mirror of
https://github.com/Findus23/halo_comparison.git
synced 2024-09-19 16:03:50 +02:00
63 lines
1.4 KiB
Python
63 lines
1.4 KiB
Python
from pathlib import Path
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from sys import argv
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import numpy as np
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import pandas as pd
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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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file = Path(argv[1])
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df = pd.read_csv(file)
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# df = df.iloc
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fig: Figure = plt.figure()
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ax: Axes = fig.gca()
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# hist2d, log?
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matches:pd.DataFrame=df["match"]
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# print(matches)
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# exit()
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print(matches.median())
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print(matches.std())
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exit()
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# x_col = "ref_cNFW"
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# y_col = "comp_cNFW"
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#
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x_col = "ref_Mvir"
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y_col = "comp_Mvir"
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min_x = min([min(df[x_col]), min(df[y_col])])
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max_x = max([max(df[x_col]), max(df[y_col])])
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bins = np.geomspace(min_x, max_x, 100)
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# ax.scatter(df["ref_sizes"], df["comp_sizes"], s=1, alpha=.3)
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# ax.scatter(df[x_col], df[y_col], s=1, alpha=.3)
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_, _, _, hist = ax.hist2d(df[x_col], df[y_col], bins=(bins, bins), norm=LogNorm())
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# ax.set_xscale("log")
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ax.set_xlabel(x_col)
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ax.set_ylabel(y_col)
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# ax.set_yscale("log")
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fig.colorbar(hist)
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ax.loglog([min_x, max_x], [min_x, max_x], linewidth=1, color="C2")
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fig2: Figure = plt.figure()
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ax2: Axes = fig2.gca()
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ax2.hist(df["distance"][df["distance"] < 50], bins=100)
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ax2.set_xlabel("distance/R_vir_ref")
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for a in [ax, ax2]:
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a.set_title(file.name)
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fig.savefig(Path(f"~/tmp/comparison_{file.stem}.pdf").expanduser())
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fig2.savefig(Path(f"~/tmp/distances_{file.stem}.pdf").expanduser())
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fig.suptitle
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plt.show()
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