read rockstar output

rockstar.py

@@ -0,0 +1,66 @@
+from pathlib import Path
+
+import pandas as pd
+
+h = 0.6777
+
+
+def make_names_unique(names: list[str]) -> list[str]:
+    """
+    https://stackoverflow.com/a/30650847
+    """
+    newlist = []
+    for i, v in enumerate(names):
+        count = names[:i].count(v)
+        newlist.append(v + f"_{count + 1}" if count > 0 else v)
+    return newlist
+
+
+def largest_halo_properties(dir: Path):
+    file = dir / "halos_127.0.ascii"
+    if not file.exists():
+        file = dir / "halos_0.0.ascii"
+    with file.open() as f:
+        first_line = next(f)
+    headers = first_line.lstrip("#").strip().split()
+    headers = make_names_unique(headers)
+    df = pd.read_csv(file, sep=" ", names=headers, comment="#")
+    df.sort_values(by=["num_p"], inplace=True, ascending=False)
+    df.set_index("id", inplace=True)
+
+    df["r200c_kpc"] = df.r200c / h
+    df["m200c_msun"] = df.m200c / h / 1e10
+    df["m500c_msun"] = df.m500c / h / 1e10
+    df["m2500c_msun"] = df.m2500c / h / 1e10
+    df["mbound_200c_msun"] = df.mbound_200c / h / 1e10
+
+    df["Rs_kpc"] = df.Rs / h
+
+    df["con"] = df.r200c_kpc / df.Rs_kpc
+
+    main_halo = df.iloc[0]
+
+    print(file)
+    print(f"r200c_kpc: {main_halo.r200c_kpc:.1f}")
+    print(f"m200c_msun: {main_halo.m200c_msun:.2f}")
+    print(f"m500c_msun: {main_halo.m500c_msun:.2f}")
+    print(f"m2500c_msun: {main_halo.m2500c_msun:.2f}")
+    print(f"mbound_200c_msun: {main_halo.mbound_200c_msun:.2f}")
+    print(f"Rs_kpc: {main_halo.Rs_kpc:.2f}")
+    print(f"con: {main_halo.con:.3f}")
+    return main_halo
+
+
+if __name__ == '__main__':
+    data = {}
+    dir = Path("/home/lukas/cosmos_data/auriga-resim/data/auriga6/7_8_10")
+    data["7_8_10"] = largest_halo_properties(dir)
+    dir = Path("/home/lukas/cosmos_data/auriga-resim/data/auriga6/7_10_10")
+    data["7_10_10"] = largest_halo_properties(dir)
+    dir = Path("/home/lukas/cosmos_data/auriga-resim/data/auriga6/7_10_12")
+    data["7_10_12"] = largest_halo_properties(dir)
+    dir = Path("/home/lukas/cosmos_data/auriga-resim/data/auriga6/adrian_ref_new")
+    data["ref"] = largest_halo_properties(dir)
+    df = pd.DataFrame(data).T
+    print(df)
+    df.T.to_csv(Path("~/tmp/halo_comp.csv"))