Overview · CHEMOTOOLS

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1

Improve WhittakerSmooth, AirPLS, and ArPLS performance - sparse matrix operations

#44

2

44 Improve WhittakerSmooth, AirPls, and ArPls performance

#120

3

Add pybaseline support

#128

4

Enable automated window size determination of Savitzky-Golay and Mean filter (maybe also Median filter)

#125

5

Implement maximum entropy deconvolution

#123

6

Use of TensorLy for N-way data?

#64

7

Improve compatability with the set_output API from scikit-learn

#46

8

Datasets module imports polars unconditionally, causing compatibility issues on Windows ARM64

#198

9

Proposal: Add Discovery Utilities (all_estimators, all_displays, all_functions)

#199

10

Epic: Model Selection Module

#202

11

Epic: Model Module

#203

12

Implementation in PLS-like methods

#207

13

Define ResidualMixIn

#204

14

Refactor outliers module

#205

15

Implementation in PCA-like methods

#206

16

Epic: Inspector Module

#208

17

Refactor Augmentation module

#209

18

#210

19

Implement successor of Savitzky-Golay: The Modified Sinc Smoother

#121

20

#38

21

#39

22

Extended Multiplicative Scatter Correction

#5

23

Norris Williams

#4

24

Add scale by index

#28

25

Savitzky Golay Filter

#7

26

#3

27

Whitakker smoothing

#9

28

Multiplicative Scatter Correction

#1

29

Standard Normal Variate

#2

30

Adaptive Iterative Reweighted Penalized Least Squares

#8

31

Normalize by min/max

#14

32

#6

33

Range Cut by Wavenumbers

#12

34

#15

35

Splines baseline correction

#17

36

#13

37

#10

38

#11

39

Linear correction

#16

40

Remove tuple in input of baseline correction instances

#18

41

Add subtraction of reference spectrum

#19

42

Improve perfomance ow whittaker

#20

43

Factor sklearn cheks out of each function

#22

44

Add logger to the different functions

#23

45

Add robust normal variate

#24

46

Use plotly for html plots in documentation 😎

#25

47

Normalize by given index

#26

48

Add scale by index

#27

49

add range cut by index

#29

50

add range cut by wavenumbers

#30

51

Improve performance whittaker filter and airPLS

#31

52

SelectByIndices

#32

53

Add data Augmentation module

#40

54

Implement Weighted Least Squares

#33

55

Enable set output API

#34

56

Enable pandas api

#35

57

Improve speed in ArPls()

#36

58

#37

59

Migrate to pyptoject.toml

#53

60

Improve feature selection integration with sklearn API

#55

61

Harmonize naming convention with other libraries for better LLM integration

#56

62

Substitute check_array by ._validate_data()

#57

63

Implement variable of importance for projections and selectioc raito

#58

64

Update sklearn api

#60

65

Deploy package to conda

#61

66

Provide Polars support when scikit-learn 1.4 is released

#63

67

BaselineShift fails on 2d array with dtype=int

#87

68

#66

69

Feature/fix augmentation noise

#133

70

Feature/improve add noise

#134

71

Feature/improve index shift

#135

72

Feature/augmentation add fractional padding

#136

73

Feature/add metrics

#137

74

Refactor residuals

#144

75

58 implement variable of importance for projections and selectioc raito

#146

76

#164

77

164 update project

#179

78

Release v0.1.20

#181

79

181 release v0120

#182

80

Bug fix in Fractional Shift

#183

81

183 bug fix in fractional shift

#184

82

#185

83

#186

84

Add small epsilon to SNV and RNV divisor

#187

85

Part 1: Whittaker Method Refactoring and Performance Improvements

#188

86

188 part 1 whittaker method refactoring and performance improvements

#189

87

187 add small epsilon to snv and rnv divisor

#190

88

DModX scale calculation.

#191

89

191 dmodx scale calculation

#192

90

#193

91

#194

92

Improve documentation page generating it automatically

#195

93

195 improve documentation page generating it automatically

#196

94

ImportError: cannot import name 'Self' from 'typing_extensions' on Python 3.13

#197

95

195 improve documentation page generating it automatically

#201

96

Proposal: Batch Testing Estimators Using parametrize_with_checks

#200