw * rhoSD * cw**2) / (np.pi * G * SigmaG**2)
omega = SigmaG / Sigma_h
print('Sigma_h: ', Sigma_h)
print('s: ', S)
print('omega: ', omega)
def Gdiff_frac(x):
return omega * (1. + (1. + (1. / (omega * (1. - x))) +
(S / (1. - x)**2.))**(1. / 2.)) - (1 / x)
x = opt.brentq(Gdiff_frac, 10**-5, 1)
print('x: ', x)
Sigma_diff = x * SigmaG
Sigma_GBC = (1 - x) * SigmaG
print('Sigma_diff', Sigma_diff)
print('Sigma_GBC', Sigma_GBC)
#diffuse-gas thermal equilibrium
# phi_d = (1./4.)*(1+3*(Z*SigmaG/SigmaG_0)**0.4)
# Pth = (1-phi_d)*(Pth_0/SigmaSF_0)*(Sigma_GBC/t_SF)
# Pth = ((np.pi*G*Sigma_diff**2)/(4*alpha))*(1+2*(Sigma_GBC/Sigma_dff)+((1+2*(Sigma_GBC/Sigma_diff))**2+((32*zd*alpha*fw*cw**2)/(np.pi*G))*(rhoSD/(Sigma_diff**2)))**(1/2))
SigmaSF = (Sigma_GBC / t_SF)
print('tSF: ', t_SF)
print('SigmaSFR: ', SigmaSF)
return SigmaSF.in_units('Msun/yr/kpc**2')
def _entrdens(field, data):
"""
create a new derived field to show both entropy and density
if density > PNS_DENSITY:
entropy = PNS_ENTR
else:
entropy = entropy
"""
dens = data["dens"]
entr = data["entr"]
entrdens = entr * (
np.exp(-(dens.in_cgs() / PNS_DENSITY)**5)) + PNS_ENTR
kb_by = yt.YTQuantity(1, 'erg') / yt.YTQuantity(
1, 'K') / yt.YTQuantity(1, 'g') * (1.3806488e-16 / 1.674e-24)
return entrdens * kb_by
def SFDensity(ds, center, size, height, cutoff):
#define center, establish YT Quantities
x, y, z = center
size = yt.YTQuantity(size,'pc')
height = yt.YTQuantity(height, 'pc')
#max_age = yt.YTQuantity(max_age, 'Myr')
cutoff = yt.YTQuantity(cutoff, 'Myr')
max_age = (ds.current_time.in_units('Myr') - cutoff).in_units('Myr')
#Create spatial patch
box = cell_patch(ds, center, size, height)
#Create array of masses & ages of all particles
star_mass = box['particle_mass'].in_units('Msun')
creation_time = box['creation_time']
#Select new star particles in patch
new_stars = creation_time > 0
new_star_time = creation_time[new_stars].in_units('Myr')
new_star_ages = (ds.current_time.in_units('Myr') - new_star_time).in_units('Myr')
birth_years = creation_time[new_stars].in_units('Myr')
#Create cutoff after SFR is stabilized (~200MYR)
# cutoff = yt.YTQuantity(200, 'Myr')
# cut_mask = new_star_ages < cutoff
# cut_ages = new_star_ages[cut_mask]
#young = new_star_ages < max_age
#stars = new_star_ages[young]
#stars = new_star_ages[young]
young = birth_years > cutoff
stars = birth_years[young]
#Get masses of new stars
new_star_mass = star_mass[new_stars]
# new_star_mass = new_star_mass[cut_mask]
young_star_mass = new_star_mass[young]
#Find total mass of new stars, then surface density
total_star_mass = np.sum(young_star_mass)
sfrDen = (total_star_mass/((size**2)*max_age)).in_units('Msun/yr/kpc**2')
return sfrDen
def nonlinear_G0(G0):
fH2_found = opt.brentq(nonlinear_fH2, 0, 1, args = (G0))
tff = yt.YTQuantity(31*SigmaG_0**(-1/4), 'Myr')
SigmaSF = fH2_found*Eff*SigmaG/tff
return SigmaSF/SigmaSF_0 - G0
def set_units(input_units):
"""
sets units used for all calculations
"""
global length_unit
global velocity_unit
global mass_unit
