Index A | B | C | D | E | F | I | K | L | M | N | P | R | S | T | U | V A add_noise() (FDApy.simulation.simulation.Simulation method) add_noise_and_sparsify() (FDApy.simulation.simulation.Simulation method) append() (FDApy.representation.functional_data.MultivariateFunctionalData method) argvals (FDApy.representation.functional_data.DenseFunctionalData property) (FDApy.representation.functional_data.FunctionalData property) (FDApy.representation.functional_data.IrregularFunctionalData property) argvals_stand (FDApy.representation.functional_data.FunctionalData property) B bandwidth (FDApy.preprocessing.smoothing.local_polynomial.LocalPolynomial property) Basis (class in FDApy.representation.basis) basis_name (FDApy.simulation.simulation.Simulation property) Brownian (class in FDApy.simulation.brownian) C center() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) clear() (FDApy.representation.functional_data.MultivariateFunctionalData method) concatenate() (FDApy.representation.functional_data.DenseFunctionalData static method) (FDApy.representation.functional_data.FunctionalData static method) (FDApy.representation.functional_data.IrregularFunctionalData static method) (FDApy.representation.functional_data.MultivariateFunctionalData static method) covariance (FDApy.preprocessing.dim_reduction.fpca.MFPCA property) (FDApy.preprocessing.dim_reduction.fpca.UFPCA property) covariance() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) D degree (FDApy.preprocessing.smoothing.local_polynomial.LocalPolynomial property) DenseFunctionalData (class in FDApy.representation.functional_data) DenseFunctionalDataIterator (class in FDApy.representation.functional_data) dimension (FDApy.representation.basis.Basis property) (FDApy.representation.basis.MultivariateBasis property) E eigenfunctions (FDApy.preprocessing.dim_reduction.fcp_tpa.FCPTPA property) (FDApy.preprocessing.dim_reduction.fpca.MFPCA property) (FDApy.preprocessing.dim_reduction.fpca.UFPCA property) eigenvalues (FDApy.preprocessing.dim_reduction.fcp_tpa.FCPTPA property) (FDApy.preprocessing.dim_reduction.fpca.MFPCA property) (FDApy.preprocessing.dim_reduction.fpca.UFPCA property) extend() (FDApy.representation.functional_data.MultivariateFunctionalData method) F FCPTPA (class in FDApy.preprocessing.dim_reduction.fcp_tpa) FDApy.misc.loader module FDApy.misc.utils module FDApy.preprocessing.dim_reduction.fcp_tpa module FDApy.preprocessing.dim_reduction.fpca module FDApy.preprocessing.smoothing.local_polynomial module FDApy.representation.basis module FDApy.representation.functional_data module FDApy.simulation.brownian module FDApy.simulation.karhunen module FDApy.simulation.simulation module FDApy.visualization.plot module fit() (FDApy.preprocessing.dim_reduction.fcp_tpa.FCPTPA method) (FDApy.preprocessing.dim_reduction.fpca.MFPCA method) (FDApy.preprocessing.dim_reduction.fpca.UFPCA method) FunctionalData (class in FDApy.representation.functional_data) I inner_product() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) insert() (FDApy.representation.functional_data.MultivariateFunctionalData method) inverse_transform() (FDApy.preprocessing.dim_reduction.fcp_tpa.FCPTPA method) (FDApy.preprocessing.dim_reduction.fpca.MFPCA method) (FDApy.preprocessing.dim_reduction.fpca.UFPCA method) IrregularFunctionalData (class in FDApy.representation.functional_data) IrregularFunctionalDataIterator (class in FDApy.representation.functional_data) is_normalized (FDApy.representation.basis.Basis property) (FDApy.representation.basis.MultivariateBasis property) K KarhunenLoeve (class in FDApy.simulation.karhunen) kernel (FDApy.preprocessing.smoothing.local_polynomial.LocalPolynomial property) kernel_name (FDApy.preprocessing.smoothing.local_polynomial.LocalPolynomial property) L LocalPolynomial (class in FDApy.preprocessing.smoothing.local_polynomial) M