Table Of Contents

Documentation

• Dimension reduction
• Deep dim reduction
  • VAMPNets
  • Time-lagged autoencoders
    • Autoencoders
    • Variational autoencoders
• SINDy
  • Main ideas
  • Approximation problem
  • Deeptime SINDy objects
  • Example
• Markov state models
  • Transition counting
    • Selecting a submodel
  • Maximum-likelihood MSMs
    • Bayesian sampling
  • Coarse-graining with PCCA+
  • Transition path theory
    • The committor
    • Reactive probability flux
    • Coarse-graining of fluxes
    • Pathway decomposition
    • Example from trajectories
  • TRAM
    • Introduction
    • Application to a double well
    • Recovering the PMF
• Hidden Markov Models
  • Estimation
  • Bayesian sampling
• Clustering
  • K-means
    • uniform initialization
    • k-means++ initialization
  • Mini-batch k-means
  • Regular space clustering
  • Box discretization
  • Defining a custom metric (advanced)
• Examples
  • General examples
  • Notebook examples
    • VAMPNets on Alanine Dipeptide
    • MSM on Prinz potential
    • Dimension reduction of double-wedge dataset
      • TICA
      • EDMD
      • VAMP with backtransform
      • Kernel EDMD
      • Kernel CCA
      • VAMPNets
      • Markov state models
    • Coherent set comparison on Bickley jet
      • Kernel CCA
      • VAMPNets
      • VAMP
      • KVAD
      • KVADNets
      • Comparison of scores
• Datasets
  • ODEs
  • SDEs
  • Other
• For developers
  • Writing a custom estimator
  • Adding transformer capabilities
  • Depending on PyTorch
  • Testing your code
  • Documenting the code

