pysindy.utils

Functions

`concat_sample_axis`	Concatenate all trajectories and axes used to create samples.
`wrap_axes`	Add axes to object (usually, a sparse matrix)
`comprehend_axes`
`capped_simplex_projection`	Projection of trimming_array onto the capped simplex
`drop_nan_samples`	Drops samples from x and y where either has a nan value
`get_prox`	Args: regularization: 'l0' \| 'weighted_l0' \| 'l1' \| 'weighted_l1' \| 'l2' \| 'weighted_l2'
`get_regularization`	Args: regularization: 'l0' \| 'weighted_l0' \| 'l1' \| 'weighted_l1' \| 'l2' \| 'weighted_l2'
`reorder_constraints`	Switch between 'feature' and 'target' constraint order.
`supports_multiple_targets`	Checks whether estimator supports multiple targets.
`validate_control_variables`	Ensure that control variables u are compatible with the data x.
`validate_input`	Forces input data to have compatible dimensions, if possible.
`validate_no_reshape`	Check types and numerical sensibility of arguments.
`flatten_2d_tall`
`linear_damped_SHO`
`cubic_damped_SHO`
`linear_3D`
`lotka`
`van_der_pol`
`duffing`
`rossler`
`cubic_oscillator`
`hopf`
`lorenz`
`lorenz_control`
`lorenz_u`
`meanfield`
`oscillator`
`burgers_galerkin`
`mhd`
`enzyme`
`yeast`
`bacterial`
`pendulum_on_cart`
`kinematic_commonroad`
`double_pendulum`

Classes

A numpy-like array that keeps track of the meaning of its axes.