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Title: Tutorials — datafold 2.0.1 documentation

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Skip to main contenthttps://datafold-dev.gitlab.io/datafold/tutorial_index.html#main-content
https://datafold-dev.gitlab.io/datafold/index.html
Getting started https://datafold-dev.gitlab.io/datafold/gettingstarted.html
Tutorials https://datafold-dev.gitlab.io/datafold/tutorial_index.html
Software documentation https://datafold-dev.gitlab.io/datafold/api.html
Contributing https://datafold-dev.gitlab.io/datafold/contributing.html
References https://datafold-dev.gitlab.io/datafold/references.html
GitLabhttps://gitlab.com/datafold-dev/datafold/
PyPIhttps://pypi.org/project/datafold/
Getting started https://datafold-dev.gitlab.io/datafold/gettingstarted.html
Tutorials https://datafold-dev.gitlab.io/datafold/tutorial_index.html
Software documentation https://datafold-dev.gitlab.io/datafold/api.html
Contributing https://datafold-dev.gitlab.io/datafold/contributing.html
References https://datafold-dev.gitlab.io/datafold/references.html
GitLabhttps://gitlab.com/datafold-dev/datafold/
PyPIhttps://pypi.org/project/datafold/
Data structure for time series collections TSCDataFramehttps://datafold-dev.gitlab.io/datafold/tutorial_01_datastructures.html
Uniform subsampling of point cloud manifoldhttps://datafold-dev.gitlab.io/datafold/tutorial_02_pcm_subsampling.html
Diffusion Maps: Embedding of an S-curved manifoldhttps://datafold-dev.gitlab.io/datafold/tutorial_03_dmap_scurve.html
Manifold learning on handwritten digitshttps://datafold-dev.gitlab.io/datafold/tutorial_04_dmap_digitclustering.html
RObust and Scalable Embedding via LANdmark Diffusion (Roseland)https://datafold-dev.gitlab.io/datafold/tutorial_05_roseland_scurve_digits.html
Embeddings invariant to the observables with Mahalanobis kernelhttps://datafold-dev.gitlab.io/datafold/tutorial_06_dmap_mahalanobis_kernel.html
Jointly Smooth Functions: An Examplehttps://datafold-dev.gitlab.io/datafold/tutorial_07_jsf_common_eigensystem.html
Geometric Harmonics: interpolate function values on data manifoldhttps://datafold-dev.gitlab.io/datafold/tutorial_08_gh_oos.html
Dynamic mode decomposition on two mixed spatial signalshttps://datafold-dev.gitlab.io/datafold/tutorial_09_dmd_mixed_spatial_signals.html
Extended Dynamic Mode Decomposition on Limit Cyclehttps://datafold-dev.gitlab.io/datafold/tutorial_10_edmd_limitcycle.html
Dynamic mode decomposition with controlhttps://datafold-dev.gitlab.io/datafold/tutorial_11_dmd_control.html
Model-based control using Extended Dynamic Mode Decompositionhttps://datafold-dev.gitlab.io/datafold/tutorial_12_edmd_control.html
Dictionary Learning for enhanced Koopman Operator approximationshttps://datafold-dev.gitlab.io/datafold/tutorial_13_EDMD_with_dictionary_learning.html
Koopman operator model predictive control for flow controlhttps://datafold-dev.gitlab.io/datafold/tutorial_14_kmpc_flowcontrol.html
Koopman operator-based model predictive control of a bilinear motorhttps://datafold-dev.gitlab.io/datafold/tutorial_15_kmpc_motor_engine.html
An example to demonstrate online dynamic mode decompositionhttps://datafold-dev.gitlab.io/datafold/tutorial_16_online_dmd.html
https://datafold-dev.gitlab.io/datafold/index.html
#https://datafold-dev.gitlab.io/datafold/tutorial_index.html#tutorials
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Downloadhttps://gitlab.com/datafold-dev/datafold/-/archive/master/datafold-master.zip?path=tutorials/
Data structure for time series collections TSCDataFramehttps://datafold-dev.gitlab.io/datafold/tutorial_01_datastructures.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/01_datastructures.ipynb?inline=false
Uniform subsampling of point cloud manifoldhttps://datafold-dev.gitlab.io/datafold/tutorial_02_pcm_subsampling.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/02_pcm_subsampling.ipynb?inline=false
Diffusion Maps: Embedding of an S-curved manifoldhttps://datafold-dev.gitlab.io/datafold/tutorial_03_dmap_scurve.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/03_dmap_scurve.ipynb?inline=false
scikit-learn tutorialhttps://scikit-learn.org/stable/auto_examples/manifold/plot_compare_methods.html#sphx-glr-auto-examples-manifold-plot-compare-methods-py
Manifold learning on handwritten digitshttps://datafold-dev.gitlab.io/datafold/tutorial_04_dmap_digitclustering.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/04_dmap_digitclustering.ipynb?inline=false
