From 1af06dcd2ca3ba8b68f28f0b27ece893747ed4d9 Mon Sep 17 00:00:00 2001 From: Lukas Winkler Date: Wed, 24 Aug 2022 23:42:10 +0200 Subject: [PATCH] pbh and more comparisons --- auriga_comparison.py | 22 +-- find_center.py | 10 +- halo_mass_profile.py | 1 - pbh_comparison.py | 66 +++++++++ poetry.lock | 327 ++++++++++++++++++++++++++++++++++++++----- readfiles.py | 49 ++++--- 6 files changed, 406 insertions(+), 69 deletions(-) create mode 100644 pbh_comparison.py diff --git a/auriga_comparison.py b/auriga_comparison.py index 99127f9..4eaf3e4 100644 --- a/auriga_comparison.py +++ b/auriga_comparison.py @@ -15,6 +15,7 @@ from matplotlib.figure import Figure from cache import HDFCache from cic import cic_from_radius, cic_range +from find_center import find_center from halo_mass_profile import halo_mass_profile from nfw import fit_nfw from paths import auriga_dir, richings_dir @@ -55,7 +56,8 @@ def main(): ax1: Axes = fig1.gca() fig2: Figure = plt.figure(figsize=figsize_from_page_fraction()) ax2: Axes = fig2.gca() - + fig4, axs_baryon = plt.subplots(nrows=3, ncols=5, sharex="all", sharey="all", figsize=(10, 4)) + baryon_plot_counter = 0 for ax in [ax1, ax2]: ax.set_xlabel(r"R [Mpc]") ax1.set_ylabel(r"M [$10^{10} \mathrm{M}_\odot$]") @@ -92,7 +94,7 @@ def main(): print(levelmin, levelmin_TF, levelmax) if not has_baryons: continue - if levelmax != 11: + if is_ramses: continue input_file = dir / "output_0009.hdf5" @@ -150,6 +152,7 @@ def main(): part_numbers.append(len(df) * particles_meta.particle_mass) # halo = halos.loc[1] center = np.array([halo.X, halo.Y, halo.Z]) + center = find_center(df, center) log_radial_bins, bin_masses, bin_densities, center = halo_mass_profile( df, center, particles_meta, plot=False, num_bins=100, vmin=0.002, vmax=6.5 ) @@ -231,13 +234,12 @@ def main(): if has_baryons: interpolation_method = "nearest" # "linear" - fig3, axs_baryon = plt.subplots(nrows=1, ncols=5, sharex="all", sharey="all", figsize=(10, 4)) extent = [46, 52, 54, 60] # xrange[0], xrange[-1], yrange[0], yrange[-1] extent = [42, 62, 50, 70] for ii, property in enumerate(["cic", "Densities", "Entropies", "InternalEnergies", "Temperatures"]): key = f"grid_{property}_{interpolation_method}" cached_grid = cache.get(key, str(input_file)) - if cached_grid is not None and False: + if cached_grid is not None: grid = cached_grid else: if property == "cic": @@ -247,7 +249,7 @@ def main(): grid = create_2d_slice(input_file, center, property=property, extent=extent, method=interpolation_method) cache.set(key, grid, str(input_file), compressed=True) - ax_baryon: Axes = axs_baryon[ii] + ax_baryon: Axes = axs_baryon[baryon_plot_counter, ii] img = ax_baryon.imshow( grid, norm=LogNorm(), @@ -259,11 +261,8 @@ def main(): # ax_baryon.set_xlabel("X") # ax_baryon.set_ylabel("Y") ax_baryon.set_aspect("equal") - fig3.suptitle(input_file.parent.stem) - fig3.tight_layout() - fig3.savefig(Path("~/tmp/slice.png").expanduser(), dpi=300) # exit() - plt.show() + baryon_plot_counter += 1 # plot_cic( # rho, extent, @@ -298,9 +297,14 @@ def main(): cbar_ax = fig3.add_axes([0.85, 0.05, 0.05, 0.9]) fig3.colorbar(img, cax=cbar_ax) + fig1.savefig(Path(f"~/tmp/auriga1.pdf").expanduser()) fig2.savefig(Path(f"~/tmp/auriga2.pdf").expanduser()) fig3.savefig(Path("~/tmp/auriga3.pdf").expanduser()) + + fig4.tight_layout() + fig4.savefig(Path("~/tmp/slice.png").expanduser(), dpi=300) + pprint(centers) plt.show() print(part_numbers) diff --git a/find_center.py b/find_center.py index 605ecb6..fcbd26a 100644 --- a/find_center.py +++ b/find_center.py @@ -11,9 +11,13 @@ cache = HDFCache(Path("center_cache.hdf5")) def find_center(df: pd.DataFrame, center: np.ndarray, initial_radius=1): - plt.figure() + # plt.figure() all_particles = df[["X", "Y", "Z"]].to_numpy() - hash = hashlib.sha256(np.ascontiguousarray(all_particles).data).hexdigest() + hashdata = hashlib.sha256() + hashdata.update(np.ascontiguousarray(all_particles).data) + hashdata.update(np.ascontiguousarray(center).data) + hashdata.update(np.array(initial_radius)) + hash = hashdata.hexdigest() cached_center = cache.get(hash) if cached_center is not None: return np.array(cached_center) @@ -31,7 +35,7 @@ def find_center(df: pd.DataFrame, center: np.ndarray, initial_radius=1): center_of_mass = in_radius_particles.mean(axis=0) new_center = (center_of_mass + center) / 2 shift = np.linalg.norm(center - new_center) - radius = max(2 * shift, radius * 0.9) + radius = max(0.8 * shift, radius * 0.9) center = new_center i += 1 center_history = np.array(center_history) diff --git a/halo_mass_profile.py b/halo_mass_profile.py index ed2c91a..786bfc2 100644 --- a/halo_mass_profile.py +++ b/halo_mass_profile.py @@ -24,7 +24,6 @@ def halo_mass_profile( plot=False, num_bins=30, ): - center = find_center(particles, center) positions = particles[["X", "Y", "Z"]].to_numpy() distances = np.linalg.norm(positions - center, axis=1) group_radius = distances.max() diff --git a/pbh_comparison.py b/pbh_comparison.py new file mode 100644 index 0000000..e198830 --- /dev/null +++ b/pbh_comparison.py @@ -0,0 +1,66 @@ +import numpy as np +import pandas as pd +from matplotlib import pyplot as plt +from matplotlib.axes import Axes +from matplotlib.figure import Figure + +from cic import cic_from_radius, plot_cic +from find_center import find_center +from halo_mass_profile import halo_mass_profile +from paths import pbh_dir +from readfiles import read_g4_file, ParticlesMeta +from utils import figsize_from_page_fraction + + +def cic_comparison(pbh_high_coord, ref_high_coord,center): + rhos = [] + i = 0 + for coord in [ref_high_coord, pbh_high_coord]: + rho, extent = cic_from_radius( + coord[::, 0], coord[::, 2], 3000, center[0], center[2], .2, periodic=False + ) + rhos.append(rho) + + plot_cic( + rho, extent, title=f"test{i}" + ) + i += 1 + plot_cic( + np.absolute(rhos[0] - rhos[1]), extent, title="abs(diff)" + ) + + +def main(): + ref_data = read_g4_file( + pbh_dir / "CDM-L50-N128" / "snapshot_039.hdf5", + zoom_type="cdm") + pbh_data = read_g4_file( + pbh_dir / "DM-L50-N128" / "snapshot_039.hdf5", + zoom_type="pbh") + fig1: Figure = plt.figure(figsize=figsize_from_page_fraction()) + ax1: Axes = fig1.gca() + fig2: Figure = plt.figure(figsize=figsize_from_page_fraction()) + ax2: Axes = fig2.gca() + center = [32.423177, 37.255220, 36.026005] + centered = False + for data in [ref_data, pbh_data]: + highres_coords, lowres_coords, highres_mass, lowres_mass = data + df = pd.DataFrame(highres_coords, columns=["X", "Y", "Z"]) + particles_meta = ParticlesMeta(particle_mass=highres_mass) + # center = np.median(highres_coords, axis=0) + print(center) + # if not centered: + # center = find_center(df, center, initial_radius=0.01) + centered = True + log_radial_bins, bin_masses, bin_densities, center = halo_mass_profile( + df, center, particles_meta, plot=False, num_bins=100, vmin=0.002, vmax=5 + ) + ax1.loglog(log_radial_bins[:-1], bin_masses) + + ax2.loglog(log_radial_bins[:-1], bin_densities) + plt.show() + cic_comparison(ref_data[0], pbh_data[0],center) + + +if __name__ == '__main__': + main() diff --git a/poetry.lock b/poetry.lock index d465a4e..59a4090 100644 --- a/poetry.lock +++ b/poetry.lock @@ -27,7 +27,7 @@ python-versions = ">=3.6" [[package]] name = "cython" -version = "0.29.30" +version = "0.29.32" description = "The Cython compiler for writing C extensions for the Python language." category = "main" optional = false @@ -35,7 +35,7 @@ python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" [[package]] name = "fonttools" -version = "4.33.3" +version = "4.36.0" description = "Tools to manipulate font files" category = "main" optional = false @@ -76,7 +76,7 @@ numpy = ">=1.14.5" [[package]] name = "imageio" -version = "2.19.3" +version = "2.21.1" description = "Library for reading and writing a wide range of image, video, scientific, and