Particle Representation Factory

docs/next/index.md

@@ -0,0 +1,12 @@
+# Next Outline
+
+Next is the next iteration of the particula simulation model. It is a complete rewrite of the model, with a focus on improving the modularity and extensibility of the model. The goal is to make it easier to add new features and to make the model more flexible and easier to use.
+
+## Tutorials
+
+- [Aerosol Distribution](Tutorials/Aerosol_Distributions.ipynb)
+- [Vapor Pressure](Tutorials/next_vapor_pressure.ipynb)
+
+## Guides for Developers
+
+![Four Quadrant representation of Tutorials, How to guides, References, and Discussions Areas](DocsImageDevGuide.png)

mkdocs.yml

@@ -11,7 +11,7 @@ theme:
     - navigation.sections
     - navigation.tracking
     - navigation.top
-    - navigation.footer
+    # - navigation.footer
     - toc.integrate
     - header.autohide
     - search.suggest
@@ -87,11 +87,10 @@ markdown_extensions:
 
 plugins:
   - search
-  # - social
   - mkdocs-jupyter:
-      include_source: True
-      execute: False  # takes too long, should build separately
-      allow_errors: True
+      include_source: True  # This enables the download of notebook sources.
+      execute: False        # Avoid executing notebooks during the build.
+      allow_errors: True    # Allow errors in the notebooks.
 
 extra_css:
   - stylesheets/extra.css

particula/data/lake.py

@@ -20,7 +20,6 @@ def add_stream(self, stream: Stream, name: str) -> None:
         """Add a stream to the lake.
 
         Args:
-        -----------
             stream (Stream): The stream object to be added.
             name (str): The name of the stream.
 

particula/data/lake_stats.py

@@ -2,24 +2,48 @@
 
 from typing import Optional, Union
 import numpy as np
+from numpy.typing import NDArray
 
 from particula.data.lake import Lake
 from particula.data import stream_stats
 
 
 def average_std(
-        lake: Lake,
-        average_interval: Union[float, int] = 60,
-        new_time_array: Optional[np.ndarray] = None,
-        clone: bool = True,
+    lake: Lake,
+    average_interval: Union[float, int] = 60,
+    new_time_array: Optional[NDArray[np.float_]] = None,
+    clone: bool = True,
 ) -> Lake:
-    """"
-    Averages the data in a lake over a specified time interval.
+    """Averages the data in each stream within a 'Lake' object.
+
+    If 'clone' is True, a new 'Lake' instance is created and the averaged
+    data is stored there. If 'clone' is False, the original 'Lake' instance
+    is modified. The averaged output also includes the standard deviation of
+    the data.
+
+    Example:
+        ```python
+        # Example lake with two streams, each containing numerical data
+        lake_data = Lake({'stream1': [1, 2, 3], 'stream2': [4, 5, 6]})
+        # Average over a 60-second interval without creating a new lake.
+        averaged_lake = average_std(lake_data, 60, clone=False)
+        print(averaged_lake)
+        Lake({'stream1': [2], 'stream2': [5]})
+        ```
+
+    Args:
+        lake: The lake data structure containing multiple streams.
+        average_interval: The interval over which to average the data.
+            Default is 60.
+        new_time_array: A new array of time points at which to compute the
+            averages.
+        clone: Indicates whether to modify the original lake or return a new
+            one. Default is True.
+
+    Returns:
+        Lake: A lake instance with averaged data.
     """
-    # nice line of code
     lake_averaged = Lake() if clone else lake
-
-    # iterate over streams in lake
     for name, stream in lake.items():
         lake_averaged[name] = stream_stats.average_std(
             stream=stream,