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99 lines
3.6 KiB
Python
99 lines
3.6 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Created on Tue Mar 8 11:16:06 2022
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@author: ben
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"""
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import h5py
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from pathlib import Path
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import numpy as np
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directory = Path(r"/home/ben/sims/swiftsim/examples/agora/")
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# directory = Path(r"/home/ben/Pictures/Gadget4/vsc4_256/")
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# directory = Path(r'/home/ben/sims/music-panphasia/test/')
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# ics = h5py.File(directory / "agora_128.hdf5", "r")
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file = h5py.File(directory / "output_0001.hdf5", "r")
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# file_2 = h5py.File(directory / 'output_0001.hdf5', 'r')
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# file = h5py.File(directory / "cosmo_ics_gadget_256_pbh_vsc.hdf5", "r")
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# for key in file.keys():
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# print(key) #for finding all header entries, which are:
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Header = file["Header"]
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#ICs_parameters = file["ICs_parameters"]
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PartType1 = file["PartType1"]
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Units = file["Units"]
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# PartType2 = file['PartType2']
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# print(list(Header.attrs.items()))
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# print(list(ics['Header'].attrs.items()))
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print(Header.attrs['Scale-factor'])
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# print(PartType1.keys())
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# # print(PartType2.keys())
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# print(PartType1['Masses'][0:10])
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# print(PartType1['Velocities'][0:10])
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# ic_ids = ics['PartType1']['ParticleIDs'][:]
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# ic_velocities = ics['PartType1']['Velocities'][:]
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# ic_absolute_vel = np.sqrt(np.sum(ic_velocities ** 2, axis=1))
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# ic_data = np.vstack([ic_ids, ic_absolute_vel]).T
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# ic_positions = ics['PartType1']['Coordinates'][:]
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# ic_distances = np.sqrt(np.sum(ic_positions ** 2, axis=1))
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# ic_data = np.vstack([ic_ids, ic_distances]).T
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# snap_ids = PartType1['ParticleIDs'][:]
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# snap_velocities = PartType1['Velocities'][:]
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# snap_absolute_vel = np.sqrt(np.sum(snap_velocities ** 2, axis=1))
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# snap_data = np.vstack([snap_ids, snap_absolute_vel]).T
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# snap_data_sorted = snap_data[snap_data[:, 0].argsort()]
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# snap_positions = PartType1['Coordinates'][:]
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# snap_distances = np.sqrt(np.sum(snap_positions ** 2, axis=1))
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# snap_data = np.vstack([snap_ids, snap_distances]).T
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# snap_data_sorted = snap_data[snap_data[:, 0].argsort()]
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# snap_2_ids = file_2['PartType1']['ParticleIDs'][:]
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# snap_2_velocities = file_2['PartType1']['Velocities'][:]
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# snap_2_absolute_vel = np.sqrt(np.sum(snap_2_velocities ** 2, axis=1))
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# snap_2_data = np.vstack([snap_2_ids, snap_2_absolute_vel]).T
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# snap_2_data_sorted = snap_2_data[snap_2_data[:, 0].argsort()]
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# snap_2_positions = file_2['PartType1']['Coordinates'][:]
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# snap_2_distances = np.sqrt(np.sum(snap_2_positions ** 2, axis=1))
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# snap_2_data = np.vstack([snap_2_ids, snap_2_distances]).T
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# snap_2_data_sorted = snap_2_data[snap_2_data[:, 0].argsort()]
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# velocity_difference = np.abs(ic_data[:, 1] - snap_data_sorted[:, 1])
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# mean_velocity_difference = np.mean(velocity_difference)
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# velocity_difference_2 = np.abs(snap_data_sorted[:, 1] - snap_2_data_sorted[:, 1])
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# mean_2_velocity_difference = np.mean(velocity_difference_2)
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# print(mean_velocity_difference, mean_2_velocity_difference)
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# print(np.min(velocity_difference), np.max(velocity_difference))
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# print(np.min(velocity_difference_2), np.max(velocity_difference_2))
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# distance_difference = np.abs(ic_data[:, 1] - snap_data_sorted[:, 1])
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# mean_distance_difference = np.mean(distance_difference)
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# distance_difference_2 = np.abs(snap_data_sorted[:, 1] - snap_2_data_sorted[:, 1])
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# mean_2_distance_difference = np.mean(distance_difference_2)
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# print(mean_distance_difference, mean_2_distance_difference)
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# print(np.min(ic_distances), np.max(ic_distances))
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# print(np.min(snap_distances), np.max(snap_distances))
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# print(PartType2['Masses'][0:10])
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# print(list(Units.attrs.items()))
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# use list(Header.attr.keys()) to list all attributes contained in the Header and .attr.values() to see their values
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# even otherwise empty things like ICs_parameters can contain such attributes
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