volumetric data formats." category = "main" optional = false @@ -105,7 +105,7 @@ tifffile = ["tifffile"] [[package]] name = "kiwisolver" -version = "1.4.3" +version = "1.4.4" description = "A fast implementation of the Cassowary constraint solver" category = "main" optional = false @@ -121,7 +121,7 @@ python-versions = ">=3.7,<3.11" [[package]] name = "matplotlib" -version = "3.5.2" +version = "3.5.3" description = "Python plotting package" category = "main" optional = false @@ -136,7 +136,7 @@ packaging = ">=20.0" pillow = ">=6.2.0" pyparsing = ">=2.2.1" python-dateutil = ">=2.7" -setuptools_scm = ">=4" +setuptools_scm = ">=4,<7" [[package]] name = "numba" @@ -153,11 +153,11 @@ setuptools = "*" [[package]] name = "numexpr" -version = "2.8.1" +version = "2.8.3" description = "Fast numerical expression evaluator for NumPy" category = "main" optional = false -python-versions = "*" +python-versions = ">=3.7" [package.dependencies] numpy = ">=1.13.3" @@ -184,7 +184,7 @@ pyparsing = ">=2.0.2,<3.0.5 || >3.0.5" [[package]] name = "pandas" -version = "1.4.2" +version = "1.4.3" description = "Powerful data 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ParticlesMeta]: reference_file = h5py.File(file) has_fof = "FOFGroupIDs" in reference_file["PartType1"] - masses = reference_file["PartType1"]["Masses"] - if not np.all(masses == masses[0]): - raise ValueError("only equal mass particles are supported for now") + try: + masses = reference_file["PartType1"]["Masses"] + if not np.all(masses == masses[0]): + raise ValueError("only equal mass particles are supported for now") + meta = ParticlesMeta(particle_mass=masses[0]) + + except KeyError: + meta = ParticlesMeta(particle_mass=0) df = pd.DataFrame( reference_file["PartType1"]["Coordinates"], columns=["X", "Y", "Z"] ) @@ -43,7 +48,6 @@ def read_file(file: Path) -> Tuple[pd.DataFrame, ParticlesMeta]: if has_fof: print("sorting") df.sort_values("FOFGroupIDs", inplace=True) - meta = ParticlesMeta(particle_mass=masses[0]) print("saving cache") with meta_cache_file.open("wb") as f: pickle.dump(meta, f) @@ -74,23 +78,28 @@ def read_halo_file(file: Path) -> DataFrame: def read_fof_file(path: Path): file = path / "" -def read_g4_file(file: Path, zoom_type: str) -> Tuple[np.ndarray, np.ndarray]: - reference_file = h5py.File(file) - hubble_param = reference_file["Parameters"].attrs["HubbleParam"] - if zoom_type == 'pbh': - highres_parttype = 'PartType0' - lowres_parttype = 'PartType1' - elif zoom_type == 'cdm': - highres_parttype = 'PartType1' - lowres_parttype = 'PartType2' - highres_mass = reference_file['Header'].attrs['MassTable'][1] / hubble_param - else: - raise ValueError('Please select pbh or cdm as zoom_type!') +def read_g4_file(file: Path, zoom_type: str) -> Tuple[np.ndarray, np.ndarray, float, float]: + with h5py.File(file) as reference_file: - highres_coordinates = reference_file[highres_parttype]["Coordinates"][:] #all coordinates in Mpc/h without adaption! - lowres_coordinates = reference_file[lowres_parttype]["Coordinates"][:] + hubble_param = reference_file["Parameters"].attrs["HubbleParam"] + masstable = reference_file['Header'].attrs['MassTable'] + if zoom_type == 'pbh': + highres_parttype = 'PartType0' + lowres_parttype = 'PartType1' + highres_mass = masstable[0] / hubble_param + lowres_mass = masstable[1] / hubble_param - reference_file.close() + elif zoom_type == 'cdm': + highres_parttype = 'PartType1' + lowres_parttype = 'PartType2' + highres_mass = masstable[1] / hubble_param + lowres_mass = masstable[2] / hubble_param + else: + raise ValueError('Please select pbh or cdm as zoom_type!') - return highres_coordinates, lowres_coordinates + # all coordinates in Mpc/h without adaption! + highres_coordinates = reference_file[highres_parttype]["Coordinates"][:] + lowres_coordinates = reference_file[lowres_parttype]["Coordinates"][:] + + return highres_coordinates, lowres_coordinates, highres_mass, lowres_mass