mean (FDApy.preprocessing.dim_reduction.fpca.MFPCA property) (FDApy.preprocessing.dim_reduction.fpca.UFPCA property) mean() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) method (FDApy.preprocessing.dim_reduction.fpca.MFPCA property) (FDApy.preprocessing.dim_reduction.fpca.UFPCA property) MFPCA (class in FDApy.preprocessing.dim_reduction.fpca) module FDApy.misc.loader FDApy.misc.utils FDApy.preprocessing.dim_reduction.fcp_tpa FDApy.preprocessing.dim_reduction.fpca FDApy.preprocessing.smoothing.local_polynomial FDApy.representation.basis FDApy.representation.functional_data FDApy.simulation.brownian FDApy.simulation.karhunen FDApy.simulation.simulation FDApy.visualization.plot MultivariateBasis (class in FDApy.representation.basis) MultivariateFunctionalData (class in FDApy.representation.functional_data) N n_components (FDApy.preprocessing.dim_reduction.fcp_tpa.FCPTPA property) (FDApy.preprocessing.dim_reduction.fpca.MFPCA property) (FDApy.preprocessing.dim_reduction.fpca.UFPCA property) n_dimension (FDApy.representation.functional_data.FunctionalData property) (FDApy.representation.functional_data.MultivariateFunctionalData property) n_functional (FDApy.representation.functional_data.MultivariateFunctionalData property) n_obs (FDApy.representation.functional_data.FunctionalData property) (FDApy.representation.functional_data.MultivariateFunctionalData property) n_points (FDApy.representation.functional_data.FunctionalData property) (FDApy.representation.functional_data.MultivariateFunctionalData property) name (FDApy.representation.basis.Basis property) (FDApy.representation.basis.MultivariateBasis property) new() (FDApy.simulation.brownian.Brownian method) (FDApy.simulation.karhunen.KarhunenLoeve method) (FDApy.simulation.simulation.Simulation method) noise_variance() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) norm() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) normalize (FDApy.preprocessing.dim_reduction.fcp_tpa.FCPTPA property) (FDApy.preprocessing.dim_reduction.fpca.MFPCA property) (FDApy.preprocessing.dim_reduction.fpca.UFPCA property) normalize() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) P poly_features (FDApy.preprocessing.smoothing.local_polynomial.LocalPolynomial property) pop() (FDApy.representation.functional_data.MultivariateFunctionalData method) predict() (FDApy.preprocessing.smoothing.local_polynomial.LocalPolynomial method) R read_csv() (in module FDApy.misc.loader) remove() (FDApy.representation.functional_data.MultivariateFunctionalData method) rescale() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) reverse() (FDApy.representation.functional_data.MultivariateFunctionalData method) robust (FDApy.preprocessing.smoothing.local_polynomial.LocalPolynomial property) S Simulation (class in FDApy.simulation.simulation) simulation_type (FDApy.representation.basis.MultivariateBasis property) smooth() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) sparsify() (FDApy.simulation.simulation.Simulation method) standardize() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) T to_long() (FDApy.representation.functional_data.DenseFunctionalData method) (FDApy.representation.functional_data.FunctionalData method) (FDApy.representation.functional_data.IrregularFunctionalData method) (FDApy.representation.functional_data.MultivariateFunctionalData method) transform() (FDApy.preprocessing.dim_reduction.fcp_tpa.FCPTPA method) (FDApy.preprocessing.dim_reduction.fpca.MFPCA method) (FDApy.preprocessing.dim_reduction.fpca.UFPCA method) U UFPCA (class in FDApy.preprocessing.dim_reduction.fpca) V values (FDApy.representation.functional_data.DenseFunctionalData property) (FDApy.representation.functional_data.FunctionalData property) (FDApy.representation.functional_data.IrregularFunctionalData property)