global time_unit
for key in input_units.keys():
if key in units.keys():
units[key] = input_units[key]
length_unit = yt.YTQuantity(units["length_unit"][0],
units["length_unit"][1])
velocity_unit = yt.YTQuantity(units["velocity_unit"][0],
units["velocity_unit"][1])
mass_unit = yt.YTQuantity(units["mass_unit"][0], units["mass_unit"][1])
time_unit = yt.YTQuantity(units["time_unit"][0], units["time_unit"][1])
density_unit = yt.YTQuantity(units["density_unit"][0],
units["density_unit"][1])
def luminosity(global_data, sink_inds, global_ind):
"""
Calculates the luminosity of the given indexes
"""
global f_acc
radius = yt.YTQuantity(2.0, 'rsun')
M_dot = accretion(sink_inds, global_ind)
M = yt.YTArray(global_data['m'][global_ind,sink_inds]*units['mass_unit'].in_units('msun'), 'Msun')
L_acc = f_acc * (yt.units.G * M.in_units('g') * M_dot.in_units('g/s'))/radius.in_units('cm')
L_tot = L_acc.in_units('Lsun')
return L_tot
def generate_column_data(output, ion_list, res=800, axis='y'):
sim = 'romulusC'
field_list = ion_help.generate_ion_field_list(ion_list, 'number_density')
ds = yt.load('/nobackupp2/ibutsky/simulations/%s/%s.%06d' %
(sim, sim, output))
trident.add_ion_fields(ds, ions=ion_list)
cdens_file = h5.File(
'/nobackupp2/ibutsky/data/%s/%s.%06d_column_data.h5' %
(sim, sim, output), 'a')
rom_center = rom_help.get_romulus_center(sim, output)
id_list, center_x_list, center_z_list, width_list = \
np.loadtxt('data/temp_coordinate_list.dat'%(sim, output, axis), skiprows=3, unpack = True)
for region_id, center_x, center_z, width in zip(id_list, center_x_list,
center_z_list, width_list):
cdens_file = h5.File(
'/nobackupp2/ibutsky/data/%s/%s.%06d_column_data_region_%i.h5' %
(sim, sim, output, region_id), 'a')
width = yt.YTQuantity(width, 'kpc')
px, py = np.mgrid[-width / 2:width / 2:res * 1j,
-width / 2:width / 2:res * 1j]
radius = (px**2.0 + py**2.0)**0.5
if "px" not in cdens_file.keys():
cdens_file.create_dataset("px", data=px.ravel())
if "py" not in cdens_file.keys():
cdens_file.create_dataset("py", data=py.ravel())
if "radius" not in cdens_file.keys():
cdens_file.create_dataset("radius", data=radius.ravel())
center = [
rom_center[0] + center_x, rom_center[1], rom_center[2] + center_z
]
center = (center / ds.length_unit).d
frb = ion_help.make_projection(ds,
axis,
field_list,
center,
width,
res=res)
for i, ion in enumerate(ion_list):
dset = "%s_%s" % (ion.replace(" ", ""), axis)
if dset not in cdens_file.keys():
cdens_file.create_dataset(dset,
data=frb[field_list[i]].ravel())
cdens_file.flush()
def expectedSFR_calculator(ds, center, size, height):
#Create patch of cells
box = cell_patch(ds, center, size, height)
#Make inputs into YT Quantites
size = yt.YTQuantity(size, 'pc')
height = yt.YTQuantity(height, 'pc')
#Find cells in patch
cell_sfr = box['expectedSFR'].in_units('Msun/yr/kpc**3')
v_cells = box['cell_volume']
#Create Temperature Cut
# cell_temp = ad['temperature'].in_units('K')
# cell_temp_patch = cell_temp[box]
# cold_gas = cell_temp_patch < 10**4
#Add up mass of cells in patch under temp cut
