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https://github.com/Findus23/halo_comparison.git
synced 2024-09-18 14:53:49 +02:00
fix HMF
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parent
910a73498f
commit
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GPG key ID:
54DE4D798D244853
3 changed files with 72 additions and 28 deletions
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@ -10,6 +10,7 @@ from matplotlib.figure import Figure
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from paths import base_dir, has_1024_simulations
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from read_vr_files import read_velo_halos
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from readfiles import read_gadget_halos
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from utils import print_progress, figsize_from_page_fraction
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@ -46,17 +47,26 @@ def monofonic_tests():
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print(cosmology.getCurrent())
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x = None
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for i, waveform in enumerate(
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["DB2", "shannon", "shannon_rehalo", "resim_master", "resim_newrandom", "resim_newerrandom",
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"resim_newswift"]):
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[
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"DB2", "shannon", "shannon_rehalo",
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# "resim_master", "resim_newrandom", "resim_newerrandom",
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# "resim_newswift",
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"resim_mastergadget"
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]):
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for j, resolution in enumerate(resolutions):
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if (waveform == "shannon_rehalo" or "resim" in waveform) and resolution != 128:
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continue
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print(waveform, resolution)
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dir = base_dir / f"{waveform}_{resolution}_100"
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halos = read_velo_halos(dir)
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halo_masses: np.ndarray = halos["Mvir"].to_numpy() * 1e10 * 0.67742
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if "gadget" in waveform:
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halos = read_gadget_halos(dir)
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halo_masses: np.ndarray = halos["Masses"].to_numpy() * 1e10
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else:
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halos = read_velo_halos(dir)
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halo_masses: np.ndarray = halos["Mvir"].to_numpy() * 1e10 * 0.67742
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# halo_masses = halo_masses[halo_masses > 0]
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halo_masses.sort()
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print(halo_masses[-4:])
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# halos = read_halo_file(dir/"fof_output_0004.hdf5")
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# halo_masses: np.ndarray = halos["Masses"].to_numpy() * 1e10 * 0.67742
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@ -68,7 +78,7 @@ def monofonic_tests():
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number_densities,
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lower_error_limit,
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upper_error_limit,
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) = halo_mass_function(halo_masses)
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) = halo_mass_function(halo_masses, sim_volume=(100 * 0.67742) ** 3)
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ax.set_xscale("log")
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ax.set_yscale("log")
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@ -79,11 +89,12 @@ def monofonic_tests():
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name = f"{waveform} {resolution}"
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ax.step(
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left_edges,
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number_densities / (0.67742 ** 3),
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number_densities,
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where="post",
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color=f"C{i + 1}",
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linestyle=linestyles[j],
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label=name,
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zorder=10
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)
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# ax.fill_between(
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@ -99,12 +110,31 @@ def monofonic_tests():
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# break
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mfunc = mass_function.massFunction(
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x, 1, mdef="vir", model="tinker08", q_out="dndlnM"
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x, z=0, mdef="vir", model="tinker08", q_out="dndlnM"
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)
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ax.plot(x, mfunc, label="tinker08 (vir)", color="C0")
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ax.set_xlabel("M")
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ax.set_ylabel("dndlnM")
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ax.set_xlabel("Mass ($h^{-1} M_{\odot}$)")
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ax.set_ylabel(r"$\frac{dN}{d\log M}$ ($h^{3}Mpc^{-3}$)")
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# s: GadgetHDFSnap = pynbody.load(str(base_dir / "resim_mastergadget_128_100" / "output" / "snapshot_019.hdf5"))
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# s.physical_units()
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# h3 = s.properties["h"] ** 3
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# bin_center, bin_counts, err = pynbody.analysis.hmf.simulation_halo_mass_function(
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# s, log_M_min=10, log_M_max=15, delta_log_M=0.1
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# )
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# ax.errorbar(
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# bin_center, bin_counts * h3,
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# yerr=err,
