2022-06-01 15:09:40 +02:00
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import sys
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from pathlib import Path
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2022-05-05 10:40:25 +02:00
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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from matplotlib.axes import Axes
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from matplotlib.figure import Figure
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2022-06-01 15:09:40 +02:00
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from readfiles import ParticlesMeta, read_file, read_halo_file
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2022-05-05 11:10:07 +02:00
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2022-05-05 10:40:25 +02:00
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def V(r):
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return 4 * np.pi * r ** 3 / 3
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2022-05-05 11:12:37 +02:00
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def cumulative_mass_profile(particles_in_halos: pd.DataFrame, halo: pd.Series,
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particles_meta: ParticlesMeta, plot=False):
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2022-05-05 10:40:25 +02:00
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print(type(particles_in_halos))
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centre = np.array([halo.X, halo.Y, halo.Z])
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positions = particles_in_halos[["X", "Y", "Z"]].to_numpy()
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print(positions)
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print(positions.shape)
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distances = np.linalg.norm(positions - centre, axis=1)
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group_radius = distances.max()
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normalized_distances = distances / group_radius
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2022-06-02 00:12:44 +02:00
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num_bins = 100
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2022-05-05 10:40:25 +02:00
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log_radial_bins = np.geomspace(0.01, 2, num_bins)
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2022-05-05 11:10:07 +02:00
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bin_masses = []
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2022-05-05 10:40:25 +02:00
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bin_densities = []
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for k in range(num_bins - 1):
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bin_start = log_radial_bins[k]
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bin_end = log_radial_bins[k + 1]
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in_bin = np.where((bin_start < normalized_distances) & (normalized_distances < bin_end))[0]
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count = in_bin.shape[0]
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2022-05-05 11:10:07 +02:00
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mass = count * particles_meta.particle_mass
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2022-05-05 10:40:25 +02:00
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volume = V(bin_end * group_radius) - V(bin_start * group_radius)
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2022-05-05 11:10:07 +02:00
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bin_masses.append(mass)
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2022-06-02 00:12:44 +02:00
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density = mass / volume
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2022-05-05 10:40:25 +02:00
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bin_densities.append(density)
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2022-05-05 11:10:07 +02:00
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print(bin_masses)
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2022-05-05 10:40:25 +02:00
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print(bin_densities)
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2022-05-05 11:12:37 +02:00
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if plot:
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fig: Figure = plt.figure()
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ax: Axes = fig.gca()
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2022-05-05 10:40:25 +02:00
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2022-05-05 11:12:37 +02:00
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ax2 = ax.twinx()
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2022-05-05 10:40:25 +02:00
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2022-05-05 11:12:37 +02:00
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ax.loglog(log_radial_bins[:-1], bin_masses, label="counts")
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ax2.loglog(log_radial_bins[:-1], bin_densities, label="densities", c="C1")
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ax.set_xlabel(r'R / R$_\mathrm{group}$')
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ax.set_ylabel(r'M [$10^{10} \mathrm{M}_\odot$]')
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2022-06-06 23:29:44 +02:00
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ax2.set_ylabel("density [$\\frac{10^{10} \\mathrm{M}_\\odot}{Mpc^3}$]")
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2022-06-02 00:12:44 +02:00
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plt.legend()
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2022-05-05 11:12:37 +02:00
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plt.show()
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2022-05-05 10:40:25 +02:00
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2022-05-05 11:10:07 +02:00
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return bin_masses, bin_densities
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2022-06-01 15:09:40 +02:00
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if __name__ == '__main__':
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2022-06-02 11:15:18 +02:00
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input_file = Path(sys.argv[1])
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df, particles_meta = read_file(input_file)
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df_halos = read_halo_file(input_file)
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2022-06-01 15:09:40 +02:00
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halo_id = 1
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particles_in_halo = df.loc[df["FOFGroupIDs"] == halo_id]
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halo = df_halos.loc[halo_id]
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cumulative_mass_profile(particles_in_halo, halo, particles_meta, plot=True)
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