deeptime.decomposition¶
The decomposition package contains algorithms which can be used to project data onto dominant slow processes.
Estimators¶
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Variational approach for Markov processes (VAMP). |
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Time-lagged independent component analysis (TICA). |
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Dynamic mode decomposition estimator. |
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Extended dynamic mode decomposition for estimation of the Koopman (or optionally Perron-Frobenius) operator. |
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Estimator implementing kernel extended mode decomposition. |
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Estimator implementing the kernelized version of canonical correlation analysis. |
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An estimator for the "Kernel embedding based variational approach for dynamical systems" (KVAD). |
Deep estimators¶
Note that usage of these estimators requires a working installation of PyTorch.
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Implementation of VAMPNets. |
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Time-lagged autoencoder. |
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The time-lagged variational autoencoder. |
Models¶
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Model which contains a finite-dimensional transfer operator (or approximation thereof). |
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A type of Koopman model \(\mathbb{E}[g(x_{t+\tau})] = K^\top \mathbb{E}[f(x_{t})]\) which was obtained through diagonalization of covariance matrices. |
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Model produced by the |
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The EDMD model which can be estimated from a |
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The kEDMD model containing eigenvalues and eigenfunctions evaluated in the instantaneous data. |
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The model produced by the |
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The model produced by the |
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A VAMPNet model which can be fit to data optimizing for one of the implemented VAMP scores. |
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Model produced by time-lagged autoencoders. |
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Model produced by the time-lagged variational autoencoder ( |
Utils¶
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Compute the VAMP score between a covariance-based Koopman model and potentially a test model for cross-validation. |
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Computes VAMP score based on data and corresponding time-lagged data. |
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Scores the MSM using the variational approach for Markov processes and cross-validation. |
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Splits the trajectories into a training and test set with approximately equal number of trajectories |
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Splits trajectories into approximately uncorrelated fragments. |
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A kind of |
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Computes the Koopman matrix |
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Utility function that returns the inverse of a matrix, with the option to return the square root of the inverse matrix. |
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Computes instantaneous and time-lagged covariances matrices. |
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Computes the VAMP score based on data and corresponding time-shifted data. |
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Loss function that can be used to train VAMPNets. |
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