API Reference#
Classes
Represents a model. |
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Represents a model parameter or a single parameter vector. |
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Represents a penalty term of the objective function. |
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Represents the results of a fit. |
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Represents the uncertainty quantification of fit results. |
Functions
Fit the model(s) to the dataset(s) |
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Create a multi-response model from multiple individual models. |
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Create equality relationships between parameters |
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Create model whose response is a linear combination of multiple individual model responses. |
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Create functional relationships between model parameters. |
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Computes the discrete approximation to the derivative operators used as regularization operators. |
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Selection of optimal regularization parameter based on a selection criterion. |
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Estimate the noise level in a dataset. |
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Generates a vector of white Gaussian (normal) noise |
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Computes statistical quantities for the location, spread, and shape of a distance distribution, with or without their corresponding uncertainties. |
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Phase correction of complex-valued data. |
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Bootstrap analysis for uncertainty quantification |
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Profile likelihood analysis for uncertainty quantification |
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Separable non-linear least squares (SNLLS) solver |
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Fast non-negative least-squares (NNLS) solver. |
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Non-negative least-squares (NNLS) via the CVXOPT package. |
Dipolar EPR functions
Generate a dipolar EPR signal model. |
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Construct penalties based on the distance distribution. |
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Load file in BES3T format (Bruker EPR Standard for Spectrum Storage and Transfer) |
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Compute the (multi-pathway) dipolar kernel operator which enables the linear transformation from distance-domain to time-domain data. |
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Calculate multi-pathway dipolar background decays. |
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Fast-Fourier transform spectrum |
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Empirical distance range given a DEER time axis |
Utility functions
All functions in deerlab.utils
are private functions used internally by other functions.
Stable functionality is not guaranteed.
Save/export an object to a |
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Load a pickled object file |
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Heteroscedasticity Consistent Covariance Matrix (HCCM) |
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Finite difference Jacobian estimation |
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Find the nearest positive semi-definite matrix |
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Moving mean filter |
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Overlap index |
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DER-SNR noise estimation |