# cold_gas_mass = patch_cells[cold_gas]
cell_sfr = cell_sfr*v_cells
total_sfr = np.sum(cell_sfr)
density = (total_sfr/size**2).in_units('Msun/yr/kpc**2')
return density
def GasDensity(ds, center, size, height, temp):
x,y,z = center
#Create patch of cells
box = cell_patch(ds, center, size, height)
#Make inputs into YT Quantites
size = yt.YTQuantity(size, 'pc')
height = yt.YTQuantity(height, 'pc')
#Find cells in patch
mass = box['cell_mass'].in_units('Msun')
# patch_cells = cell_mass[box]
#Create Temperature Cut
cell_temp = box['temperature'].in_units('K')
# cell_temp_patch = cell_temp[box]
if temp == 'cold':
cold_gas = cell_temp < 10**4
#Add up mass of cells in patch under temp cut
cold_gas_mass = mass[cold_gas]
total_mass = np.sum(cold_gas_mass)
elif temp == 'warm':
warm_gas = cell_temp > 10**4
warm_gas_mass = mass[warm_gas]
total_mass = np.sum(warm_gas_mass)
elif temp == 'all':
total_mass = np.sum(mass)
print(total_mass, size**2)
#Calculate density (Divide by area)
density = total_mass/(size**2)
return density
def test_patch(data):
''' Define a patch in the middle of the galaxy, and add up all the star formation inside, estimated based on the gas-only quantities. Just testing if the patch function and the expectedSFR field are working as expected.'''
a = define_patch(data, (yt.YTQuantity(0.1, 'kpc'), yt.YTQuantity(
0.1, 'kpc'), yt.YTQuantity(0.0, 'kpc')), yt.YTQuantity(3, 'kpc'),
yt.YTQuantity(1.0, 'kpc'), yt.YTQuantity(1.0e4, 'K'))
print(
np.sum((data['expectedSFR'][a] *
data['cell_volume'][a]).in_units('msun/yr')))
def calculateKnownExtrema(Param_Dict, Edit_Dict):
"""Our Dataset already has some of the extrema as attributes, so we can add
those to the Mins and Maxs.
Parameters:
Edit_Dict: To set the center edits"""
ds = Param_Dict["CurrentDataSet"]
axes = ["X", "Y", "Z"]
if Param_Dict["Geometry"] == "cartesian":
edgeList = ["x", "y", "z"]
elif Param_Dict["Geometry"] == "cylindrical":
edgeList = ["r", "z", "theta"]
else:
raise NotImplementedError("only cartesian and cylindrical geometries "
"have been implemented so far")
for i, field in enumerate(edgeList):
minArray = ds.domain_left_edge
maxArray = ds.domain_right_edge
unit = Param_Dict["FieldUnits"][field]
if field == "theta":
minVal = minArray[i].value
maxVal = maxArray[i].value
minTextVal, maxTextVal = 0, 0
else:
minVal = yt.YTQuantity(ds.quan(minArray[i],
'code_length')).to_value(unit)
maxVal = yt.YTQuantity(ds.quan(maxArray[i],
'code_length')).to_value(unit)
minTextVal = yt.YTQuantity(minVal,
unit).to_value(Param_Dict["GridUnit"])
maxTextVal = yt.YTQuantity(maxVal,
unit).to_value(Param_Dict["GridUnit"])
Param_Dict["FieldMins"][field] = minVal
Param_Dict["FieldMaxs"][field] = maxVal
center = 0.5 * (maxTextVal + minTextVal)
cenEdit = Edit_Dict[axes[i] + "Center"]
cenEdit.setText(f"{center:.3g}")
cenEdit.textChanged.emit(cenEdit.text())
def SlicePlot(Param_Dict, worker):
"""Takes a DataSet object loaded with yt and performs a slicePlot on it.
