How saloniemi/asp-360-group-56 works
This repository is a hurricane-track prediction project: storm records are cleaned and segmented, sequences are normalized for model training, and a saved Keras model can be used to predict and map a storm track. The sampled code supports the data-preparation, training, and mapping flow; the README is only a placeholder, and the notebooks were not inspected, so their specific behavior is not represented.
Main entry points: mapping.py Track Prediction Map · read_data.py Clean and Segment · segmented_data_2s.csv Segmented Sequences · format_data.py Normalize and Split
Components 10
Storm Data
- Storm Records
data_processing/storms.csv - Clean and Segment
data_processing/read_data.py - Stripped Records
data_processing/stripped_storms.csv - Segmented Sequences
data_processing/segmented_data_2s.csv
Prediction Model
- Normalize and Split
model/format_data.py - Model Training
model/model_keras.py - Saved Keras Model
model/output/Model Trials/Model_0_(16-50).keras
Track Results
- Track Prediction Map
model/mapping.py - Rendered Map
model/output/Model Trials
Other components
- Researcher
Connections 11
- Storm Records → Clean and Segment: reads
data_processing/read_data.py - Clean and Segment → Stripped Records: writes
data_processing/read_data.py - Clean and Segment → Segmented Sequences: writes
data_processing/read_data.py - Segmented Sequences → Normalize and Split: loads
model/format_data.py - Model Training → Normalize and Split: uses
model/model_keras.py - Model Training → Saved Keras Model: saves
model/model_keras.py - Researcher → Track Prediction Map: runs
- Track Prediction Map → Segmented Sequences: reads
model/mapping.py - Track Prediction Map → Normalize and Split: uses
model/mapping.py - Track Prediction Map → Saved Keras Model: loads
model/mapping.py - Track Prediction Map → Rendered Map: saves
model/mapping.py