mirror of
https://github.com/Findus23/halo_comparison.git
synced 2024-09-19 16:03:50 +02:00
139 lines
5.1 KiB
Python
139 lines
5.1 KiB
Python
from pathlib import Path
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from sys import argv
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from typing import List
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import h5py
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import numpy as np
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from matplotlib import pyplot as plt
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from matplotlib.axes import Axes
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from matplotlib.colors import LogNorm
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from matplotlib.figure import Figure
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from matplotlib.patches import Circle
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from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar
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from halo_vis import Coords
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from paths import base_dir, vis_datafile, has_1024_simulations
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from read_vr_files import read_velo_halos
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from utils import figsize_from_page_fraction, rowcolumn_labels, waveforms
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def coord_to_2d_extent(coords: Coords):
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radius, X, Y, Z = coords
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return X - radius, X + radius, Y - radius, Y + radius
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def in_area(coords: Coords, xobj, yobj, zobj, factor=1.3) -> bool:
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radius, xcenter, ycenter, zcenter = coords
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radius *= factor
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return (
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(xcenter - radius < xobj < xcenter + radius)
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and (ycenter - radius < yobj < ycenter + radius)
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and (zcenter - radius < zobj < zcenter + radius)
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)
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def main():
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offset = 2
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resolutions = [128, 256, 512]
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if argv[1] == "box":
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initial_halo_id = 0
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else:
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initial_halo_id = int(argv[1])
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is_box = not initial_halo_id
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if has_1024_simulations:
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resolutions.append(1024)
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fig: Figure = plt.figure(
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figsize=figsize_from_page_fraction(columns=2, height_to_width=1.05), layout="constrained"
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)
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axes: List[List[Axes]] = fig.subplots(
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len(waveforms), 4, sharex="row", sharey="row"
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)
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with h5py.File(vis_datafile) as vis_out:
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halo_group = vis_out[str(initial_halo_id)]
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vmin, vmax = halo_group["vmin_vmax"]
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print(vmin, vmax)
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for i, waveform in enumerate(waveforms):
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for j, resolution in enumerate(resolutions):
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dir = base_dir / f"{waveform}_{resolution}_100"
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halos = read_velo_halos(dir)
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ax = axes[i][j]
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dataset_group = halo_group[f"{waveform}_{resolution}"]
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rho = np.asarray(dataset_group["rho"])
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# radius, X, Y, Z
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coords: Coords = tuple(dataset_group["coords"])
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radius, X, Y, Z = coords
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mass = dataset_group["mass"][()] # get scalar value from Dataset
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main_halo_id = dataset_group["halo_id"][()] if initial_halo_id else None
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vmin_scaled = (vmin + offset) * mass
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vmax_scaled = (vmax + offset) * mass
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rho = (rho + offset) * mass
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extent = coord_to_2d_extent(coords)
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img = ax.imshow(
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rho.T.T,
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norm=LogNorm(vmin=vmin_scaled, vmax=vmax_scaled),
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extent=extent,
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origin="lower",
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cmap="Greys",
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interpolation="none"
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) # ax.set_axis_off()
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ax.set_xticks([])
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ax.set_yticks([])
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if j == 0:
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scalebar = AnchoredSizeBar(
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ax.transData,
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1,
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"1 Mpc",
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"lower left",
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# pad=0.1,
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color="black",
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frameon=False,
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# size_vertical=1
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)
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ax.add_artist(scalebar)
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if not is_box:
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found_main_halo = False
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for halo_id, halo in halos.iterrows():
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if halo["Vmax"] > 50:
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if in_area(coords, halo.X, halo.Y, halo.Z):
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if halo_id == main_halo_id:
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color = "C2"
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elif halo["Structuretype"] > 10:
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color = "C1"
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else:
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color = "C0"
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if halo_id == main_halo_id:
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found_main_halo = True
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print("plotting main halo")
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circle = Circle(
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(halo.Y - Y + X, halo.X - X + Y),
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halo["R_200crit"],
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zorder=10,
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linewidth=1,
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edgecolor=color,
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fill=None,
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alpha=0.2,
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)
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ax.add_artist(circle)
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assert found_main_halo
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print(img)
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# break
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# break
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ylabels = waveforms
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rowcolumn_labels(axes, ylabels, isrow=True)
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rowcolumn_labels(axes, resolutions, isrow=False)
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fig.tight_layout()
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fig.subplots_adjust(wspace=0, hspace=0)
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fig.savefig(Path(f"~/tmp/halo_plot_{initial_halo_id}.pdf").expanduser())
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fig.savefig(Path(f"~/tmp/halo_plot_{initial_halo_id}.png").expanduser(), dpi=300)
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plt.show()
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if __name__ == "__main__":
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main()
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