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correct temperature calculation

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Lukas Winkler 2022-08-23 16:36:48 +02:00
parent d83da6d742
commit 5d7afeac68
Signed by: lukas
GPG key ID: 54DE4D798D244853
3 changed files with 63 additions and 14 deletions
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4
auriga_comparison.py
View file

@ -93,9 +93,9 @@ for dir in sorted(root_dir.glob("*")):
if levelmax != 11:
continue
input_file = dir / "output_0007.hdf5"
input_file = dir / "output_0009.hdf5"
if mode == Mode.richings:
input_file = dir / "output_0002.hdf5"
input_file = dir / "output_0004.hdf5"
if is_by_adrian or is_ramses:
input_file = dir / "output_0000.hdf5"
softening_length = None

25
fix_hdf5_masses.py
View file

@ -10,8 +10,6 @@ from utils import print_progress
gamma = 5 / 3
YHe = 0.245421
Tcmb0 = 2.7255
const_proton_mass_cgs = 1.67262192369e-24
const_boltzmann_k_cgs = 1.380649e-16
def calculate_gas_internal_energy(omegab, hubble_param_, zstart_):
@ -22,7 +20,7 @@ def calculate_gas_internal_energy(omegab, hubble_param_, zstart_):
npol = 1.0
unitv = 1e5
adec = 1.0 / (
160.0 * (omegab * hubble_param_ * hubble_param_ / 0.022) ** (2.0 / 5.0)
160.0 * (omegab * hubble_param_ * hubble_param_ / 0.022) ** (2.0 / 5.0)
)
if astart_ < adec:
Tini = Tcmb0 / astart_
@ -84,12 +82,24 @@ hydrogen_mass_function = 1 - const_primordial_He_fraction_cgs
mu_neutral = 4.0 / (1.0 + 3.0 * hydrogen_mass_function)
mu_ionised = 4.0 / (8.0 - 5.0 * (1.0 - hydrogen_mass_function))
T_transition = 1.0e4
UnitMass_in_cgs = 1.98848e43 # 10^10 M_sun in grams
UnitLength_in_cgs = 3.08567758e24 # 1 Mpc in centimeters
UnitVelocity_in_cgs = 1e5 # 1 km/s in centimeters per second
UnitTime_in_cgs = UnitLength_in_cgs / UnitVelocity_in_cgs
const_proton_mass_cgs = 1.67262192369e-24
const_boltzmann_k_cgs = 1.380649e-16
const_proton_mass = const_proton_mass_cgs / UnitMass_in_cgs
const_boltzmann_k = const_boltzmann_k_cgs / UnitMass_in_cgs / UnitLength_in_cgs ** 2 * (UnitTime_in_cgs ** 2)
print(const_proton_mass)
print(const_boltzmann_k)
print()
@njit
def calculate_T(u):
T_over_mu = (
hydro_gamma_minus_one * u * const_proton_mass_cgs / const_boltzmann_k_cgs
hydro_gamma_minus_one * u * const_proton_mass / const_boltzmann_k
)
if T_over_mu > (T_transition + 1) / mu_ionised:
return T_over_mu / mu_ionised
@ -118,4 +128,9 @@ def add_temperature_column():
if __name__ == "__main__":
# fix_initial_conditions()
add_temperature_column()
# add_temperature_column()
internal_energies = [6.3726251e+02, 7.7903375e+02, 1.7425287e+04, 6.4113910e+04, 3.8831848e+04,
1.1073163e+03, 7.7394878e+03, 7.5230023e+04, 9.1036992e+04, 2.4060946e+00]
for u in internal_energies:
print(calculate_T(u))

48
slices.py
View file

@ -1,3 +1,4 @@
import random
from pathlib import Path
from typing import List
@ -7,25 +8,55 @@ import numpy as np
from matplotlib.colors import LogNorm
from scipy.interpolate import griddata
from fix_hdf5_masses import calculate_T
from utils import create_figure
def create_2d_slice(
input_file: Path, center: List[float], property: str, axis="Z", thickness=3
input_file: Path, center: List[float], property: str, axis="Z", thickness=3, method="nearest"
):
axis_names = ["X", "Y", "Z"]
cut_axis = axis_names.index(axis)
limits = {
"X": (46, 52),
"Y": (54, 60),
"Z": (center[cut_axis] - 10, center[cut_axis] + 10)
}
with h5py.File(input_file) as f:
pt0 = f["PartType0"]
coords = pt0["Coordinates"]
data = pt0[property]
coords = pt0["Coordinates"][:]
energies = pt0["InternalEnergies"][:]
entropies = pt0["Entropies"][:]
print((center[cut_axis] - thickness < coords[::, cut_axis]).shape)
# in_slice = (center[cut_axis] - thickness < coords[::, cut_axis]) & (
# coords[::, cut_axis] < center[cut_axis] + thickness)
# print("got slice")
# coords_in_slice = coords[in_slice]
# data_in_slice = data[in_slice]
print("stats")
filter = (
(limits["X"][0] < coords[::, 0]) &
(coords[::, 0] < limits["X"][1]) &
(limits["Y"][0] < coords[::, 1]) &
(coords[::, 1] < limits["Y"][1]) &
(limits["Z"][0] < coords[::, 2]) &
(coords[::, 2] < limits["Z"][1])
)
print("before", coords.shape)
energies = energies[filter]
entropies = entropies[filter]
coords = coords[filter]
print("after", coords.shape)
print("calculating temperatures")
print(np.random.choice(energies,10))
temperatures = np.array([calculate_T(u) for u in energies])
print(temperatures.min(),temperatures.max(),temperatures.mean())
print("done")
exit()
other_axis = {"X": ("Y", "Z"), "Y": ("X", "Z"), "Z": ("X", "Y")}
x_axis_label, y_axis_label = other_axis[axis]
x_axis = axis_names.index(x_axis_label)
@ -34,7 +65,7 @@ def create_2d_slice(
yrange = np.linspace(coords[::, y_axis].min(), coords[::, y_axis].max(), 1000)
gx, gy, gz = np.meshgrid(xrange, yrange, center[cut_axis])
print("interpolating")
grid = griddata(coords, data, (gx, gy, gz), method="linear")[::, ::, 0]
grid = griddata(coords, temperatures, (gx, gy, gz), method=method)[::, ::, 0]
print(grid.shape)
# stats, x_edge, y_edge, _ = binned_statistic_2d(
# coords_in_slice[::, x_axis],
@ -47,15 +78,18 @@ def create_2d_slice(
# stats = np.nan_to_num(stats)
print("plotting")
img = ax.imshow(
grid.T,
grid,
norm=LogNorm(),
interpolation="nearest",
origin="lower",
extent=[xrange[0], xrange[-1], yrange[0], yrange[-1]],
)
ax.set_title(input_file.parent.stem)
ax.set_xlabel(x_axis_label)
ax.set_ylabel(y_axis_label)
fig.colorbar(img, label=property)
ax.set_aspect("equal")
fig.colorbar(img, label="Temperatures")
fig.tight_layout()
fig.savefig(Path("~/tmp/slice.png").expanduser(), dpi=300)
plt.show()
exit()