Skip to content

Latest commit

 

History

History
92 lines (55 loc) · 3.51 KB

NEWS.md

File metadata and controls

92 lines (55 loc) · 3.51 KB
Raw

specprepper 0.3.5 (2023-10-06)

Fixes

  • sg_apply(dt_prep_sets): add extra "_row<row-number>" string to prep_label column of dt_prep_sets input when combining with Savitzky-Golay parameter sets. This modification makes sure that cartesian products of existing preprocessing sets supplied as input are correctly formed with the repeated Savitzky-Golay plans.

specprepper 0.3.4 (2023-10-05)

Fixes

  • sg_apply(dt_prep_sets): There was an intermediary list-column called prep_params_in, that was outputted when dt_prep_sets was supplied as argument. This column is now omitted in the output data.table with the updated preprocessing sets, so that the objects produced can be easily row-bound with later objects downstream, or combined with the input object when append_rows = TRUE.

specprepper 0.3.3 (2023-10-05)

Fixes

  • failed to commit changes. Keeping entry for reproducibility. The intended fix is is in version 0.3.4 (see above).

specprepper 0.3.2 (2023-10-05)

Fixes

  • snv_apply(X): add prep_params as list-column with a single-row data.table (snv = NA) to the output when X is provided. This makes binding outputs to other (pre)processed collections of spectra possible without further intervention; also, append_rows = TRUE will work with other methods, when output of snv_apply() is used as input of other *_apply() functions.

specprepper 0.3.1.9000 (2023-10-05)

Fixes

  • sg_apply(): allow joins of Savitzky-Golay plans and preprocessing labels, and then also prepared Savitzky-Golay plans with inputted dt_prep_sets, when there is duplicated is. This is the case when dt_prep_sets input has already multiple rows (multiple collections) of spectra. Now, the desired duplicate joins are explicitly allowed by setting allow.cartesian = TRUE for respective data.table joins inside the sg_make_dt_prep() helper.

specprepper 0.3.0 (2023-10-05)

Features

  • Implement colmean_group_apply() and group label constructor ids_apply.R(). This is to apply column means to to spectral collections, each by a group label.

specprepper 0.2.1 (2023-09-13)

  • patch sg_apply() so that the extra "-snv" that got accidentally added to both prep_set and prep_label is not there anymore.

specprepper 0.2.0 (2023-09-13)

  • patch sg_apply(), so that it can be run after e.g. snv_apply() (via dt_prep_sets input argument).

specprepper 0.1.0 (2023-09-09)

Features

  • added snv_apply() to compute the standard normal variate (SNV) of spectral collections (#15).
  • added sg_apply() to process spectral collections with Savitzky-Golay smoothers with different parameter sets (derivative order, window size, polynomial degree).

Chores

  • Started semantic versioning via {fledge}

specprepper

Chemometrics and machine learning offer a large set of mathematical tooling to extract and apply chemical and physical knowledge from spectra in automated fashion. For this, spectra are typically preprocessed as part of the workflow. This is mostly to reduce light scattering and other optical artefacts.

The goal of {specprepper} is not only to wrap different signal processing methods and make them more accessible, but also to offer some of the exisiting algorithms with faster code implementations. It features a recipe-like interface, which also makes it possible to chain different methods in sequence.