fix doc

Author: HydrogenSulfate

ppsci/loss/integral.py

@@ -36,7 +36,7 @@ class IntegralLoss(base.Loss):
     $M$ is the number of samples in monte carlo integration.
 
     Args:
-        reduction (str, optional): Reduction method. Defaults to "mean".
+        reduction (Literal["mean", "sum"], optional): Reduction method. Defaults to "mean".
         weight (Optional[Union[float, Dict[str, float]]]): Weight for loss. Defaults to None.
 
     Examples:

ppsci/loss/l1.py

@@ -34,7 +34,7 @@ class L1Loss(base.Loss):
     $$
 
     Args:
-        reduction (str, optional): Reduction method. Defaults to "mean".
+        reduction (Literal["mean", "sum"], optional): Reduction method. Defaults to "mean".
         weight (Optional[Union[float, Dict[str, float]]]): Weight for loss. Defaults to None.
 
     Examples:
@@ -85,7 +85,7 @@ class PeriodicL1Loss(base.Loss):
     """Class for periodic l1 loss.
 
     Args:
-        reduction (str, optional): Reduction method. Defaults to "mean".
+        reduction (Literal["mean", "sum"], optional): Reduction method. Defaults to "mean".
     """
 
     def __init__(

ppsci/loss/l2.py

@@ -109,8 +109,8 @@ class L2RelLoss(base.Loss):
     $$
     L =
     \begin{cases}
-        \dfrac{1}{N}\sum\limits_{i=1}^{N}{\dfrac{\Vert \bm{X_i}-\bm{Y_i}\Vert_2}{\Vert \bm{Y_i}\Vert_2}}, & \text{if reduction='mean'} \\
-        \sum\limits_{i=1}^{N}{\dfrac{\Vert \bm{X_i}-\bm{Y_i}\Vert_2}{\Vert \bm{Y_i}\Vert_2}}, & \text{if reduction='sum'}
+        \dfrac{1}{N}\sum\limits_{i=1}^{N}{\dfrac{\Vert \mathbf{X_i}-\mathbf{Y_i}\Vert_2}{\Vert \mathbf{Y_i}\Vert_2}}, & \text{if reduction='mean'} \\
+        \sum\limits_{i=1}^{N}{\dfrac{\Vert \mathbf{X_i}-\mathbf{Y_i}\Vert_2}{\Vert \mathbf{Y_i}\Vert_2}}, & \text{if reduction='sum'}
     \end{cases}
     $$
 

ppsci/loss/mse.py

@@ -35,7 +35,7 @@ class MSELoss(base.Loss):
     $$
 
     Args:
-        reduction (str, optional): Reduction method. Defaults to "mean".
+        reduction (Literal["mean", "sum"], optional): Reduction method. Defaults to "mean".
         weight (Optional[Union[float, Dict[str, float]]]): Weight for loss. Defaults to None.
 
     Examples:
@@ -130,7 +130,7 @@ class PeriodicMSELoss(base.Loss):
     """Class for periodic mean squared error loss.
 
     Args:
-        reduction (str, optional): Reduction method. Defaults to "mean".
+        reduction (Literal["mean", "sum"], optional): Reduction method. Defaults to "mean".
         weight (Optional[Union[float, Dict[str, float]]]): Weight for loss. Defaults to None.
     """
 

ppsci/visualize/visualizer.py

@@ -292,7 +292,6 @@ class Visualizer3D(base.Visualizer):
         output_expr (Dict[str, Callable]): Output expression.
         batch_size (int, optional): Batch size of data when computing result in visu.py. Defaults to 64.
         label_dict (Dict[str, np.ndarray]): Label dict.
-        transforms (Optional[Dict[str, ]]): Transformer dict.
         time_list (Optional[Tuple[float, ...]]): Time list.
         num_timestamps (int, optional): Number of timestamps.
         prefix (str, optional): Prefix for output file.