scikit-learn tutorialhttps://scikit-learn.org/stable/auto_examples/manifold/plot_lle_digits.html
RObust and Scalable Embedding via LANdmark Diffusion (Roseland)https://datafold-dev.gitlab.io/datafold/tutorial_05_roseland_scurve_digits.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/05_roseland_scurve_digits.ipynb?inline=false
scikit-learn tutorial 1https://scikit-learn.org/stable/auto_examples/manifold/plot_compare_methods.html#sphx-glr-auto-examples-manifold-plot-compare-methods-py
scikit-learn tutorial 2https://scikit-learn.org/stable/auto_examples/manifold/plot_lle_digits.html
Embeddings invariant to the observables with Mahalanobis kernelhttps://datafold-dev.gitlab.io/datafold/tutorial_06_dmap_mahalanobis_kernel.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/06_dmap_mahalanobis_kernel.ipynb?inline=false
Jointly Smooth Functions: An Examplehttps://datafold-dev.gitlab.io/datafold/tutorial_07_jsf_common_eigensystem.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/07_jsf_common_eigensystem.ipynb?inline=false
Geometric Harmonics: interpolate function values on data manifoldhttps://datafold-dev.gitlab.io/datafold/tutorial_08_gh_oos.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/08_gh_oos.ipynb?inline=false
Dynamic mode decomposition on two mixed spatial signalshttps://datafold-dev.gitlab.io/datafold/tutorial_09_dmd_mixed_spatial_signals.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/09_dmd_mixed_spatial_signals.ipynb?inline=false
pykoopman tutorialhttps://github.com/dynamicslab/pykoopman/blob/master/docs/tutorial_dmd_separating_two_mixed_signals_400d_system.ipynb
2016https://datafold-dev.gitlab.io/datafold/references.html#id33
Extended Dynamic Mode Decomposition on Limit Cyclehttps://datafold-dev.gitlab.io/datafold/tutorial_10_edmd_limitcycle.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/10_edmd_limitcycle.ipynb?inline=false
Dynamic mode decomposition with controlhttps://datafold-dev.gitlab.io/datafold/tutorial_11_dmd_control.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/11_dmd_control.ipynb?inline=false
Original PyDMD tutorialhttps://github.com/mathLab/PyDMD/blob/master/tutorials/tutorial7/tutorial-7-dmdc.ipynb
Model-based control using Extended Dynamic Mode Decompositionhttps://datafold-dev.gitlab.io/datafold/tutorial_12_edmd_control.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/12_edmd_control.ipynb?inline=false
Templated tutorialhttps://github.com/i-abr/mpc-koopman/blob/master/mpc_with_koopman_op.ipynb
Dictionary Learning for enhanced Koopman Operator approximationshttps://datafold-dev.gitlab.io/datafold/tutorial_13_EDMD_with_dictionary_learning.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/13_EDMD_with_dictionary_learning.ipynb?inline=false
2017https://datafold-dev.gitlab.io/datafold/references.html#id36
Koopman operator model predictive control for flow controlhttps://datafold-dev.gitlab.io/datafold/tutorial_14_kmpc_flowcontrol.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/14_kmpc_flowcontrol.ipynb?inline=false
Original code (Matlab)https://github.com/arbabiha/KoopmanMPC_for_flowcontrol
2018https://datafold-dev.gitlab.io/datafold/references.html#id4
Koopman operator-based model predictive control of a bilinear motorhttps://datafold-dev.gitlab.io/datafold/tutorial_15_kmpc_motor_engine.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/15_kmpc_motor_engine.ipynb?inline=false
Original code (Matlab)https://github.com/MilanKorda/KoopmanMPC/
2018https://datafold-dev.gitlab.io/datafold/references.html#id32
An example to demonstrate online dynamic mode decompositionhttps://datafold-dev.gitlab.io/datafold/tutorial_16_online_dmd.html
downloadhttps://gitlab.com/datafold-dev/datafold/-/raw/master/tutorials/16_online_dmd.ipynb?inline=false
Original demohttps://github.com/haozhg/odmd/blob/master/demo/demo_online.ipynb
2019https://datafold-dev.gitlab.io/datafold/references.html#id48
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Jupyter homepagehttps://jupyter.org/
previous Introduction https://datafold-dev.gitlab.io/datafold/intro.html
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Run notebooks with Jupyterhttps://datafold-dev.gitlab.io/datafold/tutorial_index.html#run-notebooks-with-jupyter
Download fileshttps://datafold-dev.gitlab.io/datafold/tutorial_index.html#download-files
Start Jupyterhttps://datafold-dev.gitlab.io/datafold/tutorial_index.html#start-jupyter
Show Source https://datafold-dev.gitlab.io/datafold/_sources/tutorial_index.rst.txt
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