Parameters:
Param_Dict: Dict with Parameters
"""
ds = Param_Dict["CurrentDataSet"]
gridUnit = Param_Dict["GridUnit"]
c0 = yt.YTQuantity(Param_Dict["XCenter"], gridUnit)
c1 = yt.YTQuantity(Param_Dict["YCenter"], gridUnit)
if Param_Dict["Geometry"] == "cartesian":
c2 = yt.YTQuantity(Param_Dict["ZCenter"], gridUnit)
else:
c2 = Param_Dict["ZCenter"]
field = Param_Dict["ZAxis"]
width = (Param_Dict["HorWidth"], gridUnit)
height = (Param_Dict["VerWidth"], gridUnit)
if Param_Dict["NormVecMode"] == "Axis-Aligned":
plot = yt.AxisAlignedSlicePlot(ds, Param_Dict["NAxis"], field,
axes_unit=Param_Dict["GridUnit"],
fontsize=14, center=[c0, c1, c2],
width=(width, height))
else:
normVec = [Param_Dict[axis + "NormDir"] for axis in ["X", "Y", "Z"]]
northVec = [Param_Dict[axis + "NormNorth"] for axis in ["X", "Y", "Z"]]
plot = yt.OffAxisSlicePlot(ds, normVec, field, north_vector=northVec,
axes_unit=Param_Dict["GridUnit"],
fontsize=14, center=[c0, c1, c2],
width=(width, height))
emitStatus(worker, "Setting slice plot modifications")
# Set min, max, unit log and color scheme:
setAxisSettings(plot, Param_Dict, "Z")
# # yt will automatically make it quadratic, so we'll set the individual
# plot.set_width((max(width, height), gridUnit)) # width and height later
plot.zoom(Param_Dict["Zoom"])
emitStatus(worker, "Annotating the slice plot")
annotatePlot(Param_Dict, plot)
finallyDrawPlot(plot, Param_Dict, worker)
def getDerFieldInfo(Param_Dict, ComboBox_Dict, Misc_Dict, dialog):
"""If the user has filled everything in correctly and presses apply, this
function is called to store the function"""
# get all of the information from the dialog:
fieldName = dialog.fieldName
displayName = dialog.displayName
fieldFunction = dialog.fieldFunction
unit = dialog.unit
dim = dialog.dim
override = dialog.override
if dim == 1:
dim = "dimensionless"
text = dialog.functionText
# Add the field to the known fields in Param_Dict and comboboxes:
for axis in ["X", "Y", "Z"]:
Param_Dict[axis + "Fields"].insert(3, fieldName)
ComboBox_Dict[axis + "Axis"].insertItem(3, fieldName)
if axis != "X":
ComboBox_Dict[axis + "Weight"].insertItem(3, fieldName)
Param_Dict["WeightFields"].insert(3, fieldName)
yt.add_field(("gas", fieldName),
function=fieldFunction,
units=unit,
dimensions=dim,
force_override=override,
display_name=displayName,
take_log=False)
reloadFiles(Param_Dict, Misc_Dict)
# Save the parameters in Param_Dict for the ScriptWriting function
Param_Dict["NewDerFieldDict"][fieldName] = {}
Param_Dict["NewDerFieldDict"][fieldName]["Override"] = override
Param_Dict["NewDerFieldDict"][fieldName]["DisplayName"] = displayName
Param_Dict["NewDerFieldDict"][fieldName]["FunctionText"] = text
if unit == "auto":
Param_Dict["NewDerFieldDict"][fieldName]["Unit"] = dialog.baseUnit
else:
Param_Dict["NewDerFieldDict"][fieldName]["Unit"] = unit
Param_Dict["NewDerFieldDict"][fieldName]["Dimensions"] = dim
if unit == "auto":
unit = fieldFunction(
"Hello, I'm a fancy placeholder, why did you \
call me?", dialog.sp).units
ds = Param_Dict["CurrentDataSet"]
Param_Dict["FieldUnits"][fieldName] = yt.YTQuantity(ds.arr(1, unit)).units
GUILogger.log(
29, f"The new field <b>{fieldName}</b> with {dim}-dimension \
has been added successfully.")
