DOI-USGS/nhm-assist

AI Summary: Optimize the performance of the last plot in notebook 5 of the nhm-assist project to reduce rendering time, especially when dealing with large datasets. This likely involves identifying and addressing performance bottlenecks within the plotting code, potentially through code optimization, algorithm improvements, or leveraging more efficient plotting libraries.

AI Summary: Parallelize the creation of embedded Plotly graphs within Jupyter Notebook 3 of the nhm-assist project to reduce processing time from approximately 40 minutes to a shorter duration. This involves optimizing the code to utilize multiple CPU cores for generating the graphs, potentially using multiprocessing libraries in Python.

AI Summary: Modify the Jupyter notebook (notebook 2) within the `nhm-assist` project to incorporate agency identification information into the color scheme of streamflow observations displayed in Plotly graphs embedded within the hydrofabric map. This involves updating the code to use the agency ID to assign colors to different observation datasets, enhancing the visualization's clarity and interpretability.

AI Summary: Enhance the Jupyter notebooks within the `nhm-assist` project by adding interactive sliders to Notebook 5. These sliders should allow users to dynamically control the displayed timeseries data on the map, selecting the year, month (if applicable), and variable without needing to rerun cells. This improves user experience by providing a more interactive and intuitive way to explore the data.

AI Summary: The task requires modifying the autocomplete dropdown functionality in the `nhm-assist` Python project. Currently, when a gage is pre-selected (likely for continuous integration testing), the dropdown hides other available gages, preventing users from selecting different gages. The fix involves ensuring that pre-selected gages do not prevent other gages from appearing in the autocomplete suggestions.