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# fmt='o',
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# capthick=2,
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# elinewidth=2,
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# color='darkgoldenrod'
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# )
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# m, sig, dn_dlogm = pynbody.analysis.hmf.halo_mass_function(
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# s, log_M_min=10, log_M_max=15, delta_log_M=0.1, kern="ST"
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# )
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# ax.plot(m, dn_dlogm, color='darkmagenta', linewidth=2)
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ax.legend()
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fig.tight_layout()
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@ -202,7 +232,7 @@ def hmf_from_rockstar_tree(file: Path):
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cosmology.setCosmology("aurigaCosmo")
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print(cosmology.getCurrent())
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mfunc = mass_function.massFunction(
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left_edges, 1, mdef="vir", model="tinker08", q_out="dndlnM"
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left_edges, z=0, mdef="vir", model="tinker08", q_out="dndlnM"
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)
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ax.plot(left_edges, mfunc)
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40
hmf_test.py
40
hmf_test.py
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@ -1,28 +1,34 @@
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import matplotlib.pyplot as plt
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from velociraptor import load, tools
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import read_vr_files
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from paths import base_dir
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from read_vr_files import read_velo_halos
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from unyt import Mpc
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import unyt
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for i, waveform in enumerate(["DB2", "DB4", "DB8", "shannon"]):
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for i, waveform in enumerate(
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["DB2", "DB8", "shannon"]):
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for j, resolution in enumerate([128, 256, 512]):
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if (waveform == "shannon_rehalo" or "resim" in waveform) and resolution != 128:
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continue
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print(waveform, resolution)
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dir = base_dir / f"{waveform}_{resolution}_100"
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data = load(str(dir)+"/vroutput.properties.0")
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print(data)
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masses_200crit = data.masses.mass_200crit
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masses_200crit.convert_to_units("msun")
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lowest_halo_mass = 1e9 * unyt.msun
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highest_halo_mass = 8e15 * unyt.msun
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bin_centers, mass_function, error = tools.create_mass_function(
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masses_200crit, lowest_halo_mass, highest_halo_mass, (100*Mpc)**3
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)
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plt.loglog(bin_centers,mass_function)
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# halos = read_velo_halos(dir)
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# data = load(str(dir) + "/vroutput.properties.0")
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# print(data)
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# masses_200crit = data.masses.mass_200crit
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# masses_200crit.convert_to_units("msun")
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# lowest_halo_mass = 1e9 * unyt.msun
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# highest_halo_mass = 8e15 * unyt.msun
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# bin_centers, mass_function, error = tools.create_mass_function(
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# masses_200crit, lowest_halo_mass, highest_halo_mass, (100 * Mpc) ** 3
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# )
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#
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# print(halos["Rvir"].sort_values(ascending=False)[:4].to_numpy())
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# name = f"{waveform} {resolution}"
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# plt.loglog(bin_centers, mass_function, label=name)
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# halos = read_halo_file(dir/"fof_output_0004.hdf5")
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#
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# print(halos["Masses"].sort_values(ascending=False)[:4].to_numpy())
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halos = read_vr_files.read_velo_halos(dir)
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print(halos["R_200mean"].sort_values(ascending=False)[:4].to_numpy())
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plt.legend()
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plt.show()
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@ -75,6 +75,14 @@ def read_halo_file(file: Path) -> DataFrame:
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return df
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def read_gadget_halos(directory: Path):
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reference_file = h5py.File(directory / "output" / "fof_subhalo_tab_019.hdf5")
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df1 = pd.DataFrame(reference_file["Subhalo"]["SubhaloPos"], columns=["X", "Y", "Z"])
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df2 = pd.DataFrame(reference_file["Subhalo"]["SubhaloMass"], columns=["Masses"])
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df = df1.merge(df2, "outer", left_index=True, right_index=True)
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return df
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def read_fof_file(path: Path):
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file = path / ""
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