AIModels¶
AIModels is a Python package that provides a set of tools for training and testing AI models for climate data analysis.
The library is best used together with the Anaconda distribution.
Submodules¶
- AIModels.AIClasses module
- AIModels.ClimFormer module
- AIModels.ClimLSTM module
- AIModels.LocalInformer module
- AIModels.ModelTraining module
- AIModels.UtilPlot module
- AIModels.AIutil module
- Utility Treatment Routines for ML Predicting models
func_name()
copy_dict()
select_field()
select_field_key()
select_field_eof()
select_area()
make_matrix()
make_eof()
make_field()
make_field_V5()
make_field_HAD()
make_data()
make_features()
make_data_base()
init_weights()
count_parameters()
epoch_time()
create_time_features()
rescale()
make_dyn_verification()
eof_to_grid_new()
matrix_rank_light()
Package contents¶
AIModels is a Python package for the designing ML networks of atmospheric and ocean data. It is based on the xarray package.
It uses xarray as a basic data structure.
AIModels contains several modules with classes and utility routines The plotting modules are based on matplotlib and cartopy. The computation modules are based on numpy and scipy.
- ClimFormer :
Class for ClimFormer network
- ClimLSTM :
Class for ClimLSTM network
- LocalInformer :
Class for LocalInformer network, a modified version of Informer for time series from HuggingFace
- ModelTraining :
Class for training, validate and inference the models
- UtilPlot :
Routines for plotting and visualization of the data
- AIutil :
Utilities for the rest of the modules
Version 2.1