API docs

• deeptime.base
  • class Model
    • Model
  • class Estimator
    • Estimator
  • class Transformer
    • Transformer
  • class Dataset
    • Dataset
• deeptime.clustering
  • Estimators
    • class KMeans
    • class MiniBatchKMeans
    • class RegularSpace
    • class BoxDiscretization
  • Models
    • class ClusterModel
    • class KMeansModel
    • class BoxDiscretizationModel
  • Functions
    • function kmeans_plusplus
  • Adding a new metric
    • data metrics
    • class MetricRegistry
• deeptime.sindy
  • Estimators
    • class SINDy
  • Models
    • class SINDyModel
  • Solvers
    • class STLSQ
• deeptime.covariance
  • Estimators
    • class Covariance
    • class KoopmanWeightingEstimator
  • Models
    • class CovarianceModel
    • class KoopmanWeightingModel
  • Utilities
    • class WhiteningTransform
    • function covar
    • function covars
    • function moments_XX
    • function moments_XXXY
    • function moments_block
• deeptime.decomposition
  • Estimators
    • class VAMP
    • class TICA
    • class DMD
    • class EDMD
    • class KernelEDMD
    • class KernelCCA
    • class KVAD
  • Deep estimators
    • class VAMPNet
    • class TAE
    • class TVAE
  • Models
    • class TransferOperatorModel
    • class CovarianceKoopmanModel
    • class DMDModel
    • class EDMDModel
    • class KernelEDMDModel
    • class KernelCCAModel
    • class KVADModel
    • class VAMPNetModel
    • class TAEModel
    • class TVAEModel
  • Utils
    • function vamp_score
    • function vamp_score_data
    • function vamp_score_cv
    • function cvsplit_trajs
    • function blocksplit_trajs
    • class TVAEEncoder
    • function koopman_matrix
    • function sym_inverse
    • function covariances
    • function vamp_score
    • function vampnet_loss
    • function kvad_score
• deeptime.markov
  • Estimators
    • class MaximumLikelihoodMSM
    • class BayesianMSM
    • class TRAM
  • Models
    • class MarkovStateModel
    • class MarkovStateModelCollection
    • class BayesianMSMPosterior
    • class TRAMModel
  • Analysis tools
    • function pcca
    • function reactive_flux
    • class PCCAModel
    • class ReactiveFlux
  • Utilities and alternatives
    • function number_of_states
    • function count_states
    • function compute_connected_sets
    • function compute_dtrajs_effective
    • function compute_effective_stride
    • function indices_by_distribution
    • function compute_index_states
    • function indices_by_sequence
    • function indices_by_state
    • class TRAMDataset
    • Transition counting
    • Special MSM estimators and models
• deeptime.markov.hmm
  • Estimators
    • class MaximumLikelihoodHMM
    • class BayesianHMM
  • Output models
    • class OutputModel
    • class DiscreteOutputModel
    • class GaussianOutputModel
  • Initial guess
    • function random_guess
    • function metastable_from_data
    • function metastable_from_msm
    • function from_data
  • Models
    • class HiddenMarkovModel
    • class BayesianHMMPosterior
• deeptime.markov.tools
  • MSM estimation
    • Countmatrix
    • Connectivity
    • Estimation
    • Sampling
    • Bootstrap
    • Priors
  • MSM analysis
    • Validation
    • Decomposition
    • Expected counts
    • Passage times
    • Committors and PCCA
    • Fingerprints
    • Sensitivity analysis
  • Transition path theory tools
    • Reactive flux
    • Reaction rates and fluxes
    • Pathway decomposition
• deeptime.basis
  • class Observable
    • Observable
  • class Concatenation
    • Concatenation
  • class Identity
    • Identity
  • class Monomials
    • Monomials
• deeptime.kernels
  • class Kernel
    • Kernel
  • class GaussianKernel
    • GaussianKernel
  • class GeneralizedGaussianKernel
    • GeneralizedGaussianKernel
  • class LaplacianKernel
    • LaplacianKernel
  • class PolynomialKernel
    • PolynomialKernel
  • class TorchGaussianKernel
    • TorchGaussianKernel
  • function is_torch_kernel
    • is_torch_kernel()
• deeptime.data
  • Deterministic datasets
    • function abc_flow
    • function bickley_jet
    • function lorenz_system
    • function thomas_attractor
    • function position_based_fluids
  • Stochastic datasets
    • function tmatrix_metropolis1d
    • function birth_death_chain
    • function ornstein_uhlenbeck
    • function double_well_2d
    • function double_well_discrete
    • function triple_well_1d
    • function triple_well_2d
    • function quadruple_well
    • function quadruple_well_asymmetric
    • function time_dependent_quintuple_well
    • function prinz_potential
    • function ellipsoids
    • function sqrt_model
    • function swissroll_model
    • function drunkards_walk
  • Custom systems
    • function custom_sde
    • function custom_ode
  • Implementations
    • class DoubleWellDiscrete
    • class Ellipsoids
    • class PBFSimulator
    • class DrunkardsWalk
    • class BickleyJet
    • class BirthDeathChain
    • class TimeDependentSystem
    • class TimeIndependentSystem
    • class CustomSystem
• deeptime.plots
  • function plot_implied_timescales
    • plot_implied_timescales()
  • function plot_ck_test
    • plot_ck_test()
  • function plot_energy2d
    • plot_energy2d()
  • class Energy2dPlot
    • Energy2dPlot
  • function plot_contour2d_from_xyz
    • plot_contour2d_from_xyz()
  • function plot_density
    • plot_density()
  • function plot_adjacency
    • plot_adjacency()
  • function plot_markov_model
    • plot_markov_model()
  • function plot_flux
    • plot_flux()
  • class Network
    • Network
• deeptime.numeric
  • General numerical tools
    • function drop_nan_rows
    • function is_diagonal_matrix
    • function is_square_matrix
    • function schatten_norm
  • Numerical tools for eigenvalue problems
    • function eigs
    • function eig_corr
    • function sort_eigs
    • function spd_eig
    • function spd_truncated_svd
    • function spd_inv
    • function spd_inv_split
    • function spd_inv_sqrt
    • exception ZeroRankError
• deeptime.util
  • Model validation utils
    • function implied_timescales
    • function ck_test
    • class ImpliedTimescales
    • class ChapmanKolmogorovTest
  • Data utilities
    • function timeshifted_split
    • function sliding_window
    • class TimeLaggedDataset
    • class TimeLaggedConcatDataset
    • class TrajectoryDataset
    • class TrajectoriesDataset
    • class ConcatDataset
  • Statistics utilities
    • function energy2d
    • class EnergyLandscape2d
    • class QuantityStatistics
    • function confidence_interval
  • Type utilities
    • function to_dataset
    • function is_timelagged_dataset
    • function atleast_nd
  • Differentiation utilities
    • function tv_derivative
    • function finite_difference_coefficients
    • function finite_difference_operator_midpoints
  • Other utilities
    • function handle_n_jobs
    • class cached_property
    • function plotting_function
    • function deprecated_argument
    • function supports_progress_interface
    • class ProgressCallback
    • function module_available
    • function handle_progress_bar

Other

• Imprint
• Software License