nasa-nccs-hpda / astrotime / 13358973679

Builds Branch Commit Type Ran Committer Via Coverage
13358973679 main Add notebook for wavelet transform plots and NetCDF loader Introduced a Jupyter notebook to visualize wavelet transforms using SignalTransformPlot. Added a new `ncSinusoidLoader` class to handle loading of sinusoid datasets from NetCDF files, sup... push ThomasMaxwell github
80.0
13358841417 main Streamline wavelet_plot notebook and refactor structure. Reorganized the notebook to use cell-based sections for better readability and execution flow. Updated the `SignalTransformPlot` initialization to include a plot title. Removed unnecessary ... push ThomasMaxwell github
80.0
13358637773 main Refactor wavelet_plot notebook to script-style format. Replaced JSON notebook format with script-style `%matplotlib widget` cells for better readability and maintainability. This enhances code organization and simplifies version control handling. push ThomasMaxwell github
80.0
13358306511 main Refactor wavelet_plot notebook and add logging setup. Simplified notebook structure using script-style formatting and added logging initialization for better debugging. Updated imports and included log management to align with project standards. push ThomasMaxwell github
80.0
13358273457 main Refactor wavelet_plot notebook to use script-style sections Restructured the notebook by replacing JSON-format metadata with script-style `#%%` sections for better modularity and readability. Updated data directory path to align with the current ... push ThomasMaxwell github
80.0
13358108959 main Refactor wavelet plotting notebook and related modules Simplified and updated the wave push ThomasMaxwell github
80.0
13357383885 main Refactor norm_concat to remove debug print and tnorm usage The debug print statement was removed for cleaner code, and the tnorm function is no longer applied to the concatenated tensor. This change simplifies the norm_concat function and aligns ... push ThomasMaxwell github
80.0
13357343717 main Refactor norm_concat to improve debugging. Added a debug print statement to log the shape of the tensor during concatenation in norm_concat. This helps with troubleshooting and ensures tensor dimensions are as expected. No functional behavior was... push ThomasMaxwell github
80.0
13350670458 main Adjust batch size from 64 to 32 in wavelet embedding script. Reduced the batch size to 32 to optimize memory usage and training stability. This change helps ensure the model runs efficiently with the current hardware setup. Other parameters remai... push ThomasMaxwell github
80.0
13350539192 main Refactor tensor concatenation with normalization. Introduced a `norm_concat` utility function to streamline and normalize tensor concatenation. Updated `WaveletEncoder` to use this function for improved code readability and consistency. push ThomasMaxwell github
80.0
13350245275 main Refactor wavelet encoding return logic indentation Adjusted the indentation of the wavelet encoding return logic to align with the correct nested scope. This ensures proper execution flow and avoids potential errors caused by incorrectly scoped o... push ThomasMaxwell github
80.0
13350208232 main Add wavelet-based CNN training script and reorganize workflow Introduced a new script `wavelet-cnn.py` for training a CNN model using wavelet-transformed data. The script implements dataset loading, model compilation, and training with callbacks ... push ThomasMaxwell github
80.0
13350179221 main Refactor normalization to use `tnorm` in WaveletEncoder. Replaced `keras.utils.normalize` with the more efficient `tnorm` function for tensor normalization in `WaveletEncoder`. This change improves performance and ensures consistency with other u... push ThomasMaxwell github
80.0
13350164640 main Add tnorm function and update ValueEncoder to use it Introduced the tnorm function in math utilities for tensor normalization. Updated ValueEncoder to normalize target data using tnorm instead of keras.utils.normalize, ensuring consistency in pre... push ThomasMaxwell github
80.0
13350047084 main Add `tmag` function and integrate it into `ValueEncoder` Introduced the `tmag` function to calculate the maximum magnitude of tensor values in `math.py`. Updated `ValueEncoder` to display the magnitude (`mag`) of the tensor `Y` alongside its mean... push ThomasMaxwell github
80.0