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turbox

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This commit is contained in:
Noe Brucy
2024-01-24 18:34:33 +01:00
parent a1e4f775b6
commit 006cbca80f
1 changed files with 9 additions and 5 deletions
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turbox/turbox.py
+9 -5
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@@ -110,8 +110,12 @@ def build_turbox_data(pl, redo=False, cs0=0.28834810480560674):
df = {} df = {}
df["snapshots"] = pl.nums.values() df["snapshots"] = pl.nums.values()
df["n0"] = pl.study.get_nml("galbox_params/dens0").values() try:
df["turbinit"] = pl.study.get_nml("galbox_params/turb").values() df["n0"] = pl.study.get_nml("galbox_params/dens0").values()
df["turbinit"] = pl.study.get_nml("galbox_params/turb").values()
except KeyError:
df["n0"] = pl.study.get_nml("init_params/d_region").values()
df["turbinit"] = 0
df["solver"] = pl.study.get_nml("hydro_params/riemann").values() df["solver"] = pl.study.get_nml("hydro_params/riemann").values()
df["slope"] = pl.study.get_nml("hydro_params/slope_type").values() df["slope"] = pl.study.get_nml("hydro_params/slope_type").values()
df["res"] = pl.study.get_nml("amr_params/levelmin").values() df["res"] = pl.study.get_nml("amr_params/levelmin").values()
@@ -131,7 +135,7 @@ def build_turbox_data(pl, redo=False, cs0=0.28834810480560674):
pl.study.avg_time_sigma("y", overwrite_dep=False) pl.study.avg_time_sigma("y", overwrite_dep=False)
pl.study.avg_time_sigma("z", overwrite_dep=False) pl.study.avg_time_sigma("z", overwrite_dep=False)
pl.study.time(overwrite=True) pl.study.time(overwrite=True)
df["time"] = np.empty(len(pl.runs), dtype=list) df["time"] = np.empty(len(pl.runs), dtype=list)
time = pl.study.get_value("/series/time", unit=U.Myr) time = pl.study.get_value("/series/time", unit=U.Myr)
for run in pl.runs: for run in pl.runs:
@@ -145,10 +149,10 @@ def build_turbox_data(pl, redo=False, cs0=0.28834810480560674):
for run in sigma_ax: for run in sigma_ax:
sigma_ax[run] = sigma_ax[run].T[0] sigma_ax[run] = sigma_ax[run].T[0]
sigma1d.append(sigma_ax) sigma1d.append(sigma_ax)
sigma3d = {} sigma3d = {}
for run in pl.runs: for run in pl.runs:
sigma3d[run] = np.sum([sigma1d_i[run]**2 for sigma1d_i in sigma1d], axis=0) sigma3d[run] = np.sum([sigma1d_i[run] ** 2 for sigma1d_i in sigma1d], axis=0)
sigma3d[run] = list(map(np.sqrt, sigma3d[run])) sigma3d[run] = list(map(np.sqrt, sigma3d[run]))
df["sigma"] = np.zeros(len(pl.runs)) df["sigma"] = np.zeros(len(pl.runs))