GUILogger.info("You can find it in the comboBoxes for the field selection,"
" and it will be added to every new dataset.")
def generate_column_data(sim, ion_list, width=400, res=800):
field_list = ion_help.generate_ion_field_list(ion_list, 'number_density')
ds, center = rom.load_charlotte_sim(sim)
trident.add_ion_fields(ds, ions=ion_list)
fn = '/nobackupp2/ibutsky/data/charlotte/%s_column_data.h5' % (sim)
cdens_file = h5.File(fn)
axis_list = ['x', 'y', 'z']
width = yt.YTQuantity(width, 'kpc')
px, py = np.mgrid[-width / 2:width / 2:res * 1j,
-width / 2:width / 2:res * 1j]
radius = (px**2.0 + py**2.0)**0.5
if "px" not in cdens_file.keys():
cdens_file.create_dataset("px", data=px.ravel())
if "py" not in cdens_file.keys():
cdens_file.create_dataset("py", data=py.ravel())
if "radius" not in cdens_file.keys():
cdens_file.create_dataset("radius", data=radius.ravel())
for axis in axis_list:
#frb = ion_help.make_projection(ds, axis, field_list, center, width, res = res)
for i, ion in enumerate(ion_list):
dset = "%s_%s" % (ion.replace(" ", ""), axis)
if dset not in cdens_file.keys():
print(dset)
sys.stdout.flush()
#frb = ion_help.make_projection(ds, axis, field_list[i], center, width, res = res)
p = yt.ProjectionPlot(ds,
axis,
field_list[i],
width=width,
weight_field=None,
center=center)
p.set_zlim(field_list[i], 1e13, 1e15)
p.save()
frb = p.data_source.to_frb(width, res)
print(frb)
print(frb.keys())
print(frb[field_list[i]])
cdens_file.create_dataset(dset,
data=frb[field_list[i]].d.ravel())
cdens_file.flush()
def test_unequal_bin_field_profile(self):
density = np.random.random(128)
temperature = np.random.random(127)
cell_mass = np.random.random((128, 128))
my_data = {
"density": density,
"temperature": temperature,
"cell_mass": cell_mass}
fake_ds_med = {"current_time": yt.YTQuantity(10, "Myr")}
yt.save_as_dataset(fake_ds_med, "mydata.h5", my_data)
ds = yt.load('mydata.h5')
assert_raises(
YTProfileDataShape,
yt.PhasePlot, ds.data, 'temperature', 'density', 'cell_mass')
def generate_frame_times(files,
dt,
start_time=0,
presink_frames=25,
end_time=None,
form_time=None):
if form_time != None:
sink_form_time = form_time
else:
sink_form_time = find_sink_formation_time(files)
if end_time != None or len(files) == 1:
max_time = end_time
else:
csv.register_dialect('dat', delimiter=' ', skipinitialspace=True)
with open(files[-1].split("info")[0] + 'stars_output.snktxt',
'r') as f:
reader = csv.reader(f, dialect='dat')
for row in reader:
time = yt.YTQuantity(
float(row[1]) * time_unit.in_units('yr').value, 'yr')
break
if form_time != None:
max_time = time.in_units('yr') - form_time
else:
max_time = time.in_units('yr')
if len(files) == 1:
m_times = [time]
else:
if presink_frames != 0:
m_times = np.logspace(0.0, np.log10(sink_form_time),
presink_frames) - sink_form_time
else:
m_times = np.array([])
m_times = m_times.tolist()
postsink = 0.0
while postsink <= max_time:
if start_time is not None:
if postsink >= start_time:
m_times.append(postsink)
else:
m_times.append(postsink)
postsink = postsink + dt
return m_times
def validateUnit(self):
"""Checks whether the unit given matches the dimensionality of the out-
put of the function."""
if self.fieldFunctionEdit.isValid:
if self.unitEdit.text() == "auto":
self.unitEdit.turnTextBlack()
setValidity(self.unitEdit, True)
return
try:
unit = yt.YTQuantity(self.sp.ds.arr(
1, self.unitEdit.text())).units
if unit.dimensions == self.dim:
self.unitEdit.turnTextBlack()
setValidity(self.unitEdit, True)
else:
self.unitEdit.turnTextRed()
setValidity(self.unitEdit, False)
except (UnitParseError, AttributeError):
self.unitEdit.turnTextRed()
setValidity(self.unitEdit, False)
else:
self.unitEdit.turnTextRed()
setValidity(self.unitEdit, False)
def setProfileAxisSettings(Param_Dict, axis, axes):
"""Sets the axis settings for profile plots. This includes log scaling,
limits and setting the labels to the correct latex representation.
