diff --git a/olaflow/README.md b/olaflow/README.md
index 5805740..594d81c 100644
--- a/olaflow/README.md
+++ b/olaflow/README.md
@@ -14,3 +14,21 @@ données.
 * `-v` : verbose
 * `-m` : au-lieu d'une animation, tracer le maximum de chaque grandeur dans le modèle
 * `-i` : au-lieu d'une animation, tracer la valeur initiale de chaque grandeur
+
+### Bathy
+
+`bathy.py` permet de générer la bathymétrie utilisée par Olaflow.
+
+```python -m processing.bathy [-c CONFIG] [-v]```
+
+* `-c CONFIG` : choix d'un fichier de configuration
+* `-v` : verbose
+
+```
+[bathy]
+bathy : bathymétrie générée dans data
+hstru : hauteur de poreux générée dans data
+scale* : échelle de la bathymétrie en [x,y,z]
+translate* : translation de la bathymétrie en [x,y,z]
+out : dossier de sortie de la bathymétrie
+```
diff --git a/olaflow/processing/animateU.py b/olaflow/processing/animateU.py
deleted file mode 100644
index 915cc2e..0000000
--- a/olaflow/processing/animateU.py
+++ /dev/null
@@ -1,104 +0,0 @@
-import argparse
-import gzip
-import logging
-import multiprocessing as mp
-import pathlib
-import pickle
-
-import matplotlib.pyplot as plt
-import matplotlib.animation as animation
-from matplotlib.gridspec import GridSpec
-import numpy as np
-from scipy import interpolate
-
-from .olaflow import OFModel
-
-parser = argparse.ArgumentParser(description="Post-process olaflow results")
-parser.add_argument("-v", "--verbose", action="count", default=0)
-parser.add_argument(
-    "-o",
-    "--output",
-    type=pathlib.Path,
-    help="Output directory for pickled data",
-    required=True,
-)
-args = parser.parse_args()
-
-logging.basicConfig(level=max((10, 20 - 10 * args.verbose)))
-log = logging.getLogger("ola_post")
-
-log.info("Animating olaFlow output")
-out = args.output
-out.mkdir(parents=True, exist_ok=True)
-
-with (
-    path.open("rb")
-    if (path := out.joinpath("pickle")).exists()
-    else gzip.open(path.with_suffix(".gz"), "rb")
-) as f:
-    model = pickle.load(f)
-
-flt = np.where((model.x >= -60) & (model.x <= -20) & (model.z >= 0) & (model.z <= 10))[
-    0
-]
-x0, idx0 = np.unique(model.x[flt].astype(np.half), return_inverse=True)
-z0, idz0 = np.unique(model.z[flt].astype(np.half), return_inverse=True)
-
-X, Z = np.meshgrid(x0, z0)
-
-P = np.full((model.t.size, *X.shape), np.nan)
-P[:, idz0, idx0] = model.fields["porosity"][:, flt]
-
-AW = np.full((model.t.size, *X.shape), np.nan)
-AW[:, idz0, idx0] = model.fields["alpha.water"][:, flt]
-
-watl = z0[np.argmax((AW > 0.5)[:, ::-1, :], axis=1)]
-
-U = np.full((model.t.size, 2, *X.shape), np.nan)
-UU = np.full((model.t.size, *X.shape), np.nan)
-U[..., idz0, idx0] = model.fields["U"][..., flt][:, (0, 2)]
-UU[..., idz0, idx0] = np.linalg.norm(model.fields["U"][..., flt], axis=1)
-
-figU = plt.figure(figsize=(19.2, 10.8), dpi=100)
-gsU = GridSpec(2, 1, figure=figU, height_ratios=[1, 0.05])
-axU = figU.add_subplot(gsU[0])
-caxu1 = figU.add_subplot(gsU[1])
-# caxu2 = figU.add_subplot(gsU[2])
-
-alp = np.clip(np.nan_to_num(AW), 0, 1)
-axU.pcolormesh(X, Z, P[1], vmin=0, vmax=1, cmap="Greys_r")
-u_m = axU.quiver(
-    X,
-    Z,
-    *U[0],
-    UU[0],
-    alpha=alp[0],
-    cmap="inferno_r",
-    clim=(0, 20),
-)
-# (wat_p,) = axU.plot(x0, watl[0])
-
-axU.set(xlabel="x (m)", ylabel="z (m)", aspect="equal", facecolor="#bebebe")
-axU.grid(c="k", alpha=0.2)
-titU = axU.text(
-    0.5,
-    0.95,
-    f"t={model.t[0]}s",
-    horizontalalignment="center",
-    verticalalignment="top",
-    transform=axU.transAxes,
-)
-
-figU.colorbar(u_m, label=r"$U$", cax=caxu1, shrink=0.6, orientation="horizontal")
-
-
-def animU(i):
-    titU.set_text(f"t={model.t[i]}s")
-    u_m.set_UVC(*U[i], UU[i])
-    u_m.set_alpha(alp[i])
-    # wat_p.set_ydata(watl[i])
-
-
-aniU = animation.FuncAnimation(figU, animU, frames=model.t.size, interval=1 / 24)
-
-aniU.save(out.joinpath("animUzoom.mp4"), fps=24)