doc106 (PaddlePaddle#762)

huohuohuohuohuo123 · Jan 22, 2024 · d3fa030 · d3fa030
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diff --git a/docs/zh/examples/bubble.md b/docs/zh/examples/bubble.md
@@ -91,7 +91,7 @@ $$\frac{\partial \phi}{\partial t}+\mathbf{u} \cdot \nabla \phi=\gamma \nabla \c
   ![bubble.png](https://paddle-org.bj.bcebos.com/paddlescience/docs/BubbleNet/bubble.jpeg){ loading=lazy style="height:80%;width:80%" align="center" }
 </figure>
 
-本文我们主要考虑单气泡流(图 A )，当然对于多气泡流问题同样适用。对于单气泡情况，气泡初始直径设置为 $d =  4~μmm$，微通道长度为 $15~μm$，宽度为 $5~μm$。沿轴向施加压力差 $\Delta p = 10~Pa$ 来驱动气泡流动，通道末端的压力保持为恒定压力 $p_0 = 799.932~Pa(6~mmHg)$，对应于人脑和淋巴液流动中间质液的压力。初始条件 (IC) 即设置为 $p=p_0$，室温为 $293.15~K$，如图 A 所示。该数值设置旨在模拟脑血管中的气泡传输，以研究血脑屏障。同时我们设 $\gamma=1$ 和 $\epsilon_{l s}=0.430$。
+本文我们主要考虑单气泡流(图 A )，当然对于多气泡流问题同样适用。对于单气泡情况，气泡初始直径设置为 $d =  4~μm$，微通道长度为 $15~μm$，宽度为 $5~μm$。沿轴向施加压力差 $\Delta p = 10~Pa$ 来驱动气泡流动，通道末端的压力保持为恒定压力 $p_0 = 799.932~Pa(6~mmHg)$，对应于人脑和淋巴液流动中间质液的压力。初始条件 (IC) 即设置为 $p=p_0$，室温为 $293.15~K$，如图 A 所示。该数值设置旨在模拟脑血管中的气泡传输，以研究血脑屏障。同时我们设 $\gamma=1$ 和 $\epsilon_{l s}=0.430$。
 
 本文的算法 BubbleNet 的主要内容如下：
 

diff --git a/ppsci/visualize/vtu.py b/ppsci/visualize/vtu.py
@@ -104,14 +104,30 @@ def save_vtu_from_dict(
     value_keys: Tuple[str, ...],
     num_timestamps: int = 1,
 ):
-    """Save dict data to '*.vtu' file.
+    """
+    Save dict data to '*.vtu' file.
 
     Args:
         filename (str): Output filename.
         data_dict (Dict[str, np.ndarray]): Data in dict.
         coord_keys (Tuple[str, ...]): Tuple of coord key. such as ("x", "y").
         value_keys (Tuple[str, ...]): Tuple of value key. such as ("u", "v").
         num_timestamps (int, optional): Number of timestamp in data_dict. Defaults to 1.
+
+    Examples:
+        >>> import ppsci
+        >>> import numpy as np
+        >>> filename = "path/to/file.vtu"
+        >>> data_dict = {
+        ...     "x": np.array([[1], [2], [3],[4]]),
+        ...     "y": np.array([[2], [3], [4],[4]]),
+        ...     "z": np.array([[3], [4], [5],[4]]),
+        ...     "u": np.array([[4], [5], [6],[4]]),
+        ...     "v": np.array([[5], [6], [7],[4]]),
+        ... }
+        >>> coord_keys = ("x","y","z")
+        >>> value_keys = ("u","v")
+        >>> ppsci.visualize.save_vtu_from_dict(filename, data_dict, coord_keys, value_keys) # doctest: +SKIP
     """
     if len(coord_keys) not in [2, 3, 4]:
         raise ValueError(f"ndim of coord ({len(coord_keys)}) should be 2, 3 or 4")