Parameters:
Param_Dict: Parameter dictionary for dataset, axis and unit
axis: "X" or "Y" for the axis
axes: the axes instance to put the label on
"""
if Param_Dict[axis + "Log"]:
eval(f"axes.set_{axis.lower()}scale('log')")
field = Param_Dict[axis + "Axis"]
ds = Param_Dict["CurrentDataSet"] # is necessary for eval commands
unit = yt.YTQuantity(1, Param_Dict[axis + "Unit"]).units.latex_repr # get latex repr for unit
if unit != "": # do not add empty brackets
unit = r"$\:\left[" + unit + r"\right]$"
if field == "dens" or field == "temp":
name = eval(f"ds.fields.flash.{field}.get_latex_display_name()")
elif field == "time":
name = r"$\rm{Time}$"
else:
name = eval(f"ds.fields.gas.{field}.get_latex_display_name()")
eval(f"axes.set_{axis.lower()}label(name + unit)")
eval(f"axes.set_{axis.lower()}lim(Param_Dict[axis + 'Min'], Param_Dict[axis + 'Max'])")
def doit(field):
ds = yt.load(args.infile)
if not args.width:
width = max(ds.domain_width)
else:
width = yt.YTQuantity(args.width, 'cm')
maxv = ds.all_data().max(field)
minv = ds.all_data().min(field)
pos_maxv = np.ceil(np.log10(maxv))
neg_maxv = np.ceil(np.log10(minv))
logmaxv = max(pos_maxv, neg_maxv)
linminv = min(abs(maxv), abs(minv))
if args.octant:
dcenter = width.in_units('cm').v / 2.0
cpos = ds.arr([dcenter, dcenter, dcenter], 'cm')
s = yt.SlicePlot(ds,
'x',
field,
center=cpos,
width=width,
origin="native")
else:
s = yt.SlicePlot(ds, 'x', field, center='c', width=width)
s.annotate_scale()
if args.drawcells:
s.annotate_cell_edges()
if args.drawgrids:
s.annotate_grids()
s.set_buff_size(2048)
if minv < 0.0 and maxv > 0.0:
s.set_cmap(field, 'PiYG')
linthresh = 0.1
if ((args.logscale or args.symlog) and not args.sign
and not field == 'conv_type'):
if args.linthresh:
linthresh = args.linthresh
s.set_log(field, args.logscale, linthresh=linthresh)
else:
s.set_log(field, args.logscale)
if args.sign or field == 'conv_type':
s.set_zlim(field, -1.0, 1.0)
plot = s.plots[field]
colorbar = plot.cb
s._setup_plots()
if field != 'conv_type':
colorbar.set_ticks([-1, 0, 1])
colorbar.set_ticklabels(['$-1$', '$0$', '$+1$'])
else:
colorbar.set_ticks([-0.8, 0, 0.65])
colorbar.ax.tick_params(axis=u'both', which=u'both', length=0)
colorbar.ax.set_yticklabels(
['stable', 'semiconvective', 'convective'], rotation=90)
elif args.field_min and args.field_max:
s.set_zlim(field, args.field_min, args.field_max)
elif args.field_min and args.field_min < 0.0:
s.set_zlim(field, args.field_min, -args.field_min)
elif args.field_max and args.field_max > 0.0:
s.set_zlim(field, -args.field_max, args.field_max)
else:
s.set_zlim(field, -linthresh, linthresh)
else:
s.set_cmap(field, 'Greens')
s.save('{}.slice.{}.png'.format(args.infile, field))